European Commission Industrial Emissions of Nanomaterials and Ultrafine Particles

European Commission Industrial emissions of nanomaterials and ultrafine particles

Final Report (Main)

AMEC Environment & Infrastructure UK Limited in partnership with the Institute for Occupational Medicine (IOM) and Aether

October 2011

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Third-Party Disclaimer Any disclosure of this report to a third party is subject to this disclaimer. The report was prepared by AMEC at the instruction of, and for use by, our client named on the front of the report. It does not in any way constitute advice to any third party who is able to access it by any means. AMEC excludes to the fullest extent lawfully permitted all liability whatsoever for any loss or damage howsoever arising from reliance on the contents of this report. We do not however exclude our liability (if any) for personal injury or death resulting from our negligence, for fraud or any other matter in relation to which we cannot legally exclude liability.

Document Revisions

No. Details Date

1 Draft final report outline for client 30th September 2010 comment

2 Draft final report outline with 18th October 2010 client comments

3 Progress Report 1st February 2011

4 Interim Report 6th May 2011

5 Revised interim report taking 31st May 2011 into account client comments

6 Draft Final Report 1st September 2011

7 Final Report 20th October 2011

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Executive Summary

The European Commission contracted AMEC – supported by Aether, the Institute for Occupational Medicine (IOM) and Professor Roy Harrison – to study industrial emissions of nanomaterials (NMs) and ultrafine particles (UFPs). The objective of the study was to improve the understanding of their emissions in order to contribute to setting priorities for future policy.

The following definitions were assumed for this study:

Nanomaterial means a material in which one or more properties are determined to a significant degree by the presence of nanoscale1 structural features.

Ultrafine particles are defined as particles that have at least one dimension between 1 and 100 nm or have an aerodynamic diameter between 1 and 100 nm. Structures of larger dimensions such as aggregated NMs2 are included provided that they have retained properties and/or functionalities. NMs of biological origin and capable of replication such as viruses are outside the scope of this study.

The findings in this report are based on a detailed review of the available literature, feedback from consultation with a wide range of stakeholders during the study as well as discussions with stakeholders at a workshop held on 6 June 2011 and subsequent feedback.

Policy context

Exposure to particulate matter (PM) is one of the major causes of air pollution health damage in the European Union, but source-oriented legislation has significantly reduced PM atmospheric emissions from industrial and vehicular sources. The legislation has addressed total PM emissions (defined as dust emissions from industrial sources or primary PM emissions from vehicles) and has set air quality standards for various size fractions, such as

1 Nanoscale means a scale at which the surface or interfacial properties of a material become significant compared with those of the bulk material. The term nanoscale is generally used to refer to the dimensions of the order of 1 nm to 100 nm.

2 NMs have specific properties and/or functionalities and can be nano-objects (sheets, tubes or particles) that may have respective one, two or three dimensions at the nanoscale, or nano-structured materials which have an internal or a surface structure at the nanoscale both of which lead to these specific functionalities. The definition of NMs therefore explicitly also covers in nanostructured materials, agglomerates or aggregates of parts which have internal or surface structures at the nanoscale, but which are larger than nanoscale and retain properties and/or functionalities that lead to specific properties that are characteristic to the nanoscale.

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the total mass of PM10 and PM2.5. There is, however, information on smaller-sized particles that needs to be analysed and reviewed in order to understand if existing legislative controls are sufficient.

The Commission’s review of EU legislation in relevant sectors in its 2005-2009 action plan concluded that current legislation covers, in principle, the potential health, safety and environmental risks of NMs and that protection from these risks could be most efficiently enhanced by improvement of the implementation of existing legislation. The review also indicated a need to improve the knowledge-base with regard to the characterisation of NMs, their hazards, exposure, risk assessment and risk management.

In response to the Commission’s regulatory review, the European Parliament adopted a resolution asserting that current EU legislation is devoid of any nano-specific provisions and expressing reservations about the conclusions of the Commission with regard to the regulatory aspects. The resolution identifies EU legislation with relevance for NMs and lists specific concerns to be addressed by the Commission within a time frame of two years. In addition, the Parliament called for an evaluation of the mass-based metrics currently used for setting emission limit values and defining air quality standards and for an assessment of the extent to which metrics based on particle number and/or particle surface are more appropriate with regard to releases of NMs.

In response to the Parliament’s resolution, the Commission announced that it would report on the Parliament’s requests in 2011. One of the requests is to evaluate the need to review legislation to address, in a cost-effective manner, NMs that are created as unintended by-products of combustion processes. The aim of this study is to support the Commission in the assessments requested by the European Parliament on this aspect.

Review of the current understanding of the emissions and sources of NM/UFP and evaluation of the control measures and risks should allow progress to be made towards supporting a decision on whether the current legalisation is adequate to cover NM and UFP. Of specific interest is whether this legislation can help to achieve the aims of ensuring a high level of protection for human health and the environment, or whether further policy measures are required to achieve those aims.

Objectives of the study

The specific objectives of this project were:

• To summarise current knowledge on atmospheric releases of NMs and UFPs in the EU27.

• To provide an in-depth analysis of the characteristics, dynamics, and impact on human health and the environment of NMs and UFPs released from industrial processes.

• To provide recommendations on how to address identified knowledge gaps.

• To review EU legislation on industrial emissions to determine whether it addresses releases of NMs and UFPs appropriately.

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• If necessary, to develop policy options for the regulation of NMs and UFPs in EU legislation related to industrial emissions.

Summary of evidence available

Overview of report Section 2 of this report provides a summary of the information gathered for each of the topics that formed the scope of this project. The information presented in the report is primarily based on published literature sources supplemented with inputs gathered directly from a wide range of stakeholders. This is further supplemented with information gathered from stakeholders during and after the stakeholder workshop.

The table below summarises the topics covered and corresponding section numbers for reference.

Table 1 Topics addressed in the report and signposting to relevant sections

Section reference Topic

Section 2.2 Topic 1: Composition, size distribution and, where appropriate, shape of atmospheric releases of NMs and UFPs from industrial sources

Sections 2.3 and 2.4 Topic 2: Relative contribution of NMs and UFPs to overall PM releases

Section 2.5 Topic 3: Analytical tools for monitoring of NMs and UFPs releases

Section 2.6 Topic 4: Analytical tools to trace NMs and UFPs to their source (fingerprinting)

Section 2.7 Topic 5: Overview of abatement techniques for NMs and UFPs

Topic 6: Maturation (aggregation, changes of surface properties, chemical reactivity) of newly formed NMs and UFPs Section 2.8 Topic 7: Summary of knowledge on the regional and potentially hemispheric transport of NMs and UFPs Topic 9: Persistence of NMs and UFPs

Section 2.9 Topic 8: Estimation of human exposure to NMs and UFPs from the all sources identified in task 1

Section 2.10 Topic 10: Risk assessments of NMs and UFPs

Section 2.11 Topic 11: Impact of NMs and UFPs on human health, the environment (ecotoxicity) and relevance to climate forcing (cloud formation and persistence); comparison to the impact of PM2.5 and PM10 (a brief summary)

Section 2.12 Topic 12: Discuss the NMs and UFPs metric(s) (particle mass, surface, number) that are most appropriate to describe dose-effect relationships

Emissions Most published work on emissions of UFPs relates to road transport activities. There is limited information on emissions from specific industrial sources and thus considerable uncertainties with regard to factors such as emitted quantities, fractionation profiles and variations in particle size distribution between industrial sectors and activities.

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Data on emissions from different sources for PM10 and PM2.5 have been used to calculate emissions of PM0.1. PM10 emissions data for the EU27 submitted under the Convention on Long-range Transboundary Air Pollution (LRTAP) was used, supplemented by point source emissions data from the European Pollutant Release and Transfer Register (E-PRTR) and fractionation data from a range of sources. It should be appreciated that these estimates are subject to considerable uncertainty.

The PM0.1 emission estimates calculated by source are shown in the figure below, with PM10 emissions included alongside for context. Overall, total EU27 PM0.1 emissions are estimated to be approximately 13% of equivalent

PM10 emissions although there is considerable variation between different sources.

Figure 1 Percentage Contributions to EU-27 (a) PM10 and (b) PM0.1 Emissions Totals (2008)

(a) PM10 (b) PM0.1

From the above, it can be seen that – as compared to PM10 – industrial emissions of UFPs from combustion

(expressed as PM0.1) are estimated to constitute a larger share of the total emissions, whereas industrial process emissions of UFPs represent a lower proportion of the total. Combined, industrial emissions of UFP represent a smaller share of the total than is the case for PM10. The share of UFP emissions arising from transport sources is striking, with over half of total emissions arising from road transport, other transport and machinery (compared to only a quarter of PM10 emissions).

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The figure below shows a breakdown of the industrial component of UFP emissions according to the source types involved. This highlights minerals; iron and steel; heat and electricity production; and pulp and paper as the most significant industrial sources. (These are all covered, to an extent at least, by EU industrial emissions legislation.)

Figure 2 PM0.1 Emissions from Industrial Sources by NFR Sector (2008)

It has not been possible to make quantitative estimates of atmospheric releases of NMs, as insufficient data has been found from the literature. However, it has been possible to provide an overview of the industrial sources that are considered likely to be the largest users of NMs. Information on the potential for emission from the different uses of NMs is very limited. Therefore it has been necessary to consider the use of NMs in different industrial sectors as an indicator of likely emissions to atmosphere.

Monitoring and detection A number of monitoring techniques have been identified that can monitor releases of NMs and UFPs. It is often necessary to apply two or more techniques in combination.

Conditions at industrial installations such as high temperatures, semi volatile flue gas components and dynamic physicochemical processes present limitations for monitoring NMs and UFPs from these sources. There are limited instances of monitoring of NM and UFP emissions from industrial sources and seemingly no examples of its use in a regulatory context. Techniques applicable for monitoring NMs and UFPs releases have only been applied in a limited number of industrial settings and the majority of investigations seem to have been dedicated to traffic sources. This is not surprising given that no regulation is currently in place that makes it mandatory for industrial

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installations to routinely monitor NMs and UFPs (or even PM2.5). In addition, there are currently no standards or guidelines for their measurement from industrial installations.

There are further limitations in the approaches commonly adopted for measurements. These are generally conducted with conventional hot stack gas sampling, with no information available on the potential effects on particle number concentrations of particle nucleation and/or condensation phenomena, arising from semi-volatile flue gas components and driven by atmospheric dilution.

Additional limitations include:

• Little information is available on the costs of monitoring equipment.

• Information presented in this report comes largely from experimental laboratory work.

• There is little information on the reliability and repeatability of testing, as well as complications associated with monitoring where certain abatement techniques are applied, such as wet scrubbers.

Consideration has also been given in this study to the use of analytical tools to trace NMs and UFPs to their source (fingerprinting). Whilst there are a number of different characteristics of NM/UFP that could, in principle, be used to trace them to their (industrial) sources, there are limited instances of fingerprinting for NM/UFP having been applied in practice for industrial sources and little or no examples of its use in a regulatory context. Furthermore, it does not currently seem to be clear which properties of NM/UFP are likely to be of most use in fingerprinting.

Metrics A key issue in the measurement of NMs/UFPs in terms of emissions as well as levels in the environment is the metrics used for characterisation of those levels. Various metrics may be used such as particle mass, surface or number.

There is some data from epidemiological studies which indicates that mass concentration is a suitable dose metric for airborne PM, but not specifically NMs/UFPs. There is limited evidence from epidemiological studies that particle number concentration may be a suitable, possibly better, dose metric for these species. Data from toxicological studies largely suggests particle surface area is an appropriate dose metric but with marked exceptions. However, there is a paucity of relevant human data in this area.

On the basis of current knowledge, there are difficulties in separating the relative importance of different factors that give rise to toxicity, including particle size, surface area, surface properties, shape, leachable metals content and others. Factors governing toxicity depend on the dose metric employed.

Health and environmental fate, exposure and risks A number of fate and transport processes affect UFPs emitted to the atmosphere, including evaporation, condensation, coagulation, chemical reactions and deposition. All of these will affect their fate. There are very

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few direct measurements available relating to manufactured NMs and the majority of focus to date has been on road traffic emissions which will not be representative of most manufactured NMs nor necessarily of emissions from industrial sources.

In relation to human exposure to NMs and UFPs, there are few measurement data describing the exposure of the EU population to UFPs in ambient air and no identified information about potential exposure to engineered NMs. Projects undertaken within the EU Framework Programmes 6 and 7 and to support the development of air quality policy in the EU have played an important role in developing understanding between emissions sources and population exposure to PM10 and PM2.5 in Europe, but these initiatives have not specifically considered population exposure to UFPs/NMs to date.

Based on existing atmospheric modelling and monitoring it is clear that emissions from elevated stacks from industrial sources affect ground level concentrations over a wide area but are a relatively small influence on ground level concentrations at any location. On the other hand, vehicle emissions have a disproportionately greater impact on ground level concentrations in urban areas in relation to the total particle masses emitted. In addition, based on the emission estimates produced as part of this study, PM0.1 emissions from road transport and other mobile machinery appear to contribute significantly more to total PM0.1 emissions than PM10 emissions. It therefore seems likely that population exposure to UFPs in ambient air is dominated by primary and secondary particles originating from traffic emissions.

Oversimplification of the approach to estimation of NP/UFP exposure is likely to significantly misrepresent the relative importance of different NP sources. Understanding relative contribution of different NP sources to human exposure would require a major modelling exercise including a more robust underlying emissions inventory.

In relation to the risks and impacts of NMs and UFPs, the harmfulness of ambient PM is well established. The review undertaken for this study has identified the following main points:

• Toxicity generally increases with decreasing particle size when dose is expressed in mass terms. Surface properties have an important influence on toxicity. However, the relationship between particle size and toxicity is not consistent and it is difficult to compare across studies. There is also uncertainty about the relevance of experimental test systems to prediction of human health effects and uncertainty about particle properties in ambient air compared with those of particles employed in experimental systems.

• There are few experimental comparisons of engineered NMs and ambient PM and almost no epidemiological information describing effects of engineered NMs in humans.

• UFPs are generally more harmful to health than larger particles, based on equivalent mass doses, with combustion-generated NMs/UFPs being particularly damaging to health.

• NM/UFP composition is an important influence on toxicity with leachable metals appearing to be of particular importance in giving rise to adverse effects.

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• There is a paucity of information about the environmental fate of NMs, their actual impacts on environmental quality and the likely levels of exposure of organisms in natural ecosystems.

• UFPs have been shown to be damaging to a range of organisms in experimental systems and it is possible – although not yet shown – that they could have adverse effects on biodiversity with consequences for water and soil quality.

• A wide range of ecotoxicity assays have been undertaken with NMs/UFPs but these employ simplified test systems that are substantially different from natural waters or soils. It is likely that the degree of particle aggregation and particle surface properties differ substantially between the idealised conditions of test systems and the natural environment. This substantially limits the predictive power of laboratory assays for understanding toxic effects in the wider environment.

There are also potential implications in relation to climatic effects. Atmospheric UFPs may directly affect atmospheric absorbance or reflection of heat, depending on the type. They can have indirect temperature effects through promoting cloud formation and affecting cloud persistence. There is, however, no consensus as to the likely net effect of atmospheric NMs/UFPs on climate. Models of weather and climate are extremely complex. It is not possible to include all possible variables that may influence weather and climate and small variations in input variables may lead to substantially different predictions of the nature, rate and size of potential climate change.

Key data gaps / inconsistencies

There are currently a significant number of data gaps preventing the development of a comprehensive description of releases of NMs and UFPs, their control through industrial emissions legislation and their impacts on health and the environment. The key gaps identified during this study include:

• There are little or no data available on emissions of NMs from industrial sources.

• There are limited data on emissions of UFPs from industrial sources. The fractionation data used in this study is based on a very small number of sources and there are uncertainties associated with the impacts of factors such as different abatement techniques, fuels used and process types.

• There remain considerable uncertainties on the behaviour and ultimate fate of these particles in the environment.

• There are limited data available on the exposure of the population to NMs/UFPs (NMs in particular) and associated impacts on health and the environment.

A number of possible options to address these gaps have been identified and categorised according to the significance of the issue (in terms of understanding the impacts of NMs and UFPs) as well as the potential for achieving improved control of risks, possible timescales for implementation, feasibility, possible cost implications of resolving the issue (for example, through further research), as well as who would be most appropriate to take ownership. These are described in Section 5.2.

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Review of the Industrial Emissions Directive (IED, 2010/75/EU) and supporting BREF documents

Overview The aim of this review was to assess whether the current legislation related to industrial emissions appropriately addresses the prevention and control of NM and UFP emissions from industrial sources. Specific attention was given to the categories of installations covered, relevant emission limit values (ELVs) and emission levels associated with the use of best available techniques (BAT-AELs) from the BAT reference documents (BREFs) and associated metrics.

Coverage of relevant emission sources by the IED In general, based on the inventory of emissions produced for this study, there appears to be good coverage of the major industrial sources of NM/UFP emissions by the IED, at least in terms of whether or not sectors are covered at all by the IED.

Perhaps the most significant gap relates to industrial installations that fall below the capacity thresholds of the IED. There may be sectors emitting high levels of NMs/UFPs where the IED only covers installations above a certain threshold i.e. some of the emissions from the sector may be from installations below the IED thresholds and they are therefore not covered by the legislation. The information available on emissions, gathered as part of this study, is not sufficiently well developed to quantify this.

A specific gap could be for combustion installations where the directive only includes installations with a capacity greater than 50MW3. A study for the Commission developed to support the review of the IPPC Directive found that plants <50MW contributed 18% of total PM10 emissions from industrial combustion across Europe (EU25 at the time). Whilst the Commission’s original proposal for the IED included a change in the threshold from 50MW to 20MW, this was removed during the co-decision process. However, a clause was included under Article 73(2)(a) requesting the Commission to review the need to control emissions from these activities.

Furthermore, despite there being a good level of disaggregation of sectors within the inventory, there remains some uncertainty as to the proportions of emissions that occur from within specific sub-sets of the sources concerned. This is a limitation on identifying the degree of coverage of emissions by current industrial emissions legislation.

A more sophisticated inventory would perhaps help to identify specific gaps in coverage at a sector level, based on the sizes of the installations concerned and the IED thresholds. This could, for example, include further disaggregation within certain sectors into a greater number of sub-sectors (e.g. minerals) and/or emissions from installations above or below the relevant IED capacity thresholds (e.g. combustion). Obviously the resource

3 Although some of these installations (and units) may already be covered by the Directive where the aggregated capacity on site is more than 50 MW or if they are "directly associated activities with a technical connection" to other IPPC activities.

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requirements associated with the development of a more detailed inventory would need to be considered against the benefits.

Coverage of emissions by ELVs and BAT-AELs for sectors where the IED does apply This aspect relates to whether, for those sources of emissions where industrial emissions legislation does apply, the practical steps taken to reduce emissions will have an impact on reducing emissions of NM/UFP.

Based on the analysis undertaken, it appears that there are a wide range of techniques that are expected to be applied within the sectors concerned to prevent and reduce emissions of dust emissions in general. In many cases, these are also likely to have a significant effect in reducing emissions of NM/UFP as well as coarser fractions although there is some uncertainty. However, there are some instances where typical techniques for control of dust emissions are likely to have lower efficiency in abating emissions of NM/UFP. Nonetheless, there are a number of more recent abatement techniques – some of which are BAT according to the BREFs or which are reportedly already being applied in industrial installations – that can achieve more comparable levels of emission reduction.

Coverage within the BREFs Overall, the current level of coverage of NM and UFP within the BREFs is limited, although there is some mention of the effectiveness of techniques in reducing sub-micron size particles. However, this is perhaps not surprising given that there has been little regulatory focus in contrast to the broader size fractions (PM2.5, PM10) and given the level of available evidence on differences in health effects at lower size fractions compared to effects from broader size fractions.

Metrics The ELVs and BAT-AELs in the IED and BREFs are almost all based on units of mass concentration (mg/m3), with a small number based on mass emissions per unit of production. A metric based on mass concentration may not necessarily be the most appropriate for monitoring NM/UFP emissions, although the usefulness of other metrics such as particle number is primarily linked to the ability to consider population exposure and health impacts. Any attempt to set limits for releases of NMs/UFPs from industrial sources in the future would have to consider this further.

Initial policy options Within the scope of this project, a range of possible policy options were developed with the aim of addressing potential gaps in the coverage of industrial emissions legislation as concerns emissions of NM/UFP, specifically in relation to factors such as activities not covered and the metrics and levels at which ELVs/BAT-AELs are set. A shortlist of possible options was developed and presented at a stakeholder workshop for discussion. This included:

• Extending the coverage of the industrial emissions legislation to activities below the current thresholds so as to capture additional emissions of NM/UFP.

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• Ensuring specific consideration within the BREF review process of NM/UFP, including their emissions, what constitutes BAT in reducing such emissions and techniques to reduce those emissions.

Conclusions Stakeholders agreed at the workshop that the evidence gaps and uncertainties are currently too high to consider making any changes to the legislation in the short term. Key knowledge gaps and/or uncertainties relate to the level of emissions of UFPs from different sources including the impacts of abatement technology; the ability to accurately and consistently monitor these emissions in industrial sites; as well as the fate of these particles in the environment. These need to be understood much better before considering any legislative changes.

At this stage, it was agreed that an appropriate way forward could be for the BREF review process to consider the inclusion of information regarding impacts of techniques on PM10, PM2.5 and PM0.1 emissions, where available and appropriate. Whilst this has been reported in some instances, it has not been required as such and therefore has not been reported more widely. The workshop participants concluded that this should only apply where techniques to reduce dust emissions are already reported.

As the knowledge base improves there may be a need to revisit the current scope and effectiveness of the legislation with respect to NMs/UFPs.

