Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
Biffa Brookhurst Wood Landfill
Air Quality Impact Assessment
Biffa Waste Services Ltd
Project number: 60586541
Date: 29th July 2019
Prepared f or: Biffa Waste Services Ltd AECOM
Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
Quality information
Prepared by Checked by Verified by Approv ed by
Andy Brown Danny Duce Garry Gray Angela Graham Air Quality Consultant Principal Air Quality Technical Director -Air Project Manager Consultant Quality
Revision History
Rev ision Rev ision Details Authorized Name Position date
R01 15/04/2019 Internal Review
R02 29/06/2019 Final 29/07/2019 Angela Graham Project Manager
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
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This document has been prepared by AECOM Infrastructure & Environment UK Limited (“AECOM”) for sole use of our client (the “Client”) in accordance w ith generally accepted consultancy principles, the budget for fees and the terms of reference agreed betw een AECOM and the Client. Any information provided by third parties and referred to herein has not been checked or verified by AECOM, unless otherw ise expressly stated in the document. No third party may rely upon this document w ithout the prior and express w ritten agreement of AECOM.
Prepared f or: Biffa Waste Services Ltd AECOM
Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
Table of Contents
Figures...... 5 Tables 5 1. Introduction ...... 1 1.1 Process Emissions ...... 1 1.2 Road Traffic Emissions ...... 2 1.3 Site Description ...... 2 1.4 Sources of Information...... 2 1.5 Assessment Structure...... 3 2. Assessment Criteria ...... 4 2.1 Environmental Standards for the Protection of Human Health ...... 4 2.2 Assessment Criteria for Sensitive Ecological Receptors ...... 5 3. Planning Policy and Legislation ...... 7 3.1 National Planning Policy Framew ork ...... 7 3.2 Planning Practice Guidance ...... 7 3.3 Local Planning Policy...... 8 3.3.1 West Sussex Waste Local Plan...... 8 3.3.2 Horsham District Council Planning Framew ork ...... 8 3.3.3 Local Air Quality Management...... 9 4. Background Air Quality...... 10 4.1 HDC A mbient Monitoring Data ...... 10
4.1.1 NO2 Monitoring Data ...... 10
4.1.2 PM10 Monitoring Data...... 10 4.2 AECOM Project Specific Monitoring Data ...... 10 4.3 UK Air Quality Archive Background Data...... 11 4.4 Summary of Background Air Quality ...... 11 5. Assessment Methodology ...... 13 5.1 Soil Washing and Heat Treatment Facility Point Source Emissions ...... 13 5.1.1 Dispersion Model Selection ...... 13 5.1.2 Emissions Data...... 14 5.1.3 Modelled Domain – Sensitive Human Receptors ...... 14 5.1.4 Modelled Domain – Sensitive Ecological Receptors ...... 15 5.1.5 Meteorological Data ...... 16 5.1.6 Terrain ...... 18 5.1.7 Surface Roughness...... 18 5.1.8 Specialised Model Treatments ...... 18
5.1.9 NOX to NO2 Conversion ...... 18 5.1.10 Calculation of Deposition at Sensitive Receptors...... 18 5.2 Road Traffic Emissions ...... 18 5.2.1 Traffic Data ...... 19
5.2.2 Bias Adjustment of Road Contribution of NOX, PM10 and PM2.5 ...... 19
5.2.3 Predicting the Number of Days in w hich the PM10 24-hour mean Objective is Exceeded...... 21
5.2.4 Predicting the Number of Days in w hich the NO2 Hourly Mean Objective is Exceeded ...... 21 5.2.5 Point Source Operational Emissions Assessment of Significance – Human Health...... 21 5.3 Point Source Operational Emissions Assessment of Significance – Ecological Habitats...... 22 5.3.1 Road Traffic Operational Emissions Assessment of Significance ...... 22 5.3.2 Road Traffic Assessment of Significance...... 23 6. Baseline Dispersion Modelling Results ...... 24
6.1 Modelling Results for Baseline NO2 ...... 24
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
6.2 Modelling Results for Baseline PM10 ...... 24
6.3 Modelling Results for Baseline PM2.5...... 26 6.4 Modelling Results for Baseline Road Derived NOx, Nutrient Nitrogen and Acid Depos ition ...... 27 7. Operation Dispersion Modelling Results ...... 29
7.1 Modelling Results for Operational NO2...... 29 7.2 Modelling Results – Impacts on Sites of Ecological Importance...... 35 7.3 Assessment Limitations and Assumptions ...... 40 8. Cumulative Impacts ...... 41 8.1 Identified Existing / Approved Projects ...... 41
8.2 Modelling Results for Baseline NO2 ...... 41
8.3 Modelling Results for Baseline PM10 ...... 42
8.4 Modelling Results for Baseline PM2.5...... 44 8.5 Modelling Results for Baseline Road Derived NOx, Nutrient Nitrogen and Acid Depos ition ...... 45
8.6 Modelling Results for Operational NO2 w ith Cumulative Developments ...... 47 8.7 Modelling Results – Impacts on Sites of Ecological Importance...... 50 9. Summary and Conclusions ...... 52 10. References...... 53 Appendix A ...... 55 Appendix B ...... 63
Figures
Figure 1:Modelled NO2 verses Monitored NO2...... 20
Figure A 1: Location of the selected sensitive receptors, point sources, and the modelling boundary...... 56 Figure A 2: Annual NOx process contribution for thermal oxidiser on ecological receptors, 2017 meteorological data ...... 57 Figure A 3: Annual NOx process contribution for thermal oxidiser for 2017 meteorological data ...... 58 th Figure A 4: 99.79 Percentile NOx process contribution for thermal oxidiser for 2018 meteorological data ...... 59 Figure A 5: Annual NOx process contribution for GA C filter for 2017 meteorological data ...... 60 th Figure A 6: 99.79 Percentile NOx process contribution for GA C Filter for 2017 meteorological data ...... 61 Figure A 7: Land north of Horsham planning boundary extent w ithin the modelled area ...... 62
Tables
Table 2-1: Env ironmental Standards for Modelled Pollutants, Point & Road Sources ...... 5 Table 2-2: Critical Level Environmental Standards for Air (Protection of Designated Habitat Sites) ...... 6 Table 4-1: HDC NO2 Diffusion Tube Monitoring Data ...... 10 Table 4-2: Site Specific NO2 Diffusion Tube 2017 Annual Mean Concentrations ...... 11 Table 4-3: Assessment of Background Air Quality Contributions ...... 12 Table 5-1: General ADMS 5 Model Conditions ...... 13 Table 5-2: General ADMS-Roads Model Conditions ...... 13 Table 5-3: Modelled Emission Sources ...... 14 Table 5-4: Physical Properties, Emissions from the Soil Washing and Heat Treatment Facility Process ...... 14 Table 5-5: Modelled Domain Selected Discrete Receptors ...... 15 Table 5-6: Modelled Domain Gridded Output ...... 15 Table 5-7: Modelled Domain Selected Ecological Receptors ...... 15 Table 5-8: Wind Rose for 2014 to 2018 for Gatw ick Airport...... 17 Table 5-9: Conversion Factors - Calculation of Nitrogen Deposition...... 18 Table 5-10: Conversion Factors - Calculation of Acid Deposition...... 18
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Table 5-11: Summary of Bias Adjustment Process...... 20 Table 5-12: Effects Descriptors at Individual Receptors - Annual Mean PM10 and NO2 ...... 22 Table 6-1: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2018 and 2020 Baseline Scenarios ...... 24 Table 6-2: Air Quality Statistics Predicted for Annual Mean PM10 Concentration for 2018 and 2020 Baseline Scenarios ...... 25 Table 6-3: Air Quality Statistics Predicted for 24-hour Mean PM10 Concentration for 2018 and 2020 Baseline Scenarios ...... 26 Table 6-4: Air Quality Statistics Predicted for Annual Mean PM2.5 Concentration for 2018 and 2020 Baseline Scenarios ...... 27 Table 6-5: Air Quality Statistics Predicted for Road Derived Annual Mean NOx Concentration for 2018 Baseline and 2020 Future Baseline Traffic Scenarios ...... 27 Table 6-6: Air Quality Statistics Predicted for Road Derived Annual Mean Nutrient Nitrogen Concentration for 2018 Baseline and 2020 Future Baseline Traffic Scenarios ...... 28 Table 6-7: Air Quality Statistics Predicted for Road Derived Annual Mean Acid Deposition Concentration for 2018 Baseline and 2020 Future Baseline Traffic Scenarios ...... 28 Table 7-1: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions – LPG Heating Plant and Thermal Ox idiser Scenario ...... 29 th Table 7-2: Air Quality Statistics Predicted for 99.79 percentile of 1-hour mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions– LPG Heating Plant and Thermal Oxidiser Scenario ...... 30 Table 7-3: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions – LPG Heating Plant and GA C Scenario...... 30 th Table 7-4: Air Quality Statistics Predicted for 99.79 percentile of 1-hour mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions– LPG Heating Plant and GAC Scenario ...... 31 Table 7-5: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst-Case Meteorological Year - LPG Heating Plant and Thermal Oxidiser Scenario ...... 33 Table 7-6: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst-Case Meteorological Year - LPG Heating Plant and GA C Scenario...... 34 Table 7-7: Stac k Dispersion Modelling Results for Sensitive Ecological Receptors – Annual Mean NOX ...... 35 Table 7-8: Stack and Roads Dispersion Modelling Results for Sensitive Ecological Receptors – Annual Mean NOX ...... 36 Table 7-9: Stac k Dispersion Modelling Results for Sensitive Ecological Receptors – Daily Mean NOX ...... 36 Table 7-10:Stack Dispersion Modelling Results for Sens itive Ecological Receptors – Annual Mean SO2 ...... 37 Table 7-11: Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Nutrient Nitrogen ...... 38 Table 7-12: Stack and Roads Dispersion Modelling Results for Sensitive Ecological Receptors – Nutrient Nitrogen ...... 39 Table 7-13: Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Acid Deposition ...... 39 Table 7-14: Stack and Roads Dispersion Modelling Results, w ithout LNH traffic for Sensitive Ecological Receptors – Acid Deposition ...... 40 Table 8-1: Air Quality Statistics Predicted for Annual Mean NO2 Concentration 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith Traffic from cumulative developments Scenarios...... 41 Table 8-2: Air Quality Statistics Predicted for Annual Mean PM10 Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith Traffic from Cumulative Developments Scenarios ...... 42 Table 8-3: Air Quality Statistics Predicted for 24-hour Mean PM10 Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith Traffic from Cumulative Developments Scenarios ...... 44 Table 8-4: Air Quality Statistics Predicted for Annual Mean PM2.5 Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith Traffic from Cumulative Developments Scenarios ...... 45 Table 8-5: Air Quality Statistics Predicted for Road Derived Annual Mean NOx Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith the Cumulative Traffic from Cumulative Developments Scenarios ...... 45 Table 8-6: Air Quality Statistics Predicted for Road Derived Annual Mean Nutrient Nitrogen Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith Traffic from Cumulative Developments Scenarios ...... 46 Table 8-7: Air Quality Statistics Predicted for Road Derived Annual Mean Acid Deposition Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith Traffic from Cumulative Developments Scenarios ...... 46 Table 8-8: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario w ith cumulative developments and Point Source Emissions – LPG Heating Plant and Thermal Ox idiser Scenario...... 47 Table 8-9: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario w ith Cumulative Developments and Point Source Emissions – LPG Heating Plant and GAC Scenario ...... 48
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Table 8-10: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst-Case Meteorological Year - LPG Heating Plant and Thermal Oxidiser Scenario, w ith Cumulative Developments ...... 49 Table 8-11: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst-Case Meteorological Year - LPG Heating Plant and GAC Scenario w ith Cumulative Developments ...... 49 Table 8-12: Dispersion Modelling Results w ith Cumulative Development traffic for Sensitive Ecological Receptors – Annual Mean NOX ...... 50 Table 8-13: Dispersion Modelling Results, w ith Cumulative Developments traffic for Sensitive Ecological Receptors – Nutrient Nitrogen ...... 50 Table 8-14: Dispersion Modelling Results, w ith Cumulative Developments traffic for Sensitive Ecological Receptors – Acid Deposition ...... 51
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
1. Introduction
AECOM has been instructed by Biffa Waste Services to prepare an assessment of the impact of emissions to air from a new Soil Washing Facility and Soil Heat Treatment Facility located at Brookhurst Wood, Horsham, West Sussex. Two planning applications are being prepared, one for the Soil Washing Facility and one for the Soil Heat Treatment Facility, how ever this assessment has been prepared to consider the effect of both facilities operating simultaneously.
Emissions to air from the facility have the potential to adversely affect human health and sensitive ecosystems. This report details the results of a dispersion modelling investigation of emissions from the LPG Heating Plant, the Thermal Oxidiser (TO) or Heat Treatment Vapour Phase Granulated Activated Carbon (GAC) filter, and emissions from road traffic. The only source of emissions to air from the Soil Washing Facility w ould be from road traffic.
1.1 Process Emissions
The assessment considers the impact of process emissions on local air quality, under the follow ing operating scenarios for the operation of new Soil Washing and Heat Treatment Facility:
• normal operation of the LPG Heating Plant and the Thermal Oxidiser; or
• normal operation of the LPG Heating Plant and the Heat Treatment Vapour Phase GAC. Only one of the tw o emission scenarios w ould occur at the facility at any one time. The option selected to abate emissions from the heat treatment process w ould be varied depending on the type of material being treated, w ith the best suited technique being employed.
The dispersion of emissions is predicted using the dispersion model ADMS 5.2. The results are presented in both tabular format and as contours of predicted ground level concentrations overlaid on mapping of the surrounding area.
The assessment of emissions to air from the LPG Heating Plant and the Thermal Oxidiser has considered the follow ing substances:
• Oxides of Nitrogen (NOX) (as Nitrogen Dioxide (NO2)); • Carbon Monoxide (CO); and
• Sulphur Dioxide (SO2). A screening assessment of emissions from the facility has been undertaken, using the Environment Agency’s H1 screening methodology, as part of the preparation of the Environmental Permit application (EPR.AB3700LS). The H1 assessment demonstrated that emissions of hydrocarbons (including benzene) could be screened out from the need to undertake a detailed assessment, for both the thermal oxidiser and GAC options. Emissions of these pollutants have therefore been determined to be insignificant, and they have not been included w ithin the scope of this assessment.
A comparison has been made betw een predicted model output concentrations, and short-term and long- term Environmental Standards, set out w ithin Environment Agency Risk Assessment for environmental permit guidance (Environment Agency, 2019).
The closest designated statutory ecological receptor is the Warnham Site of Special Scientific Interest (SSSI). This site has been declared as a SSSI on geological conservation grounds, it is considered unlikely that changes in air pollutant concentrations w ould significantly affect the integrity of the site, and therefore it is not considered further w ithin this assessment. There are, how ever, a number of local w ildlife and ancient w oodland sites near to the proposed facility, and the impact on these locations due to emissions to air from the process has been considered.
Cumulative impacts from existing industrial facilities in the area (the existing landfill site and the brickw orks) have been accounted for in the adoption of site-specific background pollutant concentrations from archive sources.
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
1.2 Road Traffic Emissions The incomplete combustion of fuel in vehicle engines results in the presence of hydrocarbons (HC) such as benzene and 1,3-butadiene, and carbon monoxide (CO) and PM10 in exhaust emissions. In addition, at the high temperatures and pressures found w ithin vehicle engines, some of the nitrogen in the air and the fuel is oxidised to form NOX, mainly in the form of nitric oxide (NO), w hich is then converted to NO2 in the atmosphere. NO2 is associated w ith adverse effects on human health. Better emission control technology and fuel specifications are expected to reduce emissions per vehicle over time.
The assessment therefore considers emissions of nitrogen oxides and particulate matter from road traffic, using the dispersion model ADMS-Roads. The magnitude of road traffic emissions for the baseline and w ith development scenarios are calculated from traffic flow data using Defra and the Devolved Administrations’ emissions factor database tool, EFT version 9.0.1. The assessment considers the impac t of road traffic emissions at receptors adjacent to roads in the vicinity of the proposed facility.
Although CO, benzene and 1,3-butadiene are present in motor vehicle exhaust emissions, detailed consideration of the associated impacts on local air quality is not considered relevant in the context of the proposed facility. Road traffic emissions of these substances have been review ed by Horsham District Council (HDC) and now here w ithin the administrative area is at risk of exceeding these objectives. The proposed changes to road traffic flow s w ould not be capable of compromising the achievement of the relevant air quality objectives for the protection of human health. Emissions of CO, benzene and 1,3- butadiene from road traffic are therefore not considered w ithin the assessment.
Emissions associated w ith the operation of the Proposed Development also have the potential to impac t upon local air quality. The potential change to emissions w ould occur as a result of a change in the number of vehicle movements from the development on the local road netw ork. The air quality assessment uses traffic flow s provided by AECOM transport consultants.
Traffic data has been provided for: an existing 2018 baseline scenario; a future w ithout-development scenario and a future w ith-development scenario. The potential for changes to long term and short term mean concentrations of particulate matter (PM10 and PM2.5) and NO2 to occur as a result of predicted changes in road traffic movements on the local road netw ork have been considered specifically for the follow ing scenarios:
• 2018 Existing Baseline for model verification purposes (Scenario 1: using 2017 meteorological year, 2018 AECOM measurement concentrations, traffic counts for the year of 2018, Emission Factor Toolkit v9.0.1 year of 2017 and Defra backgrounds of 2017);
• 2020 Future Without-Development (using 2017 meteorological year, traffic data for the year of 2020, Emission Factor Toolkit v9.0.1 year of 2017 and Defra backgrounds of 2017); and
• 2020 Future With-Development (using 2017 meteorological year, traffic data for year of 2020, Emission Factor Toolkit v9.0.1 year of 2017 and Defra backgrounds of 2017).
