Worker Exposure to Dusts and Bioaerosols in the Sheep Shearing Industry in Eastern NSW.

by

Ryan Kift

BAppSc (Hons) (Occupational Health and Environment)

BAppSc (Environmental Health)

A thesis presented in fulfillment of the requirement for the degree of

Doctor of Philosophy

March 2007

CERTIFICATE OF ORIGINALITY

The text of this thesis contains no material which has been accepted as part of the requirements for another degree or diploma in any University, or material previously published or written by another author unless due reference to this material has been made.

Ryan Kift 2 March 2007

ii

ACKNOWLEDGEMENTS

Thank you to my family, supervisors, friends and colleagues that helped and supported me throughout this study. Thank you to the University of Western Sydney for their financial, academic and resource support. Thank you to all of the people involved in the sheep shearing industry that participated in this study. Without the help and support of all of these people this study would not have been possible.

iii ABSTRACT

The air found in a sheep shearing environment is normally contaminated with many different airborne substances. These contaminants include dust (predominantly organic), bioaerosols (fungi and bacteria) and gases (ammonia and carbon monoxide). Respiratory disorders, such as Hypersensitivity Pneumonitis, chronic bronchitis and asthma, have been associated with exposure to the types of airborne contaminants found in a normal sheep shearing environment.

The majority of Australian and international research in the livestock handling industries that has investigated dust exposure has focused on the poultry and pig industries. Some worldwide studies have been undertaken on feedlot cattle. Research in the sheep shearing industry in relation to worker exposure data for airborne contaminants has been identified as a major need as no documented studies have been undertaken anywhere in the world. Many of the past studies have focused on investigating the health of the animals exposed to these environments rather than that of the workers.

Twenty nine sheep shearing sheds in the state of New South Wales in Eastern Australia were sampled for concentrations of airborne contaminants. These contaminants include inspirable and respirable dust (that was sampled both personally and statically) and bioaerosols (bacteria and fungi). The dust was collected using gravimetric means and the bioaerosols were collected using an Andersen Instruments 2-Stage bioaerosol sampler. The use of this equipment allowed only static samples to be collected while shearing was being undertaken in each shed.

This study found that in relation to dusts the mean concentrations for each farm and the majority of most individual concentrations were below either the 3 mg m-3 recommended standard for respirable dust or the 10 mg m-3 recommended standard for inhalable dusts. A major issue is whether the current exposure standards for dusts (not otherwise classified) should be used in agricultural animal handling environments, including shearing sheds. This debate centres on the exposure to organic dusts which can contain high concentrations of microorganisms and their constituents. The current literature suggests that current exposure standards should be reduced.

iv Bacteria concentrations recorded in this study ranged from 35 to 57,224 cfu m-3 and fungi from 0 to17,173 cfu m-3. There are no current exposure standards adopted for bioaerosol exposure anywhere in the world making it hard to determine if a potential health risk from bioaerosol exposure exists in these sheds. Some bioaerosol concentration limits have been suggested in the past. One suggested exposure limit was 103 cfu m-3 and if this limit was adopted in Australia then 83% of farms sampled exceeded it for bacteria concentration. In the case of fungi the number of sheds exceeding this concentration is lower with only 65% of concentrations for fungi exceeding 103 cfu m-3.

The collected concentrations for both dusts and bioaerosols were analysed against the important variables that can exist in the shearing environment. The variables analysed were: the type of job completed by workers; the position of the static sampling equipment; the different geographical region that the samples were collected from; the indoor air temperature of the shed when the samples were collected; the number of sheep shorn during each sampling session and the shearing session (time of the day) in which the samples were collected.

The concentration of respirable dust (both static and personal) was found to be most influenced by the concentration of inspirable dust that is present at the time of sampling. Inspirable dust was found to have a statistically significant relationship (
=0.492, and p= 0.000) with the number of sheep shorn during the session, the indoor air temperature of the shed(r=0.249, p=0.014 for static samples, r=0.213, p=0.019 for personal samples) and the region in which the shed is located. The concentration of bacteria was found to be influenced by the shearing region where the samples were collected but was not found to be significantly related to any other variables. The concentration of fungi was found to have a statistically significant relationship with the indoor air temperature of the shed(r=0.228, p= 0.044), the region the shed was in (F(94, 493)=17.213, p<0.001) and the concentrations of both inspirable dust(r=0.351, p=0.013) and bacteria (r=0.466, p<0.001) present during sampling.

Based on the results of the study the following recommendations are made for the shearing industry: under the current dust and bioaerosol exposure standards there is no requirement to instigate mechanical ventilation to reduce airborne contaminants and there is no need for respiratory protection in any of the monitored sheds.

v However, it is recommended that if a person has a known predisposition to respiratory illness/stress they should be closely monitored while working in a shearing shed. However if bioaerosol standards are implemented in Australia (such as 103 cfu m-3) then respiratory protection and new ventilation strategies may need to be introduced to reduce concentrations. If lower dust exposure standards are implemented then additional recommendations would include: reducing dust at the source, rotating shearing and wool handling positions within the shed and respiratory protection may need to be used.

There are issues raised in this thesis that require further research including the need for an epidemiological study on the health of people working in shearing sheds in relation to their respiratory health. The monitoring of shearing sheds in other regions in Australia needs to be undertaken and based on available literature similar studies are needed in other livestock industries in Australia.

vi TABLE OF CONTENTS

TITLE PAGE i CERTIFICATE OF ORIGINALITY ii

ACKNOWLEDGEMENTS iii

ABSTRACT iv

TABLE OF CONTENTS vii

LIST OF APPENDICES xiii

LIST OF TABLES xv

LIST OF FIGURES xvi

LIST OF PLATES xviii

GLOSSARY OF TERMS xix

Chapter 1 Introduction 1

1.1 Aim and Objectives 4

Chapter 2 Literature Review 5

2.1. Overview of agriculture 5

2.1.1 Different work done on farms 5

2.1.2 Confinement housing 6

2.1.3 Sheep 8

2.2 Airborne Contaminants 8

2.2.1 Dusts 9

2.2.2 Bioaerosols 12

vii 2.2.3 Gases 23

2.3 Health Impacts 24

2.3.1 Respiratory System 27

2.3.2 Respiratory Diseases 31

2.3.3 Other diseases 40

2.4 Positive effects of exposure 46

2.5 Assessment of Airborne Contaminants 47

2.5.1 Dust Monitoring 48

2.5.2 Bioaerosol Monitoring 50

2.5.3 Endotoxin 57

2.5.4 Alternative sampling methods 58

2.5.5 Identification of bioaerosols 59

2.5.6 Sampling Statistics 60

2.6 Sampling variables that impact on airborne contaminants 61

2.6.1 Season 62

2.6.2 Indoor temperature 63

2.6.3. Outside concentrations of airborne contaminants 63

2.6.4 Type of flooring in animal shed 64

2.6.5 Ventilation rates 65

2.6.6 Animal diet and living area (grasses and soil type) 66

2.6.7 Number, activity and species of animals 67

2.6.8 Sampling collection methods 68

viii 2.7 Standards 69

2.7.1 Dusts 69

2.7.2 Bioaerosols 70

2.7.3 Endotoxin 71

2.7.4 Standards for Agriculture 72

2.8 Methods of Controlling Exposures 73

2.8.1 Elimination 73

2.8.2 Substitution 74

2.8.3 Engineering 74

2.8.4 Administrative controls 78

2.8.5 Personal Protective Equipment (PPE) 80

2.8.6 Problems with control measures 81

2.8.7 Costs 81

2.9 Exposure in agriculture 82

2.9.1 Factors that may affect agricultural exposures 82

2.9.2 Relevant exposure studies from the literature 86

Chapter 3 Methods 90

3.1 Dust Monitoring and Analysis 92

3.1.1 Sampling for respirable dust 93

3.1.2 Inspirable dust 94

3.1.3 Calculations used to determine concentration of dust 96

3.2 Bioaerosol monitoring and analysis 97

ix 3.2.1 Bioaerosol Sampling method 98

3.2.2 Bioaerosol Analysis 99

3.3 Additional parameters monitored 99

3.4 Ethical approval 100

3.5 Statistical analysis of data 100

Chapter 4 Results and Discussion 102

4.1 Introduction to Sampling Variables 102

4.2 Data analysed by the job type and static sampling position 104

4.2.1 Introduction 104

4.2.2 Mean personal respirable and inspirable dust concentrations for the different jobs undertaken 106

4.2.3 Mean static respirable and inspirable dust concentrations for sample location110

4.2.4 Conclusion of effects of job undertaken or sample location on mean airborne dust concentration 114

4.3 Data analysed by the region of NSW in which the data was collected 114

4.3.1 Introduction 114

4.3.2 Mean personal and static respirable and inspirable dust concentrations for each region sampled 118

4.3.3 Mean bacteria and fungi concentrations for sample region 122

4.3.4 Conclusion of effects of region on airborne concentration 125

4.4 Data analysed by taking into account the indoor temperature on the day that dust and bioaerosol samples were collected 125

4.4.1 Introduction 125

x 4.4.2 Mean personal respirable concentrations for each temperature range 127

4.4.3 Mean personal inspirable concentrations for each temperature range 129

4.4.4. Mean static respirable concentrations for each temperature range 130

4.4.5. Mean static inspirable dust concentrations for each temperature range 131

4.4.6 Mean bacteria concentrations for each temperature range 133

4.4.7 Mean fungi concentrations for each temperature range 134

4.4.8 Conclusion of effects of temperature on airborne concentration of contaminants 136

4.5 Analysis of dust and bioaerosol concentrations according to the number of sheep shorn in a session 137

4.5.1 Introduction 137

4.5.2 Mean personal and static respirable and inspirable dust concentrations for each range of sheep shorn per session at each farm 139

4.5.3 Mean bacteria and fungi concentrations for each range of sheep shorn per session at each farm 144

4.5.4 Conclusion of effects of number of sheep shorn per session on airborne concentration 147

4.6 Data analysed by the shearing session from which it was collected 148

4.6.1 Introduction 148

4.6.2 Dust concentrations for each sampling session 150

4.6.3 Bacteria and fungi concentrations for each sampling session 154

4.6.4 Conclusion of Effects of Sampling Session on Airborne Contaminant Concentration 157

4.7 Comparison between indoor and outdoor bioaerosol concentrations 158

xi 4.7.1 Introduction 158

4.8.1 Comparison of Dust Concentrations to relevant Exposure Standards 162

4.8.2 Bioaerosol Exposure standards 165

4.9 Factors that impact on air concentrations in a shearing shed 167

Chapter 5 Conclusions and Recommendations 170

5.1 Recommendations for the Shearing Industry 171

5.2 Areas of further research 172

References 174

APPENDICES 195

xii List of Appendices

Appendix A Letter to Shearers 196

Appendix B Dust and bioaerosol concentrations collected from Farm 2 199

Appendix C Dust and bioaerosol concentrations collected from Farm 2 200

Appendix D Dust and bioaerosol concentrations collected from Farm 3 201

Appendix E Dust and bioaerosol concentrations collected from Farm 4 203

Appendix F Dust and bioaerosol concentrations collected from Farm 5 204

Appendix G Dust and bioaerosol concentrations collected from Farm 6 205

Appendix H Dust and bioaerosol concentrations collected from Farm 7 206

Appendix I Dust and bioaerosol concentrations collected from Farm 8 207

Appendix J Dust and bioaerosol concentrations collected from Farm 9 208

Appendix K Dust and bioaerosol concentrations collected from Farm 10 209

Appendix L Dust and bioaerosol concentrations collected from Farm 11 210

Appendix M Dust and bioaerosol concentrations collected from Farm 12 211

Appendix N Dust and bioaerosol concentrations collected from Farm 13 212

Appendix O Dust and bioaerosol concentrations collected from Farm 14 213

Appendix P Dust and bioaerosol concentrations collected from Farm 15 214

Appendix Q Dust and bioaerosol concentrations collected from Farm 16 215

Appendix R Dust and bioaerosol concentrations collected from Farm 17 216

Appendix S Dust and bioaerosol concentrations collected from Farm 18 217

Appendix T Dust and bioaerosol concentrations collected from Farm 19 218

Appendix U Dust and bioaerosol concentrations collected from Farm 20 219

Appendix V Dust and bioaerosol concentrations collected from Farm 21 220

Appendix W Dust and bioaerosol concentrations collected from Farm 22 221

Appendix X Dust and bioaerosol concentrations collected from Farm 23 222

xiii Appendix Y Dust and bioaerosol concentrations collected from Farm 24 223

Appendix Z Dust and bioaerosol concentrations collected from Farm 25 224

Appendix AA Dust and bioaerosol concentrations collected from Farm 26 225

Appendix AB Dust and bioaerosol concentrations collected from Farm 27 226

Appendix AC Dust and bioaerosol concentrations collected from Farm 28 227

Appendix AD Dust and bioaerosol concentrations collected from Farm 29 228

xiv List of Tables

Table 2.5.1 Recommended frequency of repeat monitoring based on 61 previously recorded exposures compared with recommended exposure guidelines Table 4.1 Variables associated with each farm sampled. 103 Table 4.2.1 Mean (±SE) dust exposure concentrations compared to job 107 type Table 4.2.2 Mean dust concentrations at different locations throughout 111 the shed. Table 4.3.1 Mean concentrations based on region ± SE. 117 Table 4.4.1 Mean concentrations of dusts and bioaerosols in relation to 127 ambient indoor temperatures (± SE) measured inside the shearing sheds sampled in this study. Table 4.5.1 Mean concentrations based on the number of sheep shorn 139 per shearing session ± SE. Table 4.6.1 Mean concentrations of dusts and bioaerosols in relation to 150 the shearing session they were collected in (± SE) measured inside the shearing sheds sampled in this study. Table 4.7.1 Mean (± SE) bacteria and fungi concentration (cfu m-3) for 159 each shearing shed monitored in NSW. Table 4.8.1 Dust concentration compared to current and proposed 163 standards.

xv List of Figures

Figure 2.3.1 Anatomical features of a set of human lungs 28 Figure 4 2.1 The steps involved in wool harvesting in a shearing shed. 106 Figure 4.2.2 Personal respirable dust concentrations in comparison to 108 job type Figure 4.2.3 Personal inspirable dust concentrations compared to job 109 type Figure 4.2.4 Static inspirable dust concentrations in relation to the 112 location of the monitors in the shearing sheds Figure 4.2.5 Static respirable dust concentrations in relation to the 113 location of the monitors in the shearing sheds Figure 4.3.1 Regions within NSW, Australia where monitoring was 116 undertaken Figure 4.3.2 Personal inspirable dust concentrations in relation to the 119 region of NSW that was sampled Figure 4.3.3 Personal respirable dust concentrations in relation to the 120 region of NSW that was sampled Figure 4.3.4 Static inspirable dust concentrations in relation to the 121 region of NSW that was sampled Figure 4.3.5 Static respirable dust concentrations in relation to the 122 region of NSW that was sampled Figure 4.3.6 Bacteria concentrations in relation to region of NSW that 123 was sampled Figure 4.3.7 Fungi concentrations in relation to region of NSW that was 124 sampled Figure 4.4.1 Personal respirable dust concentrations measured in relation 128 to a range of temperatures Figure 4.4.2 Personal inspirable dust concentrations measured in relation 129 to a range of temperatures Figure 4.4.3 Static respirable dust concentrations measured in relation to 131 a range of temperatures Figure 4.4.4 Static inspirable dust concentrations measured in relation to 132 a range of temperatures Figure 4.4.5 Bacteria concentrations measured in relation to a range of 133 temperatures Figure 4.4.6 Fungi concentrations measured in relation to a range of 135 temperatures Figure 4.5.1 Personal respirable dust concentrations relative to the 141 number of sheep shorn in a day

xvi Figure 4.5.2 Static respirable dust concentrations relative to the number 142 of sheep shorn in a day Figure 4.5.3 Static inspirable dust concentrations relative to the number 143 of sheep shorn in a day Figure 4.5.4 Personal inspirable dust concentrations relative to the 144 number of sheep shorn in a day Figure 4.5.5 Bacteria concentrations relative to the number of sheep 145 shorn in a day Figure 4.5.6 Fungi concentrations relative to the number of sheep shorn 146 in a day Figure 4.6.1 Static respirable dust concentrations in relation to the 151 shearing session during the day Figure 4.6.2 Static inspirable dust concentrations in relation to the 152 shearing session during the day Figure 4.6.3 Personal respirable dust concentrations in relation to the 153 shearing session during the day Figure 4.6.4 Personal inspirable dust concentrations in relation to the 154 shearing session during the day Figure 4.6.5 Bacteria concentrations in relation to the shearing session 155 during the day Figure 4.6.6 Fungi concentrations in relation to the shearing session 156 during the day Figure 4.7.1 Percentage change increase from outside to inside air 160 concentrations for bacteria and fungi measured on each farm Figure 4.8.1 Mean concentrations found at each farm for inspirable and 164 respirable dusts Figure 4.8.2 Average concentrations of bacteria recorded from all farms 165 inside and outside the shearing shed. Figure 4.8.3 Average concentrations of fungi from all farms for inside 166 and outside the shearing shed

xvii List of Plates

Plate 3.1 A 3 stand shearing shed (inside) 90

Plate 3.2 A 3 stand shearing shed (outside) 90

Plate 3.3 A 7 stand shearing shed 91

Plate 3.4 A 2 stand shearing shed 91

Plate 3.5 Wooden floored shed 91

Plate 3.6 Concrete floored shed 91

Plate 3.7 Holding pends 92

Plate 3.8 Slightly enclosed holding area 92

Plate 3.9 Rouseabout with respirable sample head 95

Plate 3.10 Shearer with inspirable sampling head 95

Plate 3.11 Inspirable static sampling (near sheep) 95

Plate 3.12 Respirable static sampling (near rouseabouts) 95

Plate 3.13 Bioaerosol sampler 97

xviii Glossary of Terms

µm Micrometers oC Degrees Celsius ACGIH American Conference of Governmental Industrial Hygienists ABARE Australian Bureau of Agriculture and Resource Economics ABS Australian Bureau of Statistics ADUK Asbestos Diseases United Kingdom AGI All Glass Impinger AS Australian Standard ASCC Australian Safety and Compensation Council BAL Broncoalveolar lavage b1 Weight of blank filter before sampling, in milligrams b2 Weight of blank filter after sampling, in milligrams BGI Billings Gussman Instruments Blue collar Working class BMRC British Medical Research Council Bioaerosol Airborne microorganism BOM Australian Bureau of Meteorology CCH CCH Australia Limited CEN European Committee for Standardisation. C Dust concentration, in milligrams per cubic metre Central The sampling area in NSW centred around the town of Mudgee, with Highlands most of the monitoring carried out near the township of Lue. Central West A sampling area in NSW, the larger towns in this area include, Bathurst, Orange, Cowra and Dubbo. Monitoring in this area was around the towns of Grenfell, Yeoval, Canowindra and Lyndhurst. cfu Colony Forming Units

CH4 Methane Crutching When a sheep has only part of it’s rump and face shorn CO Carbon monoxide

CO2 Carbon Dioxide DNA Deoxyribonucleic acid EAA Extrinsic Allergic Alveolitis

xix EU Endotoxin Unit (approximately 10ng m-3) ELISA Enzyme-linked immunosorbent assays F Frequency FEV Forced Expiratory Volume

FEV1 Forced Expiratory Volume in 1 second FHP Farmers Hypersensitivity Pneumonitis FLD Farmer's Lung Disease FM Fluorescence microscopy FVC Forced Vital Capacity G’s. Acceleration due to gravity GC-MS Gas chromatography-mass spectrometry HREC Human Research Ethics Committee HMW High molecular weight HP Hypersensitivity Pneumonitis HSE Health and Safety Executive

H2S Hydrogen Sulfide Inorganic The non-viable fraction of dusts Inspirable Dusts that have a median diameter of greater than 4.0 µm, and hence Dust can settle higher that respirable dusts, in the respiratory system ISO International Organisation for Standardisation. ISU Iowa State University 1 kDalton 1000 daltons, 1 Dalton is ⁄12 of the mass of one atom of carbon-12 L Litres L min-1 Litres per minute LAL Limulaus Amoebocyte Lysate LEV Local Exhaust Ventilation LPS Lipopolysaccharides Lux Luminosity function m Meter ml Millilitres mg Milligram mm Millimetres MEA Malt Extract Agar

xx min Minute NA Nutrient Agar NAL Nasal lavage

NH3 Ammonia NIOSH National Institute for Occupational Safety and Health (USA) nm Nanometres NOC Not Otherwise Classified NOEL No Observed Effect Level Northern A sampling area in NSW, including the towns of Tamworth and Highlands Armidale. Most of the monitoring was carried out near the town of Walcha. NSW New South Wales ODTS Organic Dust Toxic Syndrome OEL Occupational Exposure Level OES Occupational Exposure Standard OHS Occupational Health and Safety Organic Dust composed of microorganisms and their metabolites OSHC Occupational Safety and Health Council (Hong Kong) OSHA Occupational Safety and Health Association p Probability PEL Permissible Exposure Levels pg Per gram PM Particulate Matter PPE Personal Protective Equipment ppm Parts Per Million PVC Polyvinyl Chloride Q average flow rate, in litres per minute

Q1 Initial flow rate, in litres per minute

Q2 final flow rate, in litres per minute Q fever Query fever r Standardized Coefficient REL Recommended Exposure Level

xxi Respirable Dusts that have a median diameter of 4.0 µm or less, and able to Dust penetrate to the level of the terminal bronchioles and the alveoli in the lung s Second SE Standard Error Session A time period during the day when sheep are shown, usually of 2 hours duration. SKC SKC Incorporated spp. Species STG Stage SPSS Statistical Package for the Social Sciences Southern A sampling area in NSW, centred around the town of Goulburn with Highlands most of the monitoring being carried out between the towns of Goulbourn and Taralga. Sydney A sampling area in NSW, centred around the town of Richmond in Basin the outer western region of Sydney. t Sampling duration, in minutes TLV Threshold Limit Value TSA Tryptic Soy Agar TSI Thomson Scientific Instruments TWA Time Weighted Average UK United Kingdom USA United States of America UV Ultraviolet UVC Short Wave Ultraviolet (< 280 nm) UVGI Ultraviolet Germicidal Irradiation UWS University of Western Sydney V Air volume, in cubic metres w Corrected weight of dust collected on the filter, in milligrams w1 Weight of unladen filter, in milligrams w2 Weight of used filter, in milligrams Wool The process of removing wool from a sheep, and preparing it for harvesting processing, synonymous with sheep shearing YES Young Environmental Systems

xxii CHAPTER 1 INTRODUCTION

Rural life conjures up an image of good health, sunshine, clear air and far removed from the smog and industrial pollution measured in cities. Unfortunately, this is not true. In fact more adult farm workers are disabled by respiratory tract illness than urban dwellers (Popendorf et al, 1985). Agricultural processes generate occupational exposure to a variety of potential disease causing hazards including chemical, physical and biological agents (Ferguson, 1998). One of the many different jobs carried out on farms is animal handling which can result in exposure to many different potentially harmful dusts. Various diseases can be acquired from exposure to these dusts and there are also multiple ways to assess and measure the impact of these different diseases. In an attempt to reduce the health risks to workers exposed to these diseases it is very important to look at preventative methods that can be implemented. There are many unique features to the occupational disorders of farmers. Occupational disorders can affect workers and also family members and other relatives and friends who live and help on the farm. It is estimated that only 50% of farmers injured at work seek workers compensation (Virtanen et al, 2003). Due to Australian agricultural businesses being mainly run by families the farmers are considered self-employed and consequently they are also not usually covered by Worker’s Compensation or disability insurance (Warren, 1989). Work related injury and disease suffered by a farmer or a worker can impact not just on the worker but also on the agricultural business and wider community supported by that farm.

People working with animals can be exposed to many hazards in their normal working environment. Potential health and safety risks come from manual handling, chemical usage, machinery operation, animal husbandry and production procedures such as shearing (Kift et al, 2003). Other hazards include depression (Scarth et al, 2000), hearing loss (Fragar et al, 2001) and skin cancer (Mathias, 1989). This project focuses on airborne contaminants such as dusts and bioaerosols. Dutkiewicz (1978) concluded that exposure to dust-born bacteria creates a serious problem for occupation health in agriculture and requires further research. Internationally, health problems associated with swine operation workers have been extensively studied while other animal handling operations have not been so well studied (Donham, 1986). Until now, the limited research that has been undertaken in Australia in

1 relation to dust and bioaerosol exposure within the livestock handling industries has been in the poultry (McGarry et al, 2002; Miflin and Blackall, 1998) and pig sectors (Banhazi et al, 2004; Holyoake, 2002). There has been some research in the horse sector (Reed et al, 2003; Cargill, 1999) and there has been some preliminary work completed in the deer sector (Kift et al, 2002a). Little research has been undertaken in other areas of livestock handling in Australia although several studies have been done on cattle in Europe (Takai et al, 1998; Louhelainen, 1997) and America (Purdy et al, 2004; Kullman et al, 1998).

This thesis will focus on worker exposure while handling sheep. Sheep are handled in a shearing shed where there is minimal ventilation as buildings often have four solid walls with a limited number of windows and doors which can mean that most of the airborne contaminants are kept inside the building. When sheep are indoors they are normally on wooden floors. The floor material is important as there is more chance of dust being generated from the wood flooring than concrete. Wooden floors can also become a breeding area for different diseases whereas concrete floors are easily washed with water or disinfectant.

Shearing of sheep is the crucial part of a whole process that is termed “wool harvesting” which involves the shearing of sheep and the work involved in the preparation of wool for sale. Wool harvesting occurs in all states in Australia. There are many different jobs that people do during this process including: shearer, rouseabout, wool classer, stockman and wool presser. Due to the working conditions in a shearing shed there is a high turnover of shearers and rouseabouts (Primary Skills, 2005). In Australia during the major shearing periods wool harvesting involves an estimated 27,000 paid workers (Freeman, 1988), not including the unpaid family and friends who will visit and/or work in the shearing shed while shearing is undertaken.

When sheep are shorn they must first be brought from their grazing paddocks into outside holding areas and they may be kept in this area for up to three days depending on demand. If there is room inside the shed they could also be kept inside the shed for three days. When the sheep are to be shorn they are brought inside and held inside in a variety of holding pens. Once shorn the sheep are placed in holding pens beneath the shed until they are ready to be returned to their grazing paddock.

2 The wool fleece is then moved from the shearing area, and roughly hand cleaned and classed. After classing the wool is packed into bales and transported to wool storage facilities.

Respiratory illness has been reported, by those in the shearing industry, as a common occurrence for people working in the industry. However, the reporting of cases is often hidden as many shearers in Australia are self employed and their work related illnesses do not appear in workers’ compensation statistics. Fragar et al, (2001) estimated that Australian sheep shearing injuries are responsible for $7 to $19 million per annum of agricultural workers’ compensation claims. Due to the lack of reporting in the shearing industry this figure is considered a gross underestimation. Respiratory diseases are also under-reported because many workers leave the industry at the first sign of illness.

In eastern New South Wales (NSW), Australia farm size, quantity and variety of commodities (sheep), agricultural practices (mechanical shearing), soil types and the temperate climate are substantially different from those in many other parts of Australia and the rest of the world (Nieuwenhuijsen et al, 1998).

It has been suggested that research into occupational disease, especially research demonstrating the definite link to particular industries and/or work processes, needs to be increased. Such information also needs to be readily available to workers and unions. If available, this information would help to reform the way workers’ compensation systems adjudicate on possible disease claims (Bohle and Quinlan, 2000). Workers compensation premiums vary between different industries in NSW. The average cost across all industries is 2.57% with the current rate for sheep farming at 11.14% and sheep shearing at 11.19% (WorkCover, 2004a). The higher premium for sheep farming indicates that the industry is considered more dangerous.

3 1.1 Aim and Objectives

The aim of this project was to determine if workers shearing sheep and handling wool in a shearing shed environment are exposed to airborne particulate and bioaerosol hazards that may present a potential risk to their respiratory health.

To meet this aim the project has the following objectives:

• To identify possible respiratory diseases that may be caused or exacerbated by exposure to dusts and bioaerosols in this environment.

• To develop an exposure sampling strategy for worker exposure to particulates and bioaerosols in Australian rural animal handling facilities.

• To quantify the exposure of workers in a shearing environment to inspirable and respirable particulates during the shearing process.

• To quantify the exposure of workers in a shearing environment to bacteria and fungi during the shearing process.

• To identify the variables that may contribute to increasing or decreasing particulate or bioaerosol exposures.

4 CHAPTER 2 LITERATURE REVIEW

2.1. Overview of agriculture

More people are involved worldwide in agriculture than in any other work related activity (Jacobs, 1994). However, in the developed nations, the proportion of the workforce engaged in agricultural production is now less than 2% and continues to contract as modern production techniques are adopted (Merchant and Reynolds, 2000). Technological advances and socio-economic forces have brought about dramatic changes in agriculture and in working conditions. In some cases these changes have proved beneficial (increasing awareness of risks) while in others, exposures to potentially harmful dusts and bioaerosols have intensified. The use of livestock confinement housing for production has led to an increase in specialisation, with workers spending more time on fewer tasks. In general agricultural workers still continue to work long hours and preform a wide variety of jobs, and some of these can be under adverse climatic conditions. The agricultural workforce tends to differ from most other occupations in that it has a larger proportion of the workforce older than 65 years and younger than 16 years (Merchant and Reynolds, 2000). Agricultural enterprises may be categorized as production agriculture (work-on-the- farm), agribusiness (supply, service, maintenance, intermediate processing and transportation of commodities) and finish processing (delivering and/or finalising the product for sale) (Jacobs 1994). An agricultural farm has been defined in America as a “business with at least $1000 income from agricultural products sold annually” (Scarth et al, 2000, p383). The production of wool can be classed as both production agriculture (the farming of sheep) and agribusiness (the process of shearing the sheep and processing the wool through to sale, including value adding). In all cases the farms used in this study produced at least $A1000 from agricultural products (wool) hence they are all working farms.

2.1.1 Different work done on farms

Agriculture is a diverse industry that includes multiple occupational and environmental exposures to dusts and bioaerosols associated with widely varying

5 work practices (Kirkhorn and Garry, 2000). Many occupational health and safety risks are shared between the different types of work carried out on a farm with each type of work having its own risks (Fragar et al, 2001). These many different types of tasks are regularly carried out by the same agricultural worker. The tasks may include preparing feed, animal feeding, cleaning buildings, harvesting, moving animals, performing veterinary treatments, maintenance and other husbandry tasks. In contrast to workers in other industries the activities of agricultural workers vary throughout the year depending on the nature of the crop, geographical location of the agricultural endeavour and the type of handling or processing required to bring the product to market (Ferguson, 1998). Each of these activities brings its own individual risk. Such risks include potential disease transmission, injury or other miscellaneous hazards. Farm workers in the animal production industries have the risk of different types of injuries depending on the animal and living area of that animal. For example the slippery surfaces in confinement facilities (Virtanen et al. 2003).

Many people involved in the shearing industry also work in some capacity, for example farm hands, on other types of farms during the shearing off season. This situation can make it difficult to prove that possible disease development has come from their exposure in the shearing industry.

2.1.2 Confinement housing

Confinement housing was first applied in Australia and worldwide, to poultry production in the early 1960’s. Since that time it has also been used predominately in pig production and in a limited fashion for dairy operations and beef and sheep production (Donham, 1994). Confinement houses, or intensive animal housing, are a different production method to the historical outdoor farming method which is used in the raising of livestock. Confinement houses for livestock enable the producer to raise a large number of animals under controlled conditions so that labour, time, feed and management of the environment for the animals can be used more efficiently than in the field (Gurney et al, 1991). Confinement houses are now used worldwide for the large-scale commercial production of sheep, cattle, deer, pigs and poultry

6 (Zejda and Dosman, 1993). However the greatest use occurs in Europe and in particular Scandinavian countries. Their use in these countries is widespread as it is often too cold and/or wet for the animals to be kept outdoors, especially in winter. In Australia confinement houses are used mainly for swine and poultry and to a lesser degree for medium (sheep, goats) and larger animals (cattle, horses and deer). This is because the environmental conditions found in Australia are more favourable for the raising of livestock outdoors. In Australia animals can be kept outside in winter without adverse effects. Large animals may be kept indoors to increase their uptake of food. Confinement housing for cattle occurs in India and an increase in respiratory symptoms among farmers has been reported by Adhikari et al, (2004). Many confinement workers are also involved in other types of farming as they grow their own feed (Virtanen et al, 2003).

Health risks on farms with animal housing have increased as a result of labour saving technology. Factors that contribute to these risks include: (1) Building designs that have allowed crowding to minimize facility costs per animal; (2) Feeding has been mechanized, and (3) Air exchange has been reduced to minimize supplementary heating. These factors result in poor air quality which could produce adverse health effects, primarily respiratory, (McDuffie et al, 1995) to both workers and animals.

Animal confinement can also be used to hold animals when veterinarian treatments and other husbandry activities are undertaken on the animals and is very different to raising the animals indoors. When an activity is carried out on an animal indoors large numbers are often held in indoor holding pens, for a short time period resulting in the workers being exposed to air-borne contaminants brought in or produced by the animals. This is common in Australia and can affect people who work with larger animals that are usually kept outdoors (sheep, cattle, horses, deer). When animals are brought indoors the animals’ behaviour often becomes unpredictable and anything but docile (Renwick, 1986). Exposure may also be substantially increased by the method of feeding or the method of animal waste removal (Murphy, 1992). Animal wastes can be categorized into the following: (i) fresh manure, including that which is scraped daily; (ii) manure collected in shallow to medium depth pits;

7 (iii) manure collected in pits with drying fins or boards beneath the holding areas; (iv) manure collected in pits with in-house forced air drying; (v) deep pit stored manure; (vi) liquid systems involving flush or dilution and tank storage; and (vii) litter systems (Overcash et al, 1983).

The airborne dust can also impact on the building itself as well as the people working in the building. Dust that collects on most building surfaces can lead to a deterioration of building materials and equipment in livestock buildings (Takai et al, 1998).

2.1.3 Sheep

Wool has in the past been, and still is, a major component of Australian agricultural production. In 2004 there were approximately 40,000 sheep and wool producers in Australia (ABARE, 2005). Between them they produced 551,100 tonnes of wool in 2002-03 (ABS, 2005). NSW produces the most wool, with approximately 15,000 agricultural establishments reporting sheep production in 2004 (ABARE, 2005).

Many of the husbandry procedures applied to sheep are carried out in handling facilities that are classified as indoor and these facilities are often dusty and poorly ventilated. A sheep farm typically consists of a series of fields (paddocks) linked to a handling facility via a central laneway. Sheep yard complexes serve four main functions: to hold, draft (sort), close handle and load out (or receive) sheep. The actual building in the yard complex is mostly used to hold the sheep so they can be shorn or crutched. Other husbandry activities include treating the sheep with chemicals for disease.

2.2 Airborne Contaminants

In buildings where animals are handled a variety of airborne contaminants are present in varying concentrations. The contaminants include dust (mostly organic

8 and a small amount of inorganic dust), bioaerosols (aerosolised faecal, food material and animal proteins) and gases (ammonia, methane, nitrogen oxide, carbon dioxide, carbon monoxide) (Cargill et al, 2000). Farmers and farm workers are often exposed to airborne dust especially when working with plant and animal material (Eduard, 1997). Exposure to airborne contaminants can have a general performance reducing impact on exposed animals mainly due to a reduction in feed efficiency. The airborne contaminants may also impair the animals’ immune competence thus increasing the risk for clinical or, more subclinical, diseases in these exposed animals (Sevi et al, 2002). The health impacts on animals may also be related to possible health impacts on humans.

2.2.1 Dusts

Dusts (or particulates) are a broad category that describes solid particles suspended in air (Tranter, 1999). Inorganic dusts are generally derived from a mineral source such as rock or soil (although some plants contain silicates). Most are relatively benign but they may act non-specifically as a mild irritant and they do this by placing an added load on the clearance mechanisms of the lung. Inorganic dusts are primary nuisance dusts (Donham, 1986) but can be potentially hazardous as they can cause a mechanical blockage of macrophages found in the respiratory tract (Wathes, 1992). A few inorganic dusts, silica and asbestos for example, can have severe health effects (Donham, 1986). Plants, animals and soil are the basic sources of farm dusts in descending order of importance. A large range of other sources, such as feed additives, pesticides and metallic fumes, make lesser contributions (Watson, 1986). Inorganic dusts are prevalent but less clinically significant than organic dusts (Eduard, 1997). Organic dusts are derived from an organic source, either plant or animal, they are more biologically active than inorganic dusts (Donham, 1986). A tractor tilling a field trailed by large plumes of dust is a common sight throughout the rural landscape but that is not the only method of exposure to inorganic dusts (Kirkhorn and Garry, 2000). Modern agriculture involves utilizing technologies and work practices that generate substantial amounts of dusts. The extent and nature of exposures vary according to the task. For example, tillage work is associated with exposure to mainly inorganic dust in concentrations ranging between 1.5 mg m-3 and

9 60 mg m-3 (Zejda and Dosman, 1993). Research has suggested that animal feed is the greatest source of potential dust that a farmer can come in contact with (Pearson and Sharples, 1995). In relation to pigs it has been found that of the total bioaerosol exposure of the collected samples 8% were from skin, 1% from hair and the remaining 91% were attributed to feed (Pearson and Sharples, 1995). Exposure to organic dusts is more frequent than inorganic dusts during outdoor farm work with exposures ranging between 4 mg m-3 and 31 mg m-3 and maximum concentrations as high as 60 mg m-3 for organic dusts. Airborne concentrations of organic dusts associated with routine operations on dairy farms (feeding, cleaning, chopping of bedding) may vary between 0.05 mg m-3 and 40 mg m-3 and mean concentrations of the respirable fraction of this dust may range from 1.6 mg m-3 to 2.5 mg m-3 (Zejda and Dosman, 1993). Approximately 90% of the dust found in the air of cow houses is composed of fine dust particles (Kotimaa et al, 1987).

Agricultural dust is composed of nonviable and viable (ability to grow and reproduce) fractions. The non-viable fraction includes substances such as vegetable particles (grain and feed) litter, dander, dried faecal material and mineral particles. The viable fraction is composed of micro-organisms (bacteria, mites, fungi) and their metabolites (Zejda and Dosman, 1993). Only a small proportion of moulds found in indoor buildings are viable (Walinder et al, 2001).

Any dust has the potential to cause lung disease if: (a) the particle is small enough to penetrate the lungs and down to the alveoli, and/or (b) the agents are water or lipid soluble, and/or (c) inflammatory reactions occur at realistic concentrations of the agents (Zuskin et al, 1994).

The dense stocking (holding) of animals within buildings may result in large quantities of respirable dusts being generated. These dusts are generated not only from feeding and bedding activities but from the animals themselves as dried urine, faecal matter and hair and feather particles (Murphy, 1992). It is thought that all dust falls in to three size related categories: respirable, inspirable (inhalable) and total (Attwood, 1985).

10 The European Community described respirable dust as having a median diameter of 4.0 µm (ISO, 1995) and they are hazardous when deposited in the gas-exchange area of the lung and penetrate to the level of the terminal bronchioles and the alveoli (the gas-exchange area) (Kirkhorn and Garry, 2000). The ACGIH (2006) defines the respirable dust sampling upper aerodynamic diameter cut-off as 10 µm. Hence, according to that definition the respirable size fraction of dust can be up to 10µm in diameter. The ACGIH (2006) also defines respirable dust as having a median cut point or diameter as 4 µm.

Inhalable (also called inspirable) dusts have been defined by ACGIH (2006) as having a median aerodynamic diameter of 100 µm. This is a larger aerodynamic equivalent diameter then respirable dusts and because of this, inspirable dusts settle higher in the respiratory system (Tranter, 1999). Inspirable dusts have also been defined as dust that is able to penetrate into the human respiratory system (Attwood, 1985).

The term “total dust” is used for the collection of all particles (Buchan et al, 2002), but only refers to the dust that was collected by the instrument used. It does not refer to the total amount of dust in the air (Pearson and Sharples, 1995).

Dusts that have not been currently identified as having a toxic effect are considered to be benign particles that can induce serious adverse pulmonary effects if they are inhaled chronically at high concentrations (Oberdorster, 1995).

The size of the particle dictates where in the body that particle can lodge after inhalation. Particles of aerodynamic diameter greater than 20 µm deposit in the turbulent airflow regions of the nose and upper respiratory tract (nasopharyngeal region, the trachea, and the lung bronchi). They are considered less important and damaging since many are trapped in the upper respiratory tract, nose and windpipe (Pearson and Sharples, 1995). Smaller particles, from 0.5 to 20 µm, deposit in the smaller airways and alveoli. There is debate as to whether particles between 0.1 and 0.5 µm normally remain suspended and are expelled when exhaling (Pearson and Sharples, 1995) or whether they impact on the lungs. It is suggested that because they have a low terminal velocity there is not enough time for deposition (ACGIH, 2002). Particles below 0.1 µm are considered too small to be exhaled and have many

11 collisions and great energy which enables them to be deposited in the alveoli (Que Hee, 1993). Gustafsson, (1999) suggested that the settling rate is also effected by the concentration of dust in the air. Agricultural dust particles can consist of either a single simple organism or can be made up of a mixture of particulates from many different sources (Jacobs, 1994), they may contain approximately 25% protein (Donham, 1986).

2.2.2 Bioaerosols

Particulate matter is emitted into the air from various pollution sources such as industrial activities, vehicles and agricultural processes (Adel Hameed and Khodr, 2001). Agricultural operations are one of the most important sources of airborne organic dust and bioaerosols. Bioaerosols are defined by Douwes et al (2003) as aerosols or particulate matter of microbial, plant or animal origin that is often used synonymously with organic dust. Bioaerosols of different and complex composition are produced from soil and crops during different agricultural operations and occur in diverse environments and can be a vehicle for the dissemination of human and animal pathogens (Pillai and Ricke, 2002). Workers are exposed to microorganisms from laden aerosols emitted from grains, cotton, hay, jute, and tobacco (Adel Hameed and Khodr, 2001). The primary sources of toxic and allergenic contributors in animal confinement facilities are animal faeces, endotoxins and pollens. Faeces dried on animals can also be dust sources (Takai et al, 1998).