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Contents

1. Introduction 1 1.1 This report 1 1.2 Definition of NMs and UFPs 1 1.3 Policy context 2 1.4 Aims and objectives 4 1.5 Report structure 5

2. Current knowledge of atmospheric sources of NMs and UFPs from industrial sources [Tasks 1-3] 6 2.1 Overview 6 2.2 Topic 1: Composition, size distribution and shape of atmospheric releases of NMs and UFPs from industrial sources 7 2.2.1 Introduction 7 2.2.2 Composition of UFPs 7 2.2.3 Size Distribution of UFPs 8 2.2.4 Shape of UFPs (and NMs) 11 2.2.5 Conclusions 12 2.3 Topic 2a: Relative contribution of UFPs to overall PM releases 13 2.3.1 Introduction 13

2.3.2 Non-Anthropogenic PM0.1 Emission Estimates 13

2.3.3 Anthropogenic PM0.1 Emission Estimates 15 2.3.4 QA/QC for Anthropogenic Emission Methodology 19

2.3.5 Results of Anthropogenic PM0.1 Emission Estimates 22 2.3.6 Conclusions and recommendations 32 2.4 Topic 2b: Relative contribution of NMs to overall PM releases 34 2.4.1 Introduction 34 2.4.2 Products using NMs 34 2.4.3 Use of NMs by Type 35 2.4.4 Quantitative estimates of NM usage 36 2.4.5 Conclusions 37 2.5 Topic 3: Analytical tools for monitoring of NMs and UFPs releases 37 2.5.1 Introduction 37 2.5.2 Key factors affecting the measurement of NMs and UFPs 38 2.5.3 Monitoring methods 39

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2.5.4 Key uncertainties 44 2.5.5 Conclusions 44 2.6 Topic 4: Analytical tools to trace NMs and UFPs to their source (fingerprinting) 45 2.6.1 What is fingerprinting? 45 2.6.2 Characteristics of NM and UFP that may aid fingerprinting 45 2.6.3 Source characteristics that can be identified 47 2.6.4 Types of analytical tools 48 2.6.5 Conclusions 49 2.7 Topic 5: Abatement techniques for NMs and UFPs 50 2.7.1 Introduction 50 2.7.2 Abatement technique summary 50 2.7.3 Conclusions 52 2.8 Topics 6, 7 and 9: Processes affecting NMs and UFPs in the air 52 2.8.1 Introduction 52 2.8.2 Evaporation and Condensation 53 2.8.3 Coagulation 56 2.8.4 Chemical reactions 58 2.8.5 Deposition processes 60 2.8.6 Application to manufactured NMs 62 2.9 Topic 8: Estimation of human exposure to NMs and UFPs 64 2.9.1 Information sources 64 2.9.2 Reported measurements of NMs and UFPs in ambient air 64 2.9.3 Estimated human exposure to NMs and UFPs 71 2.9.4 Uncertainties in exposure estimates 73 2.9.5 Gaps in knowledge and possible future research areas 73 2.10 Topic 10: Risk assessments of NMs and UFPs 74 2.10.1 Information sources and data availability 74

2.10.2 Toxicological investigations of toxicity of NMs and UFPs relative to toxicity of PM10/PM2.5 75

2.10.3 Epidemiological investigations of the effects of UFPs in ambient air and comparisons with PM10/PM2.5 76 2.10.4 Relationship between particle size and potency and effects 77 2.10.5 The relative importance of particle size, particle composition and surface reactivity in determining toxicity78 2.10.6 Sources of uncertainty 79 2.10.7 Conclusions 80 2.10.8 Gaps in knowledge and possible future research areas 81 2.11 Topic 11: Impact of NMs and UFPs on human health, the environment (ecotoxicity) and relevance to climate forcing (cloud formation and persistence) 82 2.11.1 Information sources 82

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2.11.2 Health impacts 82 2.11.3 Environmental Impacts 85 2.11.4 Climate forcing potential 92 2.11.5 Sources of uncertainty 95 2.11.6 Conclusions 96 2.12 Topic 12: NMs and UFPs metric(s) (particle mass, surface, number) most appropriate to describe dose-effect relationships 97 2.12.1 Information Sources 97 2.12.2 Epidemiological Studies 97 2.12.3 Toxicology 100 2.12.4 Conclusions 102

3. Data assessment [Task 4] 103 3.1 Introduction 103 3.2 Assessment 103 3.3 Summary 111

4. Review of relevant EU legislation and supporting documents [Task 5] 114 4.1 Background 114 4.2 Approach 114 4.3 Coverage of relevant emissions sources by the IED 115 4.4 Coverage of emissions by ELVs and BAT-AELs for sectors where the IED does apply 117 4.4.1 ELVs, BAT-AELs and compliance techniques 117 4.4.2 Coverage within the BREFs 120 4.4.3 Metrics 121 4.5 Identified gaps in coverage 121 4.5.1 Sector coverage 121 4.5.2 Gaps in coverage based on techniques applied 122 4.6 Policy options 123 4.6.1 Conclusions 123

5. Conclusions 124 5.1 Conclusions 124 5.2 Key uncertainties/limitations and options for further work 127

6. References 132

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Table 1 Topics addressed in the report and signposting to relevant sections vi Table 2.1 Topics addressed in this section 6 Table 2.2 Emissions of UFPs from industrial sources 9 Table 2.3 Datasets used to estimate PM0.1 emissions in 2008 (ktonnes) 16 Table 2.4 PM0.1 and PM10 Emissions Estimates for the EU27 in 2008 (ktonnes) [Note 1] 22 Table 2.5 Generic PM0.1 emission factors by fuel type, for heat and electricity generation plant and refineries 29 Table 2.6 Generic PM0.1 emission factors by fuel type, for other large industrial plant 29 Table 2.7 Summary of measurement techniques for NMs and UFPs 41 Table 2.8 Summary of particulate abatement techniques 50 Table 2.9 Time for number concentration to halve and particle size to double by simple monodisperse coagulation (data from Hinds, 1999) 57 Table 2.10 Coagulation coefficients for coagulation between aerosol particles of different sizes (data from Hinds, 1999) 58 Table 2.11 Percentage of molecules on the surface of particles as a function of sizea (from Finlayson-Pitts, 2009) 59 Table 2.12 Estimated population mean exposure concentrations by source for PM0.1 and PM10 based on emissions estimates for the EU27 in 2008 (developed as part of this study); 1 ngm-3 = 0.001 ugm-3 72 Table 3.1 Data assessment matrix 104 Table 3.2 Ongoing nanomaterial projects funded under the Sixth Framework Programme FP6 and Seventh Framework Programme FP7 111 Table 4.1 Coverage of main industrial emission sources of NM/UFP by the IED 115 Table 4.2 Extent to which IED emission limit values are likely to cover NM/UFP emissions for main sectors 118 Table 5.1 Assessment matrix 128

Figure 1 Percentage Contributions to EU-27 (a) PM10 and (b) PM0.1 Emissions Totals (2008) vii Figure 2 PM0.1 Emissions from Industrial Sources by NFR Sector (2008) viii Figure 2.1 Non-Anthropogenic Emissions of (a) PM10 and (b) PM2.5 15 Figure 2.2 Percentage Contributions to EU-27 (a) PM10 and (b) PM0.1 Emissions Totals (LRTAP, 2008) 23 Figure 2.3 PM0.1 Emissions from Industrial Sources by NFR Sector (2008) 25 Figure 2.4 PM0.1 emissions from ‘Other’, disaggregated by NFR code 27 Figure 2.5 EU27 LRTAP PM0.1 Emissions (2008) 28 Figure 2.6 PM0.1 Emissions from Industrial Combustion and Processes: (a) Sectoral Totals (LRTAP) and (b) Point Sources (E- PRTR) (kt) 30 Figure 2.7 EU27 Emissions of PM10 and PM0.1 from Industrial Mobile and Fugitive Sources 32 Figure 2.8 Schematic representation of atmospheric aerosol and the processes that modify it (adapted from Hinds, 1999) 53 Figure 2.9 Processes influencing nanoparticle formation from semi-volatile compounds upon emission in hot gases from a vehicle tailpipe 54 Figure 2.10 Particle dry deposition velocity data for deposition on a water surface in a wind tunnel (Slinn et al., 1978) 61 Figure 2.11 Semi-empirical correlation for the collection efficiency E of two drops (Slinn, 1983) as a function of the collected particle size. The collected particle is assumed to have unit density 62 Figure 2.12 Particle size distributions measured at 3 locations in the UK (NPL, 2010) 66 Figure 2.13 Average particle size distributions (mobility diameter, nm) at Marylebone Road, Regents Park and BT Tower (London) 68

Appendix A Current knowledge of atmospheric sources of NMs and UFPs from industrial sources Appenidx B Stakeholder consultation Appendix C Summary of stakeholder feedback on interim report

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1. Introduction

1.1 This report

The European Commission contracted AMEC (supported by Aether, IOM and Professor Roy Harrison) to investigate industrial emissions of nanomaterials (NMs) and ultrafine particles (UFPs) with the objective of improving the understanding of their emissions in order to contribute to setting priorities for future policy.

The purpose of this final report is to provide the Commission with the outputs of the study including a summary of the available evidence identified on NMs and UFPs. This report constitutes the outputs of Tasks 1, 2, 3, 4 and 5 of the study and incorporates feedback received from stakeholders at a workshop held on 6th June 2011.

1.2 Definition of NMs and UFPs

Over the last few years there has been significant discussion on definitions with regards to nanomaterials. Many national and international organisations (including for example International Organisation for Standardisation (ISO), the European Standardisation Committee (CEN) and the OECD Working Party on Engineered Nanomaterials (WPNM)) have sought to develop and implement definitions for ‘nanomaterial’ and other related terms (e.g. nanoparticle, nanotube, nanoscale) (see Box 1). At the current time, a formal definition has not been agreed at a European level.

For the purposes of this study the following definitions were assumed, as outlined in the project specifications:

Nanomaterial means a material in which one or more properties are determined to a significant degree by the presence of nanoscale4 structural features.

4 Nanoscale means a scale at which the surface or interfacial properties of a material become significant compared with those of the bulk material. The term nanoscale is generally used to refer to the dimensions of the order of 1 nm to 100 nm.

5 NMs have specific properties and/or functionalities and can be nano-objects (sheets, tubes or particles) that may have respective one, two or three dimensions at the nanoscale, or nano-structured materials which have an internal or a surface structure at the nanoscale both of which lead to these specific functionalities. The definition of NMs therefore explicitly also covers in nanostructured materials, agglomerates or aggregates of parts which have internal or surface structures at the nanoscale, but which are larger than nanoscale and retain properties and/or functionalities that lead to specific properties that are characteristic to the nanoscale.

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included provided that they have retained properties and/or functionalities. NMs of biological origin and capable of replication such as viruses are outside the scope of this study.

Box 1 - Current status of developments in terminology and definitions for ‘nanoparticle’

In 2009, the European Parliament called “for the introduction of a comprehensive science-based definition of nanomaterials in Community legislation as part of nano-specific amendments to relevant horizontal and sectoral legislation”, and “on the Commission to promote the adoption of a harmonised definition of nanomaterials at the international level and to adapt the relevant European legislative framework accordingly”. Since then, considerable efforts have been made to produce a harmonised definition of ‘nanoparticle’. Definitions by the International Organisation for Standardisation (ISO) and the European Standardisation Committee (CEN) Technical Committee (TC) 229 of the ISO is responsible for standardisation work related to nanotechnologies. TC 229 finalised and released the technical specification (TS) CEN ISO/TS 27687 ‘Nanotechnologies — Terminology and definitions for nano-objects - nanoparticle, nanofibre and nanoplate’ in 2008. The standard is concerned with the terminiology and definitions for objects at the nano-scale, which come in several shapes. After revision, it will be released with a new number, ISO/TS 80004-2. Core terms are defined in the standard as followed • Nanoscale: size range from approximately 1 nm to 100 nm • Nano-object: material with one, two or three external dimensions in the nanoscale • Nanoparticle: nano-object with all three external dimensions in the nanoscale • Nanofibre: nano-object with two similar external dimensions in the nanoscale and the third dimension significantly larger • Nanoplate: nano-object with one external dimension in the nanoscale and the two other external dimensions significantly larger • An ultrafine particle is defined as: a particle with an equivalent diameter less than 100 nm In the same series, a second document was published in 2010: ISO/TS 80004-3:2010 ‘Nanotechnologies - Vocabulary - Part 3: Carbon nano-objects’. This document defines terms such as graphene, fullerene, and carbon nanotube (singlewall and multi-wall). Also in 2010, ISO/TS 80004-1 ‘Nanotechnologies - Vocabulary - Part 1: Core Terms’, was published. This document lists a number of core terms including: • Nanomaterials: material with any external dimension in the nanoscale or having internal structure or surface structure in the nanoscale (note: this generic term is inclusive of nano-object and nanostructured material) Definitions regarding nanomaterials by other international organisations and committees Certain organisations are using their own working definitions regarding nanoparticles, including: • OECD • EU Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR) • EU Scientific Committee on Consumer Products (SCCP) • European Union: Cosmetic Products Regulation For further information on the harmonisation of definitions see JRC (2010) “Considerations on a Definion of Nanomaterials for Regulatory Purposes’. European Commission Recommendation (October 2011) The Commission has recently adopted a Recommendation on the definition of a nanomaterial (18 October 2011). This describes a nanomaterial as: "a natural, incidental or manufactured material containing particles, in an unbound state or as an aggregate or as an agglomerate and where, for 50% or more of the particles in the number size distribution, one or more external dimensions is in the size range 1 nm – 100 nm. In specific cases and where warranted by concerns for the environment, health, safety or competitiveness the number size distribution threshold of 50 % may be replaced by a threshold between 1 and 50 %. By derogation from the above, fullerenes, graphene flakes and single wall carbon nanotubes with one or more external dimensions below 1 nm should be considered as nanomaterials." Available from: http://ec.europa.eu/environment/chemicals/nanotech/pdf/commission_recommendation.pdf

1.3 Policy context

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vehicular sources. The legislation has addressed total PM emissions (defined as dust emissions from industrial sources or primary PM emissions from vehicles) and has set air quality standards for various size fractions, such as the total mass of PM10 and PM2.5. There is, however, information on smaller sized particles that needs to be analysed and reviewed in order to understand how and if legislative controls are sufficient, including:

• Atmospheric emissions of NMs and UFPs and their behaviour once emitted.

• Techniques to monitor NMs and UFPs from industrial sources and in ambient air.

• Effectiveness of abatement techniques for reducing emissions of NMs and UFPs.

• Appropriate metrics for setting any future standards if required (e.g. particle mass, number or surface area).

• Toxicological information on the importance of different (smaller) size fractions such as PM0.1 and the chemical composition of PM.

In response to the Parliament’s resolution, the Commission announced that it would report on the Parliament’s requests in 2011. One of the requests is to evaluate the need to review legislation to address NMs that are created as unintended by-products of combustion processes in a cost effective manner. The aim of this study is to support the Commission in the assessments requested by the European Parliament on this aspect.

Review of the current understanding of the emissions and sources and evaluation of the control measures and risks should allow progress to be made towards supporting a decision on whether the current legalisation is adequate to cover NM and UFP in terms of achieving the aims of ensuring a high level of protection for human health and the environment, or whether further policy measures are required to achieve those aims.

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1.4 Aims and objectives

The overall objective of this project was to improve the understanding of emissions of NMs and UFPs in order to contribute to the setting of priorities for policies directed towards their regulation. More specifically, the objectives of this project were:

• To summarize current knowledge on atmospheric releases of NMs and UFP in the EU27.

• To provide an in-depth analysis of the characteristics, dynamics, and impact on human health and the environment of NMs and UFPs released from industrial processes.

• To provide recommendations on how to address identified knowledge gaps.

• To review EU legislation on industrial emissions to determine whether it addresses releases of NMs and UFPs appropriately.

• To develop policy options for the regulation of NMs and UFPs in EU legislation related to industrial emissions.

To achieve these objectives, the work was broken down into the following main tasks:

• Task 1: Overview of current knowledge of atmospheric emissions of NMs and UFPs from all sources (the outputs from this task are combined with Task 2 – topic 2 in this report).

• Task 2: Literature review of available evidence in relation to the following topics:

- Composition, size distribution and, where appropriate, shape of atmospheric releases of NMs and UFPs from industrial sources (Topic 1);

- Relative contribution of NMs and UFPs to overall PM releases focussed on industrial sources (Topic 2);

- Analytical tools for monitoring of NMs and UFPs releases (Topic 3);

- Analytical tools to trace NMs and UFPs to their source (fingerprinting) (Topic 4);

- Overview of abatement techniques for NMs and UFPs (Topic 5);

- Maturation (aggregation, changes of surface properties, chemical reactivity) of newly formed NMs and UFPs (Topic 6);

- Summary of knowledge on the regional and potentially hemispheric transport of NMs and UFPs (Topic 7);

- Estimation of human exposure to NMs and UFPs from the all sources identified in task 1 (Topic 8);

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- Persistence of NMs and UFPs (Topic 9);

- Risk assessments of NMs and UFPs (Topic 10);

- Impact of NMs and UFPs on human health, the environment (ecotoxicity) and relevance to climate forcing (cloud formation and persistence); comparison to the impact of PM2.5 and PM10 (a brief summary) (Topic 11); and

- Discuss the NMs and UFPs metric(s) (particle mass, surface, number) that are most appropriate to describe dose-effect relationships (Topic 12).

• Task 3: Stakeholder consultation to supplement data gathered under Task 2 and to try and address data gaps and/or key uncertainties identified.

• Task 4: Assessment of data comprehensiveness and quality.

• Task 5: Review of the IED to identify whether it adequately and appropriately addresses the prevention and control of NM and UFP emissions from industrial sources.

• Task 6: Organisation of a stakeholder workshop to discuss draft outputs.

• Task 7: Meetings with the Commission.

1.5 Report structure

This report is structured as follows:

• Section 2 presents an overview of the available evidence on NMs and UFPs against each of the topics described in the previous section (Tasks 1-3). Appendix A includes further details for some of the topics.

• Section 3 provides an assessment of the data available for each topic in terms of comprehensiveness and quality (Task 4).

• Section 4 presents a review of the IED to investigate whether it addresses NM and UFP emissions (Task 5).

• Section 5 presents the main conclusions for the study.

• References are provided in Section 6.

Appendix B includes a summary of discussions at the stakeholder workshop and Appenndix C summarises feedback received on the interim report circulated to participants and other stakeholders in advance of the workshop and the way in which it has been taken into account for the preparation of this report.

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2. Current knowledge of atmospheric sources of NMs and UFPs from industrial sources [Tasks 1- 3]

2.1 Overview

This section provides a summary of the information gathered for each of the topics of interest. The table below summarises the topics covered and corresponding section numbers for reference.

Table 2.1 Topics addressed in this section

Section reference Topic

Section 2.2 Topic 1: Composition, size distribution and, where appropriate, shape of atmospheric releases of NMs and UFPs from industrial sources

Sections 2.3 and 2.4 Topic 2: Relative contribution of NMs and UFPs to overall PM releases

Section 2.5 Topic 3: Analytical tools for monitoring of NMs and UFPs releases

Section 2.6 Topic 4: Analytical tools to trace NMs and UFPs to their source (fingerprinting)

Section 2.7 Topic 5: Overview of abatement techniques for NMs and UFPs

Section 2.9 Topic 8: Estimation of human exposure to NMs and UFPs from the all sources identified in task 1

Section 2.10 Topic 10: Risk assessments of NMs and UFPs

Section 2.12 Topic 12: Discuss the NMs and UFPs metric(s) (particle mass, surface, number) that are most appropriate to describe dose-effect relationships

The information presented in the following sections is primarily based on published literature sources supplemented with inputs gathered direct from a range of stakeholders. This was further supplemented with additional information gathered from stakeholders during and after the stakeholder workshop for the study.

For many of the topics, further detail is provided in Appendix A.

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2.2 Topic 1: Composition, size distribution and shape of atmospheric releases of NMs and UFPs from industrial sources

2.2.1 Introduction

In the urban environment, the majority of UFPs are associated with emissions from traffic and stationary combustion sources. In terms of the total number of particles, UFPs dominate in the urban atmosphere. However their contribution to the total mass of particulate matter is very small in comparison.

The majority of the literature on the physical and chemical properties of UFPs focuses on the road transport sector, as this is generally the largest contributing source in urban areas at street level where the majority of exposure occurs. Although measurements made near Los Angeles in Southern California indicate that stationary combustion sources comprise approximately 46% of the total primary emission of UFPs (Cass et al, 2000), the literature is dominated by measurement studies where road transport is the focus of attention, and there is considerably less information available on emissions specifically from industrial sources.

This section provides a review of literature on the measured number concentrations, size distributions and morphology of UFPs and NMs from a number of industrial facilities, including Waste-to Energy (WTE) plants, Combined Heat and Power (CHP) plants and coal-fired power stations.

2.2.2 Composition of UFPs

The chemical composition of UFPs from industrial combustion sources is highly dependent on the fuel type and operating conditions (Charron and Harrison, 2009). Analysis of fly ash composition from laboratory-based coal combustion experiments show that the UFP fraction has a significant enrichment of trace metals, up to 50 times higher than in the fine or coarse particle fractions (Yinon, 2010).

Chemical analysis of particles emitted from nine CHP plants was carried out by Fuglsang et al. (2010) using Energy Dispersive X-ray Spectroscopy (EDX). A significant enrichment of metals such as Fe, Mn and Cu was also found in the UFP fraction from plants burning waste material. Investigations by Tolocka et al. (2004) also found metals to be important in concentrations of particles smaller than 100 nm from stationary combustion sources.

For plant using biomass, Fuglsang et al. (2010) found that Si, Fe and S and Cu predominated. For gas and oil-fired plants, UFPs were found to be predominantly composed of carbon. Carbon also forms a significant component of UFPs generated by biomass-fired plants.

For NMs, Christian (2009) notes that the chemistry of the surface of a nanoparticle can differ significantly from that at the core. The example of silica is cited, where the core is comprised of SiO2, but the surface would be better represented as SiO(OH)2. This is particularly relevant for inorganic carbon and metallic nanoparticles.

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A short summary of the chemical composition of NMs is included in Section 2.4, where the different industrial sectors and applications which have the potential to give rise to NM emissions are considered. It is apparent that in mass terms, commercially available NMs are dominated by inorganic non-metallic species.

2.2.3 Size Distribution of UFPs

Charron and Harrison (2009) note that 70-80% of atmospheric particles across European measurement locations have a size diameter of below 100 nm. The largest contributing source in urban areas is road transport, however there have been some studies on industrial sources.

In combustion systems, UFP may be formed by nucleation (homogeneous condensation) of semi-volatile species (e.g. metal vapours) when hot exhaust gases are diluted by ambient air, resulting in rapid cooling and supersaturated conditions (Chang et al., 2004). Newly-formed particles then grow by condensation and/or coagulation depending on the temperature and relative humidity of the aging plume and the concentration of larger particles (which provide a large surface area for coagulation and vapour condensation).

A review of research on stationary and industrial sources of UFP was carried out by Biswas and Wu (2005). The particle number and size distribution was noted to depend on the fuel content, the residence time and dilution ratio. This is consistent with the behaviour of particles consisting of semi-volatile species.

Research into particles arising from combustion sources usually employ dilution sampling methods to simulate the cooling that arises when exhaust gases leave a stack and mix with ambient air. Whilst dilution acts to increase the particle number concentration through homogenous nucleation, it also reduces the number concentration of primary particulate matter (e.g. fly ash) and consequently reduces the likelihood of heterogeneous nucleation (condensation onto pre-existing particles) and coagulation (Cernuschi et al., 2009). Therefore, dilution does not necessarily result in increased particle number concentrations, but enhanced nucleation does lead to a shift in the mode of the particle size distribution towards the nanoparticle range (Cernuschi et al., 2009; Giugliano et al., 2008).

Table 2.2 shows examples of measured number concentration and mode diameter for size distributions arising from a variety of industrial sources. The number concentration of particles emitted to atmosphere from a facility is highly dependent on the pollution control system used, operating conditions and fuel type (Buonanno et al., 2009; Giugliano et al., 2008). Therefore comparisons made between different facilities can only be illustrative. Similarly, the method used to sample the exhaust gas and determine particle size and number/mass concentration (e.g. sampling temperature, dilution ratio and analyser type) varies significantly between the studies presented.