1.3 Site Description
The facility is located on land to the w est of Langhust Wood Road, North Horsham, and is accessed via the A264 and Langhurst Wood Road. The surrounding land use is a mixture of, industrial, agricultural and residential.
The approximate grid reference of the site is TQ 173 344. The location of the facility, in relation to the surrounding area and nearby sensitive receptors is show n in Figure A1 of Appendix A to this report.
1.4 Sources of Information
The information used w ithin this assessment includes:
• All data on emissions to atmosphere from the process, modelled as provided by Celtic Technologies and Biogenie;
• Details on the site layout provided by Biffa;
• Ordnance Survey Mapping; • Baseline air quality data from archive sources, and Local Authority monitoring data; and
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
• Meteorological data supplied by ADM Ltd.
1.5 Assessment Structure
The remainder of this assessment report is set out as follow s:
Section 2: Assessment Criteria.
Section 3: Planning Policy and Legislation
Section 4: Summary of baseline air quality w ithin the modelled domain.
Section 5: Assessment methodology.
Section 6: Baseline dispersion modelling results
Section 7: Operation dispersion modelling results.
Section 8: Cumulative Impacts.
Section 9: Summary and Conclusions.
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
2. Assessment Criteria
2.1 Environmental Standards for the Protection of Human Health
This section sets out the assessment criteria against w hich the modelled impacts from the Soil Washing and Heat Treatment Facility are assessed. The assessment criteria for Soil Washing and Heat Treatment Facility emissions from the soil w ashing and heat treatment and road traffic movements from the Facility are presented in Section 2.1.
The Environmental Standard criteria, against w hich impacts from the Soil Washing and Heat Treatment process are evaluated and road emissions associated w ith the MBT process, are set out w ithin Table 2.1. The criteria are derived from the Environmental Benchmarks contained w ithin Environment Agency Air emission risk assessment guidance (Environment Agency, 2019).
The Clean Air for Europe (CAFE) programme revisited the management of Air Quality w ithin the EU and merged much of the existing legislation into a single legal act, the Ambient Air Quality and Cleaner Air for Europe Directive 2008/50/EC (Council of European Communities, 2008). This act incorporated:
• The EU Framew ork Directive 96/62/EC (Council of European Communities, 1996) on ambient air quality assessment and management;
• The associated Daughter Directives: 1999/30/EC (Council of European Communities, 1999), 2000/69/EC (Council of European Communities, 2000) and 2002/3/EC (Council of European Communities, 2002) w hich together set out objectives and long-term target values for pollutant concentrations in ambient air; and
• The Council Decision 97/1010/EC (Council of European Communities, 1997) w hich established the exchange of information and data from netw orks and individual stations measuring ambient air pollution w ithin member states;
The new Directive 2008/50/EC (Council of European Communities, 2008) also introduces the follow ing:
• New air quality objectives for PM2.5 (fine particles) including the limit value and exposure related objectives – exposure concentration obligation and exposure reduction target
• The possibility to discount natural sources of pollution w hen assessing compliance against limit values
• The possibility for time extensions of three years (PM10) or up to five years (NO2, benzene) for complying w ith limit values, based on conditions and the assessment by the European Commiss ion.
Directive 2008/50/EC is currently transcribed into UK legislation by the Air Quality Standards Regulations 2010 (H.M. Government 2010) w hich came into force on 11th June 2010. These limit values are binding on the UK and have been set w ith the aim of avoiding, preventing or reducing harmful effects on human health and on the environment as a w hole.
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Bif f a Brookhurst Wood Landfill Air Quality Impact Assessment Project number: 60586541
Table 2-1: Environmental Standards for Modelled Pollutants, Point & Road Sources
Env ironmental Concentration Pollutant Source Measured as Standard for (µg/m3) Air Quality Limit Values 40 Annual Mean Road & Point 1-hour mean, not to NO2 Sources Air Quality Limit Values 200 be exceeded more than 18 times a year Air Quality Limit Values 40 Annual Mean 24-hour mean, not Road Sources PM10 to be exceeded Air Quality Limit Values 60 more than 35 times a year
Road Sources PM2.5 Air Quality Limit Values 25 Annual Mean 15-min mean, not to Air Quality Limit Values 266 be exceeded more than 35 times a year 1-hour mean, not to Air Quality Limit Values 350 be exceeded more Point Sources SO2 than 24 times a year 24-hour mean, not to be exceeded Air Quality Limit Values 125 more than 3 times a year Maximum daily Point Sources CO Air Quality Limit Values 10,000 running 8-hour mean
2.2 Assessment Criteria for Sensitive Ecological Receptors
The UK is bound by the terms of the European Birds and Habitats Directives and the Ramsar Convention. The Conservation of Habitats and Species Regulations 2010 (H.M Government, 2010) provides for the protection of European sites created under these polices, i.e. Special Areas of Conservation (SACs) designated pursuant to the Habitats Directive, Special Protection Areas (SPAs) classified under the Birds Directive, and Ramsar Sites designated as w etlands of international importance. The 2010 Regulations apply specific provisions of the European Directives to SACs, SPAs, candidate SACs (cSACs) and proposed SPAs (pSPAs), w hich require them to be given special consideration and further assessment by any development w hich is likely to lead to a significant effect upon them.
The legislation concerning the protection and management of designated sites and protected species w ithin England is set out w ithin the provisions of the 2010 Regulations, the Wildlife and Countryside Act 1981 (as amended) (H.M. Government, 1981) and the Countryside and Rights of Way Act 2000 (as amended) (H.M. Government, 2000)
The critical levels for the protection of vegetation and ecosystems are set out in Table 2-2, w hich apply regardless of habitat type.
In the case of SO2, the greater sensitivity of lichens and bryophytes to these pollutants is reflected in the application of a stricter EAL at locations w here such species are present. This value has been adopted as the assessment criteria for the impact of the process on ecological sites on a precautionary basis.
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Table 2-2: Critical Level Environmental Standards for Air (Protection of Designated Habitat Sit es)
Pollutant Source Concentration Measured as Notes (µg/m3)
SO2 Environmental Agency 10 Annual mean For sensitive lichen Environmental Permit communities & Guidance bryophytes and ecosystems where lichens and bryophytes are an important part of the system’s integrity
20 Annual mean For all higher plants (all other ecosystems)
NOX (as NO2) Environmental Agency 30 Annual mean - Environmental Permit Guidance 75 Daily mean - Critical load criteria for the deposition of acids and nutrient nitrogen are dependent on the habitat type and species present and are specific to the sensitive receptors considered w ithin the assessment. The critical loads are set out on the Air Pollution Information System w ebsite (APIS, 2019).
The critical load criteria adopted for the sensitive ecological receptors considered by the assessment are presented in the model results section of this report.
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3. Planning Policy and Legislation
3.1 National Planning Policy Framework
The revised National Planning Policy Framew ork (NPPF) w as published in July 2018 and amended in February 2019 (Ministry of Housing, Communities and Local Government, 2018a) and concisely sets out national policies and principles on land use planning. Paragraph 103 of the NPPF states that:
“The planning system should actively manage patterns of growth in support of these objectives. Significant development should be focused on locations which are or can be made sustainable, through limiting the need to travel and offering a genuine choice of transport modes. This can help to reduce congestion and emissions, and improve air quality and public health.”
Air quality is considered as an important element of the natural environment. On conserving and enhancing the natural environment, Paragraph 170 states that:
“Planning policies and decisions should contribute to and enhance the natural and local environment by: …
e) preventing new and existing development from contributing to, being put at unacceptable risk from, or being adversely affected by, unacceptable levels of soil, air, water or noise pollution or land instability. Development should, wherever possible, help to improve local environmental conditions such as air and water quality …”
Air quality in the UK has been managed through the Local Air Quality Management regime using national objectives. The effect of a proposed development on the achievement of such policies and plans are matters that may be a material consideration by planning authorities, w hen making decisions for individual planning applications. Paragraph 181 of the NPPF states that:
“Planning policies and decisions should sustain and contribute towards compliance with relevant limit values or national objectives for pollutants, taking into account the presence of Air Quality Management Areas and Clean Air Zones, and the cumulative impacts from individual sites in local areas. Opportunities to improve air quality or mitigate impacts should be identified, such as through traffic and travel management, and green infrastructure provision and enhancement. So far as possible these opportunities should be considered at the plan-making stage, to ensure a strategic approach and limit the need for issues to be reconsidered when determining individual applications. Planning decisions should ensure that any new development in Air Quality Management Areas and Clean Air Zones is consistent with the local air quality action plan.”
The different roles of a planning authority and a pollution control authority are addressed by the NPPF in paragraph 183:
“The focus of planning policies and decisions should be on whether proposed development is an acceptable use of land, rather than the control of processes or emissions (where these are subject to separate pollution control regimes). Planning decisions should assume that these regimes will operate effectively. Equally, where a planning decision has been made on a particular development, the planning issues should not be revisited through the permitting regimes operated by pollution control authorities.”
3.2 Planning Practice Guidance
The Planning Practice Guidance (PPG) w as updated on 22 October 2018 (Ministry of Housing, Communities and Local Government, 2018b), w ith specific reference to air quality, w hich w as published on 6 March 2014. The PPG states that the planning system should consider the potential effect of new developments on air quality w here relevant limits have been exceeded or are near the limit. Concerns also arise w here the development is likely to adversely affect the implementation of air quality strategies and action plans and/or, in particular, lead to a breach of EU legislation (including that applicable to w ildlife). In addition, dust can also be a planning concern, for example, because of the effect on local amenity.
When deciding w hether air quality is relevant to a planning application the PPG states that a number of factors should be taken into consideration including if the development w ill:
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• Significantly affect traffic in the immediate vicinity of the proposed development site or further afield. This could be by generating or increasing traffic congestion; significantly changing traffic volumes, vehicle speed or both; or significantly altering the traffic composition on local roads. Other matters to consider include whether the proposal involves the development of a bus station, coach or lorry park; adds to turnover in a large car park; or result in construction sites that would generate large Heavy Goods Vehicle flows over a period of a year or more.
• Introduce new point sources of air pollution. This could include furnaces which require prior notification to local authorities; or extraction systems (including chimneys) which require approval under pollution control legislation or biomass boilers or biomass-fuelled CHP plant; centralised boilers or CHP plant burning other fuels within or close to an air quality management area or introduce relevant combustion within a Smoke Control Area;
• Expose people to existing sources of air pollutants. This could be by building new homes, workplaces or other development in places with poor air quality.
• Give rise to potentially unacceptable impact (such as dust) during construction for nearby sensitive locations.
• Affect biodiversity. In particular, is it likely to result in deposition or concentration of pollutants that significantly affect a European-designated wildlife site, and is not directly connected with or necessary to the management of the site, or does it otherwise affect biodiversity, particularly designated wildlife sites.
On how detailed an air quality assessment needs to be, the PPG states:
“Assessments should be proportionate to the nature and scale of the development proposed and the level of concern about air quality... Mitigation options where necessary will be locationally specific, will depend on the proposed development and should be proportionate to the likely impact. It is important therefore that local planning authorities work with applicants to consider appropriate mitigation so as to ensure the new development is appropriate for its location and unacceptable risks are prevented.”
3.3 Local Planning Policy
3.3.1 West Sussex Waste Local Plan
The West Sussex Waste Local Plan w as produced in partnership w ith the South Dow ns National Park Authority and w as adopted by both authorities in 2014. It provides the basis for making consistent decisions regarding planning applications for w aste management facilities (WSCC and SDNPA, 2014).
Policy W16 covers emissions to air, soil and w ater:
“Proposals for waste development will be permitted provided that:
(a) there are no unacceptable impacts on the intrinsic quality of, and where appropriate the quantity of, air, soil, and water resources including ground, surface, transitional, and coastal waters);
(b) there are no unacceptable impacts on the management and protection of such resources, including any adverse impacts on Air Quality Management Areas and Source Protection Zones;
(c) the quality of rivers and other watercourses is protected and, where possible, enhanced (including within built-up areas); and (d) they are not located in areas subject to land instability, unless problems can be satisfactorily resolved.”
3.3.2 Horsham District Council Planning Framework
The Horsham District Planning Framew ork is the overarching planning document for HDC and replaces the Core Strategy and General Development Control Policies documents that w ere adopted in 2007 (HDC, 2015). Policies regarding odour and air quality management are highlighted below :
“Policy 24
Strategic Policy: Environmental Protection
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The high quality of the district’s environment will be protected through the planning process and the provision of local guidance document. Taking into account any relevant Planning Guidance Documents, developments will be expected to minimise exposure to and the emission of pollutants including noise, odour and light pollution and ensure that they:
4. Minimise the air pollution and greenhouse gas emissions in order to protect human health and the environment;
5. Contribute to the implementation of local Air Quality Action Plans and do not conflict with its objectives; 6. Maintain or reduce the number of people exposed to poor air quality including odour. Consideration should be given to development that will result in new public exposure, particularly where vulnerable people (e.g. the elderly, care homes or schools) would be exposed to the areas of poor air quality.”
3.3.3 Local Air Quality Management
As required by the Environment Act 1995, HDC have carried out an extensive phased review and assessment of air quality in the city against air quality objectives given in the National Air Quality Strategy. Where it is unlikely that Air Quality Objectives w ill be met, an Air Quality Management Area (AQMA) must be declared and an Air Quality Action Plan (AQAP) produced w ith the aim of achieving the Objectives.
HDC completed their first review and assessment in the year 2000 and concluded that none of the air quality objectives w ere likely to exceeded anyw here w ithin the district. This original assessment has since been used as a benchmark by the Authority against w hich they have measured future progress in making improvements to the local air quality. DEFRA guidance requires Horsham District Council to undertake periodical progress reports of local air quality.
The monitoring data for 2010 presented w ithin the most recent report confirms the results of earlier air quality reports that measured levels of nitrogen dioxide (NO2) at Storrington and Cow fold are exceeding the Air Quality Objective for this pollutant.
Detailed Assessments of air quality for these villages w ere submitted in 2010 and 2011 respectively, w hich found exceedances of the Air Quality Objective for NO2. An AQMA w as subsequently declared for Storrington and is planned for Cow fold. How ever, both of these locations are remote to the tow n of Horsham and the proposed development itself and are therefore unlikely to be affected by the proposed development.
The most recent report (HDC, 2017) commented that the monitoring of NO2 show a slight increase in 2016 compared to the tw o years previous. Nonetheless, there is still a distinct dow nw ard trend in measured NO2 concentrations over the 2006 to 2016 monitoring period. There w ere no exceedances of PM10 objectives at the tw o monitoring sites in the district.
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4. Background Air Quality
This section presents the baseline information used to determine the background ambient air quality in the area surrounding the proposed facility. Information from the follow ing sources has been used in the determination of background values. Where appropriate, the study focuses on data gathered in the vicinity of the Facility site:
• AECOM site specific NO2 diffusion tube monitoring; • HDC Ambient Monitoring Data; and
• The UK National Air Quality Information Archive.
4.1 HDC Ambient Monitoring Data
4.1.1 NO2 Monitoring Data
The 2017 Annual Status Report stated that HDC undertook monitoring at 41 locations throughout Horsham District during 2010.
The closest NO2 monitoring sites are tw o locations on Langhurst Wood Road to the south of the site access point. HDC have been monitoring NO2 at these locations using diffusion tubes since July 2008. A summary of NO2 monitoring data collected by HDC betw een 2013 and 2016 is presented in Table 4-1.
The 2017 annual mean concentration has been calculated using LAQM (TG)16 guidance using the national bias adjustment factor of 0.77 for ESG Didcot 50% TEA in Acetone and four Automatic Urban Rural Netw ork (AURN) sites: Canterbury, Chilbolton Observatory, Reading New Tow n and London Eltham.
Table 4-1: HDC NO2 Diffusion Tube Monitoring Data
3 Measured Annual Mean NO2 Concentration (µg/m ) Site Description 2013 2014 2015 2016 20171 N. Horsham 1N Outside Home Farm, Roadside 21.9 23.0 22.9 23.1 16.2 Langhurst Wood Road N. Horsham 2N Outside Graylands Roadside 19.2 18.9 17.4 20.5 14.3 Farm Cottages, Langhurst Wood Road
4.1.2 PM10 Monitoring Data
HDC monitor concentrations of particulate matter (PM10) at the continuous monitoring stations on Park Way, Horsham and at the Storrington AURN (Manleys Hill, Storrington). The annual mean PM10 concentrations recorded by these sites betw een 2013 and 2016 are w ell w ithin the objective value of 40µg/m3.
4.2 AECOM Project Specific Monitoring Data
AECOM undertook project specific NO2 diffusion tube monitoring along Langhurst Wood Road, Primros e Close, Skylark View, Durfold Road and near to the A264 betw een 28th September 2018 and 27th December 2018. A summary of the diffusion tube locations and annualisation process follow ing LAQM TG(16) (Defra, 2016) are displayed in Table 4-2. The AURN monitoring sites used in the annualisation process w ere London Eltham, Reading New Tow n, Chilbolton Observatory and Canterbury. The locations of the diffusion tubes are in Figure A1 of Appendix A.