Bioaerosol particles range in size from <0.01 to 100 µm with up to 40% in the respirable range (Kirkhorn and Garry, 2000). As with all airborne matter particle size controls the site of deposition in the respiratory tract and therefore will affect potential development of allergic respiratory disease (Mishra et al, 1997). All airborne particles are subject to Brownian motion, gravity, electrical forces, thermal gradients, electromagnetic radiation, turbulent diffusion, inertial forces, oxygen concentrations, and relative humidity (Pillai and Ricke, 2002). The extent of the impact that these forces have on bioaerosols is dependant on the bioaerosols physical properties such as size, shape, and quantity (Pillai and Ricke, 2002). There is also the biotic factors of the bioaerosol including the organisms type, viability status,

12 growth phase and any inherent resistance that may be present (Pillai and Ricke, 2002). Particles with an aerodynamic diameter of 20µm settle at approximately 1.0 m s-1, whereas particles of 5.0µm diameter settle at approximately 0.1 m s-1 (Pearson and Sharples, 1995). The gravitational effect on a bioaerosol particle is countered by the drag or frictional force exerted on that particle. When the forces are equal, the particle reaches its final or terminal velocity (Pillai and Ricke, 2002). For example, the size of Aspergillus fumigatus spores makes them able to penetrate deep into the human lung where within minutes of deposition they release a toxin to inhibit macrophage activity and enhance their ability to persist (Kenny et al, 1998).

Spores from fungi and actinomycetes are often liberated as single spores or small aggregates (Karlsson and Malmberg, 1989). They are often liberated when mouldy hay and grain is handled and many inhaled spores may reach the alveoli (Eduard, 1997). Materials other than hay or grain from the interaction with animals may also cause considerable exposure to spores in farm environments (Kotimaa et al, 1987).

Microorganisms are important components of dusts since they occur naturally in such materials as manure, silage and compost and can colonize in other farm materials when conditions are favourable for growth, e.g., during storage of moist grain, hay and straw (Eduard, 1997). Although microorganisms need to be viable for pathogenic effects to occur allergic responses (which are much more widespread) can be triggered by both viable (culturable and non-culturable but viable) and non-viable cells (Kenny et al, 1998). Most of the microorganisms present are mainly non- infectious (Dutkiewicz, 1992) but inhalation of non-infectious microorganisms and their constituents can cause inflammation of the respiratory system while antigens and allergens may activate the immune system and cause allergic and immunotoxin effects (Eduard, 1997). Theoretically, bioaerosols can be launched from point, linear or area sources (Pillai and Ricke, 2002).

Structural constituents of microorganisms are referred to as primary metabolites while compounds excreted by microorganisms into the environment, e.g., mycotoxins and proteolytic enzymes are referred to as secondary metabolites. Bioaerosols may consist of pathogenic or non-pathogenic live or dead bacteria and fungi, viruses high molecular weight (HMW) allergens, bacterial endotoxins, mycotoxins, peptidoglycans,
(13)-glucans, pollen, plant fibres, etc (Douwes et al,

13 2003). Examples of primary metabolites that have been associated with health effects are endotoxins present in the cell walls of Gram-negative bacteria and β-glucans in the cell walls of many fungi. Secondary metabolites may be found in particles from colonized materials as well as in the microorganisms and their spores (Eduard 1997). Despite the acknowledgement of the importance of bioaerosol exposure on human health the precise role of biological agents in the development and aggravation of symptoms and diseases is not very well understood (Douwes et al, 2003). It is not clear (with a few exceptions) which specific component(s) primarily accounts for the associated health effects (Douwes et al, 2003). Microbial toxins should not be excluded from the discussion of the causative agents of diseases in exposed persons (Lundholm et al, 1986). Factors determining the intensity of exposure to the predominant species of bacterial, fungal and actinomycetous spores in the agricultural setting include meteorological conditions of the region, field moisture, technology of hay or grain storage, construction of the building and type of farming activity. Inhalation of airborne microorganisms can expose workers to risks from infection, toxicosis and allergy (Crook and Sherwood-Higham, 1997). Previous results (Pasanen et al, 1989) showed that in a cow barn the airborne viable spore levels were 103 to 105 cfu m-3 and the total spore counts were 104 to 107 spores m-3 depending on the work situation. In this same study the main fungal genera identified from the collected samples were Acremonium, Alternaria, Botrytis, Chrysosporium and actinomycetes. Spore concentrations found in farm homes have been shown to be several orders of magnitude higher than the typical urban home environment (Pasanen et al, 1989). Past studies also suggest that workers can carry spores from their working environment into their homes (Pasanen et al, 1989).

Microorganisms can be broken up into different categories that show what temperature the fungi best lives and grows in. Most microorganisms will grow well at temperatures favoured by humans. The three main groups of classification based on preferred temperature are psychrophiles, mesophiles and thermophiles. Psychrophiles can grow between 0oC and 30oC with an optimum growth temperature around 20oC, mesophiles can grow between 10 and 50oC with an optimum growth temperature of 25-40oC, and thermophiles can grow between 40 and 75oC with an optimum growth temperature of 50-60oC (Tortora et al, 1998). According to these

14 temperature categories most microorganisms found in animal handling buildings are going to be psychrophiles or mesophiles.

2.2.2.1 Bacteria

Bacteria are relatively simple, single-celled procaryotic organisms and they generally appear in one of several shapes. Bacillus (rod-like), coccus (spherical or oval) and spiral (corkscrew or curved) are the common shapes but square and star shapes are also possible. Individual bacteria may form pairs, chains, clusters or other groupings. Bacteria generally reproduce by binary fission but some can form spores to reproduce (Tortora et al, 1998). The different types of bacteria found in bioaerosols can be broken up into two main groups; Gram-negative and Gram- positive. The most common bacteria occurring in the farm environment are Gram- positive cocci (Staphylococcus, Aerococcus, Streptococcus, Micrococcus) and bacilli (Arthrobacter spp., Corynebacterium spp., Brevibactium spp., Microbacterium spp.). Aerobic endospore-forming bacilli (Bacillus subtilis, B. megaterium, B. cereus) are always present in organic dust but usually not in large numbers (Dutkiewicz, 1997).

Gram-positive bacteria are the predominant organisms in dusts of animal origin and may be common in dusts from stored plant materials. Gram-positive bacteria, despite their abundance in airborne dusts, are generally regarded as relatively less harmful than Gram-negative bacteria (Dutkiewicz, 1997). Nevertheless, they do contain many elements that may be dangerous such as muramyl dipeptide, peptidoglycan, teichuronic acid and formyl-methionyl-leucyl-phenylalanine-like peptides (Zhiping et al, 1996) and should be regarded as potential immunotoxicants (Burrell 1995). Thermophilic actinomycetes are irregular non-spore forming Gram- positive rods (Tortora et el, 1998) that can fragment into coryneform cells. They are associated with farmer’s lung. For these microbes to survive for long in stored material, the environment needs to have at least 35% water content (Lacey, 1986). During handling of mouldy hay the most common thermophilic actinomycete in the farmers’ breathing zone was reported to be Thermoactinomyces vulgaris, with Saccharopolyspora rectivirgula (formerly Micropolyspora faeni) also found in small numbers (Kotimaa et al, 1987).

15 Gram-negative bacterial species (Proteus, Pseudomonas, Escherichia, Erwinia) are generally less common but are potentially more pathogenic (Zejda and Dosman, 1993) because all species produce endotoxins in their outer membrane. In dusts of animal origin the most common are coccoid, non-fermentative species such as Actinobacter calcoaceticus, whilst less common are enterobacteria (Klebsiella spp., Escherichia coli) and Alcaligenes faecalis (Zejda and Dosman, 1993). Gram- negative bacteria are important producers of endotoxins which are the main pulmonary immunotoxicants.

Concentrations of bacteria up to 108 cfu m-3 and 109 total cells m-3 have been reported in animal houses (Eduard, 1997). These concentrations were measured using viable culture methods. From the same study it was shown that viable culture methods produce results that record microorganism concentrations approximately an order of magnitude less than concentrations determined using non-viable culture methods, which count dead cells as well as living cells. This is high compared with the median airborne concentration of bacteria in the urban atmosphere where 100 cfu m-3 in a new apartment and 10 cfu m-3 or less outdoors have been reported (Dutkiewicz, 1997). The percentage of Gram-negative species varies substantially in the farm environment. However in some livestock confinement units the airborne concentrations of Gram-negative species may account for 80-90% of total bacteria and median airborne concentrations of 104 cfu m-3 and 105 cells m-3 have been reported. The species Erwinia herbicola, found in concentrations of 103 cells m-3 is regarded as one of the most potent bacterial species and is linked to a number of respiratory effects through combined allergic and toxic activity (Dutkiewicz, 1997). In most occupational environments bacteria form a dominant fraction of the total microorganisms found in the air at a ratio to fungi of 10:1 (Dutkiewicz, 1992).

2.2.2.2 Fungi

Fungi are eukaryotes and may be unicellular or multicellular. Unicellular forms are often called yeasts and are normally larger in size than bacteria. The most typical fungi are moulds. Fungi can reproduce sexually, asexually or through budding (Tortora et al, 1998). There are more than 106 identified species of mould

16 (Umbrell, 2003). Most of the moulds and yeasts occur in nature as soil-dwelling saprobes or plant pathogens that become airborne (Mishra et al, 1992). Airborne concentrations of total spores in farm environments vary between 108 and 1011 spores m-3 whereas urban concentrations are usually lower at around 101-104 spores m-3. This relates to total concentrations of spores (Zejda and Dosman, 1993). In a very early study fungal spore concentrations in cowsheds were found to be 10-100 times that of farmyard air (Baruah, 1961). The concentrations of spores in livestock confinement buildings may reach 104-105 cfm m-3 compared with median urban concentrations of 102 cfu m-3 indoors and outdoors (Macher et al, 1991). During combine harvesting airborne spores may constitute as much as 90% of all spores with predominant genera being Cladosporium and Alternaria (Zejda and Dosman, 1993).

Other dominant genera of moulds that can be collected and cultured from an agricultural environment in India have been found to be Aspergillus, Absidia, Penicillium, Rhizopus and Syncephalastrum. (Adhikari et al, 2004). Wallemia sebi may be an important fungus as an aspect of health effects because it’s spores are small (2.5-3.5 µm in diameter) and they usually occur in spore aggregates of less than three spores when airborne (Hanhela et al, 1995). Fungal spores can often be 100-1000 times more numerous than other airborne particles such as grains (Adhikari et al, 2004). Yeasts represented about 17% of fungi collected in a study of farms in France (Reboux et al, 2001). The pathogenic significance of yeasts has not yet been definitely proven but certainly needs further studies as zymosan and other yeast glucans are strong immunomodulators and potential immunotoxicants (Dutkiewicz, 1997).

Relatively few fungi species are capable of causing primary mycotic diseases in individuals with no obvious or discernible pre-existing defects in their immune system (Mishra et al, 1992). However, there are certain cytopathogens and mycotoxins capable of causing cutaneous and subcutaneous infections that may cause damage to the lungs (Mishra et al, 1992). The concentration of fungi found in an agricultural environment can vary greatly between different farms (Hanhela et al, 1995). In that study xerophilic spore concentrations were higher and thermophilic spore concentrations lower than those of mesophilic fungi. Fungi are also known to produce mycotoxins which are known to cause adverse health affects (Macher, 1999)

17

2.2.2.3 Allergens

Allergens can comprise a large variety of macro-molecular structures ranging from low, mainly chemicals such as di-isocyanates, to high molecular weight sensitizers which are most often proteins of biological origin (Douwes et al, 2003). Most of these allergens include enzymes derived from fungi and bacteria. Allergens are often proteins or glycoproteins of molecular weights ranging from 5-70 kDalton (Eduard and Heederik, 1998).

Pollens, insect fragments, fungal moulds and bacteria are different allergens and can occur in high concentrations in grain or animal confinement areas. Allergenic effects from exposures in enclosed space facilities can vary from simple upper respiratory responses to bronchial hyperreactivity and asthma (Kirkhorn and Garry, 2000). Approximately 70 species of mites have been identified in various agricultural environments (Zejda and Dosman, 1993). Several animal proteins (dust mite, cat, mouse and rat allergens) are known to have strong allergenic properties (Douwes et al, 2003). Storage mites of the species Acarus siro, Lepidoglypys destructor and Gypcyphagus domesticus have been associated with type I allergic reactions (barn allergy) and are found in warm, humid and mouldy environments (Kirkhorn and Garry, 2000). The species of mite infestation depends on geographical and climatic conditions as well as on the type and condition of stored vegetable material (Zejda and Dosman, 1993). Mites are abundant in animal barns with concentrations as high as 1600 mites per gram of dust (Leskinen and Klen, 1987). A study by Kotimaa et al (1987) on the spores in a farm working environment found that the quality and quantity of airborne spores suggests farm work exposes farmers to a high risk of becoming sensitized which can lead to the development of diseases such as asthma or farmer’s lung.

Fungi and thermophilic bacteria are well-known sources of allergens that play a role in the development of many respiratory diseases. The specific species involved include many common species such as Penicillium and Aspergillus which are very common in the agricultural working environment (Douwes et al, 2003). Both of

18 these microbes have been associated with upper respiratory and other symptoms (Walinder et al, 2001).

Most bacteria and bacterial agents are not very potent allergens with the exception of the spore-forming actinomycetes. Bacterial cell wall components such as endotoxin and peptidoglycans are agents with important pro-inflammatory properties that may induce some respiratory symptoms (Douwes et al, 2003).

In studies with controls it has been found that there is no difference in antibody levels between people who work in confinement houses and the control population (Donham, 1994). However, allergies may affect up to 10% of the general population (Umbrell, 2003). Many in the population have an absence of symptoms when exposed to allergens but may report an irritant or inflammatory response (Cullinan et al, 2001).

2.2.2.4 Endotoxins

Endotoxins are high molecular weight lipopolysaccharides (LPS) that are integral components in the outer membrane of the cell walls of Gram-negative bacteria as heteropolymers with proteins and phospholipids (White and Ashley, 2002). They can easily be released in large quantities into organic dusts in the form of discoid particles (microvesicles) 30-50nm in diameter with a characteristic triple-tracked membrane (Dutkiewicz, 1997). Different endotoxins can have tremendous variety in their molecular structures. This variability in composition is of importance and may explain the differences in the strength of toxicities found with different endotoxins (Buchan et al, 2002). Both respirable and inspirable dust can contain endotoxins (Olenchock et al, 1986) making them ubiquitous in the agricultural environment (Michel et al, 1997). However they can only be released by organic dusts (Dutkiewicz, 1992). Endotoxins can be found in many different environments but the mass median aerodynamic diameter found in a farm environment for these particles can vary from 2 to 8µm (Buchan et al, 2002). Endotoxin can still be released when the bacteria are dead and fragmented (Rask-Andersen et al, 1989).

19 Some research has found correlations between levels of airborne endotoxin and dusts (Reynolds et al, 1994), however other studies have not (Castellan et al, 1987; Lundholm et al, 1986). In theory, endotoxin could be a marker for some other agent and it is possible that the effects seen in endotoxin-contaminated environments may be the result of combined exposures to several of the bioactive agents resulting in the observed effects. However, there is also a lot of evidence that environmental endotoxin is related to several lung diseases (Michel et al, 1997). This has been observed in many different occupations including farming. Clear dose-response relationships were also reported between exposure and response (Douwes et al, 2003; Michel et al, 1997; Dutkiewicz, 1992). “The time-related response has been intensively investigated by measuring several systemic (blood level) and local (lung function and bronchial lavage) inflammatory parameters after inhalation of a given dose of endotoxin” (Michel et al, 1997, p1157).

In humans an acute inhalation of endotoxin can induce a blood and lung inflammatory reaction in which neutrophils and macrophages are involved (Michel et al, 1997). In the past there was no correlation found between exposure to endotoxin and symptoms. Now, endotoxins exposure has been associated with many different diseases and conditions including: both reversible (asthma) and chronic airway obstruction and increased airway responsiveness (Douwes et al, 2003) where clinical symptoms include fever and shaking chills (Michel et al, 1997). Other studies into the indoor environment have suggested a causal relationship between endotoxin and asthma exacerbation in children and adults (Douwes et al, 2003). Endotoxins have a strong adjuvant effect on the reaction to antigens and increase the production of antibodies. There is only one study suggesting that such effects are found in endotoxin-contaminated environments (Rylander, 1997). White blood cell counts may also be reduced after exposure to endotoxin (White and Ashley, 2002).

Airborne endotoxin concentrations have been reported in different units by various authors in the literature. Rask-Andersen et al, (1989) reported that endotoxin concentrations in dairy farms may range between 0.01 µg m-3 and 50µg m-3 during feeding and cleaning operations with concentrations as high as hundreds of micrograms. A different study found the concentration range for endotoxins between 499 EU m-3 and 54,653 EU m-3 as measured by total dust sampling (Buchan et al,

20 2002). Farming animals is associated with increased exposure to endotoxins (Douwes et al, 2002). The variability of airborne endotoxin concentrations depends on geographical location and production techniques including feeding methods (Zejda and Dosman, 1993). In a study conducted by Olenchock, et al, (1986) it was found that the mean airborne levels of endotoxins differed depending on the size that was being collected with concentrations of 2 ng m-3 for the smallest sample size sampled and 400 ng m-3 for the largest sampled size. This depended on the size of dust being sampled.

It is not clear exactly how much endotoxin makes a person sick. It is also hard to define what “sick” is but there are some microbial exposure concentrations that have been found to cause certain diseases or conditions. Suggestions have been made that the concentration of endotoxins that could cause possible reactions to take place in humans is 0.2 µg m-3 (Lundholm et al, 1986). It has been suggested that 0.2 µg m-3 of endotoxin in the environment is a level where toxic pneumonitis will not develop among the general farming population (Rylander, 1997). Exposure to 30µg of endotoxin can lead to a small decrease in FEV1 but not exposure to 20µg of endotoxin (Rylander, 1997). In an experiment on cotton workers and previously unexposed persons the threshold values for FEV1 decreased after four-hour exposures and were 0.17 µg m-3 among non-smoking cotton workers and students and 0.08 µg m-3 among cotton workers who smoked (Rylander, 1997). In relation to airways inflammation it is suggested that 0.01 µg m-3 or 10 ng m-3 will not lead to an increased risk in normal subjects (Rylander, 1997). What is clear is that in occupational settings endotoxin concentrations are frequently above 100 ng m-3 in air. This has been reported to occur in swine and poultry confinement buildings, cotton industries and waste handling (Michel et al, 1997). Endotoxin concentrations were found to be at least tenfold higher in swine barns than in sawmills (Pillai and Ricke, 2002). This level is higher than all of the levels that have been found to cause potential diseases and conditions. Endotoxin concentrations tend to be higher in the day than the night in animal confinement buildings (Pillai and Ricke, 2002). Co- exposure to other airborne irritants (e.g. tobacco smoke) and probably also genetic predisposition may enhance the effects of the inhaled endotoxin (Dutkiewicz, 1992).

21 2.2.2.5 Mycotoxins

Mycotoxins are low molecular weight bimolecular toxins produced by some fungal species that are toxic to both animals and humans. They can cause a toxic reaction if food is contaminated with toxigenic fungi (Lacey et al, 1994). For exposed workers inhalation is another source of exposure (Brera et al, 2002). The possible adverse health effects are mainly related to genotoxicity, carcinogenicity, mutagenicity, teratogenicity and immunotoxicity (Brera et al, 2002). Mycotoxins are commonly seen as the aetiologic agent behind the clinical picture of farmers with sudden acute illness after working with mouldy hay (Selim et al, 1998). It has been suggested that there is no credible evidence that mycotoxins have adverse effects on humans (Umbrell, 2003). However, it has been recognised that pre-term births or late abortions in farm women exposed to mycotoxins have occurred (Douwes et al, 2003).

Mycotoxin-contaminated dusts have been proven to have an immunosuppressive effect on the body (Brera et al, 2002) with some being potent carcinogens (Douwes et al, 2003). The mycotoxins that have been established as carcinogens are well proven (Douwes et al, 2003). The best-known carcinogenic mycotoxin is aflatoxin from Aspergillus flavus. Aflatoxin B is more concentrated on the smaller dust particles (Selim et al, 1998). Exposure to low levels of aflatoxin over a long period of time could produce a dose capable of causing cancer (Selim et al, 1998). Aflatoxin is not detectable on all farms (Selim et al, 1998).

Studies looking for the concentration of aflatoxin on farms have found that the range of concentrations is large from 23 to 5100 ng g-1 in settled dust from swine buildings (Selim et al, 1998). Ochratoxin is also considered a possible human carcinogen (Douwes et al, 2003). Other species that may produce mycotoxin include Penicillium and Fusarium (Seedorf et al, 1998). A study on wheat grain and grain dust in the Lublin province of eastern Poland carried out in 2001 found that farmers were exposed to notable quantities of fusaria and/or fusariotoxins. This study collected 10 samples of stored wheat grain and 10 samples of grain dust which was released during use of a threshing machine. The potential problem with fusaria and fusariotoxins is that they are mycotoxins whose potential health effects are not completely known (Krysillska-Traczyk et al, 2001). However, very little is known

22 about occupational airborne exposures to mycotoxins in relation to respiratory health effects (Douwes et al, 2003) and this needs further clarification. What is known about respiratory exposure is that the lungs may be more susceptible to toxic effects from inhalation of mycotoxins than by oral ingestion (Lacey et al, 1994).

2.2.2.6
(13)-glucans

(13)-glucans are glucose polymers with variable molecular weight and a variable degree of branching that is found in most fungi, some bacteria and most plants (Douwes et al, 2003). Glucans can elicit a direct antibody-independent response with bronchial tissue cells resulting in activation of cellular and humoral inflammatory mechanisms (Eduard and Heederik, 1998). Results of several studies where humans were exposed to airborne
(13)-glucans suggest that these agents play a role in bioaerosol induced inflammatory responses and resulting respiratory symptoms. It has also been suggested that
(13)-glucans may act synergistically with endotoxin in causing airway inflammation and also have pro-inflammatory capacities (Douwes et al, 2000). There is a small amount of evidence that there is a health link between
(13)-glucans exposures in the occupational environment but most studies concluded this was small (Douwes et al, 2003). A link between exposure to high levels of
(13)-glucans and changes in some parts of the inflammatory and immunological system has been proven (Beijer et al, 2003). They can also be used as a marker of mould growth (Walinder et al, 2001).

2.2.3 Gases

It is difficult to distinguish the separate health impacts of gases and dusts as they often occur together in agricultural environments (Kirkhorn and Garry, 2000) and may have a synergistic effect. High-density animal confinement facilities and in particular swine confinement operations, generate high levels of gases as part of the by-products of animal waste. These gases include hydrogen sulfide (H2S), ammonia

(NH3), carbon dioxide (CO2) and methane (CH4). Carbon dioxide (CO2) is a by- product of animals or humans breathing. The gases of primary concern are H2S and ammonia. H2S at low levels is a respiratory irritant and at higher levels a chemical asphyxiant. Ammonia is a common gas found in animal and poultry confinement

23 operations, is very soluble and is a respiratory and mucous membrane irritant. It is common to many farming areas as it is produced by the decomposition of manure. Ammonia has been associated with upper airway irritation, sinusitis, chronic obstructive pulmonary conditions and mucous membrane inflammation syndrome (Kirkhorn and Garry, 2000). It has also been suggested that a decrease in baseline and cross-shift lung function is associated with the concentration of ammonia that the worker is exposed to (Chang et al, 2001). Prolonged exposure to ammonia at levels below the OSHA (Occupational Health and Safety Association) Personal Exposure Limit of 25 ppm has been linked to adverse health effects. Unlike hydrogen sulfide and ammonia, carbon monoxide and methane are simple asphyxiants and generally not primary causes of adverse health effects (Kirkhorn and Garry, 2000). Carbon monoxide (CO) can also be present in animal housing areas. CO within a confined animal space originates from the incomplete combustion of fossil fuels. Unacceptable concentrations may result from back drafting of exhaust gases from fossil fuel space heaters or from improper adjustment of the heater burners (Feddes and Barber, 1995). There are no heater burners used in a shearing shed but sometimes generators are used which may be either diesel or petrol powered. In high concentrations (over the acceptable limits) some of the gaseous pollutants may have a direct health risk but in sufficiently ventilated farm buildings dangerous levels are rarely reached in practice (Tamminga 1992).

2.3 Health Impacts

Agriculture has been shown to be among the highest risk groups for occupational injury and illness worldwide. In Australia the industry has the third highest rate of fatalities after transport and mining. Rural industry (including agriculture) normally accounts for 19% of all Australian occupational deaths with an average of 100 deaths annually. Non-fatal injury is also considered significant with an average of 30 injuries per 100 farms per annum with an average loss of 10 working days (Aoun and Jennings, 2003).

Farm accidents are considered to be under-reported. In Queensland the incidence of injury to farm employees who have a lodged workers’ compensation claim represents

24 only 7-19% of all injuries that occurred. The most common activities being undertaken at the time the farm injury occurred were animal handling (40% of the injuries), general maintenance (27%), cropping (10%) and produce handling/processing (5%) (Aoun and Jennings, 2003). The best estimates available from 2000, indicate that throughout Australia sheep shearing injuries alone made up 14.8% of the agricultural sector workers compensation claims at a figure of between $7 to $19 million per annum (Fragar et al, 2001). This is approximately 0.5% of the gross value of wool production in Australia in 2002-03 or an estimated 5% of the net value of wool production in Australia (ABS, 2005). Almost half the workers compensation claims for shearers involve body stressing with another 40% being associated with the body hitting or being hit by another object (mostly sheep or the shearing equipment). Body parts injured are most commonly the hand (22%) and back (20%). The incidence of annual injury/disease per 1000 wage and salary earners per annum is 89.6 for people working in sheep shearing services. For sheep shearers this rate increases to 151.5 in comparison to the all Australian industries rate of 25.5. The average number of working days lost per injury is 68.6 which is higher than the all occupations average of 49.9 working days lost (Fragar et al, 2001).

Compared with other occupations farmers have been reported to have a higher prevalence of depression and higher suicide rates. The overall depression rate was 12.2 % for one group of farmers and 7.4% for a second (Scarth et al, 2000). Depression rates in farmers increased as general health declined. The risk factors for high depression rates were found to be: negative life events, lower general health and being unmarried. Unmarried farmers were 3.46 times more likely to show depressive symptoms than farmers who were married (Scarth et al, 2000). The relative risk of agricultural employees developing skin disease was four times greater than the risk for all non-agricultural employees (Mathias, 1989). The prevalence of skin cancer was also three times higher for farmers (Brackbill et al, 1994).

New Zealand workers in agricultural occupations have a three times greater risk of fatal injury compared with the all industry average. Most fatal injuries occurred in the animal producer occupations of agriculture. In Australia the number of compensatable fatal injuries fell from 28 in 1994 to 14 in 2004 (ACSS, 2006a). Farmers also have a 3.5 times higher rate of amputations than other occupations (Brackbill et al, 1994). Only 22% of people working in the sheep industry have

25 normal hearing and there is a reported gradual deterioration in hearing thresholds of farmers as their years in the industry increase (Fragar et al, 2001).

Agricultural workers are exposed to a host of irritant and sensitising plants, chemical irritants and skin sensitisers as well as arthropod bites and stings and heat, cold, and ultraviolet radiation. It is not surprising, therefore, that in America it has been found that the agricultural sector consistently has the highest incidence of occupational dermatoses of any occupational sector (Merchant and Reynolds, 2000). Contact dermatitis has been reported in a variety of agricultural occupations most commonly in fish or meat handling. Common contact urticaria-producing meats and fowl include beef, pork, lamb, liver (various meats), chicken and turkey (Reiche, 2002). Shearers’ hands often have some form of dermatoses from the handling of sheep and wool.

Pesticides are defined as substances used to destroy, prevent, control, attract or repel pests or to regulate plant growth. The hazard level of any pesticide will depend on the pesticide’s toxicity, the concentration of the chemical, the duration of exposure and the route of entry or absorption into the body. Research is being conducted with Australian wool to examine the potential problem of pesticide residues in wool. These residues have the potential to result in unacceptable exposure to pesticides by shearers and other workers handling treated sheep and wool (Fragar et al, 2001). Pesticides can be potentially dangerous to a persons’ health but the concentrations that shearers may be exposed to is currently unknown.

Lack of lighting can be a problem in some shearing sheds. Good light is essential to ensure that the activities are undertaken with minimal chance of an accident being caused because the workers can not see what they are doing. Marchant (2000), recommended illumination levels for shearing sheds of 500 lux for the classing table, 250 lux for the shearing board and between 100 to 200 lux for the sheep storage area and wool room. The incident rate caused by poor lighting is hard to calculate because workers compensation information does not include this.

Ramazzini (1713) cited by Ferguson (1998), described lung disease associated with work in farming occupations. This report acknowledged some fear that respiratory disorders such as chronic bronchitis were associated with exposure to fibrous plant

26 materials and dusty conditions encountered in farming occupations. So, potential respiratory problems are not really new to agriculture.

There are many different diseases and conditions that can be found in agricultural workers. Since the average human inhales about 10 m3 of air per day inhalation is the predominant route resulting in adverse health effects (Pillai and Ricke, 2002). Nevertheless this does not mean that the respiratory tract is the sole route of exposure. Other pathways of exposure include the conjunctiva while ingestion of microbes from surfaces (eg hands, food, etc) contaminated by deposition may also provide the necessary dose of infection. However, many of the important respiratory diseases are found to involve the respiratory tract. This is because many diagnosed work related diseases for farm workers are known to be transmitted through the air (Wathes, 1992). Respiratory symptoms and lung function are considered the most widely studied and believed to be amongst the most important associated health effects from exposure to bioaerosols (Douwes et al, 2003). Many respiratory diseases caused by exposure to agricultural dusts are also known to affect cattle (Rylander, 1986) and many other species (Hungerford, 1990).

2.3.1 Respiratory System

In comparison with skin the mucosal membranes form a weak mechanical barrier but they provide an extensive defence system that comprises specific and non-specific elements (Feron et al, 2001). The nose, in humans and some animals, serves as a filter, humidifier and thermoregulator of inspired air and possesses an effective mucociliary apparatus for removal of insoluble particles and extensive metabolic capacity to deal with soluble particulate and gaseous air pollutants. In both humans and animals the inhaled air is monitored in the nose for the presence of odorants, pheromones, sensory irritants, and immunogens by the olfactory, vomeronasal, trigeminal sensory, and immune systems, respectively. The mucosal surface of the upper respiratory tract does not respond with inflammatory reactions to all environmental antigens. Instead, the nasal passages are a major site for the development of tolerance to environmental antigens (Feron et al, 2001).

27 At its simplest the lung is a series of branching tubes of progressively smaller individual diameter tubes, of increasing total surface area, leading to a thin alveolar membrane through which exchange of oxygen and carbon dioxide takes place (Figure 2.3.1). By the time human lung growth is complete, at adolescence, there are some 28 orders of division of the airways with about 25000 terminal bronchioles leading to a total alveolar surface area of some 40-80 m2. The vulnerability of this system to inhaled particles is illustrated by the importance of lung infection as a cause of death worldwide – tuberculosis and pneumonia are the main causes of death in the third world and increasingly threaten health in the developed world (Seaton, 1999).

Figure 2.3.1 Anatomical features of a set of human lungs (ADUK, 2006).

The lung’s defences are both mechanical and chemical. The airways are lined by an epithelium, a self-regenerating system of cells, which secretes mucus with antibacterial properties. Any inhaled organism deposited on to the airway wall is likely to be removed by the mucus and neutralized by the chemicals within it.

28 Damage to this defensive system by, for example, cigarette smoke or inhaled toxic fumes will lead to inflammation and the symptoms of cough and sputum production known as bronchitis. The role of the respiratory system is to protect the body against inhaled organisms. It generally does this well unless a serious overload of contaminants is inhaled. Some organisms have evolved mechanisms to counter these defences and are therefore important causes of illness. An example relevant to agriculture is Aspergillus fumigatus (Seaton, 1999).

The spectrum of agriculture related non-malignant respiratory diseases is wide and includes infections, acute chemical injuries and chronic non-specific lung diseases. In developed countries the latter group constitutes a priority from a public health standpoint (Zejda and Dosman, 1993). In the past 40 years there has been a tremendous increase of interest in the study of respiratory disease associated with agriculture and these investigations have confirmed that certain agricultural activities may be associated with adverse health effects (Ferguson, 1998). The different respiratory diseases that will be reviewed in detail in this study are mostly non- specific lung diseases that are related to organic dusts and agricultural exposure such as chronic bronchitis, hypersensitivity pneumonitis and Organic Dust Toxic Syndrome (ODTS).

Farmers experience an overall older average mortality age compared with the general population (Coble et al, 2002). This is supported by a study of farmers in Iowa and North Carolina where the standardized mortality ratios for total mortality, cardiovascular disease, diabetes, total cancer and cancers of the esophageus, stomach and lung were 0.6 or lower for both farmers and their spouses (Blair et al, 2005). Scandinavian farmers appear to have an increased mortality from respiratory diseases than the general population (Larsson et al, 1988). Farmers were also 10% less likely to go to hospital than the general population. When the different diseases are analysed farmers had lower mortality and morbidity rates than the average population for mental disease, cardiovascular disease and less well-defined causes. However farmers had higher rates of tumours, eye disease, urinary tract disease, musculoskeletal disorders and trauma (Stiernstrom et al, 2001). In another study elevated rates for certain types of cancer suggested the role of environmental causes had been detected (Coble et al, 2002).

29 An increased prevalence of respiratory symptoms has also been observed when farmers were compared with non-farming populations (Monso et al, 2003). The rate of respiratory conditions was found to be higher among farmers in America but the rate was not statistically significant (Brackbill et al, 1994). A Scandinavian study of pig farmers found that 30% of workers exposed to air in pig confinement buildings lost work time due to respiratory problems (Philip, 1995). Agricultural workers are the largest population at risk of exposure to occupational hazards of the lung (Lenhart and Reed, 1989). Epidemiological data shows that disability attributed to respiratory diseases is greater in the agricultural sector than in other occupational categories (Rylander and Donham, 1986). It has been shown that agricultural workers who claim workers’ compensation for respiratory problems have a significantly elevated risk of mortality from respiratory diseases than that of the general population (Beaumont et al, 1995). This is supported by claims that an excess of deaths from respiratory diseases among people employed in agriculture has been confirmed by mortality statistics obtained in both Europe (Heller and Kelson, 1982) and North America (Beaumont et al, 1995). Higher rates of non-malignant respiratory diseases have also been reported in America (Blair et al, 2005). About 20% of the farming workforce in Scotland suffers from some form of respiratory disease or disorder (Watson et al, 1986). Thirty percent of American farmers self- reported cardiovascular disease (Brackbill et al, 1994) and prevalence figures for some diseases (up to 40%) have been found for certain farming subgroups (Donham and Rylander, 1986). The known health effects of airborne particles have been comprehensively studied and strong associations have been observed between human mortality and morbidity and particulate matter (PM) concentrations (Hopke, 2003).

Diseases and disorders are most likely to appear in workers who have worked for several years in animal handling buildings (Murphy, 1992). The exposure time of workers to potentially hazardous dust varies from a few hours a week to 8 hours or more per day. Gurney et al (1991) reported that the prevalence of chronic respiratory symptoms among people that work in swine confinement buildings is very high. Up to 70% had symptoms of bronchitis, 10%-15% had asthmatic symptoms, and 10%- 15% had episodes of a hypersensitivity pneumonitis-like syndrome.

Many farming activities (including poultry and grain growing) are clinically proven risk factors for more than one respiratory symptom (Monso et al, 2003). Agricultural

30 respiratory conditions tend to have overlapping symptoms. These symptoms are frequently non-specific and are often mistaken for common viral or bacterial respiratory infections. In many cases a patient will not present with a textbook picture of a disease and this does not mean that the patient is not suffering from environmental exposures. Many of the symptoms are non-specific making it futile to look for one specific agent such as a microorganism (Rylander, 1986). It has also been suggested that it is not important to find out what the problem agent is - only what control measures need to be put in place (Lacey, 1986).

2.3.2 Respiratory Diseases

2.3.2.1 Hypersensitivity Pneumonitis (HP)

In agriculture, Farmers Hypersensitivity Pneumonitis (FHP) has also been called extrinsic allergic alveolitis (EAA) or Farmer’s Lung Disease (FLD) (Yi, 2002). This disease has been documented in relation to dairy farmers, poultry farmers and other groups of farmers exposed to mould and organic material such as mushrooms (Zejda and Dosman, 1993). After an initiating event (acute phase) high-level exposures to mouldy dusts results in clinical effects symptomatically equivalent to ODTS but generally with radiographically demonstrable alveolar lung infiltrates and oxygen desaturation. More commonly repeated exposure to relatively low levels of antigens in organic dusts leads to the insidious loss of pulmonary function. Pathologically, extensive and localised alveolar infiltrates of lymphocytes are noted in the initial phases of this disease progressing to the formation of granuloma. As the disease progresses a chest X-ray will show fibrotic changes in sections of the lung (Kirkhorn and Garry, 2000). Digital clubbing may also be found (Yi, 2002). Later collagen may be deposited and giant cells may form (Rylander, 1986). 80% of individuals with acute symptoms have abnormal chest X-rays (Yi, 2002). Chest radiographs, pulmonary function tests and routine laboratory tests are not specific in HP. The acute form is the most frequent presenting form. Symptoms of fever, chills, cough, dyspnea, chest tightness and malaise occur about 4 to 8 hours after exposure to antigens and usually resolve within a few days (Yi, 2002). Inspiratory crackles are also common (Reboux et al, 2001). The subacute form often appears over several

31 weeks or months of exposure with marked progressive pulmonary manifestations including cough and dyspnea (Yi, 2002). In the chronic form of the disease, extensive lung fibrosis occurs (Craighead, 1995). The lung function changes are non- specific and similar to other diseases including sarcoidosis, collagen vascular diseases and other interstitial lung diseases. The loss of lung volume, impaired diffusion capacity of carbon monoxide, decreased compliance, and exercise-induced hypoxemia are all common. Gas exchange impairment is predominant in a small number of the patients (Yi, 2002). Many patients who develop HP report a recent viral respiratory infection and often complain of “flu-like” symptoms (Yi, 2002). Increased percentages of lymphocytes and increased albumin levels can be found in the broncoalveolar lavage (BAL) by patients with HP (Larsson et al, 1988).

The identification of antibodies plays an important role in defining cause and effect in FHP. Diagnosis is usually based on a positive clinical and occupational history and is generally confirmed by the findings of circulating antibodies to antigens from FHP (Guernsey et al, 1989). It often goes misdiagnosed as viral pneumonia or idiopathic interstitial lung disease unless a careful history is taken (Yi, 2002). In this history it is important to ascertain if the person is a smoker as this is an indicator against the diagnosis of HP which is important as most patients (80-95%) are non- smokers. It is speculated that smoking may alter the defence mechanism or immunologic reactivity of the lung (Yi, 2002). The validity of diagnostic procedures can be substantially enhanced by the recognition of the importance of individual exposures and the modifying effect of the clinical stage of the disease (Zejda and Dosman, 1993). Skin testing has limited diagnostic value in HP. Specific serum precipitating antibodies (IgG) are found in most patients with HP as well as approximately 40% of asymptomatic exposed persons. A timely diagnosis is important so that further exposure to the antigen can be avoided before irreversible lung injury occurs (Yi, 2002).

It should be noted that prevalence of the disease varies according to climate. FHP is most common in cool and moist northern climates. Symptomatic attacks are more common in late winter or early spring when stored hay or grains are used to feed livestock. Extremely high levels of bacterial spores can be released from these activities (May and Schenker, 1996). It has been estimated that between 5 and 15% of an exposed population will develop HP and the reasons why are not clear. It is

32 more frequent in men and nearly all cases are in adults (Yi, 2002). FHP is a workers compensable disease in Great Britain (HSE, 2005). Once sensitisation has occurred, continued exposure to low levels of antigen can lead to progressive irreversible pulmonary disease including emphysema (Kirkhorn and Garry, 2000).

In most cases adequate treatment consists of the patient’s avoidance of the antigen, minor symptomatic therapy with antiinflammatory drugs and, if necessary, bronchodilators. In some cases the use of steroids for 2 to 4 weeks produces a resolution of clinical, functional, and radiological findings. For chronic forms of the disease, steroid use may delay the onset of increased lung damage. It has been suggested that steroid therapy hastens the recovery from the acute stages of the disease but does not provide a beneficial affect on the long-term prognosis (Yi, 2002).

The American Thoracic Society summarises FHP as: (a) FHP leads to progressive symptoms in at least one-third of those affected; (b) FHP may be fatal if unrecognised; (c) Recurrences are an important determinant of clinical outcome; and (d) Emphysema is an important outcome of FHP. Early recognition of the sources of exposure and symptoms by farmers and their physicians is a key to prevention and control of this disease (Kirkhorn and Garry, 2000).

The development of HP is suspected to be caused by inhalation of microorganisms especially fungi (Lundholm et al, 1986). The suggested antigens that are responsible for HP in farmers are: thermophilic and mesophilic actinomycetes, Aspergillus spp., Thermoactinomyces vulgaries, and Micropolyspora farni, and this list is ever increasing as different environments and being farmed (Yi, 2002). Most of these antigens are found in mouldy hay, straw and grain dust. The bacterium that is most commonly considered responsible is Saccharopolyspora rectivirgula. T. beigelii is also thought to be responsible and is seen as a cream-coloured yeast-like colony, which becomes yellowish-grey and has a wrinkled or radially furrowed surface and grows rapidly at 28oC (Summerbell et al, 1994). Fungi has also been related to HP, and A. corymbifera is a common fungi that is suspected of causing HP in France and

33 Eurotium umbrosum is suspected in Finland. Cross-reactions, that is, reactions to more than one microbe have also been reported (Reboux et al, 2001). There is no data suggesting that endotoxins are causative agents for HP (Rylander, 1997).