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Table 2.2 Emissions of UFPs from industrial sources

Facility Type Fuel Pollution Control System (Note 1) Particle Concentration Measured Particle Particle Mode Data Source (Number cm-3) Diameter Range Diameter

Pilot-scale pulverised Subbitumous Coal ESP 17 nm – 10 μm 75 nm Li et al., 2009 coal combustor

Power Plant Coal ESP 6.0 x 108 5.6 nm – 560 nm Wang et al., 2008

District Heating Sawdust Multi-cyclones 5.7 x 107 17 nm – 300 nm Wierzbicka et al., 2005 (Biomass) Wood Pellets 6.3 x 107

Forest Residues 7.7 x 107

Experimental Fluid Bed Coal None 1.1 x 107 Urciuolo et al., 2008 Reactor Biomass (pine seed shells) 1.49 x 106

Granulated Sludge 1.06 x 107

Refuse Derived Fuel 7.52 x 105

Waste to Energy ESP, dry absorption system, fabric filter, SNCR 3 x 103 – 1.7 x 104

Dry absorption system, fabric filter, SNCR 4 x 103 – 7 x 103 Municipal Solid Waste Cernuschi et al.,2009

Dry absorption system, fabric filter, SNCR, wet 3 4 2.45 x 10 – 7 x 10 absorption system, quencher

Waste to Energy Refuse Derived Fuel Fabric filter 1 x102 – 1 x 103 10 nm – 10 μm 90 nm Buonanno et al., 2010

Waste to Energy Municipal Solid Waste ESP, spray absorber, fabric filter, SNCR 1.00x 105 30 nm – 10 μm 80 nm Buonanno et al., 2009b

Biomass Boiler Wood Pellet Multicyclones 2.0 x 107 – 6.7 x 107 72 nm Guigliano et al., 2008

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Facility Type Fuel Pollution Control System (Note 1) Particle Concentration Measured Particle Particle Mode Data Source (Number cm-3) Diameter Range Diameter

Domestic Boiler Light Fuel Oil None 3.3 x 106 – 1.1 x 108 7 nm – 10 μm 21 nm

Domestic Boiler Natural Gas None 4.3 x 103 – 6.3 x 103 21 nm

Pilot-scale Furnace Coal None 40 – 60 nm Chang et al., 2004

Fuel Oil 70 – 100 nm

Natural Gas 15 – 20 nm

Waste-to Energy Municipal Solid Waste DENOx (SNCR), ESP, desulphurization (2 stage Up to 100 nm Fuglsang et al., 2009 scrubber incl. CaO addition), activated charcoal, 2.0 x 104 agglomeration filter

DENOx (SNCR), ESP, desulphurization (semi-dry 2 8.00 x 10 addition of CaO), activated charcoal, bag filter

DENOx (SNCR), ESP, desulphurization (2 stage scrubber incl CaO addition), CaO and activated 5.30 x 101 charcoal, bag filter

Biomass CHP Straw Bag Filter 2.21 x 106

Straw Bag Filter 8.27 x 104

Woodchips/sawdust Bag Filter 1.28 x 106 30 – 50 nm

CHP Natural Gas None 1.31 x 106

Biogas 5.54 x 105

Gas-oil 6.23 x 105 30 – 50 nm

Note 1: ESP = Electrostatic Precipitator, SNCR = Selective Non-Catalytic Reduction

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The majority of the studies presented in Table 2.2 use an Electrical Low Pressure Impactor (ELPI) to calculate the number concentration of UFPs in the flue gas. The sampling probe is heated to prevent additional condensation, whilst air is added to achieve the required dilution ratio.

Observed UFP size distributions are generally unimodal, with a mode diameter of around 70 to 100 nm for coal and waste-derived fuels (Yinon, 2010). Size distributions for gas and oil combustion sources have been shown to peak at particle diameters of less than 10 nm (Bond et al., 2006; Shi et al., 2001). High numbers of soot/ash particles (of relatively large surface area) are produced during coal combustion resulting in increased coagulation and condensation rates and a shift in the size distribution towards larger diameters. However, in the case of natural gas combustion, fewer particles are generated overall. Therefore the vapour is not depleted so rapidly resulting in higher super-saturations, increased nucleation rates and a smaller mode diameter (Chang et al., 2004).

Particle size distributions for biomass burning measured by Morawska (1999) indicate that the particle mode diameters are in the 40-60 nm range. However, these are studies of the open burning of biomass i.e. forest fires and agricultural field burning. As such they are not representative of the combustion conditions under which biomass may be burned in industrial sources. It is considered most likely that biomass burned in controlled conditions in stationary combustion – in a boiler or generator – will emit particles with similar size distribution to those from coal and other solid fuels. Indeed Guigliano et al. (2008) report a mode diameter of 72 nm for combustion of wood pellets in a domestic biomass boiler, which agrees well with the results from Li et al. presented in Table 2.2 above.

A number of the studies shown have measured the total particulate concentration, rather than UFP concentrations. Of the total number of particles measured in the flue gas at an Italian municipal waste incinerator, 65% were found to be in the ultrafine range (Buonanno et al., 2009). Other studies have found the UFP fraction to be as high as 89- 99% of the total particulate concentration (Cernuschi et al., 2009; Giugliano et al., 2008), particularly for high levels of dilution.

A study by Przybilla et al. (2002) found that the particle number concentration is strongly dependent on the composition and purity of the combusted fuel. Purer fuels produce fewer particles overall, but increase the proportion of particles in the ultrafine fraction. Bimodal UFP distributions were observed when a fuel additive, such as ferrocene, was used.

Pollution control systems significantly reduce the number of particles emitted from a stack; Maughn et al. (2003) showed that using a wet Electrostatic Precipitator (ESP) reduces the total particulate concentration by around a third compared with the raw flue gas. However, wet particle control systems may increase the UFP fraction by increasing the absolute humidity of the flue gas, triggering nucleation (Cernuschi et al., 2009; Maughn et al., 2003). A more detailed consideration of the impacts of abatement technologies is included in Section 2.7 of this report.

2.2.4 Shape of UFPs (and NMs)

Christian (2009) proposes a number of different classes for the shape of nanoparticles in general. These are:

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• Spherical: Typical in non-crystalline materials and very small crystalline particles.

• Tear Drop: An extension of the spherical morphology.

• Geometric solid: Typical of crystalline materials. May be a range of shapes including cubic, tetrahedral, icosahedral, etc.

• Dendritic: Composed of nanoscale wires, the dendrite may be much larger than 100 nm.

• Rod or Wire: May have a range of cross sections including circular, cubic and pentagonal.

• Dumbbell: Formed by the growth of one material only at the ends of a rod of another material.

• Discotic: Thin flat plate, often wider than 100 nm. Maybe a range of shapes including hexagonal and irregular.

• Tetrapod: Formed by the growth of hexagonal phase rods from a cubic seed crystal.

The majority of UFPs are formed by combustion and can be in either the solid or the liquid phase. They can be partially or totally composed of semi-volatile material. They can be spherical or of irregular shape and may also be fractal-like agglomerations (Charron and Harrison, 2009).

Fuglsang et al. (2009) recently measured and characterised particles emitted from nine CHP plants powered by waste, biomass, gas and gas oil. The shape of the particles was determined by Scanning Electron Microscopy (SEM). Particles from the plants burning waste were mainly found to be porous and irregular in shape. In the gas, gas oil and to a lesser extent the biomass-fired plants, spherical soot particles dominated the size distribution. The SEM analysis of particles emitted from the gas oil fired plant showed that, in the UFP fraction, the majority of the particles were agglomerations of primary particles with a diameter between 30 and 50 nm.

2.2.5 Conclusions

Literature on emissions of UFPs is dominated by studies undertaken on road transport activities, and there is limited information on emissions from specific industrial sources. Whilst it has been possible to collate and present emissions information (see Table 2.2 and Section 2.4), variations in the particle size distribution amongst industrial sectors and activities are high in uncertainty. Further measurement campaigns, undertaken in a co-ordinated way, to ensure a degree of consistency and comparability, would therefore help to deliver more extensive information on particle size fractionation from industrial sources. This would not only improve the understanding of the emission characteristics, but allow more accurate estimates of PM0.1 emissions to be quantified as they are derived from the fractionation of PM10 emission estimates.

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2.3 Topic 2a: Relative contribution of UFPs to overall PM releases

2.3.1 Introduction

An initial assessment of UFP emissions for the EU27 was made by applying fractionation profiles to PM10 emission estimates held in the GAINS model. The methodology and results from this simple approach were detailed in an earlier progress report under this study (February 2011).

The results provided initial estimates of PM0.1 emissions across the EU27. However a number of conclusions were reached regarding ways in which the methodology could be improved to give emission estimates that were more accurate, complete and consistent:

• Geographical resolution: It was considered desirable to improve the geographical resolution. As a result, the use of national level emissions data was considered preferable. National submissions under the LRTAP Convention were identified as a suitable source of up-to-date data.

• Detailed industrial emissions: To improve the accuracy of emissions data from industrial sources, it was considered appropriate to target the incorporation of point source emissions data into the PM10 emissions dataset. Data from the European Pollutant Release and Transfer Register were identified as suitable data sources6.

• Fuel and capacity data: Emissions by fuel was recognised as being important data for the calculation of PM0.1 emissions. In addition, it was considered valuable to hold capacity data for any point source data that was being incorporated into the dataset. Fuel data are included in the submissions to the LRTAP Convention and the Large Combustion Plant Directive.

• PM fractionation profiles: An initial PM fractionation profile dataset was compiled at the start of the project. However it was clear that this was limited in scope and detail, and far from complete. Improving the detail and completeness was immediately identified as a priority task. Work continued on this throughout the project.

• Use of the latest reported data: The most recently available input datasets were used, as it is expected to bring improvements to the accuracy of the resulting PM0.1 emission calculations.

2.3.2 Non-Anthropogenic PM0.1 Emission Estimates

The PM10 emissions data typically reported at the national level (e.g. under the LRTAP Convention) do not provide reliable estimates, or even identify the main sources, of non-anthropogenic PM10 so alternative sources of information are required.

6 Although it is recognised that there are emissions reporting thresholds under E-PRTR.

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Non-anthropogenic PM10 emissions were estimated as part of the NatAir Research project under the 6th Framework Programme (Contract No. 513699)7 for a number of years up to 2003. The project included an investigation into emissions from a range of sources for different pollutants. The sources of PM considered in the project are:

• Biomass burning and forest fires

• Marine aerosol and estuarine sources

• Windblown dust

• Volcanoes

• Primary Biological Aerosol Particles (PBAPs)

It is also appropriate to recognise that nanoparticles can form through atmospheric homogenous nucleation processes (detailed in Section 2.8). This is a source of nanoparticles in the atmosphere, but does not constitute an emissions source per se. As a result it was not considered in this project.

The NatAir project concluded that the non-anthropogenic emissions of PM10 for the EU27 (and Norway and Switzerland) would be broadly comparable to the anthropogenic emissions in 2010 (NatAir, 2007). Annual emission values of approximately 1,200 kt PM10 and 200 kt PM2.5 are given. However it is recognised that these are high in uncertainty, and will vary greatly from year to year.

Emissions of sea salt and from volcanoes included only sources within the NatAir geographical extent. This covered the EU27 and some surrounding areas of sea (the volcanoes therefore being located in Italy and Iceland only). The emissions for windblown dust also represent emissions originating from the EU27 (Theloke, 2011). Estimates for material entrained from other continents are presented in the project final report (NatAir 2007), but are not included in the figures presented here.

The following figures provide an indication of the contribution from the different non-anthropogenic components to total non-anthropogenic PM10 and PM2.5 emissions.

7 http://natair.ier.uni-stuttgart.de/

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Figure 2.1 Non-Anthropogenic Emissions of (a) PM10 and (b) PM2.5

(a) PM10 (b) PM2.5

Sea Salt 35% Volcanoes 43%

Sea Salt PBAPs 18%

9% Volcanoes 16% Biomass Burning 2% PBAPs 6% Biomass Windblown Dust Windblown Burning Dust 12% 21% 38%

The emissions from all of these sources are high in uncertainty, but the data provide an indication of the relative importance of the different sources for PM10 and PM2.5.

These data have been used to calculate emissions of non-anthropogenic PM0.1. However, it should be appreciated that for some sources it has not been possible to source suitable fractionation profiles. As a result, expert judgement has been used (notably for volcanoes).

A short overview of the current knowledge of each of the sources from the NatAir project, and their expected contribution to a non-anthropogenic PM0.1 emissions total, is included in Appendix A1. Based on these comments and assumptions, the total emission is estimated to be 7 Gg of PM0.1, and is comprised of approximately 50%-50%

Biomass Burning and Volcanoes. This emission total equates to approximately 2% of the anthropogenic PM0.1 emissions presented in Section 2.3.5. In the context of a similar calculation for PM10 emissions, it is clear that non- anthropogenic emissions occur primarily in the coarse fraction of PM.

2.3.3 Anthropogenic PM0.1 Emission Estimates

The methodology in this Task uses official EU27 emissions datasets as input data. These datasets represent a collation of individual national submissions under different reporting requirements. The resulting emissions are regarded as including both “intentional” and “unintentional” emissions.

A number of countries were contacted regarding the availability of UFP emissions data, but as expected, there was very little coverage of the EU27, and no consistent approach. Therefore available PM10 data were combined with size fractionation profiles (which estimate the proportion of ultrafine particles present in PM10 emissions), to produce an estimate of PM0.1 emissions across the EU27.

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The following sections (and associated Appendices) consider in some detail the input datasets (PM10 emission estimates and PM size fractionation profiles) and the methodology used to produce an estimation of PM0.1 emissions across Europe.

PM10 Emission Inventories

To obtain PM10 emissions data across the EU27, data from the most recent submissions under the LRTAP Convention was used (data for 2008)8. Whilst these data do provide emissions at a national level, there are gaps in the reporting. An alternative would have been to use the data from the GAINS model, which is derived from the LRTAP datasets. However the most recent GAINS dataset is for 2005 so the more recent LRTAP data were used in preference. The LRTAP data also represent the official submissions from Parties to the Convention.

To improve the detail in the industrial sectors across the EU27, it was decided that the LRTAP data should be supplemented by a point source emissions dataset. Data from the European Pollutant Release and Transfer Register (E-PRTR)9 and the Large Combustion Plant Directive (LCPD)10 were reviewed to provide point source data for large industrial facilities6.

Appendix A1 provides a detailed explanation of the inventories used in this investigation as well as the additional sources of information required for the methodology. These are summarised in Table 2.3 which also highlights the reporting differences between the inventories. Additional data manipulation was therefore needed to convert the data formats into a single compatible data structure.

Table 2.3 Datasets used to estimate PM0.1 emissions in 2008 (ktonnes)

Geographical Sectoral Detail & Fuel/Activity Reporting Format Year Pollutant Resolution Format Data

Input Dataset

LCPD Country (Point) Point source (address) Point source 2006 Dust Yes

LRTAP Country NFR NFR (level 3) 2008 PM Yes Convention 10

8 Available from: http://www.ceip.at/submissions-under-clrtap/2010-submissions/

9 Available from http://www.eea.europa.eu/data-and-maps/data/member-states-reporting-art-7-under-the- european-pollutant-release-and-transfer-register-e-prtr-regulation-2

10 Available from: http://www.eea.europa.eu/data-and-maps/data/plant-by-plant-emissions-of-so2-nox-and- dust-and-energy-input-of-large-combustion-plants-covered-by-directive-2001-80-ec

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Geographical Sectoral Detail & Fuel/Activity Reporting Format Year Pollutant Resolution Format Data

NACE, E-PRTR code, E-PRTR Country (Point) Point source (Note 1) 2008 PM No point source address 10

Format Many (including NACE, Conversion - - - - - 11 E-PRTR & NFR) Spreadsheet

Emission Factors 12 - NFR, fuel NFR (level 3) 2010 PM - Spreadsheet 10

Output Datasets

LRTAP Country NFR NFR (level 3) 2008 PM Yes Convention 10

Point source and NFR Converted LCPD Country (Point) NFR (level 3) 2008 PM Yes (level 3) 10

E-PRTR Country (Point) NFR Point source and Industry 2008 PM10 Yes (Note 1)

Note 1: Each E-PRTR data point is not assigned to a specific fuel type. However, the data are assigned to the national fuel mix at a detailed NFR sectoral resolution.

A significant amount of time was invested in converting and processing the LCPD data, to give PM10 (and subsequently PM0.1) emission estimates from industrial point sources for the EU27 for 2008. However it became clear that the dataset derived from the E-PRTR data was not only considerably more complete, but was also considered to provide more reliable emission estimates6. As a result the data derived from the LCPD data was not used in the final data presented in this report.

PM Fractionation

In the emission inventory field it is common practice to derive emission estimates for smaller particulate fractions such as PM2.5, PM1 and PM0.1 by combining PM10 emission estimates with PM10 “size fractionation profiles”. These size fractionation profiles indicate the proportion of the PM10 by mass that is in the PM2.5 size range, and similarly for PM1 and PM0.1. These will henceforth be referred to simply as “fractionation profiles”, although they are specifically for PM10 and refer to size fractionation by mass.

11 This was recently developed by Syke, Finland, and circulated by the TFEIP, and available on the CEIP website (http://www.ceip.at/emission-data-webdab/). The spreadsheet provides a mapping between the reporting formats commonly used for emission estimates.

12 These emission factors were taken from the EMEP/EEA Guidebook, 2009

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The fractionation profiles that are available from the literature are typically derived from measurement campaigns and/or modelling studies. A fractionation profile is usually specific to a particular source of emission, and in the case of combustion emissions, specific to a fuel as well. However, fractionation profiles are very limited in terms of scope and detail, and are not generally available in enough detail to allow additional variables to be taken into account. For example, it is not possible to distinguish between similar sources in different countries, nor is it possible to take different fractionation profiles for different types of solid fuels or liquid fuels into account, or similar fuels with differing sulphur contents. Furthermore, there are a limited number of fractionation profiles, and the resulting coverage across all sources of PM10 is therefore very limited.

An additional issue is that historically there has been a limited amount of research on the PM0.1 component of fractionation profiles. The method that is used to measure emissions of PM is an important factor with regards to determining the size distribution. Historically, particulate mass has been measured and reported, and this provides a body of data albeit rather limited. However, particle number or surface area are increasingly being favoured as measurement metrics because they are considered to be more applicable for health impact studies regarding fine and ultrafine particles. As a result, much of the recent research data for PM0.1 is expressed using particle numbers or surface area based measurements. This was problematic because, for PM0.1 emission inventories, it is necessary to 13 express the emissions in terms of mass if using PM10 inventories as the basis . Therefore the available literature on fractionation profiles is somewhat limited.

A number of different sources were investigated to bring together a range of fractionation profiles and a detailed description of this is given in Appendix A1. The most recent data were used in preference over older fractionation profiles.

Emission Estimates Methodology

A brief description of the methodology for compiling detailed PM10 emissions across the EU27 is included here. The LRTAP and E-PRTR datasets both required a level of manipulation before their data could be compared and combined to give a final emissions dataset. A detailed description of these manipulation techniques is included in Appendix A1.

Ensuring that the PM0.1 emissions calculation resolves combustion emissions by fuel type is important as the fractionation profiles are highly dependent on the fuel. Values of the PM0.1:PM10 ratio for combustion sources using biomass, gaseous, liquid and solid fuels are in the order of 0.08, 0.5, 0.1-0.2 and 0.07, respectively. PM0.1:PM10 ratio values for industrial processes are highly variable ranging from 0 to 0.42.

13 The conversion of particle number and surface area measurements to mass was investigated. However, most literature sources did not provide enough information to allow a specific conversion to be determined, and the wide range of particle shape, composition, and general dependence on the source, means that a generic conversion was not considered appropriate.

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The LRTAP Convention emissions data required the least data manipulation as the reporting format used in the inventory (NFR codes) was that used to unify all of the datasets and provide the final estimates of PM0.1 emissions. However, it was necessary to split the NFR sectoral emissions into emission by fuel type.

For each Party, the fuel data reported under the LRTAP Convention was combined with generic PM10 emission factors to generate emissions by fuel type. These were then scaled so that they summed to the NFR sector total

PM10 emission reported by the Party. This provides a reasonable method for splitting the reported PM10 emission estimates into different fuel types for each country and each NFR category.

Fractionation profiles were applied to the PM10 estimates to produce estimated PM0.1 emissions by NFR sector for each EU27 country. A particularly detailed approach utilising GAINS data was used for transport fractionation profiles, as the information was readily available.

The E-PRTR data was not reported by NFR but the standard reporting format was easily converted to NFR code to reflect the main industry of each point source. Plant emitting over 50 tonnes per year of PM10 are required to report emissions estimates under the E-PRTR14. Each point source emissions datum contains both process and combustion emissions. Using LRTAP data, fractionation profiles were calculated to take into account specific fuel use and the process and combustion emissions split. These fractionation profiles were applied to the point source PM10 data to produce point source PM0.1 emission estimates.

Gap-filling

The method outlined above also ensures that meta-data (and underlying data) are retained for potential use later in the project, or for subsequent projects. Gap filling procedures, that follow emissions inventory best practice, were used on these datasets and are explained in Appendix A1.

2.3.4 QA/QC for Anthropogenic Emission Methodology

There are numerous techniques that can be used to check the quality of the estimated data. The following sections describe some those used in this investigation. Throughout the methodology process, quality assurance techniques such as plotting simple scatter plots were used to visually represent relationships between datasets, and check for outliers. By doing this, any anomalous points were easily highlighted. Information on these manual changes are documented in Appendix A1.

14 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:033:0001:0017:EN:PDF#page=8

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LRTAP Dataset Consistency

As explained above, the LRTAP emissions were divided into emissions by fuel type. Fuel data for combustion 15 sources were combined with generic PM10 emission factors to produce “generic” PM10 emissions by fuel. Generic emissions total were then rescaled so that they summed to the NFR sector total reported under the LRTAP Convention.

However, the generic PM10 emissions are in fact emission estimates in their own right (albeit drawing on generic emission factors and using a simple methodology). It is of interest to understand how well these generic estimates compare with the emission estimates actually reported by Parties under the LRTAP Convention i.e. to what extent the emissions need to be rescaled (and hence the extent to which the ratio of the two emission estimates differs from unity).

The ratio of the LRTAP PM0.1 sectoral emission to the sum of generic emissions was calculated for all countries, and all 1A NFR categories. Assessing the extent to which the ratio deviates from unity gives a general indication of how well-matched country-specific emission factors are with default values from the literature. The results have proved to be very useful in terms of quality assuring the data.

Reassuringly, the data from most countries have ratios which are close to unity. However some countries display data which is consistently higher than literature averages, across the NFR sectors. For other countries, values deviating from unity are only evident for specific NFR categories. This analysis of emissions “intensity” across the countries and source sectors provides useful information for quality assurance purposes and has also been used in other parts of the project (e.g. investigating abatement options). The results from this assessment are provided in Appendix A1.

Area Source Emissions

The LRTAP sectoral data can be regarded as the sum of both point and area sources; the E-PRTR data include only industrial point source data. The difference between the two, as calculated on an individual NFR basis, can be defined as the area source for each NFR within each EU27 country (this defines any source emitting below the E-

PRTR reporting threshold for PM10 as an “area” source, although it is recognised that is likely to include some individual industrial plant).

It is important to note that a number of assumptions have been incorporated into the methodology, and the accuracy level of the LRTAP and E-PRTR datasets can be questionable at times. Furthermore, the use of fractionation profiles to convert the PM10 into PM0.1 emission estimates also impacts on the levels of uncertainty.

15 Emission factors were sourced from the current version of the EMEP/EEA Emissions Inventory Guidebook (http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009) and then aggregated to match the detail of the emissions by NFR and by fuel.

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The following is an example of how the area source estimate was used for QA/QC purposes, and in particular the combination of NFR categories (for combustion and process emissions). Consider an industry for a single country (e.g. Austria, paper and pulp):

Area source emissions = LRTAP emissions(1A2d+2D1) – E-PRTR emissions(paper and pulp)

This calculation was completed for all sectors and all countries after all gap-filling techniques had been performed and thus included all assumptions that had been made throughout the investigation. Only 12% of the calculated area source emissions were less than zero, and most were very small in magnitude. This is considered to be a positive result, and gives an indication of the extent to which estimates may be affected by the assumptions and inaccuracies inherent in the methodology and input datasets. Positive area source emissions accounted for 88% of the data, and hence the point source emission estimates derived from the E-PRTR dataset are generally able to be incorporated into the emission estimates from the LRTAP dataset without any modifications. Over 60% of the area source emissions that are less than zero are in the heat and electricity sector for three countries. This could be a result of the labelling system used within the E-PRTR reporting.

GAINS Emissions Comparison

PM10 emissions data for 2005 are available from the GAINS model, and can be used for checking purposes.