1 Calculated using LAQM (TG)16 guidance.
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Table 4-2: Site Specific NO2 Diffusion Tube 2017 Annual Mean Concentrations
Grid Reference 2017 Period Mean NO2 Diffusion Annualised Diffusion Tube Concentration Tube Site Type NO2 Location X Y (not annualised) Identification Concentration (µg/m3) (µg/m3) Skylark View, 1 517555 133424 Roadside 21.5 21.3 Horsham Langhurst Wood 2 517695 133589 Roadside 23.3 23.1 Road, Horsham Durfold Road, 3 518006 133475 Roadside 23.6 23.4 Horsham Langhurst Wood 4 517437 134135 Roadside 19.1 18.8 Road, Horsham Primrose Urban 5 Copse, 517995 133039 24.2 24.0 Background Horsham
Langhurst Wood 6 517474 133933 Roadside 16.4 16.2 Road, Horsham Old Holbrook, 7 518319 133516 Roadside 35.7 35.3 Horsham
Bold denotes an exceedance of the air quality objective value.
3 All of the annualised NO2 diffusion tube concentrations are w ell below the objective of 40µg/m . The highest concentration is located at site 7 w hich is adjacent to the A264.
4.3 UK Air Quality Archive Background Data
Defra (Defra, 2019) provides projections of pollution concentrations across the UK at a resolution of 1 km2 for pollutants w ith objectives set out w ithin the Air Quality Strategy (AQS) for the baseline year of 2017.
Recent research (Carslaw et al, 2011) has show n that concentrations of NOX and NO2 have not reduced in line w ith predictions included in the future year background mapping available from Defra. Due to this uncertainty in the assumption that year on year background NO2 concentrations w ill decrease, 2015 background data has been used to establish the baseline conditions in order to provide a more robust estimate of background concentrations in comparison to if data projected to the opening year w as to be used.
Average background concentrations for the area around the site have been determined by taking mean values from the square in w hich the Facility is located, centred on national grid reference 517500, 134500. Where archive background concentrations have been used w ithin the assessment, these are presented in Table 4-3.
4.4 Summary of Background Air Quality The selected background concentrations for each of the pollutants considered w ithin the assessment are listed in Table 4-3.
Background concentrations of NO2, PM10 and PM2.5 have been obtained from the Defra LAQM support pages for 2017 based background maps (Defra, 2019a). The project specific monitoring survey included 3 an NO2 diffusion tube in a background location (at site 5), how ever w ith a concentration of 24.0µg/m this is higher than other monitored locations so Defra background maps for 2015 have been used for NO 2 also. The background data includes contributions from existing industrial sources, inc luding the existing landfill site and brickw orks.
Background concentrations of SO2 and CO have also been obtained from the Defra LAQM support pages, for a 2001 base year. This is considered to be the best available source of representative data for these pollutants.
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Short-term background values have been calculated by multiplying the annual mean background concentration by a factor of tw o.
The values for the background contribution to pollutant concentrations are presented in Table 4-3, as used for the calculation of long-term (LT) environmental concentrations. The LT values are all annual mean values. The values used to calculate the respective short term (ST) concentration values are also presented.
Table 4-3: Assessment of Background Air Quality Contributions
Background concentration (µg/ m3)
Receptor NO2 PM10 PM2.5 SO2 CO ID
LT ST LT LT LT ST LT ST
R1 12.4 24.8 18.3 12.8 2.6 5.1 250 500 R2 12.4 24.8 18.3 12.8 2.6 5.1 250 500
R3 12.4 24.8 18.3 12.8 2.6 5.1 250 500 R4 12.4 24.8 18.3 12.8 2.6 5.1 250 500
R5 12.4 24.8 18.3 12.8 2.6 5.1 250 500
R6 12.3 24.5 15.6 10.5 2.7 5.4 268 536 R7 10.2 20.3 14.9 9.9 2.7 5.4 245 490 R8 10.2 20.3 14.9 9.9 2.7 5.4 245 490 R9 9.9 19.8 14.5 9.7 2.7 5.4 240 480
R10 9.9 19.8 14.5 9.7 2.7 5.4 240 480 R11 9.9 19.8 14.5 9.7 2.7 5.4 240 480
R12 12.0 24.1 16.1 10.1 2.6 5.1 242 484
R13 12.0 24.1 16.1 10.1 2.6 5.1 242 484 R14_1 12.3 24.5 15.6 10.5 2.7 5.4 268 536 R14_2 12.3 24.5 15.6 10.5 2.7 5.4 268 536 R14_3 12.6 25.3 15.6 10.6 2.7 5.4 270 540
R14_4 12.6 25.3 15.6 10.6 2.7 5.4 270 540 R14_5 12.6 25.3 15.6 10.6 2.7 5.4 270 540 R15 12.6 25.3 15.6 10.6 2.7 5.4 270 540
R16 12.3 24.5 15.6 10.5 2.7 5.4 268 536
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5. Assessment Methodology
5.1 Soil Washing and Heat Treatment Facility Point Source Emissions
5.1.1 Dispersion Model Selection
The assessment of emissions from the process has been undertaken using ADMS 5.2, supplied by CERC. ADMS is a modern dispersion model that has an extensive published validation and verification history for use in the UK (CERC, 2019). ADMS Roads has been used to model the impact of road traffic emissions from the Facility. These models are regularly used throughout the UK to demonstrate regulatory compliance.
The general model conditions used in the assessment are summarised in Table 5-1 and Table 5-2. Other more detailed data used to model the dispersion of emissions is considered below.
Table 5-1: General ADMS 5 Model Conditions
Variable Input Surface Roughness at source 0.5m
Surface Roughness at Meteorological Site 0.2m
Minimum Monin-Obukhov length for stable conditions 10m Receptors Selected discrete receptors Receptor grid, variable spacing Receptor Location X, Y co-ordinates determined by GIS, z = 1.5m
Source Location X, Y co-ordinates determined by GIS Emissions Data provided by Celtic Technologies and Biogenie
Sources Burner Fan and Thermal Oxidiser; or Burner Fan and GAC filter Meteorological Data 5 years of hourly sequential data, Gatwick (2014 to 2018)
Terrain Data Complex Terrain
Table 5-2: General ADMS-Roads Model Conditions
Variable Input Surface Roughness at source 0.5m
Surface Roughness at Meteorological Site 0.2m Minimum Monin-Obukhov length for stable conditions 10m Receptors Selected discrete receptors Receptor grid, variable spacing Receptor Location X, Y co-ordinates determined by GIS, z = 1.5m
Emissions Oxides of nitrogen (NOX), particulate matter (PM 10), fine
particulate matter (PM 2.5) Emission factors EFT Version 9.0.1 emission factor dataset for 2017 Meteorological data 1 year (2017) hourly sequential data from Gatwick Airport meteorological station Emission Profile No emission profiles have been used
Model output Long-term annual mean oxides of nitrogen concentrations
Long-term annual mean particulate matter (PM 10) concentrations
Long-term annual mean fine particulate matter (PM 2.5) concentrations
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5.1.2 Emissions Data Emissions data have been sourced from Celtic Technologies and Biogenie based on the intended soil w ashing and heat treatment facility equipment likely to be installed.
Table 5-3: Modelled Emission Sources
Modelled Scenario Sources National Grid Reference
Emissions from the thermal Thermal oxidiser 517112, 134605 oxidiser and burner fan Burner fan 517121, 134600
Emissions from the thermal GAC 517118, 134598 oxidiser and GAC Burner fan 517121, 134600
Table 5-4: Physical Properties, Emissions from the Soil Washing and Heat Treatment Facility Process
Parameter Unit Burner Fan Thermal Oxidiser Granulated Activ ated Carbon Filter (GAC) Temperature (oC) 150 850 Ambient
Stack release height (m) 3 3 3
Stack internal diameter (m) 0.25 0.15 0.15
Stack gas exit velocity (m/s) 28 25 6.3
Normalised volumetric gas flow (Nm3/s) 0.89 0.11 -
Actual volumetric gas flow (Am3/s) 1.37 0.44 0.11
-1 -2 -2 NOX emission rate (g/s) 1.92 x 10 1.7 x 10 2.8 x 10
CO emission rate (g/s) 1.44 x 10-1 5.6 x 10-3 8.3 x 10-3
-2 -3 -2 SO2 emission rate (g/s) 4.81 x 10 5.6 x 10 2.6 x 10
5.1.3 Modelled Domain – Sensitive Human Receptors
Ground-level concentrations of the modelled pollutants have been predicted at the tw enty air quality sensitive receptors listed in Table 5-5. The flagpole height of the receptors has been set at 1.5 m.
The locations of these receptors are also show n in Figure A1 of this report.
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Table 5-5: Modelled Domain Selected Discrete Receptors
Receptor Description National Grid Reference
R1 South Lodge 517474, 134925
R2 Graylands Lodge 517430, 134571 R3 Bramblehurst 517386, 134221
R4 Wealdon 517406, 134152
R5 Graylands Farm Cottages 517501, 134063 R6 Home Farm 517673, 133581
R7 Andrews Farm 516514, 134126 R8 Cox Farm 516682, 134652
R9 Horsham Auction 516614, 135001
R10 Cuxfold Hill Farm 516712, 135276 R11 Nowhere House 516833, 135428
R12 Holmwood 517422, 135556
R13 Langhurst Cottage 517914, 135608
R14_1 Skylark View 517548, 133443
R14_2 Durfold Road 517932, 133496 R14_3 Durfold Road 518002, 133494
R14_4 Haybarn Drive 518199, 133461
R14_5 Northlands Road 518261, 133540 R15 Near Holbrook Park 518355, 133566
R16 Mercer Road 518052, 133962
Emissions from the facility have also been modelled on a receptor grid, in order to determine the location and magnitude of maximum ground level impacts, and to enable the generation of pollutant contour plots. The receptor grid is centred on the site, the details are presented in Table 5-6. As w ith discrete receptors, the flagpole height of receptors w ithin the grid has been set at 1.5 m.
Table 5-6: Modelled Domain Gridded Output
Spacing (m) Dimensions (m) National Grid Reference of SW Corner
25 2,000 x 2,000 516300, 518300
5.1.4 Modelled Domain – Sensitive Ecological Receptors In accordance w ith the Environmental Agency’s air emissions risk assessment guidance, the impacts associated w ith emissions from the combustion process on sensitive ecological sites have been quantified. Although there are no sensitive SSSIs w ithin 2km or European designated sites w ithin 10 km of the proposed facility, there are a number of sites of local importance and ancient w oodland w ithin 2 km of the proposed facility. Receptor locations from these sites have been included in the study.
For sensitive ecological receptors, the flagpole height has been set at 0 m.
Ground-level concentrations of the modelled pollutants relevant to sensitive ecological receptors have been predicted at locations listed in Table 5-7. The locations of these receptors are show n in Figure A2 of this report
Table 5-7: Modelled Domain Selected Ecological Receptors
Receptor Description National Grid Reference
E1 Warnham LNR 517241, 133403
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E2 Warnham Mill Pond 517241, 133403
E3 Tickfold Gill 516450, 136505 E4 Brookhurst Wood & Gill & Morris's Wood 517464, 134843
E5 Hurst Wood 518984, 134691
E6 Ancient Woodland S of LFS 517245, 134073
E7 Ancient Woodland E of Langhurst Wood Road 516919, 134703
E8 Ancient Woodland W of LFS 516980, 134221 E9 Ancient Woodland W of LFS 516934, 134708
E10 Ancient Woodland NW of LFS 516856, 135084
E11 Ancient Woodland N of LFS 517238, 135229 E12 Ancient Woodland E of Langhurst Wood Road 517495, 135206
E13 Ancient Woodland SE of LFS 517672, 133991
E14 North Heath Copse 517806, 133122
E15 Ancient Woodland, S of Warnham 515845, 133191
E16 Andrew's Gill 516492, 134355 E17 Durfold Gill 516279, 134926
E18 Hoopers Copse 515325, 135035
E19 Trueloves Wood 516096, 135765
E20 Ancient Woodland N of Marches Road 515787, 135925
E21 Tickfold Gill 516450, 136505
E22 Old Barn Gill 517730, 136602
E23 Langhurst Copse 517716, 135692
E24 Well Copse 518036, 135572 E25 Upper Rapeland Wood Furzefield 518645, 135142
E26 Holbrook Plantation 518056, 134183
E27 Graylands Plantation 517855, 134743
5.1.5 Meteorological Data
Hourly sequential data from Gatw ick Airport for the years 2014 to 2018 inclusive w ere used in this study. The station is approximately 9 km to the north-east of the Facility site. Table 5-8 displays w ind roses for 2014 to 2018 for Gatw ick Airport. The predominant w ind direction is from the south-w est for all five meteorological years.
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Table 5-8: Wind Rose for 2014 to 2018 for Gatw ick Airport
\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 Biffa BHW and Meece\400_Technical\432_Air_Quality\Met Data\Gatwick_15.met \\nm-man-001.scottwilson.co.uk\data\Projects\605865412014 Biffa BHW and Meece\400_Technical\432_Air_Quality\Met Data\Gatwick_14.met2015 0° 0° 350° 10° 350° 10° 340° 20° 340° 20° 1000 1000 330° 30° 330° 30° 900 900 320° 40° 320° 40° 800 800 310° 50° 310° 700 50° 700 600 600 300° 60° 300° 60° 500 500 400 290° 400 70° 290° 70° 300 300 200 280° 200 80° 280° 80° 100 100 270° 90° 270° 90°
260° 100° 260° 100°
250° 110° 250° 110°
240° 120° 240° 120°
230° 130° 230° 130°
220° 140° 220° 140° 210° 150° 210° 150° 200° 160° 200° 160° 190° 180° 170° 190° 180° 170° 0 3 6 10 16 (knots) 0 3 6 10 16 (knots) Wind speed Wind speed 0 1.5 3.1 5.1 8.2 (m/s) 0 1.5 3.1 5.1 8.2 (m/s) \\nm-man-001.scottwilson.co.uk\data\Projects\605865412016 Biffa BHW and Meece\400_Technical\432_Air_Quality\Met\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 Data\Gatwick_16.met2017 Biffa BHW and Meece\400_Technical\432_Air_Quality\Met Data\Gatwick_17.met 350° 0° 10° 350° 0° 10° 340° 20° 1000 340° 1000 20° 330° 30° 330° 30° 900 900 320° 40° 320° 40° 800 800 310° 700 50° 310° 700 50° 600 600 300° 60° 300° 60° 500 500 400 290° 70° 290° 400 70° 300 300 280° 200 80° 280° 200 80° 100 100 270° 90° 270° 90°
260° 100° 260° 100°
250° 110° 250° 110°
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220° 140° 220° 140° 210° 150° 210° 150° 200° 160° 200° 160° 190° 170° 180° 190° 180° 170° 0 3 6 10 16 (knots) 0 3 6 10 16 (knots) Wind speed Wind speed 0 1.5 3.1 5.1 8.2 (m/s) 0 1.5 3.1 5.1 8.2 (m/s)
\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 2018 Biffa BHW and Meece\400_Technical\432_Air_Quality\Met Data\Gatwick_18.met 350° 0° 10° 340° 1000 20° 330° 30° 900 320° 40° 800 310° 700 50° 600 300° 60° 500
290° 400 70° 300 280° 200 80° 100 270° 90°
260° 100°
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220° 140° 210° 150° 200° 160° 190° 180° 170° 0 3 6 10 16 (knots) Wind speed 0 1.5 3.1 5.1 8.2 (m/s)
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5.1.6 Terrain The land in the area around the Facility is gently undulating. There is how ever a potentially significant difference in ground levels betw een the site and sensitive receptors on Langhurst Wood Road. For this reason, terrain effects have been considered w ithin the model.
5.1.7 Surface Roughness
A surface roughness of 0.5 m w as used w ithin ADMS. This is representative of the land betw een the main stack and the selected sensitive receptors.
5.1.8 Specialised Model Treatments
Emissions have been modelled such that they are not subject to dry and w et deposition or depleted through chemical reactions. This is likely to result in an over-estimation of impacts at receptors.
5.1.9 NOX to NO2 Conversion
Emissions of NOX from the stacks w ill consist mainly of Nitric Oxide (NO) at the point of release, oxidising w ithin the atmosphere to form NO2 as it moves dow nw ind.
This assessment has assumed a 70% NOX to NO2 conversion rate at ground level in the calculation of long-term annual mean calculations and a 35% NOX to NO2 conversion rate at ground level in the calculation of short-term hourly concentrations. This is unlikely to occur in practice, especially at locations in close proximity to the Facility boundary and can be considered to represent a w orst-case approach to the assessment of impacts on local NO2 concentrations and an over-estimation of impacts.
5.1.10 Calculation of Deposition at Sensitive Receptors
The deposition of nutrient nitrogen and acid at sensitive ecological receptors is calculated, using the modelled process contribution predicted at the receptor points. The deposition rates are determined using conversion rates and factors contained w ithin Environment Agency guidance, w hich account for variations deposition mechanisms in different types of habitat.
The conversion rates and factors used in the assessment are detailed in Table 5-9 and Table 5-10.