2.3.2.2 Organic Dust Toxic Syndrome (ODTS)

Typical Organic Dust Toxic Syndrome (ODTS) occurs as a result of exposure to mould-laden hays and grains (silo unloader’s syndrome) (Kirkhorn and Garry, 2000). The symptoms of ODTS are experienced by 6-8% of farmers and have been found to be more common among swine producers and grain workers affecting up to 30% of exposed subjects (Zejda and Dosman, 1993) in Europe. ODTS cannot be distinguished from FHP by clinical symptoms. They both occur 4-8 hours after exposure and result in a self-limited flu-like illness consisting of chest tightness, shortness of breath, dry cough, fever, chills, myalgias, and fatigues. ODTS is often misdiagnosed as farmer’s lung, which is the default diagnosis for many respiratory illnesses resulting from agricultural exposures, particularly if an adequate exposure history is not obtained and appropriate testing is not performed (Kirkhorn and Garry, 2000). Symptoms are directly related to dust levels and can be reproduced in subjects experimentally exposed to grain dust in high concentrations (doPico et al, 1982). It is probable that ODTS is a toxic reaction rather than an immune reaction (Kirkhorn and Garry, 2000). The clinical findings for toxic pneumonitis are leukocytosis and increased numbers of neutrophils and markers of inflammation in the airways. The disease affects the lung tissue, as shown through a reduction of alveolocapillary gas transfer and restrictive lung-function changes (Rylander, 1997). ODTS may be a risk factor for chronic bronchitis (Monso et al, 2003).

Unlike FHP, ODTS is not associated with sensitisation and neither skin tests nor serologic tests can identify apparent immunologic involvement. Other distinct features, in contrast to FHP, include normal chest X-ray and normal lung function (Zejda and Dosman, 1993). Endotoxin is the probable chief cause of inflammation but endotoxin-free grain extract can also contribute to a pulmonary inflammatory reaction (Kirkhorn and Garry, 2000). Direct toxic response to inhaled mycotoxin, proteinases, enzymes or endotoxin may be etiologic factors (Zejda and Dosman,

34 1993). It is not a progressive disease and the sufferer normally recovers within several days. ODTS can come from many different types of exposures including uncapping silos, cleaning out animal housing areas and breaking open mouldy hay and straw bales. Preventive measures are similar to most preventive possibilities for agriculture and include the use of personal respiratory protection and work practices designed to decrease dust production and increase ventilation (Kirkhorn and Garry, 2000).

2.3.2.3 Chronic bronchitis

Inhalation of grain dust may cause non-immunologic and immunologic respiratory responses. The influx of neutrophils into alveoli and bronchial walls has been documented, in exposed human subjects and animals, as a result of direct attraction of grain extracts or through stimulation of alveolar macrophages and release of chemotactic factors (Zejda and Dosman, 1993). Chronic bronchitis is characterized by an increased number of goblet cells in the epithelium, enlarged subepithelial glands and increased production of mucus in the airways. The mucus has altered rheologic characteristics and hence, is more viscous (Rylander, 1997).

Macrophage activation can also be mediated by endotoxin present in grain dust. Another substance that has been identified as a biologically active agent is glucan, a component of fungal cell wall. Both endotoxin and glucan are thought to activate local release of arachidonic acid metabolites, hydrolases and toxic oxygen metabolites that are important mediators of neutrophilic inflammation of the respiratory tract. Intensive exposure to organic dusts inside livestock confinement buildings is a risk factor for chronic bronchitis in swine producers (Zejda and Dosman, 1993) but is also associated with years of exposure (Merchant and Donham, 1989). A significant increase in the risk of chronic bronchitis was found for both smoking and non-smoking agricultural workers (Zock et al, 2001). Studies of animal farmers have reported chronic bronchitis in almost one quarter of European farmers. This high exposure for European farmers seems to depend partly on the indoor work that is done by this group of farmers. The clinically proven association between chronic bronchitis and work inside confinement buildings suggests that the high

35 prevalence of chronic bronchitis in European farmers is attributable to work with animals and exposure to high dust levels. Exposure to oil-producing plants also increases the risk of chronic bronchitis (Monso et al, 2003).

2.3.2.4 Asthma

Asthma represents a mixed group of reactions (Rylander, 1986), but can generally be defined as airway hyperresponsiveness to specific immunological, i.e., allergic, or non-specific, nonimmunological agents. The distinguishing feature of asthma is that, in sensitised subjects, very small and often minute doses can elicit asthmatic responses in contrast to the larger doses needed to produce responses by non- immunological mechanisms in either sensitised or non-sensitized subjects (Pepys, 1989). No chest X-ray changes are present. In the acute phase, there is an increased amount of mucus in the airways, disintegration of the surface epithelium and an increased number of eosinophils (Rylander, 1986). It is characterized clinically by episodic cough, dyspnea, and/or wheezing (Michel et al, 1996). Questionnaires are known to be unsatisfactory tools for the diagnosis of occupationally related asthma. Also generally accepted is that a previous history of asthma is not a risk factor for the development of occupational asthma (Gautrin et al, 2001).

There is a reported association of asthmatic symptoms with agricultural exposures to livestock confinement environments (Zejda and Dosman, 1993), and asthma has been found to be common in animal confinement workers (Merchant and Donham, 1989). However, other studies (Kimbell-Dunn et al, 1999) have reported no additional risk or even a lower risk for asthma in farmers. It seems that asthma is more prevalent in adult farmers and lower in farmers’ children. An increased risk of asthma morbidity and mortality in farmers has also been reported (Douwes et al, 2002). Population based studies conducted in farming populations have reported that between 3.0% and 7.7% of farmers suffer from asthma, and as many as 20-30% report symptoms of chest wheezing (Terho, 1990). In poultry farmers in New Zealand the prevalence of asthma was reported as 17% (Kimbell-Dunn et al, 1999). It has been thought that work-related factors were responsible for five to ten per cent of asthma cases. However, a Finnish research study (Karkainen, 2002a) has

36 concluded that work-related factors play a greater role than this. Research conducted between 1986 and 1998 looked at the 50,000 new asthma cases diagnosed in that country in that time period and covered the entire working population aged between 25 and 59 years. The people that were studied were taken from two national registries. It was found that work related factors were blamed in 29 % of the male cases and 17 % of the female cases. The greatest risk occurred for workers in the food production sector, agriculture, painting and metal industries. Asthma was twice as prevalent in these occupational groups as among office workers (Karkainen, 2002a). The high rate in Finnish farmers was attributed to the high concentrations of airborne contaminants that farmers are exposed to when animals are kept indoors over winter (Karjalainen et al, 2000). In a study of people exposed to animal dander 6.7 % developed asthma (Gautrin et al, 2001).

In swine producers, acute lung function changes may be related to the inhalation of endotoxin (Zejda and Dosman, 1993; Donham et al, 1995). Endotoxin has also been shown to increase airway responsiveness in asthmatic subjects (Michel et al, 1996) however Rylander (1997) has disputed this. Michel et al (1996) also suggested that endotoxin is a risk factor for asthma severity and that it is a triggering factor for an increase in the severity of the disease. Endotoxin in house dust is also associated with exacerbations of pre-existing asthma in children and adults (Douwes et al, 2002). Asthmatic symptoms could be further exacerbated by bacteria-induced histamine releases. Thus it appears that inflammatory processes are central in the etiology and pathogenesis of asthma in exposed workers and may explain seasonal variations in non-specific bronchial responsiveness in farmers and in other workers exposed to grain (Zejda and Dosman, 1993). Alternaria spores are considered to be one possible cause of asthma (Sarica et al, 2002). High incidences of certain mould spores more than double the risk of asthma related deaths (Corden and Millington, 2001). Skin sensitization to pets and atopy were found to increase the risk of developing work related asthma (Gautrin et al, 2001). Unlike many other chronic conditions, primarily affecting older persons, asthma disproportionately affects those of a working age (Karjalainen et al, 2000).

In the agriculture industry animal dander has been reported to be the main cause of occupational asthma in Finland since 1982. This trend has declined among farmers since Finland joined the European Union and the prevalence of small farms began to

37 decrease (Karkainen, 2002b). Animal dander can contain animal derived allergens which are considered a major cause of occupational asthma (Gautrin et al, 2001). Animal dander was found to be the primary cause of asthma in 69% of farmers in one study (Karjalainen et al, 2000). The onset of asthma may take no longer than six months after exposure. However in the case of some farmers exposure to irritants has lasted for as long as twenty years before symptoms have appeared (Karkainen, 2002b).

2.3.2.5 Non-allergic asthma syndrome

Non-allergic asthma, often referred to as ‘asthma-like’ or ‘irritant-induced asthma’, is highly prevalent in farmers and farm-related occupations. It is chronic asthma which persists after a single inhalation, usually for a short period of time, of a respiratory irritant in toxic concentrations. Irritant induced asthma may be distinguished from “asthma” by the absence of a latent time period after exposure. Asthma like syndrome develops within a few hours of a clearly identifiable exposure (Newman Taylor, 1999). Non-allergic asthma is normally triggered by exposure to sulphur dioxide, toluene diisocyanate, anhydrous ammonia fumes and smoke. It has also been associated with bioaerosol exposures (particularly endotoxin) (Douwes et al, 2003).

2.3.2.6 Airways inflammation

Airways inflammation is an inflammatory process in the airway epithelium and the underlying mucosa that develops gradually during continuous exposure to endotoxins (Rylander, 1997). In more advanced stages of the disease there may be an impairment of lung function usually measured as the decrease in forced expiratory volume in 1 second (FEV1). Lung function can be impaired over the day (workshift) and the maximum reduction in peak flow appears six to eight hours after exposure (Rylander, 1997). It has been debated whether airways inflammation should be recognized as a disease or limited to a description of symptoms. However, as the condition can lead to a decrease in working capacity, can cause general symptoms

38 and can necessitate medical treatment there is a case to consider it a disease. Endotoxins are a known causative agent for airway inflammation (Rylander, 1997). Dairy farmers and silage workers have significantly lower lung function indices and this means they have lower mean values for FEV (Forced Expiratory Volume) and FVC (Forced Vital Capacity) than the general population (Zejda and Dosman, 1993).

2.3.2.7 Pulmonary function

Pulmonary function baseline values of swine confinement workers are generally within normal limits when compared to standard, non-farming, urban control populations. In a study of 318 farmers certain individuals had clinically significant decrement and the mean decrement in FEV ranged from 1.2 to 3.3%. FEV1 ranged up to 6% and the FEV1/FVC showed a decrement of 3%. Of swine farmers in the

Netherlands 12% had significant decrements in FEV1 and 20% had decrements in flow rates (Donham, 1994). Related to the decrease in FEV1 is the general increase in white blood cells in BAL fluids with predominance of lymphocytes in the chronically exposed and of neutrophils in the acutely exposed (Donham, 1994).

2.3.2.8 Lung fibrosis

“Fibrosis” is a term used to refer to scarring and pulmonary fibrosis means scarring throughout the lungs. Lung fibrosis can be caused by many conditions including chronic inflammatory processes (e.g. sarcoidosis, Wegener’s granulomatosis), infections, environmental agents (e.g. asbestos, silica, dust or exposure to certain gases), exposure to ionizing radiation (such as radiation therapy to treat tumors of the chest), chronic conditions (e.g. lupus, rheumatoid arthritis) and certain medications (Witschi and Last, 1996). After exposure to pathogenic agents the air sacs of the lungs are replaced by fibrotic tissue. When a scar forms the tissue becomes thicker causing an irreversible loss of the tissue’s ability to transfer oxygen into the bloodstream. The symptoms of Lung fibrosis are: shortness of breath, particularly with exertion; chronic dry, hacking cough; fatigue and weakness; discomfort in the

39 chest; loss of appetite; and rapid weight loss. There are currently no effective treatments or a cure for Pulmonary Fibrosis (Pulmonary Fibrosis Foundation, 2005).

In industries involving animal handling, lung fibrosis most commonly occurs when the lung becomes overloaded with low toxicity dust particles. High concentrations of particulates seem to overwhelm the capacity of alveolar macrophages to clear the deposited particles efficiently from the alveolar region. If exposure continues, the retained lung burden increases, hence increasing the chance of disease developing (Oberdorster, 1995). The most common form of lung fibrosis is when a person’s lung is exposed to asbestos and in this form the disease is asbestosis (McCunney and Rountree, 1998). Hypersensitivity pneumonitis is the most common form of the disease in people working in animal handling facilities (MedicineNet.com, 2005).

2.3.3 Other diseases

Animal confinement units have been associated with recently recognised pulmonary conditions such as mucus membrane inflammation syndrome. Mucous membrane inflammation syndrome consists of nasal, eye, and throat symptoms. Nasal symptoms are reported by approximatly 50% and sinusitis by approximately 25% of swine confinement workers (Von Essen and Romberger, 2001). Nasal lavage has demonstrated immunomodulatory effects including increased levels of interleukin- 1α, and interleukin-1β, and interleukin-6. These are the most commonly reported symptoms in people exposed to dusts and gases (Kirkhorn and Garry, 2000).

Byssinosis is an occupational disorder observed most commonly in textile workers and is caused by the exposure and inhalation of cotton, flax, or hemp dust. Vegetable dusts are not associated with byssinosis (Castellan et al, 1987). It is characterised by chest tightness and/or shortness of breath occurring on Monday or the first day of work after time off (Salvaggio et al, 1986). It is thought that byssinosis can occur even below current recommended dust concentrations. The response to cotton dust that causes the byssinosis is related to the concentration of endotoxin in the inhaled dust. It has been shown that there is a correlation between the occurrences of byssinosis related symptoms with exposure to airborne gram- negative bacteria. However the correlation cannot be found with airborne dust

40 (Castellan et al, 1987). Ninety percent of those with byssinosis also tested positive to cotton dust skin test reactions (Salvaggio et al, 1986). There are other disorders related to livestock production and these diseases can range from acute mild conditions that (at least at first) hardly affect daily life to severe chronic disease that require constant specialist care (Douwes et al, 2003) and do not relate to the respiratory system.

2.3.3.1 Zoonoses

Zoonoses is the term that denotes diseases caused by infectious agents common to both animals and man (Murphy, 1992). Some types of zoonoses are caused by direct respiratory contact but many are not (Gurney et al, 1991). There are over 25 known zoonoses that may be transmitted from animals to humans and about one-half of these cause respiratory illness. Professions involving direct contact with livestock - veterinarians, slaughter-house workers, livestock producers – may be exposed to several potentially life-threatening zoonotic diseases including brucellosis, leptospirosis, tularaemia, psittacosis, toxoplasmosis and Q fever. Fortunately, many of these diseases (eg, anthrax and plague) are rare pathogens in Australian and other developed countries and have been controlled through herd vaccinations or eradication. However, in developing countries zoonoses still remain a serious health problem (Gurney et al, 1991).

A zoonotic disease associated with sheep production is hydatid disease associated with hydatid tape worms. These worms cause cysts in the liver, kidney and other organs of sheep, humans, and other animals. The disease is transmitted in Australia through the dog/sheep life cycle with humans becoming a host following ingestion of eggs from an infected dog (Fragar et al, 2001). Sheep are the most important intermediate host normally acquiring infection by grazing on pastures contaminated with infected dog faeces (Heptonstall et al, 1999). Hydatid infection occurs predominantly in the eastern half of NSW along the Great Dividing Range. The mean annual prevalence of hydatidosis in rural NSW is 2.6 cases per 100 000 per head of population (Fragar et al, 2001). If sheep are known to be infected then the carcasses should be properly and rapidly disposed of. A property with an outbreak needs to be quarantined (Heptonstall et al, 1999).

41 Q fever is an other zoonotic disease of concern to people involved in animal production in NSW. It is caused by a small organism, Coxiella burnetii and while most people who contact the disease suffer headaches, fever and debility for only a few weeks a small number of exposed persons can go on to have more serious complications (Fragar et al, 2001). Recovery usually takes 1-2 weeks, though atypical pneumonia can be rapidly progressive leading to respiratory failure. Treatment with tetracycline or doxycycline is effective if given early in the acute infection (Heptonstall et al, 1999). Commonly the mode of transport is airborne in the form of dust particles. Direct contact with infected animals or material is also possible. The occurrence is considered under reported because of the mildness of many cases (Chin, 2000). Heptonstall et al, (1999) suggested that up to half of all acute infections are asymptomatic. It is recommended that all people working in the shearing industry are immunised against Q Fever (Heptonstall et al, 1999).

Orf is another zoonotic disease that can result from exposure to sheep and is a zoonotic skin disease (Heptonstall et al, 1999). It is a viral disease of the skin transmitted to humans by contact with infected sheep and goats. In sheep it causes scabby mouth with ulcers and sores around the muzzle and nostril. In humans it typically causes blister like lesions on the hands, wrist, and sometimes the face (Fragar et al, 2001). Human infection occurs following direct entry of the virus through abraded skin. Diagnosis is usually clinical and recovered patients will have antibodies to the Orf virus (Heptonstall et al, 1999). Shearers are considered to be at a high risk of contracting the disease but figures for NSW shearers are not available (Fragar et al, 2001).

A person may become infected by a zoonosis through direct and/or indirect contact with diseased animals, their manure, urine, bedding or through animal products (meat, milk, hides, hair, etc.). Indirect contact includes soil, plants, and water contaminated by animal waste products. If the disease is transported through the air then it is normally carried by what is called droplet nuclei. The average size is about 3 µm in diameter and when inhaled they are capable of bypassing the protective mechanisms of the body and causing infection. When a contagious person or animal coughs or sneezes sputum, droplets containing infectious particles are released into the air. After release the larger particles fall to the floor and the smaller particles are available for others to inhale. There is no specific number of particles that must to

42 inhaled for a person to become ill and in some cases one particle is enough for a person to become ill (Brickner et al, 2003). Intestinal diseases, respiratory disorders, general feelings of ill health and skin rashes and diseases (dermatoses) are the most common manifestations of zoonotic diseases (Murphy, 1992).

2.3.3.2 Infectious diseases

Infectious diseases are diseases that are caused by contact with microorganisms (Macher, 1999) and they can be spread by viruses, bacteria, fungi, protozoa and worms and involve the transmission of an infectious agent from a reservoir to a susceptible host through, direct contact, airborne transmission or vector-borne transmission (Douwes et al, 2003). Many infectious diseases are not treatable but that does not mean that there is no risk if they are not diagnosed (Heptonstall et al, 1999). There are several diseases that may be spread by the inhalation of fungal spores in the course of handling decaying matter, faeces, compost or soil. These diseases include aspergillosis, histoplasmosis, blastomycosis, coccidioidomycosis, adiaspiromycosis and many others (Douwes et al, 2003). The infectious diseases related to sheep shearing have been discussed in section 2.3.3.1 Zoonoses.

2.3.3.3 Immunodeficiency

Autoimmunity, first described in 1901, has held an interest for many researchers. It is the development of immune system reactivity in the form of autoantibodies and T- cell responses to exposures to foreign particles and biological antigens (Cooper et al, 2002). Autoimmune disorders develop when the automatic immune response mistakenly targets normal body cells and tissues. In an immunodeficiency disease either the immune system develops abnormally or the immune response is blocked in some way (Martini et al, 1998). The symptoms produced depend on the identity of the antigen attacked by these misguided antibodies (Martini et al, 1998). There is limited but growing epidemiological and experimental literature related to the association between autoimmune diseases and occupational exposure to silica, solvents, pesticides and ultraviolet radiation (Cooper et al, 2002). There is the

43 potential in agricultural industries for exposure to silica and pesticides. In relation to autoimmunity diseases farm work has been associated with a small increased risk of rheumatoid arthritis (Olsson et al, 2000) but this is related to pesticide exposure not to direct work with animals. It has also been found that extensive exposure to crystalline silica can cause silicosis - a progressive and ultimately fatal form of fibrotic lung disease. Any relationship between autoimmune disease and occupational exposures is very hard to determine because of a lack of exposure assessment methods and more studies are needed to better define the risks (Cooper et al, 2002).

2.3.3.4 Heart disease

The term “heart disease” covers a wide range of disorders including congenital defects, damaged heart muscle, conditions brought on by a lack of oxygen supply to the heart valves and problems caused through substance abuse (Blitz Editions, 1998). Heart disease is a major contributor to overall mortality in most industrialized countries (Hernberg, 1992). The most prevalent form of heart disease is myocardial infarction (heart attack) and is usually characterised by crushing pain in the chest or arm (Stone, 1996). Heart disease can be related to exposure to certain chemicals including carbon disulfide, organic nitrates and organic solvents. Both heat stress and exposure to cold temperatures have been linked to heart disease (Hernberg, 1992). Ischaemic heart disease mortality was lower in most rural areas of NSW than in the metropolitan area of Sydney in the late 1960’s to early 1970’s. However in the 1990’s it was significantly more elevated in inland small towns and rural areas than in the metropolis but only in males. The reason for this could be an increase in awareness and hence reporting of the disease (Burnley 1998).

2.3.3.5 Rhinitis

Rhinitis is an inflammation of and discharge from the mucous membranes in the nose (Macher, 1999). Occupational rhinitis may be irritative or allergic in nature. Irritation can occur after exposure to a variety of physical or chemical agents.

44 Allergic reactions may result from exposure to high or low weight molecular weight antigens (McCunney and Rountree, 1998). The symptoms may also be caused by a blockage of the nasal passages or sinuses (Macher, 1999). In the sheep shearing industry this is most commonly from exposure to dust mites, fungal spores and animal danders. The initial symptoms of the onset of rhinitis are sneezing and nasal irritation, discharge and congestion, which can begin almost immediately upon contact with potentially harmful dust. Some people exposed to antigens that cause rhinitis also report irritation, tissue swelling and watering of the eyes while others suffer laryngeal and pharyngal symptoms. When a person has rhinitis it is rare that severe pulmonary reactions will occur (Karkainen, 2002a). Rhinitis may also be caused by microbial contamination of the working environment (Sherwood Burge, 1999). Californian farmers were found to have rhinitis rates of 23.9%, and European Farmers rates of 21%. The higher rate in California is attributed to environmental factors. Rhinitis is believed to be primarily caused by exposure to allergens (Donham, 1986).

2.3.3.6 Cancer

Cancer is caused by a variety of factors including oncogenic viruses and other biological agents. The only clearly established non-viral biological occupational carcinogens are the mycotoxins which are outlined in section 2.2.2.5 (Douwes et al, 2003).

Douwes et al, (2003) reported that workers exposed to livestock feed have an increased risk of liver cancer as well as cancers of the biliary tract, salivary gland and multiple myeloma. Farmers as a special group are also at increased risk for specific cancers including haematological cancers, lip, stomach, prostate, connective tissue and brain all of which are believed to be related to specific bioaerosol exposure. Different explanations for this increased risk have been suggested, including that exposure to pesticides or to oncogenic viruses or other biological agents carried by farm animals play a role in disease development. Lung cancer related to exposure to organic dust overload has been found in studies using animals but not humans (Oberdorster, 1995). Nasal carcinogens are possible and the potential is represented

45 by the sum of the biological activities such as mutagenic activity and effects associated with cytotoxicity, inflammation and regenerative cell propagation (Feron et al, 2001). Cancer generally, and liver cancer specifically, among farm workers has been found to be more than three times that in a matched control group but the number of workers exposed was too small to provide statistical significance (Selim et al, 1998).

Leukaemia is a form of cancer that is found in the organs of the body that form white blood cells. This means that it is normally found in the lymphatic system or in the bone marrow inside certain bones (Stacey, 1993). The white blood cells grow without control and without performing their natural functions (Harbert, 1994). In a study of 52,000 American farmers (North Carolina and Iowa), an elevated risk of leukaemia was detected among workers compared with non-workers (Coble 2002). Increased leukaemia risks have been linked to the meat industries (Douwes et al, 2003). The direct contact with animals was determined to be an important factor suggesting that biological exposures are likely to be responsible (Douwes et al, 2003).

Studies have shown a consistent link between lung cancer and abattoir workers and butchers (Douwes et al, 2003) while an increased risk of cancer appears to exist for meatworkers as an occupational group. The main cancer risks include respiratory tract cancer and malignant neoplasm of the lung and larynx (Reif et al, 1989).

2.4 Positive effects of exposure

Several studies investigating farmers’ children have shown that growing up on a farm may protect people against atopy and asthma (Douwes et al, 2003) and the development of childhood allergic diseases (Riedler et al, 2001). It is believed that microbial exposures and in particular endotoxin exposure, early in life may protect the exposed person from developing atopy and allergic asthma. However the mechanisms and reasons for this are not well understood (Douwes et al, 2003). Farm children are exposed to higher inhaled concentrations of endotoxin in their normal living environment, including dust in kitchens and mattresses, than non-farming

46 children (Riedler et al, 2001). Farm children will sometimes drink farm or raw milk which contains more gram-positive bacteria than pasteurised milk (Riedler et al, 2001). It has been found that the timing of exposure to farm characteristics, in or before the first year of life, and the amount and duration of exposure from the first to the fifth years of life are crucial for this protective effect (Riedler et al, 2001). Sensitisation may start in pregnancy or be a maternal factor passed from the mother that could contribute to an infant’s protection (Riedler et al, 2001). In studies with rats it has been shown that one exposure to lipopolysaccharide, up to 4 days after sensitisation, can protect against bronchial hyperresponsiveness, and inflammation in bronchoalveolar lavage fluid. After 4 days of sensitisation this inhalation had detrimental effects and lead to an increase in allergic responses (Riedler et al, 2001). The evidence for this protective effect of endotoxin has mostly been proven only for in-vitro studies (Douwes et al, 2002).

Respiratory symptoms including non-allergic asthma are generally more prevalent in working populations exposed to high levels of microorganisms and endotoxins. In spite of this some studies indicate that atopy is less prevalent, consequently suggesting that exposure may protect from atopy and atopic symptoms also in the working population (Douwes et al, 2003). There is reason to be concerned that, although endotoxin exposure may protect against the development of atopy, at most only 50% of asthma cases appear to be attributable to mechanisms involving atopy (Douwes et al, 2002). It has been suggested that endotoxin exposure, mostly from organic dusts, results in reduced lung cancer rates. This reduced lung cancer rate was first identified in textile workers and later in agricultural and other groups exposed to endotoxin (Lange, 2003). When considering any of these possible positive effects of endotoxin it is also important to remember than endotoxin exposure is related to causing and exasperating many diseases including asthma (Douwes et al, 2002).

2.5 Assessment of Airborne Contaminants

Risk assessments for all potentially dangerous activities are a legislative requirement in NSW but are considered to be seriously hampered by the lack of valid quantitative exposure assessment methods (Douwes et al, 2003). There are recognised dust

47 sampling methods used in Australia but for bioaerosols different measurement processes will give different results and there are no accepted standard methods against which to compare the different possible techniques that can be used (Hopke, 2003). There are no generally accepted standard methods and sampling procedures which are suitable for measuring bioaerosols or endotoxins in animal houses (Reed et al, 2006).

2.5.1 Dust Monitoring

The majority of dust monitoring in Australia has been undertaken to characterise exposures inside enclosed livestock facilities using area/static sampling. The data may be limited in determining health risks, as they do not sample actual exposures, but they are useful to get an idea of dust concentrations in the area. Air sampling in the breathing zone is the appropriate method for individual exposures, taking into account the effects of different tasks and locations over time (Merchant and Reynolds, 2000). In general personal dust exposure measurements are higher than measurements collected by area sampling (Kullman et al, 1998). The sampling period may consist of the whole work shift or may be limited to shorter time periods reflecting the duration of specific tasks (Merchant and Reynolds, 2000). Short sampling times can be used in cases where the activity is of a short duration (Nieuwenhuijsen et al, 1998). Parameters that have been most commonly measured include dust, gases and chemicals such as pesticides and in recent years, microorganisms and endotoxins (Merchant and Reynolds, 2000).

As outlined in section 2.2 on airborne contaminants there are many different types of dusts depending on size selection. This project is aimed at measuring the concentrations of two size fractions of dusts, respirable and inspirable (inhalable). Finding the concentration for either is a two-stage process: (a) sampling for respirable or inspirable dust using a size-selective monitoring device, and (b) analysing the sample gravimetrically (by weight) or chemically (for a specific analyse) (Tranter, 1999).

48 Dust is collected on pre-weighed non-hygroscopic filters using personal or static (area) sampling pumps at flow rates of approximately 2 L min-1 (NIOSH, 1994). Sampling for both types of dusts follows the same principles. An airborne sample of a known substance is collected in the breathing zone using a size-selective sampling device that is connected to a sampling pump. The method for monitoring respirable dusts in Australia is described in Australian Standard AS2985 (Standards Australia, 2004a). Australian Standard AS3640 (Standards Australia, 2004b) describes the technique for sampling and gravimetric analysis of inspirable dust. In both cases change in mass is determined gravimetrically and the airborne mass concentrations then calculated (Merchant and Reynolds, 2000). Gravimetric measurements have traditionally involved the movement of air through a filter resulting in matter being trapped on the filter. Filters used include Polyvinyl Chloride (PVC), Teflon, glass fibre, and polycarbonate (Merchant and Reynolds, 2000). Teflon filters are more stable for analysis than glass fibre filters (Paik and Vincent, 2002). The PVC filters are the standard filter prescribed by many dust sampling standards (Chun et al, 1999). A minimum of two sampling blanks per sampling time are recommended by NIOSH method 0500 (NIOSH, 1994) however to lower the chance of variation the use of several blanks is recommended (Paik and Vincent, 2002). The sampler that the filter is placed in is designed so that a particular fraction of the particle size distribution is separated aerodynamically from the ambient aerosol and trapped on the filter (Hopke, 2003). There are many different brands of respirable and inspirable sampler available. The SKC respirable cyclone sampler is based on the Higgins- Dewell design and is intended to approximate the accepted dust definition of BMRC (British Medical Research Council) when run at a flow rate of 1.9 L min-1 (Groves et al, 1994). Both the IOM and 7-hole sampler, meet the ACGIH sampling criteria for inhalable particulate mass (SKC, 2007) when run at a sampling rate of 2 L min-1. Other studies have shown that using different respirable sampling heads will give different results under the same conditions. A study by Groves et al (1994) showed that when comparing the SKC, BGI and Sensidyne cyclones the SKC cyclones yielded the highest respirable dust concentrations and this was for all tests carried out. When inspirable sampling heads have been performance tested against one another, the results have been comparable (Linden et al, 2000; Marley, 1994; Vaughan et al, 1990).

49 A real-time aerosol monitor such as a DustTrak is an analyser used to measure concentrations of particulate matter using light scattering technology. Niu et al, (2002) reported that the detection range is from 0.001 to 100 mg m-3 and the resolution is 1% of the reading. To sample, air is continually pulled through the sample inlet, set at a specific dust fraction, into an internal chamber. In the internal chamber a laser light is used to scatter light in all directions. Some of the scattered light is collected and then converted into a voltage. Under this method the mass concentration of particulate matter is proportional to the amount of light scattered and the voltage generated. The actual reading of mass concentration can be calculated once the voltage is multiplied by an internal calibration factor. Using continuous monitoring a logging interval can be selected so that the data recorded is an average of the values collected over that interval during the monitoring period. In the study conducted by Niu et al, 2002, the monitoring results from a real-time monitor were approximately twice as high as results obtained using an integrated sampling device. It was suggested from that study that real-time analysis should only be used for preliminary screening.

Dust sampling is generally available and a relatively cheap marker for exposure to agricultural airborne contaminants though it has been suggested that dust exposure alone is insufficient as a predictor for the possibility of lung function decline in farmers (Vogelzang et al, 1998). Measuring only total dust concentration for exposure to agricultural dust might not always correlate well with the incidence of the specific respiratory disease (Buchan et al, 2002).

2.5.2 Bioaerosol Monitoring

Bioaerosols can be monitored by using different methods (CEN, 2000). It can be argued that viable microorganisms produce more allergens and toxins after deposition in the respiratory system and may induce stronger responses than nonviable microorganisms (Eduard and Heederik, 1998). In some studies the Petri plate gravitational method has been used. This method allows gravity to settle particles out of the air onto different agar plates, is relatively cheap, but is not an accurate method for finding an approximation as to how much is being inhaled by

50 workers (Sarica et al, 2002). Studies have shown that this method produces results that are so inaccurate that they are neither qualitatively nor quantitatively comparable to the results obtained by other sampling methods (Pillai and Ricke, 2002).

A different method involves dust collection on a filter followed by extraction, staining with acridine orange dye, refiltering on a black filter and counting with fluorescence microscopy (FM). This allows direct characterization of how airborne microorganisms appear (Karlsson and Malmberg, 1989). The advantage of this method is that total spore counts can appear up to 6 times higher than the number of cfu in cultural methods. It also allows measurement of the size and aggregation tendency of microbes (Karlsson and Malmberg, 1989). A downside is that it is not possible to distinguish between actinomycetes and other bacteria and some bacteria cannot be seen by this staining method (Karlsson and Malmberg, 1989). Another problem is that human error can limit the use of this technique as a collection tool (Pillai and Ricke, 2002).

Filtration-based sampling is another possibility. This method involves the biological particles being collected when the stream of air flows through a porous material, often a membrane filter (Pillai and Ricke, 2002). When using filtration the pore size used is important with a pore size of 5 µm collecting 0.3 µm particles with an efficiency of 95% or better (Eduard and Heederik, 1998). Electrostatic precipitation is a method that allows “gentle” collection. During this collection the airborne particles become electrically charged which causes them to drift and be deposited onto a suitable collection media (Pillai and Ricke, 2002). Several handheld air samplers exist but most are made for collection in low concentration areas and are therefore impractical in farming environments (Eduard and Heederik, 1998).

Other methods are microbial cascade impactors (Andersen microbial samplers) with selective media or all-glass impingers (Merchant and Reynolds, 2000). These are both examples of the inertial collection method. The impaction method separates particles from the airstream by utilizing the inertia of particles to force their deposition onto a surface media (Pillai and Ricke, 2002). This technique allows microbes to be collected by either impacting onto a surface or impinging into a liquid. The liquid or surface media must be especially suitable for this type of

51 collection. It is usually agar with nutrients that will ensure the viability of the microbes for incubation and counting (Tranter, 1999).

The main difference between impaction and impingement is the way the bioaerosols are collected. Impingers collect their bioaerosols into a liquid. Often, the liquid is a buffer that is designed to maintain the viability of the microbial cells (Pillai and Ricke, 2002). The multistage impactors allow fractioning according to the aerodynamic size of the particles (Karlsson and Malmberg, 1989). Meaningful exposure estimates, by using area or environmental samplers, can only be ensured by the generation of data that are both precise and accurate.

The Andersen six-stage viable (microbial) particle sizing sampler (6-STG) and the Ace Glass all-glass impinger-30 (AGI-30) have been suggested as the samplers of choice for the collection of viable microorganisms by the International Aerobiology Symposium and the ACGIH (Jensen et al, 2001). The bioaerosol sampling parameters used to evaluate environmental fungi and bacteria are total concentrations and particle-size distribution (Pasanen 1989). These parameters decide the environment that the bioaerosol can be sampled from and also the laboratory environment that the bioaerosol can be grown in. At present there is not a generally accepted standard sampling method (Seedorf et al, 1998).

The Andersen two-stage viable (microbial) particle sampler (2-STG) has been developed for monitoring bioaerosols. It is a multi-orifice, cascade impactor with 400 holes per stage, drawing air at a flow rate of 28.3 L min-1 (Jensen et al, 2001). This sampling rate is comparative to the breathing rate of a person going about their normal work. However worker respiration rates will rise with increased metabolic rate. In women respiration rates are lower (Collins, 2003). The different stages separate the airborne particles in size fractions. The stages have 50% cut-off diameters of 0.6 to 7 µm (depending on the orifice used) and the impaction holes are arranged in a regular pattern that facilitates counting of colonies (Eduard and Heederik, 1998). As the air velocity increases across the different impacting surfaces the smaller particles get deposited resulting in the upper stages collecting the larger particles while the lower stages collect the smaller particles (Pillai and Ricke, 2002). The organisms get deposited because the air is forced to make a 90 degree turn to pass around the edge of the plate. This allows the smaller particles to pass around the

52 growth medium while the larger particles cannot make the turn and impact on the surface (Collins, 2003). Dividing bioaerosols into size categories is important for epidemiological research (Bartley et al, 1994). Investigators aim for sampling times that are: (a) sufficiently long to collect a detectable and representative number of particles or other amount of material, but (b) short enough to avoid masking or overcrowding (i.e., the overlap of particles on microscope specimens or the contact of colonies on culture media).

The density of colonies growing on a culture plate affects the reliability of the information that can be obtained. Too few colonies may inaccurately reflect what is present whereas too many colonies are difficult to count and examine. However, this is a good way of finding a quantitative measure of viable bacteria (Krahmer et al, 1998). It is important to anticipate bioaerosol concentrations correctly and to collect samples that will yield an appropriate colony surface density (Macher, 1999). A large variation in spore concentrations has been observed in air samples regardless of the sampling and counting methods (Hanhela et al, 1995). The variation in spore concentration can be up to 400 times depending on the day (Baruah, 1961). In an early study (Kotimaa 1987) a six-stage Andersen bioaerosol sampler was used for sampling for the time periods, 5 to 30 seconds, depending on the visible mouldiness of the stored material. In this study the samples were taken as near to the farmer’s breathing zone as possible to estimate the actual exposure levels. In a study carried out in a pig shed the air was sampled for 5 minutes using an Anderson 6-stage sampler set at a flow rate of 1.9 L min-1 (Banhazi et al, 2002) which is not considered the optimum flow rate for this sampler (Reed et al, 2006).

Area sampling should always be carried out near the potential sources of bioaerosols such as air supply systems, machinery and at or near the workers’ position (Attwood, 1985). An Indian study used an Andersen sampler for three minutes in a study of feedlot cattle (Adhikari et al, 2004). Duplicate samples in time and place must always be taken (Attwood, 1985). A further study also developed and used a sampling method with the 2-STG for the Australian deer industry (Kift et al, 2002a; Kift et al, 2002b). This method was modified from the NIOSH method 0800 (NIOSH, 1998), which had been adopted as a standard method for indoor air

53 sampling in the America by NIOSH. A similar method using a 2-Stage sampler was applied in an American study by Gibbs et al (2004) in the swine industry. This study sampled for 30 seconds, 1 minute and 2 minutes inside the shed while it contained animals.

The Andersen microbial sampler is easily overwhelmed at high bioaerosol concentrations associated with enclosed livestock buildings, silo unloading and other operations (Merchant and Reynolds, 2000) making analysis and interpretation difficult. The use of impaction and impingement has been criticized because of the short sampling times, a risk of overloaded agar plates and a consequent large variability in concentrations between samples (Hanhela et al, 1995). The size separation of the particles is not sharp which can lead to smaller particles being deposited on the upper stages and yielding non-representative colonies for a particular particle size (Eduard and Heederik, 1998). The counting of particles can also cause a problem when the impaction patterns become distorted (Eduard and Heederik, 1998). It has been found that methods using dilution plating have higher yields than methods using directly cultured plates (Eduard and Heederik, 1998).

Sampling at field sites and transporting samples several hours or overnight to a laboratory can give organisms the opportunity to multiply or die in transit (Lin and Li, 2003). This is more of a problem when using impingement rather than impaction. Colony forming units (cfu) concentrations for impinger samples have been shown to decrease as storage time increased regardless of whether or not the samples were refrigerated (Lin and Li, 2003). Storage time also affects dissimilar organisms differently. Penicillium spores decreased as they were stored whereas yeast cells have been shown to survive and bud more cells while stored (Lin and Li, 2003). Delays in plating after sampling have been shown not to affect the viable concentration of bacteria but it does decrease viable yeast concentrations (Thorne et al, 1994). In using this impaction method the collected media can also be washed with a suitable buffer and the solution subsequently analysed but the collection effectiveness of this method is not 100% (Pillai and Ricke, 2002).

54 2.5.2.1 Media used in sampling bioaerosols

Two different sampling media can be used in the 2-STG Andersen bioaerosol sampler at the same time. It is important that the media selected is suitable for contaminant/s it is required to collect. The most important consideration in deciding on the types of counting media used lies between those suitable for high water activity environments and those suitable for low water activity environments. For media to sample for fungi, another consideration lies in whether the primary interest is in moulds, yeasts or both. Consideration should also be given to the presence or absence of preservatives (Pitt and Hocking, 1985). To be an effective general purpose enumeration medium for the sampling of fungi, the media must fulfil several requirements.

These are: • to inhibit the growth of bacteria; • to strongly inhibit the growth of rapidly spreading fungi, especially the Mucorales but not to prevent their growth entirely; • to induce compact colony development in all fungi so that a reasonable number of colonies can be distinguished on a plate (Pitt and Hocking, 1985).

Fulfilling the above requirements necessitates the use of potent inhibitory compound and there is sometimes a fine line between inhibition of undesirable organisms and the suppression of growth of those being sought (Pitt and Hocking, 1985).

The simplest enumeration and growth medium for most environmental yeasts is Malt Extract Agar (MEA). Although originally introduced as a growth medium for moulds its rich nutritional status makes it very suitable for yeasts and its relatively low pH (usually near 5.0) reduces problems with bacteria contamination. Plates are normally incubated at 25oC for 3 days (Pitt and Hocking, 1985) but can be incubated for up to 7 days (Power and McCuen, 1988). MEA has been used as a collection and culture medium in past bioaerosol studies (Pasanen et al, 1989). No significant difference in the performance of MEA, Dichloran Glycerol and Dichloran Rose Bengal (RBS) agars has been found (Mishra et al, 1992). It has been suggested that RBS agar is the most suitable for sampling fungi from air as it is a broad spectrum agar that is good

55 for aeromycological sampling (Sarica et al, 2002). One problem with MEA is that it favours the detection of xerophilic fungal contaminants and hydrophilic fungal contaminants do not grow well. This is because the agar favours growth of fungi with a water activity of 0.6-0.8 (Collins, 2003).

Nutrient Agar (NA) is used for the cultivation of bacteria and is capable of growing a broad spectrum of microbes. The NA plates are normally incubated for 2 days at 35oC (Power and McCuen, 1988).