The GAINS 2005 EU27 emissions were converted to PM0.1 emissions using the format conversion spreadsheet and appropriate fractionation profiles. These data were then compared to the PM0.1 estimates from the LRTAP 2008 inventory as a QA exercise. The two datasets of PM0.1 emission estimates were comparable in their proportion of emissions from different sectors. This provides some reassurance that the more detailed and more refined method using the LRTAP and E-PRTR dataset reflects the source distribution of emissions. Appendix A1 includes more details of this QA exercise.

IEA Fuel Data Comparison

The data from the International Energy Association (IEA) balance sheets16 were also used as a comparative QA exercise.

Total fuel consumption (TFC) and total primary energy supply (TPES) were extracted from the balance sheets and compared to the total fuel use reported under LRTAP (see Appendix A1 for the results of this comparison). There was initially a discrepancy for one country, which was investigated and the origin of the discrepancy addressed. Differences between the TFC (or TPES) data and the fuel data reported under LRTAP do exist for some countries, but it is important to note that the LRTAP data only includes biomass, solid, liquid and gaseous fuel and does not take into account other fuels used (such as nuclear, wind, solar and hydro) because they are not relevant for emissions to air. The comparison is only intended to be approximate, and is used to identify significant data issues.

16 http://www.iea.org/stats/prodresult.asp?PRODUCT=Balances

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2.3.5 Results of Anthropogenic PM0.1 Emission Estimates

The following sections provide an overview of the calculated emission results.

Emissions from All Sources

The PM0.1 emission estimates calculated from the LRTAP data provide PM0.1 emissions for each of the EU countries, for different NFR codes. The data can be summed across the countries to provide EU27 total emissions by source sector. These data are shown in the table and figures below. PM10 emissions are included for context.

Table 2.4 PM0.1 and PM10 Emissions Estimates for the EU27 in 2008 (ktonnes) [Note 1]

PM0.1 PM10 PM0.1/PM10

Power Generation 10 119 8%

Industrial Combustion 33 197 17%

Residential and Commercial 41 589 7%

Road Transport 93 290 32%

Other Transport and Mobile Machinery 59 225 26%

Industrial Processes 12 269 4%

Agriculture 22 262 8%

Other 0.01 142 0.01%

TOTAL 271 2,092 13%

Note 1: The emission total is referred to as an EU27 total, although emissions from Greece and Luxembourg are omitted from this analysis due to data gaps.

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Figure 2.2 Percentage Contributions to EU-27 (a) PM10 and (b) PM0.1 Emissions Totals (LRTAP, 2008)

(a) PM10 (b) PM0.1

When comparing PM10 to PM0.1 for the LRTAP data (Figure 2.2 above), the most significant difference is the portion of the emissions accounted for by road transport, other transport and mobile machinery: 25% for PM10 and

56% for PM0.1. This reflects the the fact that sources of PM10 using liquid fuel are assigned very different size fractionation with transportation having a higher proportion of PM0.1 in PM10 than stationary combustion. The opposite trend is observed for industrial processes: the percentage contribution to PM0.1 emissions is lower than that for PM10 (5% versus 13%). This is partly because the contribution from transport makes a larger contribution, but also because many industrial processes (such as handling raw materials) primarily emit in the coarse fraction.

Power generation and industrial combustion (sources contributing to the main focus of this report) contribute 21% of the total PM0.1 emissions. PM0.1 emissions from the two combustion sectors are dependent on the use of different fuel types because the fractionation profiles associated with the different fuels can vary significantly. In addition, the PM10 emission factor also varies significantly from source to source. Combining the impact of these two factors results in varying PM0.1 emissions per unit of energy for the different fuel types. In most cases, biomass produces the greatest emissions per unit of energy (see Table 2.5).

Table 2.4 above presents the different percentages of PM0.1 in PM10 for aggregated NFR sources at an EU level. The data show that, despite different fuel mixes in different source categories, the percentage contribution of

PM0.1to the PM10 emission is 4-8% (with the exception of transport, mobile machinery and industrial combustion). This will not be the case when the data are presented at the national level, because each country has a unique mix

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of fuels (or “activity”) for each NFR category. These country-specific variations are considered in more detail later in this section.

Industrial Emissions

With the incorporation of the E-PRTR point source emissions data into the LRTAP dataset, the industrial emissions can be considered in more detail. To combine the two datasets, the E-PRTR dataset was converted into the NFR categorisation to identify the main industrial activity of each point source. This allowed PM0.1 emissions to be reported by the different industry groups listed below. The detailed methodology for this categorisation is explained in Appendix A1:

• Heat and electricity production (source code 1A1a);

• Petroleum refining (1A1b);

• Iron and Steel production (1A2a, 2C1);

• Other metal production (1A2b, 2C2,3,5);

• Paper and pulp production (1A2d, 2D1);

• Food and beverage production (1A2e, 2D2);

• Mineral production17 (1A2fi, 2A); and

• Chemical production (1A2c, 2B).

By grouping together the process and combustion emissions for each industry group, it is possible to investigate the total contribution that each industry group makes to the EU27 PM0.1 emissions total, but also on a country-by- country basis.

Whilst the NFR reporting format provides a convenient categorisation structure, it does have some shortcomings.

Under the NFR reporting structure, waste-to-energy plants are included in “Heat and Electricity Production”. Unfortunately data on the use of waste as a fuel for generating heat and electricity is not readily available from the LRTAP dataset. As a result it is not straightforward to specifically quantify waste-to-energy plant from other power generating stations.

17 There is added uncertainty in this sector due to the use of the ‘other combustion’ sector when calculating the PM0.1 emissions, as described in Appendix A.

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Data on emissions from plants such as chemical and clinical waste incineration is very variable from country to country. Recent changes to the reporting structure in NFR should facilitate a better characterisation of the PM10

(and hence PM0.1) emissions from these sources in future years.

An “Other” category is included under industrial combustion (as well as in several other NFR categories). Emissions from the minerals industry are reported in this sector, along with sources that cannot be easily identified.

It was therefore not possible to accurately quantify the PM10 emissions from the minerals industry without including emissions from the “other” combustion sector. As a result, emissions from “other” are known to include the minerals industry but also industrial emissions that countries have been unable to assign to a specific industrial NFR category. The E-PRTR data does not suffer from this drawback, and the data gives a much smaller proportion of emissions originating from the minerals sector. The industry-specific fractionation profiles, however, are calculated using the LRTAP data (as this includes activity data) and they are thus affected by the lack of disaggregation.

The following figures show the PM0.1 emissions from different industrial sources from both the LRTAP and E- PRTR data, and the difference in the mineral and other sectors is abundantly clear.

Figure 2.3 PM0.1 Emissions from Industrial Sources by NFR Sector (2008)

(a) E-PRTR (16kt) (b) LRTAP (46kt)

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The fundamental difference between these two datasets are that the LRTAP includes all sources within the NFR category (point and areas sources), whereas the E-PRTR only includes the point source emissions, and only those of large emitters. The heat and electricity industry, therefore, features more highly in the E-PRTR results because it is made up entirely of large sources (see figure (c) above). There was not expected to be such a large difference between LRTAP and E-PRTR data for petroleum refining or the iron and steel sector. This has been investigated further in Appendix A1, which concludes that for iron and steel emissions, the differences are present in the PM10 emissions estimates, and are not caused by the application of fractionation profiles to convert the PM10 emissions into PM0.1 emission estimates. Both refineries and iron and steel have emissions reported in process and combustion categories, and there is considerable variability between the Parties in the proportions reported to these two categories. It may be that a significant amount of the process emissions being included in the LRTAP emission estimates are not being included in the point source reporting to E-PRTR. This provides an indication of the uncertainties involved in the PM10 datasets, even before any conversion to PM0.1 is applied. The paper and pulp industry also shows a large difference between the two emission estimates. But, in contrast to the iron and steel sector, this is to be expected as numerous smaller sources captured by the LRTAP dataset are expected to be omitted from the E-PRTR dataset.

As explained above, PM10 emissions from the minerals industry in the LRTAP dataset cannot be individually quantified as a component of the “Other” industrial emissions. It is therefore not possible to generate an accurate estimate of PM0.1 emissions. The data are therefore not included in Figure 2.3 above. However, it is possible to identify some of the sources included in “Other” industrial combustion and the methodology can be found in Appendix A1. The figure below (Figure 2.4) shows the results of disaggregating this sector. The Combustion emissions shown in this figure represent emissions from the ‘other industrial stationary combustion’ sector. The

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remainder of the data originate from other process categories, allowing a degree of disaggregation. However, 29% of the emissions cannot be expressed as individual sources, and remain “Other” which includes mineral production.

Figure 2.4 PM0.1 emissions from ‘Other’, disaggregated by NFR code

Resolving Industrial Process and Combustion Emissions

Emissions from industrial combustion and industrial processes are summarised in the following two figures.

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Figure 2.5 EU27 LRTAP PM0.1 Emissions (2008)

(a) Industrial Combustion (b) Industrial Processes

As can be seen, one difficulty of using the data presented here is that a high proportion of the emission estimates are assigned to NFR categories for “Other Combustion” and “Other Processes” (shown with Minerals). Iron and steel production make large contributions to the total emission of PM0.1 from industrial processes. However it should be remembered that some plants give rise to both combustion and process emissions, which are often difficult to individually quantify. Parties therefore often report both combustion and process emissions in combustion NFR codes in the LRTAP dataset. A degree of caution is therefore needed when interpreting these data.

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There is a more detailed analysis of these data in Appendix A1.

PM0.1 Emissions and Fuel Type

The ratio of PM0.1:PM10 for a specific country will depend on the distribution of PM10 emissions across the different NFR codes (and thus the fractionation profiles) as well as the fuel use mix. Whilst gas combustion produces less PM10 per unit of energy than coal, PM0.1 as a fraction of PM10 emissions is higher. The following tables show the result of combining generic PM10 emission factors (i.e. not source specific) for combustion with

PM0.1 fractionation data to give emissions of PM0.1 per unit of energy (i.e. an emission factor for PM0.1) for different fuel types.

Table 2.5 Generic PM0.1 emission factors by fuel type, for heat and electricity generation plant and refineries

Generic PM Emission Factor (g/GJ) Generic PM :PM ratio PM Emission Factor (g/GJ) Fuel Type 10 0.1 10 0.1 [Note 1] [Note 1]

Solid 20 0.065 1.3

Liquid 2 0.1a 0.3

Gaseous 0.9 0.5 0.45

Biomass 38 0.075 2.85

Note 1: Emission factors were taken from the EMEP/EEA Emissions Inventory Guidebook for different fuels at a detailed sectoral level, and then aggregated. Similarly, detailed PM0.1:PM10 ratios were used to generate an averaged fractionation value.

Table 2.6 Generic PM0.1 emission factors by fuel type, for other large industrial plant

Generic PM Emission Factor (g/GJ) Generic PM :PM ratio PM Emission Factor (g/GJ) Fuel Type 10 0.1 10 0.1 [Note 1] [Note 1]

Solid 117 0.065 7.6

Liquid 21.5 0.15 3.2

Gaseous 0.5 0.5 0.3

Biomass 149.9 0.075 11.2

Generic data have been presented here and used in a simple way, but it illustrates a number of important points.

First, PM10 emission factors from the literature are highly variable across the industry types. For example, these data suggest that an oil fired large combustion plant in e.g. the iron and steel sector, emits an order of magnitude

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more PM10 than an oil fired power station on a per unit of energy basis. This is probably a reflection of the limited data that is being used to produce the emission factors in the EMEP/EEA Emissions Inventory Guidebook, and may go some way to explaining the discrepancies observed in Figure 2.3 (where LRTAP and E-PRTR data are compared). Despite these issues, it is apparent that biomass produces considerably more PM0.1 than the other fuel types, and solid fuel produces more than liquid and gaseous fuels per unit of energy.

Emissions by Country

The following figure shows the PM0.1 industrial emissions by country, based on the methodology set out in previous sections (and detailed in the Appendices). As with the figures above, the data is presented as “LRTAP” sectoral totals, and the point source data included within these sectoral totals (“E-PRTR” data). Whilst the point source emissions do not represent a full national emissions inventory, they are presented here because they provide a good general indication of emissions from the industrial sources which have been the main focus of this study.

Figure 2.6 PM0.1 Emissions from Industrial Combustion and Processes: (a) Sectoral Totals (LRTAP) and (b) Point Sources (E-PRTR) (kt)

(a) LRTAP Sectoral Emissions (kt)

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(b) E-PRTR (Point Sources Only) (kt)

The PM0.1 emissions calculated from the E-PRTR dataset (Figure 2.5b above) are very variable across the countries.

However, the data show very similar patterns to those of the PM10 emissions data reported to E-PRTR (not shown here), both in terms of the relative contributions from different sources, and in terms of the relative country totals.

Trends in the large point source emissions of PM0.1 are therefore strongly determined by the reported PM10 emissions, rather than the fractionation profiles.

However, it should not necessarily be concluded that to improve the data, more PM10 measurements are the priority. The similarity in trends between the PM10 and PM0.1 emissions may be due to the limited fractionation profiles not reflecting the real world variability between the sources.

Some source sectors show substantial variation in the extent to which the point sources (Figure 2.6b) account for the total sectoral emission (Figure 2.6a). This might suggest differing size distributions across the countries for a particular industry sector, but it may also be affected by incomplete reporting in the E-PRTR data or non-standard reporting in the LRTAP inventory.

Fugitive and Mobile Industrial Emissions

Emissions from fugitive sources and mobile industrial emissions are not included in the above analyses of PM0.1 emissions. A quick assessment of the fugitive and mobile emissions from industry was made, in order to evaluate the importance of these categories that have otherwise been excluded from the industrial emissions analysis. As seen in Section 2.3.5 (Figure 2.2) the mobile sector contributes significantly to total estimated EU27 PM0.1 emissions. The following figure presents PM10 and PM0.1 emissions from ‘mobile combustion in manufacturing industries and construction’ as well as fugitive emissions and compares them to total emissions from the industrial stationary combustion and processes.

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Figure 2.7 EU27 Emissions of PM10 and PM0.1 from Industrial Mobile and Fugitive Sources

The figure indicates that fugitive emissions are not significant for PM0.1, but this is primarily due to a lack of fractionation profiles for these categories. The figure also shows that mobile combustion is far more significant for

PM0.1 emissions than PM10 emissions, emitting 43% of the PM0.1 that is estimated to be emitted from all other sources. It is not possible to quantitatively split these emissions by sector, which is why these emissions are not included in the industrial analysis, but they are clearly an important source of PM0.1 emissions. This is consistent with the large contribution from mobile sources presented in Figure 2.2.

2.3.6 Conclusions and recommendations

Two main conclusions can be drawn from this work that in order to provide more robust estimates of PM0.1:

• A larger body of data on PM10 fractionation would be required; in particular the source coverage needs to be improved.

• Reporting of PM10 emission estimates in the EU wuold need to be more complete, and more consistent between countries.

These two conclusions are considered in more detail below and possible options for future work are included.

Whilst it has been possible to provide quantitative estimates of PM0.1 emissions from individual industrial sectors and countries, it is recognised that the emission estimates are high in uncertainty. This is primarily because there is a very limited body of data on PM fractionation from industrial sources, in particular PM10 emission estimates can only be converted to PM0.1 emission estimates with data that has limited sectoral detail. This is particularly the case for industrial sources, and is considered to be a priority for improving the methodology that has been used here.

Improving the body of data on PM fractionation would require measurement campaigns that captured both stack and area sources. Section 2.5 includes a review of the different measurement techniques that can be used, and is it

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clear that undertaking these measurements is far from routine. Emission inventories make estimates of emissions at source, and therefore draw on stack measurements. However for assessing impacts, consideration needs to be given to particle formation and other transformation processes.

In improving the body of information on PM size fractionation from stationary sources the first step could be to assess the variability between large combustion sources using the same fuel type. This would require a co-ordinated and well structured stack measurement programme to ensure that results are consistent. The output should provide an indication of how reliable the generalised fractionation profiles used in this study are.

Option 1: Undertake a well co-ordinated and consistent programme of measurements to determine the variability of PM fractionation across stationary combustion sources using the same fuel type. Repeat this programme to capture data for all of the following fuels: Biomass, Coal, Oil and Natural Gas.

Following this, it would be beneficial to consider investigating process emissions. However, given that many sources of process emissions are fugitive in nature, designing a measurement programme is challenging. A combination of modelling and measurement would presumably be needed.

Option 2: Design and undertake a programme of co-ordinated measurement and modelling to evaluate the size fractionation of PM10 from a range of process emissions.

The second conclusion that can be drawn from this element of the study is that the quality, consistency and comprehensiveness of existing emissions data for PM10 is highly variable between Member States. Possible options to address these issues are discussed further below. Whilst they are not a high priority for improving our understanding of emissions of NMs and UFPs directly, they have influenced the ability to develop robust emission estimates during this study.

As explained in this report, gap filling routines have been needed to ensure that the input datasets are complete. The completeness of the input datasets has been very variable across different countries, as has the extent to which the

NFR reporting structure has been followed. The LRTAP and E-PRTR PM10 emissions datasets are reasonable in terms of data capture. However, additional assumptions and processing have been required to review the way different countries have assigned emissions to the different NFR categories. Based on the inter-country variations of emissions, and comments from LRTAP international expert reviews, some reported emission estimates are clearly questionable. Given that PM is likely to be included in upcoming revisions to Protocols and Directives, it would be sensible to review the Guidance available to Parties, and the extent to which Parties are following this.

Option 3: Undertake a review of the PM10 and PM2.5 emissions data currently submitted under the LRTAP Convention, to check for completeness, consistency and weaknesses in the information currently provided by the EMEP/EEA Emissions Inventory Guidebook.

It has been challenging to incorporate the E-PRTR dataset into the LRTAP because no fuel use data is available with the point source emission estimates. Work was also required to convert the different datasets into a unified

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sectoral structure. In line with streamlining initiatives, it would be sensible to review whether changes can be made to allow data to be more easily combined.

Option 4: Consider whether it is possible to capture fuel use data for large point sources through the existing reporting routes (such as the E-PRTR).

Option 5: Review the content of the Reporting Format Conversion spreadsheet developed by the TFEIP, and assess whether there is scope to make amendments to either the NFR or E-PRTR reporting structures to allow a more straightforward unification of the data being reported to both.

2.4 Topic 2b: Relative contribution of NMs to overall PM releases

2.4.1 Introduction

Unlike PM0.1, it has not been possible to source quantitative data on the emissions of manufactured NMs, and an entirely different approach is required to assess emissions to air. A “bottom-up” approach is used here to consider the manufacturing and service sectors which in which NMs (or products containing them) are made or used. The different sectors or applications can then be considered in terms of current scale and potential to emit NMs to air from the manufacture and use of product, or service that is offered.

Very little quantitative information has been sourced. The approach outlined above therefore has been used to provide indicative and qualitative information on potential emissions, albeit with a high degree of uncertainty. This should indicate where more focused work can be undertaken. It is also noted that during the course of this project, RIVM have been undertaking work for the Commission which aims to compile a NM inventory for the EU. Results can be found in the report by Wijnhoven et al. (2011) titled ‘Nanomaterials in consumer products: Update of products on the European market in 2010’. This provides an update of a study in 2007. For 2010, 858 consumer products that claimed to include, or use some form of nanotechnology or nanomaterials were identified to be present on the European market. This represented a six fold increase of the market in the preceding three years.

The chemical and physical properties of NMs vary considerably, as do the applications for which they are currently being used. To approach estimating emissions to air, the most extensive applications will need to be given priority, and the following sections consider the industrial applications which are the most extensive in terms of NM usage.

2.4.2 Products using NMs

The European Commission’s Second Implementation Report (European Commission, 2009) titled “Nanosciences and Nanotechnologies: An action plan for Europe 2005-2009” provides a review of NMs on the market, indicating a list of compounds and the sectors in which they are used. The report also refers to the Woodrow Wilson database,

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which lists commercially available products claiming to include some form of nanotechnology18. The European Consumers Organisation also compiles an inventory of products containing NMs (ANEC/BEUC, 2010).

Data from both of these product inventories have been obtained, and a review of the content indicates that they provide some simple data which can be used to determine the relative importance of different market sectors. However, caution is needed regarding the levels of uncertainty that result. For example, the Woodrow Wilson database includes all products that use the term “nanomaterials”, and this is sometimes applied by manufacturers in a very non-scientific way. RIVM have undertaken studies to investigate whether consumer products claiming to use or contain NMs actually do so. Oomen et al. (2011) found that a significant number of products claiming to contain NMs did not, and some products amongst those not claiming to contain NMs did.

The Commission contracted Risk and Policy Analysis Limited (RPA) to assess the products on the market containing NMs, and they reported at a conference on “Nanomaterials on the Market” on 9 October 200919. Their presentation explains the extent to which the use of NMs are captured by legislation such as REACH, but does not include comment on the applications which are the most extensive, or those which have the greatest potential for releasing NMs into the atmosphere.

2.4.3 Use of NMs by Type

The following lists some of the more extensive commercial applications of NMs known to exist.

• Nanosilver: Commercially used in bacteriocides, cosmetics, fabrics, as well as medical and health- related products. Nanosilver is one of the more widespread NMs. RIVM undertook an assessment of whether information might be obtained on nanosilver through REACH (Pronk et al, 2009), but concluded that this was not a sufficiently detailed framework for assessing nanomaterials20.

• Titanium oxide and zinc oxide: Used commercially in sunscreens, cosmetics and self cleaning surfaces. Titanium oxide is also used as a bacteriocide.

• Fullerenes, dendrimers, nanotubes etc: The vast majority of the literature reviewed for this task cites a wide range of potential uses of these NMs. The most significant commercial uses appear to be limited to high performance equipment (such as sports equipment and wind turbine blades) and coatings. Given the diverse nature of these applications, collating reliable quantitative data has been challenging.

• Cerium oxide: Used as an additive in diesel.

18 http://www.nanotechproject.org/inventories/consumer/

19 http://www.nanomaterialsconf.eu/stakeholder-conference.html

20 It should be noted that the provisions of REACH are currently being reviewed in relation to nanomaterials

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• Nano-iron and aluminosilicates: Used in water purification.

• Nanoparticles of silica, alumina and cerium (IV) oxide: Used in surface polishing in the semi-conductor industry.

• Carbon black: This is a mass production chemical largely in the nanoparticle size range. It has a number of different industrial applications including use as a pigment.

2.4.4 Quantitative estimates of NM usage

National Industrial Chemicals Notification and Assessment Scheme (NICNAS) (2007 and 2010) provide quantitative estimates of the tonnage of NMs used in Australia, and therefore provide a useful indication of the commercial areas to focus on in determining similar information for the EU. On a mass basis, acrylic latex used in surface coating applications is by far the largest source. Other significant sources include: Aluminosilicates (water treatment), Carbon black pigment, Phthalocyanine, Silicon dioxide (all used in surface coatings).

The Dutch research group at RIVM have also undertaken research into exposure to NMs in consumer products (Wijnhoven et al. 2009). This included a review of the commercially available products containing NMs and the corresponding market values. The research drew on the following data sources:

• Internet sites of Dutch manufacturers and distributors;

• Contact with Dutch manufacturers (by telephone);

• Internet sites of foreign manufacturers and distributors;

• The Woodrow Wilson database of consumer product (US);

• The Nanotech Product Directory (www.nanoshop.com);

• Information from manufacturers present at the Nanosolutions 2007 symposium in Köln.