Table 5-9: Conversion Factors - Calculation of Nitrogen Deposition
Pollutant Deposition Velocity Deposition Velocity Conv ersion Factor Grasslands (m/s) Forests (m/s) (µg/m2/s to kg/ha/yr)
NOX as NO2 0.0015 0.003 96
Table 5-10: Conversion Factors - Calculation of Acid Deposition
Pollutant Deposition Velocity Deposition Velocity Conv ersion Factor Conv ersion Factor Grasslands (m/s) Forests (m/s) (µg/m2/s to kg/ha/yr) (kg/ha/yr to keq/ha/yr)
SO2 0.012 0.024 157.7 0.0625
NO2 0.0015 0.003 96 0.0714
5.2 Road Traffic Emissions
To accompany the publication of the guidance document LAQM TG (16) (Defra, 2016), a NOX to NO 2 converter w as made available by Defra as a tool to calculate the road NO2 contribution from modelled road oxides of nitrogen contributions (Version 6.1; Defra, 2019b). The tool comes in the form of an MS Excel spreadsheet and uses borough specific data to calculate annual mean concentrations of NO2 from dispersion model output values of annual mean concentrations of NOX. This tool w as used to calculate the total NO2 concentrations at receptors from the modelled road oxides of nitrogen contribution and associated background concentration. Due to the location of the proposed development, Horsham District Council has been specified as the local authority and the ‘All other urban UK traffic’ mix selected.
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5.2.1 Traffic Data The air quality predictions are based on traffic data for Langhurst Wood Road, the A264 eastbound from the A24 to Rusper Road and the A264 w estbound from A24 to Rusper Road.
Data in the form of traffic flow s, composition (percentage heavy goods vehicles) and speed for the existing junction layout and the proposed layout have been provided by AECOM. Details of the traffic data are provided in Table B- 1 in Appendix B.
Due to the uncertainty in the rate of vehicle emissions improvement over the coming years, this assessment has used emission rates (EFT Version 9.0.1 emission factor dataset) for 2017 to represent all assessment year scenarios.
5.2.2 Bias Adjustment of Road Contribution of NOX, PM10 and PM2.5
Model verification has been informed by monitoring undertaken by Horsham District Council and AECOM. Details of the monitoring sites used in the verification process, and a summary of that process, are shown in Table 5-11 and in Figure A1 in Appendix A.
The monitoring sites w ere divided into zones representing the different conditions expected near the A264 dual carriagew ay and Langhurst Wood Road. Monitoring tubes 1, 2, 3 and 7 represented conditions near the A264, and tubes 4 and 6 w ere representative of Langhurst Wood Road.
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Table 5-11: Summary of Bias Adjustment Process
Monitoring Diffusion Tube Measured Total Unadjusted Adjusted Road NOX
Identification Description NO2 for Modelled Total Modelled Total contribution 3 3 3 2017(µg/m ) NO2 (µg/m ) NO2 (µg/m ) adjustment factor applied 1 Skylark View, 21.3 16.4 17.9 1.4 Horsham 2 Langhurst Wood 23.1 22.4 27.1 1.4 Road, Horsham 3 Durfold Road, 23.4 17.3 19.2 1.4 Horsham 4 Langhurst Wood 18.8 15.5 18.1 1.9 Road, Horsham 6 Langhurst Wood 16.2 15.0 17.1 1.9 Road, Horsham
7 Old Holbrook, 35.3 27.8 34.3 1.4 Horsham
A comparison of the unadjusted predictions and the measured concentrations at these diffusion tube locations is illustrated in Plot 1, by the blue dots and trend line (the dashed lines either side of the centre line indicate y=x +/-10% and +/- 25%).
The red dots on the chart (Figure 1) show the variation of unadjusted modelled concentration of total annual mean NO2 at the measurement (and projected measurement) locations. The blue dots show the adjusted modelled concentration of total annual mean at the measurement (and projected measurement) locations. The comparison of measured and modelled concentrations here suggests that the model performed w ithin 25% of measured values across the study area.
Figure 1:Modelled NO2 verses Monitored NO2 40.0
35.0 y = 1.2066x
30.0 y = 1.0196x
25.0
20.0
concentrations
2 )
3 15.0
(µg/m 10.0
5.0
0.0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 3
Modelled Annual Mean NO2 concentrations (µg/m ) MeasuredNO MeanAnnual Unadjusted Adjusted Unadjusted Linear Fit Adjusted Linear Fit Linear 10% 25%
The uncertainty in the model has been assessed by comparing the adjusted modelled predictions to the measured concentrations of NO2 and calculating the Root Mean Square Error (RMSE). LAQM TG (16) (Defra, 2016) identifies a standard of model uncertainty, expressed as a RMSE value that is w ithin 10% 3 of the objective value as the ideal. For annual mean NO2 10% of the objective value is 4µg/m . The combined RMSE for all the tubes in the study area w as 2.8 µg/m3 w hich can be considered robust. The
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RMSE for the tubes near Langhurst Wood Road, w hich is the location likely to be most affected by the traffic associated w ith the development, is 0.9 indicating that the model performs w ell for the area around Langhurst Wood Road.
Tubes 1 to 3 and 7 performed similarly as they w ere all located near the A264 therefore a bias adjustment factor of 1.4 w as applied to all receptors near the A264. Tubes 4 and 6 performed similarly as they w ere located near Langhurst Wood Road therefore a bias adjustment factor of 1.9 w as applied to the receptors near Langhurst Wood Road.
In the absence of suitably located sampled measurement data for the primary pollutants PM10 and PM2.5, the same approach to bias adjustment has been applied to the modelled road PM10 and PM2.5 contributions as to the primary road NOx contribution, as recommended in LAQM.TG (16).
5.2.3 Predicting the Number of Days in which the PM10 24-hour mean Objective is Exceeded
The guidance document LAQM.TG (03) (Defra, 2003) sets out the method by w hich the number of days in w hich the particulate matter 24hr objective is exceeded can be obtained based on a relationship w ith the predicted particulate matter annual mean concentration. The most recent guidance LAQM.TG (16) (Defra, 2016) suggests no change to this method. As such, the formula used w ithin this assessment is:
3 206 No. of Exceedances = 0.0014 * C + − 18.5 C
w here C is the annual mean concentration of PM10.
5.2.4 Predicting the Number of Days in which the NO2 Hourly Mean Objective is Exceeded Research projects completed on behalf of Defra and the Devolved Administrations (Laxen and Marner, 2003; and AEAT, 2008) have concluded that the hourly mean NO2 objective is unlikely to be exceeded if annual mean concentrations are predicted to be less the 60 µg/m3.
In 2003, Laxen and Marner concluded:
“…local authorities could reliably base decisions on likely exceedances of the 1-hour objective for nitrogen dioxide alongside busy streets using an annual mean of 60 µg/m3 and above.”
The findings presented by Laxen and Marner (2003) are further supported by AEAT (2008) w ho revisited the investigation to complete an updated analysis including new monitoring results and additional monitoring sites. The recommendations of this report are:
“Local authorities should continue to use the threshold of 60 µg/m3 NO2 as the trigger for considering a likely exceedance of the hourly mean nitrogen dioxide objective.”
Therefore this assessment w ill evaluate the likelihood of exceeding the hourly mean NO2 objective by comparing predicted annual mean NO2 concentrations at all receptors to an annual mean equivalent 3 threshold of 60 µg/m NO2. Where predicted concentrations are below this value, it can be concluded that 3 the hourly mean NO2 objective (200 µg/m NO2 not to be exceeded more than 18 times per year) w ill be achieved.
5.2.5 Point Source Operational Emissions Assessment of Significance – Human Health
The evaluation of the significance of air quality effects from the operational point sources has been based on the criteria referenced in the IAQM publication ‘Land Use Planning and Development Control: Planning for Air Quality’ (IAQM, 2017), and on the criteria outlined in the EA EPR Risk Assessment (Environment Agency, 2019).
The IAQM guidance (IAQM, 2017) indicates that the EA threshold criterion of 10% of the short-term Environmental Standard is sufficiently small in magnitude to be regarded as having an ‘insignificant’ effect. The IAQM guidance deviates from the EA guidance (discussed below ) w ith respect to the background contribution; the IAQM guidance indicates that severity of peak short-term concentrations can be described w ithout the need to reference background concentrations as the Process Contribution (PC) is used to measure impact, not the overall concentration at a receptor. The peak short-term PC from an elevated source is described as follow s:
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• PC ≤ 10% of the NAQS represents an ‘insignificant’ (negligible) impact;
• PC 11-20% of the NAQS is small in magnitude representing a ‘slight’ (minor) impact;
• PC 21-50% of the NAQS is medium in magnitude representing a moderate impact; and
• PC > 51% of the NAQS is large in magnitude representing a ‘substantial’ (major) impact.
The Environment Agency Risk Assessment (Environment Agency, 2019) screening criteria for comparison of PCs w ith Environmental Standards state that an emission may be considered insignificant (or negligible) w here:
• Short term PC ≤ 10% of the Environmental Standard; and
• Long term PC ≤ 1% of the Environmental Standard.
The second stage of screening considers the PCs in the context of the existing background pollutant concentrations; the predicted environmental concentration (PEC) is considered acceptable w here:
• Short term PC < 20% of the short-term Environmental Standard minus tw ice the long-term background concentration; and
• Long term PEC (PC + background concentration) < 70% of the Environmental Standard. Where the PEC is not predicted to exceed the Environmental Standard and the proposed emissions comply w ith the BAT associated emission levels (or equivalent requirements) the emissions are considered acceptable by the Environment Agency.
Where emissions are not screened as insignif icant (negligible), the descriptive terms for the air quality effect outlined in Table 5-12 below have been applied.
5.3 Point Source Operational Emissions Assessment of Significance – Ecological Habitats Specific significance criteria relating to impacts on sensitive designated ecological receptors are set out w ithin the Environmental Agency air emissions risk assessment guidance. The impact of stack emissions can be regarded as insignificant at sites w ith statutory designations if:
• The long-term impact is less than 1% of the critical load or critical level, or if greater than 1% then the Predicted Environmental Concentration is less than 70% of the critical load or critical level.
• The short-term impact is less than 10% of the critical load or critical level. The impact of stack emissions can be regarded as insignificant at sites of local importance if:
• The long-term impact is less than 100% of the critical load or critical level. • The short-term impact is less than 100% of the critical load or critical level.
5.3.1 Road Traffic Operational Emissions Assessment of Significance
With regard to road traffic emissions, the change in pollutant concentrations w ith respect to baseline concentrations has been described at receptors that are representative of exposure to impacts on local air quality w ithin the study area. The absolute magnitude of pollutant concentrations in the baseline and w ith development scenario is also described and this is used to consider the risk of the air quality limit values being exceeded in each scenario.
For a change in annual mean concentration NO2 or PM10 concentration, of a given magnitude, the IAQM have published recommendations for describing the effects of such impacts at individual receptors (IAQM, 2017).
Table 5-12: Effects Descriptors at Individual Receptors - Annual Mean PM 10 and NO2
3 Annual Mean Change in Annual Mean Concentration of NO2/PM10 (µg/m as Proportion of Objective Pollutant Value) Concentration at Receptor in <1% 1% - 2% 2% - 5% 5% - 10% >10% Assessment Imperceptible Very Low Low Medium Large Year (µg/m3)
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≤30.0 Negligible Negligible Negligible Slight Moderate 30.1 -37.9 Negligible Negligible Slight Moderate Moderate 38.0 – 40.9 Negligible Slight Moderate Moderate Substantial 41.0 – 43.9 Negligible Moderate Moderate Substantial Substantial ≥44.0 Negligible Moderate Substantial Substantial Substantial
The terminology used in Table 5-12 has been adapted from the IAQM guidance
3 A change in predicted annual mean concentrations of NO2 or PM10 of less than 0.1 µg/m is considered to be so small as to be imperceptible. A change (impact) that is imperceptible, given normal bounds of variation, w ould not be capable of having a direct effect on local air quality that could be considered to be significant.
The criteria in Table 5-12 relate to air quality statistics that are elevated about the objective values in many urban locations; this is not the case w ith PM2.5. A change in the annual mean concentration of PM2.5 equivalent to 1% of the objective value is 0.25 μg/m3. It is unusual for schemes of this type to give rise to a change of more than 0.1 μg/m3.
All relevant receptors that have been selected to represent locations w here people are likely to be present are based on impacts on human health. The air quality objective values have been set at concentrations that provide protection to all members of society, including more vulnerable groups such as the very young, elderly or unw ell. As such the sensitivity of receptors w as considered in the definition of the air quality objective values and therefore no additional subdivision of human health receptors on the basis of building or location type is necessary.
5.3.2 Road Traffic Assessment of Significance The significance of all of the reported impacts is then considered for the development in overall terms. The potential for the scheme to contribute to or interfere w ith the successful implementation of policies and strategies for the management of local air quality are considered if relevant, but the principle focus is any change to the likelihood of future achievement of the air quality objective values set out in Table 2-1 for the follow ing pollutants:
3 • Annual mean nitrogen dioxide (NO2) concentration of 40 μg/m ;
3 • Annual mean particulate matter (PM10) concentration of 40 μg/m ;
3 • Annual mean fine particulate matter (PM2.5) concentrations of 25 μg/m ;
3 • 24-hour mean PM10 concentration of 50 μg/m not to be exceeded on more than 35 days per year; and
3 • 1-hour mean NO2 concentration of 200 µg/m not to be exceeded on more than 18 times per year. The achievement of local authority goals for local air quality management are directly linked to the achievement of the air quality objective values described above and as such this assessment focuses on the likelihood of future achievement of the air quality objective values.
In terms of the significance of the consequences of any adverse impacts, an effect is reported as being either ‘not significant’ or as being ‘significant’. If the overall effect of the development on local air quality or on amenity is found to be ‘moderate’ or ‘substantial’ this is deemed to be ‘significant’. Effects found to be ‘slight’ are considered to be ‘not significant’, although they may be a matter of local concern. ‘Negligible’ effects are considered to be ‘not significant’.
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6. Baseline Dispersion Modelling Results
This section reports the baseline road modelling results for the 2018 baseline and 2020 future baseline traffic scenarios annual mean NO2, PM10 and PM2.5
6.1 Modelling Results for Baseline NO2
Predicted annual mean concentrations of NO2 at the selected receptors during the 2018 baseline and 2020 baseline scenario, are listed in Table 6-1.
Table 6-1: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2018 and 2020 Baseline Scenarios
3 Receptor Annual Mean NO2 Concentration (µg/m )
2018 Baseline 2020 Baseline R1 16.4 16.5 R2 16.5 16.6 R3 15.1 15.1 R4 15.0 15.1
R5 16.3 16.4
R6 28.2 28.6 R7 10.5 10.5
R8 10.5 10.5 R9 10.2 10.2
R10 10.2 10.2
R11 10.2 10.2 R12 12.7 12.7
R13 13.9 14.0 R14_1 19.2 19.4
R14_2 20.8 21.0
R14_3 21.5 21.7 R14_4 20.7 21.0
R14_5 20.5 20.7 R15 23.4 23.7
R16 13.4 13.5 Bold denotes a concentration that is greater than the air quality objective value.
For most receptor locations there is an increase in annual mean NO2 concentration in the 2020 baseline scenario compared to the 2018 baseline scenario. The largest increase in annual mean NO2 3 concentration is 0.4 µg/m at receptor R6. The rest of the receptors see now modelled change in NO2 concentration betw een the 2018 and 2020 baseline scenarios. At all receptor locations, the annual mean 3 NO2 concentration is w ell below the air quality limit value of 40 µg/m .
6.2 Modelling Results for Baseline PM10
Predicted annual mean concentrations of PM10 at the selected receptors during the 2018 baseline and 2020 baseline scenario, are listed in Table 6-2.
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Table 6-2: Air Quality Statistics Predicted for Annual Mean PM 10 Concentration for 2018 and 2020 Baseline Scenarios
3 Receptor Annual Mean PM 10 Concentration (µg/m )
2018 Baseline 2020 Baseline R1 19.0 19.0 R2 19.0 19.0 R3 18.7 18.7 R4 18.7 18.7
R5 18.9 18.9
R6 18.2 18.2 R7 15.0 15.0
R8 14.9 14.9 R9 14.5 14.5
R10 14.5 14.5
R11 14.5 14.5 R12 16.2 16.2
R13 16.4 16.4 R14_1 16.6 16.6
R14_2 16.8 16.9
R14_3 16.9 16.9 R14_4 16.8 16.8
R14_5 16.7 16.8 R15 17.2 17.2
R16 15.8 15.8 Bold denotes a concentration that is greater than the air quality objective value.
3 For all of the receptors there is little (0.1 µg/m ) or no change in annual mean PM10 concentration betw een the 2018 baseline and the 2020 baseline scenarios. At all receptor locations, annual mean PM 10 concentration is w ell below the air quality limit value of 40 µg/m3 for both baseline scenarios.
Predicted annual mean concentrations of the number of exceedances of the 24-hour 50 µg/m3 particulate matter air quality objective, at the selected receptors during the 2018 and 2020 baseline scenarios, are listed in Table 6-3.
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Table 6-3: Air Quality Statistics Predicted for 24-hour Mean PM10 Concentration for 2018 and 2020 Baseline Scenarios
3 Receptor Number of days PM 10 greater than 50µg/m
2018 Baseline 2020 Baseline R1 3 3 R2 3 3 R3 2 3 R4 3 3 R5 3 3 R6 2 2
R7 1 1
R8 1 1 R9 1 1 R10 1 1
R11 1 1
R12 1 1
R13 1 1 R14_1 1 1 R14_2 1 1 R14_3 1 1
R14_4 1 1
R14_5 1 1 R15 1 1
R16 1 1 Bold denotes a concentration that is greater than the air quality objective value.