In an early bioaerosol study, Dutkiewicz (1978) looked at the concentration of viable bacteria and actinomycetes in air sampled on Blood Agar and NA plates. The plates were subsequently incubated at 37oC (1 day), 22oC (3 days), and 4oC (3 days). This prolonged incubation at lower temperatures was introduced for enabling the growth of some mesophilic and psychrophilic species. In this same study air sampling for the estimation of fungi was carried out using Sabouraud Agar plates which were subsequently incubated at 30oC (4 days) and 22oC (4 days). In some cases Czapek- Dox Agar and Malt Agar were used for isolation (Dutkiewicz 1978). Other media that can be used are Plate-Count-Agar for total bacteria (Sevi et al, 2002; Krahmer et al, 1998; Seedorf et al, 1998;), Violet-Red-Bile-Agar for gram-negative bacteria (Sevi et al, 2002; Seedorf et al, 1998), Sabouraud-Agar for total fungi (Sevi et al, 2002; Wilson et al, 2002; Seedorf et al, 1998), Tryptic Soy Agar (TSA) (Krahmer et al, 1998) or Sheep Blood Agar for aerobic bacteria (Banhazi et al, 2002; Wilson et al, 2002).

Counting of culturable microorganisms has some serious drawbacks including poor reproducibility, selection for certain species due to chosen culture media and incubation temperature etc. and the fact that dead microorganisms, cell debris and microbial components are not detected as these components may have allergic or toxic properties (Douwes et al, 2003). These possible variations must be considered when the results are interpreted (Attwood, 1985).

56

2.5.3 Endotoxin

Previous results suggest that measuring concentrations of endotoxin in air is a much more reliable means of assessing the risk of an acute airway response to airborne contaminants than measuring the mass concentration of dust (Castellan et al, 1987). In principle it should be possible to quantify the load of gram-negative bacteria via the concentration of endotoxin and vice versa. In reality there has been no significant correlation between the concentrations of Gram-negative bacteria and aerial endotoxin (Seedorf et al, 1998). There is no accepted and standardized method for analysis of endotoxin from environmental samples in America (Buchan et al, 2002). However a European method (CEN, 2003) has been published.

The common method for endotoxin detection is the limulus (Limulaus Amoebocyte Lysate (LAL)) method (Rylander, 1997). The lysate prepared from the amebocytes of Limulus blood was found to be a delicate and sensitive indicator for endotoxin (White and Ashley, 2002). The LAL test is a comparative method providing an estimate of relative biological activity of LPS rather than a measure of the exact amount of the substance present (Eduard and Heederik, 1998). The assay measures LPS potency, which is dependent on variables such as the fatty acid content of the Lipid A portion, polysaccharide content and LPS aggregation properties (White and Ashley, 2002). It is suggested that this method detects only about a third of biologically active endotoxin and that the remainder is present inside fragments of dust particles/bacterial cells but still able to exert effects when deposited in the lung (Rylander, 1997). Some sampling techniques produce results that are generally below the detection limit of some assays used (0.6 pg m-3) (Beijer et al, 2003). There is also a possible problem with an enhancement phenomena and this may lead to discrepancies in airborne endotoxin data. This can come from false positives owing to cross-reactions of (13)-
-D-glucan with endotoxin in the LAL assay (White and Ashley, 2002).

The standard guidelines developed by Rylander (1997), were based on an analytic procedure where glass fibre filters with airborne dust samples are extracted for 15 minutes to one hour in pyrogen-free water (with or without 0.05% Tween-20

57 solution) and centrifuged for 10 minutes at a force of 1000 G’s. Other studies have found that glass fibre filters yield slightly, but not significantly higher, endotoxin biological activity than polycarbonate filters with cellulose acetate filters showing the lowest recovery of activity (Reynolds et al, 2002).

The methods used for the analysis of endotoxin in environmental samples vary from laboratory to laboratory. Laboratories that use proprietary methods yield fairly consistent data on an intra-laboratory basis however there may not be a basis for comparison with laboratories that use other methods. Variations in analytical techniques and between operator can significantly influence the data that is produced (White and Ashley, 2002). Results are often reported in different units of measurement, making comparison difficult. Studies report in either nanograms per cubic meter (ng m-3) or endotoxin units per cubic meter (EU m-3). There are conversion factors to relate the two units together but they are not the same thing (Reynolds et al, 2002).

2.5.4 Alternative sampling methods

At this stage of technological development, in relation to aerosol sampling, many chemical markers and components can still not be sampled for. This is expected to change over time, so that more than just dust concentrations can be recorded (Krahmer et al, 1998).

Instead of counting culturable or non-culturable colonies, constituents or metabolites of microorganisms can be measured as an estimate of microbial exposure. Toxic (eg mycotoxins) or pro-inflammatory (eg endotoxin) components can be measured. Endotoxin is measured by using a Limulaus Amoebocyte Lysate (LAL) test. Analytical chemistry methods for quantification of LPS have also been developed employing GC-MS (Seedorf et al, 1998). It should be noted that most of the methods to measure microbial constituents are in an experimental phase and have as yet not been routinely applied and/or are not commercially available (Douwes et al, 2003). The advantages of sampling for microbial constituents is that they may be present in the environment in an easily measurable form, and can be measured with longer

58 sampling times, often using well-established environmental and personal dust sampling methods (Eduard and Heederik, 1998).

Antibody-based immunoassays, particularly enzyme-linked immunosorbent assays (ELISA) are widely used for the measurement of aeroallergens and allergens in settled dust in buildings (Douwes et al, 2003). However, the sampling methods used are not yet practical for use as environmental air sampling methods at this time.

Nasal lavage (NAL) is a tool which has been used to assess work-related airway inflammatory responses in the nasal epithelium of occupational groups with microbial exposure (Douwes et al, 2000). The NAL testing can be used to look for either different cell types or specific biomarkers (Walinder et al, 2001). This is a measurement tool that is dependant on worker involvement and does not provide environmental readings.

2.5.5 Identification of bioaerosols

Fungi should always be examined microscopically as wet mounts rather than fixed and stained like bacteria (Pitt and Hocking, 1985). Fungal colonies can be classified by their morphological appearance and eventually identified by their characteristics in culture, organoleptic appearance, and micro-morphology observed with a light microscope (Eduard and Heederik, 1998). When identifying fungi, it is not possible to go beyond genus level using spore morphology alone (Adhikari et al, 2004).

Bacteria can be identified by morphology, gram-staining, growth on specific substances and under special conditions, and production of specific metabolites (Eduard and Heederik, 1998). After gram staining of bacteria, a study by Krahmer et al (1998) divided the results into four categories as: actinomycetes, gram positive rods, gram negative rods, and gram positive cocci. Bacteria was identified by Wilson et al (2002) using Becton Dickinson Micro Systems bacterial identification kits.

59 2.5.6 Sampling Statistics

Deciding how many samples to collect remains a difficult issue in any monitoring strategy. The number of samples collected will influence the precision of the exposure estimate and the associated confidence limits (Grantham, 2001). Monitoring agricultural working environments can be difficult and time consuming, which can lead to a small number of samples being collected (Nieuwenhuijsen et al, 1998). When deciding how many samples need to be collected, calculation of confidence limits needs to be carried out. In most situations a 90% confidence limit is acceptable. This means that a sampling estimate with a 90% confidence limit is not more than 10% in error of the true mean (Dewell, 1989).

For this project 95% confidence was applied and the top 10% of possible exposures was used to interpret data as opposed to the top 20%. Both of these estimates gave the recorded data better accuracy and reliability to reflect potential exposures. According to the tables reported by Dewell (1989), for occupational hygiene sampling, if there are more than 50 farms and farm workers in NSW, the minimum number of farms that need to be sampled to comply with the confidence levels applied is 22. Leidel (1977) advised that the minimum number that needs to be sampled, if there are more than 50 farms or workers, is 29. This higher sample size is for the top 10% of exposures, with a confidence limit of 0.95, and is the sample size adopted for this study. This sampling number will enable the results to be compared to the current recommended standards with 95% confidence.

It is advised that the worker who is considered at the maximum risk from a group of workers with a similar potential exposure risk should be sampled (Leidel et al, 1977). This will enable the greatest potential exposure to be found. Sometimes it is not possible to know who the maximum risk worker is and therefore the exposure of a greater number of workers needs to be sampled. This needs to be done in such a way so that the results will be representative of the overall exposures (Attwood, 1985).

The results of previous monitoring may give an indication of the need for repetition. If first exposures were found to be well below the exposure standard by a significant amount, (Table 2.5.1) then repetition is not needed. If however, the results were found to be close to or greater than the recommended standard, then immediate

60 repetition is needed. Control measures should also be immediately looked at (Grantham, 2001).

Table 2.5.1 Recommended frequency of repeat monitoring based on previously recorded exposures compared with recommended exposure guidelines (adapted from Grantham, 2001)

Measured exposure/s divided by Number of shifts required to be recommended exposure standards monitored per 10 workers exposed 1 - 2 1 per month 0.5 - 1 or 2 - 4 1 per quarter 0.1 - 0.5 or 4 - 20 1 per year <0.1 or >20 No repeat monitoring needed

2.6 Sampling variables that impact on airborne contaminants

There are many variables that can have an effect on the concentration of airborne contaminants in an animal handling facility. Some may increase the dust and/or bioaerosol concentrations while other variables may decrease the dust and/or bioaerosol concentrations. All variables should be considered when evaluating the results of airborne contaminant monitoring. The variables considered to be of major concern are: • Season of the Year; • Temperature at the time of monitoring; • The concentration of contaminants outside the building • Flooring type • Ventilation rates in the building; • Animal diet and living area • Number, activity and species of animals; and • Sampling collection methods.

61 2.6.1 Season

Seasonal variation with both temperature and relative humidity changes can influence bioaerosol growth with moist conditions assisting bacterial growth (Tortora et al, 1998). In seasons where the temperature and relative humidity are high more fungal spores will germinate (Adhikari et al, 2004). A moist environment can be provided by natural rainwater or water used to reduce airborne dust in animal handling facilities. Studies have shown that fungal spores are more likely to be released into the air during times of high relative humidity (Pillai and Ricke, 2002). In a Canadian study the maximum number of bioaerosols occurred during winter and early spring. The factors that influenced this growth pattern were the increasing temperature, decreasing humidity and increasing solar irradiance (Pillai and Ricke, 2002). In comparison a Danish Study reported the highest bioaerosol concentrations occurred during summer (Blom et al, 1984). A study conducted in India had the highest total spore and cfu concentration levels during winter and the late spring rainy season (Adhikari et al, 2004). The rainy season in India is known to have very high relative humidity. Dry conditions are considered better for dust generation in cattle feedlots (Wilson et al, 2002). An American study (Purdy et al, 2004) found higher bioaerosol concentrations for all types of bacteria and fungi during the summer months. Damp flooring materials bind settled dust on to the floor which reduces the likelihood of it becoming airborne after animal activity (Takai et al, 1998). A United Kingdom study found that the highest average concentrations of Alternaria spores occurred at the end of winter and the highest peaks occurred during dry weather conditions (Corden and Millington, 2001). The finding of higher concentrations in dry conditions also depends on occasional rainfall which causes higher average monthly bioaerosol concentrations than if the month was totally dry (Corden and Millington, 2001). Season plays a role in the amount of dust produced but can only influence dust and bioaerosol concentrations in conjunction with humidity and rainfall.

62 2.6.2 Indoor temperature

The optimum growing temperature for both bacteria and fungi is in the range of 10 to 60oC (Tortora et al, 1998). Depending on the region in Australia these temperatures are common in spring, summer and autumn indicating that more growth is likely to occur in summer than in winter. Temperature can change airborne fungal spore concentrations with the concentration of microorganisms found to be directly proportional to the atmospheric temperature (Sarica et al, 2002). Mean temperature and relative humidity were also significant predictors of endotoxin (Carty et al, 2003) with increased indoor humidity shown to create better conditions for microorganism growth (Beijer et al, 2003). In seasons with high temperature and relative humidity more fungal spores will germinate (Adhikari et al, 2004). Wool grown on sheep kept in areas of high rainfall is more likely to be heavily contaminated with bacteria and fungi than wool from sheep kept in arid areas (Jacobs, 1994).

2.6.3. Outside concentrations of airborne contaminants

When there are differences in internal and external temperatures bioaerosol particles will generally move down the thermal gradients present from warmer to cooler areas (Pillai and Ricke, 2002). This means that if a building is cooler inside than outside, bioaerosol particles are likely to move into the building. Outdoor dust concentrations can be a health problem in many areas (Jalaludin and Morgan, 2003). Outdoor dust and bioaerosol concentrations can influence the indoor levels of airborne contaminants (Adhikari et al, 2004). To overcome this problem, and for comparison, outdoor air should be sampled away from obvious sources of bioaerosols (Adhikari et al, 2004). Normally there is a good correlation between the indoor and outdoor concentrations and the types of bacteria and fungi present (Mishra et al, 1992). Depending on the available possible entry routes only very small numbers of spores may be able to enter the building from the outside (Corden and Millington, 2001). The type of building will determine the effect that ambient air temperature has on the concentrations of dust with fully enclosed buildings being less affected by outside changes in temperature (Takai et al, 1999). Stock movement around the outside yards and paddocks associated with a livestock holding facility, such as a shearing shed, is

63 an example of how these concentrations can rapidly increase in dry weather conditions (Kift et al, 2005).

2.6.4 Type of flooring in animal shed

The type of flooring that can be used in animal handling sheds is a very important variable, as certain floor types are more likely to release dust than others. Sand, sawdust and other soft coverings will release more dust than hard flooring such as concrete (Langridge, 1992). When evaluated the softer flooring types have been found to release more dust than harder flooring types. If the flooring material in the animal handling shed is sand, sawdust or clay then it is more likely to be dusty in summer (Langridge, 1992) and the dust is more easily generated. As flooring is compacted the amount of dust generated decreases (Kaliste et al, 2003). Flooring has been shown to be the predominant characteristic explaining variation in endotoxin exposure in animal handling buildings (Preller et al, 1995).

People have previously sprayed liquids such as diesel fuel or cooking oils over floors of animal handling sheds in an attempt to reduce the amount of dust produced. These products themselves can have an impact on health of the people working in the animal handling shed. If the flooring material is wet then settled dust will bind onto the floor and may not become airborne after animal activity. This lack of flight availability is due to a high equilibrium moisture content (Takai et al, 1998). However spraying water can have a negative effect by providing better conditions for the growth of bacteria or fungi. Bacterial endospores are formed so that bacterial cells can survive adverse environmental conditions and fungi spores are a natural way for fungi to reproduce (Tortora et al, 1998). Temperature and water availability will also affect the release of both types of spores (Jones and Harrison, 2004). In both cases the release of spores can quickly increase the number of microorganisms present. If the flooring of an animal handling shed is wetted down a day in advance of use to settle the dust, which is commonly done, the moisture in the flooring could encourage the release of spores therefore altering the airborne concentration of microorganisms in the shed. The different flooring type and the preparation that occurs before the shed is used can affect the results for different animal handling

64 sheds and this needs to be considered when analysing the data from an air- monitoring program.

2.6.5 Ventilation rates

Unfortunately for workers air quality is almost inevitably compromised once animals are brought into a building. The most effective measure for preventing occupational respiratory diseases associated with microorganisms is the reduction of dust by effective ventilation systems (Dutkiewiz, 1997; Merchant and Donham, 1989). The design and operation of a ventilation system can play an important role in determining air quality in animal handling buildings.

The three mechanisms by which ventilation may impact on health and the growth of both humans and animals are aerial spread of pathogens and pheromones, regulation of thermal exchanges and maintenance of air quality (Wathes, 1992). Airflow through an animal house can be driven by either natural or mechanical means (Wathes, 1992). In many cases natural ventilation is used as it is the most cost effective (Mathews and Arndt, 2003). It has been shown that the concentration of gases and dust concentrations fall rapidly with higher ventilation rates (Wathes, 1992) and adequate ventilation has been shown to reduce fungi levels by up to nine times (Summerbell et al, 1994). It has also been shown that the lower the ventilation rate inside an animal handling shed the more likely a microbe will be able to grow undisturbed in one place (Tortora et al, 1998).

A major flaw in the design and operation of ventilation systems in livestock (and other) buildings arises from the assumption of perfect mixing of incoming and ambient air. Other problems may be experienced in the distribution of sources of heat, pollutants and other atmospheric constituents that may cause the clean air to not reach all parts of the enclosed area (Wathes, 1992). Ventilation rates in the cooler months are slower to conserve heat. The net result is poorer air quality as the mixing with fresh air is not as regular, and this can lead to especially high concentrations of ammonia and airborne dust (Hartung, 1994). Another problem with dilution ventilation is that the system is designed to maintain a predetermined temperature in the building with little regard to other conditions (Randall and Boon, 1994).

65 Variation in outdoor climatic conditions show higher dust concentrations with lower outdoor temperatures and this was due to reduced ventilation rates (Preller et al, 1995). This means that when the outside temperature is cold, ventilation is reduced and dust concentrations increased. Fortunately this is changing as people become more aware of the other roles that ventilation systems play.

Maintenance of ventilation equipment is essential for the proper function of fans, filters and air-ducts. In agriculture these components of the ventilation system are often not properly cleaned or maintained (Jacobs and Donham, 1994). Another ventilation variable that must be considered is the rate at which ventilation takes place. In sheds using natural ventilation and extraction fans the ventilation rate can vary. This may be because the wind outside is changing between sampling periods and the volume to be extracted can vary. If the ventilation rate is different for the same farm, at different sampling times, then this can affect both dust and bioaerosol concentrations recorded. The ventilation rate should then be considered when the results are being examined.

2.6.6 Animal diet and living area (grasses and soil type)

The surrounding grasses/crops to which animals are exposed to can impact on the types of dusts that an animal will generate. Different fungi and bacteria are generated from different plants (Miller, 1995) and fungi, bacteria, dust and endotoxin concentrations are affected by the type of crop that is present (Olenchock et al, 1990). Some plants have different growth pattens which means pollen may be released at different times of the year (Carty et al, 2003). If the animals are kept in a paddock with different grasses to another paddock then the pollen and dust that the animals are in contact with will vary. In addition the type of crop grown and plant variety may also contribute to different dust toxicities (Jacobs, 1994). The exposure levels vary considerably depending on: local growth of microorganisms in different batches of a variety of organic materials and the amount of agitation of the material during handling (Larsson et al, 1988). If harvesting of crops is delayed then continued weathering of the crop increases the friability of the dried plant structures which then increases the amount of dust that can be generated when harvesting does

66 occur. This may also be compounded by the new growth of the crop which can increase the amount of botanical trash in the harvest and can provide a place for growth of microorganisms (Jacobs, 1994). The dust and bioaerosols that are carried into the shed may also change. It is important to note that if animals are being treated for diseases, or other health problems, this can alter the microorganism concentrations that animals are hosting. If these host concentrations are altered the concentrations of microbes measured in the animals’ faeces will also be altered, which in turn can change the concentrations of bioaerosols measured within an animal handling shed. Gram-negative bacteria and their related microbiological constituents will be affected by the animal’s health especially if there is a change in the animals’ natural digestive system (Seedorf et al, 1998).

Outdoor dust concentrations can be a health problem in many areas (Jalaludin and Morgan, 2003). Outdoor dust and bioaerosol concentrations will sometimes influence the levels of airborne concentrations found indoors (Adhikari et al, 2004). Depending on the different ways that bioaerosols can enter buildings sometimes only very small numbers of spores can penetrate from the outside into a building (Corden and Millington, 2001). Normally there is a good correlation between the indoor and outdoor air concentrations and types of bacteria and fungi present (Mishra et al, 1992). To overcome this problem and for comparison, outdoor air should be sampled away from obvious sources of bioaerosols (Adhikari et al, 2004).

2.6.7 Number, activity and species of animals

The number of animals brought into the shed greatly changes the concentration of both dusts and bioaerosols present. Generation of dust has been shown to be proportional to the number of animals and the weight and size of the animals present (Gustafsson, 1999). The activity of the animals can also influence the amount of dust produced. When animals are managed indoors they often become unpredictable and are anything but docile (Renwick, 1986). If the animals have been previously handled in a “positive way”, that did not induce high stress levels in the animals, then they are less likely to be flighty and hard to handle the next time they are handled indoors (Waiblinger et al, 2004; Grandin, 2003).

67 Dust concentrations are higher when animals are fed, handled or moved (ISU, 1992). Dust and bioaerosol concentrations rise when animals are feeding because of a general increase in activity (Pearson and Sharples, 1995) and higher concentrations of inhalable dust are found in compartments close to animals when they are disturbed by the farmer. Peak exposure concentrations were higher by a factor of up to 100 when animals were disturbed (Preller et al, 1995). High movement of feedlot cattle is a principal contributor to dust production (Wilson et al, 2002) whilst the movement of chickens did not result in a greater increase in dust production (Wathes et al, 1998). In one study approximately 67% of the variation in dust mass concentration collected could be attributed to variation in animal activity (Pederson, 1993). In general young animals tend to be more active than older animals (Takai et al, 1998).

The type of animal present will also affect dust and bioaerosol concentrations. Studies have shown that piggeries regularly have higher dust and bioaerosol concentrations than poultry buildings, cowsheds and horse stables (Dutkiewicz et al, 1994; Sigsgaard et al, 1999). However as the housing conditions for these animals are not the same it is very hard to determine if it is the animal or the living conditions that are responsible for the higher results.

2.6.8 Sampling collection methods

The place where the dust or bioaerosol sample is collected can alter results. If the sample location is different between sheds then this becomes a variable. Personal dust exposure measurements normally result in higher concentrations than samples collected using area sampling techniques (Kullman et al, 1998). However personal sampling is not always possible which can lead to errors in sampling placement (Ness, 1991), because for example, the results for a particular shed are much lower than average results, this may be because the concentrations are lower or it could be due to the areas sampled not being representative of the true dust concentrations. As air turbulence affects results, samples collected from a high air flow area may have lower concentrations (Hofschreuder et al, 1996).

It is therefore important that every effort is made to ensure that the samples collected are an indication of the actual airborne concentrations in the shed. This means

68 collecting samples in areas where airborne dust is actually generated, or likely to be generated, in addition to areas where people are working. It is not necessary to sample an area where no one is working if worker exposure to dust is being assessed. It is preferable to collect personal samples where possible (Ness, 1991). It is also important that the sampling equipment is placed in a position that will give a true indication of the concentration of the airborne contaminants present. This means not placing a sampling equipment in the dirt to increase the concentration of dust measured but instead placing it in a position that will give a true indication of airborne dust that people could breathe in.

2.7 Standards

2.7.1 Dusts

2.7.1.1 Worldwide Situation

In most industries in the United States safe and healthy working conditions for all employees are covered by the US Occupational Safety and Health Act, 1970. However agriculture has been administratively exempted from industry standards (McDuffie, et al, 1995). Specific standards for acceptable concentrations of organic dust emissions do not exist. There is very limited monitoring of dust concentrations in production agriculture settings as many smaller operations are excluded from routine OSHA inspections. By default OSHA permissible exposure levels (PELs) for nuisance dusts, particles not otherwise regulated, of 15 mg m-3 for total dust and 5 mg m-3 for respirable dust and 10mg m-3 for grain dusts (oats, wheat, barley) are used in lieu of a universally accepted upper limit for organic dusts (OSHA, 2006). The American Conference of Governmental Industrial Hygienists (ACGIH) recommended threshold limit value (TLV) for nuisance dusts is 10 mg m-3 for inhalable and 3 mg m-3 for respirable (ACGIH, 2006). The TLV for grain dust (wheat, oats, barley) for 8-TWA is 4 mg m-3 (ACGIH, 2006) and the National Institute for Occupational Safety and Health (NIOSH) also recommended exposure level (REL) for grain dust is 4 mg m-3 (Kirkhorn and Garry, 2000).

69 Currently the exposure standards throughout Europe are not consistent. The Occupational exposure level (OEL) for organic dust in Denmark is 3 mg m-3 for total dust (Takai et al, 1998) whereas, the standard in the United Kingdom is 10mg m-3 for dusts Not Otherwise Classified (NOC), 4 mg m-3 for respirable dust and 10 mg m-3 for grain dust (HSE, 2005a).

2.7.1.2 Australian Situation

Inspirable dust, that does not have its own exposure standard, is classified as Rogue dust and has a TWA of 10 mg m-3 in Australia under the Australian Safety and Compensation Council (ASCC, 2006b). There appears to be no standard for non specific respirable dusts on the ASCC Hazardous Substances Information System (HSIS) but the standard for grain dust is 4 mg m-3 (ASCC, 2006b).

2.7.1.3 NSW Situation

Under the NSW Occupational Health Safety (OHS) Act, 2000 and Regulation 2001 (WorkCover, 2000; WorkCover, 2001) there is no legislative requirement for regular inspections of agricultural premises. It is up to the employer to undertake risk assessments of all the potential hazards in the work place or to employ a qualified person to carry out a risk assessment on their behalf. According to the 2001 Regulation, the Time-Weighted Average (TWA), that is, “the average airborne concentration of a particular substance when calculated over a normal 8-hour working day for a 5-day working week” (WorkCover, 2001 p69) for inspirable dust (not otherwise classified) is 10mg m-3 (WorkCover, 2001).

2.7.2 Bioaerosols

Like other countries in the world there is no exposure standard for bioaerosols in Australia because the information about the potential impact about bioaerosols is still developing. Dose-response relationships are often not been well described or understood for bioaerosols (Douwes et al, 2003). It is hard to identify the point at

70 which exposure to bioaerosols becomes a health hazard (Umbrell, 2003). This has, in turn, made it difficult to implement any exposure limits for bioaerosols.

Dust exposure is often used as the proxy exposure limit (Douwes et al, 2003). It has been suggested that it is unlikely there will be any TLVs in the future, as it is too difficult to calculate what those limits would be. (Umbrell, 2003). A threshold limit was proposed in the past of 105 cfu m-3 (total microorganisms per m3of air) (Dutkiewicz, 1992). 103-104 cfu m-3 has also been suggested as high but exposure of farmers to 106-108 spores per cubic meter has shown no negative health effect (Eduard and Heederik, 1998). Total cfu of both bacteria and fungi at a level of 103 cfu m-3 of air has also been suggested (Scarpino and Quinn, 1998) and used as an indictor of possible human health concerns (Gibbs et al, 2004). The OEL of 5-10 x 103 cfu m-3 for total microorganisms, 1 x 103 cfu m-3 for Gram-positive bacteria, was suggested in a Scandinavian study (Dutkiewicz, 1997).

2.7.3 Endotoxin

No exposure standards exist for endotoxin although attempts have been made to identify levels of exposure where there is a perceived risk to health (Simpson et al, 1999). Attempts to establish reliable threshold limits are tenuous due to a lack of consensus on standardized procedures used for the sampling and quantitative analysis of environmental endotoxin (White and Ashley, 2002). For endotoxin exposure the threshold values suggested by Michel et al (1997) for no-response to LPS acute exposure is lower than 0.5 µg, corresponding to 10 hour exposure to less than 50 ng m-3 airborne LPS. Endotoxin NOEL’s (No Observed Effect Level) for various health endpoints have been reported ranging from 50 to several hundred EU m-3. In the Netherlands an exposure limit of 50 EU m-3 was proposed, however 200 EU m-3 looks more likely to be accepted (Douwes et al, 2003). An exposure limit of 1-2 x 102 ng m-3 for endotoxin has also been supported in the past (Dutkiewicz, 1997). In occupational settings it has been established that the threshold level of airborne endotoxin inducing a 5% or greater decrease in FEV1 in normal subjects after a 6 hour exposure is 100ng m-3 (Michel et al, 1996). Another study calculated a threshold of 90 EU m-3 for acute pulmonary impairment (White and Ashley, 2002). It

71 was suggested by Simpson et al, (1999) that industry specific endotoxin exposure standards would be more appropriate than a general standard. This is because of the possibility of endotoxin acting in a facilitatory role allowing other agents to have a greater negative health impact. The introduction of exposure limits will be difficult because a standard methodology has not been developed (Simpson et al, 1999).

2.7.4 Standards for Agriculture

It has been suggested that the general recommended limit should be lowered for inhalable dusts (Oberdorster, 1995). It has also been suggested that TWA’s may be troublesome to recommend for agricultural dusts (Jacobs, 1994). There is general agreement that organic dusts containing endotoxins have important biological effects and that they cannot be considered nuisance dusts (Rylander, 1997). As well a general agreement exists that a dust standard may not be sufficient for protection of workers as the relative amounts of endotoxins in different dusts may vary and thus the same dust levels could express differences in risks from endotoxins (Rylander, 1997). Aeroallergens are also not included in the current exposure standards but can have a negative effect on the respiratory system (Cullinan et al, 2001). The numerous toxic and immunogenic constituents present in organic dust in farming environments indicate that these dusts should not be considered nuisance dusts (Kullman et al, 1998).

Pearson and Sharples (1995) reported that the daily dust exposures for 20 % of poultry workers was over the UK Occupational Exposure Standard (OES). They also reported that pig workers were not found to be over the UK OES but that workers had a high incidence of respiratory problems. This suggests that the OES should be reduced for pig and poultry workers. The idea of lowering exposure standards in agriculture, because of the amount of endotoxin present, has also been put forward by Castellan et al (1987). They state that reducing endotoxin exposure limits will only help if the pathogenesis of endotoxin is better understood. In Australia the lowering of OES in agriculture is supported by Attwood (1985) who agreed that the respirable dust concentration needed to be lowed. This has subsequently occurred in Australia. He also suggested that the total dust level needed to be lowered, which has

72 not occurred. The health effects demonstrated in a study by Vogelzang et al (2000) suggested that a threshold level for organic dust exposure should not be greater than 2.6 mg m-3. Exposure limits suggested for animal handling buildings for total dust are 2.4 mg m-3, and for respirable dust of 0.23 mg m-3 (Donham, 1999). Donham and Cumro (1999) suggested that the respirable dust concentration should be as low as 0.16 mg m-3. These suggested limits are considerably lower than current standards. The reason for reducing these levels is that the bioactive substances present in dusts in animal handling buildings may be potentially harmful to human health (Donham and Cumro, 1999). Exposure levels should be in place in agriculture for all of the major biologically active contaminants because the correlation between dust levels and biologically active constituents present is low (Attwood, 1985).

2.8 Methods of Controlling Exposures

Industrial environments are normally clearly defined, worker exposures are relatively stable and the factors that influence exposure are relatively well characterised. This is not the same in agricultural environments making prevention strategies harder to implement (Jacobs 1994). The importance of clean uncontaminated air in work environments is well known (ACGIH, 2004). There is little doubt that certain socioeconomic characteristics of farming make it difficult to encourage better dust control (Watson, 1986). Methods of reducing exposures can be divided into the hierarchy of control. The best way of controlling a risk is to eliminate it. If this is not possible then the risk must be minimised using one or more of the other control options from the hierarchy of control. The control method selected should be the highest on the hierarchy as possible (CCH, 2001).

2.8.1 Elimination

Elimination involves the removal of the potential hazard at the source and is the most effective method of controlling the risk (CCH, 2001). This is generally not possible in agriculture as elimination of the dust would eliminate the work with the animals and/or crops that are the end product of working within agriculture. Dust sources in

73 agriculture usually result from the work process (Pearson and Sharples, 1995). The other variable that may be removed is the person working in the environment however most farming procedures require the presence of people, so removal of this variable is rarely an option (Hoglund, 1986). These facts make elimination rarely possible.

2.8.2 Substitution

Substitution involves the problem being replaced with an alternative that does not produce the same negative health impacts as the original contaminant/situation. (CCH, 2001). In this study the dust producing contaminant, either the animals or the system of shearing the animals, cannot be substituted. However, some substitution can take place in the use of different machinery to do jobs that otherwise people would have to undertake in other agricultural industries. For example the use of harvesting machines in the grain industry and milking equipment in dairying that minimise exposure of workers to the pollutant. For most organic dust exposures substitution is not possible (Jacobs and Donham, 1994). Substitution is not possible in the shearing industry because there are currently no other reliable techniques for removing the wool from sheep.

2.8.3 Engineering

Engineering controls are next in the hierarchy as a way to reduce the impact of known risks (Bohle and Quinlan, 2000). Such controls are designed to prevent disease and injury by modifying the tools, equipment and physical working environment. They achieve control by removing, isolating or enclosing hazards or by changing the way the hazard is transferred to the worker (Bohle and Quinlan, 2000). Reduction of airborne agents in enclosed livestock facilities has been achieved through advances in ventilation, frequent removal of manure, addition of compounds such as fatty oils to animals’ feed and use of water or oil sprays (Merchant and Reynolds, 2000).

74 2.8.3.1 Ventilation

The key to prevention of respiratory disease among agricultural workers is improved building design and management procedures (Merchant and Donham, 1989). The most effective measure for the prevention of occupational diseases due to exogenous microorganisms is the reduction of dust in the workplace by effective ventilation systems (Dutkiewicz, 1997).

Air quality is almost inevitably compromised once animals are housed at high stocking densities which is typical in intensive production. The design and operation of a ventilation system can play an important role in determining air quality in livestock buildings. The three primary mechanisms by which ventilation affects health and growth of both humans and animals are: aerial spread of pathogens and pheromones, regulation of thermal exchanges and maintenance of air quality (Wathes, 1992). Airflow through an animal house can be driven by either natural or mechanical means. It has been shown that the concentration of gases falls rapidly with faster ventilation rates and particulate matter, such as airborne dusts, is also cleared by sedimentation at an overall rate dependent on aerodynamic size of the dust (Wathes, 1992). The use of ventilation systems can mean that there is no natural ventilation in the shed. This can lead to a build-up of contaminants (Douwes et al, 2003).

Ventilation can be categorised as dilution ventilation or local exhaust ventilation (LEV). Overall, LEV is most suited to situations where: a) The contaminant is generated from a single source or line source, b) Can be captured before it reaches the workers’ breathing zone, and c) The emission rate is not constant.

As the name suggests dilution ventilation introduces clean air into a workplace to reduce the concentration of the contaminant. For dilution ventilation the supplied air should be introduced along one side of the work area and exhaust openings located on the opposite side of the room to ensure the airflow pattern is not disrupted. Any air exhausted from the workplace must be replaced by an equal amount of uncontaminated fresh air to ensure hazardous concentrations of substances do not build up in the workplace due to an excessive negative pressure.

75 LEV systems are designed to collect contaminants as close to the original source as possible. A LEV system usually includes: a hood to capture the contaminant; ducts to transport the contaminant; air cleaning devices (to remove contaminants from the air); fans to move the air through the system and a stack or emission point. Since LEV systems incorporate forced ventilation a fan is installed between the hood and emission point. The fan must generate sufficient air flow within the ducts to ensure there is sufficient velocity to capture the contaminant and keep it entrained in the air stream while achieving the most economical efficiency (Tranter, 1999).

Both dilution and LEV systems can be used however the LEV system can only be used for a specific problem whereas the dilution system can be used in a general animal housing area. Hence it its very hard to use a LEV system in a shearing shed as the emission point for the dusts can be in many different places in the shed. Adequate ventilation has been shown to reduce fungi levels by up to nine times (Summerbell et al, 1994).

A major flaw in the design and operation of ventilation systems in livestock (and other) buildings arises from the assumption of perfect mixing of incoming with indoor air. Other problems may be experienced in the distribution of sources of heat, pollutants and other atmospheric constituents which can cause the clean air to not reach all parts of the enclosed area (Wathes, 1992). Ventilation rates in the cooler months are expectantly slower to conserve heat. The net result is poorer air quality as the mixing with fresh air is not as regular especially when dealing with high concentrations of ammonia and airborne dust (Hartung, 1994). Another problem with dilution ventilation is that sometimes the system is designed to maintain a predetermined temperature in the building with little regard to other conditions (Randall and Boon, 1994). Fortunately, as people become more aware of the roles that ventilation systems play, this is changing. Maintenance of ventilation equipment is crucial for the proper function of fans, filter and air-ducts. In agriculture these features are often not properly maintained or cleaned (Jacobs and Donham, 1994).

76 2.8.3.2 Other engineering controls

There are other engineering control measures that do not involve ventilation. Of importance is the proper storing of the raw plant materials, such as grain and hay, at low temperature and humidity which prevents growth of microorganisms and overheating. Some physical methods such as ionising of air, cleaning of production rooms with aerosols (fogging) or sterilization of the products by gamma-irradiation, are seen as more promising than using chemicals for the prevention of the growth of bacteria and fungi or for inactivation of endotoxin (Dutkiewicz, 1997). Water showering of floor surfaces to reduce the concentration of dust in the air has resulted in a limited non-significant decrease in dust generation and concentration. Spraying of a 10% rape seed oil solution has shown a significant reduction in the generation of dust (Gustafsson, 1999). Ozone gas can be used to treat the air and has been found to effectively reduce the recorded concentrations of bacteria. It has also been found to reduce the concentrations of inhalable dust particles but not respirable dust particles (Banhazi et al, 2002). However the required concentrations of ozone may exceed the acceptable exposure standards.

Ultraviolet Germicidal Irradiation (UVGI) is a newer method of disinfecting the air from pathogens. This method damages the DNA of microorganisms and destroys their ability to replicate thus making them non-infectious (Brickner et al, 2003). UVGI is produced by mercury vapour lamps normally at a wavelength of 253.7 nm, within the UV-C bandwidth of the electromagnetic spectrum. UVGI is only effective if the duration of exposure is long enough and the particle is exposed to enough energy. This process is normally installed through upper room fixtures as well as by placing UVGI lamps inside mechanical ventilation systems (Brickner et al, 2003).

A control method that is considered to be successful involves the misting with oil and water droplets. These cause the dust particles to coagulate (stick together), settle and adhere to surfaces (Pearson and Sharples, 1995). The problem with some of these control methods is that dust concentrations may decrease but the concentration of another contaminant (e.g. ammonia) may increase (Wathes et al, 1998). Spraying of water will reduce the concentrations of dust but will provide high moisture for microbial growth (Chang et al, 2001; Jacobs and Donham, 1994). Dry filters,

77 electrostatic precipitators and wet scrubbers are impracticable in livestock buildings, due to the large volumes of air that need to be treated (Takai et al, 1998).

An important method of decreasing exposure to toxic concentrations of gases and endotoxins is the storage of manure in an enclosed leak-proof structure outdoors (Kirkhorn and Garry, 2000). Different litter treatments make a big difference to the amount of dust that is produced. Bentonite is an alternative for litter treatment that is made from processed volcanic materials, is mainly composed of clay minerals and swells considerably when exposed to water (Schlumberger, 2005). It is relatively inexpensive and there are no reported adverse health effects for either animals or humans (Sevi et al, 2002). It also has the ability to capture ammonium. However, when it is used as a flooring material it can become very slippery and sand should be put down to prevent slippage (Australian Maritime Safety Authority, 2005). In a study using Bentonite or litter removal to see if either process decreased airborne dust exposure it was found that both treatments decreased the amount of dust in the air and increased milk yields from ewes. However when the two processes were combined there was no decrease in dust exposure compared with when either process was used on its own. The microbiological content also decreased with the use of Bentonite, but not with litter removal (Sevi et al, 2002).

2.8.4 Administrative controls

Administrative controls reduce or eliminate exposure to a hazard by adherence to procedures or instructions (AS4804, 2001). This includes the limitation of working hours and would occur after a problem has been identified and time periods are set to identify how long a person can be exposed to a certain irritant/s. Identification of risk occurs in agriculture but often the agricultural workers are self-employed and hence have no supervisor to regulate their time periods engaged in certain activities.

Supervision, in most cases, is an important component to administrative control. In the shearing industry there is a shearing contractor who normally organises the work but does not normally directly supervise. Time restraints often mean that a job needs to be completed by a certain time and no breaks are taken which can lead to unregulated time periods for activities. People can be educated about the dangers but

78 this may not change work practices. If a job needs to be completed by a certain time then that job will be completed with no regard to the time period that the person has been exposed to an irritant. If a worker is educated they can more readily recognize work related problems (Jacobs and Donham, 1994). Employers need to be educated about the potential effects of organic dust exposures and be made aware of suitable protective equipment (Simpson et al, 1999). Farmers generally react positively to intervention (Hoglund, 1986).

Health education is very important as is the periodical medical examination of workers exposed to organic dusts (Dutkiewicz, 1997). Compared to industry occupational health services for farmers are extremely uncommon (Jacobs and Donham, 1994). However there are organised occupational health services in most Scandinavian countries. These services are performed by an integrated team of both medical and technical personnel who visit farms, investigate workplaces and give information about health hazards and their prevention. The information is given individually or to groups of farmers. Every second year the members are offered a health check-up which concentrates on the specific risks that the farmer is exposed to (Hoglund, 1994). Unfortunately a similar service does not exist in NSW.

It is often difficult to get information out to farmers and the ways normally used are the distribution of pamphlets, booklets, videotapes and other passive material. However a more effective way is to gather farmers in small groups and allow them to discuss and learn about health hazards in their workplace. This method is time consuming and it is often not practical to bring large groups of farmers together (Hoglund, 1994). In Sweden pamphlets, slides and transparencies dealing with airborne problems were produced, distributed to farmers along with an invitation to join a training course. This three day course was for agricultural advisors and safety engineers. All of these methods were shown to increase the level of awareness about dust related respiratory problems (Hoglund, 1994). Also in Sweden an education program was undertaken to inform farmers about the risk of HP. After completion of this program the incidence of HP showed a slight decrease (Rylander and Jacobs, 1994).

Preemployment screening is a possible control strategy. It refers to medical testing which can be used to identify potential health problems in current or prospective

79 workers. If a person is predisposed to a certain problem then they can be kept away from exposure to irritants that may exacerbate that problem. However there are concerns over the use of this tool to discriminate against hiring certain people (Jacobs and Donham, 1994).

2.8.5 Personal Protective Equipment (PPE)

Respirators can be classified into two types: air-purifying respirators that remove contaminants from the ambient air and atmosphere-supplying respirators that provide air from a source other than the surrounding atmosphere (Willeke and Han, 1996). The use of personal respiratory devices is limited in agricultural operations because they are hot and uncomfortable and are not routinely worn (Kirkhorn and Garry, 2000; Jacobs and Donham, 1994). Even the best respirator may not protect the wearer sufficiently if it does not fit properly which may leave a gap between the edge of the respirator and the facial skin. Therefore respirator fit testing is required before entering specific work environments to ensure that the respirator worn satisfies a minimum of fit and that the user knows when the respirator fits properly (Willeke and Han, 1996). Only respirators with appropriate approval should be used (Lenhart and Reed, 1989). The proper use of respirators also includes their proper selection, maintenance and storage, which rarely happens in most agricultural workplaces (Gardner et al, 2004; Jacobs and Donham, 1994).