They present current and predicted global market shares of products containing NMs. The sectors estimated to currently exceed 10,000 tonnes/year of NMs are:

• Coating and adhesives

• Food packaging

• Catalytic converters

The sectors estimated to currently use 1,000-10,000 tonnes/year of NMs are:

• automotive components

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• UV absorbers

• insulation

• hard disk media

• photocatalytic coatings

• magnetic recording media

• cladding of optical fibres

This provides a guide to the industrial sectors where further research would help most in generating quantitative estimates of emissions to air.

2.4.5 Conclusions

It has not been possible to make quantitative estimates of atmospheric releases of NMs within this project, as insufficient data has been found from the literature. However, it has been possible to provide an overview of the industrial sources sectors that are considered likely to be the largest users of NMs. This provides an indication of the data needed for estimating emissions to air.

Information on the potential for emission from the different uses of NMs (i.e. emission factors) is very limited. One of the main reasons is that measurement techniques are limited. Consequently most information on emissions potential is theoretical rather than measurement based. Even these data are limited to several studies, which are not readily applicable to the industrial processes outlined above.

These uncertainties and limitations could be addressed through further assessments of the emission potential for the industrial processes outlined above are required. This information could then be combined with activity data for each of the industrial sectors to arrive at emissions estimates. It is expected that it will be several years before it is possible to verify theoretical estimates with any measurement data given that routine monitoring of NMs or UFPs is not yet conducted at industrial installations (see section 2.5).

2.5 Topic 3: Analytical tools for monitoring of NMs and UFPs releases

2.5.1 Introduction

Monitoring of particulate matter has been carried out in Europe for many years. During the 1980s, total suspended particulates were measured (Directive 80/779/EC). Studies on the health impact of particles lead to the revision of

European air quality policy during the 1990s. The PM10 fraction was introduced with the publication of Directive 1999/30/EC. In line with the ‘Clean Air for Europe’ strategy to minimise harmful effects of pollution on human

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health and the environment and to improve monitoring and assessment of air quality, the measurement of PM2.5 was introduced by the Air Quality Directive 2008/50/EC. However, traditional mass-based measurement techniques are not suitable for the fraction of particulate matter in question, so new technologies are required.

The development of robust and reliable detection and monitoring technologies for NMs and UFPs is of fundamental importance in determining and monitoring emission points and exposure routes for the meaningful assessment of hazards from such particles. Methods are required that reliably detect NMs and UFPs and measure their physicochemical properties. Methods must support studies to assess the risk of nanoparticles, such as with toxicological and ecotoxicological studies. However, up until recently, this small-sized fraction was frequently ignored by researchers because it was assumed that such particles would undergo intense Brownian motion21 and high collision frequency so that their lifetime would be negligible (Hinds, 1999; Carbone, 2008, 2010). To date, few quantitative analytical tools for measuring NMs and UFP are available, which results in a serious lack of information about their occurrence in the environment (Baalousha and Lead, 2010; Nowack and Bucheli, 2007).

In particular, there is a lack of information on monitoring of NM and UFP releases from industrial sources (Schmatloch, 2000; Ohlstrom et al., 2000; Gaegauf et al., 2001; Maguhn et al., 2003; Chang et al., 2004; Wierzbicka et al., 2005; Buonanno et al., 2009b). So far, studies have been oriented to occupational exposure in the industrial sector and NMs and UFPs in ambient air. There has been a long history of occupational exposure to UFPs (e.g. Knight et al., 1983; Camata et al., 2000; Zimmer and Maynard, 2002) and much work is currently focussed on occupational exposure to engineered NMs (e.g. NIOSH, 2009; Methner et al., 2007). Whilst some attention has been given to emissions from combustion activities, the majority of investigations in this field have been dedicated to traffic sources such as diesel vehicles (e.g. Kittelson, 1998), with rather limited studies for stationary energy production systems.

There are currently no standards or guidelines for the measurement of NMs and UFP emissions from industrial installations. However, there are several ISO standards that provide details on specific monitoring techniques. For instance, ISO 15900:2009 provides guidelines on the determination of aerosol particle size distribution by means of the analysis of electrical mobility of aerosol particles. This analytical method is applicable to particle size measurements ranging from approximately 1nm to 1µm. ISO 28439:2011 provides guidelines for the determination of the number concentration and size distribution of UFP and NM aerosols by use of mobility particle sizers. There is also an ISO standard (ISO/TR 27628:2007) which contains guidelines on characterising occupational exposure from ultrafine, nanoparticle and nano-structured aerosols

2.5.2 Key factors affecting the measurement of NMs and UFPs

There are certain characteristics that must be taken into consideration in the measurement of NMs and UFPs, as their unique features can make them differ from their molecular counterparts (Mackay and Henry et al., 2009).

21 The random movement of small particles resulting from the incessant bombardment of the molecules of suspending medium against the particle.

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They are too small to be effectively detected with instruments such as optical particle counters (OPCs) because the wavelength of light, around 400 to 700 nm, is the limit of resolution. Also, unless they are abnormally high in density, they have insufficient mass to be detected, easily weighed or collected effectively by filtration involving mechanical capture mechanisms. Particles smaller than 50 nm may display quantum mechanical behaviour rather than obeying classical mechanics and in response may exhibit physico-chemically unique optical, magnetic, and electrical characteristics (Kreyling et al., 2006). Other challenges may include the need to differentiate the material of interest from those similarly sized natural materials, the need for sensitive and specific techniques to measure the required metrics, the need to measure NM properties in several media and the need to measure several properties in parallel. According to Baalousha and Lead (2010) all current measuring methods and techniques fall some way short of addressing these requirements.

Furthermore, conditions at industrial installations present further limitations for monitoring NMs and UFPs. High temperatures, semi volatile flue gas components and dynamic physicochemical processes (nucleation, coagulation and condensation) and chemistry make it difficult to obtain a representative measurement.

A further consideration is that, for sources emitting semi-volatile components, much of the nanoparticle load may be formed after emission from the stack as the hot gases cool and mix with ambient air. The implication is that source monitoring, unless simulating these dilution processes, is likely to significantly underestimate emissions of nanoparticles at least by number. Effects on mass are less easy to predict. Further details of the processes affecting NMs and UFPs when emitted to ambient air are provided in Section 2.8.

See Appendix A2 for further details.

At the stakeholder workshop it was highlighted that a key consideration deciding which particles to measure as this will have an impact on the measurement technique i.e. volatiles/condensables/secondary organic formations. PM may not be the most appropriate means of monitoring for NMs/UFPs. For example, it may be more appropriate to focus on specific chemicals instead such as e.g. heavy metals.

2.5.3 Monitoring methods

Overview of techniques

Gravimetric techniques are the most widely used for monitoring PM10 and PM2.5. NMs and UFPs, unless abnormally high in density, have insufficient mass to be easily weighed. Furthermore, dynamic changes undergone by these particles (nucleation, volatilisation, condensation and coagulation, strongly influenced by sampling conditions) might lead to rather inconsistent and inaccurate results (see Appendix A2). Therefore, measurement of mass is not necessarily appropriate; instead for UFPs and NMs, exposure metrics such as particle number and surface area concentration may be important (see Section 2.12 for further information).

A straightforward monitoring technique may simply detect the presence of NMs and UFPs; others may quantify the number, size distribution or surface area. These measurement techniques differ from characterisation techniques

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which assess the chemical content of a nanoparticle sample, the reactions on the surface of the nanoparticles or the interactions with other chemical species present. There is also a divide between techniques for bulk aerosol characterisation and those that can look at individual particles. Measurement techniques may be combined to provide more information from one sample. It should be noted that because effective methods have historically been available for number measurement, this has been the most commonly used means of characterisation, with surface area and mass commonly estimated by manipulation of number size distribution data (Charron and Harrison, 2010).

A summary of currently available devices and methods for measurement of number, mass and surface area concentration is provided in Table 2.7 (further detail on the individual techniques is available in Appendix A2).

Several of the instruments and methods listed also enable information about particle size to be generated. As the table shows, different techniques are applicable to different sample types. For example, some require the sample to be gaseous and others use suspensions or a liquid sample. Besides the analysis itself, sampling, pre-treatment (e.g. dilution) and separation play a very important role in obtaining accurate and reliable measurements (Burthscher, 2002) (see Appendix A2).

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Table 2.7 Summary of measurement techniques for NMs and UFPs

Metric Technique (Note 1) Real-time/ Sample Lower range Commercially Notes/ Limitations Continuous available

Surface area

Surface area – Transmission electron microscopy No <1µg has to be prepared as a thin film Down to 1nm 3 Additions to TEM can provide more information (TEM) direct and Off-line and be stable under an electron beam e.g. Scanning Transmission Electron Microscopy characterisation and a high vacuum analysis (STEM); High Resolution TEM or in-situ measurements as Environmental TEM

Surface area – Scanning electron microscopy No Sample must be conductive or sputter Down to 1nm 3 Can be used in-situ as Environmental SEM. (SEM) Simonet et al (2008) direct and Off-line coated. Easier to prepare than TEM characterisation sample analysis

Surface area Diffusion charger Yes Aerosol 25-300nm 3 Real-time measurement of aerosol active surface area. Not all commercially available diffusion chargers have a response that scales with particle active surface area below 100 nm. Diffusion chargers are only specific to nanoparticles if used with an appropriate inlet pre-separator.

Surface area Electrical Low Pressure Impactor Yes Aerosol 7 nm–10 μm 3 Real time measurement of particle number, (ELPI) surface area and mass concentration and size distribution. Aerodynamic size classification with possibility for chemical analysis of collected particles. Additional measurement of particle inherent charge possible..

Particle size

Particle size Atomic force microscopy (AFM) No Samples must adhere to a substrate and 1nm – 8µm 3 A form of Scanning Probe Microscopy (SPM). be rigid and dispersed on the substrate. Requires less time and cost than SEM and TEM. Off-line analysis The appropriate substrate must be chosen. Air or liquid samples.

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Metric Technique (Note 1) Real-time/ Sample Lower range Commercially Notes/ Limitations Continuous available

Particle size Differential Mobility Analyser Unknown Aerosol Down to 3nm. 3 Can be combined with other techniques to create (DMA) differential mobility particle sizer (DMPS)

Average Particle Photon Correlation Spectroscopy No Sample must be a very dilute 1nm – 10µm 3 Based on Dynamic Light Scattering suspension size and Off-line characterisation analysis

Average particle X-ray diffraction (XRD) No Larger crystalline samples (>1mg) Down to 1nm 3 Can identify individual crystals size for a bulk required Off-line sample and analysis characterisation

Number

Number – direct Condensation Particle Counter Yes Aerosol, concentrations 0 to 100,000 Down to 10nm 3 CPC instruments become increasingly insensitive (CPC) particles/cm3, can be in a flow, higher to particles smaller than 10 nm to 20 nm. However, temperatures to 200ºC possible new developments may reach the 1nm limit (Kim et al 2003).

Number – direct Optical particle counter (OPC) Yes Aerosol 300-10,000nm 3 OPCs provide real-time number concentration measurements. HSE (2006)

Number – direct Electron microscopy: SEM or TEM No Variable. Down to 1nm 3 Off-line analysis of electron microscope samples and can provide information on size-specific aerosol Off-line characterisation number concentration analysis

Number – direct Scanning Mobility Particle Yes Aerosol, can be a concentration sample 3-1000nm 3 Incorporates an electrostatic classifier and a CPC. Spectrometer/ Sizer (SMPS) of <1,000 – 2,400,000 particles/cm3 Typically ~2min cycle

Mass

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Metric Technique (Note 1) Real-time/ Sample Lower range Commercially Notes/ Limitations Continuous available

Mass – direct Size selective static sampler No Aerosol Down to 100nm X Assessment of the mass of nanoparticles can be achieved using a size-selective sampler with a cut- off point of approximately 100 nm and the sample analysed by gravimetric weighing or by chemical analysis. Although there are no commercial devices of this type currently available, some cascade impactors (Berner-type low pressure impactors or MOUDI) have selection points around 100 nm and can be used in this way.

Mass – direct Tapered Element Oscillating Yes Aerosol Unknown 3 Microbalance (TEOM)

Mass – direct Filter collection and elemental No Aerosol Microfiltration: 3 Filtration methods are the most simple and analysis 0.2-10µm common fractionation methods. They are distinguished based on the pore size and Ultrafiltration 1kDa- 100MDa molecular weight cut-off of the membranes being used. Filtration may result in sampling artefacts, Nanofiltration: for example piston filtration may result in 100-1000Da agglomeration of particles, and does not allow a good time resolution (Hasselov and Kaegi, 2010; Burtscher, 2002).

Mass Micro-orifice uniform-deposit No Aerosol Down to 10nm 3 Off-line gravimetric mass measurement device concentration impactor (MOUDI) Off-line analysis

Note 1: See Appendix A2 for further details on each individual technique. Note 2: Insufficient information is available regarding costs and so has not been included in this table.

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2.5.4 Key uncertainties

According to Cernuschi et al. (2009) limitations arise from the approaches adopted for measurements, generally conducted with conventional hot stack gas sampling, with no information available on the potential effects on particle number concentrations of particle nucleation and/or condensation phenomena, arising from semi-volatile flue gas components and driven by atmospheric dilution.

Given that no regulation is currently in place that makes it mandatory for industrial installations to routinely monitor NMs and UFPs (or even PM2.5), it is not surprising that little information is available from industrial installations directly. Instead, information comes largely from recent experimental work (a summary of relevant studies is provided in Appendix A2). For instance, several studies considered the formation of combustion aerosols using model systems such as laboratory burners (e.g. Bockhorn, 1994; Siegmann and Siegmann, 1998) whereas little or no detailed data are available on the properties of combustion aerosols in the state of formation from industrial incineration plants (Maguhn et al., 2003). It is known that aerosols formed by industrial combustion processes exhibit residence times of several tens of seconds in the plant prior to emission. This causes strong interactions between the gas and particle phase. Thus, a largely different behaviour with respect to laboratory experiments is likely.

2.5.5 Conclusions

This assessment of the current knowledge on available analytical tools to monitor NMs and UFPs from industrial sources has been based on a review of available literature, supplemented by consultation with authors of key papers providing examples of monitoring UFPs and NMs from industrial installations and with suppliers of monitoring/ measurement equipment.

There have been many studies on particle size distribution of UFPs. In order to understand the transient and rapidly changing nature of NMs and UFPs, real-time measuring instruments are essential. Current analytical capabilities are limited and most measurements have been conducted in laboratory settings. Most studies rely on the use of high-velocity impactor stages for the collection of UFPs and NMs on a time-weighted average basis (e.g. 24-hour average). It is important to distinguish between monitoring and measurement techniques. As illustrated by Table 2.6, there are well established meausurement techniques but there is no routine monitoring of NMs or UFPs taking place at industrial installations. However, this is still a rapidly developing area and further refinements are likely to occur in the future.

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2.6 Topic 4: Analytical tools to trace NMs and UFPs to their source (fingerprinting)

2.6.1 What is fingerprinting?

For this study, “fingerprinting” is interpreted to be about tracking pollutants emitted to the environment to their source. The focus has been primarily on industrial sources. Other sources of NMs and UFPs emitted to the environment have also been considered briefly, where there are relevant examples of fingerprinting being applied.

Fingerprinting could potentially be applied in several different ways. It might be used to determine the source of emissions – such as an individual installation – responsible for measured ambient levels of NM/UFP in the environment, primarily air. Alternatively, it might be used to identify the source of emissions amongst a number of different sources within an individual installation, such as where emissions from several processes are emitted via a single stack or where different fuels are used. Where NM/UFP are transported in the environment, fingerprinting might also provide insights into the environmental fate and behaviour of these species.

Fingerprinting could thus be a useful aid to developing future policy on NM and UFP.

2.6.2 Characteristics of NM and UFP that may aid fingerprinting

There is clearly a wide range of different types of NM and UFP. The characteristics of these species may often be determined – or at least affected – by their source. Examples of such characteristics include:

• Particle size distribution. Across the particle size range, different emission sources may have different proportions of particles within different size ranges. Sometimes there may be a peak at one particular size range whereas, in other cases, there may be bimodal or trimodal distributions. By way of example, Li et al (2009) refer to several studies in which ultrafine PSDs were measured from coal combustion: one, from a pilot-scale coal-fired combustor using medium-sulphur bituminous coal, had a peak of particle number concentrations at 40-50nm; in another study, trimodal PSDs (with peaks at 0.07-0.08, 0.8-2 and 7-10μm on the basis of mass concentration) were observed when burning one sub-bituminous and two bituminous coal seams; in a third study bimodal PSDs (with peaks at 0.1-1 and 5-10 μm) were observed when burning one anthracite and two bituminous coal seams.

• Another example of the use of fingerprinting based on PSD comes from work by Morawska et al (2006). They examined an oil shale project in Australia and levels in the surrounding environment. Their work was able to identify plant signatures through stack measurements, with bimodal PSDs found (with average modal count median diameters of 24nm and 52nm). This distribution was seen to be distinct from the most common emission source in the area (vehicle emissions). This source was found to contribute an increase of about 50% in particle concentration over local ambient concentrations. However, they highlight that the increase in concentration in this rural area was not significant compared to concentrations generally encountered in urban areas nearby.

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• Particle morphology. The shape and form of particles can also vary significantly. For example, Fuglsang et al (2009) measured large, hollow soot particles from gas-fired engines but identified crystalline, porous particles in emissions from selected waste-to-energy plants in a study of a variety of CHP plant in Denmark. Spherical soot particles were found to dominate in particles from gas and gasoil-fired plants, but not from WTE plants.

• Larrion et al (2003) attempted to characterise the source profile (size-resolved chemical and morphological distributions) in the surroundings of a cement plant and in the stack itself. Whilst they were able to use real-time measurements to characterise the matter collected and highlight the method as making it possible to establish relationships with process conditions, they indicate that fingerprinting based on emission factors or typical source profiles has an excessive degree of uncertainty when considering the current state of development of measurement equipment.

• Morphology of engineered NMs is also clearly indicative of a particular type of source – or product life-cycle – though not necessarily of a specific individual source.

• Particle mass / number concentration. The number concentration of UFP in stack gases can seemingly vary according to a number of factors, including air pollution control methods used, as well as factors such as fuel composition and combustion process. For example, one study (Yinon, 2010) provides examples of particle number concentration variability amongst a range of different sources, highlighting that – in that particular analysis – number concentration of UFP emitted from coal-fired power plants in the US was at least one order of magnitude higher than that observed in waste to energy power plants (see Appendix B for details).

• Chemical composition. There are various studies that have attempted to characterise chemical composition and relate this to sources of emission. Once it has been determined that species are indeed NM/UFP through a first analytical technique (generally in-situ), a second analytical technique can be used to determine chemical composition22, which may potentially be done off-site. The approach to analysing chemical composition need not necessarily be specific to NM/UFP but can be similar to fingerprinting based on other characteristics23, albeit with some limitations. Chemical composition can indicate differences in fuel type, for example, between different samples of UFP from different combustion sources. There may be enrichment of certain elements within particular size fractions and the extent of this enrichment may also vary according to the type of source24.

22 However, it is of note that Biswas and Wu (2005) suggest that “to study the transient and rapidly changing nature of nanoparticles, real-time measuring instruments are a must to provide the necessary data.”

23 An example not specific to NM/UFP comes from fingerprinting origins of mercury emissions from different sources of coal, based on isotopic fractionation, in which differences have been highlighted between mercury from coal and from use of metallic mercury in industry, as well as between different coal deposits (see, for example, work by Blum et al at the University of Michigan).

24 Fuglsang et al (2008) identified enrichment of metals such as Fe, Mn and Cu in the PM0.1 and PM1 fraction in particles from both waste-to-energy and biomass burning plants. In theory, such enrichment could be indicative of a source of NM/UFP, even where particles are transformed through agglomeration in the environment.

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• Biswas and Wu (2005) suggest that metals can serve as markers for specific emission sources, with selenium associated with coal combustion; nickel and vanadium with oil combustion; and zinc with municipal waste incineration. The presence of these elements in UFP could thus potentially be an aid to source apportionment.

These are all things that may vary according to the source of emissions. However, this variation does not necessarily imply that these characteristics can be used to identify any individual source of emissions. Similarly, the extent of transformation of these characteristics in the environment after release will have an effect and this is an area that is seemingly less well developed.

For example, Biswas and Wu (2005) indicate that presence of trace metals in PM10 and PM2.5 have been used in the past to determine the contributions of various emission sources by using receptor models. However, they suggest that similar chemical mass balance modelling of the nanometer fraction has not been done.

Other characteristics such as surface area or state of agglomeration may potentially be indicative of particular sources, though there is less evidence available from the literature on use in practice.

2.6.3 Source characteristics that can be identified

As partly alluded to above, the attributes of particular types of emissions sources can have an effect on the characteristics of the NM/UFP that are emitted. These may include, for example: particular types of processes applied at installations; fuel composition in processes responsible for UFP emissions (see above); or types of abatement techniques used. These characteristics may still be present in ambient samples, potentially allowing fingerprinting to be applied.

For example, in relation to processes applied, Chang et al (2005) measured fine particle (PM2.5) emission rates and compositions from a gray iron metal casting foundry. Different mechanisms for pouring and shakeout resulted in variations in chemical abundances and particle size distributions. The highest PM2.5 mass and number concentrations were observed when shakeout started. (This study considered PSDs with size ranges from <0.03 to 2.5μm.)

Cernuschi et al (2010) have undertaken work to examine UFP in flue gases of municipal waste-to-energy plants, with different combinations of abatement techniques, all of which were reportedly types of BAT according to the IPPC Waste Incineration BREF. Their work indicated that particle concentrations are influenced by the design and process configuration of the flue gas cleaning system. Wet scrubbers appeared to enhance the presence of UFP and fabric filter operating temperature was seemingly capable of affecting particle number concentrations by influencing gas-to-particle conversion. They also used dilution and cooling of flue gases as a way of simulating behaviour following atmospheric dispersion; this was found to lead to an increase in particles of less than 20nm diameter (which suggestive of nucleation of species in the flue gases).

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The changes that occur after emission from installations obviously have a bearing on the ability to use such characteristics in fingerprinting. Indeed, the lead author (Cernushi, 2011) highlights the dynamic behaviour of particles as being a factor which makes source apportionment difficult, even when chemical speciation is available.

Another example is provided in a paper by Charron et al (2008) in which source/origin signatures were assigned to anthropogenic and natural sources, by using PSDs and modal diameters. In this case, smaller modal diameters (<50nm) were measured in air from clean maritime sources; with those over 50nm assigned to anthropogenic sources. It was identified that accumulation-mode particles (of 90-120nm modal diameter) were associated with aged polluted air masses. The sources of these were also characterised, including those arriving from other countries. Aitken mode diameter particles were attributed to various sources according to their diameter and PSD, including UK-based anthropogenic sources (largest diameter), local vehicular emissions (bimodal distributions) and maritime air masses.

2.6.4 Types of analytical tools

Whilst this is clearly not a well-developed field in terms of practical application in a regulatory context, there are various types of techniques that are seemingly needed to be able to effectively undertake fingerprinting of NMs/UFPs.

Firstly, it will be important to understand the characteristics of the sources in question and differences amongst them, including differences amongst individual industrial installations as well as other anthropogenic sources (such as vehicle emissions) and natural sources. These may include chemical testing of fuel types, information on abatement techniques applied or knowledge of processes applied and their effect on NM/UFP characteristics.

In some cases, it is possible to first identify and quantify the relevant UFP fraction and then undertake more detailed characterisation of that fraction as compared to other fractions (e.g. determining chemical composition by spectroscopy).

Analytical techniques are required to identify and characterise the NMs and UFPs, both in the releases from industrial installations and in the wider environment. The section on analytical tools for monitoring of releases provides details of some of these techniques. Examples are also provided in Appendix A3 based on reviews by Morawska et al (2009) and by Biswas and Wu (2005). Depending on the characteristics of the NMs/UFPs, it may be necessary to determine some or all of the characteristics set out in Section 2.6.2 above. Many of these techniques are already well developed.