For all receptor locations in each baseline scenario, the number of exceedances of the 24-hour mean 3 PM10 air quality limit value of 50 µg/m is betw een 1 and 3 days in the year. This is w ell below the limit of 35 exceedances a year.
6.3 Modelling Results for Baseline PM2.5
Predicted annual mean concentrations of PM2.5 at the selected receptors during the 2018 baseline and 2020 baseline scenario, are listed in Table 6-4.
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Table 6-4: Air Quality Statistics Predicted for Annual Mean PM 2.5 Concentration for 2018 and 2020 Baseline Scenarios
3 Receptor Annual Mean PM 2.5 Concentration (µg/m )
2018 Baseline 2020 Baseline R1 13.2 13.2 R2 13.2 13.2 R3 13.0 13.0 R4 13.0 13.1 R5 13.2 13.2 R6 12.1 12.1
R7 9.9 9.9
R8 9.9 9.9 R9 9.7 9.7 R10 9.7 9.7
R11 9.7 9.7
R12 10.2 10.2
R13 10.3 10.3 R14_1 11.1 11.1 R14_2 11.3 11.3 R14_3 11.4 11.4
R14_4 11.3 11.3
R14_5 11.3 11.3 R15 11.6 11.6
R16 10.6 10.6 Bold denotes a concentration that is greater than the air quality objective value.
At all receptors, there is no change in the annual mean PM2.5 concentration betw een the 2018 baseline and 2020 baseline scenario. In both scenarios, all concentrations are below the air quality limit value of 25 µg/m3 for annual mean PM2.5 concentration.
6.4 Modelling Results for Baseline Road Derived NOx, Nutrient Nitrogen and Acid Deposition
Baseline data for NOx, nutrient nitrogen and acid deposition are presented below. The data includes baseline traffic for each scenario respectively at ecological receptors w hich are w ithin 200m of affected roads. The tables show that under the baseline scenarios, all pollutants are w ithin critical levels and critical loads, w ith the exception of E1 and E2. These receptor points w hich are immediately adjacent to the A246, NOx, nutrient nitrogen and deposited acid concentrations at these points are currently above critical levels/loads and w ill continue to be in the future w ithout the development.
Table 6-5: Air Quality Statistics Predicted for Road Derived Annual Mean NOx Concentration for 2018 Baseline and 2020 Future Baseline Traffic Scenarios
Receptor ID 2018 Baseline 2020 Baseline
3 3 NOX (µg/m ) % Critical Level NOX (µg/m ) % Critical Level (30 µg/m 3) (30 µg/m 3)
E1 142.7 475.6 146.7 488.8
E2 142.7 475.6 146.7 488.8
E6 2.6 8.7 2.7 9.0
E12 12.2 40.7 12.6 41.8
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E13 5.6 18.8 5.8 19.4
E23 2.0 6.7 2.1 6.9
E24 1.4 4.7 1.4 4.8
Table 6-6: Air Quality Statistics Predicted for Road Derived Annual Mean Nutrient Nitrogen Concentration for 2018 Baseline and 2020 Future Baseline Traffic Scenarios
Receptor ID 2018 Baseline 2020 Baseline
N Deposition % Lower Range N Deposition % Lower Range (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Critical Load (10 kgN/ha/Yr) (10 kgN/ha/Yr)
E1 41.1 410.9 42.2 422.4 E2 41.1 410.9 42.2 422.4
E6 0.8 7.5 0.8 7.8
E12 3.5 35.1 3.6 36.2
E13 1.6 16.2 1.7 16.7
E23 0.6 5.8 0.6 6.0
E24 0.4 4.0 0.4 4.2
Table 6-7: Air Quality Statistics Predicted for Road Derived Annual Mean Acid Deposition Concentration for 2018 Baseline and 2020 Future Baseline Traffic Scenarios
Receptor ID 2018 Baseline 2020 Baseline
Acid Deposition % Lower Range Acid Deposition % Lower Range (keq/ha/Yr) CLMaxN Critical Load (keq/ha/Yr) CLMaxN Critical Load Value Value (1.536 keq/ha/Yr) (1.536 keq/ha/Yr)
E1 2.939 191.4 3.0 196.7 E2 2.939 191.4 3.0 196.7
E6 0.070 4.5 0.1 4.7
E12 0.320 20.8 0.3 21.3
E13 0.136 8.9 0.1 9.1
E23 0.071 4.6 0.1 4.7
E24 0.050 3.3 0.1 3.3
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7. Operation Dispersion Modelling Results
This section reports the results of the modelling runs described in Section 5. The results summarise the modelling results obtained from each of the scenarios outlined in Table 5-3. Contour plots, show ing the modelled process contributions to NOx concentrations, are presented as Figures A3 to A6 of this report.
In respect of each pollutant and averaging period assessed, the maximum impact reported from the modelling of five years of meteorological data is presented.
7.1 Modelling Results for Operational NO2
Oxides of nitrogen have the greatest potential impact on local air quality. This section focuses on the change in local annual mean NO2 concentrations that w ould occur as a result of the operation of the Facility and the associated road traffic emissions.
The predicted process contribution from the normal operation of the Facility w ith a thermal oxidiser, to ground-level long-term annual mean and 1-hour NO2 concentrations, at the selected sensitive receptors, are presented in Table 7-1 and Table 7-2. The same results for the GAC scenario are presented in and Table 7-3 and Table 7-4. The combined annual mean NO2 concentrations w hich include stack and roads 3 emissions are substantially below 60 µg/m it is highly unlikely that 1-hour NO2 emissions w ould be greater than the limit value, as reasoned in 5.2.4.
In both operational scenarios, the operation of the development and associated road traffic results in an increase in the annual mean NO2 concentration for the majority of receptor locations compared to the 2020 baseline scenario. The increase is small for all receptors and in the range of <0.1 to 0.8 µg/m3. The 3 annual mean NO2 limit value of 40 µg/m is not predicted to be exceeded in either operational scenario.
Table 7-1: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions – LPG Heating Plant and Thermal Oxidiser Scenario
3 Receptor Annual Mean NO2 Concentration (µg/m )
Background Road Traffic Process Total NO2 Change from Concentration Contribution Contribution Concentration 2020 Baseline from Point Scenario Sources R1 12.4 4.3 0.6 17.3 0.8
R2 12.4 4.4 0.3 17.1 0.5 R3 12.4 2.8 0.2 15.4 0.3
R4 12.4 2.8 0.2 15.4 0.3 R5 12.4 4.1 0.1 16.6 0.2 R6 12.3 16.4 <0.1 28.7 0.1
R7 10.2 0.4 0.1 10.7 0.2 R8 10.2 0.3 0.1 10.6 0.1 R9 9.9 0.3 0.1 10.3 0.1 R10 9.9 0.3 0.1 10.3 0.1 R11 9.9 0.3 0.1 10.3 0.1 R12 12 0.8 0.2 13.0 0.3 R13 12 2.1 0.2 14.3 0.3 R14_1 12.3 7.2 <0.1 19.5 0.1 R14_2 12.3 8.7 <0.1 21.0 <0.1 R14_3 12.6 9.1 <0.1 21.7 <0.1 R14_4 12.6 8.3 <0.1 20.9 <0.1 R14_5 12.6 8.1 <0.1 20.7 <0.1 R15 12.6 11.1 <0.1 23.7 <0.1 R16 12.3 1.2 0.1 13.6 0.1
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th Table 7-2: Air Quality Statistics Predicted for 99.79 percentile of 1-hour mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions– LPG Heating Plant and Thermal Oxidiser Scenario
th 3 Receptor 99.79 Percentile of 1-hour Mean NO2 Concentration (µg/m )
Background Concentration Process Contribution from Total NO2 Concentration Point Source
R1 24.8 3.0 27.8 R2 24.8 4.1 28.9
R3 24.8 2.9 27.7 R4 24.8 2.7 27.5 R5 24.8 2.2 27.0
R6 24.5 1.3 25.8 R7 20.3 1.9 22.2 R8 20.3 4.0 24.3
R9 19.8 2.4 22.2 R10 19.8 2.0 21.8 R11 19.8 1.9 21.7 R12 24.1 1.9 26.0 R13 24.1 1.5 25.6 R14_1 24.5 1.1 25.6 R14_2 24.5 1.0 25.5 R14_3 25.3 1.1 26.4 R14_4 25.3 1.0 26.3 R14_5 25.3 1.0 26.3 R15 25.3 1.0 26.3 R16 24.5 2.2 26.7
Table 7-3: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions – LPG Heating Plant and GAC Scenario
3 Receptor Annual Mean NO2 Concentration (µg/m )
Background Road Traffic Process Total NO2 Change from Concentration Contribution Contribution Concentration 2020 Baseline from Point Scenario Sources
R1 12.4 4.3 0.6 17.3 0.8 R2 12.4 4.4 0.4 17.2 0.6 R3 12.4 2.8 0.3 15.5 0.4
R4 12.4 2.8 0.2 15.4 0.3 R5 12.4 4.1 0.2 16.7 0.3 R6 12.3 16.4 0.1 28.8 0.2
R7 10.2 0.4 0.2 10.8 0.3 R8 10.2 0.3 0.2 10.7 0.2 R9 9.9 0.3 0.1 10.3 0.1 R10 9.9 0.3 0.1 10.3 0.1 R11 9.9 0.3 0.1 10.3 0.1
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3 Receptor Annual Mean NO2 Concentration (µg/m )
Background Road Traffic Process Total NO2 Change from Concentration Contribution Contribution Concentration 2020 Baseline from Point Scenario Sources R12 12 0.8 0.2 13.0 0.3 R13 12 2.1 0.2 14.3 0.3
R14_1 12.3 7.2 <0.1 19.5 0.1 R14_2 12.3 8.7 0.1 21.1 0.1 R14_3 12.6 9.1 0.1 21.8 0.1 R14_4 12.6 8.3 0.1 21.0 <0.1 R14_5 12.6 8.1 <0.1 20.7 <0.1 R15 12.6 11.1 0.1 23.8 0.1 R16 12.3 1.2 0.1 13.6 0.1
th Table 7-4: Air Quality Statistics Predicted for 99.79 percentile of 1-hour mean NO2 Concentration for 2020 Operational Scenario and Point Source Emissions– LPG Heating Plant and GAC Scenario
th 3 Receptor 99.79 Percentile of 1-hour Mean NO2 Concentration (µg/m )
Background Concentration Process Contribution from Total NO2 Concentration Point Source
R1 24.8 4.0 28.8 R2 24.8 5.0 29.8 R3 24.8 3.6 28.4 R4 24.8 3.1 27.9 R5 24.8 2.7 27.5
R6 24.5 1.4 25.9 R7 20.3 2.4 22.7 R8 20.3 4.4 24.7 R9 19.8 2.7 22.5 R10 19.8 2.3 22.1 R11 19.8 2.4 22.2
R12 24.1 2.3 26.4 R13 24.1 1.7 25.8 R14_1 24.5 1.3 25.8 R14_2 24.5 1.2 25.7 R14_3 25.3 1.3 26.6 R14_4 25.3 1.2 26.5 R14_5 25.3 1.2 26.5 R15 25.3 1.1 26.4 R16 24.5 2.7 27.2
The maximum Process Contribution (PC) and Predicted Environmental Concentration (PEC) w ithin the modelled domain, for each pollutant and operational scenario, are summarised in Table 7-5 and Table 7- 6. The PC listed, in respect of each pollutant and averaging period assessed, is the maximum impac t reported from the modelling of five years of meteorological data.
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The results show that the maximum PC values for all the pollutants is less than the relevant Environmental Assessment Levels (EAL). How ever, combined road and process annual averaged NO2 values for some receptors, including R1 and R2, are predicted to be greater than 1% of the annual mean environmental standard. Therefore, the PEC value for annual mean NO2 is compared against the long-term environmental standard. It is show n that these values, 17.3 for R1 and R2, are less than 70% of the long- term limit of 40 µg m3.
It is show n than the combined maximum process contributions and, if relevant, road emissions for particulate matter, SO2 and CO are low er than the relevant EALs.
It should be noted that the assessment is made against some w orst-case assumptions, such as a NOx to NO2 conversion rate of 70%, continuous operation of the plant throughout the year and a conservative estimation of background concentration levels.
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Table 7-5: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst -Case Meteorological Year - LPG Heating Plant and Thermal Oxidiser Scenario
Receptor Road Traffic PEC (including PEC (including where Env ironmental Point Source Pollutant Av eraging Period Contribution background) background, % Env maximum PC Standard (µg/m3) PC (µg/m3) (µg/m3) (µg/m3) Std) is located R1 Annual Mean 40 0.6 4.3 17.3 43.4 NO2 R2 99.79th percentile of 1-hour means 200 4.1 - 28.9 14.0
R6 PM10 Annual Mean 40 - 2.0 18.3 45.8
R6 PM2.5 Annual Mean 25 - 1.1 12.1 48.4 R8 99.9th percentile of 15-minute means 266 4.8 - 10.1 3.8
rd R8 SO2 99.73 percentile of 1-hour means 350 2.8 - 8.1 2.3 R1 99.18th percentile of 24-hour means 125 0.8 - 6.0 4.8 R8 CO Maximum 8-hour running mean 10,000 8.3 - 508.3 5.1
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Table 7-6: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst-Case Meteorological Year - LPG Heating Plant and GAC Scenario
Receptor Road Traffic PEC (including PEC (including where Env ironmental Point Source Pollutant Av eraging Period Contribution background) background, % Env maximum PC Standard (µg/m3) PC (µg/m3) (µg/m3) (µg/m3) Std) is located R1 Annual Mean 40 0.6 4.3 17.3 43. NO2 R2 99.79th percentile of 1-hour means 200 5.0 - 29.8 14.9
R6 PM10 Annual Mean 40 - 2.0 18.3 45.8
R6 PM2.5 Annual Mean 25 - 1.1 12.1 48.4 R2 99.9th percentile of 15-minute means 266 12.0 - 17.1 6.4
rd R2 SO2 99.73 percentile of 1-hour means 350 7.0 - 12.1 3.5 R1 99.18th percentile of 24-hour means 125 1.3 - 6.8 5.4 R8 CO Maximum 8-hour running mean 10,000 10.1 - 510.1 5.1
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7.2 Modelling Results – Impacts on Sites of Ecological Importance The results of the dispersion modelling of predicted impacts on sensitive ecological receptors are presented in this section. The tables set out the predicted PC to atmospheric concentrations of NOX and SO2, and also acid deposition and nutrient nitrogen deposition. Annual mean NOx, nutrient nitrogen deposition and acid deposition concentrations derived from roads and stack emissions are also presented for ecological receptors <200m from an affected road (E1, E2, E6, E12, E13, E23 and E24).
The impact of stack emissions can be regarded as insignificant at sites of local importance if the long- term or short-term PC is less than 100% of the critical load or critical level, regardless of baseline conditions. As there are no sensitive ecological receptors designated as being of National or European importance w ithin the study area, the assessment has not considered the baseline if the PC is less than 100% of the critical load or critical level.
Nutrient nitrogen and acidity targets vary depending on location, how ever defined critical loads for nitrogen and acid deposition are not available for sites of local importance. In the absence of bespoke values, representative critical loads for the types of habitat considered have been selected from the APIS w ebsite. In this assessment, all receptors w ere assumed to be composed of unmanaged broadleaved and deciduous w oodland habitat.
The critical load range for unmanaged broadleaved and deciduous w oodland is 10 – 20 kgN/ha/year. The low er range acidity critical load is:
• CLMinN – 0.142 keq/ha/year.
• CLMaxS – 1.251 keq/ha/year. • CLMaxN – 1.536 keq/ha/year.
The assessment results show that the predicted impacts are w ithin the criteria for insignificance at all of the selected receptors for both the thermal oxidiser and GAC filter scenarios. Where concentrations of annual mean NOx, nutrient nitrogen deposition and acid deposition are presented for ecological receptors <200m from an affected road, concentrations at E1 and E2 are show n to be above critical levels/loads . This is also the case in base scenarios, indicating that NOx, nutrient nitrogen and deposited acid concentrations at the closest points to the road for these receptors are currently above critical levels/loads and w ill continue to be in the future w ith or w ithout the development.