Good preventive measures also include the use of positive-pressure helmets during work with decomposed vegetable and grass materials, provision of machines with ventilated cabins and remote control of the production processes. PPE including dust masks, air purifying respirators, safety shoes and protective clothing that could be used to minimise exposure are sometimes difficult to obtain and are seldom accepted readily by workers in agricultural settings (Merchant and Reynolds, 2000). Engineering controls are preferable to long-term use of personal respiratory protection (Kirkhorn and Garry, 2000). In agriculture appropriate PPE may not be available on the farm and little help exists on its selection and use (Jacobs 1994). In a study of farmers (Watson et al, 1986) 60% didn’t have any PPE available. The

80 available protection was frequently the wrong type, badly maintained or not worn often enough.

2.8.6 Problems with control measures

Despite significant fatal and non-fatal injury rates (see Section 2.3) there is still a low adoption of farm safety practices. Farm safety also seems to remain a low or medium-low priority for most farmers. The reasons for this include; a low perception of personal risk, reluctance to change traditional work practices, a generally tolerant attitude towards risk and a lack of relevant authority inspections for compliance (Aoun and Jennings, 2003). Production agriculture consists primarily of thousands of small independent family-run businesses where occupational health is a generally foreign concept. Prevention strategies are generally not readily applied as the workplace is not clearly defined, worker exposures are highly variable, and the factors that influence exposure are not well characterized (Jacobs and Donham, 1994). Many farmers have the theory that “I’m not sick so what is the problem?” They also don’t see the potential for their health to be improved (R. Kift, unpublished data).-

2.8.7 Costs

The cost of dust reduction measures has not been investigated by many researchers. Out of the limited number of dust removal systems that have been costed, the dry filtration systems have been found to be more cost effective than the wet scrubbing systems (Pearson and Sharples, 1995).

The benefits of dust reduction are difficult to evaluate in financial terms. Benefits of human health are particularly difficult to evaluate because of the long-term impacts of respiratory disease (Pearson and Sharples, 1995). In NSW it is possible for a company to be fined for not insuring the safety of the workplace which carries a maximum fine of $550,000 for the first offence and $825,000 for any subsequent offences. On the spot fines for employers of $600 can also be given and if an

81 employer does not comply with improvement notices the fine can be between $1000 and $1500 (WorkCover, 2001). The maximum penalty that has been given in NSW agriculture was $275,000 in 2004 to a cotton grower after the death of a worker (WorkCover, 2004b). Although it is generally thought that reducing dust concentration in livestock buildings improves the health, and thereby the productivity, of the animals there are still questions as to whether this is a fact (Pearson and Sharples, 1995). The possible impact on the price paid for livestock is often the important reason why a farmer would control contaminant exposure, not to control the possible risk of disease.

2.9 Exposure in agriculture

2.9.1 Factors that may affect agricultural exposures

After exposure to the etiological agents of disease the infective process depends on a number of factors including the resistance or susceptibility of the host, the exposure routs and dose and the virulence of the specific pathogen (Tullis and Stopford, 2002). Not all workers with similar exposure to dusts are affected similarly suggesting the possible importance of host factors in addition to environmental factors (Zuskin et al, 1994). Many different factors can be expected to change exposure and factors may also be interrelated, e.g. mechanical operations may release more dust into the air than manual work but the worker may be located further from the source during mechanical operation and may even be enclosed in a ventilated cab. In studies of intensive animal production, type of equipment, housing and ventilation were related to dust concentrations in poultry houses and farm characteristics and activities were related to endotoxin exposure of pig farmers (Eduard, 1997). Environmental factors such as the chemical properties of the agents and the concentration and duration of exposure are of great importance in the development of occupational lung disease particularly occupational asthma. Host factors are also important but only a small percentage of exposed workers are affected (Zuskin et al, 1994). Interactions between farm animals and their caretakers provide the possibilities of both healthy and traumatic injury hazards to the caretaker. One obvious factor in working out

82 whether a person can develop negative health affects is exposure time. The more contact there is between an animal and a person the more likely it is that an injury or illness resulting from contact with the animal will eventuate (Murphy, 1992).

There are three different patterns of exposure to dust and bioaerosols: • The first pattern has very high exposure for long periods of time but only for a limited number of days. This commonly occurs with seasonal jobs, such as harvesting field crops. • The second pattern of exposure is to high concentrations at short but frequent intervals over a prolonged period of time. This is normally found in weekly jobs. • The third pattern is of long daily exposure to lower levels that occur every day (Jacobs, 1994). The exposure that is experienced by shearers varies from between the first and second pattern. They have medium to high exposures for medium lengths of time (months). Information is also needed about the specific hazards, the exposure routes and the dose-responses to enable the assessment of health risks (Pillai and Ricke, 2002).

Exposure of farmers and farm workers to airborne non-infectious microorganisms and endotoxin depends on task and production and can be highly variable. Length of work days are highly variable such as how long it takes to complete the job (Jacobs, 1994). It has been found that studies into the assessment of exposure in relation to farmers can be quite challenging due to seasonal and day-to-day variability in one’s activities (Coble et al, 2002). The activities of humans can also change the amount of dust that a person will inhale. The work carried out is often strenuous so that farmers will inhale large amounts of dusts (Takai et al, 1998).

There are different host factors that may influence the effects of exposure with the two most important being family history and history of smoking. Genetic predisposition may change the response a persons’ body has to an irritant and this can influence the immunity that some people have to certain irritants. Smoking has been shown to play a role in exposure as a person who smokes could already have an increased risk of certain diseases and exposure to dust may increase the damage that the cigarette smoke is doing (Zuskin et al, 1994). Cigarette smoking is the major

83 determinant of chronic obstructive pulmonary disease which suggests that occupational exposures may interact with smoking (Zock et al, 2001). It has been suggested that smoking could be related to animal allergy (Gautrin et al, 2001). In farmers who smoke there is an increased relative risk of 1.5 to 2.0 for coughing and wheezing but no increased risk could be found regarding phlegm, shortness of breath and/or work absence (Donham, 1994). Farmers can develop small opacities from biological responses however, in a minority, they may not be the result of dust exposure but other factors such as smoking or aging (Soutar et al, 1997). In a Finnish study (Heloma et al, 2000) workers who smoke were broken up into groups by the type of job they did. It was found that the highest proportion of smokers was found in workers with a “blue collar” job including farmers (34.6% were smokers). The problem with nicotine is that it is a strong polar substance and attaches easily to particles of dust (Heloma et al, 2000) further increasing possible synergistic effects.

People may be exposed for months or even years before the onset of symptoms (Karkainen 2002b). An association has been found between the number of years working with animals and the prevalence of mild bronchial responsiveness (Vogelzang et al, 2000). In a study of people exposed to animal dander it was concluded that there was no correlation between exposure time for animal allergens and negative health impacts (Gautrin et al, 2001).

Agricultural workers who enter the workforce with airway hyper-responsiveness, or who develop it as the result of exposure, frequently select themselves out by leaving their agricultural related work (Merchant and Reynolds, 2000). Those people who have health problems are less able to maintain their particular job (Burnley, 1998). A 6-year follow-up study revealed about 15% of farmers had dropped out of farming because of respiratory disease (Donham, 1994). Self-selection from agricultural environments normally occurs more frequently with workers involved in the transportation, storage and processing of agricultural products (Jacobs, 1994). People who develop asthma from work are the first to select themselves out of that work (Vogelzang et al, 2000). This means that follow up studies on the same people are often hard to conduct. This can also make long-term investigations into health impacts very difficult so it is important that many different studies are carried out throughout the world (Burnley, 1998). When a person who is susceptible to disease leaves that job they are leaving behind a relatively less susceptible group of workers

84 who are potentially more able to tolerate the work environment (Fishwick et al, 1997). These workers seem to have a resistance to the effects of the dust exposure (Buchan et al, 2002).

Sometimes the health of workers is better than the health of the general population because the general population includes people who are ill (Harrington et al, 1999). This is commonly referred to as “healthy worker effect”. Older studies may show that the risk for workers in agricultural environments was greater in the past than it is now. In some studies both young and older workers have been studied. The younger workers are exposed to a cleaner work environment, over a shorter time period, which means that their risk for possible disease is less than older workers. This must be taken into consideration when comparing agricultural groups to the general population (Zock et al, 2001).

Traditionally farming has been a family operation with land ownership passed from generation to generation. For this reason family or social pressures to remain in agriculture may be greater for farmers than for workers in other environments (Jacobs, 1994) and farmers are more likely to remain working in farming, even with a limiting disability, than workers in other jobs (Brackbill et al, 1994).

The age of the farmer involved can also determine the chance of injury. It has been shown in a Finnish study that a farmer is most likely to become injured if they are aged between 50-54. The reason for this is not clear. It was expected that younger farmers (due to inexperience) or older farmers (due to physical wear and tear) would be the most injured (Virtanen et al, 2003). On average farmers are 5.6 years older than the average American workforce (Brackbill et al, 1994). 19% of farmers were older than 65 years, in contrast to 3.6% of other employed people (Brackbill et al, 1994). In a study of Finnish farmers the weekly pattern of injuries was quite clear with the peak day for injuries being Monday followed by a steady decline. Nearly half of the injuries happened during the afternoon hours, particularly late afternoon (Virtanen et al, 2003).

85

2.9.2 Relevant exposure studies from the literature

In a study of livestock buildings (cattle, pig, poultry) in four European countries (England, The Netherlands, Denmark and Germany) carried out by Seedorf et al, (1998), the lowest levels of endotoxin were found in the cattle houses (15.1 ng m-3), compared to pig (135.1 ng m-3) and chickens (785.7 ng m-3). The highest total bacteria concentrations were found in the chicken houses with mean concentrations of 6.43log cfm m-3. For pigs the mean concentration was 5.1 log cfm m-3 and for cattle, 4.3 log cfu m-3. The composition of airborne microorganisms in all of the livestock buildings in this study was comprised mainly of two types of Gram- positive bacteria. Staphylococcus spp. and Streptococcus spp with a relative concentration of 90% or more of total bacteria collected.

In a Scandinavian study (Larsson et al, 1998), the background levels for the total count of airborne microorganisms in the farmers’ work environment was 1.51±0.58x107 cfu m-3. During animal tending the range was 0.42-5.10x107 total organism’s m-3 of air. When the maximal exposure was obtained it was a 15-fold increase from background concentrations to 0.11-6.5x108 (worst case estimate).

In the United Kingdom 9 different occupational environments were studied (Simpson et al, 1999) including the textile, agricultural and animal handling. Dust exposure and endotoxin were measured in all industries. The highest personal dust exposures were recorded during cleaning activities in the grain (72.5 mg m-3) and wool (62 mg m-3) industries. The highest median exposures were found in the animal handling industries (poultry 11.5 mg m-3, swine 6.7 mg m-3). The highest personal endotoxin exposures were measured in the poultry (71995 ng m-3) swine (14923 ng m-3) industries. In the swine confinement workers studied 11 different sites were visited and 27 different workers were monitored, whist the poultry workers studied were either catching gangs (higher average dust concentrations) or shacklers (higher average endotoxin concentrations). The results highlighted that dust exposures are greater in a number of industries than the set exposure standards. The workers who worked with wool had different exposures depending on the job they were doing. The wool workers undertaking sorting had the highest median dust (13.18 mg m-3)

86 and endotoxin (694 ng m-3) exposure. Sorting had median dust exposure of 2.03 mg m-3 and median endotoxin exposure of 288 ng m-3, combing had median dust exposures of 2.86 mg m-3 and median endotoxin exposures of 52 ng m-3, and the finishing process had the lowest median exposures of any wool handling process (0.96mg m-3 dust, and 5 ng m-3 for endotoxin). These results showed that in the wool processing industry the higher in the process an individual worker was the higher the air contamination they were exposed to. The only industries not recording a reading higher than the exposure standard were weaving and mushroom cultivation (Simpson et al, 1999).

In a French study the maximum values for the concentration of microorganisms per cubic meter of air varied from 6.5x105 cfu m-3 for moulds and from 103 to 6.4x105 cfu m-3 for actinomycetes. It was also shown that the lowest exposure found was at the beginning of work shifts and the time taken for the concentration of microbes to double was, on average 5 mins. At the end of the work shift the microbial concentration returned to initial values in 12 of 22 cases for fungi and 9 of 22 cases for actinomycetes (Reboux et al, 2001).

Pig farmers in Holland, studied by Vogelzang et al (1998) showed the estimated long-term average exposure to inhalable dust was 2.63 mg m-3 and to endotoxin this -3 -1 was 105 ng m . The mean annual decline in FEV1 of 73ml yr is high compared to the expected age related decline of 29 ml yr-1. It also found that after adjustment for age, the decline in FEV1 during a 3 yr period was significantly associated with exposure to endotoxin alone whereas the decline in FVC was associated with both endotoxin and inhalable dust exposure.

In an indoor dairy cattle shed an Indian study estimated that the average concentration range of total fungal spores was 233-2985 m-3 and concentration of cfu’s ranged between 165 and 225 cfu m-3(Adhikari et al, 2004). In a study in Holland amongst 198 pig farmers the mean concentrations for dust was 3.0 mg m-3 and for endotoxin was 130 ng m-3 which the researches considered to be high (Preller et al, 1995).

Tasks being carried out by the farmer was investigated in a Californian study (Nieuwenhuijsen et al, 1998). It was found that those working in the dairy farming

87 industry could be exposed to many different concentrations of dust depending on the task. The average dust concentration for milking was 0.7 mg m-3, manure removal was 2.6 mg m-3 and the highest levels recorded were found in the feeding operation (25.9 mg m-3).

In 1997 a major study was undertaken in Denmark, Germany, the Netherlands and England and reported by Hinz and Linke, 1998a; Hinz and Linke, 1998b; Phillips et al, 1998; Seedorf et al, 1998; Takai et al, 1998; Wathes et al, 1988. The main objective of the project was to undertake a field survey of the emissions of aerial pollutants within and from 329 livestock buildings. The survey covered the major types of livestock housing for cattle, pigs and poultry. In each building seven locations were sampled and outside an eighth site was sampled. The concentrations of airborne dust were measured with modified personal samplers which separated the dust into the inhalable and respirable size fractions. The bioaerosol concentrations were collected using a specifically designed sampler called a novel automated slit sampler. The mean concentrations of both inhalable and respirable dust were highest in poultry houses (3.6 and 0.45 mg m-3) and were lowest in cattle buildings (0.38 and 0.07 mg m-3). None of the respirable dust results were affected by the season that the results were collected in. The dust results were on average 30-40% lower at night than during the day. At no times were dust concentrations in cattle houses considered hazardous to cattle health. Dust concentrations were lower in the farmers working area than in the area above the animals holding pens. The effects of floor type on dust concentration in cattle and pig buildings were not consistent. The bacteria results were 10 to 100 times greater than the fungi results. Compared with pigs and poultry the endotoxin concentrations in cattle houses were low. In cattle houses the mean aerial concentrations ranged between 7.4 and 63.9 ng m-3. Poultry had the highest endotoxin concentrations.

In a Dutch study (Vogelzang et al, 2000), 171 pig farmers were investigated over a three year period. Over this period the average exposure to inhalable dust was 2.63 mg m-3 and average endotoxin exposure was 105 ng m-3. The average exposure to inhalable dust was associated with increases in bronchial responsiveness. The majority of the dust was generated from the use of wood shavings as bedding material.

88 A study of six open style swine houses in Taiwan (Chang et al, 2001) found that the mean airborne respirable dust was between 0.15 and 0.34 mg m-3. The average temperature of the buildings was 30.4-30.7oC. The authors found that the results were lower than previously recorded and attributed this to the open style of the building that allowed the dust and gasses to be dissipated into the general environment.

An American study of workers in 85 Dairy Barns in central Wisconsin (Kullman et al, 1998) found that the average concentration of static dust was 0.74 mg m-3, personal sampling was 1.78 mg m-3 and static respirable 0.07 mg m-3. This study showed a correlation between concentrations of dust and total spore and bacteria concentrations.

A study by Holyoake (2002) cited by Reed et al (2006) sampled two types of pig shed and reported on dust and bioaerosols exposures of workers, as well as samples from the general shed environment. Personal exposures of workers to respirable dust ranged from 0.02 to 3.57 mg m-3 and for inspirable dust ranged from 0.40 to 42.3 mg m-3. Personal exposure to respirable endotoxin ranged from below detectable levels to 833 EU/m3 and for inspirable endotoxin from below detectable levels to 2117 EU/m3.

From reviewing the literature it is apparent that airborne dusts and bioaerosols can occur in high concentrations in agricultural workplaces and that some exposure concentrations may be hazardous and cause respiratory illness. The present study investigates dust and bioaerosol concentrations in the sheep shearing industry, with emphasis on the shearing shed environment

89 CHAPTER 3 METHODS

Air monitoring for dust and bioaerosols was undertaken at 29 sheep shearing sheds located on different farms throughout the eastern area of NSW. The farms were selected through contact with the Australian Shearer’s Association, who supplied names of shearing contractors to the researchers. Shearing contractors were contacted by letter to gauge their interest in being part of the study (Appendix A). If a shearing contactor was interested they were contacted by follow up phone call to find out when would be the best time and place to sample the working environment. During this process care was taken to try to sample during different times of the year and at different locations throughout eastern NSW. It was not possible to sample each variable the same number of times in this study due to seasonal variations in the time of shearing (more in spring than summer), the availability of interested shearing contractors (more sheds were sourced from the western region of NSW), or the activity that the shearers were undertaking (more shearing is undertaken in NSW compared to crutching). The difference in sampling numbers is explained in each relevant section on variables (Chapter 4). Each shed was sampled once during each period of sampling. Three farms were sampled twice, however they were either sampled during different years, at different times of the year or were undertaking a different shearing activity, and on that basis were considered different to the last sampling day. The shearing sheds sampled were mid sized, most with 4 or 5 shearing stands (Plates 3.1 and 3.2). All sheds had between 2 and 6 shearers working per day. The largest shed had 7 shearing stands (Plate 3.3) and the smallest had 2 shearing stands (Plate 3.4).

Plate 3.1 A 3 stand shearing shed (inside) Plate 3.2 A 3 stand shearing shed (outside)

90

Plate 3.3 A 7 stand shearing shed Plate 3.4 A 2 stand shearing shed

The sheds monitored had interconnecting holding pens that lead into the shearing area. The flooring material was in most cases wooden (there was one shed with wooden floors in the shearing and holding areas and concrete flooring in the wool sorting area) (Plates 3.5 and 3.6).

Plate 3.5 Wooden floored shed Plate 3.6 Concrete floored shed

On all farms the sheep were held in outside holding pens, with a dirt base, prior to entering the shed (Plate 3.7). In some cases there was an additional holding area that was slightly enclosed and had dirt or woodchip flooring (Plate 3.8).

91

Plate 3.7 Holding pens Plate 3.8 Slightly enclosed holding area

The shearing day is made up of four 2 hour shearing sessions. On the majority of farms three out of the four shearing sessions were monitored. Session 2 from 10am to 12 noon, Session 3 from 1pm to 3pm and Session 4 from 3:30pm to 5:30pm. On one farm Session 1, from 7:30am to 9:30am, was monitored and on some farms the last session was not monitored because shearing had been completed for that day.

3.1 Dust Monitoring and Analysis

Two types of dust monitoring were undertaken at each farm. Respirable dust, carried out according to Australian Standard AS2985-1987 (Standards Australia, 1987) and inspirable (inhalable) dust, carried out according to Australian Standard AS3640- 1989 (Standards Australia, 1989). These were the appropriate standards at the commencement of the study in 2003 but were reissued in 2004 (Section 3.1.1). The dust sampling undertaken included both personal and static sampling. Sampling is considered “personal sampling” when the collection point is within the breathing zone of the worker being sampled. The breathing zone is defined as a hemisphere with a radius of 300mm extending in front of the face and measured from the midpoint of a line joining the ears (Tranter, 1999). Static or environmental sampling is when the sample is taken from the general area where the person is working (Tranter, 1999). Static sampling does not record the concentration the worker is inhaling but the general concentration that can be found in the air at the time of sampling. In all cases field blanks were used as controls. A field blank is a filter that undergoes the same handling as the sample filters which includes conditioning and loading into the samplers or transport containers and transportation between

92 laboratory and sampling site, but not used for sampling (Standards Australia, 1987). Ten percent of filters (with a minimum of two) need to be selected as field blanks (Standards Australia, 1989).

3.1.1 Sampling for respirable dust

37mm Millipore PVC membrane filters, with 5µm pores, were placed in sterile Advantec tight lid type petri dishes with a support pad. They were then labelled and left with their lids slightly ajar in the balance room overnight to come to equilibrium with the balance room atmosphere. After acclimatization the filters were then pre- weighed using a Mettler Toledo MX5 calibrated scale. After weighing each filter was placed into a Casella respirable dust sampling filter holder. In the field the filter holder (with filter) was placed in a Casella respirable dust sampling cyclone. This sampling cyclone was then connected to an SKC Airlite sampling pump using flexible tubing. This sampling device was then calibrated using a Bios DryCal DC lite to establish the sampling rate of the pump before use. The sampling head was connected to the calibrator by flexible tubing. It should be noted that during the period of this study the Australian Standard for sampling for respirable dust was reviewed and reissued in 2004. AS 2985-2004 (Standards Australia, 2004a) now requires a sampling flow rate of 2.2 L m-1, however, because the sampling was started in 2003 using AS 2985-1987 (Standards Australia, 1987) the pump was set at 1.9 L m-1.

In most cases both personal and static samples were collected. When personal sampling was being undertaken the sampling device was located within the worker’s breathing zone and connected to the pump unit which was worn on a belt. The pump was turned on and the person being monitored went about his or her normal work activities. The static sampler was placed in the room near where the majority of the shearing was being undertaken. The position of the static sample changed from farm to farm due to the design of the building and work place design.

After completion of the work session, and therefore the sampling period, the pumps were removed from each person or the place where the static sample was located and recalibrated (using the same calibrator) to determine an after sampling rate. The

93 pumps were then turned off. The process was repeated for each work session sampled. The sampled filters were returned to the laboratory to allow each filter to acclimatise in their original labelled petri dishes for 24 hours. Each filter was then re-weighed using the same calibrated microbalance as was used to weigh the filters prior to use. The field blanks were also re-weighed. Calculations (see Section 3.1.3) were then carried out to find the concentration of respirable dust that the workers were exposed to.

3.1.2 Inspirable dust

As with the respirable dust samples, 25mm Millipore PVC membrane filters, with 5µm pores, were placed in sterile Advantec tight lid type petri dishes with a support pad, labelled and left with their lids slightly ajar in the balance room overnight to come to equilibrium with the balance room atmosphere. After acclimatization the filters were weighed using a Mettler Toledo MX5 calibrated scale. Prior to sampling each filter was placed into a SKC 7 hole inspirable dust sampling head or a SKC IOM inhalable sampling head. The appropriate sampling standard for Australia, AS3640 suggests that either sampling head can be used to sample for inspirable dust as both meet the ISO 7708 sampling criteria. Both sampling heads can be used up to the point where particles greater then 30 to 50 m are being collected, and if this is to happen the IOM head is preferable. The particles collected for this study were considered to be less than 30 m. According to Linden et al (2000) there is a different in the sampling efficiency of the sampling heads, when sampling for larger particles using the IOM sampling head and an open style sampling head. Each sampling head was connected to SKC Airlite sampling pump using flexible tubing. This sampling device was then calibrated using a Bios DryCal DC lite to establish the sampling rate of the pump before use. The sampling head was calibrated according to AS 3640-1987 (Standards Australia, 1987) and the pump sampling rate was set at 2 L m-1.

This procedure was repeated for all inspirable sampling heads. Similar to respirable dust samples, both personal and static samples were collected on most farms. If personal samples were being collected the sampling device was located within the worker’s breathing zone and connected to the pump unit worn on a belt. The person

94 being sampled for the inspirable dust was normally doing a different job to the person being sampled for respirable dust. Different jobs in the sampled sheds include, “shearer”, “rouseabouts”, “classer”, “presser” and “stockman” (Plates 3.9 and 3.10) . The pump was turned on and the person being monitored then went about his or her normal activities.

Plate 3.9 Rouseabout with respirable sample head Plate 3.10 Shearer with inspirable sampling head

The static samples were collected from a number of locations in the work area. The placement of the sampling device changed from farm to farm but in most cases the static samples were collected from the same relative position. The static sampling positions included “near shearers”, “near classers”, “near rouseabouts”, “near press” and “near sheep” (Plates 3.11 and 3.12). On some farms not all of these positions were sampled.

Plate 3.11 Inspirable static sampling (near sheep) Plate 3.12 Respirable static sampling (near rouseabouts)

95 Similar to respirable samples the pumps were collected from each person and from the static sample locations after completion of the shearing/sampling session. The pumps were recalibrated (using the same calibrator) to determine the flow-rate after sampling before being turned off. At the end of the work day the samples were returned to the laboratory where each filter was allowed to acclimatise in the original labelled petri dishes for 24 hours. After acclimatisation each filter was re-weighed using the same calibrated microbalance. The field blanks was also re-weighed. Calculations (see calculations section) were used to determine the concentration of the respirable dust that the workers were exposed to.

3.1.3 Calculations used to determine concentration of dust

Three calculations are needed to determine average dust exposure (AS 2985, SA, 2004a, p 12 and 13).

The first to calculate the weight of dust collected,

w = (w2 − w1 ) − (b2 − b1 )

Where- w = corrected weight of dust collected on the filter, in milligrams

w1 = weight of unladen filter, in milligrams

w2 = weight of used filter, in milligrams

b1 = weight of blank filter before sampling, in milligrams

b2 = weight of blank filter after sampling, in milligrams

The second to calculate the average flow rate (Q),

Q + Q Q = 1 2 2

and then to calculate total volume of air sampled

(Q × t) V = 1000

96 Where- Q = average flow rate, in litres per minute

Q1 = initial flow rate, in litres per minute

Q2 = final flow rate, in litres per minute t = sampling duration, in minutes V = air volume, in cubic metres

The final calculation is the determination of the average concentration (C) of dust is calculated using

w C = V

Where- C = dust concentration, in milligrams per cubic metre w = net weight of dust, blank corrected, in milligrams V = air volume, in cubic metres

3.2 Bioaerosol monitoring and analysis

The bioaerosol monitoring was undertaken using an Andersen Instruments 2-Stage Bioaerosol Sampler, connected to a SKC Hi-lite 30 suction pump operating at 28.3 L min-1. As outlined in section 2.5.2, the 2-Stage sampler uses a critical orifice to maintain this flow rate. A field rotameter supplied by Andersen Instruments, was used before and after each sampling session to ensure that flow rate was maintained. The pump was powered by an SKC 12V Power Pak battery pack (Plate 3.13).

Plate 3.13 Bioaerosol sampler

97 Different types of agar were placed on each stage with Nutrient Agar (NA) used for to utilise the correct growth of bacteria on the top stage and Malt Extra Agar (MEA) used to maximise the growth of fungi on the bottom stage. As outlined in section 2.5.2, different stages collect different size bioaerosol particles. In this study the 2-

Stage Andersen Instruments impactor the top stage had a d50 of 8.0 m and the bottom stage has a d50 of 0.95 m (Jensen and Schafer, 1998). The top stage collects the larger particles that contain the greatest concentration of bacteria, and the bottom stage was used to collect fungi particles which have a smaller mean diameter. NA plates were prepared using the mixture as directed by the manufacturer, Difco. The agar was prepared following the instructions outlined on the container. MEA made from Oxide dry material was also made up following the instructions on the container. Agar was made up and poured aseptically into sterile Sarstedt 90mm by 14mm full plate petri dishes.

3.2.1 Bioaerosol Sampling method

When in the area to be sampled the Andersen 2-Stage bioaerosol sampler was removed from its case and connected to a sampling pump using rubber tubing. The bioaerosol sampler was taken apart and appropriate agar plates were loaded into the sampler (with the lids removed) and the sampling top of the sampler was screwed on.

Sampling was carried out for 2 min, 1 min and 30 seconds. The sampling times used were the times that were developed and used for sampling in the Australian deer industry (Kift et al, 2002a; Kift et al, 2002b). This method was modified from the NIOSH method 0800 (NIOSH, 1998) which had been adopted as a standard method for indoor air sampling in the USA by NIOSH. However, the method developed by Kift et al (2002a) is considered to be the most relevant to this sampling project because it relates directly to the Australian agricultural industry. A similar method using a 2-Stage sampler was applied in an American study by Gibbs et al (2004) in the swine industry.

After the samples were collected, both sets of agar were removed and the impactor was cleaned using Livingstone 70% alcohol Liv wipes to try to ensure sterilization. The sampler was then reassembled with new NA and MEA plates and further sampling carried out. This was repeated twice for each sampling session. Samples

98 were collected while the shed was in use approximately in the middle of each working (sampling) session. The outcome of this sampling method was that six samples were collected from each session resulting in an average of 18 bacteria samples and 18 fungi samples collected each day.

Outside samples were collected using the same methodology. The only difference was that samples were only collected once each day during the middle sampling period. This produced six bacteria and six fungi samples. The placement of the collection equipment for the outside samples differed from shed to shed with the samples collected approximately 100 m from the shed (including outside holding paddocks). This sampling was not always conducted in the same direction from the shed but collected upwind of the shed so that the air sampled was not contaminated with matter that may be blown from the shed.

3.2.2 Bioaerosol Analysis

On returning to the laboratory the agar plates were placed on a sampling tray which also held three control agar plates. These plates had been out to the farm, but were not used for sample collection. The control plates were not removed from bags used to house the containers while out on site. Three other control growth plates were also made up. The control growth plates were made by taking a known microorganism (Aspergillus for the NA and Mucor for the MEA) and contaminating the plates with the microorganism. All of the plates were then incubated in separate Labec IE-18 incubators. NA plates were incubated for 2 days at 37oC and the MEA plates for 4 days at 25oC, according to the manufacturer’s recommendations. After incubation was complete the plates were removed from the incubator and on each plate the visible colonies were counted and the concentration of colony forming units (cfu) per cubic meter (m3) was calculated.

3.3 Additional parameters monitored

At each site testing was undertaken to ascertain the environmental conditions. The main environmental condition sampled for was temperature and this was done using

99 a Young Environmental Systems YES 205 Air Quality Monitor. This monitor also sampled the average concentrations of different gases in some of the sheds. Humidity is also included for 3 sheds. Temperature was taken in some sheds using the TSI VelociCALC air velocity meter when the indoor air monitor could not be used. In all cases temperature was taken in the middle of the shed.

The air velocity within the shed was measured using the TSI VelociCALC air velocity meter. The measurements for air velocity were taken for each sampling session and in most cases three different places were sampled for air velocity. Normally this included, “near the shearers”, “near the classers” and either in “the back” of the shed or the “middle” of the shed. In all cases, the average of 10 samples, the maximum and the minimum reading were collected. The three positions for the sampling were selected to get an average reading from around the shed.

3.4 Ethical approval

The sampling methods and recruitment strategies were approved by the Human Research Ethics Committee (HREC) of University of Western Sydney (UWS). The HREC Approval No is 03/100. Letters explaining the project were given to all participants (Appendix A).

3.5 Statistical analysis of data

Means and standard errors were determined for all sampling parameters of interest. Peak exposures were reported and kept in the data analysis, as these are important measurements when compared with the current exposure limits. Data were collected to be compared with the current exposure standards, though it should be recognised that inclusion of peak exposures will affect the mean concentrations calculated. Each variable was visually tested for normality using P-P plot. Levene’s test was used for testing the assumption of equality of error variance. The need for transformation was determined and was necessary if data approached normality and satisfied the assumption of equality of variance after the completion of ln(x+1) transformation.

100 The transformation of data was not necessary if data met assumptions of normal distribution and equality of variance was found without the completion of data transformation.

Significant differences in sampling region, sampling period, different job type and sample location were investigated using the analysis of variance General Linear Model (SPSS v12). The Dunnett T3 post hoc test was used to separate treatment means if F test was found to be significant.

Regression analysis was undertaken using the linear regression model (SPSS v12) or multiple linear regression model (SPSS v12). Each sampling parameter was compared to the other as well as the temperature at sampling and the number of sheep shorn during the sampling period. These were the only parameters that could be used for multiple linear regressions as they are presented as single numbers and not a range of numbers.

101 CHAPTER 4 RESULTS AND DISCUSSION

4.1 Introduction to Sampling Variables

To determine the conditions likely to generate high concentrations of dust and bioaerosols many of the variables were analysed as outlined in Section 2.6. Some of these variables may increase the dust and/or bioaerosol concentrations while others may decrease the concentrations. Not all the variables outlined in Section 2.6 could be statistically analysed. Due to climate conditions the data were not analysed according to season because temperature and humidity can vary dramatically during any one season. The majority of samples were collected in spring and summer because shearing is normally undertaken in NSW at these times of the year which reduces the variable possibilities. The indoor air temperature of the shearing shed was monitored and analysed as it may influence dust concentrations more than the season that the samples were collected in (Table 4.1).

Air velocities were not analysed as it was not possible to effectively determine them for the whole shearing shed. The static samples were collected from areas within the shed and the personal samples were collected from workers moving around the shed thus making it difficult to find the air velocities that workers would be exposed to. The openness of the shed varied throughout the day which would impact on the air velocities, thus making it difficult to standardise the results

The activity of the animals was not analysed because there is no scale to measure how much an animal moves around while in a shed during shearing. This movement would change during the day due to the animals’ individual behaviour and activity. Types of activities being undertaken in the shed were also not analysed because in all but two cases it was shearing. In those two cases the activity was crutching and the sample size was too small to statistically analyse (Table 4.1). This variation in type of activity changed the number of sheep handled. The number of sheep shorn in a shearing period was analysed against the concentration of both dusts and bioaerosols.

For a break down of the concentrations of dust or bioaerosols measured for each farm see Appendices B through to AD

102 Table 4.1 Variables associated with each farm sampled.

Region Tempera Weather conditions Number Number Type of Activity ture oC of people of sheep sheep shearing shorn/per day Farm 1 Southern Highlands 13-17 Overcast 3 400 Merino Shearing Farm 2 Southern Highlands 8-11 Fine, some clouds 2 240 Merino Shearing Overcast, storm Merino cross Farm 3 Sydney Basin 24-29 2 220 Shearing building, fair breeze Dorset Farm 4 Southern Highlands 25-31 Fine 3 450 Merino Shearing Farm 5 Central Highlands 33-39 Fine, slight breeze 6 700 Merino Shearing Fine, slight breeze, no Farm 6 Central Highlands 24-29 6 700 Merino Shearing clouds Fine, slight breeze, low Farm 7 Central Highlands 24-29 3 400 Merino Shearing fine clouds Fine, slight breeze, some Farm 8 Central West 15-17 4 630 Merino Shearing clouds Overcast, rain, fair Farm 9 Central West 15-16 4 600 Merino Shearing breeze Overcast, slight breeze, Farm 10 Central West 11-15 4 650 Merino Shearing some clouds Overcast, slight breeze Farm 11 Central West 13-17 2 850 Merino Crutching some clouds Dorset Farm 12 Central West 15-16 Fine, fine clouds 2 400 crossed Shearing Merino Fine, slight breeze, some Farm 13 Northern Highlands 15-21 4 700 Merino Shearing clouds Fine, slight breeze, some Farm 14 Northern Highlands 20-25 3 480 Merino Shearing clouds Fine, strong breeze, Farm 15 Northern Highlands 20-24 3 520 Merino Shearing some clouds Strong breeze, little rain, Farm 16 Northern Highlands 18-22 4 700 Merino Shearing storm brewing Mostly Fine, slight breeze, some Farm 17 Northern Highlands 20-24 4 650 Merino, Shearing clouds some Dorset Fine, slight breeze, some Merino cross Farm 18 Sydney Basin 35-41 2 250 Shearing clouds Dorset Breeze, storm, overcast, Farm 19 Northern Highlands 17-23 3 650 Merino Shearing rain Breeze, storm, overcast, Farm 20 Northern Highlands 16-20 3 600 Merino Shearing rain Farm 21 Northern Highlands 20-26 Overcast, slight breeze 2 400 Merino Shearing Farm 22 Northern Highlands 23-25 Overcast, slight breeze 5 1100 Merino Shearing Farm 23 Central Highlands 27-29 Sunny, strong breeze 5 700 Merino Shearing Farm 24 Central West 30-39 Sunny, slight breeze 5 800 Merino Shearing Farm 25 Central West 35-41 Sunny, strong breeze, 5 800 Merino Shearing late storm Farm 26 Central West 28-29 Sunny, Strong breeze 5 800 Merino Shearing Farm 27 Central West 31-35 Sunny, Medium breeze 4 1800 Merino Crutching Farm 28 Central Highlands 21-27 Sunny, Medium breeze 6 700 Merino Shearing Overcast, late rain, Farm 29 Central West 25-33 3 600 Merino Shearing strong breeze

103

Section 2.6 discusses the variables that may change from farm to farm or between sampling days and consequently the type of work completed by the worker and the shearing session completed during the day may influence results and will be discussed in Sections 4.5 and 4.6 respectively.

The variables that were used for analysis and will be discussed in this chapter are:

• The different job completed by workers.

• The position of the static sampling equipment.

• The regions of NSW that the data was collected from.

• The indoor air temperature of the shed when the samples were collected.

• The number of sheep shorn during each session.

• The shearing session (time of day) the samples were collected from.

• The influence of the outside concentration of contaminants.

4.2 Data analysed by the job type and static sampling

position

4.2.1 Introduction

Previous research (Simpson et al, 1999) in the wool processing industry has suggested that the earlier in the product processing chain an individual worker is the higher the potential for exposure to air contamination. This was only relevant for the personal dust exposures. The aforementioned research was completed in a wool mill where wool is cleaned and processed for manufacture which is a different work environment to that experienced by shearers harvesting wool in a shearing shed. The wool harvesting process occurs before the wool reaches the wool mill, suggesting that exposure may be different.

If there are higher concentrations of dust earlier in the processing chain in a wool mill then this may also apply to the wool harvesting process. A shearer could have

104 the highest dust exposure concentrations of all jobs monitored because the shearer works closely with the wool when liberating it from the skin of the sheep. The shearing process is the first in the wool harvesting process and may cause dust to become airborne within a shed as the wool and sheep are moved about. The second step in the wool harvesting process is the transferring of the fleece onto a table, undertaken by rouseabouts, for inspection where the broken pieces of wool are removed. Dust may be released in this process when the wool is picked up and moved from the shearing area and thrown onto a table. During this process rouseabouts are likely to have high exposure to concentrations of airborne dusts. The wool is classed (graded) by specialist wool classers who either class the wool on the rouseabouts table or at their own table. Classers are also likely to be exposed to high dust concentrations from working in close vicinity to the rouseabouts. After classing, the wool is sorted into a holding area and packed into bales by a wool presser using a mechanical press. The mechanical press may push some dust out of the wool as it is packed into the bales. It is harder to classify the stockman’s exposure because their actual position in the process is not clear, as they are moving sheep before and after they have been shorn, and it is expected that their exposure is more dependant on other variables such as temperature, humidity and the vegetation in the area that the sheep are living in (as outlined in section 2.6). Most of his/her work is also outside the shed or in the livestock handling area (away from the shearers’ area) of the shed where the sheep are not being shorn. If the climatic conditions are dry then there may be more dust released by the sheep when they move over dry ground thus increasing the stockman’s dust exposure.

105 Sheep are brought into the shed in a large mob and then divided into smaller holding pens by the stockman

Wool is removed from the sheep (sheep are shorn) by the shearer

Fleece is removed from shearing area and inspected by the rouseabouts

Fleece is classed (graded) by the classer and moved to a storage area

Fleece is moved from the storage area and pressed into bales of wool (mechanically) by the wool presser

Figure 4.2.1 The steps involved in wool harvesting in a shearing shed.

4.2.2 Mean personal respirable and inspirable dust concentrations for the different jobs undertaken

For the statistical analysis of the personal respirable dust concentrations the result for stockman has been excluded because only one sample was collected for this job type from one farm (Table 4.2.1). This farm may have had higher exposure concentrations for that job because of the design and layout of the farm.

106 Table 4.2.1 Mean (±SE) dust exposure concentrations compared to job type. Number of samples in ( )

Parameter Job Description Shearer Wool Rouseabout Stockman Wool classer presser Personal 0.43±0.12 0.98±0.32 0.37±0.10 1.35 0.02±0.01 Respirable Dust (24) (8) (55) (1) (5) (mg m-3) Personal 1.06±0.12 0.91±0.24 0.90±0.16 1.05±0.59 - Inspirable Dust (65) (10) (26) (8) (mg m-3)

The mean respirable dust concentration for the wool presser was found to be the lowest compared with other jobs (Table 4.2.1) and it is significantly lower than the job of classer (F(3, 88)=2.912, p=0.0194). There were no other significant differences between any of the other jobs. When the jobs were classified from highest personal respirable dust exposure to lowest the list is: wool classer, shearer, rouseabout and wool presser. This is close to the expected result except for the job of wool classer which was expected to have lower results. In this case the sample size for the job of classer may have been too small to adequately find the mean because many of the samples for the classer were collected from the same sampling time period and sampling area. The concentration recorded may also be affected by the different handling methods used by the wool classer. This may have biased the results as samples were not collected from all areas and different temperature ranges. The wool presser also has very low dust exposure concentrations to deal with which may suggest that much of the dust has been removed from the wool before it is pressed into bales. This low result may also have occurred because the wool presser works in an area that that is further away from the main shearer/work area. When the two main jobs sampled (shearers and rouseabouts) were statistically analysed there was not a significant difference in risk to workers depending on the job they undertook (Figure 4.2.2).

107 6.0 Respirable Dust Results Average Respirable Dust Concentrations 5.0 ) -3

4.0

3.0

2.0 DustConcentrations m (mg 1.0

0.0 Shearers Rouseabout Classer Stockman Presser Job Type Figure 4.2.2 Personal respirable dust concentrations in comparison to job type There were no concentrations measured for the wool presser relating to personal inspirable dust exposure. The highest mean concentrations were found for the job of shearer followed by stockman and then wool classer with the job of rouseabout recording the lowest mean concentrations as can be seen in Figure 4.2.3. There were sufficient samples collected for the stockman to be included in the analysis however there were no samples collected for the job of wool presser. There was no significant difference between the mean results for any of the job types.