An understanding of the fate and behaviour of NM/UFP in the environment, between the stack and the ambient sampling point or other receptor, is required. This is particularly important given that the lifetime of UFPs in the atmosphere can be very short (15 minutes for 10nm particles quoted by Biswas and Wu (2005), although particle lifetimes are critically dependent on the particle number concentration and, to some extent, also on the size distribution). It is therefore important to also understand how UFPs will be generated from stack gas constituents

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and how they will be removed, such as by agglomeration. Receptor models have reportedly been used for larger size fractions, but no information has been found on their use for NM/UFP.

In terms of specific examples of combinations of techniques, it has been highlighted that the combination of transmission electron microscopy (TEM) with energy-dispersive X-ray spectroscopy (EDX) can potentially be a powerful tool in identification of sources, especially when the major compounds/elements present in the sources are known (e.g. Won et al., 2006).

The EU-SAPHIR-Project, which aims to develop an integrated approach for safe production of nanostructured materials, has used advanced detection, monitoring and characterisation technologies. SAPHIR has used multi angle laser light scattering (MALLS) and Fourier Transform InfraRed (FT-IR) for liquid solution characterisation. For aerosol characterisation, SAPHIR has employed the following techniques: Light induced breakdown spectroscopy (LIBS); Radio Frequency Plasma Metrology (RFPM); Fast Particulate Spectrometer (FPS); NanoMOUDI (not real-time) and TEM25.

2.6.5 Conclusions

This assessment of the current knowledge on available analytical tools to trace NMs and UFPs to their source is based on a review of available literature, supplemented by consultation with authors of key papers providing examples of fingerprinting and with suppliers of measurement equipment.

It is clear that there are well-developed techniques to measure the characteristics of NMs/UFPs both at industrial installations and in the wider environment, although this is still a rapidly developing area and further refinements are sure to occur in the future. What is less straightforward is apportioning contributions of particular sources to measured levels in the environment. There are some useful examples where the signature of specific individual plants has been used to determine the contribution of UFP to ambient levels nearby and examples where contributions to ambient levels have been related to different types of natural and anthropogenic sources.

It is likely that significant additional work would be required in order to use fingerprinting operationally in a regulatory context, not least in better understanding and modelling environmental fate and behaviour. If such a technique is to be used, it is also likely to be heavily data-intensive, requiring information on the characteristics and releases of a range of different sources.

It should also be noted that, in 2007, the European Commission issued a mandate (M/409) addressed to CEN, CENELEC and ETSI for the elaboration of standards on nanotechnology and NMs taking into account related risks. In 2010, a new mandate (M/461) was addressed to the same bodies emphasising the need for standardisation

25 SAPHIR Presentation “Overview of the technologies tested in the SAPHIR project for the on-line monitoring of nanoparticles synthesis” at NANOSAFE (2010): http://www.nanosafe.org/home/liblocal/docs/Nanosafe%202010/2010_oral%20presentations/O12c-2_Dufour.pdf

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as regards measurement and testing tools for the characterisation, behaviour of NMs and exposure. Such developments in standardisation will be important to accompany the introduction of nanotechnologies and NMs on the market and also to support their regulation.

2.7 Topic 5: Abatement techniques for NMs and UFPs

2.7.1 Introduction

The objective of this review of abatement techniques is to summarise the type and range of techniques that may be applicable for the control of emissions of NMs and UFPs and their associated abatement efficiency. A desk based literature review has been performed and in addition a number of abatement equipment manufacturers have been contacted.

The following two points were considered in the review:

• how well existing techniques aimed at abating PM10 also reduce emissions of NMs and UFPs; and

• whether alternative techniques are available, or under development, which are specifically intended for the reduction of NMs and UFPs.

A review of the BREFs was also undertaken to identify if they consider possible techniques for NMs and/or UFPs already.

2.7.2 Abatement technique summary

The findings of this review as regards abatement performance are summarised in the table below, with further details presented in Appendix A4.

Table 2.8 Summary of particulate abatement techniques

Technique Abatement performance Comments

Cyclone Efficiency drops for particles <100 nm. Low cost and widely used.

Advanced Close to 100% for 100 nm size range, with a 50% cut off size of 50 nm. Low pressure cyclones have been developed to cyclone demonstration stage. Potential for hybrid system incorporating ESP to improve UFP abatement.

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Technique Abatement performance Comments

Wet scrubber Widely used principle with a variety of sub- technologies. Efficiency varies significantly for particles less than 5,000 nm.

Source: US EPA, 2010

Charged, wet 100 - 2,500 nm: >99% Small number of commercially operating scrubber UFPs as small as 10 nm can be effectively treated. installations.

Fabric filters Efficiencies of clean filters can be 99% by mass. The collected dust Widely used, although the majority of coal-fired (baghouse) forms a cake on the filter which in turn can further increase the power stations tend to use ESPs instead of abatement efficiency. fabric filters.

Electrostatic Efficiency decrease with particle size. Widely used (either wet or dry systems). precipitators >10,000 nm : 99.9% (ESP) 100 - 1,000 nm : 99% <50 nm : <90%

Wet ESP Abatement efficiency over of 99% for sub-micron particulates. Commercially available.

Enhanced Particle size (nm) Preliminary tests Theoretical (R&D Laboratory tests and theoretical calculations charging for (wood pellet boiler) target) values indicate potential for improved UFP abatement ESP efficiencies. >1,000 70 + % >90%

100 - 1,000 >80 % >90%

100 80% >85%

30 - 100 70 + % >85%

10 not measured no estimation available

Fabric filter – 1,000 nm: 99.999% A number of systems are commercially available ESP hybrid or under development.

Injecting One test indicates 35% reduction for UFPs. NMs and UFPs coagulate with the injected particles particles which can then be captured using conventional techniques.

Impactors Not identified. Used for NM and UFP collection rather than abatement, but possible potential for development.

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Technique Abatement performance Comments

Sonic Not identified Ultrasound vibrations can be used to move techniques particles to increase the occurrence of collisions of particles. This leads to the aggregation of particles. Aggregates are easier to remove than individual particles. It can be applied before or after existing abatement techniques.

2.7.3 Conclusions

The information available on abatement techniques and the impacts they have on NMs and UFPs is highly variable. Whilst the regulatory regime for industrial emissions is currently focussed on larger particles, some of the abatement techniques currently available (and in some cases already being applied by certain sectors) appear to also abate smaller particles with varying levels of efficiency.

A high-level review of the BREFs has indicated that there is limited information included on techniques applicable to finer particles.

The information gathered on this topic has been used to support the review of the Industrial Emissions Directive and supporting provisions (e.g. BREFs) under Task 5 of the study (see Section 3.3 for further details).

2.8 Topics 6, 7 and 9: Processes affecting NMs and UFPs in the air

2.8.1 Introduction

This section aims to provide a summary of the key processes affecting the fate of NMs and UFPs in the air and covers the following topics from the project specification (where possible):

• Topic 6: Maturation (aggregation, changes of surface properties, chemical reactivity) of newly formed NMs and UFPs

• Topic 7: Regional and potentially hemispheric transport of NMs and UFPs

• Topic 9: Persistence of NMs and UFPs.

The processes affecting emitted UFPs are summarised in Figure 2.8 and the text in the following sections describes in detail the processes which can occur. In summary, these are:

• evaporation

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• condensation

• coagulation

• chemical reactions

• deposition

These will be considered in turn.

Figure 2.8 Schematic representation of atmospheric aerosol and the processes that modify it (adapted from Hinds, 1999)

2.8.2 Evaporation and Condensation

Many of the materials emitted to the atmosphere from high temperature sources in nanoparticulate form are semi- volatile, i.e. they actively partition between the vapour phase and the particle phase of the aerosol. An example is the high molecular weight alkanes in engine oil which form the major component of the sub-30nm nanoparticle emissions in diesel exhaust. The condensation and/or evaporation of such materials is determined by the equilibrium saturation vapour pressure of the substance at the particle surface, itself a strong function of temperature but also a function of particle size due to the Kelvin effect and the ambient concentration of vapour. The processes occurring are summarised in Figure 2.9. Initially, the main driver is the rapid reduction in the equilibrium vapour pressure at the particle surface as the hot emissions dilute with ambient air and are cooled. As a result, condensation occurs depleting the atmospheric concentration of vapour. As the particles travel further from source, so the aerosol becomes more diluted and the equilibrium vapour pressure at the particle surface will exceed the ambient vapour pressure of the semi-volatile substance and there will be a net particle evaporation.

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Figure 2.9 Processes influencing nanoparticle formation from semi-volatile compounds upon emission in hot gases from a vehicle tailpipe

The continuum regime is defined as that in which the particle diameter is less than the mean free path ( of the gas molecules surrounding. For air at 1 atmosphere and 293 K, the mean-free path is 66 nm, so for the majority of emitted nanoparticles, the continuum regime applies. The rate of condensation or evaporation is then given by equation 1. (1)

In the above equation, dp is particle diameter, M is the molecular weight of the substance, αc is the accommodation coefficient which expresses the efficiency with which molecules striking the liquid surface are incorporated into the liquid. This can take values from around 0.01 to 1 depending on the substance. is the partial pressure of vapour in the gas surrounding the droplet and is the partial pressure of vapour at the equilibrium surface as given by the Kelvin equation below. is the particle density, Na is Avogadro’s number, m is the mass of a

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vapour molecule, k is Boltzmann’s constant and T the Kelvin temperature. It may be seen from this equation that when , i.e. the concentration of atmospheric vapour exceeds the vapour pressure at the particle surface, , there will be net condensation and when is greater than , net evaporation occurs.

For nanoparticles, there is an important modification to the equilibrium partial pressure at the particle surface. For a flat surface or a large particle, the normal equilibrium vapour pressure for bulk substance at a particular temperature, ps prevails. However, for very small particles with high surface curvature, the curvature of the surface modifies the attractive forces between the surface molecules and increases the equilibrium vapour pressure above the surface. This is expressed by the Kelvin ratio KR (2)

in which M and are respectively the surface tension, molecular weight and density of the droplet liquid and d* is the Kelvin diameter which is the diameter of the droplet which will neither grow nor evaporate when the partial pressure of vapour at the droplet surface is pd. For most substances, the Kelvin effect becomes important for sizes below about 100 nm diameter but this depends on the specific properties of the substance considered.

In the case of vehicle-emitted nanoparticles, the majority of particles by number are formed in the immediate dilution of the exhaust gases as semi-volatile vapours condense to the liquid phase. This process is however competitive with condensation of vapour to the surfaces of larger existing particles (referred to as the condensation sink) which would lead to the growth of pre-existing atmospheric particles rather than the formation of new nanoparticles in the process referred to as homogeneous nucleation. Similar processes occur in the plume of gases emitted from other combustion source such as power plants and incinerators. There is strong evidence that semi- volatile particles from road traffic are liable to evaporate quite rapidly during transport away from the road traffic source of emissions (Dall’Osto et al., 2010).

Many manufactured NMs are not of a semi-volatile nature and therefore are not subject to evaporative loss in the atmosphere. They do, however, act as passive substrates for condensation of atmospheric vapours. The atmosphere is continually oxidising gas-phase species, leading to the formation of vapours of low volatility. Examples are the oxidation of sulphur dioxide to sulphuric acid which rapidly condenses to the liquid phase and the oxidation of volatile organic compounds to form alcohols, carbonyls, carboxylic acids and peroxy compounds of much lower vapour pressure than their parent molecule, which subsequently condense onto airborne particles. Due to the influence of the Kelvin effect and the likelihood of rather low accommodation coefficients, nanoparticles are likely to be a rather poor substrate for condensation and therefore may not grow very effectively by this mechanism. Low volatility vapour will preferentially condense upon larger particles which are unaffected by the Kelvin effect. Typically, the largest available surface area in an atmospheric aerosol is in the accumulation mode (approximately 100 – 1000 nm) (Harrison et al., 2000), although diffusion processes may limit the rate of access of vapours to particles in this size range (see below).

When the particle diameter exceeds the mean-free path of the gas molecules (i.e. for the larger end of the nanoparticle range), there are diffusion limitations to the condensation of vapour and the rate of condensation is

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expressed by equation 3 (3)

In this equation, R is the gas constant, Dv the vapour diffusion coefficient and is the Fuchs correction factor and other notation is as in equation 1. In this case, the condensation rate expressed as a growth in particle diameter is inversely proportional to the particle diameter in contrast to the continuum regime in which the condensation rate is independent of particle diameter. The value of approaches 1 for particles > 1 µm diameter, and provides a smooth transition to equation (1) for smaller particles.

If a NM is water soluble, its atmospheric behaviour will be modified. Soluble materials are subject to deliquescence (i.e. water uptake) at high relative humidities which converts solid particles into aqueous solution droplets. The presence of a solute within the droplet reduces the surface vapour pressure and makes further condensation of water more facile. However, for nanoparticles, the Kelvin effect still applies and there is unlikely to be a tendency for the particles to take up water. Consequently, nanoparticles do not make good cloud condensation nuclei, which generally comprise larger particles of soluble material. It should however be borne in mind that if the nanoparticle is subject to growth by coagulation, this may effectively reduce the surface curvature and reduce the magnitude of the Kelvin effect therefore making water uptake more likely.

It should be noted that condensation processes serve to make particles larger but do not change the number concentration of particles. Similarly, loss of size by evaporation will make particles smaller and will only reduce the number concentration of particles if the particle evaporates completely.

2.8.3 Coagulation

Coagulation is the process in which aerosol particles collide and join together, hence increasing particle size and decreasing the number concentration of particles, as when two particles join together to form a larger particle, they have cut the particle number from two to one.

The theory of coagulation is in outline simple but when examined in detail is relatively complex. The rate of change of number concentration can be expressed by equation 4

(4)

In this equation, N is the number concentration of particles (in number per unit volume) and K0 is the coagulation coefficient. The value of K0 for larger particles (diameter greater than 100 nm) is given by equation 5 (5)

in which k is the Boltzmann constant, T the constant temperature, Cc the Cunningham slip correction and the dynamic viscosity of the gaseous medium. The Cunningham slip correction is a semi-empirical correction applied

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to aerosol behaviour for particles of small sizes, comparable or smaller than the mean free path of gas molecules, describing the fact that they do not experience the supporting gas as a fluid continuum. For application to particles of < 100 nm, equation 5 requires a further correction factor which effects a progressively greater correction as particle size decreases, reducing the estimated value of K0.

The key point to note from equation 4 is that the coagulation rate (i.e. change in number concentration with time) is a function of the square of the number concentration. The coagulation of simple monodisperse particles (i.e. particles of all the same size) is crucially dependent upon number concentration and Table 2.9 expresses the time for number concentration to halve and particle size to double by simple monodisperse coagulation. Typical urban particle number concentrations are of the order of 2 x 104 cm-3 implying a rather slow rate of coagulation for monodisperse particles. Rural areas have particle concentration around an order of magnitude lower which reduces coagulation rates by a factor of 100.

The rates indicated in Table 2.9 are for monodisperse coagulation but nanoparticles entering the atmosphere are mixing with a polydisperse aerosol with a very wide range of particle sizes. Coagulation rates between very small and very large particles are far greater than those for the same number concentration of monodisperse particles and Table 2.10 illustrates how coagulation coefficients can increase by orders of magnitude for polydisperse coagulation. However, it needs to be borne in mind that the number concentrations of larger particles are orders of magnitude lower than those for small particles and hence this effect may be rather more of theoretical than actual importance.

Table 2.9 Time for number concentration to halve and particle size to double by simple monodisperse coagulation (data from Hinds, 1999)

3 Initial Concentration, N0 (number/cm ) Time to reach 0.5 N0 Time for particle size to double (N = 0.125 N0)

1014 20 µs 140 µs 1012 2 ms 14 ms 1010 0.2 s 1.4 s 108 20 s 140 s 106 33 min 4 h 104 55 h 16 days 102 231 days 4 yr

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Table 2.10 Coagulation coefficients for coagulation between aerosol particles of different sizes (data from Hinds, 1999)

Values of K1,2

d1 (µm) d2 = 0.01 µm d2 = 0.1 µm d2 = 1.0 µm d2 = 10 µm

0.01 9.6 122 1700 17000

0.1 122 7.2 24 220

1.0 1700 24 3.4 10.3

10 17000 220 10.3 3.0

2.8.4 Chemical reactions

Chemical reaction processes can affect airborne particles in a number of ways. These include the following:

• Uptake of reactive gases. Nanoparticles have a high surface area per unit mass and may consequently be an effective substrate for adsorption of trace gases from the atmosphere. Such adsorption processes will influence the surface chemistry and may also lead to chemical reactions. Well known reactions are those of sulphur dioxide on carbonaceous surfaces which tend to facilitate the conversion of sulphur dioxide to sulphate. Carbonaceous particles also absorb nitrogen dioxide undergoing surface oxidation with desorption of nitric oxide (NO). Such processes have been shown to occur with nanoparticles and NO2, although the rate was very slow at ambient temperatures (Choo et al., 2008). There has been much less work done on other particle types but it is well recognised that alkaline particles such as those containing calcium carbonate are an effective substrate for adsorption of sulphur dioxide and nitric acid vapour with a subsequent acid based chemical reaction leading to the formation of calcium sulphate or calcium nitrate.

Atmospheric particles are also an effective substrate for the absorption of low volatility molecules such as those of carboxylic acids formed from the atmospheric oxidation of VOCs. Such adsorbed compounds may be chemically relatively unreactive or may lead to the uptake of other constituents. Examples are carboxylic acids leading to the uptake of ammonia through simple acid-base chemistry, or reactions of adsorbed organic compounds with adsorbed ozone.

The reaction of ozone with reactive organic compounds on the surface of particles has been the subject of rather extensive study. Examples are reactions of oleic acid droplets (Hung and Tang, 2010) and maleic acid aerosol (Pope et al., 2010). Heterogeneous oxidation reactions of atmospheric particles by gas phase radicals are also possible (George and Abbatt, 2010). Such reactions involve radical uptake onto the particle surface with subsequent chemical reactions. There are also examples of radical- initiated reactions of adsorbed aldehydes on silicate cluster active sites (Iuga et al., 2010). Reactions on aerosol surfaces have been reviewed by Finlayson-Pitts (2009) who presents Table 2.11 highlighting the percentage of molecules in the surface of small particles. This makes it very clear that a very large percentage of the molecules in nanoparticles are on the particle surface, consequently giving much scope for chemical reaction processes involving the nanoparticle itself. The article also

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highlights the fact that photochemistry may play an important part in such processes. It should be borne in mind, however, that surface coatings derived from adsorption of molecules from the atmosphere may limit surface reactivity.

• Catalysis of chemical reactions on solid surfaces. This overlaps significantly with the discussion above. Finlayson-Pitts (2009) points particularly to the surface photochemistry of oxides of nitrogen to form nitrous acid, a very important substance in atmospheric photochemistry. These are very complex reactions whose dependence on surface properties is as yet not well understood. Adsorption of gases upon surfaces can bring about a bathochromic shift which changes the adsorption spectrum of the absorbate, possibility facilitating reactions at wavelengths typical of the lower atmosphere that might not otherwise take place. Titanium dioxide is known to be a very strong catalyst for photo- oxidation of organic compounds. Such processes are likely to be very efficient for titanium dioxide in the aerosol phase although the overall contribution to atmospheric chemistry will be modest unless the concentrations of airborne titanium dioxide are very high.

• Reactions between aerosol constituents subsequent to coagulation. Measurement of the composition of individual particles within the atmospheric aerosol makes it clear that the composition is often complex, most probably as a result of coagulation processes. Sometimes such processes will lead to chemical reactions particularly if both constituents are water soluble and humidity is sufficiently high to lead to hygroscopic uptake of water. A wide range of mixed metal sulphates are present in airborne particles as a result of chemical reactions within aerosol droplets (Sturges et al., 1989).

• Surface reactions of the nanoparticles themselves. As indicated above and shown in Table 2.11, a large proportion of molecules within nanoparticles reside within the surface. In some cases, this leads to a structure at the edges of the particles different from that of the bulk phase and it seems highly probable that the physical and chemical properties of these particles are also different from bulk material (Jefferson, 2000). For this reason it has been suggested that nanoparticles may be substantially more reactive than the bulk materials. Such an effect is distinct from the quantum effects which influence the chemical properties of extremely small particles, generally less than around 3 nm, where it is recognised that physicochemical properties may be completely different from the bulk material because of the existence of different molecular orbital formations (Wang et al., 2005). Some nanoparticulate materials are likely to be significant reactive with atmospheric gases, for example, the surface of elemental iron nanoparticles is likely to oxidise during atmospheric aging and it has been postulated that there may be changes in the valence state of cerium oxide nanoparticles due to atmospheric processing. However, firm experimental evidence is generally lacking.

Table 2.11 Percentage of molecules on the surface of particles as a function of sizea (from Finlayson-Pitts, 2009)

Particle diameter Volume per Total number of Surface area per Number of Percentage of (µm) particle (cm3) molecules particle (cm2) molecules on molecules on surface surface

1.0 5.2 x 10-13 1.3 x 109 3.1 x 10-8 1.6 x 107 1.2

0.5 6.6 x 10-14 1.6 x 108 7.9 x 10-9 3.9 x 106 2.5

0.1 5.2 x 10-16 1.3 x 106 3.1 x 10-10 1.6 x 105 12

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Particle diameter Volume per Total number of Surface area per Number of Percentage of (µm) particle (cm3) molecules particle (cm2) molecules on molecules on surface surface

0.05 6.6 x 10-17 1.6 x 105 7.9 x 10-11 3.9 x 104 25

0.003 1.4 x 10-20 34 2.8 x 10-13 34 100 a Assuming a spherical liquid particle with a bulk density of 1.2 g cm-3 and that this applies even at the smallest sizes, an average molecular mass of 300 and a surface concentration of 5.0 x 1014 molecules cm-2

2.8.5 Deposition processes

Manufactured NMs will be subject to the same depositional processes as other airborne particles. These processes are as follows:

• Dry deposition. This term describes the removal of particles from the atmosphere by attachment to surface elements such as vegetation, buildings, etc. Such processes involve the turbulent transfer of particles through the atmosphere followed by diffusions through a laminar surface boundary layer of millimetre thickness immediately above the surface itself. For small particles it is generally assumed that, once the particle reaches the surface, attachment is irreversible. Such processes become more efficient as particle size decreases below 100 nanometres diameter, and Figure 2.10 shows particle dry deposition velocity data for deposition on a water surface in a wind tunnel. The data for very small particles are an extrapolation but show an increase of around an order of magnitude between 30 nm and 10 nm diameter.

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Figure 2.10 Particle dry deposition velocity data for deposition on a water surface in a wind tunnel (Slinn et al., 1978)

The atmospheric lifetime, τ, relative to dry deposition is given by equation 6

(6)

in which H is the atmospheric mixing depth and vd is the particle deposition velocity. For a typical daytime mixing depth of 1000 metres and a deposition velocity for a 20 nanometre particle of 1 millimetre per second (typical of the water surface in Figure 3), the atmospheric lifetime is 106 seconds or around 11 days. Considerably higher deposition velocities would be expected above surfaces of greater roughness and consequently lifetimes would be reduced commensurately. Also during periods of more restricted vertical mixing of the atmosphere (smaller mixing depth) more rapid deposition would be expected.