Table 7-7: Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Annual Mean NOX
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 NOX PC (µg/m ) % Critical Level NOX PC (µg/m ) % Critical Level (30 µg/m3) (30 µg/m3)
E1 0.04 0.1 0.04 0.1
E2 0.04 0.1 0.04 0.1 E3 0.05 0.2 0.05 0.2
E4 0.71 2.4 0.74 2.5
E5 0.03 0.1 0.03 0.1 E6 0.13 0.4 0.16 0.5
E7 0.35 1.2 0.51 1.7 E8 0.34 1.1 0.42 1.4
E9 0.39 1.3 0.55 1.8
E10 0.22 0.7 0.27 0.9
E11 0.47 1.6 0.61 2.0
E12 0.56 1.9 0.68 2.3
E13 0.18 0.6 0.21 0.7 E14 0.04 0.1 0.04 0.1
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Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 NOX PC (µg/m ) % Critical Level NOX PC (µg/m ) % Critical Level (30 µg/m3) (30 µg/m3)
E15 0.03 0.1 0.04 0.1
E16 0.32 1.1 0.41 1.4
E17 0.07 0.2 0.08 0.3
E18 0.04 0.1 0.04 0.1
E19 0.04 0.1 0.04 0.1
E20 0.03 0.1 0.03 0.1
E21 0.05 0.2 0.05 0.2
E22 0.10 0.3 0.12 0.4
E23 0.25 0.8 0.30 1.0
E24 0.23 0.8 0.25 0.8
E25 0.06 0.2 0.06 0.2
E26 0.11 0.4 0.12 0.4
E27 0.15 0.5 0.16 0.5
Table 7-8: Stack and Roads Dispersion Modelling Results for Sensitive Ecological Receptors – Annual Mean NOX
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 NOX PC (µg/m ) % Critical Level NOX PC (µg/m ) % Critical Level (30 µg/m3) (30 µg/m3)
E1 146.8 489.2 146.8 489.2
E2 146.8 489.2 146.8 489.2 E6 2.9 9.5 2.9 9.6
E12 14.0 46.6 14.1 47.0
E13 6.1 20.2 6.1 20.3 E23 2.4 8.1 2.5 8.3
E24 1.7 5.8 1.8 5.8
Table 7-9: Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Daily Mean NOX
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 NOX PC (µg/m ) % Critical Level NOX PC (µg/m ) % Critical Level (75 µg/m3) (75 µg/m3)
E1 0.77 1.0 0.83 1.1
E2 0.77 1.0 0.83 1.1
E3 0.61 0.8 0.67 0.9
E4 3.13 4.2 3.19 4.3
E5 0.36 0.5 0.38 0.5
E6 2.84 3.8 3.18 4.2
E7 6.01 8.0 9.06 12.1
E8 4.78 6.4 6.11 8.2
E9 6.30 8.4 8.23 11.0
E10 2.80 3.7 3.45 4.6
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Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 NOX PC (µg/m ) % Critical Level NOX PC (µg/m ) % Critical Level (75 µg/m3) (75 µg/m3)
E11 3.57 4.8 4.12 5.5
E12 2.48 3.3 3.02 4.0
E13 1.98 2.6 2.36 3.1
E14 0.87 1.2 1.02 1.4
E15 0.62 0.8 0.71 0.9
E16 3.05 4.1 3.84 5.1
E17 5.67 7.6 6.56 8.8
E18 2.00 2.7 2.09 2.8
E19 0.75 1.0 0.80 1.1
E20 0.50 0.7 0.54 0.7
E21 0.61 0.8 0.67 0.9
E22 0.67 0.9 0.76 1.0
E23 1.17 1.6 1.41 1.9
E24 1.23 1.6 1.34 1.8
E25 0.46 0.6 0.48 0.6
E26 1.13 1.5 1.28 1.7
E27 1.04 1.4 1.17 1.6
Table 7-10:Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Annual Mean SO2
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 SO2 PC (µg/m ) % Critical Level SO2 PC (µg/m ) % Critical Level (10 µg/m3) (10 µg/m3)
E1 0.01 0.1 0.02 0.2
E2 0.01 0.1 0.02 0.2
E3 0.01 0.1 0.02 0.2
E4 0.18 1.8 0.24 2.4
E5 0.01 0.1 0.01 0.1
E6 0.03 0.3 0.07 0.7
E7 0.09 0.9 0.26 2.6
E8 0.09 0.9 0.18 1.8
E9 0.10 1.0 0.27 2.7
E10 0.06 0.6 0.11 1.1
E11 0.12 1.2 0.28 2.8
E12 0.14 1.4 0.29 2.9
E13 0.05 0.5 0.09 0.9
E14 0.01 0.1 0.02 0.2
E15 0.01 0.1 0.01 0.1
E16 0.08 0.8 0.19 1.9
E17 0.02 0.2 0.03 0.3
E18 0.01 0.1 0.01 0.1
E19 0.01 0.1 0.02 0.2
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Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 SO2 PC (µg/m ) % Critical Level SO2 PC (µg/m ) % Critical Level (10 µg/m3) (10 µg/m3)
E20 0.01 0.1 0.01 0.1
E21 0.01 0.1 0.02 0.2
E22 0.03 0.3 0.05 0.5
E23 0.07 0.7 0.13 1.3
E24 0.06 0.6 0.09 0.9
E25 0.02 0.2 0.02 0.2
E26 0.03 0.3 0.04 0.4
E27 0.04 0.4 0.06 0.6
Table 7-11: Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Nutrient Nitrogen
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
N Deposition % Lower Range N Deposition % Lower Range (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Critical Load (10 kgN/ha/Yr) (10 kgN/ha/Yr)
E1 0.01 0.1 0.01 0.1
E2 0.01 0.1 0.01 0.1
E3 0.01 0.1 0.02 0.2
E4 0.20 2.0 0.21 2.1
E5 0.01 0.1 0.01 0.1
E6 0.04 0.4 0.05 0.5
E7 0.10 1.0 0.15 1.5
E8 0.10 1.0 0.12 1.2
E9 0.11 1.1 0.16 1.6
E10 0.06 0.6 0.08 0.8
E11 0.13 1.3 0.17 1.7
E12 0.16 1.6 0.20 2.0
E13 0.05 0.5 0.06 0.6
E14 0.01 0.1 0.01 0.1
E15 0.01 0.1 0.01 0.1
E16 0.09 0.9 0.12 1.2
E17 0.02 0.2 0.02 0.2
E18 0.01 0.1 0.01 0.1
E19 0.01 0.1 0.01 0.1
E20 0.01 0.1 0.01 0.1
E21 0.01 0.1 0.02 0.2
E22 0.03 0.3 0.04 0.4
E23 0.07 0.7 0.09 0.9
E24 0.07 0.7 0.07 0.7
E25 0.02 0.2 0.02 0.2
E26 0.03 0.3 0.03 0.3
E27 0.04 0.4 0.05 0.5
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Table 7-12: Stack and Roads Dispersion Modelling Results for Sensitive Ecological Receptors – Nutrient Nitrogen
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario N Deposition % Lower Range N Deposition % Lower Range (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Critical Load (10 kgN/ha/Yr) (10 kgN/ha/Yr)
E1 42.3 422.7 42.3 422.7
E2 42.3 422.7 42.3 422.7
E6 0.8 8.2 0.8 8.3
E12 4.0 40.3 4.1 40.6 E13 1.7 17.5 1.8 17.6
E23 0.7 7.0 0.7 7.2
E24 0.5 5.0 0.5 5.0
Table 7-13: Stack Dispersion Modelling Results for Sensitive Ecological Receptors – Acid Deposition
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario Acid Deposition % Lower Range Acid Deposition % Lower Range (keq/ha/Yr) CLMaxN Critical Load (keq/ha/Yr) CLMaxN Critical Load Value Value (1.536 keq/ha/Yr) (1.536 keq/ha/Yr)
E1 0.003 0.2 0.005 0.3
E2 0.003 0.2 0.005 0.3
E3 0.004 0.3 0.005 0.4
E4 0.058 3.7 0.073 4.7
E5 0.003 0.2 0.003 0.2 E6 0.011 0.7 0.019 1.3
E7 0.029 1.9 0.071 4.6
E8 0.028 1.8 0.051 3.3 E9 0.032 2.1 0.076 4.9
E10 0.018 1.2 0.033 2.1
E11 0.038 2.5 0.078 5.0
E12 0.046 3.0 0.083 5.4
E13 0.015 1.0 0.025 1.6 E14 0.003 0.2 0.005 0.3
E15 0.003 0.2 0.004 0.2
E16 0.026 1.7 0.053 3.4 E17 0.005 0.4 0.009 0.6
E18 0.003 0.2 0.004 0.3
E19 0.003 0.2 0.004 0.3
E20 0.002 0.2 0.003 0.2
E21 0.004 0.3 0.005 0.4 E22 0.008 0.5 0.015 1.0
E23 0.021 1.3 0.036 2.3
E24 0.019 1.2 0.026 1.7
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Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
Acid Deposition % Lower Range Acid Deposition % Lower Range (keq/ha/Yr) CLMaxN Critical Load (keq/ha/Yr) CLMaxN Critical Load Value Value (1.536 keq/ha/Yr) (1.536 keq/ha/Yr)
E25 0.005 0.3 0.006 0.4
E26 0.009 0.6 0.013 0.8
E27 0.012 0.8 0.017 1.1
Table 7-14: Stack and Roads Dispersion Modelling Results, without LNH traffic for Sensitive Ecological Receptors – Acid Deposition
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
Acid Deposition % Lower Range Acid Deposition % Lower Range (keq/ha/Yr) CLMaxN Critical Load (keq/ha/Yr) CLMaxN Critical Load Value Value (1.536 keq/ha/Yr) (1.536 keq/ha/Yr)
E1 3.0 196.7 3.0 196.8 E2 3.0 196.7 3.0 196.8
E6 0.1 4.4 0.1 4.9 E12 0.3 21.0 0.4 23.4
E13 0.1 8.8 0.1 9.5
E23 0.1 4.3 0.1 5.3 E24 0.0 3.2 0.1 3.7
7.3 Assessment Limitations and Assumptions This section outlines the potential limitations associated w ith the dispersion modelling assessment. Where assumptions have been made, this is also detailed w ithin this section.
The greatest uncertainty w ith any dispersion modelling assessment arises through the inherent uncertainty associated w ith the use of the dispersion modelling itself. Despite this, the use of dispersion modelling is a w idely applied and accepted approach for the prediction of impacts from a Facility such as this one.
In order to minimise the likelihood that the ground-level process contribution due to the Facility’s emissions have not been under-estimated, the follow ing w orst-case assumptions have been made w ithin the assessment in order to provide a robust assessment of impacts:
• The modelling predictions are based on the use of five full years of meteorological data from Gatw ick, for the years 2014 to 2018. The use of five years data can be considered to represent the majority of adverse meteorological conditions that w ould be experienced during the future operation of the Facility;
• A 70% NOX to NO2 conversion rate has been assumed in predicting the long-term Process Contribution to background NO2 concentrations;
• A 35% NOX to NO2 conversion rate has been assumed in predicting the short-term Process Contribution to background NO2 concentrations; and
• The continuous operation of the plant through the year.
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8. Cumulative Impacts
8.1 Identified Existing / Approved Projects
In terms of potential cumulative effects due to the interaction of noise during construction and operational stages of other nearby development schemes, the follow ing developments have been identified:
• Wealden Brickw orks Energy from Waste Plant (West Sussex County Council, planning reference WSCC/015/18/NH); and
• Land North of Horsham Residential Area (Horsham District Council, planning reference DC/16/1677).
The Energy from Waste Plant Site is located directly adjacent to the application site on an existing w aste site. The site w as refused planning permission but is going to enquiry in early Autumn 2019. The Air Quality Environmental Statement chapter submitted w ith the Planning Application concluded that the development w ould not result in any significant effects on surrounding air quality sensitive receptors during construction or operational stages.
The North Horsham Residential Site is located to the east of the application Site, w ith the nearest boundary approximately w ithin 650m of the proposed development. The Air Quality Environmental Statement chapter submitted w ith the Planning Application concluded that the development w ould not result in any significant effects on air quality sensitive receptors during construction or operational stages. The receptors presented in results section 7 of this report provide a sufficiently conservative estimate of potential stack emissions at the Land North of Horsham development. The cumulative impact of the Land North of Horsham development, w ith road traffic and stack emissions at human and ecological receptors is presented in this section. Figure A7 show s the planning application boundary for the Land North of Horsham development and the location of the representative air quality receptors used in this study.
8.2 Modelling Results for Baseline NO2
Predicted annual mean concentrations of NO2 at the selected receptors during the 2018 baseline, 2020 baseline scenario and 2020 future baseline w ith the traffic from cumulative developments, are listed in Table 8-1.
Table 8-1: Air Quality Statistics Predicted for Annual Mean NO2 Concentration 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline with Traffic from cumulative developments Scenarios
3 Receptor Annual Mean NO2 Concentration (µg/m )
2018 Baseline 2020 Baseline 2020 Baseline with Cumulative Developments R1 16.4 16.5 16.5 R2 16.5 16.6 16.6
R3 15.1 15.1 15.2 R4 15.0 15.1 15.1 R5 16.3 16.4 16.4
R6 28.2 28.6 28.8
R7 10.5 10.5 10.5
R8 10.5 10.5 10.5
R9 10.2 10.2 10.2 R10 10.2 10.2 10.2 R11 10.2 10.2 10.2
R12 12.7 12.7 12.8 R13 13.9 14.0 14.0
R14_1 19.2 19.4 19.6 R14_2 20.8 21.0 21.1
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R14_3 21.5 21.7 21.9
R14_4 20.7 21.0 21.1 R14_5 20.5 20.7 20.8
R15 23.4 23.7 23.9 R16 13.4 13.5 13.5 Bold denotes a concentration that is greater than the air quality objective value.
For most receptor locations there is an increase in annual mean NO2 concentration in the 2020 baseline scenario compared to the 2018 baseline scenario. The largest increase in annual mean NO2 concentration 3 from 2018 to 2020 is 0.4 µg/m at receptor R6. Baseline NO2 concentrations for 2020 w ith cumulativ e developments are greater than w ithout. The largest increase in annual mean NO2 concentration from 2018 to 2020 w ith cumulative developments is 0.6 µg/m3 at receptor R6. At all receptor locations, the annual 3 mean NO2 concentration is w ell below the air quality limit value of 40 µg/m .
8.3 Modelling Results for Baseline PM10
Predicted annual mean concentrations of PM10 at the selected receptors during the 2018 baseline, 2020 baseline scenario and 2020 future baseline w ith the cumulative traffic from cumulative developments , are listed in Table 8-2.
Table 8-2: Air Quality Statistics Predicted for Annual Mean PM 10 Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline with Traffic from Cumulative Developments Scenarios
3 Receptor Annual Mean PM 10 Concentration (µg/m )
2018 Baseline 2020 Baseline 2020 Baseline with Cumulative Developments R1 19.0 19.0 19.0 R2 19.0 19.0 19.0 R3 18.7 18.7 18.7 R4 18.7 18.7 18.7
R5 18.9 18.9 18.9 R6 18.2 18.2 18.3
R7 15.0 15.0 15.0 R8 14.9 14.9 14.9 R9 14.5 14.5 14.5
R10 14.5 14.5 14.5 R11 14.5 14.5 14.5
R12 16.2 16.2 16.2 R13 16.4 16.4 16.4 R14_1 16.6 16.6 16.7
R14_2 16.8 16.9 16.9 R14_3 16.9 16.9 16.9
R14_4 16.8 16.8 16.8 R14_5 16.7 16.8 16.8 R15 17.2 17.2 17.3
R16 15.8 15.8 15.8 Bold denotes a concentration that is greater than the air quality objective value.
For all of the receptors there is little or no change in annual mean PM10 concentration betw een the 2018 baseline and the 2020 baseline scenarios. Receptors R1, R2 and R6 are the only ones w here a difference is observed, each is 0.1 µg/m3. Similar observations can be made w hen considering 2020 baseline w ith cumulative developments relative to 2018, w here R1, R2, R6, R7, R14_3 and R14_4 are the only changes
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3 each by 0.1 µg/m . At all receptor locations, annual mean PM10 concentration is w ell below the air quality limit value of 40 µg/m3 for both baseline scenarios.
Predicted annual mean concentrations of the number of exceedances of the 24-hour 50 µg/m3 particulate matter air quality objective, at the selected receptors during the 2018 baseline, 2020 baseline scenario and 2020 future baseline w ith the cumulative traffic from cumulative developments, are listed in Table 8-3.
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Table 8-3: Air Quality Statistics Predicted for 24-hour Mean PM10 Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline with Traffic from Cumulative Developments Scenarios
3 Receptor Number of days PM 10 greater than 50µg/m
2018 Baseline 2020 Baseline 2020 Baseline with Cumulative Developments R1 3 3 3 R2 3 3 3 R3 2 3 3
R4 3 3 3 R5 3 3 3
R6 2 2 2 R7 1 1 1
R8 1 1 1
R9 1 1 1 R10 1 1 1
R11 1 1 1 R12 1 1 1
R13 1 1 1
R14_1 1 1 1 R14_2 1 1 1
R14_3 1 1 1 R14_4 1 1 1
R14_5 1 1 1
R15 1 1 1 R16 1 1 1 Bold denotes a concentration that is greater than the air quality objective value.
For all receptor locations in each baseline scenario, the number of exceedances of the 24-hour mean 3 PM10 air quality limit value of 50 µg/m is betw een 1 and 3 days in the year. This is w ell below the limit of 35 exceedances a year.
8.4 Modelling Results for Baseline PM2.5
Predicted annual mean concentrations of PM2.5 at the selected receptors during the 2018 baseline, 2020 baseline scenario and 2020 future baseline w ith the cumulative traffic from cumulative developments, are listed in Table 8-4.
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Table 8-4: Air Quality Statistics Predicted for Annual Mean PM 2.5 Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline with Traffic from Cumulative Developments Scenarios
3 Receptor Annual Mean PM 2.5 Concentration (µg/m )
2018 Baseline 2020 Baseline 2020 Baseline with Cumulative Developments R1 13.2 13.2 13.2 R2 13.2 13.2 13.2 R3 13.0 13.0 13.1
R4 13.0 13.1 13.1 R5 13.2 13.2 13.2
R6 12.1 12.1 12.1 R7 9.9 9.9 9.9
R8 9.9 9.9 9.9
R9 9.7 9.7 9.7 R10 9.7 9.7 9.7
R11 9.7 9.7 9.7 R12 10.2 10.2 10.2
R13 10.3 10.3 10.3
R14_1 11.1 11.1 11.2 R14_2 11.3 11.3 11.3
R14_3 11.4 11.4 11.4 R14_4 11.3 11.3 11.4
R14_5 11.3 11.3 11.3
R15 11.6 11.6 11.6 R16 10.6 10.6 10.6 Bold denotes a concentration that is greater than the air quality objective value.