108 6.0 Inspirable Dust Results Average Inspirable Dust Results 5.0 ) -3

4.0

3.0

2.0 Dust Concentrations (mg m Dust Concentrations 1.0

0.0 Shearers Rouseabout Classer Stockman Presser Job Type Figure 4.2.3 Personal inspirable dust concentrations compared to job type Inspirable dust has a larger aerodynamic diameter than the respirable dust (Tranter, 1999) and different job types may produce different dust size fractions. It was expected that the inspirable dust concentration would have a similar relationship to the different jobs undertaken as respirable dust. Compared with the respirable dust concentrations data the wool classer has changed position in relation to the other jobs in ranking of exposure to higher dust concentrations. However there is very little difference in exposure concentration for any of the jobs. The job of shearer was expected to have the highest concentrations and this was supported. The high mean concentration was heavily influenced by one very high recorded concentration, and if this is removed then the mean is greatly reduced. It was not known how high the mean concentrations for the stockman would be but these results show that the respirable dust concentrations were similar to that of the shearers. Exposure for the wool classer was found to be lower for inspirable dust but higher for respirable dust in relation to the other jobs. The classer was exposed to simular concentrations of inspirable dust suggesting that the dust exposure is made up of a greater percentage of respirable dust than the other jobs. The wool classer and the rouseabout had very similar inspirable dust exposures. It was expected that the mean concentrations for

109 rouseabouts would be greater, because the activity they undertake may release more dust into the air but this was not found to be the situation in this study.

4.2.3 Mean static respirable and inspirable dust concentrations for sample location

An attempt was made to locate static dust sampling apparatus in similar positions in the different shearing sheds so results between sheds could be compared. However, this was not always successful because the size and design of the shearing sheds varied greatly. In all cases samples were collected in the general area where people were working except for samples collected outside the shed. People only worked in the area outside the shed when the sheep were being moved into or out of the shed.

Outside samples were collected to give an indication of the dust concentrations outside the shed where the dust was not expected to build up. It was not known if the samples collected outside would be low, due to ambient levels, or high because of the dust generated from the sheep moving around the holding yards becoming airborne.

The “near sheep” sample was collected from the area inside the shed where the sheep are held prior to shearing. Stockmen regularly go into this area to move sheep between the pens and the shearers go into this area to collect sheep for shearing. Due to the consistent movement of sheep and people it is expected that this area could have higher dust concentrations than some of the other areas. The samples collected in the middle of the shed were from the area between where the rouseabouts, wool classer/s and presser work. This area gives a general indication of the dust concentration found in the shed as a whole and what the workers are exposed to in addition to their individual work.

110 Table 4.2.2 Mean dust concentrations at different locations throughout the shed. Number of samples in ( )

Different sampling position undertaken Near Near Near Near Near Middle of Outside Shearers Rouseabout Press Classer sheep shed Static Respirable 0.16±0.0 0.27±0.11 0.16±0.04 0.10± 0.45±0.16 0.28± - Dust 2 (2) (22) (6) 0.03 (11) (20) 0.13 (6) (mg m-3) Static Inspirable 0.65±0.0 0.51± 0.10 0.44±0.06 0.73± 0.81±0.12 0.32± 0.49± Dust 8 (82) (44) (70) 0.13 (36) (30) 0.10 (16) 0.06 (22) (mg m-3)

There was no significant difference between any of the areas sampled for either respirable or inspirable dust. However the greatest mean concentrations for both respirable and inspirable dust were collected from samples nearest the sheep (Figures 4.2.4 and 4.2.5). These data show that the sheep moving around within a building may increase the dust concentrations. The area where sheep are held is often not very well ventilated and in some areas there is no ventilation at all. This may be why stockmen had higher personal dust exposures and why shearers had higher exposures than rouseabouts.

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Monitor Location Figure 4.2.4 Static inspirable dust concentrations in relation to the location of the monitors in the shearing sheds The samples collected from the area near the classer had the lowest mean respirable dust concentration (Figure 4.2.4), which is interesting considering that the classer recorded the highest mean personal respirable dust concentrations. In most cases the dust concentrations measured near the classer were collected on different days than the days used to collect the personal dust samples from the classer. There were no outside respirable dust samples collected but the inspirable dust concentrations were found to be lowest outside, meaning that the dust generated from the sheep moving in the holding paddocks is quickly dissipated in the surrounding air.

112 6.0 Respirable Dust Concentrations Ave Respirable Dust Concentrations 5.0 ) -3

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0.0 rs ts s er p d are ou res ss hee she he eab ar P Cla r s of r S us Ne ear ea dle Nea r Ro N N Mid Nea Monitor Location Figure 4.2.5 Static respirable dust concentrations in relation to the location of the monitors in the shearing sheds Static respirable dust concentrations, ranked from highest to lowest, were: near sheep, middle of shed, near rouseabouts, near press, near shearers and finally near classers. The mean respirable dust concentration near the rouseabouts is higher than near the shearers. Results for middle of the shed were high because of all of the activity being undertaken in the shed as a whole. It is also possible that the samples collected in the middle of the shed were from an area of the shed with the lowest level of ventilation.

Static inspirable dust concentrations ranked from highest to lowest, were: near sheep, near classers, near shearers, near rouseabouts, middle of shed, near press and then outside. This is different to the respirable dust concentrations with samples collected near the classers being higher in the ranking. The middle of the shed also had lower inspirable dust concentrations than near either the rouseabouts or shearers, whereas the respirable dust concentrations were higher.

The difference in ranking of the different sampling positions when compared with dust fractions could be due to the inherent differences in the generation and movement of the different dust fractions. It should also be noted that the samples for

113 either dust fraction were collected from different sheep shearing sheds which would change and influence the general concentrations of dust found in the air.

4.2.4 Conclusion of effects of job undertaken or sample location on mean airborne dust concentration

The job with the greatest exposure to high respirable dust concentrations was the wool classer and there was a significant difference when compared with the job of wool presser. However the sample size was relatively small and collected from the same region which needs to be taken into account when interpreting the results. There was no other significant difference between the other job types. For the inspirable dust concentration there was no difference between any of the job types. This study shows that the wool classer may be exposed to greater respirable dust concentrations than the other workers in the shearing shed and this needs to be further investigated in the context of possible negative health impacts.

There was no significant difference in mean dust concentrations measured for the different sampling positions for either respirable or inspirable dust. The mean dust concentrations measured near the sheep had the highest recorded measurements, indicating that this area may have the highest exposure to dust. This area is not a place where people are regularly working but it does need to be well ventilated to assist in dust minimisation in other areas of the shed.

4.3 Data analysed by the region of NSW in which the data was

collected

4.3.1 Introduction

The potential impact of geographical region on concentrations of airborne contaminants in a shearing shed has been discussed in Section 2.6. Region as a potential sampling variable may be closely related to other variables such as temperature, rainfall and the environment that the sheep are living in. The way the

114 shearers go about shearing sheep did not seem to change between the regions in which they shear. It should be noted that shearers shear in different regions and may have been monitored in more than one region during this study, however, due to human ethics constraints it was not possible to compare the results for the same shearer when they worked in the different regions.

The five regions sampled within NSW are shown on Figure 4.3.1, they are the:

• “Sydney basin” is shown in pink. This region is centred around the town of Richmond in the outer western region of Sydney.

• “Southern highlands” is shown in dark green. This region is centred around the town of Goulburn with most of the monitoring carried out between the towns of Goulburn and Taralga.

• “Northern highlands” is shown in blue. This region includes the towns of Tamworth and Armidale with most of the monitoring carried out near the town of Walcha.

• “Central highlands” is shown in olive green. This region is centred around the town of Mudgee with most of the monitoring carried out near the township of Lue.

• “Central west” is shown in purple. The larger towns in this area include Bathurst, Orange, Cowra and Dubbo. Monitoring in this area was around the towns of Grenfell, Yeoval, Canowindra and Lyndhurst.

115

Figure 4.3.1 Regions within NSW, Australia where monitoring was undertaken

Each region has it own characteristics including, climate, soil and/or vegetation type but many of the farms in the same region may also have different characteristics such as soil and/or vegetation. This may mean that farms next door to each other could have completely different vegetation if the land has been developed. Each region also receives different levels of rainfall (BOM, 2004). The further west the region is the lower the average rainfall is as illustrated in Table 4.3.1. The Sydney basin, southern and northern highlands all have similar average rainfall. Interestingly the average temperatures for these areas showed that the Sydney basin is 5-6oC higher than the average temperature for the southern and northern highlands. The central west region has lower average rainfall and higher average temperature than the other regions. However because this region covers a large area, the average rainfall and temperature vary greatly throughout. As explained in section 2.6.2 on temperature the dryer the region the higher the expected concentrations of dust which suggests that the concentrations of dust should be higher for the central west region. Wool grown on sheep from high rainfall areas is also more likely to be heavily contaminated with bacteria and fungi compared with sheep from arid areas (Jacobs, 1994) suggesting that the wetter the area the higher the concentration of bioaerosols will be.

It should be noted that one week of testing in the northern highlands was very wet with steady rainfall for the four days samples were collected and this may have helped to reduce the airborne concentrations of dust in this region. This may mean that the northern highlands have lower concentrations of dust, but higher

116 concentrations of bioaerosols, than would have been recorded if there been no rain. The samples in all regions were collected at different temperatures which could have affected the results. This is because one region may have been visited only in winter, which may have decreased the expected concentrations. Conversely if a region was only sampled in summer the mean concentrations may be higher.

Table 4.3.1 Mean concentrations based on region ± SE. Number of samples in ( ). Highest mean concentration per parameter shown in yellow.

Sydney Southern Northern Central Cental West Basin Highlands Highlands Highlands Average 23.9 18.0 19.2 23.0 Mudgee 22.0 Cowra o Temp ( C) Richmond Taralga Walcha 19.7 Bathurst 24.5 Dubbo 24.7 Canowindra Average 801.3 804.4 808.0 674.6 637.6 Cowra Rainfall (mm) Richmond Taralga Walcha Mudgee 631.1 Bathurst 586.5 Dubbo 602.0 Canowindra Personal 0.42±0.22 0.66±0.24 0.22±0.04 0.38±0.13 0.59±0.19 (29) Respirable (8) (12) (26) (18) (mg m-3) Personal 0.34±0.05 0.60±0.06 0.64±0.11 1.56±0.22 1.57±0.22 (31) Inspirable (16) (18) (26) (18) (mg m-3) Static 0.14±0.03 - 0.15±0.03 0.13±0.03 (8) 0.47±0.14 (29) Respirable (4) (26) (mg m-3) Static 0.18±0.03 0.33±0.03 0.26±0.02 0.54±0.05 0.97±0.08 (116) Inspirable (13) (20) (104) (47) (mg m-3) Bacteria 4784±1625 1283±116 2199±236 2955±509 1852±114 (174) (cfu m-3) (36) (54) (156) (78) Fungi 2111±256 1631±140 1404±142 3679±332 2069±129 (174) (cfu m-3) (36) (54) (156) (78) Table 4.3.1 contains the mean concentrations of all of the different air pollutants that were sampled for. In all cases two regions were sampled more than the other regions. The central west” always had the highest number of samples collected and the

117 northern highlands had the second highest number of samples for all parameters. The Sydney basin area had the lowest number of samples collected for each parameter.

4.3.2 Mean personal and static respirable and inspirable dust concentrations for each region sampled

The different fractions of sampled dusts behaved in the same way and for this reason will be discussed together. There was no significant difference found in any of the regions for respirable dust concentrations. For both the personal and static inspirable dust samples the region with the highest mean concentration was the central west (Figures 4.3.2 and 4.3.3). This was expected because of the lower rainfall in this area which allowed the dust to have a lower moisture content which reduces the binding power of the particles. If rainfall is reduced the concentration and abundance of vegetation may also be reduced which leads to an increase in exposed topsoil. This topsoil can then become an airborne fine particulate if sheep move over this ground and cause the soil to release dust. If sheep are moved near the shed this airborne soil can, provided the air is moving in the right direction, blow into the shed.

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Region Figure 4.3.2 Personal inspirable dust concentrations in relation to the region of NSW that was sampled The central west was sampled during winter and summer in an attempt to reduce the bias that may exist if only one season was sampled. Repeat monitoring in this region was important as it has low average temperatures in winter and high average temperatures in summer when compared with other regions sampled. In summer the region is much dryer which should result in higher concentrations of dust. For mean personal samples of inspirable dust the central west was found to have a significant difference from southern highlands (F(4,104)=14.933, p<0.001), Sydney basin (F(4,104)=14.933, p<0.001), and northern highlands (F(4,104)=14.933, p=0.001) but not the central highlands (Figures 4.3.2. and 4.3.4). For static inspirable dust samples there was a significant difference between the central west and southern highlands (F(4,295)=29.720, p<0.001), Sydney basin (F(4,295)=29.720, p<0.001), northern highlands (F(4,295)=29.720, p<0.001) and central highlands (F(4, 295)=29.720, p=0.001), that means that there was a significant difference between the central west and all of the other regions (Figure 4.3.4).

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0.0 ds sin ds est ds hlan Ba hlan l W hlan Hig ney Hig tra Hig rn yd ral Cen rn the S ent rthe Sou C No Monitoring Region Figure 4.3.3 Personal respirable dust concentrations in relation to the region of NSW that was sampled The central highlands had the second highest mean concentrations of inspirable dust for both personal and static sampling. This was expected because this region receives on average, less rainfall than some of the other regions. However the results recorded for the respirable dust do not reflect this as this region recorded some of the lowest mean respirable dust concentrations (Figures 4.3.4 and 4.3.5). This region was sampled in summer in most cases which may have affected results. Lower concentrations of respirable dust were found with the middle temperature ranges and this is discussed in Section 4.4. Also this section outlined the fact that mean respirable dust concentrations were highest when the temperature was highest but when temperature was not in the highest range the respirable dust was reduced. This is what seems to have happened in this case. The central highlands were found to be significantly different for static inspirable dust concentrations from the southern highlands (F(4,295)=29.720, p=0.017), Sydney basin (F(4,295)=29.720, p<0.001), northern highlands (F(4,295)=29.720, p<0.001) and central highlands (F(4, 295)=29.720, p=0.001), which means that there was a significant difference between the central west and all of the other regions (Figure 4.3.4).

120 6.0 Inspirable Dust Concentrations Ave Inspirable Dust Concentrations 5.0 ) -3

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0.0 ds sin ds est ds hlan Ba hlan l W hlan Hig ney Hig tra Hig rn yd ral Cen rn the S ent rthe Sou C No Region Figure 4.3.4 Static inspirable dust concentrations in relation to the region of NSW that was sampled The central highlands region was found to be significantly higher for the personal samples of inspirable dust compared with southern highlands (F(4,104)=14.933, p=0.001), Sydney basin (F(4,104)=14.933, p<0.001) and northern highlands (F(4,104)=14.933, p=0.001), but not the central west (Figure, 4.3.2).

The results from the Sydney basin showed that this region had the lowest concentrations of inspirable dust of all the regions but it had higher respirable dust concentrations than one other area for static samples and two other areas for the personal sampling. It was expected that the Sydney basin, southern and northern highlands would have similar results for most of the dust samples collected as these regions had similar average recorded rainfall. The theory of similar results for these regions is supported by the results collected. There was a significant difference between the southern highlands and the Sydney basin for both personal (F(4,104)=14.933, p=0.036) and static (F(4, 295)=29.720, p=0.034) inspirable dust sampling but there was no significant relationship between the three regions for respirable dust samples.

121 The samples from the southern highlands were collected in winter and this was expected to reduce the measured concentrations of dust. However this did not occur for personal respirable dust concentrations and there does not appear to be a clear reason why this area recorded highest personal respirable dust concentrations of all of the sampled regions. It should be noted that only three sheds were tested in this region and they were recorded at one time/season period.

There were fewer respirable dust samples collected and this may help to explain why the mean respirable dust concentrations do not seem to follow the expected pattern that the inspirable dust followed. The dust concentrations measured in the southern highlands were not expected but that may be because the samples were collected in winter and shearers generally keep the shearing building closed up which allows the dust concentrations to build up. This is discussed in the temperature discussion Section 4.4.

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0.0 sin ds est ds ds Ba hlan l W hlan hlan ney Hig tra ig ig yd ral Cen rn H rn H S ent rthe the C No Sou Region Figure 4.3.5 Static respirable dust concentrations in relation to region of NSW that was sampled

4.3.3 Mean bacteria and fungi concentrations for sample region

The mean bacteria concentrations measured were lowest in the southern highlands (Figure 4.3.6, Table 4.3.1) and this region was sampled during late winter/early

122 spring. Sampling during these seasons meant that the average temperature of the area was expectantly lower than if the samples were collected in summer. This means that the growth of certain microorganisms was reduced as the sampling was in the lower temperatures and is further explained in the variables section on temperature, Section 2.6. On this basis it was expected that the concentrations for the southern highlands would be low for both bacteria and fungi and this was the case for bacteria. Fungi recorded the second lowest mean concentration compared with the other regions. There was a significant difference between the southern highlands and the Sydney basin results for mean bacteria concentrations (F(4, 493)=6.429, p=0.008). There was also a significant difference for fungi concentration between the southern highlands and the area with the highest mean concentrations - the central highlands (F(4, 493) =17.213, p<0.001).

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0 ds sin ds est ds hlan Ba hlan l W hlan ig ney ig tra ig rn H yd ral H Cen rn H the S ent rthe Sou C No

Region

Figure 4.3.6 Bacteria concentrations in relation to region of NSW that was sampled The central highlands recorded the highest mean fungi concentrations and the second highest mean bacteria concentrations (Figure 4.3.6 and 4.3.7). The area with the highest mean bacteria concentrations was the Sydney basin which also had the

123 second highest mean fungi concentrations. It is hard to explain why these areas had such high concentrations. The Sydney basin receives similar rainfall to the northern and southern highlands which would suggest that the concentrations of bioaerosols should be similar but they were not. However the Sydney basin was only sampled twice and one of the sampling days had very high concentrations which increased the mean concentrations. The mean concentrations were also influenced by the time that the sampling was conducted. In the case of the Sydney basin all samples were collected in spring as this is the time when the bacteria and fungi would be at their peak growing phase.

20000 Fungi Concentrations 18000 Ave Fungi Concentrations

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0 ds sin ds est ds hlan Ba hlan l W hlan Hig ney Hig tra Hig rn yd ral Cen rn the S ent rthe Sou C No Region Figure 4.3.7 Fungi concentrations in relation to region of NSW that was sampled The high concentrations for both bacteria and fungi in the central highlands were unexpected as the sampling was conducted in summer and this area is relatively dry in comparison to the other regions. It was expected that this region would have the lowest concentrations, because it is relatively hot and dry. The high concentrations may be influenced by the other factors involved including the animal movements in and out of the shed and the area in which the animals are living. The living area may

124 be prone to producing a higher concentration of bioaerosols during the time period that was sampled.

4.3.4 Conclusion of effects of region on airborne concentration

Region plays an important role in determining the possible concentrations of dust and bioaerosols to which a worker may be exposed. It does not play a role in isolation but works in conjunction with other variables in particular sampling seasons and temperatures. The other variables that need to be considered are the local vegetation, such as grasses, and vegetation found in the surrounding paddocks. The local vegetation can be specific for the region in which the sampling is carried out but can vary greatly even in one sampling region. For dust it seems that the main conclusion to be drawn is the further west in NSW the samples are collected, and the dryer it is, the higher the concentration of dust measured. There does not seem to be a similar relationship for bioaerosols.

If a person is working in a western region shearing shed, particularly in an environment with high temperatures, it is advisable that they take precautions to try and reduce the concentration of airborne dusts and bioaerosols that they are exposed to.

4.4 Data analysed by taking into account the indoor temperature on the day that dust and bioaerosol samples were collected

4.4.1 Introduction

General information about the possible impact of temperature on dust and bioaerosol concentrations has been previously discussed in Section 2.7.2. The actions of the shearers and aspects of shed “set-up” were observed to alter in response to temperature change. For example, when a building is hot or cold the way the building is ventilated will change. When the shearers feel hot they are more likely to

125 open all of the available windows in a building and use a fan (if available) to help increase the airflow. This may increase the movement of airborne (unbound) dust and bioaerosols into the building from outside (Pillai and Ricke, 2002). When the air temperature is “hotter” the relative humidity is normally lower. Therefore the moisture concentration that would normally help to reduce the amount of free airborne particles is reduced. Lower relative humidity can increase the amount of airborne dust (Vincent, 1980). In some cases the open windows are next to holding yards where the sheep are penned. In hot conditions the opening of windows and doors may allow movement into the shed of airborne particles that are released when the sheep are moved into the shed from these holding yards. This was not always the case in the sheds studied and is closely related to the location of the shed in relation to the surrounding paddocks. For these reasons it has been suggested that the concentrations of both dust and bioaerosols will increase as temperature increases.

When a building is colder the shearers are more likely to want the ventilation within a building reduced so that the working environment stays warmer. The closing of the building may result in airborne particulate matter generated inside the building not being able to be removed and the concentrations may increase. This is only true for the airborne material that is generated inside the shed.

Table 4.4.1 contains the mean concentrations of all the different parameters that were measured.

126 Table 4.4.1 Mean concentrations of dusts and bioaerosols in relation to ambient indoor temperatures (± SE) measured inside the shearing sheds sampled in this study. Number of samples in ( )

Temperature Range (OC) Parameter 0-10 11-20 21-30 31-40 Personal Respirable 0.60±0.19 0.45±0.20 0.33±0.06 (49) 0.70±0.20 (15) Dust (mg m-3) (4) (24) Personal Inspirable 0.64±0.12 0.81±0.10 0.90±0.12 (58) 1.91±0.34 (15) Dust (mg m-3) (2) (34) Static Respirable 0.3±0.14 0.22±0.08 (34) 0.37±0.13 (11) Dust (mg m-3) (22) Static Inspirable 0.27±0.03 0.43±0.04 0.47±0.04 (151) 1.20±0.14 (50) Dust (mg m-3) (6) (93) Bacteria (cfu m-3) 1232±255 2185±230 2428±296 (252) 2176±162 (78) (12) (156) Fungi (cfu m-3) 1175±194 1600±154 2154±135 (252) 2866±202 (78) (12) (156)

4.4.2 Mean personal respirable concentrations for each temperature range

The mean personal respirable dust concentrations were highest when the temperature decreased or increased from the middle temperature ranges (Figure 4.4.1). The temperature range with the highest mean personal respirable dust was 31-40oC (0.70 mg m-3). The lowest mean personal respirable dust concentration was recorded within the temperature range of 21-30oC (0.33 mg m-3). It should be noted that the majority of samples were collected during the temperature ranges of 11-20oC (24 samples) and 21-30oC (49 samples). Only one farm was monitored in the 0-10oC temperature range (Farm 2) and the data for this temperature range may not be representative of the effects of temperature on air quality but may have been due to other factors, on this farm, such as layout and design of the shed.

Although differences between personal respirable dust concentrations across the different temperature ranges were not significant (Figure 4.4.1 and Table 4.4.1) the data supports the argument that changes that occur within a shed when it is either too

127 hot to too cold, such as opening or closing windows, can have an effect on air quality.

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0.0 0-10 11-20 21-30 31-40 Temperature Ranges (oC) Figure 4.4.1 Personal Respirable dust concentrations measured in relation to a range of temperatures The expected outcome was that the respirable dust concentrations would increase as the temperature increased. This was expected because respirable dust particles may become less bound to the surrounding environment as the temperature increases. The results in this study do not support this concept because there is not a linear relationship between temperatures and mean personal respirable dust concentrations. Statistical analysis of the data showed that the personal respirable dust concentration was not influenced by the temperature at which the sample was collected. The second highest mean concentration was found in the lowest temperature range which may indicate that the actual lay out and design of the shed was more important than what the temperature was when work was being carried out. In this case the altering of the ventilation design of the building by closing windows may have led to an increase in the concentration of pollutant build up.

128 4.4.3 Mean personal inspirable concentrations for each temperature range

The mean personal inspirable dust concentrations were the highest when the temperature was highest and the data shows an increasing trend in concentration as temperature increases (Figure 4.4.2). It should be noted that many more samples were collected for the two middle temperature ranges, 34 samples for 11-20oC and 58 samples for 21-30oC, but only one farm was in the 0-10oC (Farm 2) range so data collected at each end of the temperature spectrum requires careful interpretation. A significant relationship was found between the different temperature ranges (r=0.213, p= 0.019) and personal inspirable dust concentrations. The highest individual result was recorded in the temperature range of 21-30oC but, again, this was based on one measurement and should be used as a guide only.

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Figure 4.4.2 Personal Inspirable dust concentrations measured in relation to a range of temperatures The means for personal inspirable dusts rose as the temperature increased and this was expected because, similar to respirable dust particles, the inspirable dust particles would become less bound to the surrounding environment as the temperature increased. The inspirable dust fraction is larger in size than the respirable fraction and as the temperature increased this may have reduced the

129 binding power of the moisture content. Because the particles are larger they need more moisture to bind together, and to the surrounding environment, so may be more susceptible to an increase in temperature. Statistical analysis of these data showed that the personal inspirable concentrations were influenced by the temperature the samples were collected in (r=0.213, p= 0.019). The data supports the proposition that an increase in inspirable dust concentration is strongly correlated to increases in ambient indoor temperature and that this increase is less dependant on the design of the shed than the respirable dust fraction. However, even if ventilation for the shed is changed the concentration of inspirable dust will probably still increase.

4.4.4. Mean static respirable concentrations for each temperature range

The mean static respirable dust concentrations were highest when the temperature decreased or increased from the middle temperature range (Figure 4.4.3) and this trend was similar to the concentrations recorded for personal respirable dust. Like the personal respirable dust results the highest mean was found in the temperature range of 31-40oC (0.37 mg m-3) and the lowest was found in the range of 21-30oC (0.22 mg m-3). Unlike for personal respirable dust there was no static respirable dust concentration recorded for the 0- 10oC temperature range because no static respirable dust samples were collected from the one farm that was monitored in this temperature range. Like personal respirable dust results there was no significant difference between the different temperature ranges. This could be due to the small range between the highest and lowest mean concentrations of 0.15 mg m-3. The highest static mean concentration was found in the range of 11-20oC on Farm 10. The highest individual personal respirable dust concentrations were also found at this farm, and this data indicates that Farm 10 had the highest concentrations of respirable dust in the general environment that the workers were exposed.

Similar to the personal respirable results it was expected that respirable dust concentrations would increase as the temperature increased. The data again does not support this idea. Similar to the results for personal respirable dust the highest mean concentration was found in the hottest temperature range and this does support the idea that the hotter it is the more dust will be released. The results were not linear

130 (Figure 4.4.3), rejecting the idea that respirable dust will increase as temperature increases. Statistical analysis of these data showed that the concentration of airborne personal respirable dust was not influenced by the temperature that the samples were collected in.

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Figure 4.4.3 Static respirable dust concentrations measured in relation to a range of temperatures

4.4.5. Mean static inspirable dust concentrations for each temperature range

Similar to personal and static respirable mean dust concentrations the mean personal and static inspirable dust concentrations follow the same patterns. That is, the mean static inspirable dust concentrations were the highest when the temperature range was highest. The highest mean was found in the temperature range of 31-40oC (1.20 mg m-3) as seen in Table 4.4.1. The lowest was found in the range of 0-11oC (0.27 mg m-3). It should be noted that many more samples were collected for the two middle temperature ranges, 93 samples for 11-20oC and 151 samples for 21-30oC. Again only one farm was monitored in the 0-10oC (Farm 2) with 6 samples collected on this farm.

131 In the same way that the personal inspirable dust concentrations supported the expected results that the dust concentration would increase as the temperature increased, the static concentrations also increased (Figure 4.4.4). The possible reasons for the increase of this dust fraction have been previously discussed in Section 4.4.3 on personal inspirable dust concentrations. However, the increased concentration indicates that as temperature increases the static (and hence general shed) exposure to inspirable dust will also increase. Like the personal inspirable dust the statistical analysis showed that the static inspirable concentrations were influenced by the ambient temperature at the time of sample collection (r=0.249, p= 0.014). This increase seems to be less reliant on the design and layout of the shed than the respirable dust fraction. The results support the argument that even if ventilation in the shed is changed the static inspirable dust concentration will still increase as temperature increases.

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Figure 4.4.4 Static inspirable dust concentrations measured in relation to a range of temperatures

132 4.4.6 Mean bacteria concentrations for each temperature range

Mean bacteria concentrations were highest when the temperature was in the middle temperature ranges (Figure 4.4.5). The highest mean was found in the temperature range of 21-30oC (2428 cfu m-3). The lowest was found in the range of 0-10oC (1232 cfu m-3). It should be noted that more samples were collected for the two middle temperature ranges 156 samples for 11-20oC and 252 samples for 21-30oC. Only one farm was monitored in the 0-10oC temperature range (Farm 2) so the low mean concentrations in this range were all collected from the one farm. There was not a significant relationship found between bacteria and the different temperature ranges. This may be due to the lowest temperature range being unable to be used in the analysis and the other three concentrations being relatively close together. The highest individual farm mean results were found in the range of 21-30oC.

60000 Bacteria Concentrations Ave Bacteria Concentrations

) 50000 -3

40000

30000

20000

Bacteria Concentration (cfuConcentration m Bacteria 10000

0 0-10 11-20 21-30 31-40 Temperature Ranges (oC)

Figure 4.4.5 Bacteria concentrations measured in relation to a range of temperatures The reason for the higher concentrations being in the middle temperature range is that the bacteria grow best in the range of 15-40oC. This is expected because in many of the places where the samples were collected the mean temperature throughout the

133 year would be in this range. A microorganism can usually only survive within the temperature range that it is most accustomed to. As outlined in Section 2.7.2 there are temperature ranges that allow certain microorganisms to grow and if a microorganism is not accustomed to that temperature range they will not multiply. This may explain why the lowest mean concentration was measured in the shed in the lowest temperature range as it was too cold for the living microorganisms to multiply.

With airborne microorganisms it would be more important to look at the temperature of the preceding week/s than the temperature of the sampling day. Microorganisms take time to grow and reproduce and are dependant on the species of organisms present in the environment monitored. Even if the temperature conditions for growth and reproduction were perfect on one day this may not be enough to increase the airborne concentration of microorganisms if the temperature has not been in the ideal range for a period of time.

Statistical analysis showed that bacteria concentrations were not influenced by the temperature that the samples were collected in. The results seem to support the concept that ambient indoor temperature at the time of monitoring influenced the concentration of bacteria found at each farm however the data analysis did not support this. This would indicate that other variables which may include shed layout and design, season, region and the general environment in which the sheep are living have a greater influence on the concentration of airborne bacteria than temperature.

4.4.7 Mean fungi concentrations for each temperature range

The mean fungi concentrations were highest when the temperature was in the highest temperature range (Figure 4.4.6). The highest mean was found in the temperature range of 31-40oC (2866 cfu m-3). The lowest was found in the range of 0-10oC (1175 cfu m-3). It should be noted that more samples were collected for the two middle temperature ranges, 156 samples for 11-20oC and 252 samples for 21-30oC. Only one farm was actually in the 0-10oC range (Farm 2) so the low mean concentrations from this range were all collected from the one farm. A significant positive relationship was found between airborne fungi concentrations and the different temperature

134 ranges (r=0.228, p=0.044). The highest individual mean results were found in the range of 21-30oC at Farm 6.

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Figure 4.4.6 Fungi concentrations measured in relation to a range of temperatures

It was expected that the airborne concentration of fungi would increase as the temperature increased however it was not clear if the highest concentrations would be found in the highest temperature range or second highest (as found for bacteria). In the case of fungi there was a linear increase in concentration as temperature increased (Figure 4.4.6). The possible reasons for the fungi concentration increase as temperature increased are the same as for bacteria. Fungi behave and grow in certain environments better then others just as bacteria do. The low airborne fungi concentrations in the lowest temperature range were similar to bacteria and this was expected as these temperatures are not commonly experienced in NSW during the shearing season. This may mean microorganisms that normally grow at the lower temperatures will not thrive during the normal shearing period.

Statistical analysis showed that the fungi concentrations were influenced by the ambient temperature when sampling was undertaken (r=0.228, and p=0.44). This analysis supports the concept that fungi concentrations are influenced by the temperature when samples are collected.

135 4.4.8 Conclusion of effects of temperature on airborne concentration of contaminants

There is a significant linear relationship between temperature and fungi but not one between temperature and bacteria. This does not mean that there is no relationship just that the relationship is not linear. Most fungi are able to release spores, but only certain bacteria can do this, which allows for their survival during periods when the temperature is not optimal. This may help fungi that prefer higher temperatures to survive in cool environments until the preferred temperature for growth and reproduction is reached and they can start growing and reproducing again.

Of the parameters tested the only ones that were influenced by temperature were inspirable dust, both personal and static, and fungi concentrations which increased as temperature increased. The results of this study suggest that respirable dust and bacteria concentrations are not influenced by the temperature of the surrounding environment. When this is related to a shearing shed environment it is deduced that the higher the ambient indoor temperature is, the higher the concentrations of inspirable dust and fungi the shearers will be exposed to. From the lack of relationship between respirable dust and bacteria with temperature it can be suggested that shed design and layout plays a role in regulating the concentration of dusts and bioaerosols that a shearer will be exposed to. Hence, if a relatively hot day is being experienced and all windows are open to allow for air flow, it is suggested that windows and doors be closed when sheep are being moved in from the surrounding paddocks to reduce the dust and bioaerosol concentrations inside the building. If it is a cold day and all of the windows and doors are closed then they should be opened 2-3 times a day to increase ventilation and therefore reduce the build up of contaminants in the building.

136 4.5 Analysis of dust and bioaerosol concentrations according

to the number of sheep shorn in a session

4.5.1 Introduction

The potential impact of a change in the number of sheep shorn in relation to the concentrations of airborne contaminants in a shearing shed has been previously discussed in Section 2.6.7. Sheep number as a sampling variable may be closely related to other variables such as temperature, rainfall and type of animal living areas. The activities of the shearers can differ when they shear in different environments and this may change the number of sheep that they may be able to shear in a day. If the climatic conditions are relatively hot or cold then the number of sheep that get shorn in a day may reduce because of the added stress that this physical change may have on the shearers’ body. Another variable that is important in determining the number of sheep shorn is the type of shearing being undertaken. If the sheep are being ‘crutched’, then the number of sheep shorn will greatly increase as this process takes less time than shearing the whole sheep. Shearers reported, anecdotally, that crutching was a dustier activity than normal shearing activities. They report that when they are crutching more dust can be seen in the air. The number of sheep shorn is an average per session and is greatly affected by the number of shearers working at the time. In most cases the more shearers there are the more sheep they can shear, but this does depend on the skill level of the shearer. A very good shearer can shear twice as many sheep as a less talented shearer, and most shearers’ average between 25 and 50 sheep shorn per session.

It is expected that as the number of sheep shorn during a session increases then the concentration of dusts measured will also increase. Animal activity can also greatly influence the concentration of dusts and bioaerosol produced and the concentrations are always higher when animals are fed, handled or moved (ISU, 1992). Dust and bioaerosol concentrations rise when animals are feeding because of a general increase in activity (Pearson and Sharples, 1995). The generation of dust has been reported by Gustafsson, 1999, as proportional to the number of animals present in the

137 shed. As the number of sheep shorn increases the general movement of people and animals through the shed also increases.

Whenever an animal is brought into the shed there is potential for that animal to release dusts and bioaerosols by either the movement of the animal itself or by the animal running into the building and releasing dusts and bioaerosols from the surrounds. It is expected that as more animals are moved through the shed they will increase the concentrations of dust measured. It is harder to know what to expect in regards to increases or decreases in the concentration of bioaerosols as no reports have been published in the literature in relation to these two parameters. If more animals are brought through a shed then it is expected that they will release more bioaerosols both from themselves and their surrounds. However if a lot of animals are brought through the shed then it may reach a point where all of the bioaerosols have been released from the surrounding environment and hence the concentration does not increase. Also bioaerosols may be more dependent on variables other than sheep number and in particular the season and temperature that were present in the time period before sampling occurred.

Table 4.5.1 contains the mean concentrations of all the air contaminants measured. On the majority of days monitored less than 200 sheep were shorn per session. The number of sheep shorn per session range of between 151 and 200 had the greatest number of samples collected for each sampling parameter. Ranges 51-100 and 101- 200 also had a large number of samples collected making it easier to determine if a possible link exists. The higher numbers of sheep shorn per session of 201-250, 251- 300 and 401-450 only had one sampling day each. This makes it harder to determine if the number of sheep shorn per session influences the concentrations of dust and bioaerosols that workers may be exposed to.

138 Table 4.5.1 Mean concentrations based on the number of sheep shorn per shearing session ± SE. Number of samples in ()

Parameter Number of sheep shorn per shearing session 51-100 101-150 151-200 201-250 251-300 301-350 351-400 401-450 Personal 0.32±0. 0.45±0. 0.44±0. 0.28±0. 0.19±0. 1.42±0. Respirable Dust 09 (22) 12 (21 ) 14 (41) 02(3) 10 (3) 11(3) (mg m-3) Personal 0.46±0. 0.94±0. 1.38±0. 0.87±0. 0.28±0. 4.14±0. Inspirable Dust 05 (38) 13 (21 ) 14 (41) 17(3) 05 (3) 99(3) (mg m-3) Static Respirable 0.14±0. 0.14±0. 0.37±0. 0.37±0. 0.02±0. 0.93±0. Dust (mg m-3) 03 (12) 02 (15) 13 (31) 27(3) 01 (3) 31(3) Static Inspirable 0.31±0. 0.41±0. 0.68±0. 0.48±0. 0.09±0. 2.23±0. Dust (mg m-3) 04 (56) 03 (69) 05 15(12) 03 (12) 42(12) (139) Bacteria (cfu m-3) 2805±5 2549±3 2071±2 925±29 1589±1 1831±2 08 27 05 2(18) 14 (18) 71 (18) (120) (108) (216) Fungi (cfu m-3) 1821±1 1825±2 2436±1 1002±1 838±95 3068±3 29 10 59 33 (18) (18) 13 (18) (120) (108) (216)

4.5.2 Mean personal and static respirable and inspirable dust concentrations for each range of sheep shorn per session at each farm

The concentrations of different dust parameters sampled seemed to increase or decrease when the number of sheep shorn increased or decreased respectively. All of the dust parameters will be discussed together in this section.

As previously mentioned sheep shorn per session ranges of 201-250, 251-300 and 401-450 only had one farm sampled in each range. The highest concentrations of inspirable and respirable dust for both the static and personal samples were found in the number of sheep shorn per session range of between 401 and 450. This farm was sampled in summer which also would have increased dust concentrations as discussed. The higher temperatures result in more dust being released into shearing sheds. The farm was located in the central west area of NSW which was the region that was expected to have the highest recorded dust concentration because it was also

139 the driest area. There were 4 shearers working on the day of monitoring but the activity undertaken was crutching which explains why so many sheep could be shorn per session. The activity of crutching was also expected to increase the concentrations of dust found as more sheep can be moved through the shed in a short space of time. The low number of samples collected for this number of sheep shorn per session makes it difficult to determine if it was the number of sheep being handled that caused the increase in dust concentration or the influence of the other variables.

The sheep shorn per session range 201-250 was for a farm that was sampled in winter, which is expected to reduce dust exposure, and was located in the central west, which is expected to increase dust exposure. There were only two shearers operating on this day but they were crutching which is why the number of sheep shorn is higher then average for two shearers. In this case the mean concentrations of dust were lower than the mean for the range of 150-200 except for static respirable dust where it is the same. It would appear in this case that other variables played a role in reducing the mean concentrations of dusts.

The farm in the sheep shorn per session range of 251-300 was sampled in spring and in the northern highlands of NSW and had average rainfall when compared to other sampling regions. The sampling was undertaken during a wet period and this would reduce dust concentrations but may help to increase bioaerosol concentrations. This farm had the lowest concentrations for all the types of dust sampled but this may be because of the design and location of the shed. This shed was sampled after four days of rain and recorded the lowest concentrations of dusts of all the farms sampled in that week. This sheep shorn per session range had the lowest mean concentrations but the results were recorded from only one shed so the overall trend of the dust concentrations increasing as the number of sheep shorn increases may not be reflected in these results.

When looking at the trends for the four dust parameters sampled the only sample ranges that can be considered are for the three ranges of sheep shorn per session between 51 and 200. There are noticeable trends between the three sheep number ranges (Figures 4.5.1, 4.5.2, 4.5.3, and 4.5.4). The personal respirable dust

140 concentrations recorded in this study were found to have a significant relationship to the number of sheep shorn (r= 0.433, p=0.001).

6.0 Respirable Dust Concentrations Ave Respirable Dust Concentrations 5.0 ) -3

4.0

3.0

2.0 Dust Dust Concentrations(mg m 1.0

0.0 0 0 0 0 0 0 0 0 0 0-5 -10 -15 -20 -25 -30 -35 -40 -45 51 101 151 201 251 301 351 400

Sheep Number Figure 4.5.1 Personal respirable dust concentrations relative to the number of sheep shorn in a day

The static respirable dust concentrations (Figure 4.5.2) were not found to be significant in their relationship to the number of sheep shorn. However the concentration of static respirable dust was found to have a significant relationship with static inspirable dust concentration (r=0.429, p= 0.019). This is expected as outlined in Section 2.2.1 because respirable dust is a smaller fraction of inspirable dust. The static inspirable dust was found to have a significant positive relationship with the number of sheep shorn (r=0.492, p=<0.001).

141 6.0 Respirable Dust Concentrations Ave Respirable Dust Concentrations 5.0 ) -3

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0.0 0 0 0 0 0 0 0 0 0 0-5 -10 -15 -20 -25 -30 -35 -40 -45 51 101 151 201 251 301 351 400

Sheep Number

Figure 4.5.2 Static respirable dust concentrations relative to the number of sheep shorn in a day

Personal inspirable dust was also found to have a significant relationship with the number of sheep shorn (r=0.492, p<0.001). Statistical analysis showed that the concentration of dust is related to the number of sheep shorn, with an increase in the number of sheep shorn producing an increase in the concentration of dust (Figure 4.5.4).