• Wet deposition. Wet deposition of particles involves the scavenging of particles by cloud droplets or raindrops either within the cloud (termed washout) or below the cloud (termed rainout). The rate of incorporation of the particle into the water droplet is dependent upon both the size of the collector droplet and the size of the collected particle as shown in Figure 2.11. As with dry deposition, the collection efficiency rises rapidly as the particle size diminishes and such processes can prove much

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more efficient for the removal of fine particles from the atmosphere than dry deposition processes. This does of course depend upon the existence of rain. Particles comprised of hygroscopic substances can take up water at high humidities (below saturation) and act as cloud condensation nuclei thereby increasing the likelihood of wet deposition. However, as pointed out in an earlier section, this is unlikely to affect nanoparticles because of the Kelvin effect acting against water uptake unless the nanoparticle has already grown by coagulation with other particles.

Figure 2.11 Semi-empirical correlation for the collection efficiency E of two drops (Slinn, 1983) as a function of the collected particle size. The collected particle is assumed to have unit density

2.8.6 Application to manufactured NMs

As indicated above, there are very few direct measurements available relating to manufactured NMs. Most current work on airborne nanoparticles is focused upon traffic-generated particles which will not be well representative of most manufactured nanoparticles. The actual atmospheric behaviour of manufactured nanoparticles will depend very much on the properties of those particles including such issues as:

• size distribution

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• chemical composition

• effectiveness as an adsorption substrate

• water solubility

• chemical reactivity

• vapour pressure

The lifetime in the atmosphere will also depend upon atmospheric properties such as relative humidity, cloud cover, presence or absence of precipitation, mixing depth, turbulence, surface roughness, etc.

Tiwari and Marr (2010) review the role of atmospheric transformations in determining environmental impacts of carbonaceous nanoparticles. This valuable article is however, like the material above, very theoretical in predicting nanoparticle behaviour. They report that in a mondisperse population of 20 nm particles, the timescales for coagulation in urban and rural settings are around 10 minutes and 10 hours respectively although they give no background to these estimates. They report estimates by Ketzel and Berkowicz (2004) of the coagulation timescale in polydisperse particle size distributions measured in urban and rural locations in Denmark as 16-25 hours. They subsequently discuss condensational growth of nanoparticles citing the review by Kulmula et al. (2004) which reports typical growth rates of 1-20 nm h-1. These data are not necessarily representative as they are taken from measurements during homogeneous nucleation events in which large concentrations of condensable vapours are generated in the presence of a relatively low pre-existing particle surface area. Growth rates therefore may often be very much slower than this. They also point out that condensational growth not only makes particles larger but also more spherical so high aspect ratio carbon nanotubes may be changed in form by this process. Loose fractal aggregates of nanoparticles such as those in combustion soots also tend to collapse and become more spherical at high relative humidities and thorough condensation of low volatility vapours (Colbeck et al., 1988; Slowik et al., 2007). Tiwari and Marr (2010) also review particle removal mechanisms from the atmosphere suggesting timescales for removal by dry deposition of about 20 hours derived from estimates in Denmark (Ketzel and Berkowicz, 2004).

Oxidation reactions are considered important because they can increase the solubility of carbon nanoparticles. Reference is made to studies of fullerene oxidation within liquids which show dimerisation reactions brought about by ozone which are considered unlikely to take place in atmospheric systems because of the much higher levels of dilution. Formation of oxides from fullerenes is considered much more likely. Oxidation of other types of carbonaceous particles including single wall carbon nanotubes is considered likely to lead to the formation of hydroxyl, carbonyl and carboxyl groups based upon studies in aqueous media (Li et al., 2008). There have been studies of reactions between ozone and fullerenes in the gas phase but using wholly unrealistic high (percentage) concentrations of ozone which lead to progressive removal of C60 in a matter of days (Tiwari and Marr, 2010). As suggested in the review, the atmospheric relevance of these results is unknown because of the very high concentrations of ozone used, although it can be anticipated that similar but very much slower oxidation reactions would proceed in the atmosphere where ozone concentrations are typically around 50 parts per billion by volume.

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Carbon nanotubes have been shown to undergo broadly similar processes, creating the presence of carbonyl and other oxidised groups on their surface, which is liable to modify their properties, particularly in terms of hygroscopicity.

Tiwari and Marr (2010) also draw attention to the potential of fullerenes and carbon nanotubes to photolytic change. Unfortunately, most studies have been carried out in aqueous dispersions and the extent to which photolysis may occur in the atmosphere is unknown.

Tiwari and Marr (2010) highlight the need for further research upon identification of manufactured nanoparticles in the environment, their atmospheric processing and whether nanoparticles subject to atmospheric aging retain any of their catalytic, therapeutic or toxicological properties. Currently, such questions are largely a matter of speculation. The question is further posed as to whether the treatment of nanoparticles in the same way as fine particles (i.e.

PM2.5) in atmospheric chemistry transport models is adequate. It is suggested that it may be necessary to incorporate more highly resolved particle size distributions within such models to address size-specific behaviour of manufactured nanoparticles.

2.9 Topic 8: Estimation of human exposure to NMs and UFPs

2.9.1 Information sources

Concentrations of particles in ambient air within the PM10 and PM2.5 size ranges are measured across the EU in order that Member States can conform to the 2008 Air Quality Directive and data are available from the European Environment Agency (EEA) website. Summary information on exposure levels is available in the 2010 State of the Environment Report published by the EEA. There are no similar routine measurement data available for NMs and UFPs. A number of studies referenced in PubMed have investigated levels of personal exposure to particles within these size ranges and other fine fractions of PM in ambient air and how it differs from the concentrations in ambient air. Other studies referenced in PubMed or Science Direct report measurements of concentrations of

UFPs/NMs (measured as PM0.1) or other fine fractions of PM in ambient air and provide some limited information on the source apportionment of ambient PM based on measurement data. This is likely to be of significance in assessing the human health risk associated with exposure to UFPs/NPs as PM0.1 from different sources is likely to have differing levels of toxicity. There is no published information on exposure to engineered NMs in ambient air.

2.9.2 Reported measurements of NMs and UFPs in ambient air

There are limited measurement data that indicate that personal exposures to NMs/UFPs are likely to differ from concentrations in ambient air. Johannesson et al. (2007) measured personal exposure to PM2.5 and PM1, together -3 with indoor and residential outdoor levels, for 30 Swedish adults. Median levels of PM2.5 were 8.4 ugm (personal), 8.6 ugm-3 (indoor), 6.4 ugm-3 (residential outdoor), and 5.6 ugm-3 (urban background). Personal -3 -3 exposure to PM1 was 5.4 ugm , while PM1 indoor and outdoor levels were 6.2 and 5.2 ugm , respectively. PM1 made up a considerable amount (70-80%) of PM2.5 in each of the investigated environments. Long-range

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transported air pollution had an important influence on outdoor particle concentrations but not on personal exposure or indoor levels.

Particle size distributions by particle number counts in ambient air are available for the UK for 2007-9 for Harwell, North Kensington and Marylebone Road which represent rural, urban background and roadside sites respectively (NPL, 2010). These data show a predominance of particles that are less than 0.1µm in diameter. There is a shift to coarser particle sizes going from the roadside to urban background to rural site which might reflect how particle size distribution is modified by increasing distance from source (Figure 2.12). It may also reflect the greater importance of naturally sourced particles at the rural site which tend not to be within the nanoparticle size range. Graphs presented by NPL show that total particle number concentrations (between about 7 nm and several microns in diameter measured using the condensation particle counter (CPC) instrument) ranged between approximately 1,000 and 20,000 particles cm-3 at the rural site with most measurements being between 5,000 and 15,000 particles cm-3, most measurements were between about 5,000 and 30,000 at the urban background site and most measurements were between approximately 20,000 and 60,000 particles cm-3 for the roadside site. Most of these particles are within the PM0.1 size range. No corresponding information is available on mass concentrations of

PM0.1. Measurements of particle number concentrations for particles ranging from 16 to 605 nm aerodynamic diameter using the Scanning Mobility Particle Sizer (SMPS) were lower by factors of between 1 and 5 (as a monthly average), but the measurement technologies are not comparable. By way of comparison, a mass concentration of 1µgm-3 would be equivalent to a particle count of approximately 1,900 particles cm-3 for spheres of 0.1µm (100 nm) diameter and unit density or about 9,000 particles cm-3 for spheres of about 60 nm, approximately the modal size measured at UK sites.

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Figure 2.12 Particle size distributions measured at 3 locations in the UK (NPL, 2010)

A number of studies have demonstrated the importance of traffic emissions as a source of exposure to UFPs in ambient air, although relatively few of these studies have been undertaken in Europe. Pakkanen et al. (2003) collected five pairs of simultaneous 24h atmospheric aerosol samples in June 1997 at 3.5 and 20 m heights at an

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urban site in Helsinki, Finland. Average concentrations of particles of submicron size were 11 μgm-3 at both heights. Five principal sources of particles were identified: (1) long-range transport, (2) mainly long-range transport with some local contribution, (3) local oil combustion, (4) vehicle exhaust and brake wear, and (5) various local sources and long-range transport. Concentrations of particles from local vehicle exhaust emissions in the 0.15–0.4 μm size range were higher at street level, particularly for 0.24 μm particles (12%). Long-range transport and sea salt were important for 0.4–1.3 μm particles leading to a slightly higher average mass concentration at the rooftop site compared to street level for this size-range.

Price et al. (2010) reported that NP/UFP concentrations in a busy traffic corridor in Swansea, Wales ranged up to a maximum of 140,000 particles cm-3. The larger particles exhibited a greater variety of morphologies (and consequently particle types) and associated metals.

Hays et al. (2010) collected 24 hour PM samples (in July–August 2006), 20m from an interstate in N Carolina with a traffic flow of 125,000 vehicles/day, the majority of which were light-duty gasoline passenger vehicles. The overall near-highway PM mass size distribution was trimodal with a major accumulation mode peak at 500–800 -3 nm. PM mass levels reflected daily traffic activity. Concentrations of PM10, PM2.5, and PM0.1 were 33 ± 7.5μg m , -3 -3 29 ± 6.8 μg m and 1.4 ± 0.3μg m , respectively. Hazardous metals were concentrated in the PM0.1 fraction. In a

Californian study of roadside particle concentrations, PM0.18 was found to be dominated by diesel fuel and motor oil combustion products while PM0.1 was dominated by diesel fuel and gasoline fuel combustion products (Riddle et al, 2008).

There are limited data that suggests that the size distribution of particles originating from vehicle exhausts evolves with distance from source. A study of particle size distributions conducted in London showed distinct differences between a roadside (Marylebone Road), urban background (Regents Park) and elevated locations (BT Tower). The size distribution of particles from the BT Tower was depleted in the smallest particles relative to the other two locations whereas concentrations of the smallest particles were relatively elevated in Regents Park (Dall’Osto et al, 2010; Figure 2.13). Measurements made during winter at a roadside site in Kawasaki City, Japan showed a sharp peak in nucleation-mode particles with a modal diameter of around 0.020μm that was not observed at a background site 200m away (Fushimi et al (2008). Carbon analysis suggested that diesel exhaust particles contributed to both the roadside and background particles in the 0.030–0.060μm size range. Organic analysis of the 0.030–0.060μm particles suggested that lubricating oil from vehicles affected the organic composition of both the roadside and background particles, and that C33 n-alkane and more volatile organic compounds partially evaporated in the atmosphere following the emission of the particles from diesel vehicles. The authors suggested that the absence of nuclei-mode particles at the background site was due to evaporation of the constituents (or possibly coagulation with pre-existing particles after shrinking by partial evaporation).

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Figure 2.13 Average particle size distributions (mobility diameter, nm) at Marylebone Road, Regents Park and BT Tower (London)

A small number of European studies have demonstrated that a significant proportion of UFPs in ambient air are of secondary origin. Pakkanen et al (2001) compared concentrations of PM0.1 at an urban and at a rural site in the Helsinki area in 10 pairs of samples. The average mass concentration was higher at the rural site (520 ngm-3) than at the urban site (490 ngm-3) whereas the average composition was similar. The most abundant of the measured components were sulphate (32 and 40 ngm-3 for the urban and rural sites, respectively), ammonium (22 and 25 ngm-3), nitrate (4 and 11 ngm-3) and the Ca2+ ion (5 and 7 ngm-3). It was estimated that the amounts of water and carbonaceous material in particulate matter were about 10% (50 ngm-3) and 70% (350 ngm-3) respectively at both sites. Average mass mean mode diameters were between about 0.06 and 0.12 μm. The average contribution of ultrafine mass to the fine particle mass (PM2.5) was about 7% at the urban site and 8.5% at the rural site.

Fernández-Camacho et al (2010) report concentrations of UFPs measured in ambient air at a university campus at Huelva in south-west Spain measured using an ultafine condensation particle counter that detects particles greater than 2.5 nm in size and has a 50% counting efficiency for particles between 3 and 4 nm. Typical concentrations were about 22,000 particles cm-3 which was reported to be within the range for other urban background sites (about 20,000 particles cm-2 in Santa Curz de Tenerife city and 22,000 in Pittsburg) and lower than recorded in street canyons and road traffic sites (about 64,000 cm-3 in Leipzig and 170,000 cm-3 in Birmingham). Fernández- Camacho et al (2010) identified two prominent processes contributing to ultrafine particle concentrations: vehicle exhaust emissions and new particle formation due to photo-chemical activity. The highest ultrafine particle concentrations were recorded during the 11:00–17:00 h period, under the sea breeze regime, when rates of secondary particle formation were greatest and it was estimated that about 80% of the particles were linked to sulphur dioxide emissions. The average overall contribution of secondary particles to total ultrafine particle concentrations was greater than 60%. They noted that similar effects had been reported in two other studies of areas of south-west Europe affected by sea breezes.

Lin et al (2009) reported that average (mass) cumulative fraction of secondary inorganic aerosols 2− − + (SO4 +NO3 +NH4 ) in PM0.01–0.056 or PM0.01–0.1 in roadside samples was three to four times that at a rural site. At

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− 2- both sites (particularly the roadside), evidence was found of NO3 /SO4 deposition (from NO2/SO2 transformation − 2− or NO3 /SO4 deposition) in the NP fraction.

Wang et al (2010) reported a daily average particle total number concentration of 19,000 cm-3 for particles between 4 and 70 nm at a location near Rome during October and November, 2007. Concentrations on workdays were about 1.3 times higher than the values on the weekends. The number concentrations of particles with diameter between

30 and 70 nm were closely correlated to NOx and relative humidity, while the number concentrations of particles between 4 and 30 or 4 and 70 nm were correlated with solar radiation, temperature and wind speed.

Several US studies have highlighted the importance of vehicle emissions and secondary particle formation in determining NP concentrations in ambient air. Moore et al (2007) undertook a summer air quality monitoring campaign focusing on the evolution of UFPs (<180 nm in diameter) concentrations at a site believed to be representative of the Los Angeles urban environment. During the morning, UFP concentrations appeared to be strongly influenced by emissions from commuter traffic whereas during the afternoon secondary photochemical reactions appeared to be the predominant formation mechanism of UFPs. The UFP number concentration peak occurred in the early afternoon.

In an investigation of secondary particle formation, Qian et al (2007) undertook continuous measurements of aerosol size distributions (3 nm–2 μm) over a 26 month period (1 April 2001–31 May 2003) in urban East St. Louis. Regional nucleation events were observed more frequently in summer months (36±13% of days) than in winter (8±7% of days), and nucleated particles grew faster in the summer (6.7±4.8 nm h−1) than in winter (1.8±1.9 nm h−1). The daily maximum in the number concentration of UFPs formed by nucleation (4.8±3.5×104 cm−3) and maximum daily rates of 3 nm particle production (17±20 cm−3 s−1) were highly variable and showed no clear seasonal dependence. Particle formation increased particle concentrations by an average factor of 3.1±2.8. Particle formation rates were typically highest between 08:00–09:00 but particle production sometimes persisted at diminishing rates until late in the afternoon (15:00–16:00).

In a study of a severe winter pollution episode in California, Kellman et al (2009) determined that concentrations of -3 -3 elemental carbon in the PM0.1 size range ranged from 0.03 ugm during the daytime to 0.18 ugm during the night time. The main sources were gasoline fuel, diesel fuel, and lubricating oil combustion products with relatively minor contributions from biomass combustion and meat cooking. Concentrations of organic carbon in the PM0.1 size range ranged from 0.2 ugm-3 during the daytime to 0.8 ugm-3 during the night time. Wood combustion was found to be the largest source with a significant component from meat cooking with minor contributions from gasoline fuel, diesel fuel, and lubricating oil combustion products. In an earlier study of severe wintertime pollution at the same location, Herner et al (2005) reported that airborne PM0.18 concentrations at the most heavily polluted site increased from 20 to 172 ugm-3 during the episode with most of the mass being ammonium nitrate forming from an excess of gas-phase ammonia. Daytime concentrations of PM0.18 were approximately 50% lower than night time concentrations. Peak PM0.1 concentrations (8-12 hr average) were approximately 2.4 ugm-3. PM0.1 concentrations did not accumulate during the multiweek stagnation period but decreased as PM0.18 mass was increasing. Most of the ultrafine particle mass was associated with carbonaceous material.

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Due to the transport of emissions from source, secondary particles formed from anthropogenic emissions are important at rural locations remote from the original emissions source but secondary particle formation also occurs at remote rural locations as a result of natural vapour emissions. There has been some investigation of the role of natural emissions of biogenic vapours from forestry and in coastal locations in triggering secondary particle nucleation and growth (e.g. Lehtipalo et al., 2010). The formation of secondary particles in rural locations will not however have a major impact on population mean exposure to secondary particles because of the relatively small numbers of people present in these areas in comparison to urban areas.

In conclusion:

• Published measurement data provides limited information about population exposure to NMs/UFPs in ambient air and no information about potential exposure to engineered NMs.

• Personal exposure to NMs/UFPs is likely to differ from concentrations measured at fixed locations.

• Particle size distributions and concentrations of NMs/UFPs evolve with distance from source and are influenced by the formation of secondary particles.

• It seems likely that population exposure to NMs/UFPs in ambient air is dominated by primary and secondary particles originating from traffic emissions.

• Much of the available information is from surveys undertaken a number of years ago and/or outside of the EU. Both emissions sources and climate are likely to differ from current conditions in the EU, particularly for studies undertaken in the US. It is unclear how relevant the findings of the published studies are to understanding current and future particle concentrations in EU cities.

• The limited measurement data suggest that typical long-term mass concentrations of PM0.1 in ambient air are likely to be less than about 1-2µgm-3 but may be higher in some locations with particularly high levels of traffic pollution (which is an important source of NPs) particularly where there is significant secondary particle formation. Relatively high concentrations of secondary particles may also arise at remote rural locations but the low population density at these locations means that the impact on population mean exposure is relatively small.

• Particle number counts suggest that typical particle concentrations in urban background locations in Europe are about 20,000 – 30,000 particles cm-3 and considerably higher at some roadside locations (>100,000 particles cm-3). Concentrations at rural locations are highly variable, depending on the extent of secondary particle formation.

• The typical relationships between exposure concentrations of UFPs/NMs and more widely measured metrics of PM exposure – PM10 and PM2.5 – in EU cities or rural areas have not been established, nor is it known how these relationships may vary across the EU.

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2.9.3 Estimated human exposure to NMs and UFPs

Approach

The available measurement data are insufficient for the purposes of estimating mean levels of exposure to NMs and UFPs in ambient air in the EU. In the absence of other information, it was decided to estimate exposures to UFPs as

PM0.1 on the basis of published estimates of population mean exposure to PM10 in EU urban areas (conurbations of

>250,000 inhabitants). It was considered that this would be representative of the exposure to PM10 for the majority of EU citizens as only a small proportion of the population live in rural areas. Estimated exposures to UFPs by source were calculated on the basis of the mass contribution of each type of source to total emissions of PM10 and

PM0.1 across the EU27 (Table 2.4). This represents a considerable approximation as the fates of particles within the

PM0.1 and larger size fractions in PM10 are likely to vary as a function of size, composition and nature of the source combined with the proximity of the source (see the discussion of uncertainty below and Section 2.8 on processes affecting UFPs in the atmosphere). Emissions from elevated stacks affect ground level concentrations over a wide area but are a relatively small influence on ground level concentrations at any location. Vehicle emissions have a disproportionately greater impact on ground level concentrations in urban areas in relation to the total particle masses emitted.

Estimated exposure

Population-weighted mean concentrations of PM10 in EU cities (conurbations with >250,000 inhabitants) ranged between 26 and 31µgm-3 as annual averages across the EU between 1999 and 2008 (EEA State of the Environment Report 2010). Estimated population mean concentrations of UFPs from different sources derived based on the emissions estimates developed during the study are shown in Table 2.12. As a first estimate, population mean -3 exposure to UFPs in ambient air from all sources (as PM0.1) may be about 3 µgm (as an annual mean; based on the ratio of total estimated emissions of PM10 to PM0.1). The exposures are estimated in terms of gravimetric mass in line with the source data underlying the estimates. For the purposes of comparison with the measurement data which is primarily in the form of particle number counts, for particles of unit density and a diameter of 100 nm, a concentration of 1µgm-3 would be equivalent to a particle number count of approximately 1,900 particles cm-3 or for particles of about 60 nm (approximately the modal size of particles measured at UK sites) about 9,000 particles cm-3. This suggests that concentrations expressed as particle number counts might be of the order of 6,000-35,000 -3 particles cm if most of the PM0.1 fraction is in the 60-100 nm size range. These estimated exposure levels are of the same order of magnitude as indicated by the limited measurement data.

The estimated exposure to PM0.1 may be an under-estimate if the lifetime of PM0.1 particles in air is longer than that of larger particles due to the greater susceptibility of larger particles to deposition. Equally particles in the PM0.1 size range may grow by aggregation and thus be removed from the PM0.1 size fraction or if particles are largely much less than 0.1 µm in diameter, they may be as susceptible to deposition as coarser elements of PM10 (see section 2.8). It is very difficult to judge how the ratio of PM0.1 to PM10 might evolve during transport from source and it is likely that the pattern of evolution will be partly depend on source type as well as local atmospheric conditions.

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It is difficult to judge how the UFP from different sources are likely to contribute to overall exposure. It is likely that exposure to UFPs from transport sources is larger than shown in the table below because of high levels of traffic emissions in densely populated areas. In contrast, emissions from large combustion plants may have a disproportionately small impact on exposure because emissions are usually emitted from tall stacks and dispersed over large areas that are largely rural in nature (because of the greater proportion of landmass is rural rather than urban).