At all receptors, there is no change in the annual mean PM2.5 concentration betw een the 2018 baseline and 2020 baseline scenario. In both scenarios, all concentrations are below the air quality limit value of 25 µg/m3 for annual mean PM2.5 concentration.
8.5 Modelling Results for Baseline Road Derived NOx, Nutrient Nitrogen and Acid Deposition
Baseline data for NOx, nutrient nitrogen and acid deposition are presented below. The data includes baseline traffic for each scenario respectively. The tables show that under the baseline scenarios, all pollutants are w ithin critical levels and critical loads, w ith the exception of E1 and E2. These r eceptor points w hich are immediately adjacent to the A246, NOx, nutrient nitrogen and deposited acid concentrations at these points are currently above critical levels/loads and w ill continue to be in the future w ithout the development and cumulative developments.
Table 8-5: Air Quality Statistics Predicted for Road Derived Annual Mean NOx Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline w ith the Cumulative Traffic from Cumulative Developments Scenarios
Receptor ID 2018 Baseline 2020 Baseline 2020 Baseline with Cumulativ e Dev elopments
3 3 3 NOX (µg/m ) % Critical Level NOX (µg/m ) % Critical Level NOX (µg/m ) % Critical (30 µg/m3) (30 µg/m3) Lev el (30 µg/m3)
E1 142.7 475.6 146.7 488.8 148.8 496.0
E2 142.7 475.6 146.7 488.8 148.8 496.0
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Receptor ID 2018 Baseline 2020 Baseline 2020 Baseline with Cumulativ e Dev elopments
3 3 3 NOX (µg/m ) % Critical Level NOX (µg/m ) % Critical Level NOX (µg/m ) % Critical (30 µg/m3) (30 µg/m3) Lev el (30 µg/m3)
E6 2.6 8.7 2.7 9.0 2.8 9.2
E12 12.2 40.7 12.6 41.8 13.4 44.8
E13 5.6 18.8 5.8 19.4 6.0 19.9
E23 2.0 6.7 2.1 6.9 2.2 7.3
E24 1.4 4.7 1.4 4.8 1.5 5.0
Table 8-6: Air Quality Statistics Predicted for Road Derived Annual Mean Nutrient Nitrogen Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline with Traffic from Cumulative Developments Scenarios
Receptor ID 2018 Baseline 2020 Baseline 2020 Baseline with Cumulativ e Dev elopments
N Deposition % Lower Range N Deposition % Lower Range N Deposition % Lower (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Range (10 kgN/ha/Yr) (10 kgN/ha/Yr) Critical Load (10 kgN/ha/Yr)
E1 41.1 410.9 42.2 422.4 42.9 428.5
E2 41.1 410.9 42.2 422.4 42.9 428.5
E6 0.8 7.5 0.8 7.8 0.8 8.0
E12 3.5 35.1 3.6 36.2 3.9 38.7
E13 1.6 16.2 1.7 16.7 1.7 17.2
E23 0.6 5.8 0.6 6.0 0.6 6.3
E24 0.4 4.0 0.4 4.2 0.4 4.4
Table 8-7: Air Quality Statistics Predicted for Road Derived Annual Mean Acid Deposition Concentration for 2018 Baseline, 2020 Future Baseline Traffic and 2020 Future Baseline with Traffic from Cumulative Developments Scenarios
Receptor ID 2018 Baseline 2020 Baseline 2020 Baseline with Cumulativ e Dev elopments
Acid % Lower Range Acid % Lower Range Acid Deposition % Lower Deposition CLMaxN Critical Deposition CLMaxN Critical (keq/ha/Yr) Range (keq/ha/Yr) Load Value (keq/ha/Yr) Load Value CLMaxN (1.536 keq/ha/Yr) (1.536 keq/ha/Yr) Critical Load Value (1.536 keq/ha/Yr)
E1 2.939 191.4 3.0 196.7 3.1 199.5
E2 2.939 191.4 3.0 196.7 3.1 199.5
E6 0.070 4.5 0.1 4.7 0.1 4.7
E12 0.320 20.8 0.3 21.3 0.3 22.5
E13 0.136 8.9 0.1 9.1 0.1 9.3
E23 0.071 4.6 0.1 4.7 0.1 4.9
E24 0.050 3.3 0.1 3.3 0.1 3.4
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8.6 Modelling Results for Operational NO2 with Cumulative Developments
Oxides of nitrogen have the greatest potential impact on local air quality. This section focuses on the change in local annual mean NO2 concentrations that w ould occur as a result of the operation of the Facility and the associated road traffic emissions are presented in and Table 8-8 and Table 8-9.
In both operational scenarios, the operation of the development and associated road traffic, w hich includes cumulative developments, results in an increase in the annual mean NO2 concentration for the majority of receptor locations compared to the 2020 baseline scenario. The increase is small for all receptors and in 3 3 the range of <0.1 to 0.6 µg/m . The annual mean NO2 limit value of 40 µg/m is not predicted to be exceeded in either operational scenario. Only annual mean NO2 concentrations are presented here, w here the emphasis is on the effect of the road traffic from cumulative developments. Total annual mean 3 NO2 concentrations w hich include stack and roads emissions are substantially below 60 µg/m it is highly unlikely that 1-hour NO2 emissions w ould be greater than the limit value, as reasoned in 5.2.4.
Table 8-8: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario w ith cumulative developments and Point Source Emissions – LPG Heating Plant and Thermal Oxidiser Scenario
3 Receptor Annual Mean NO2 Concentration (µg/m )
Background Road Traffic Process Total NO2 Change from Concentration Contribution Contribution Concentration 2020 Baseline with Cumulative from Point Scenario with Dev elopments Sources Cumulativ e Dev elopments R1 12.4 4.1 0.6 17.1 0.6 R2 12.4 4.2 0.3 16.9 0.3 R3 12.4 2.7 0.2 15.3 0.2 R4 12.4 2.7 0.2 15.3 0.2 R5 12.4 4.0 0.1 16.5 0.1
R6 12.3 16.6 <0.1 28.9 <0.1 R7 10.2 0.4 0.1 10.7 0.1 R8 10.2 0.3 0.1 10.6 0.1
R9 9.9 0.3 0.1 10.3 0.1 R10 9.9 0.3 0.1 10.3 0.1 R11 9.9 0.3 0.1 10.3 0.1 R12 12 0.7 0.2 12.9 0.2 R13 12 2.0 0.2 14.2 0.2 R14_1 12.3 7.3 <0.1 19.6 <0.1 R14_2 12.3 8.9 <0.1 21.2 <0.1 R14_3 12.6 9.2 <0.1 21.8 <0.1 R14_4 12.6 8.5 <0.1 21.1 <0.1 R14_5 12.6 8.2 <0.1 20.8 <0.1 R15 12.6 11.2 <0.1 23.8 <0.1 R16 12.3 1.2 0.1 13.6 0.1
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Table 8-9: Air Quality Statistics Predicted for Annual Mean NO2 Concentration for 2020 Operational Scenario w ith Cumulative Developments and Point Source Emissions – LPG Heating Plant and GAC Scenario
3 Receptor Annual Mean NO2 Concentration (µg/m )
Background Road Traffic Process Total NO2 Change from Concentration Contribution Contribution Concentration 2020 Baseline with Cumulative from Point Scenario with Dev elopments Sources Cumulativ e Dev elopments R1 12.4 4.1 0.6 17.1 0.6 R2 12.4 4.2 0.4 17.0 0.4 R3 12.4 2.7 0.3 15.4 0.3
R4 12.4 2.7 0.2 15.3 0.2 R5 12.4 4.0 0.2 16.6 0.2 R6 12.3 16.6 0.1 29.0 0.1
R7 10.2 0.4 0.2 10.8 0.2 R8 10.2 0.3 0.2 10.7 0.2
R9 9.9 0.3 0.1 10.3 0.1 R10 9.9 0.3 0.1 10.3 0.1 R11 9.9 0.3 0.1 10.3 0.1 R12 12 0.7 0.2 12.9 0.2 R13 12 2.0 0.2 14.2 0.2 R14_1 12.3 7.3 <0.1 19.6 <0.1 R14_2 12.3 8.9 0.1 21.3 0.1 R14_3 12.6 9.2 0.1 21.9 0.1 R14_4 12.6 8.5 0.1 21.2 0.1 R14_5 12.6 8.2 <0.1 20.8 <0.1
R15 12.6 11.2 0.1 23.9 0.1 R16 12.3 1.2 0.1 13.6 0.1
The maximum Process Contribution (PC) and Predicted Environmental Concentration (PEC) w ithin the modelled domain, for each pollutant and operational scenario, are summarised in Table 8-10 and Table 8-11. The PC listed, in respect of each pollutant and averaging period assessed, is the maximum impac t reported from the modelling of five years of meteorological data.
The results show that the maximum PC values for all the pollutants is less than the relevant Environmental Assessment Levels (EAL). How ever, combined road and process annual averaged NO2 values for some receptors, including R1 and R2, are predicted to be greater than 1% of the annual mean environmental standard. Therefore, the PEC value for annual mean NO2 is compared against the long-term environmental standard. It is show n that these values, 17.1 for R1 and R2, are less than 70% of the long- term limit of 40 µg m3.
It is show n than the combined maximum process contributions and, if relevant, road emissions for particulate matter, SO2 and CO are low er than the relevant EALs.
It should be noted that the assessment is made against some w orst-case assumptions, such as a NOx to NO2 conversion rate of 70%, continuous operation of the plant throughout the year and a conservative estimation of background concentration levels.
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Table 8-10: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Modelled Pollutants for the Worst -Case Meteorological Year - LPG Heating Plant and Thermal Oxidiser Scenario, with Cumulative Developments
Receptor Road Traffic PEC (including PEC (including where Env ironmental Point Source Pollutant Av eraging Period Contribution background) background, % Env maximum PC Standard (µg/m3) PC (µg/m3) (µg/m3) (µg/m3) Std) is located R1 Annual Mean 40 0.6 4.1 17.1 43.3 NO2 R2 99.79th percentile of 1-hour means 200 4.1 - 28.9 14.0
R6 PM10 Annual Mean 40 - 1.9 18.3 45.8
R6 PM2.5 Annual Mean 25 - 1.2 12.1 48.4 R8 99.9th percentile of 15-minute means 266 4.8 - 10.1 3.8
rd R8 SO2 99.73 percentile of 1-hour means 350 2.8 - 8.1 2.3 R1 99.18th percentile of 24-hour means 125 0.8 - 6.0 4.8 R8 CO Maximum 8-hour running mean 10,000 8.3 - 508.3 5.1
Table 8-11: Maximum Process Contribution at Sensitive Receptor and Total Contribution, all Mode lled Pollutants for the Worst-Case Meteorological Year - LPG Heating Plant and GAC Scenario w ith Cumulative Developments
Receptor Road Traffic PEC (including PEC (including where Env ironmental Point Source Pollutant Av eraging Period Contribution background) background, % Env maximum PC Standard (µg/m3) PC (µg/m3) (µg/m3) (µg/m3) Std) is located R1 Annual Mean 40 0.6 4.1 17.1 43. NO2 R2 99.79th percentile of 1-hour means 200 5.0 - 29.8 14.9
R6 PM10 Annual Mean 40 - 1.9 18.3 45.8
R6 PM2.5 Annual Mean 25 - 1.2 12.1 48.4 R2 99.9th percentile of 15-minute means 266 12.0 - 17.1 6.4
rd R2 SO2 99.73 percentile of 1-hour means 350 7.0 - 12.1 3.5 R1 99.18th percentile of 24-hour means 125 1.3 - 6.8 5.4 R8 CO Maximum 8-hour running mean 10,000 10.1 - 510.1 5.1
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8.7 Modelling Results – Impacts on Sites of Ecological Importance The results of the dispersion modelling of predicted impacts on sensitive ecological receptors are presented in this section. The tables set out the predicted PC to atmospheric concentrations of NOX and SO2, and also acid deposition and nutrient nitrogen deposition from stack and road emissions.
The impact of emissions can be regarded as insignificant at sites of local importance if the long-term or short-term PC is less than 100% of the critical load or critical level, regardless of baseline conditions. As there are no sensitive ecological receptors designated as being of National or European importance w ithin the study area, the assessment has not considered the baseline if the PC is less than 100% of the critical load or critical level.
Nutrient nitrogen and acidity targets vary depending on location, how ever defined critical loads for nitrogen and acid deposition are not available for sites of local importance. In the absence of bespoke values, representative critical loads for the types of habitat considered have been selected from the APIS w ebsite. In this assessment, all receptors w ere assumed to be composed of unmanaged broadleaved and deciduous w oodland habitat.
The critical load range for unmanaged broadleaved and deciduous w oodland is 10 – 20 kgN/ha/year. The low er range acidity critical load is:
• CLMinN – 0.142 keq/ha/year.
• CLMaxS – 1.251 keq/ha/year.
• CLMaxN – 1.536 keq/ha/year.
The assessment results show that the predicted impacts are w ithin the criteria for insignificance at all of the selected receptors for both the thermal oxidiser and GAC filter scenarios w here receptor locations are not immediately adjacent to the A464
Table 8-12: Dispersion Modelling Results with Cumulative Development traffic for Sensitive Ecological Receptors – Annual Mean NOX
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
3 3 NOX PC (µg/m ) % Critical Level NOX PC (µg/m ) % Critical Level (30 µg/m3) (30 µg/m3)
E1 148.8 496.1 148.8 496.1
E2 148.8 496.1 148.8 496.1
E6 2.9 9.7 2.9 9.7
E12 14.0 46.7 14.1 47.1
E13 6.1 20.5 6.2 20.6
E23 2.5 8.2 2.5 8.3
E24 1.7 5.8 1.8 5.9
Table 8-13: Dispersion Modelling Results, with Cumulative Developments traffic for Sensitive Ecological Receptors – Nutrient Nitrogen
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
N Deposition % Lower Range N Deposition % Lower Range (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Critical Load (10 kgN/ha/Yr) (10 kgN/ha/Yr)
E1 42.9 428.6 42.9 428.7
E2 42.9 428.6 42.9 428.7 E6 0.8 8.3 0.8 8.4
E12 4.0 40.3 4.1 40.7
E13 1.8 17.7 1.8 17.8
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Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
N Deposition % Lower Range N Deposition % Lower Range (kgN/ha/Yr) Critical Load (kgN/ha/Yr) Critical Load (10 kgN/ha/Yr) (10 kgN/ha/Yr)
E23 0.7 7.1 0.7 7.2
E24 0.5 5.0 0.5 5.1
Table 8-14: Dispersion Modelling Results, with Cumulative Developments traffic for Sensitive Ecological Receptors – Acid Deposition
Receptor ID LPG Heating Plant and TO Scenario LPG Heating Plant and GAC Scenario
Acid Deposition % Lower Range Acid Deposition % Lower Range (keq/ha/Yr) CLMaxN Critical Load (keq/ha/Yr) CLMaxN Critical Load Value Value (1.536 keq/ha/Yr) (1.536 keq/ha/Yr)
E1 3.1 199.5 3.1 199.6
E2 3.1 199.5 3.1 199.6
E6 0.1 4.4 0.1 5.0
E12 0.3 21.0 0.4 23.4
E13 0.1 9.0 0.1 9.6
E23 0.1 4.3 0.1 5.3 E24 0.1 3.3 0.1 3.7
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9. Summary and Conclusions
AECOM has been instructed by Biffa Waste Services to prepare an assessment of the impact of emissions to air from a new Soil Washing Facility and Soil Heat Treatment Facility located at Brookhurst Wood, Horsham, West Sussex. Two planning applications are being submitted, one for the Soil Washing Facility and one for the Soil Heat Treatment Facility, how ever this assessment has been prepared to consider the effect of both facilities operating simultaneously.
A detailed dispersion modelling investigation has considered emissions from road traffic, combined w ith emissions from the LPG Heating Plant and either a Thermal Oxidiser or Granulated Activated Carbon Filter during the operation of the Soil Heat Treatment facility. The modelling has been carried out using the ADMS Roads and ADMS 5 packages, w ith meteorological data covering a five-year period.
The assessment studies the impact of NO2 and particulate matter (PM10 and PM2.5) from the road emissions, and NO2, SO2 and CO from the plant stacks. The results obtained from the road emissions modelling are calibrated against a NO2 survey carried out by AECOM.
The results of the modelling show a negligible change in the annual mean concentrations of NO2 and particulate matter for the investigated receptors against the relevant baseline scenarios. It should be noted that such assessments have been based on some w orst-case assumptions discussed in Section 0.
The overall effect of the scheme on local air quality is considered not to be significant and is consistent w ith both national and local planning policies that relate to the protection of local air quality and public amenity.
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10. References
AEAT (2008), Analysis of the relationship betw een annual mean nitrogen dioxide concentration and exceedances of the 1-hour mean AQS Objective. AEA Technology plc.
APIS (2019), Centre for Ecology and Hydrology (CEH), Air Pollution Information System (APIS), w ww.apis.ac.uk
Carslaw et al (2011) Trends in NOX and NO2 emissions and ambient measurements in the UK. Version: 3rd March 2011. Draft for Comment. Available from: http://uk- air.defra.gov.uk/reports/cat05/1103041401_110303_Draft_NOX_NO2_trends_report.pdf , accessed: 14/01/2012.