The dust concentration means from the range of sheep shorn per session showed that there was a general trend for each parameter that the dust concentrations increased as the number of sheep shorn per session increased. For personal respirable dust the mean concentrations were found to be greatest in the sheep shorn per session range of 101-150, but this was only 0.01 mg m-3 greater than the 151-200 range which also had a greater standard error. The static respirable dust (Figure 4.5.2) had a similar mean for sheep shorn per session ranges of 51-100 and 101-150. This possibly explains why there was no statistical significance found for this parameter. There were more samples collected for the inspirable dust fraction (Figure 4.5.3) and a significant positive relationship was shown for this parameter as the number of sheep shorn per session increased.

142 5.0 Inspirable Dust Concentrations Ave Inspirable Dust Concentrations

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0.0 0 0 0 0 0 0 0 0 0 0-5 -10 -15 -20 -25 -30 -35 -40 -45 51 101 151 201 251 301 351 400

Sheep Number

Figure 4.5.3 Static inspirable dust concentrations relative to the number of sheep shorn in a day

It was expected that the dust concentrations would increase as the number of sheep shorn per session increased and this is supported by the data. This means that the sheep and the interaction between sheep and shearer does release dust into the environment.

143 6.00 Inspirable Dust Concentrations Ave Inspirable Dust Concentrations 5.00 ) -3

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0.00 0 0 0 0 0 0 0 0 -10 -15 -20 -25 -30 -35 -40 -45 51 101 151 201 251 301 351 400

Sheep Number Figure 4.5.4 Personal inspirable dust concentrations relative to the number of sheep shorn in a day

4.5.3 Mean bacteria and fungi concentrations for each range of sheep shorn per session at each farm

Similar to the dust parameters, most bioaerosol samples were collected for sheep shorn per session in the range between 51-200 (bacteria and fungi sampling). As has been previously discussed it was hard to predict what trend the concentrations of bioaerosols would follow and neither bacteria nor fungi were found to have a significant relationship with the number of sheep shorn. Hence other variables are more influential in the production of bioaerosol concentrations.

144 20000 Bacteria Concentrations Ave Bacteria Concentrations ) -3 15000

10000

5000 Bacteria ConcentrationBacteria (cfu m

0 0 0 0 0 0 0 0 0 0 1-5 -10 -15 -20 -25 -30 -35 -40 -45 51 101 151 201 251 301 351 400

Sheep Number Figure 4.5.5 Bacteria concentrations relative to the number of sheep shorn in a day

The mean concentrations of bacteria seem to decrease as sheep number increases (Figure 4.5.5) but this was not significant. The highest mean concentration was found when the least sheep were shorn. This may suggest that the bacteria concentration started at a high concentration and decreased as the sheep destroyed the environment the bacteria were living in. It is possible that when the sheep enter the environment they release the bacteria into the air but as more sheep are brought into the environment the bacteria can no longer grow and a point is reached where all available bacteria have been released into the air. It is also possible that with less sheep the bacteria have less wool to attach to and when released into the air, from the surrounding indoor environment, are not trapped in the wool of the sheep. When less sheep are shorn the shearing shed is normally smaller in size. This may encourage the bacteria to build up in the air after it is brought into the shed attached to the sheep and released into the air. In a bigger shed that same concentration of bacteria may be brought in on sheep but may be dispersed throughout the larger shed and therefore the concentration of bacteria is decreased. The movement of a larger number of sheep may in fact help to disperse the bacteria.

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Figure 4.5.6 Fungi concentrations relative to the number of sheep shorn in a day

The mean fungi concentrations were greatest when the number of sheep shorn was the largest. The highest concentration was found in the range 401-450 sheep shorn per session. When sheep shorn ranges that had only one farm monitored were excluded the highest concentration was still found in the sheep shorn per session range of 151-200. The fungi concentrations behaved in a similar manner to the mean dust concentrations in that they increased as the number of sheep shorn increased, as seen in Figure 4.5.6. However unlike the dust concentrations the fungi concentrations, in relation to sheep shorn, were not found to be significant. The reason that the fungi behaved in a simular pattern to dust and the bacteria behaved in the opposite way is not clear. The fungi may be more easily released from their growing environment by greater sheep number. It is also possible that there were more fungi growing, either in the shearing environments or on the sheep, and when the sheep were moved into the building more fungi could be released before that point was reached where there was no more available fungi to be released.

146 4.5.4 Conclusion of effects of number of sheep shorn per session on airborne concentration

The number of sheep shorn plays an important role in determining the possible concentrations of dust and bioaerosols to which a worker may be exposed. This role is statically significant for personal respirable and inspirable dust and also static inspirable dust. This is significant as it shows the number of sheep shorn to be an important variable that controls the concentration of dust that a person working in a shearing environment may be exposed to.

However this relationship does not seem to be present for bacteria concentrations. It seems that mean bacteria concentration actually decreases as the number of sheep shorn increases but this relationship was not statistically significant. The fungi concentration seems to increase as the number of sheep shorn increases but the relationship was found to be not statistically significant. The bioaerosol concentrations appear to be more dependant on other variables including temperature and the design of the shed where the shearing is taking place.

In relation to dust, there is a significant relationship between dust and the number of sheep shorn but no simular significant relationship exists for bioaerosols. If a person is working in a shed that is shearing a larger number of sheep (above 200) then they may need to minimise their dust exposure by using improved ventilation and, if need be, PPE. This is also advisable as the other shearing variables are expected to increase the concentration of dust present.

147 4.6 Data analysed by the shearing session from which it was

collected

4.6.1 Introduction

Shearing session is the variable that controls when the sample is collected in relation to the shearers’ working time period. A typical shearing day consists of four, two hour, work sessions.

• Session 1: 7:30am to 9:30am • Session 2: 10am to 12 noon • Session 3: 1pm to 3pm • Session 4: 3:30pm to 5:30pm

There is a half an hour break for morning tea between Session 1 and Session 2 and for afternoon tea between Session 3 and Session 4. There is a one hour break for lunch between Sessions 2 and 3. During a break all work is stopped in the shed but people may remain within the shed eating, drinking and in some cases sleeping. A door will often be opened to allow people to enter or leave the building. Most farms were monitored for three out of the four work sessions. The sessions monitored were 2, 3 and 4. Only one farm, located in the Sydney basin, was monitored for session 1 and it was sampled during spring. Sessions 2 and 3 were the sessions most monitored as in some cases Session 4 was not monitored because shearing had been completed for the day or the shearers needed to finish earlier.

The shearing session in which sampling was undertaken is a variable that may be related to other sampling variables including temperature and season and closely related to shed design. If a shed is open and allows air to pass through during a shearing session the mean concentrations of contaminants may be lower compared to sessions where the shed is closed. This may be related to temperature and season. When a day is relatively cold in the morning but later warms up then the shed may be closed during the morning shearing session/s to try to retain heat and then opened later in the day to keep the building cooler. Again the shed may be closed in the late afternoon if the day is cooling down. The reverse may happen if a day is hot and the

148 building may be closed during the middle of the day to try to reduce the hot air from entering the building. The closure of the shed may assist in the build up of contaminants. For these reasons it is difficult to predict which shearing session is likely to have the highest dust concentrations.

If a dry heat is present in the hottest part of a day, the middle, the moisture content in the air may be reduced and this may encourage the mean dust concentration to increase. This would mean that Session 3 is expected to have higher airborne concentrations. However the one hour lunch break, which allows time for the airborne contaminants to settle in the building, could mean that the concentrations will be lower.

Shearing session 1 was not normally monitored due to problems accessing the shearing sheds prior to the commencement of shearing Session 1. If this session was monitored the effect of storing the sheep in the shed overnight would have been able to be assessed. This session may also have had lower concentrations because there is less movement of animals and people in the shed or may have had higher concentrations because the shed had been closed up and the dust generated by the animals built up. Further monitoring work needs to be carried out in Session 1 to determine this.

Session 2 may have slightly higher indoor air temperatures than Session 1 or Sessions 3 & 4 in the afternoon. The contaminants may have also built up during Session 1 and the morning tea break may not be long enough to reduce the contaminants.

Bioaerosol concentrations are not dependant on air temperature to influence their concentrations. If an activity within the shed is sufficient to release the bioaerosols from their dormant area and they have a chance to build up then this is when they will be at the highest concentration. Session 1 would be expected to have the highest concentrations because the sheep, housed overnight, would allow for the bioaerosols to be released and the closed up shed would assist the increase in the concentration of bioaerosols.

Due to the uncertainty and variability that can occur between sampling sessions it is expected that there will not be a significant difference between sampling sessions for

149 dust and bioaerosol concentrations. Table 4.6.1 contains the mean concentrations for the air contaminants that were sampled for in each shearing session.

Table 4.6.1 Mean concentrations of dusts and bioaerosols in relation to the shearing session they were collected in (± SE) measured inside the shearing sheds sampled in this study. Number of samples in ( )

Sampling Session number Parameter Session #1 Session #2 Session #3 Session #4 Personal 1.14±0.80 0.58±0.17 0.25±0.05 0.45±0.13 Respirable Dust (2) (33) (32) (26) (mg m-3) Personal 0.61±0.13 1.20±0.18 0.90±0.12 0.96±0.19 Inspirable Dust (3) (36) (39) (31) (mg m-3) Static Respirable 0.42±0.17 0.21±0.03 0.22±0.08

Dust (mg m-3) (23) (24) (20) Static Inspirable 0.44 0.59±0.07 0.57±0.07 0.56±0.05 Dust (mg m-3) (1) (107) (105) (87) Bacteria (cfu m-3) 6034±1938 2293±342 1790±146 2712±354 (6) (174) (174) (144) Fungi (cfu m-3) 2659±651 2203±177 2093±129 1852±172 (6) (174) (174) (144)

4.6.2 Dust concentrations for each sampling session

There are general trends for the different dust parameters sampled. When analysing the dust exposure data the first sampling session is not considered because the sample number for this session was very small and was collected from one farm, which if considered with equal weighting to the other sampling sessions would bias results. In the case of personal respirable dust concentrations the mean Session 1 was collected from only two samples. The standard error shows that there was quite a difference in the concentrations of dust measured on each occasion. Only having the two samples made the overall mean much greater than the means from the other sampling sessions. In fact the second highest mean result was nearly half of that recorded for sampling Session 1. The personal inspirable dust mean concentration for

150 session 1 was considerably lower than the other sampling sessions. There was no result recorded for Session 1 for static respirable dust, and for static inspirable dust only one sample was recorded. This one result was lower than the other mean concentrations found for the other sampling sessions.

6 Respirable Dust Concentrations Ave Respirable Dust Concentrations 5 ) -3

4

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2 Dust Dust Concentrationsm (mg 1

0 1 2 3 4 ion ion ion ion ess ess ess ess g S g S g S g S arin arin arin arin She She She She

Shearing Session Figure 4.6.1 Static respirable dust concentrations in relation to the shearing session durng the day

The highest mean dust concentrations (excluding Session 1) were found in Session 2. Three out of four of the lowest dust concentrations were measured in Session 3 (Figures 4.6.1 and 4.6.4). The general pattern for the dust concentrations was found to be highest during Session 2 after morning tea and then to be at their lowest in Session 3, after a 1 hour break for lunch, then increasing again in Session 4. This pattern happened for three out of four of the dust parameters with the only type of dust not following this pattern being the static inspirable dust (Figure 4.6.2). Session 3 and Session 4 recorded very similar results. There was only 0.01 mg m-3 difference in mean concentration between Sessions 3 and 4 for this parameter.

151 6.00 Inspirable Dust Concentrations Ave Inspirable Dust Concentrations 5.00 ) -3

4.00

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0.00 1 2 3 4 ion ion ion ion ess ess ess ess g S g S g S g S arin arin arin arin She She She She Shearing Session Figure 4.6.2 Static inspirable dust concentrations in relation to the shearing session durng the day

There was no significant difference between any of the sampling sessions for any of the dust sampling parameters. This was expected because of the difficulty in predicting the way that dust would behave between shearing sessions. As previously discussed there are many different factors that influence the possible concentration of dusts and from this study it appears that the shearing session may not be a major variable in predicting the highest dust concentrations. This is supported by the lack of a significant difference between shearing sessions for dust concentrations. However there is a noticeable (if not significant) pattern that the dust concentration is greatest in the shearing session before lunch.

152 6.00 Respirable Dust Concentrations Ave Respirable Dust Concentrations 5.00 ) -3

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0.00 1 2 3 4 ion ion ion ion ess ess ess ess g S g S g S g S arin arin arin arin She She She She

Shearing Session Figure 4.6.3 Personal respirable dust concentrations in relation to the shearing session durng the day

The shearing sessions after the tea breaks (Sessions 2 and 4) have a higher possibility of increased dust concentrations than the other sessions because of the shorter downtime period to possibly reduce the dust concentrations generated during the previous shearing session. This may be why Session 3 has the lowest dust concentrations for three of the four dust parameters measured (Table 4.6.1). Although the Session 3 shearing took place in the hottest part of the day and the dust concentrations were expected to increase from session 2 this did not occur and concentrations were reduced. The decrease may be due to the dust settling during the lunch period, when there is low activity in the shed. The other important variable is that the lunch break allows for an increase in ventilation because of the possibility of open doors allowing the dust to move out of the shed or become diluted by fresh air. Also during this time sheep are usually not brought into the shed which decreases the dust concentration being brought in from outside. When sheep are being moved into the shed the dust particles present in the ambient air increase and may blow into the shed. There is no noticeable decease in the number of sheep shorn in Session 3 compared with other sessions so this does not influence the dust concentrations.

153 6 Inspirable Dust Concentrations Ave Inspirable Dust Concentrations 5 ) -3

4

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2 Dust ConcentrationsDust (mg m 1

0 1 2 3 4 ion ion ion ion ess ess ess ess g S g S g S g S arin arin arin arin She She She She Shearing Session Figure 4.6.4 Personal inspirable dust concentrations in relation to the shearing session durng the day

The dust concentrations measured during Session 4 may have increased from Session 3 because the afternoon tea break (30 minutes) is not as long as the lunch break (60 minutes) which allows for the settling of the large dust particles with the smaller inspirable and respirable dust particles still being airborne. Session 4 is sometimes shorter than the other sessions which reduced the movement of sheep into and out of the shed and may explain why the concentrations measured were not as high as Session 2. Less sheep being shorn also reduces the concentration of dust brought into the shed on the animals. The air temperatures are also normally lower in Session 2 which may help lower the dust concentrations, but this does not explain why Session 3 had the lowest dust concentrations recorded for three of the four parameters (static inspirable dust concentration being the exception).

4.6.3 Bacteria and fungi concentrations for each sampling session

Both the mean bacteria and fungi concentrations measured were the highest during Session 1 but as these results were collected from one farm, with only 6 samples

154 collected, they cannot be considered in comparison to the other sampling sessions. It is interesting to note however that the results for this session, in particular the bacteria samples, are a lot higher than the other sessions. These samples were collected during spring and the overall results from this sampling day were much higher than the mean concentrations for all shearing sessions. It would have been interesting to have sampled all of the first shearing sessions from every sampling day but, as previously stated, this was not possible. The bioaerosol concentrations were expected to be highest during the first sampling session because the sheep are housed in the shearing shed overnight which would allow for the bioaerosols brought into the shed by the sheep to be released during the night.

Once the results from the first shearing session are discounted the mean bacteria concentrations and the mean fungi concentrations have different patterns. The mean bacteria concentration is lowest in Session 3 and greatest in Session 4 (Figure 4.6.5). The mean fungi concentration is greatest in Session 2, decreases in Session 3 and then decreases again to be at its lowest concentration for session 4 (Figure 4.6.6)

20000 Bacteria Concentrations Ave Bacteria Concentrations ) -3 15000

10000

5000 Bacteria(cfuConcentrationm

0 1 2 3 4 ion ion ion ion ess ess ess ess g S g S g S g S arin arin arin arin She She She She

Shearing Session Figure 4.6.5 Bacteria concentrations in relation to the shearing session durng the day

155 There is no significant difference between any of the shearing sessions for the bacteria measurements as the bacteria concentrations may have dissipated over the lunch break and increased again during the last shearing session. The bacteria may also reproduce quickly if the environment is right and be released in the last shearing session which could be why there is an increased mean concentration for the last session. A further possible reason for the increase in the last shearing session is that early in the day bacteria have been able to survive attached to the surrounding environment but later are no longer able to remain attached and then are released into the air.

20000 Fungi Concentrations 18000 Ave Fungi Concentrations

) 16000 -3

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8000

6000

Fungi Concentration(cfuFungi m 4000

2000

0 1 2 3 4 ion ion ion ion ess ess ess ess g S g S g S g S arin arin arin arin She She She She

Shearing Session Figure 4.6.6 Fungi concentrations in relation to the shearing session durng the day

The relationship between fungi concentration and sampling session was also found not to be significant but the pattern still shows that the mean concentration decreased slightly as the day progressed (Figure 4.6.6). All of the fungi may be released from the environment in the first shearing session when the sheep enter the building. Fungi reproduce at a slower rate than bacteria which may explain why the mean concentration does not increase later in the day. Another possibility is that when the sheep are moved into the outside holding pens the fungi in the wool are released but

156 bacteria are not. This would allow the bacteria to grow and be released inside the shed, in the afternoon, but the fungi have not been able to reproduce as quickly and are not released inside the shed as the sheep are shorn.

4.6.4 Conclusion of Effects of Sampling Session on Airborne Contaminant Concentration

There was no significant relationship found between the mean concentrations of any of the dust parameters and the shearing sessions monitored. There was a general pattern for the dust concentrations to be the highest during Session 2, lowest during Session 3 and increasing again during the last session of the day but not as high as Session 2. This pattern suggests that the lunch break is important in the minimisation of dust concentrations in shearing sheds as it allows for the dust to settle. It is therefore important that the shearers are allowed to take the whole hour as a break because if the break is shortened the dust may not settle and the concentration will rise for the remainder of the day. The concentration of dust is related to other variables especially the number of sheep shorn and the indoor air temperature that the sheep are shorn in. If either of these two variables were to change during the sampling sessions then the dust concentrations from the sampling sessions may change.

There was also no significant relationship found between the mean concentrations of bacteria or fungi with the shearing sessions that samples were collected from. The bacteria had the highest concentrations in the afternoon. Fungi had the highest concentrations in Session 2 but decreased during the rest of the day. The concentrations of bacteria and/or fungi are related to other variables and perhaps more importantly to moisture content and the conditions in which the animals are kept. These variables appear to be more important to the concentrations of bioaerosols that a person may be exposed to, than the shearing session that the samples were collected from.

157 4.7 Comparison between indoor and outdoor bioaerosol

concentrations

4.7.1 Introduction

The potential impact of the change in concentration of contaminants outside a shearing shed and the influence this may have inside the shearing shed is outlined in section 2.6.5. Outdoor dust and bioaerosol concentrations can have an influence on the indoor concentrations of airborne contaminants (Adhikari et al, 2004). It has also been found that there is normally a good correlation between the indoor and outdoor concentrations and the types of bacteria and fungi present (Mishra et al, 1992).

Outside dust concentrations were not collected. It would have been beneficial to collect samples from an area on the farm that was not influenced by sheep movement however, due to insufficient quantity of equipment, this was not possible. It was however possible to collect bioaerosol samples in an area that was not influenced by the movement of sheep.

From previous research (Adhikari et al, 2004; Mishra et al, 1992) it was expected that there will be a relationship between high bioaerosol concentrations outside the shed and high concentrations inside the shed. It was not however expected that all of the concentrations found inside the shed came from outside the shed and it was expected that much of the bioaerosols found inside the shed will be generated by the activities therein.

Outside bioaerosol concentrations were not collected from the first six farms sampled. Without the outside concentrations the percentage increase could not be found. Hence the first six farms are not considered in the analysis of this variable (Table 4.7.1).

158 Table 4.7.1 Mean (±±± SE) bacteria and fungi concentration (cfu m-3) for each shearing shed monitored in NSW. Sample number in Brackets ( ).Highest concentrations and % changes in Yellow

Location Bacteria Fungi (cfu m-3) (cfu m-3) Outside shed Inside shed % Outside shed Inside shed % while shearing change while shearing change Farm 7 180±31 (6) 2668±296 (18) 1382 1405±644 (6) 3525±412 (18) 151 Farm 8 227±120 (6) 2353±609 (18) 937 424±128 (6) 2575±498 (18) 507 Farm 9 1163±327 (6) 2133±314 (18) 83 162±89 (6) 484±69 (18) 199 Farm 10 200±83 (6) 1349±184 (18) 575 62±45 (6) 460±107 (18) 642 Farm 11 236±84 (6) 925±292 (18) 292 468±149 (6) 908±135 (18) 94 Farm 12 97±42 (6) 2683±586 (12) 2666 345±136 (6) 1265±219 (12) 267 Farm 13 2647±1234 (6) 2747±5652 (12) 4 1364±458 (6) 1664±290 (12) 22 Farm 14 159±60 (6) 1594±659 (18) 903 292±145 (6) 887±244 (18) 204 Farm 15 2465±983 (6) 3135±540 (18) 27 557±303 (6) 663±174 (18) 19 Farm 16 297±41 (6) 732±112 (18) 146 1714±536 (6) 1962±320 (18) 14 Farm 17 109±42 (6) 575±107 (18) 428 312±154 (6) 1169±268 (18) 275 Farm 18 283±128 (6) 1225±249 (12) 333 766±227 (6) 1206±224 (12) 57 Farm 19 230±91 (6) 1911±208 (18) 731 359±282 (6) 786±98 (18) 119 Farm 20 180±97 (6) 5936±1477 (18) 3198 47±22 (6) 3582±838 (18) 7521 Farm 21 474±179 (6) 1754±141 (18) 270 727±296 (6) 832±81 (18) 14 Farm 22 654±288 (6) 1589±114 (18) 143 798±182 (6) 838±95 (18) 5 Farm 23 77±23 (6) 716±231 (18) 830 474±208 (6) 2571±512 (18) 442 Farm 24 153±113 (6) 1492±139 (18) 875 56±16 (6) 2647±314 (18) 4627 Farm 25 515±148 (6) 3378±270 (18) 556 156±69 (6) 2512±359 (18) 1510 Farm 26 127±63 (6) 1414±228 (18) 1013 130±36 (6) 2923±352 (18) 2148 Farm 27 271±51 (6) 1831±271 (18) 576 165±76 (6) 3068±313 (18) 1759 Farm 28 224±101 (6) 1642±258 (12) 633 227±89 (6) 1849±269 (12) 715 Farm 29 71±30 (6) 1240±195 (18) 1646 200±73 (6) 3527±461 (15) 1664

4.7.2. Bioaerosol concentrations found outside and inside the shed

The concentration of bioaerosols has been shown to increase inside a building when activities are being undertaken, and the number of animals brought into the shed can greatly change the concentration of both dusts and bioaerosols present (Section 2.6.7).

159 What is clear, in this analysis, is that concentrations of bioaerosols are higher inside the shed compared with outside, with every farm having an increase in both bacteria and fungi concentrations. Some farms (Figure 4.7.1) had a very low increase, Farm 13 with a bacteria increase of 4% and Farm 22 with a fungi increase of 5%. The greatest increases of fungi and bacteria both occurred at Farm 20 (3198% increase for bacteria, 7521% increase for fungi). These increases must have come from the activities (shearing, wool sorting) carried out within the shed. The sheds showing low increases may have had less microorganisms in the shed and on the animals or the sheds themselves may have been better ventilated to reduce contaminant concentrations. In an early study fungi spore concentrations in cowsheds were recorded to be 10-100 times greater than that of farmyard air (Baruah, 1961). Gibbs et al (2004) also found changes from inside and outside bioaerosols between 10 and 1000 times greater. In this study the change was not as great with the highest being closer to 100 times greater and commonly closer to 10 times greater.

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1000

0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223242526272829 Farm Number

Figure 4.7.1 Percentage change increase from outside to inside air concentrations for bacteria and fungi measured on each farm (Note: Farms 1-6 were not tested).

160 There is a possible indication that there was a relationship between high outside concentrations and high inside concentrations of bioaerosols and also with high outside concentrations increasing the general amount found in the air. However this did not lead to overall higher levels. What tended to occur was a decrease in the percentage change. Therefore if the concentrations were already high then they did not tend to increase by a great percentage and this is shown in the small percentage increase of bacteria for Farms 13 (4%) and 15 (27%) where both the outside and inside levels were high. This also occurred for fungi concentrations at Farm 13 (22%) and Farm 16 (14%) which had outside concentrations >103 cfu m-3. The reverse of this trend did not occur. If the outside level was low it did not seem to affect the possible percentage change. Very high and very low inside concentrations were found when the outside concentration was low and this happened for both fungi and bacteria.

There were some limitations experienced within this area of the research that may have affected some results. If concentrations could have been collected before the shed was used for shearing, and then once again after the completion of shearing, it may have helped to determine if the shed has higher than outside bioaerosol concentrations when the shed is not in use. If the concentrations are generally higher inside this may mean that the shed is growing many organisms within. All bioaerosols were collected using a static sampler which was set at a height that was lower than the normal breathing zone of workers, and this may mean that concentrations measured were not truly representative of the exposures experienced by people working in the shed.

Many of the other variables may have influenced the results recorded for both inside and outside the shed. Ventilation and flooring type are important as the flooring type can inhibit or help bioaerosol growth and also impact on their release (Takai et al, 1998; Langridge, 1992). The ventilation is important, in the control of bioaerosols, as the air entering through ventilation can move the bioaerosol contaminants around the building, or out into the surrounding environment (Wathes, 1992; Larsson et al, 1988). The number of sheep being shorn is an important variation that can also influence the release of bioaerosols (Gustafsson, 1999). Also, the season in which samples are collected is important for bioaerosol concentration (Coble et al, 2002; Blom et al, 1984) and weather conditions between farms and sampling days can be

161 very different even if the farms are relatively close together (Beijer et al, 2003; Sarica et al, 2002). The amount of rain and sun usually varies between farms and geographical regions. This is particularly important for bioaerosol growth as bioaerosols grow better under certain environmental conditions. For both fungi and bacteria maximum growth occurs in an environment where nutrients are in good supply, the microorganisms are sheltered from harsh environments and the temperature is ideal. For both fungi and bacteria ideal growing temperatures are between 10 to 60oC (Tortora et al, 1998). In winter, or colder climates, this can mean that many bacterial and fungal species cannot grow and regenerate and this is the same for both indoor and outdoor microbes.

4.8.1 Comparison of Dust Concentrations to relevant Exposure Standards

As outlined in Section 2.7 there is debate about the relevance of current dust exposure standards and their application in relation to agriculturally produced dusts. The current dust exposure standard for inspirable dust in Australia is set by ASCC and is a TWA of 10 mg m-3 (ASCC, 2006b). There is no non-specific respirable dusts exposure standard set in Australia, so the current American recommended threshold limit value (TLV) for nuisance dusts of 3 mg m-3 for respirable (ACGIH, 2006) is used. It is generally agreed that these current dust standards may not be sufficient for the protection of workers from agriculturally produced dust. This is because of the concentrations of endotoxins and Aeroallergens that may be found in the different dusts produced in this environment (Cullinan et al, 2001; Rylander, 1997; Dutkiewicz et al, 1994). It is also considered that the pathological effects that these dusts can produce means that they should not be classed as nuisance dusts (Kullman et al, 1998) as they are at the moment.

Other research based on health data has suggested that these current exposure standards should be lowered. Vogelzang et al (2000) suggested that a threshold level for organic dust exposure should not be higher than 2.6 mg m-3 for inspirable dust. Donham (1999) suggested a simular limit for inspirable dust of 2.4 mg m-3 and for respirable dust of 0.23 mg m-3 for dust produced in animal handling buildings

162 (Donham, 1999). Other research by Donham and Cumro, (1999) has suggested that the respirable dust level should be as low as 0.16 mg m-3.

When comparing the collected dust exposure data for the shearing industry it was decided to use both the relevant current exposure standards and the suggested concentrations by Donham (1999).

Table 4.8.1 Dust concentration compared to current and proposed standards.

Parameter Number Max Exposure % ASCC Suggested % that of concentratio standard exceeded agricultural suggested samples n (mg m-3) standard standard exceeded (Donham, 1999) standard Respirable 95 4.97 3 1.1 0.23 66.3 personal dust Respirable 67 3.19 3 1.5 0.23 29.9 static dust Inspirable 109 5.17 10 0 2.4 10.1 personal dust Inspirable 299 4.36 10 0 2.4 2.3 static dust

When the collected data is compared to the current exposure standards no inspirable samples broke the current exposure limit. In the case of the static samples the maximum sample was less than half of the exposure limit. 1.1% and 1.5% of the samples collected for the respirable dust broke the current standards. As this is quite a low number it could mean that either there is a very low risk of workers developing respiratory disease from working in this environment or that the exposure standard is relatively high. Other research suggests that the current standards are too high. Research into the development of diseases for people working in the shearing industry has not yet occurred. However the research that has been conducted into dust produced in an agricultural setting suggests that the risk of developing respiratory disease is relatively high. When the sampled concentrations are compared to the suggested agricultural samples 66.3% percent of personal respirable samples exceeded this concentration limit. This is a very high percentage. Nearly 30% of static respirable samples also exceeded this suggested concentration. The percentage of inspirable dust concentrations breaking the suggested standard concentration is

163 lower with 10.1% of personal and 2.3% of static samples exceeding this concentration (Table 4.8.1).

Against the exposure standard as it is at the moment all individual results for inspirable dust were under the recommended standards for all farms (Figure 4 8.1) confirming that under the current standards the farms tested were not in breach of the current OHS legislation. These results do not mean there is no risk of workers developing respiratory disease from exposure to these dust concentrations particularly in light of so many of the samples exceeding the suggested exposure standard for agricultural dust. If the dust exposure limit was to be reduced then there is a very real possibility that many of the recorded results would exceed the lower limit. The risk to a worker of developing respiratory disease is unclear at the moment, but according to the current exposure standards the risk is minimal. However this may not be the case as a lower exposure limit has been suggested to reduce the current expected risk. Workers with a predisposition to illness from dust exposure may develop disease from chronic exposure, or from acute exposure to high concentration on particular days.

3 3

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2 2 Inspirable -3

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mg mg m Respirable Suggested 1 1 Standard

Inspirable 0.5 0.5 Suggested Standard

0 0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223242526272829

Farm number Figure 4.8.1 Mean concentrations found at each farm for inspirable and respirable dusts

164 4.8.2 Bioaerosol Exposure standards

No exposure standards have been adopted anywhere in the world for bioaerosols such as bacteria and fungi. This highlights the difficulty of trying to provide standards for something that is not completely understood (Douwes et al, 2003). Bioaerosols and their impact on human health is an area of research that is expanding. It is known that negative health impacts and bioaerosols are linked (Ferguson, 1998) and that this link has been known for some time (Dutkiewicz, 1978). Concentrations of microorganisms that may cause this negative health impact have been suggested by a number of researchers. The exposure limits for bacteria or fungi of between 103 and 108 cfu m-3 have been proposed by (Eduard and Heederik, 1998; Scarpino and Quinn, 1998; Dutkiewicz, 1992). If the exposure limit is taken as 108 cfu m-3 then all of the concentrations recorded in this study are within the guidelines.

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2000 Bacteria Concentraion (cfu m (cfu Concentraion Bacteria

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0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223242526272829 Farm number

Figure 4.8.2 Average concentrations of bacteria recorded from all farms inside and outside the shearing shed.

The highest concentration recorded was 6.5 x 103 cfu m-3 at Farm 3. If, however, the exposure limit was 103 cfu m-3 then 25 farms had higher average bacteria concentrations for inside the shed. 86% of farms sampled exceeded this level when samples were collected inside the shed.

165 When recording fungi the number of sheds exceeding this concentration is lower with 21 farms exceeding 103 cfu m-3 therefore 72% of farms exceeded this concentration for fungi. The highest measured fungi concentration of 5.5 x103 cfu m- 3 exceeds the 103 cfu m-3 recommended exposure limit but if higher limits were recommended then there appears to be no potential problem.

6000

) 5000 -3

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Average Fungi concentration (cfu (cfu m concentration Fungi Average 1000

0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223242526272829 Farm number Figure 4.8.3 Average concentrations of fungi from all farms for inside and outside the shearing shed

Interestingly, some outside bacteria or fungi concentrations broke the suggested limit of 103 cfu m-3. Three farms had average bacteria concentrations that were greater than 103 cfu m-3 and three farms had average fungi concentrations that were also greater. Only one farm had higher concentrations for both fungi and bacteria and this was Farm 13. Outside concentrations for both types of bioaerosol were higher at Farm 13 possibly because of the vegetation grown in the surrounding paddocks or area. Farm 16 is located next to Farm 13 and also had high fungi concentrations. Different fungi and bacteria are generated from different plants (Miller, 1995) and fungi and bacteria concentrations are affected by the type of crop present (Olenchock et al, 1990). It is unclear if the whole area had higher outside concentrations of bioaerosols. Overall the concentrations found were higher than in an urban environment with medium concentrations of 102 cfu m-3 outdoors (Dutkiewicz, 1997; Macher et al, 1991).

166 4.9 Factors that impact on air concentrations in a shearing shed

All of the different variables outlined can have an impact on the concentration that a person may inhale while they work, however not all of these variables interact in the same way. Some have more influence on certain airborne contaminants than others. From the analysis of the data, using the different variables, each parameter showed which variables had a greater influence. In some cases it was hard to determine which variables influence a particular parameter and it is also likely that many of the variables may interact synergistically.

The mean respirable dust concentrations were lower than the concentrations recorded for inspirable dust recorded for the same farms. This was expected because the respirable dust fraction is a part of the inspirable dust fraction (Tranter, 1999). Both the static (r=0.429, p=0.019) and personal (r=0.257, p=0.046) mean concentrations for respirable dust were found to have a significant relationship to the concentration of inspirable dust. This relationship means that if the inspirable dust concentration was high then the respirable dust concentration was also likely to be high. The personal respirable dust concentrations were found to have a significant positive relationship to the number of sheep that were shorn (r=0.433, p=0.001) but this was not evident for the static samples. Neither the static or personal concentrations were found to have a significant relationship with the indoor temperature at which the samples were collected. Respirable dust concentrations were also found not to be significantly influenced by the concentration of bacteria or fungi present in the shed. There was no significant relationship found between respirable dust and the region that the samples were collected in. There was also no statistically significant relationship between either the personal or static dust samples or the shearing session during which the samples were collected. The relationship between the respirable dust samples and the job that was undertaken during sampling was found to only be statistically significant between two job types and one of these jobs had a small number of samples collected (5). The concentration of respirable dust seems to have been most influenced by the concentration of inspirable dust that was present at the time of sampling (r=0.429, p=0.19 for static samples, r=0.257, p=0.046 for personal samples).

167 Inspirable dust was found to have a statistically significant relationship to the concentration of fungi that was present during sampling (r=0.288, p= 0.013). This is possibly because the aerodynamic diameter size of a typical fungi fraction is a similar size to the inspirable dust fraction. The number of sheep that were shorn during the time of sampling was found to be statistically related to the concentration of inspirable dust (r=0.492, and p= 0.000). The indoor temperature when the samples were collected also had a statistically significant impact on the concentration of inspirable dust (r=0.249, p=0.014 for static samples, r=0.213, p=0.019 for personal samples). Inspirable dust was found to have a significant relationship with the shearing regions and there were significant differences between most shearing regions for both personal and static inspirable concentrations. There was no statistically significant relationship for the concentration of respirable dust and the shearing session that the samples were collected in nor between personal respirable dust concentrations and the job that was being undertaken at the time of sampling. The placement of the static samples was found not to have a significant affect on the concentration of inspirable dust but inspirable dust was found to have a statistically significant relationship with the number of sheep shorn during the shearing session (r=0.556, p,0.001 for personal samples, r=0.492, p<0.001 static samples); the indoor air temperature of the shed (r=0.213, p=0.019 for personal samples, r=0.249, p=0.14 for static samples); and the shearing region and the concentration of fungi (r=0.288, p=0.013) measured in the shed.

The concentration of bacteria was found not to have a significant relationship with the concentration of inspirable dust, respirable dust, the concentration of fungi found in a shed, the temperature of the shed during sampling, the number of sheep shorn during the sampling day or the shearing session. The concentration of bacteria was found to be influenced by the change in shearing region (F(4, 493)=3.890, p=0.004). Only one region was found to be statistically significant from one other shearing region and there was no other significant difference found between shearing regions. The concentration of bacteria measured in a shearing shed was found not to be significantly related to any of the variables analysed and this makes it difficult to predict the concentration of bacteria that may be present in a shearing shed.

The concentration of fungi was found to be statistically significant in relation to the concentration of inspirable dust measured in the shed (r=0.351, p= 0.013). This

168 means that as the concentration of inspirable dust increased the concentration of fungi should also have increased. These two contaminants have a similar aerodynamic diameter which may explain why they are related. The concentration of fungi was not found to be statistically significant in relation to the concentration of respirable dust. Fungi concentration was also significantly correlated with the concentration of bacteria measured (r=0.466, p<0.001). This was interesting because of the difference in aerodynamic diameter of the two bioaerosols. Also interesting was that it appears bacteria concentrations are significantly correlated with fungi concentrations but fungi concentrations are not significantly correlated with bacteria concentrations. It is possible that when bacteria grow they prevent fungi growth. The concentration of fungi was found to be significantly related to the air temperature of the environment in which the samples were collected (r=0.228, p= 0.044) but it was not found to be statistically related to the number of sheep shorn per session. The fungi concentration was found to be significantly influenced by the shearing region (F(94, 493)=17.213, p<0.001) and there were significant differences between most shearing regions. The concentration of fungi was not found to have a statistically significant relationship to the shearing session but did to the indoor air temperature of the shed during shearing (r=0.288, p=0.044), the different shearing regions and the concentrations of both inspirable dust (r=0.351, p=0.013) and bacteria (r=0.466, p<0.001) that were measured at the same time.

169 CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS

Negative health effects from exposure to dusts and bioaerosols in rural environments are well known and documented. What was not known was the concentrations of dusts and bioaerosols people working in sheep shearing environments may be exposed to. The results of this study show that the exposure of workers to dusts in the sheep shearing sheds monitored were below the current recommended standards for acceptable concentrations of dusts (NOC or rouge dust). However debate over the relevance of these standards is occurring and in the future these recommended exposure standards may be reduced. It is not the place of this study to suggest that these standards should be lowered as no health related data were recorded. If these exposure standards are reduced in the future it is possible that the concentrations found inside the sheds would exceed the new standards that may be developed to protect against the potential negative health impacts on exposed workers. It is also possible that chronic exposure of workers to these reasonably high levels may still represent a health hazard.

The concentrations of dusts and bioaerosols recorded in this study did not exceed the current exposure standards, however there were still elevated results recorded for some farm environments. There are many different variables that can impact on the concentrations found in any environment. The concentration of respirable dust was found to be significantly correlated with the concentration of inspirable dust measured. The inspirable dust concentrations appear to be significantly related to the number of sheep shorn on a farm, the airborne concentrations in the surrounding area of the shed; and the temperature inside the shed during shearing. The results of this study indicate that shearers in busy sheds, during hot periods of the year will be exposed to increased concentrations of dust, which may adversely affect their health.

The results of the bioaerosol monitoring showed that the concentrations varied greatly and the results need to be compared with health related studies to determine whether the concentrations during exposure could lead to possible health risks. At present no standards exist for the concentrations of bioaerosols both in Australia and other regions of the world and therefore it is difficult to comment on whether a potential health risk is present.

170 Certain shearing environments sampled had greater concentrations of bioaerosols than other environments. Similar to dust, there are many different variables that can impact on the concentration of bioaerosol in a shearing environment. The bioaerosol concentrations measured inside a sheep shearing shed are not considered reflective of the concentrations outside the shed. High concentrations of bioaerosols were measured inside the shed even when low concentrations were measured outside. The high concentrations found inside suggest that the bioaerosols are generated inside or were being moved inside the shed via the sheep. Bacteria concentrations were found not to be significantly related to any sampled variables. The fungi concentrations appear to be significantly related to the temperature inside the shed during shearing, the region that the sheep were shorn in and the concentration of either bacteria or inspirable dust that was present inside the shed. The bioaerosol data indicate that shearers are at greater risk of exposure to high concentrations of bioaerosols when they are working in hotter sheds and if the concentration of other airborne contaminants is high. Shearing contractors and farmers have a legal obligation to ensure that the working environment of people in these sheds is the safest possible. The findings of this study may have implications for the design of a shearing shed, possible job rotation, and other available control measures, particularly if current dust exposure standards are lowered or if bioaerosol exposure standards are introduced.

5.1 Recommendations for the Shearing Industry

The results of this study show that the potential exposures to airborne dusts and bioaerosols in the sampled shearing sheds are below current Australian exposure standards. If the activities in shearing sheds change or exposure standards are reduced, which is likely given the health related data reviewed in this study, then the following recommendations will assist in lowering the exposures of workers to airborne contaminants:

• Changing air flow within the sheds so that air flows from areas of relatively low airborne dust and bioaerosols concentrations to areas with higher concentrations and also restricting the potential for excessive airborne contaminants to be drawn into the shed.

171 • While exposures exceed, or are likely to exceed, the recommended exposure standards appropriate respiratory protection should worn. In most cases this would mean the use of a P1 respirator/dust mask as a minimum. If workers are required to wear respiratory protection then they should be trained in the use and maintenance of the devices selected for use.

It is also recommended that the industry should develop guidelines for:

• How to deal with a person working in the shed that has a known predisposition to respiratory illnesses/stress, in that they should be closely monitored to ensure that the environment does not aggravate the condition.

• Shearing sheds to be routinely sampled for dusts and bioaerosols to ensure that the airborne exposures for shearers are not increasing. This monitoring would assist the employers in meeting their responsibilities under the current OHS regulations.

• Changing the working positions for people within the shearing area or the wool handling area so that each workers’ exposure is equally kept to a minimum.

• Bioaerosol exposure standards to protect workers’ exposure to concentrations that may potentially have a negative impact on health. It should be noted if bioaerosol standards, such as 103 cfu m-3 for either mould or bacteria, were implemented in Australia then appropriate respiratory protection and new ventilation strategies would need to be introduced to reduce exposures.

5.2 Areas of further research

This project found many areas where the current understanding of the issues involved were either non-existent or could be improved with further research. Areas from this study that need further research are:

• An epidemiological study of people working in shearing sheds in relation to their respiratory health. This would assist in developing an understanding of the relationship between the acute and/or chronic exposure to dusts and

172 bioaerosols and chronic respiratory disease of people who work in shearing sheds.