CERC (2019), Model validation, Available from: https://w w w.cerc.co.uk/environmental-softw are/model- validation.html, Accessed on 25th January 2019
Council of European Communities (2008) Directive 2008/50/EC on Ambient Air Quality and Cleaner Air for Europe.
Council of European Communities (2002) Third Daughter Directive on ozone in ambient air, 2002/3/EC.
Council of European Communities (2000) Second Daughter Directive on limit values for benzene and carbon monoxide in ambient air, 2000/69/EC.
Council of European Communities (1999) First Daughter Directive on limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air, 1999/30/EC.
Council of European Communities (1996) Framew ork Directive on ambient air quality assessment and management, European Council, 96/62/EC.
Council of European Communities (1997) Council Decision 97/1010/EC on exchange of information and data from as amended by Commission Decision 2001/752/EC.
Defra (2003), Air Quality Management Technical Guidance 2003 LAQM, TG (03)
Defra (2016), Air Quality Management Technical Guidance 2009 LAQM, TG (16).
Defra (2019a), Local Air Quality Management Support Pages, Available from http//laqm.defra.gov.uk/, accessed on 19th June 2019
th Defra (2019b), NOX to NO2 calculator Version 7.1, dow nloaded on the 19 June 2019
Defra (2019c), Emission Factor Toolkit Version 9.0.1, dow nloaded on the 19th June 2019
Defra (2019d), Data Selector, available from: https://uk-air.defra.gov.uk/data/data_selector, accessed on 19th June 2019
Environment Agency (2011), AQTA AG06 Technical Guidance on detailed modelling approach for an appropriate assessment for emissions to air
Environment Agency (2019),Air emissions risk Assessments for your environmental permit, Published 1st February 2016, Last updated 2nd August 2016, available from https://w w w.gov.uk/guidance/air- emissions-risk-assessment-for-your-environmental-permit, accessed on 25th January 2019
Environment Agency (2011), H4 Odour Management, How to comply w ith your environmental permit, March 2011
Horsham District Council (2017), 2017 Annual Status Report (ASR) for Horsham District Council, July 2017
Horsham District Council (2015), Horsham District Planning Framew ork (excluding South Dow ns National Park), November 2015
H.M. Government (1981), Wildlife and Countryside Act 1981 (as amended)
H.M. Government (2000), Countryside and Rights of Way Act 2000 (as amended)
H.M. Government (2010) The Air Quality Standards Regulations. SI 1001, the Stationary Office.
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H.M. Government (2010), The Conservation of Habitats and Species Regulations 2010. SI490, the Stationary Office
Institute of Air Quality and Management (2017), Land-use Planning and Development Control: Planning for Air Quality, January 2017
Laxen and Marner (2003), Analysis of the Relationship Betw een 1-Hour and Annual Mean Nitrogen Dioxide at UK Roadside and Kerbside Monitoring Sites.
Ministry of Housing, Communities and Local Government (2018a), National Planning Policy Framew ork, July 2018
Ministry of Housing, Communities and Local Government (amended) (2019); National Planning Policy Framew ork, February 2019
Ministry of Housing, Communities and Local Government (2018b), National Planning Practice Guidance, July 2018
West Sussex County Council and South Dow ns National Park Authority (2014), West Sussex Waste Local Plan, April 2014.
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Appendix A
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Appendix B
Table B- 1: Summary of Traffic Data Used
2020 With- 2018 Baseline 2020 Baseline Road Speed (kph) Dev elopment AADT %HDV AADT %HDV AADT %HDV Langhurst Wood Road 64.4 (and 42.8 at Queue) 2,603 18 2,681 18 2,756 20 A264 eastbound west of 112.7 (and 42.8 at 17,906 7 18,443 7 18,481 7 Langhurst Wood Road Queue) A264 westbound west of 112.7 (and 42.8 at 18,335 7 18,885 7 18,885 7 Langhurst Wood Road Queue)
A264 eastbound east of 112.7 (and 42.8 at 17,933 7 18,471 7 18,508 7 Langhurst Wood Road Queue) A264 westbound east of 112.7 (and 42.8 at 18,335 7 18,885 7 18,885 7 Langhurst Wood Road Queue)
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Prepared f or: Biffa Waste Services Ltd AECOM 2
THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT
LEGEND !( R13 Point Sources !( R12 !( Receptors !( !( Horsham District Council NO2 Diffusion Tubes R11 !( Modelled Domain !( AECOM NO2 Diffusion Tubes
R10 !(
R9 !( R1 !(
R8 !( !(!( R2 !(
Copyright Reproduced from Ordnance Survey digital map data © Crown copyright 2019. All rights reserved. Licence number 0100031673 d x m . d o m
- Purpose of Issue
1 R3 A e FINAL r !( u g i
F Client _ R4 W
H R7 !(
B !( BIFFA WASTE SERVICES LTD _ !(
a 4 f f i B
\ Project Title d e i
f !( i AIR QUALITY d o N. Horsham 2N M \ !( IMPACT ASSESSMENT g n i
p R16 p a !( 6 Drawing Title M \ y t !( i l a u Q _ r i A _
2 LOCATION OF SELECTED 3 4 \ l
a RECEPTORS, POINT SOURCES c i n h c AND THE MODELLING e T _
0 BOUNDARY. 0 4 \ e c e e M d n a R6
W !( N. Horsham 1N R15
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B !(
!( a f f i 2 7 B R14_2 1 R14_3 !( 4
5 !( !(
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8 !( R14_5 5 R14_1 3 !( Drawn Checked Approved Date 0 !( 6
\ !( s JM DD GG 12/03/2019 t !( c 1 e j AECOM Internal Project No. Scale @ A3 o r P \
a 60586541 1:10,055 t a d
\ THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE k
u TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY .
o FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR c . FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE n o PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED. s l i w t t AECOM o c 12 Regan Way, s .
1 Chetwynd Business Park, 0 Chilwell, Nottingham 0 -
n NG9 6RZ a Telephone (0115) 907 7000 m - www.aecom.com m n \ \ : Drawing Number Rev e
m 5 a
N !( e l FIGURE A.1 i 0 340 680 1,020 1,360 m ± F *# THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT
LEGEND Modelled Domain R1 1 !( *# Ecological receptors !( Point Sources E22 E4 *# *# 3 E21 E3 NOx (ug/m ) *# !( Human health receptors
E7 E9 3 Ancient Woodlands *#*# Local Nature Reserves R8 6 !( !( !( R2 9 !( E20 *#
E19 *# E23 *# R13 R12 !( E24 !( *# R11 !(
R10 !( E11 *# E12 *# E25 E10 *# E18 *# *# R9 Copyright !( Reproduced from Ordnance Survey digital map data E17 R1 © Crown copyright 2019. All rights reserved. *# 1 !( Licence number 0100031673 E4 *# E27 E7 E9 *# E5 *# 3 Purpose of Issue d *# x R8 *# FINAL m . !( 4 12 v
_ !( R2 Client 2 !(
A !( e r u 6 BIFFA WASTE SERVICES LTD g i F _
W Project Title H B
_ AIR QUALITY a
f E16 f i B \ *# IMPACT ASSESSMENT g n i p p a E8 R3 Drawing Title M \ y t # !( E26 i * l a R4 u *#
Q R7 !( _ r i !(
A E6 X
_ R5 ANNUAL NO PROCESS 2 *# 3 !( 4 \ l E13 CONTRIBUTION FOR THERMAL a c i R16 n *# h OXIDISER ON ECOLOGICAL
c !( e T
_ RECEPTORS, 2017 MET DATA 0 0 4 \ e c e e M d n a
W H B a f f i R6
B R15
1 !(
4 !( 5
6 R14_2 R14_3 8
5 !( !( R14_4 Drawn Checked Approved Date 0 R14_1 R14_5 6
\ !( s !( JM DD GG 29/07/2019 t E1 E2 !( c e j *# AECOM Internal Project No. Scale @ A3 o r P \
a 60586541 1:7,880 t a d
\ THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE k
u TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY . o FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR c . E15 FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE n o PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED. s *# l i E14 w t t AECOM o *# c 12 Regan Way, s .
1 Chetwynd Business Park, 0
0 Chilwell, Nottingham - n NG9 6RZ a Telephone (0115) 907 7000 m - www.aecom.com m n \ \ : Drawing Number Rev e m a N e l FIGURE A.2 i 0 520 1,040 1,560 2,080 m ± F THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT
R13 !( !( Point Sources R12 !( !( Receptors
!( Horsham District Council NO2 R11 Diffusion Tubes !( 3 NOx (ug/m ) Modelled Domain R10 !( !( AECOM NO2 Diffusion Tubes
R9 !( R1 1 !(
3 R8 !( 9 !(!( R2 !( 6 Copyright Reproduced from Ordnance Survey digital map data © Crown copyright 2019. All rights reserved. Licence number 0100031673
Purpose of Issue FINAL
Client R3 BIFFA WASTE SERVICES LTD !( Project Title R4 AIR QUALITY R7 !( !( !( 4 IMPACT ASSESSMENT R5 !( Drawing Title N. Horsham 2N !( R16 !( 6 !( ANNUAL NOX PROCESS CONTRIBUTION FOR THERMAL OXIDISER, 2017 MET DATA
R6 Drawn Checked Approved Date !( N. Horsham 1N R15 JM DD GG 12/03/2019 !( !( !( AECOM Internal Project No. Scale @ A3 2 7 R14_2 R14_3 !( 60586541 1:9,232 !( !( THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE !( R14_4 TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY R14_1 3 !( R14_5 FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR !( !( FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE !( 1 PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED. AECOM 12 Regan Way, Chetwynd Business Park, Chilwell, Nottingham NG9 6RZ Telephone (0115) 907 7000 www.aecom.com
Drawing Number Rev 0 310 620 930 1,240 m ± FIGURE A.3 File Name:\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 Biffa BHW Name:\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 and Meece\400_Technical\432_Air_Quality\Mapping\Modified\Biffa_BHW_FigureA2-mod.mxd Biffa File BHW THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT
LEGEND R13 !( !( Point Sources R12 !( !( Receptors
!( Horsham District Council NO2 Diffusion Tubes 5 R11 5 !( 3 5 NOx (ug/m ) Modelled Domain R10 !( !( AECOM NO2 Diffusion Tubes 5
10
R9 !( R1 !(
5
5
28 R8 !( 55 5 !(106!( R2 !( 80 Copyright Reproduced from Ordnance Survey digital map data © Crown copyright 2019. All rights reserved. Licence number 0100031673
Purpose of Issue FINAL
Client R3 BIFFA WASTE SERVICES LTD !( Project Title R4 AIR QUALITY R7 !( !( !( 4 IMPACT ASSESSMENT R5 !( Drawing Title N. Horsham 2N !( R16 !( 6 TH !( P99.79 NOX PROCESS 5 CONTRIBUTION FOR THERMAL OXIDISER, 2018 MET DATA
R6 Drawn Checked Approved Date !( N. Horsham 1N R15 JM DD GG 12/03/2019 !( !( !( AECOM Internal Project No. Scale @ A3 2 7 R14_2 R14_3 !( 60586541 1:9,228 !( !( THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE !( R14_4 TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY R14_1 3 !( R14_5 FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR !( !( FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE !( 1 PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED. AECOM 12 Regan Way, Chetwynd Business Park, Chilwell, Nottingham NG9 6RZ Telephone (0115) 907 7000 www.aecom.com
Drawing Number Rev 0 310 620 930 1,240 m ± FIGURE A.4 File Name:\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 Biffa BHW Name:\\nm-man-001.scottwilson.co.uk\data\Projects\60586541 and Meece\400_Technical\432_Air_Quality\Mapping\Modified\Biffa_BHW_FigureA3-mod.mxd Biffa File BHW !(
THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT R11 LEGEND !( !( PointSources !( Receptors HorshamDistrict Council R10 !( !( NO 2 DiffusionTubes 3 NO x(μg/m ) M odelled DomainModelled
!( AECOMNO 2 Diffusion Tubes
R9 !(
R1 !(
R8 12 16
!( 2
10 !(!(!( 14 4 6 R2 8 !(
Copyright Reproduced from Ordnance Survey digital map data © Crown copyright 2019. All rights reserved. Licence number 0100031673
Purpose of Issue FINAL
Client BIFFA WASTE SERVICES LTD R3 !( Project Title AIR QUALITY R4 IMPACT ASSESSMENT R7 !( !( !( 4 Drawing Title R5 !( N. Horsham 2N ANNUAL NOX PROCESS !( CONTRIBUTION FOR R16 ACTIVATED CARBON FILTER, !( 6 !( 2017 MET DATA
Drawn Checked Approved Date JM DD GG 12/04/2019 AECOM Internal Project No. Scale @ A3 60586541 1:7,636
THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE R6 PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED. !( !( N. Horsham 1N R15 !( !( AECOM 2 12 Regan Way, Chetwynd Business Park, 7 Chilwell, Nottingham R14_2 R14_3 !( NG9 6RZ !( !( Telephone (0115) 907 7000 !( R14_4 www.aecom.com R14_1 3 !( R14_5 !( !( Drawing Number Rev !( 0 250 500 750 1,000 m 1 ± FIGURE A.5 File Name:B:\Projects\60586541 Biffa BHW andMeece\400_Technical\432_Air_Quality\Mapping\Modified\Biffa_BHW_FigureA2-modv2.mxd Biffa Name:B:\Projects\60586541BHW File !(
THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT R11 LEGEND !( 5 !( SourcesPoint !( Receptors !( Horsh amCouncilDistrict R10 NOTubes 2 Diffusion !( 3 NO x(μg/m ) M odelled DomainModelled !( AECOMNO 2 Diffusion Tubes
R9 !(
R1 !(
45
R8 65 !( 145 85
!(!(!( 125 R2 105 !(
Copyright Reproduced from Ordnance Survey digital map data © Crown copyright 2019. All rights reserved. 25 Licence number 0100031673
Purpose of Issue FINAL
Client 5 BIFFA WASTE SERVICES LTD R3 !( Project Title AIR QUALITY R4 IMPACT ASSESSMENT R7 !( !( !( 4 Drawing Title R5 !( N. Horsham 2N P99.79TH NOX PROCESS !( CONTRIBUTION FOR R16 ACTIVATED CARBON FILTER, !( 6 !( 2017 MET DATA
Drawn Checked Approved Date JM DD GG 12/04/2019 AECOM Internal Project No. Scale @ A3 60586541 1:7,636
THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE R6 PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED. !( !( N. Horsham 1N R15 !( !( AECOM 2 12 Regan Way, Chetwynd Business Park, 7 Chilwell, Nottingham R14_2 R14_3 !( NG9 6RZ !( !( Telephone (0115) 907 7000 !( R14_4 www.aecom.com R14_1 3 !( R14_5 !( !( Drawing Number Rev !( 0 250 500 750 1,000 m 1 ± FIGURE A.6 File Name:B:\Projects\60586541 Biffa BHW andMeece\400_Technical\432_Air_Quality\Mapping\Modified\Biffa_BHW_FigureA3-modv2.mxd Biffa Name:B:\Projects\60586541BHW File #*
THIS DRAWING IS TO BE USED ONLY FOR THE PURPOSE OF R13 ISSUE THAT IT WAS ISSUED FOR AND IS SUBJECT TO AMENDMENT (! E24 R12 #* (! LEGEND (! Point Sources R11 #* (! Ecological Receptors (! Human Health Receptors Land North of Horsham R10 (! Planning Boundary E11 #* E12 #* E25 #* E10 #* E18 #* R9 (! E17 R1 #* (!
E4 #*
E27 #* E7E9 #*#* R8 (! (!(! R2 (!
E16 #* Copyright Reproduced from Ordnance Survey digital map data © Crown copyright 2019. All rights reserved. E8 R3 Licence number 0100031673 #* ! ( E26 R4 #* R7 (! (! Purpose of Issue E6 R5 FINAL #* (! Client E13 R16 #* BIFFA WASTE SERVICES LTD (! Project Title AIR QUALITY IMPACT ASSESSMENT
Drawing Title
LAND NORTH OF HORSHAM PLANNING BOUNDARY EXTENT R6 WITHIN THE MODELLED AREA ! R15 ( (! R14_2 R14_3 (! (! R14_4 R14_1 (! R14_5 (! (! E1E2 #* d x m . W H
B Drawn Checked Approved Date \
W AB DD GG 29/07/2019 H B \ s AECOM Internal Project No. Scale @ A3 t c e j
o 60586541 1:10,000 r E15 P \
s THIS DOCUMENT HAS BEEN PREPARED PURSUANT TO AND SUBJECT TO THE t #* n TERMS OF AECOM'S APPOINTMENT BY ITS CLIENT. AECOM ACCEPTS NO LIABILITY e FOR ANY USE OF THIS DOCUMENT OTHER THAN BY ITS ORIGINAL CLIENT OR m u FOLLOWING AECOM'S EXPRESS AGREEMENT TO SUCH USE, AND ONLY FOR THE
c E14 o PURPOSES FOR WHICH IT WAS PREPARED AND PROVIDED.
D #* \ n
w AECOM o r 12 Regan Way, b . y Chetwynd Business Park, d
n Chilwell, Nottingham a \ NG9 6RZ s r
e Telephone (0115) 907 7000 s www.aecom.com U \ : C : Drawing Number Rev e m a N e l FIGURE A.7 i 0 330 660 990 1,320 m ± F