• A similar study should be conducted both in other regions in Australia and overseas to determine if the dust and bioaerosol concentrations reported in this study are typical of all shearing sheds in Australia and if there are differences in concentrations between various regions of the world.

• Methods of monitoring personal exposures to bioaerosols, especially viable microorganisms, need to developed and validated so that personal exposures to bioaerosols can be measured over longer time periods than the methods used in this study.

• In conjunction with the epidemiological study an identification of the microbiological organisms that may grow in sheep shearing sheds needs to be undertaken. This may assist in determining if there are predominant microbiological organisms that could be responsible for specific health issues.

• To enable a better picture of the airborne exposures in animal confinement houses similar studies undertaken for environments where people working with other animals in Australia, such as cattle, horses, pigs and chickens. This would provide a better understanding of the potential diseases that can be developed by agricultural workers exposed to dusts and bioaerosols.

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194

APPENDICES

195 APPENDIX A LETTER TO SHEARERS

School of Environment and Agriculture Building K8, Hawkesbury Campus

Phone: 02 4570 1492 Fax: 02 4570 1383 Email: [email protected]

14/8/2004

Name Address Address

Dear

Re: Research in Shearing Industry I am writing to ask if you would be prepared to take part in having the normal working conditions in your shearing sheds sampled for dust and bioaerosol concentrations. This sampling is designed to help the research team evaluate the current methods for control of hazards in the agricultural working environment. It is expected that the sampling will not interfere with your normal working conditions and should take between 1 to 2 hours.

If you are prepared to take part in this sampling could please let me know by 14/9/04 and fax the attached consent form to 45701383.

Once you have agreed to participate you will be contacted to arrange a time and place for the sampling to be undertaken.

Yours sincerely

Ryan Kift

196

Locked Bag 1797 Penrith South DC NSW 1797 Australia

School of Environment and Agriculture Building K8, Hawkesbury Campus

Phone: +61 2 4570 1167 Fax:+61 2 4570 1383 Email: [email protected] INFORMATION SHEET RESEARCH PROJECT The Assessment of Workers Exposure to Potentially Harmful Dusts and Bioaerosols Generated From the Handling of and the Working with Livestock You are invited to participate in a research project investigating the types and levels of air contaminants that workers handling livestock may be exposed too. Ryan Kift is undertaking this project and is being supervised by Dr Sue Reed, Senior Lecturer, School of Environment and Agriculture, University of Western Sydney. The aim of this study is to determine the potential exposure to hazardous dust by people who work with livestock in the rural industry. To meet this aim the major objectives of the study are to: • determine the sampling methods that can be used to adequately measure concentrations of dust exposures to workers handling livestock; • determine what types of bioaerosols people may be exposed to when handling livestock; and • undertake a preliminary health study to determine if there is a link between the dust levels measured and any health effects. This research will require you to wear a sampling device attached to a sampling pump, worn at the waist, to assess your potential inhalation exposure to dust. In addition you will be asked to complete a confidential questionnaire about health effects you currently have or have suffered in the past. If you need assistance with the completing the questionnaires please ask or if you have any questions in regards to the sampling equipment also feel free to ask. It is hoped that you will be part of this study. If you would like copies of the air monitoring results that relate to you please let me know and we will forward to them you with an explanation once the analysis is complete. If you have questions about this study or the results please contact Ryan at the University on 02 45701167 or email: [email protected].

NOTE: This study has been approved by the University of Western Sydney Human Research Ethics Committee. If you have any complaints or reservations about the ethical conduct of this research, you may contact the Ethics Committee through the Research Ethics Officers (tel: 02 4570 1136). Any issues you raise will be treated in confidence and investigated fully, and you will be informed of the outcome.

197

Locked Bag 1797 Penrith South DC NSW 1797 Australia

School of Environment and Agriculture Building K8, Hawkesbury Campus Phone: +61 2 4570 1167 Fax:+61 2 4570 1383 Email: [email protected]

CONSENT FORM RESEARCH PROJECT The Assessment of Workers Exposure to Potentially Harmful Dusts and Bioaerosols Generated From the Handling of and the Working with Livestock

I have been asked to participate in the above research project and give my consent by signing this form on the understanding that: ∗ the research will be carried out in a manner conforming with the terms of reference laid down by University of Western Sydney Human Research Ethics Committee; ∗ the general purposes, methods and demands, the possible risks, inconveniences and discomforts which may occur during the study have been made known to me; ∗ I am volunteering to take part in this study and may withdraw at any time; ∗ personal data obtained will only be available to the researcher and to me; ∗ this research project has been approved by the Human Research Ethics Committee of University of Western Sydney, HREC Approval No 03/100

My full name: ______

Signature: ______Date: ______

Researchers Name:

Signature: ______Date: ______

198 Note- In Appendix Sec stands for second. Appendix B Dust and bioaerosol concentrations collected from Farm 1

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Inspirable Session #2 Personal 0.24 Inspirable Session #2 Personal 0.54 Inspirable Session #2 Personal 1.08 Inspirable Session #2 Static 0.28 Inspirable Session #3 Personal 0.50 Inspirable Session #3 Personal 0.56 Inspirable Session #3 Personal 0.00 Inspirable Session #3 Static 0.00 Inspirable Session #4 Personal 0.55 Inspirable Session #4 Personal 0.31 Inspirable Session #4 Personal 0.73 Inspirable Session #4 Static 0.24

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1537 1184 707 30 Sec #2 1343 1590 1290 1 Min #1 1131 283 1519 1 Min #2 2509 813 989 2 Min #1 989 212 636 2 Min #2 4311 989 848

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2244 2138 1095 30 Sec #2 936 1307 2279 1 Min #1 106 848 2155 1 Min #2 2580 2509 1131 2 Min #1 5724 3251 1060 2 Min #2 2049 636 919

199 Appendix C Dust and bioaerosol concentrations collected from Farm 2

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.34 Respirable Session #2 Personal 1.13 Respirable Session #3 Personal 0.65 Respirable Session #3 Personal 0.28 Respirable Session #4 Personal 0.29 Respirable Session #4 Personal 0.09 Inspirable Session #2 Personal 0.77 Inspirable Session #2 Static 0.36 Inspirable Session #2 Static 0.27 Inspirable Session #2 Static 0.17 Inspirable Session #3 Personal 0.53 Inspirable Session #3 Static 0.34 Inspirable Session #3 Static 0.30 Inspirable Session #3 Static 0.19 Inspirable Session #4 Personal 0.64 Inspirable Session #4 Static 0.22 Inspirable Session #4 Static 0.17 Inspirable Session #4 Static 0.18

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 901 830 1449 30 Sec #2 106 2279 636 1 Min #1 671 1413 1943 1 Min #2 636 1873 1131 2 Min #1 636 565 2898 2 Min #2 3180 1696 989

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1095 1961 1201 30 Sec #2 88 2491 1537 1 Min #1 1519 1331 848 1 Min #2 848 1519 1590 2 Min #1 353 1131 1201 2 Min #2 565 1201 1343

200 Appendix D Dust and bioaerosol concentrations collected from Farm 3

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #1 Personal 0.34 Respirable Session #1 Personal 1.94 Respirable Session #2 Personal 0.17 Respirable Session #2 Personal 0.13 Respirable Session #3 Static 0.13 Respirable Session #3 Personal 0.39 Respirable Session #4 Static 0.18 Respirable Session #4 Personal 0.29 Inspirable Session #1 Side wall 0.44 Inspirable Session #1 Personal 0.42 Inspirable Session #1 Personal 0.85 Inspirable Session #1 Personal 0.55 Inspirable Session #2 Side wall 0.16 Inspirable Session #2 Personal 0.26 Inspirable Session #2 Static 0.19 Inspirable Session #2 Personal 0.28 Inspirable Session #2 Personal 0.36 Inspirable Session #3 Side wall 0.19 Inspirable Session #3 Personal 0.62 Inspirable Session #3 Personal 0.37 Inspirable Session #3 Personal 0.45 Inspirable Session #3 Personal 0.00 Inspirable Session #4 Side wall 0.12 Inspirable Session #4 Personal 0.15 Inspirable Session #4 Personal 0.20 Inspirable Session #4 Personal 0.25 Inspirable Session #4 Personal 0.23

201 Bacteria cfu m-3 Session Session Session Session #1 #2 #3 #4 30 Sec #1 10742 57224 7421 1908 30 Sec #2 6572 6431 18092 3746 1 Min #1 2403 2261 1343 2085 1 Min #2 1696 3993 4735 2933 2 Min #1 12615 1166 265 3057 2 Min #2 2173 1484 1307 1855

Fungi cfu m-3 Session Session Session Session #1 #2 #3 #4 30 Sec #1 2756 919 6784 1625 30 Sec #2 212 989 4382 3039 1 Min #1 4346 989 2968 4452 1 Min #2 4452 1131 2615 1979 2 Min #1 2014 1007 1219 4823 2 Min #2 2173 3569 1184 1908

202 Appendix E Dust and bioaerosol concentrations collected from Farm 4

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 1.97 Respirable Session #2 Personal 0.25 Respirable Session #3 Personal 0.02 Respirable Session #3 Personal 0.05 Respirable Session #4 Personal 0.21 Respirable Session #4 Personal 2.64 Inspirable Session #2 Personal 0.75 Inspirable Session #2 Static 0.40 Inspirable Session #2 Static 0.22 Inspirable Session #2 Personal 0.81 Inspirable Session #2 Static 0.33 Inspirable Session #3 Personal 0.42 Inspirable Session #3 Personal 0.61 Inspirable Session #3 Static 0.13 Inspirable Session #3 Static 0.60 Inspirable Session #3 Static 0.52 Inspirable Session #4 Personal 1.09 Inspirable Session #4 Personal 0.73 Inspirable Session #4 Static 0.55 Inspirable Session #4 Static 0.41 Inspirable Session #4 Personal 0.66

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 919 1131 2615 30 Sec #2 3322 1060 707 1 Min #1 1555 742 1590 1 Min #2 777 777 1166 2 Min #1 283 406 2332 2 Min #2 583 565 2032

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1484 3463 1060 30 Sec #2 2403 3322 1696 1 Min #1 3180 2686 954 1 Min #2 1519 813 919 2 Min #1 760 1078 1502 2 Min #2 1502 3905 1042

203 Appendix F Dust and bioaerosol concentrations collected from Farm 5

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 1.44 Respirable Session #2 Personal 2.11 Respirable Session #3 Personal 0.73 Respirable Session #3 Personal 0.00 Inspirable Session #2 Personal 1.27 Inspirable Session #2 Static 0.35 Inspirable Session #2 Static 0.97 Inspirable Session #2 Static 0.64 Inspirable Session #2 Personal 3.31 Inspirable Session #3 Personal 2.75 Inspirable Session #3 Personal 0.45 Inspirable Session #3 Static 0.10 Inspirable Session #3 Static 0.56 Inspirable Session #3 Personal 0.38

Bacteria cfu m-3 Session #2 Session #3 30 Sec #1 5512 565 30 Sec #2 6219 1131 1 Min #1 1555 177 1 Min #2 6042 2014 2 Min #1 2597 2261 2 Min #2 2915 2385

Fungi cfu m-3 Session #2 Session #3 30 Sec #1 7420 3322 30 Sec #2 6431 1908 1 Min #1 5866 2403 1 Min #2 5901 1802 2 Min #1 4947 6290 2 Min #2 4099 7862

204 Appendix G Dust and bioaerosol concentrations collected from Farm 6

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.27 Respirable Session #2 Personal 0.09 Respirable Session #3 Personal 0.29 Respirable Session #3 Personal 0.16 Respirable Session #4 Personal 0.07 Respirable Session #4 Personal 0.11 Inspirable Session #2 Personal 3.42 Inspirable Session #2 Personal 2.36 Inspirable Session #2 Static 0.69 Inspirable Session #2 Static 0.44 Inspirable Session #2 Static 0.70 Inspirable Session #3 Personal 1.93 Inspirable Session #3 Personal 0.60 Inspirable Session #3 Static 0.49 Inspirable Session #3 Static 0.35 Inspirable Session #3 Static 0.72 Inspirable Session #4 Personal 1.73 Inspirable Session #4 Personal 1.57 Inspirable Session #4 Static 0.38 Inspirable Session #4 Static 0.83 Inspirable Session #4 Static 0.48

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 4028 3887 8127 30 Sec #2 6431 6855 36184 1 Min #1 2544 4311 3569 1 Min #2 2403 4664 2155 2 Min #1 1979 2332 1431 2 Min #2 2544 1431 15760

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 12085 8481 6431 30 Sec #2 17173 4382 11873 1 Min #1 3922 5901 5159 1 Min #2 3569 7314 4417 2 Min #1 1201 2491 1254 2 Min #2 1661 2792 2597

205 Appendix H Dust and bioaerosol concentrations collected from Farm 7

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Static 0.22 Respirable Session #2 Personal 0.19 Respirable Session #3 Static 0.16 Respirable Session #3 Personal 0.22 Respirable Session #4 Static 0.27 Respirable Session #4 Personal 0.31 Inspirable Session #2 Personal 1.58 Inspirable Session #2 Static 1.18 Inspirable Session #2 Static 0.91 Inspirable Session #2 Static 0.41 Inspirable Session #2 Static 1.15 Inspirable Session #3 Personal 0.85 Inspirable Session #3 Static 0.55 Inspirable Session #3 Static 0.30 Inspirable Session #3 Static 0.14 Inspirable Session #3 Static 0.69 Inspirable Session #4 Personal 0.75 Inspirable Session #4 Static 0.87 Inspirable Session #4 Static 0.49 Inspirable Session #4 Static 0.22 Inspirable Session #4 Static 0.78

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 3110 5795 2332 30 Sec #2 4028 4594 2898 1 Min #1 4064 2297 1237 1 Min #2 2686 1272 2933 2 Min #1 1555 1731 2032 2 Min #2 2261 1537 1661

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 5088 5230 2544 30 Sec #2 6360 1837 4311 1 Min #1 5760 6572 1802 1 Min #2 2686 5442 2933 2 Min #1 1555 2138 2473 2 Min #2 2261 1908 2544

206 Appendix I Dust and bioaerosol concentrations collected from Farm 8

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Static 0.01 Respirable Session #2 Personal 0.26 Respirable Session #3 Static 0.44 Respirable Session #3 Personal 0.38 Respirable Session #4 Static 0.20 Respirable Session #4 Personal 0.00 Inspirable Session #2 Personal 2.07 Inspirable Session #2 Static 0.76 Inspirable Session #2 Static 0.77 Inspirable Session #2 Static 0.55 Inspirable Session #2 Static 0.44 Inspirable Session #3 Personal 1.72 Inspirable Session #3 Static 0.83 Inspirable Session #3 Static 0.54 Inspirable Session #3 Static 0.89 Inspirable Session #3 Static 0.00 Inspirable Session #4 Personal 0.52 Inspirable Session #4 Static 1.48 Inspirable Session #4 Static 1.24 Inspirable Session #4 Static 1.28 Inspirable Session #4 Static 0.87

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 11661 2332 1767 30 Sec #2 5512 1343 1484 1 Min #1 2403 318 1661 1 Min #2 3110 989 1272 2 Min #1 1201 2244 1714 2 Min #2 848 1025 1466

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 5866 2756 1060 30 Sec #2 7986 3392 707 1 Min #1 2968 1307 71 1 Min #2 3958 3781 777 2 Min #1 1784 3728 71 2 Min #2 2668 3304 159

207 Appendix J Dust and bioaerosol concentrations collected from Farm 9

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Static 0.04 Respirable Session #2 Personal 1.30 Respirable Session #3 Static 0.13 Respirable Session #3 Personal 0.18 Respirable Session #4 Static 0.06 Respirable Session #4 Personal 0.65 Inspirable Session #2 Personal 0.68 Inspirable Session #2 Static 0.56 Inspirable Session #2 Static 0.53 Inspirable Session #2 Static 0.64 Inspirable Session #2 Static 0.39 Inspirable Session #3 Personal 1.73 Inspirable Session #3 Static 0.34 Inspirable Session #3 Static 0.43 Inspirable Session #3 Static 0.38 Inspirable Session #3 Static 0.61 Inspirable Session #4 Personal 0.96 Inspirable Session #4 Static 0.87 Inspirable Session #4 Static 0.00 Inspirable Session #4 Static 0.82 Inspirable Session #4 Static 0.75

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2898 2615 1696 30 Sec #2 3604 2332 2191 1 Min #1 6148 2226 1166 1 Min #2 1484 2686 1272 2 Min #1 3180 989 901 2 Min #2 1219 1466 318

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 495 1060 0 30 Sec #2 636 777 71 1 Min #1 954 565 459 1 Min #2 601 813 424 2 Min #1 194 459 300 2 Min #2 389 318 194

208 Appendix K Dust and bioaerosol concentrations collected from Farm 10

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Static 3.19 Respirable Session #2 Personal 4.97 Respirable Session #3 Static 0.05 Respirable Session #3 Personal 0.27 Respirable Session #4 Static 0.16 Respirable Session #4 Personal 0.04 Inspirable Session #2 Personal 0.60 Inspirable Session #2 Static 0.87 Inspirable Session #2 Static 0.01 Inspirable Session #2 Static 0.04 Inspirable Session #2 Static 0.40 Inspirable Session #3 Personal 1.13 Inspirable Session #3 Static 0.18 Inspirable Session #3 Static 0.50 Inspirable Session #3 Static 0.41 Inspirable Session #3 Static 0.40 Inspirable Session #4 Personal 0.71 Inspirable Session #4 Static 0.10 Inspirable Session #4 Static 1.67 Inspirable Session #4 Static 0.24 Inspirable Session #4 Static 0.27

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 353 3039 1767 30 Sec #2 283 2898 1484 1 Min #1 1837 1837 1661 1 Min #2 954 954 1272 2 Min #1 618 618 1714 2 Min #2 760 760 1466

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 212 424 1060 30 Sec #2 424 1060 707 1 Min #1 106 106 71 1 Min #2 177 177 777 2 Min #1 1307 1307 71 2 Min #2 71 71 159

209 Appendix L Dust and bioaerosol concentrations collected from Farm 11

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.33 Respirable Session #2 Static 0.92 Respirable Session #3 Personal 0.25 Respirable Session #3 Static 0.14 Respirable Session #4 Personal 0.27 Respirable Session #4 Static 0.06 Inspirable Session #2 Personal 0.61 Inspirable Session #2 Static 0.74 Inspirable Session #2 Static 0.00 Inspirable Session #2 Static 0.36 Inspirable Session #2 Static 0.00 Inspirable Session #3 Personal 0.81 Inspirable Session #3 Static 0.89 Inspirable Session #3 Static 0.38 Inspirable Session #3 Static 0.13 Inspirable Session #3 Static 0.56 Inspirable Session #4 Personal 1.19 Inspirable Session #4 Static 0.48 Inspirable Session #4 Static 0.41 Inspirable Session #4 Static 1.83 Inspirable Session #4 Static 0.00

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 5300 353 353 30 Sec #2 2544 1060 283 1 Min #1 424 353 353 1 Min #2 353 848 459 2 Min #1 300 1502 318 2 Min #2 371 1113 353

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 565 1060 989 30 Sec #2 919 2615 1060 1 Min #1 813 424 813 1 Min #2 742 1272 1201 2 Min #1 71 671 530 2 Min #2 424 442 1731

210 Appendix M Dust and bioaerosol concentrations collected from Farm 12

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Static 0.19 Respirable Session #2 Personal 0.29 Respirable Session #3 Static 0.30 Respirable Session #3 Personal 0.00 Inspirable Session #2 Personal 0.72 Inspirable Session #2 Static 0.08 Inspirable Session #2 Static 0.03 Inspirable Session #2 Static 0.53 Inspirable Session #2 Static 0.30 Inspirable Session #3 Personal 0.43 Inspirable Session #3 Static 0.22 Inspirable Session #3 Static 0.08 Inspirable Session #3 Static 0.00 Inspirable Session #3 Static 0.00 Inspirable Session #3 Personal 0.09 Inspirable Session #3 Personal 0.26

Bacteria cfu m-3 Session #2 Session #3 30 Sec #1 7420 3604 30 Sec #2 3604 5018 1 Min #1 1908 2650 1 Min #2 3039 1272 2 Min #1 724 936 2 Min #2 495 1519

Fungi cfu m-3 Session #2 Session #3 30 Sec #1 2191 2968 30 Sec #2 1343 1555 1 Min #1 883 1095 1 Min #2 601 283 2 Min #1 601 1661 2 Min #2 724 1272

211 Appendix N Dust and bioaerosol concentrations collected from Farm 13

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.34 Respirable Session #2 Static 0.33 Respirable Session #3 Personal 0.22 Respirable Session #3 Static 0.28 Inspirable Session #2 Personal 0.54 Inspirable Session #2 Static 0.23 Inspirable Session #2 Static 0.34 Inspirable Session #2 Static 0.27 Inspirable Session #2 Static 0.29 Inspirable Session #3 Personal 0.29 Inspirable Session #3 Static 0.36 Inspirable Session #3 Static 0.40 Inspirable Session #3 Static 0.05

Bacteria cfu m-3 Session #2 Session #3 30 Sec #1 1201 495 30 Sec #2 1555 4311 1 Min #1 4700 1555 1 Min #2 1590 8163 2 Min #1 4276 830 2 Min #2 3198 1095

Fungi cfu m-3 Session #2 Session #3 30 Sec #1 1555 1555 30 Sec #2 2898 1767 1 Min #1 3640 2933 1 Min #2 1095 919 2 Min #1 389 1643 2 Min #2 724 848

212 Appendix O Dust and bioaerosol concentrations collected from Farm 14

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.54 Respirable Session #2 Static 0.21 Respirable Session #3 Personal 0.35 Respirable Session #3 Static 0.27 Respirable Session #4 Personal 0.16 Respirable Session #4 Static 0.03 Inspirable Session #2 Personal 1.00 Inspirable Session #2 Static 0.63 Inspirable Session #2 Static 0.21 Inspirable Session #2 Static 0.54 Inspirable Session #2 Static 0.00 Inspirable Session #3 Personal 0.94 Inspirable Session #3 Static 0.58 Inspirable Session #3 Static 0.51 Inspirable Session #3 Static 0.31 Inspirable Session #3 Static 0.29 Inspirable Session #4 Personal 0.44 Inspirable Session #4 Static 0.31 Inspirable Session #4 Static 0.50 Inspirable Session #4 Static 0.38 Inspirable Session #4 Static 0.30

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 919 1625 11449 30 Sec #2 777 777 5866 1 Min #1 353 742 954 1 Min #2 777 283 848 2 Min #1 35 124 2279 2 Min #2 88 159 636

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1201 495 1343 30 Sec #2 4735 1131 1272 1 Min #1 1025 742 283 1 Min #2 495 283 636 2 Min #1 106 601 442 2 Min #2 194 689 300

213 Appendix P Dust and bioaerosol concentrations collected from Farm 15

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.47 Respirable Session #2 Static 0.11 Respirable Session #3 Personal 0.15 Respirable Session #3 Static 0.11 Respirable Session #4 Personal 0.45 Respirable Session #4 Static 0.22 Inspirable Session #2 Personal 0.12 Inspirable Session #2 Static 0.05 Inspirable Session #2 Static 0.03 Inspirable Session #2 Static 0.08 Inspirable Session #2 Static 0.14 Inspirable Session #3 Personal 0.34 Inspirable Session #3 Static 0.14 Inspirable Session #3 Static 0.31 Inspirable Session #3 Static 0.15 Inspirable Session #3 Static 0.24 Inspirable Session #4 Personal 0.38 Inspirable Session #4 Static 0.09 Inspirable Session #4 Static 0.00 Inspirable Session #4 Static 0.19 Inspirable Session #4 Static 0.10

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 3039 3746 6572 30 Sec #2 3675 4382 9329 1 Min #1 3322 1661 1802 1 Min #2 1484 2898 4488 2 Min #1 1502 442 2403 2 Min #2 813 53 4823

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 283 1201 353 30 Sec #2 212 3039 1131 1 Min #1 742 1555 106 1 Min #2 919 283 883 2 Min #1 141 336 53 2 Min #2 336 159 194

214 Appendix Q Dust and bioaerosol concentrations collected from Farm 16

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.01 Respirable Session #2 Static 0.27 Respirable Session #3 Personal 0.10 Respirable Session #3 Static 0.21 Respirable Session #4 Personal 0.26 Respirable Session #4 Static 0.63 Inspirable Session #2 Personal 0.74 Inspirable Session #2 Static 0.26 Inspirable Session #2 Static 0.35 Inspirable Session #2 Static 0.09 Inspirable Session #2 Static 0.20 Inspirable Session #3 Personal 0.71 Inspirable Session #3 Static 0.07 Inspirable Session #3 Static 1.03 Inspirable Session #3 Static 0.37 Inspirable Session #3 Static 0.35 Inspirable Session #4 Personal 0.67 Inspirable Session #4 Static 0.32 Inspirable Session #4 Static 0.30 Inspirable Session #4 Static 0.10 Inspirable Session #4 Static 0.10

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1201 212 1696 30 Sec #2 424 283 1696 1 Min #1 424 424 1201 1 Min #2 707 1307 777 2 Min #1 283 565 442 2 Min #2 477 495 565

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2332 3604 1908 30 Sec #2 1837 3392 6078 1 Min #1 1943 2226 1519 1 Min #2 1696 1484 1201 2 Min #1 2138 724 300 2 Min #2 1572 1184 177

215 Appendix R Dust and bioaerosol concentrations collected from Farm 17

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.15 Respirable Session #2 Static 0.00 Respirable Session #3 Personal 0.68 Respirable Session #3 Static 0.25 Respirable Session #4 Personal 0.65 Respirable Session #4 Static 0.48 Inspirable Session #2 Personal 0.74 Inspirable Session #2 Static 0.24 Inspirable Session #2 Static 0.07 Inspirable Session #2 Static 0.27 Inspirable Session #2 Static 0.10 Inspirable Session #3 Personal 0.82 Inspirable Session #3 Static 0.09 Inspirable Session #3 Static 0.20 Inspirable Session #3 Static 0.44 Inspirable Session #3 Static 0.20 Inspirable Session #4 Personal 0.36 Inspirable Session #4 Static 0.32 Inspirable Session #4 Static 0.23 Inspirable Session #4 Static 0.25 Inspirable Session #4 Static 0.60

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 707 71 989 30 Sec #2 283 707 1625 1 Min #1 1131 954 106 1 Min #2 212 141 777 2 Min #1 989 88 795 2 Min #2 194 459 124

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1343 848 1837 30 Sec #2 424 4876 2615 1 Min #1 283 1307 495 1 Min #2 141 1201 601 2 Min #1 866 760 1926 2 Min #2 106 583 830

216 Appendix S Dust and bioaerosol concentrations collected from Farm 18

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.01 Respirable Session #2 Static 0.06 Respirable Session #3 Personal 0.13 Respirable Session #3 Static 0.17 Inspirable Session #2 Personal 0.21 Inspirable Session #2 Static 0.16 Inspirable Session #2 Static 0.00 Inspirable Session #2 Static 0.22 Inspirable Session #2 Static 0.26 Inspirable Session #3 Personal 0.30 Inspirable Session #3 Static 0.07 Inspirable Session #3 Static 0.22 Inspirable Session #3 Static 0.00 Inspirable Session #3 Static 0.27

Bacteria cfu m-3 Session #2 Session #3 30 Sec #1 2332 636 30 Sec #2 1555 283 1 Min #1 1731 1095 1 Min #2 530 883 2 Min #1 1484 512 2 Min #2 3145 512

Fungi cfu m-3 Session #2 Session #3 30 Sec #1 2403 707 30 Sec #2 1343 424 1 Min #1 2191 1519 1 Min #2 389 919 2 Min #1 1131 265 2 Min #2 2403 777

217 Appendix T Dust and bioaerosol concentrations collected from Farm 19

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.12 Respirable Session #2 Static 0.00 Respirable Session #3 Personal 0.00 Respirable Session #3 Static 0.24 Respirable Session #4 Personal 0.00 Respirable Session #4 Static 0.01 Inspirable Session #2 Personal 0.24 Inspirable Session #2 Static 0.03 Inspirable Session #2 Static 0.06 Inspirable Session #2 Static 0.10 Inspirable Session #2 Static 0.20 Inspirable Session #3 Personal 0.39 Inspirable Session #3 Static 0.03 Inspirable Session #3 Static 0.00 Inspirable Session #3 Static 0.12 Inspirable Session #3 Static 0.09 Inspirable Session #4 Personal 0.52 Inspirable Session #4 Static 0.00 Inspirable Session #4 Static 0.02 Inspirable Session #4 Static 0.31 Inspirable Session #4 Static 0.28

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2261 1060 2049 30 Sec #2 3604 1201 2191 1 Min #1 3251 883 2615 1 Min #2 954 1519 2297 2 Min #1 1290 1661 2668 2 Min #2 919 919 3057

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1413 212 777 30 Sec #2 1555 141 848 1 Min #1 1025 389 636 1 Min #2 883 530 1166 2 Min #1 495 972 1343 2 Min #2 477 336 954

218 Appendix U Dust and bioaerosol concentrations collected from Farm 20

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.12 Respirable Session #2 Static 0.09 Respirable Session #3 Personal 0.21 Respirable Session #3 Static 0.07 Respirable Session #4 Personal 0.23 Respirable Session #4 Static 0.10 Inspirable Session #2 Personal 1.07 Inspirable Session #2 Static 0.26 Inspirable Session #2 Static 0.35 Inspirable Session #2 Static 0.30 Inspirable Session #2 Static 0.38 Inspirable Session #3 Personal 1.63 Inspirable Session #3 Static 0.38 Inspirable Session #3 Static 0.56 Inspirable Session #3 Static 0.59 Inspirable Session #3 Static 0.52 Inspirable Session #4 Personal 2.75 Inspirable Session #4 Static 0.54 Inspirable Session #4 Static 0.93 Inspirable Session #4 Static 0.88 Inspirable Session #4 Static 0.85

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 3675 4594 20000 30 Sec #2 3180 7138 22756 1 Min #1 883 4064 9258 1 Min #2 742 4841 11025 2 Min #1 1643 2509 3074 2 Min #2 1095 2968 3410

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 3110 2615 10671 30 Sec #2 2261 2898 12155 1 Min #1 636 2014 5265 1 Min #2 742 1943 9223 2 Min #1 636 1696 1802 2 Min #2 477 1449 4876

219 Appendix V Dust and bioaerosol concentrations collected from Farm 21

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.00 Respirable Session #2 Static 0.00 Respirable Session #3 Personal 0.00 Respirable Session #3 Static 0.01 Respirable Session #4 Personal 0.00 Respirable Session #4 Static 0.00 Inspirable Session #2 Personal 0.67 Inspirable Session #2 Static 0.00 Inspirable Session #2 Static 0.33 Inspirable Session #2 Static 0.29 Inspirable Session #2 Static 0.24 Inspirable Session #3 Personal 0.26 Inspirable Session #3 Static 0.43 Inspirable Session #3 Static 0.02 Inspirable Session #3 Static 0.05 Inspirable Session #3 Static 0.40 Inspirable Session #4 Personal 0.06 Inspirable Session #4 Static 0.34 Inspirable Session #4 Static 0.34 Inspirable Session #4 Static 0.40 Inspirable Session #4 Static 0.32

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2898 1767 2191 30 Sec #2 1343 1625 2332 1 Min #1 2509 777 2191 1 Min #2 1625 1625 1519 2 Min #1 1696 848 2403 2 Min #2 1184 972 2067

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 777 1201 1272 30 Sec #2 1767 919 777 1 Min #1 813 954 636 1 Min #2 636 1166 883 2 Min #1 424 424 583 2 Min #2 583 512 654

220 Appendix W Dust and bioaerosol concentrations collected from Farm 22

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.18 Respirable Session #2 Static 0.02 Respirable Session #3 Personal 0.36 Respirable Session #3 Static 0.00 Respirable Session #4 Personal 0.03 Respirable Session #4 Static 0.03 Inspirable Session #2 Personal 0.29 Inspirable Session #2 Static 0.22 Inspirable Session #2 Static 0.05 Inspirable Session #2 Static 0.10 Inspirable Session #2 Static 0.13 Inspirable Session #3 Personal 0.37 Inspirable Session #3 Static 0.21 Inspirable Session #3 Static 0.00 Inspirable Session #3 Static 0.12 Inspirable Session #3 Static 0.03 Inspirable Session #4 Personal 0.18 Inspirable Session #4 Static 0.23 Inspirable Session #4 Static 0.00 Inspirable Session #4 Static 0.00 Inspirable Session #4 Static 0.04

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2049 1837 1908 30 Sec #2 1555 1555 1767 1 Min #1 2438 1696 1025 1 Min #2 1519 1625 1307 2 Min #1 1290 1343 1095 2 Min #2 830 2686 1078

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1131 919 919 30 Sec #2 848 2191 777 1 Min #1 742 1131 530 1 Min #2 601 777 495 2 Min #1 618 601 424 2 Min #2 512 760 1113

221 Appendix X Dust and bioaerosol concentrations collected from Farm 23

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.21 Respirable Session #2 Static 0.14 Respirable Session #3 Personal 0.07 Respirable Session #3 Static 0.10 Respirable Session #4 Personal 0.32 Respirable Session #4 Static 0.01 Inspirable Session #2 Personal 0.92 Inspirable Session #2 Static 0.76 Inspirable Session #2 Static 1.38 Inspirable Session #2 Static 1.00 Inspirable Session #2 Static 0.35 Inspirable Session #3 Personal 0.46 Inspirable Session #3 Static 0.33 Inspirable Session #3 Static 0.38 Inspirable Session #3 Static 0.00 Inspirable Session #3 Static 0.22 Inspirable Session #4 Personal 0.99 Inspirable Session #4 Static 0.16 Inspirable Session #4 Static 0.25 Inspirable Session #4 Static 0.00 Inspirable Session #4 Static 0.12

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 495 141 283 30 Sec #2 1908 141 141 1 Min #1 3710 247 141 1 Min #2 459 106 565 2 Min #1 1095 512 53 2 Min #2 2332 106 442

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2332 2049 2615 30 Sec #2 3958 1625 2827 1 Min #1 8516 2933 1272 1 Min #2 6961 530 671 2 Min #1 3905 1714 512 2 Min #2 2120 972 760

222 Appendix Y Dust and bioaerosol concentrations collected from Farm 24

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.04 Respirable Session #2 Static 0.12 Respirable Session #3 Personal 0.17 Respirable Session #3 Static 0.16 Respirable Session #4 Personal 0.65 Respirable Session #4 Static 0.25 Inspirable Session #2 Personal 2.49 Inspirable Session #2 Static 2.55 Inspirable Session #2 Static 1.24 Inspirable Session #2 Static 1.84 Inspirable Session #2 Static 1.89 Inspirable Session #3 Personal 2.08 Inspirable Session #3 Static 1.88 Inspirable Session #3 Static 1.18 Inspirable Session #3 Static 1.37 Inspirable Session #3 Static 1.62 Inspirable Session #4 Personal 2.09 Inspirable Session #4 Static 1.36 Inspirable Session #4 Static 1.03 Inspirable Session #4 Static 0.63 Inspirable Session #4 Static 1.70

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 848 1625 1201 30 Sec #2 1201 1060 1625 1 Min #1 1449 3004 2686 1 Min #2 1307 1201 1237 2 Min #1 883 2138 1466 2 Min #2 919 1696 1307

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 3604 5724 3180 30 Sec #2 3180 5300 2332 1 Min #1 2580 3145 1449 1 Min #2 2862 3357 1979 2 Min #1 1696 1625 830 2 Min #2 2332 1254 1219

223 Appendix Z Dust and bioaerosol concentrations collected from Farm 25

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.07 Respirable Session #2 Static 0.22 Respirable Session #3 Personal 0.21 Respirable Session #3 Static 0.51 Respirable Session #4 Personal 0.60 Respirable Session #4 Static 0.15 Inspirable Session #2 Personal 2.95 Inspirable Session #2 Static 2.52 Inspirable Session #2 Static 1.78 Inspirable Session #2 Static 2.36 Inspirable Session #2 Static 1.27 Inspirable Session #3 Personal 1.67 Inspirable Session #3 Static 2.53 Inspirable Session #3 Static 1.79 Inspirable Session #3 Static 0.95 Inspirable Session #3 Static 0.95 Inspirable Session #4 Personal 2.01 Inspirable Session #4 Static 0.94 Inspirable Session #4 Static 1.16 Inspirable Session #4 Static 1.44 Inspirable Session #4 Static 0.63

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 5230 3604 4382 30 Sec #2 2898 4664 2473 1 Min #1 4912 1449 4523 1 Min #2 4452 3145 2686 2 Min #1 1431 2138 3710 2 Min #2 2951 3410 2756

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 4664 4311 2332 30 Sec #2 2120 5866 1979 1 Min #1 4841 2155 1237 1 Min #2 3604 2544 954 2 Min #1 2014 1307 371 2 Min #2 2155 1555 1201

224 Appendix AA Dust and bioaerosol concentrations collected from Farm 26

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.01 Respirable Session #2 Static 2.60 Respirable Session #3 Personal 0.00 Respirable Session #3 Static 0.21 Respirable Session #4 Personal 0.15 Respirable Session #4 Static 0.03 Inspirable Session #2 Personal 1.60 Inspirable Session #2 Static 1.30 Inspirable Session #2 Static 1.48 Inspirable Session #2 Static 1.34 Inspirable Session #2 Static 0.47 Inspirable Session #3 Personal 2.75 Inspirable Session #3 Static 2.12 Inspirable Session #3 Static 0.94 Inspirable Session #3 Static 1.77 Inspirable Session #3 Static 0.91 Inspirable Session #4 Personal 2.71 Inspirable Session #4 Static 1.04 Inspirable Session #4 Static 1.06 Inspirable Session #4 Static 1.96 Inspirable Session #4 Static 1.09

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 1343 707 3958 30 Sec #2 1201 1201 3039 1 Min #1 636 389 1802 1 Min #2 1025 530 2509 2 Min #1 654 901 1837 2 Min #2 813 777 2138

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 6643 2544 2898 30 Sec #2 6007 4311 2544 1 Min #1 2686 2544 2862 1 Min #2 3251 1413 3958 2 Min #1 2102 1378 2420 2 Min #2 2438 1219 1396

225 Appendix AB Dust and bioaerosol concentrations collected from Farm 27

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 1.35 Respirable Session #2 Static 0.51 Respirable Session #3 Personal 1.27 Respirable Session #3 Static 0.74 Respirable Session #4 Personal 1.62 Respirable Session #4 Static 1.54 Inspirable Session #2 Personal 5.17 Inspirable Session #2 Static 2.04 Inspirable Session #2 Static 2.25 Inspirable Session #2 Static 1.06 Inspirable Session #2 Static 4.14 Inspirable Session #3 Personal 2.16 Inspirable Session #3 Static 2.95 Inspirable Session #3 Static 4.28 Inspirable Session #3 Static 1.44 Inspirable Session #3 Static 4.36 Inspirable Session #4 Personal 5.10 Inspirable Session #4 Static 0.40 Inspirable Session #4 Static 0.90 Inspirable Session #4 Static 0.59 Inspirable Session #4 Static 2.34

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2544 1272 4311 30 Sec #2 636 4170 1555 1 Min #1 601 3746 1767 1 Min #2 1166 2226 1696 2 Min #1 901 1413 1396 2 Min #2 830 1254 1466

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 5159 4240 2120 30 Sec #2 1837 6855 3039 1 Min #1 3039 2580 4488 1 Min #2 2191 3004 3039 2 Min #1 2491 2756 1714 2 Min #2 2438 2279 1961

226 Appendix AC Dust and bioaerosol concentrations collected from Farm 28

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.00 Respirable Session #2 Static 0.00 Respirable Session #3 Personal 0.23 Respirable Session #3 Static 0.14 Inspirable Session #2 Personal 1.54 Inspirable Session #2 Static 0.55 Inspirable Session #2 Static 0.15 Inspirable Session #2 Static 0.98 Inspirable Session #2 Static 1.12 Inspirable Session #3 Personal 1.70 Inspirable Session #3 Static 0.74 Inspirable Session #3 Static 0.40 Inspirable Session #3 Static 0.20 Inspirable Session #3 Static 0.44

Bacteria cfu m-3 Session #2 Session #3 30 Sec #1 1625 2120 30 Sec #2 1908 3675 1 Min #1 1272 2862 1 Min #2 989 1307 2 Min #1 654 1025 2 Min #2 724 1537

Fungi cfu m-3 Session #2 Session #3 30 Sec #1 1484 1979 30 Sec #2 2756 2615 1 Min #1 989 2580 1 Min #2 954 2509 2 Min #1 530 848 2 Min #2 1484 3463

227 Appendix AD Dust and bioaerosol concentrations collected from Farm 29

Dust concentrations Sampling Dust type time Type of Sampling Concentration mg m-3 Respirable Session #2 Personal 0.22 Respirable Session #2 Static 0.33 Respirable Session #3 Personal 0.06 Respirable Session #3 Static 0.18 Respirable Session #4 Personal 0.20 Respirable Session #4 Static 0.07 Inspirable Session #2 Personal 1.20 Inspirable Session #2 Static 0.28 Inspirable Session #2 Static 0.52 Inspirable Session #2 Static 0.18 Inspirable Session #2 Static 0.72 Inspirable Session #3 Personal 1.33 Inspirable Session #3 Static 0.94 Inspirable Session #3 Static 0.13 Inspirable Session #3 Static 0.23 Inspirable Session #3 Static 0.47 Inspirable Session #4 Personal 0.68 Inspirable Session #4 Static 0.29 Inspirable Session #4 Static 0.82 Inspirable Session #4 Static 0.41 Inspirable Session #4 Static 0.37

Bacteria cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 2898 1837 1060 30 Sec #2 2120 636 495 1 Min #1 1272 1378 459 1 Min #2 1590 2933 1484 2 Min #1 1148 424 318 2 Min #2 1502 477 283

Fungi cfu m-3 Session #2 Session #3 Session #4 30 Sec #1 8410 5866 4806 30 Sec #2 3110 2686 1625 1 Min #1 3216 4099 5901 1 Min #2 5760 3004 3074 2 Min #1 1502 1572 1466 2 Min #2 3463 2668 1254

228