Table 2.12 Estimated population mean exposure concentrations by source for PM0.1 and PM10 based on emissions estimates for the EU27 in 2008 (developed as part of this study); 1 ngm-3 = 0.001 ugm-3

PM0.1 PM10 PM0.1:PM10 Population mean concentration -3 emissions emissions of PM0.1 ngm

-3 -3 Kt Kt ratio PM10 = 26 ugm PM10 = 31 ugm

Power Generation 10 119 8% 79.0 106.3

Industrial Combustion 33 197 17% 260.6 350.9

Residential and Commercial 41 589 7% 323.8 435.9

Road Transport 93 290 32% 734.5 988.8

Other transport and mobile machinery 59 225 26% 466.0 627.3

Industrial Processes 12 269 4% 94.8 127.6

Agriculture 22 262 8% 173.8 233.9

Other (Note 1) 0.01 142 0.01% 0.1 0.1

TOTAL anthropogenic 271 2,092 13% 2140.3 2881.2

Non anthropogenic (highly uncertain) 7 1,200 1% 55.3 74.4

TOTAL 278 3,292 8% 2195.6 2955.7

Note 1: Includes open burning of waste, cigarette smoking, flaring in the oil and gas industry and barbeques

NMs and UFPs in ambient air are dominantly of combustion origin with a very small proportion of particles in these size ranges originating from other particulate emissions and natural sources. There are no readily available estimates of current and potential emissions of engineered NMs to the atmosphere. Given that these are relatively valuable specialist materials, manufactured in modern plants, mass emissions of engineered NMs to the atmosphere would be expected to be exceedingly small compared to emissions from combustion plant, transport, other combustion sources and traditional industrial sources. Whereas emissions of NMs from these sources are of the order of kilotonnes across the EU, given that total emissions of PM0.1 from industrial sources (as opposed to combustion sources, agriculture or natural sources) account for less than 5% of emissions of PM0.1, emissions of engineered NMs are likely to account for less than 1-2% of PM0.1 from “industrial” sources (assuming that a proportion of PM0.1 from industrial sources is emitted as the fine fraction of coarser dusts rather than from processes creating or employing engineered NPs). This would imply that population mean exposure to engineered

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NMs in ambient air is likely to be less than about 1-3 ngm-3, and may be very much less than this value. Population exposure to engineered NMs is likely to be dominated by NMs in consumer products with exposure occurring predominantly by the dermal route. In terms of assessing the potential risks to human health arising as a direct consequence of exposure to engineered NMs, exposure to engineered NMs in ambient air is likely to represent an extremely small proportion of any potential future health burden. Similarly in considering the health impacts of exposure to NMs in ambient air, engineered NMs are likely to contribute to <0.12% of total exposure and associated impact. The health impact as a proportion of total impact of atmospheric NMs may be even smaller because the relative harmfulness of particles of combustion origin compared with many (but not all) engineered NMs, arising from their leachable metals content (Topics 10 and 11).

2.9.4 Uncertainties in exposure estimates

Population mean exposure to PM from different sources in ambient air is not in direct proportion to the contribution that each source makes to total EU emissions. Similarly the proportions of PM10, PM2.5, UFP and NMs in emissions are likely to differ from those in population-weighted mean concentrations in ambient air because of the differing atmospheric fates of each size fraction, as a function of both size and chemistry.

Projects such as the EURODELTA modelling comparison exercise have played an important role in developing an understanding of how population exposure to PM10 and PM2.5 in Europe is related to emissions of pollutants from different sources. These initiatives have not specifically considered population exposure to UFPs/NMs to date. Key findings that are relevant to the estimation of exposure to UFPs/NMs, however, include the importance of population proximity to source in governing exposure, particularly in relation to vehicle emissions, and the complex relationship between predicted changes in emission levels of particles and gaseous pollutants and impacts on population exposure to PM. Model outputs indicate that reductions in emissions levels do not lead to pro rata reductions in exposure, reductions in emissions from different sectors (eg transport versus power generation) have different impacts on exposure and predicted reductions in exposure for a given reduction in emissions vary by location within the EU (Thunis et al., 2008)26.

Overall, it is clear that there are considerable uncertainties in the estimated exposures to PM0.1 presented in Table 2.12.

2.9.5 Gaps in knowledge and possible future research areas

There are few measurement data describing the exposure of the EU population to NMs/UFPs in ambient air in urban or rural areas. Measurement and modelling studies of PM exposure have focused on PM2.5 and PM10. Future work that would increase our understanding of population exposure to NMs/UFPs includes:

26 http://aqm.jrc.ec.europa.eu/eurodelta/publications/EDII_finalreport.pdf

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• The acquisition of measurement data to enable better characterisation of exposure of the EU population to NMs/UFPs; and

• The combination of measurement and modelling studies to better understand the link between emission sources and exposure to UFPs and NMs.

Emissions of primary and secondary UFPs/NMs from different sources are likely to be associated with differing levels of risk to human health and the environment. For the purposes of future risk assessment, it will be important to not only quantify exposure in terms of particle mass and number, but also in terms of source apportionment and the related impact on particle properties (e.g. size and composition).

2.10 Topic 10: Risk assessments of NMs and UFPs

2.10.1 Information sources and data availability

The information summarised below was derived from earlier work undertaken by IOM in collaboration with other organisations, particularly the ENRES (2009) review. In addition, PubMed, a free-to-access on line database of the peer-reviewed medical literature maintained by the US National Institute of Health was used to identify relevant articles published in the peer reviewed literature during 2009-10 that would not have been captured by the ENRES review.

No epidemiological studies have been undertaken to investigate the effects of engineered NMs/UFPs in ambient air on human health. There have been a large number of studies of the effects of PM10 and PM2.5 and a small number of studies of the specific effects of particles smaller than PM2.5. There has been limited investigation of the health effects of NM exposure in the workplace. There are no relevant data describing the toxicity of engineered NMs with differing properties in humans. A number of epidemiological studies have attempted to determine which size fraction of PM10 and which PM components are most harmful to health. There have been a limited number of investigations of the effects of experimental exposure to particles of ambient origin and of diesel particulate in humans but no comparable studies of the effects of NMs.

There has been extensive investigation of the toxicity of engineered NMs and UFPs in animals and cellular systems and also of the toxicity of PM10/PM2.5 but few comparative studies. It is difficult to compare toxicity across studies because of differences in the materials used and experimental protocols. Small differences in particle size, differences in preparation method and differences in particle aggregation resulting from differences in experimental media and conditions may affect particle toxicity and limits cross study comparison (ENRES, 2009). Differences in dose metric may also limit comparison.

There have been a limited number of investigations of the role of particle size and composition in determining the toxicity of NMs and UFPs in animals and a large number of in vitro investigations.

Further details are provided in Appendix A5.

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2.10.2 Toxicological investigations of toxicity of NMs and UFPs relative to toxicity of PM10/PM2.5

The major components of PM in ambient air are transition metals, ions (sulphate, nitrate), organic compound, stable radicals of carbonaceous material, minerals, reactive gases, and materials of biologic origin. The UFP component is largely derived from combustion and is composed predominantly of carbon with small quantities of transition metals and organic compounds including polyaromatic hydrocarbons (PAHs). Combustion emissions include carbon nanotubes (CNT) similar to engineered CNT.

The results of the relatively small number of experimental investigations of the effects of exposures of humans to ambient particles or diesel particulate have demonstrated effects on cardiovascular and respiratory parameters consistent with the observed effects of PM in ambient air reported in epidemiological studies (ENRES, 2009). Other experimental data suggest that metal oxide fumes of differing composition have different potentials to induce pulmonary and systemic inflammation in humans (ENRES, 2009).

A large number of experiments in animals have demonstrated that particles of widely ranging composition can give rise to dose-related pulmonary inflammation and raised levels of markers of oxidative stress. Oxidative stress has been observed following exposure of animals to ambient PM (Donaldson et al., 2005) and a range of engineered NMs including metal oxides, metals and CNTs (Hoet and Boczkowski, 2008). The potential importance of transition metal content, particularly the leachable or surface metal content in the production of reactive oxygen species has been highlighted by several reviews (Donaldson et al, 2005; Valavanidis et al, 2008; Hoet and Boczkowski, 2008). It has been widely suggested that leachable metals may make an important contribution to the toxicity of ambient PM in cellular and animal assays (e.g. Donaldson et al, 2005).

Although most experiments with ambient PM have focussed on respiratory outcomes, there are also data which show that exposure of rodents to ambient PM under experimental conditions can give rise to wider systemic effects, specifically cardiovascular morbidity, consistent with observed effects in epidemiological studies of humans (Lippmann and Chen, 2009). There are limited data suggesting that inhalation exposure to some types of metal oxide NM can lead to systemic effects (ENRES, 2009), but no direct comparisons with ambient PM are available.

A number of authors have demonstrated that exposure of animals to specific types of NMs including TiO2 (Wang et al (2008), MnO2 (a known neurotoxin; Oszlánczi et al, 2010; Sarkozi et al, 2009) and Ag (25 nm; Rahman et al,

2009) can give rise to markers of neurotoxic effects. With both the MnO2 and Ag, however, effects could have been due to the dissolved metal rather than translocation of NPs to the brain. There are also very limited data suggesting that inhalation exposure to diesel fume, an important component of ambient PM, may impact on neurological function (Win-Shwe et al, 2008; 2010).

The outcomes of in vitro studies confirm the importance of available metal content in determining the toxic potential of ambient and engineered NPs, although metals do not fully account for observed effects. Different metals and metals in different oxidation states appear to have differing potentials to cause inflammation (Hoet and Boczkowski, 2008). This may imply that NPs with limited potential to release metals may be less toxic than

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ambient PM provided that other factors such as shape and size were comparable (see sections 3.10.4 and 3.10.5 below).

2.10.3 Epidemiological investigations of the effects of UFPs in ambient air and comparisons with PM10/PM2.5

The results of epidemiological studies provide some information about the relative harmfulness of different size fractions in ambient PM but do not provide information that allows a direct comparison between the effects of ambient PM and engineered NPs.

The results of studies of ambient PM suggest that mortality and cardiovascular effects are more strongly associated with PM2.5 than with larger particles in the PM10 size range (e.g. Mar et al, 2000; Schwartz et al, 1996; 1999; review by COMEAP, 2009) which may be more strongly associated with respiratory effects such as chronic obstructive pulmonary disease, asthma and respiratory hospital admissions (see review by Brunekreef and Fosberg, 2005).

There are limited epidemiological data that suggest that PM1 and smaller particles are more harmful than coarser particles within the PM2.5 size range (e.g. Stolzel et al, 2007; Halonen et al, 2009), but the association of particles with adverse effects is not confined to the smallest size classes (Brunekreef and Fosberg, 2005). There are inconsistencies in the findings of different epidemiological studies and some investigators have found stronger associations between the coarser fraction of PM10 and cardiovascular parameters than for PM2.5 (e.g. Lipsett et al, 2006) and other investigators have found a stronger relationship between UFP and respiratory parameters than for coarser particles (e.g. Peters et al, 1997; Mosshammer et al, 2006).

Epidemiological studies of the effects of workplace exposure to fine particles have demonstrated adverse respiratory effects with a range of material types as well as other systemic effects specific to particular particle types. Studies in carbon-black workers found no evidence of an excess mortality risk and no proven link with lung cancer. There was evidence of an increased risk of respiratory illness but it is difficult to make a direct comparison with ambient PM. Exposure to 1,000µgm-3 in the workplace (equivalent to a time averaged exposure of 173µgm-3 for continuous exposure in the wider environment) was associated with an increase in the risk of respiratory illness between 30 and 80% (ENRES, 2009). A number of studies in children and adults exposed to PM10 in ambient air -3 have reported that a 10µgm increase in concentrations of PM10 is associated with an increase in risk of respiratory symptoms of differing severity of between about 30 and 50% (Schwartz and Neas, 2000; Schikowski et al, 2005; Bayer-Oglesby et al, 2005; Zemp et al, 1999). The results of a single study undertaken by Hrubá et al, (2001) in Slovakia suggest that ambient PM may have a considerably greater effect on children’s health (with an over three- fold increase in symptoms for a 15µgm-3 increment in total PM concentration), but it is uncertain whether the nature of the exposure to particles and other air pollutants was comparable with current exposures within typical

EU urban areas. Studies in TiO2 workers showed limited evidence for adverse respiratory effects but the TiO2 in workplace air was likely to have been present as aggregates and the findings were likely to be of limited relevance to predicting the potential impacts of NMs. The development of metal fume fever following short term exposure to very high concentrations of NMs as ZnO fume or welding fumes is well established (Antonini et al, 2003). Symptoms include breathing difficulties and fever and although metal fume fever is occasionally fatal, complete

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recovery is more a more common outcome. Long term exposure to metal oxide or metal fumes can give rise to respiratory illness and disease outcomes such as neurotoxicity or kidney disease that are dependent on the type of metal involved. Effects such as metal fume fever are specifically associated with high levels of exposure and are unlikely to be predictive of potential impacts following long term exposure to much lower particle levels. Whereas adverse effects on cardiovascular health appear to be an important outcome following exposure to ambient PM, cardiovascular health effects have not been highlighted by workplace studies of the effects of particle exposure. This may reflect the very different exposure regime with very much greater levels of particle deposition in the respiratory system and/or differences in the exposed population.

Overall, given that particle health effects appear to be related to size and composition as well as dose, it seems likely that the relative harmfulness of engineered NPs in relation to ambient PM varies by particle type. In general terms harmfulness would appear to generally increase as a function of mass concentration. Decreasing particle size for a given particle type and the bioavailability of different metals also appears to be important, particularly those able to participate in redox reactions that can contribute to oxidative stress. There are insufficient data to determine the impacts of particle size and composition on health risk in relation to dose expressed in terms of particle number or surface area.

2.10.4 Relationship between particle size and potency and effects

The outcomes of epidemiological studies suggest that the health effects associated with exposure to particles in ambient air differ for different size fractions as described above. However, given that the composition of different size fractions of ambient PM varies, it is difficult to separate the effects of size versus those of composition. For the purposes of comparison of toxic potency, it is also uncertain whether mass is the most appropriate dose metric for the finest size fractions. There are limited data that suggest PM1 may have a greater impact on cardiovascular function in humans per unit mass than PM2.5 or PM10 (eg Halonen et al, 2009; Stozel et al, 2007; Breitmer et al,

2009). There are even more limited data that suggest that PM1 is more strongly associated with impacts on respiratory health than PM2.5 or PM10 (Moshammer et al, 2006; Peters et al, 1997), although many other studies have demonstrated adverse effects on respiratory health associated with the coarser fractions of PM (see review Brunekreef and Fosberg, 2005).

A number of studies in animals have demonstrated that nano-sized particles are relatively more toxic than micro- sized particles of TiO2 when dose is expressed in terms of mass (eg Sager et al, 2008; Kobayashi et al, 2009) and similar effects have also been demonstrated with Ni oxide (Ogami et al, 2009) and fullerenes (Baker et al, 2008). For some particle types, the increase in potency with decreasing size may simply reflect the importance of particle surface area (or number) as a determinant of effects and particles of differing size have similar potencies when dose is expressed in terms of surface area. Sager et al (2008), for example, reported that when doses were equalized based on surface area of particles delivered, UFPs of TiO2 were only slightly more inflammogenic and cytotoxic than the fine sized particles following intratracheal instillation in rats. Other experimental data show less consistent results with mineral structure and particle surface properties having an important influence on toxicity. Warheit et al (2006), for example, reported the pulmonary effects of nanoscale TiO2 in the form of anatase were not

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significantly different 24 hours after intratracheal instillation in rats than those observed with larger particles of

TiO2 as rutile (although whether effects would have been similar over longer time periods more relevant to human exposure in ambient air is unclear). One source of uncertainty in the interpretation of the results of experimental studies with NPs is the degree of particle dispersion achieved at the time of dosing and the impact of agglomeration on toxicity. There are limited data that suggest that agglomerates/aggregates of NMs may be more toxic than similarly sized agglomerates/aggregates of larger particles (ENRES, 2009). A small number of studies have demonstrated that particles of a specific size are more toxic than larger of smaller particles. In the case of gold in the form of Au55 clusters, for example, this has been attributed to the ease with particles can interact with DNA (Schmid, 2008).

There has been limited investigation in experimental systems of the role of particle size in the toxicity of ambient

PM2.5/PM10, although recent reviews have identified particle size and surface area as important influences on the toxicity of combustion-derived particles (Donaldson et al., 2005; BéruBé et al, 2007; Stoeger et al, 2009; Valavanidis et al, 2008). Some of the apparent size related differences in the toxicity of ambient PM could be explicable in terms of leachable metal content rather than size (eg Jeng, 2010; Cho et al, 2005).

There are limited data from experiments in animals and cellular systems that particle size affects rates of cellular uptake and transfer to systemic circulation with smaller particles being more readily translocated than larger particles (eg Sarlo et al, 2009). This is likely to contribute to greater levels of toxicity.

Particle shape may significantly modify the relationship between particle size and effects. Particular concerns have been expressed in relation to the potential harmfulness of High Aspect Ratio Nanoparticles (HARNs) based on previous experience of the harmfulness of inhaled asbestos and other fibres. The toxicity of fibres is determined by diameter, length and persistence in the lung. Fibres must be thin enough to penetrate to the gas-exchange region of the lung and their length determines whether they can be cleared by normal cellular processes. The failure of normal cellular clearance triggers a range of inflammatory processes. The persistence of fibres in the lung leads to a prolonged inflammatory response that results in the development of abnormal tissue and eventually lead to cancers. Carbon nanotubes (CNT) have features of both NM and conventional fibres including asbestos and cause oxidative stress and inflammation that are both precursors to disease. Not all experiments with CNTs have generated results consistent with a high level of toxicity and the most recent authoritative reviews have concluded that existing experimental data do not provide a definitive comparison of the toxicity of CNTs and asbestos (Donaldson et al, 2006; Tran et al, 2008).

2.10.5 The relative importance of particle size, particle composition and surface reactivity in determining toxicity

There have been a number of epidemiological studies that have investigated the relationship between particle composition in ambient air and adverse effects. Epidemiological studies have confirmed the importance of combustion-generated particles in giving rise to effects, particularly those associated with traffic emissions (eg Yue et al, 2007; Cakmak et al, 2009). Most studies have reported that soil-derived particles are associated with lower risks to health than combustion-generated particles (eg Mar et al, 2000; Cakmak et al, 2009). Although secondary

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particles such as sulphate and nitrate would be expected to have a low toxicity on the basis of experimental findings (Schlesinger, 2007), this has not been confirmed by epidemiological investigations. Atkinson et al (2010), for example, reported that secondary pollutants, particularly secondary PM2.5, nitrate and sulphate, had significant impacts on emergency hospital admissions and mortality due to respiratory causes in a study in London and Mar et al (2006) found a significant association between secondary sulphate and cardiovascular mortality. It is possible that these salts act as important carriers of more toxic pollutants such as PAHs. There are also limited data, however, that link salt of marine origin to increased mortality risk (Mar et al, 2006) and data linking exposure to volcanic ash in the PM10 size range to adverse respiratory effects (Gordian et al, 1996). It is possible that the volcanic ash was associated with respiratory irritants such as sulphuric acid.

The results of animal experiments suggest that the availability of particular types of metals such as Ni or Cd may play an important role in the toxicity of some NMs (eg Jacobsen et al, 2009; Fujita et al, 2009) and also indicate that surface properties are likely to play a key role in determining particle toxicity (Warheit et al, 2007).

A large number of in vitro investigations have demonstrated the importance of NM composition in determining NM toxicity and a proportion of these studies have also investigated the influence of particle size. Different cell types respond differently to different NMs and this may limit the extent to which it is possible to compare the findings of different investigations that have used different NMs, cell lines and investigated different endpoints. There is some evidence linking NM toxicity to leachable metals, particularly those that can be oxidized, reduced or dissolved (Auffan, 2009). There is also evidence that the toxicity of NMs can be substantially modified by surface coatings or other treatments leading to a modification of surface properties (ENRES, 2009; findings of more recent studies including Studer et al, 2010; Yin et al, 2010).

2.10.6 Sources of uncertainty

Sources of uncertainty in the prediction of the health effects of NMs/UFPs in humans include:

• The paucity of studies of the effects of NMs in humans.

• The marked inconsistencies in the findings of epidemiological studies of the effects of ambient particles in different size fractions that reflect the very complex range of factors that affect the health of exposed populations. In addition, the particle mix in ambient air is highly variable and co-exists with a range of gaseous pollutants that may also affect health.

• The lack of standardisation of test protocols and uncertainty about the most appropriate dose metric limits interstudy comparison and the assessment of the role of particle size and composition in determining the toxic effects of NMs in animal and cellular test systems.

• In experimental investigations of particle size effects in animals and cell systems, it is difficult to be certain that particles of different sizes differ only in size as they may also have different surface properties and internal structures.

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• The description of the materials used in many studies is not sufficient to determine whether an apparent increase in toxicity with smaller particle size when doses are expressed in units of mass might disappear if dose is rescaled to particle number or surface area.

• The extent to which laboratory experiments using well characterised NMs are predictive of effects associated with NMs in ambient air.

• While in vitro screening tests provide a useful tool for screening NM toxicity, they are not necessarily predictive of effects in animals or humans.

2.10.7 Conclusions

The following conclusions can be made from the review of available literature:

• There are insufficient data to allow comparison of the effects of engineered NMs and UFPs and ambient PM10/PM2.5 in humans.

• Experimental data suggest ambient PM may be disproportionately harmful in comparison to some types of chemically inert NP because of the presence of leachable metals and toxic organic substances that confer a significant potential to generate oxidative stress within the respiratory system.

• Other types of metallic and metallic oxide NMs may have a greater toxicity than that of ambient PM but there are few comparative data. Some metal and metal oxide NMs such as manganese which is a potent neurotoxin may be particularly harmful.

• The toxicity of many types of particulate material appears to be size dependent although differences in internal structure and surface properties may limit the extent of comparison between different size fractions.

• The results of a number of experimental investigations suggest that toxicity generally increases with decreasing particle size when doses are expressed in units of mass but not all studies have found clear relationships between size and potency.

• There is less evidence that toxicity increases with decreasing size when doses are expressed as particle numbers or surface area. There are insufficient data to exclude the possibility that smaller particles are more toxic than larger particles.

• There are growing epidemiological data that suggest that there are differences in the health effects associated with different size fractions of ambient PM.

• Some particle types may show particularly high toxicity at a specific particle size, for example, particles of a particular size may interact with DNA.

• Based on experience with asbestos and various man-made fibre types, particles with a high aspect ratio such as CNTs may be potentially more toxic than other particles of similar composition and aerodynamic size, although there are experimental data indicating the CNTs may be harmful, there are insufficient data to enable a definitive comparison with asbestos at this time.

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• NM/UFP composition is an important influence on toxicity with leachable metals appearing to be of particular importance in giving rise to adverse effects.

• NM/UFP toxicity may be substantially altered through modification of their surface properties leading to uncertainties in the relevance of the findings of laboratory investigations to NMs/UFPs in ambient air.

2.10.8 Gaps in knowledge and possible future research areas

There are a number of gaps in knowledge that limit the extent to which the human health effects of exposure to UFPs/NMs in ambient air can be predicted:

• The extent to which the differing health effects associated with differing size fractions of ambient PM are due to differences in particle composition versus differences in particle size;

• The relationship between particle size and toxicity when dose is expressed in terms of surface area or particle number, rather than mass;

• The impacts of particle aggregation on relative harmfulness and the differences in particle aggregation between different experimental studies and real life exposures;

• The extent to which NM toxicity in ambient air is likely to be modified as a result of modification of their surface properties;

• The relative toxicity of CNTs in comparison to asbestos fibre; and

• The relevance of experimental findings with NMs in a laboratory system to prediction of the effects of ambient PM exposure, including UFPs/NMs in humans.

More experimental data would help to better understand:

• The role of particle aggregation in modifying toxicity;

• The effects of absorption of species typically present in ambient air on particle toxicity;

• The relationship between particle size, shape and composition and toxicity, particularly in relation to ambient PM; and

• The relative toxicity of different types of widely used NMs in relation to different fractions of ambient PM.

More epidemiological data would help to better understand:

• The differences in potency and effects associated with different fractions of ambient PM and to better separate the effects of size versus composition; and

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• The relationship between potency and particle size when dose is expressed in metrics of surface area or particle number count as opposed to mass.

2.11 Topic 11: Impact of NMs and UFPs on human health, the environment (ecotoxicity) and relevance to climate forcing (cloud formation and persistence)

2.11.1 Information sources

The information for on health, ecotoxicity and environmental quality impacts was based on the ENRES (2009) review and information available from other EU funded projects that were identified in an internet search. In addition, PubMed was used to identify relevant articles published in the peer reviewed literature during 2009-10 that would not have been captured by the ENRES review. The information about the climatic impacts of NMs was derived from a recent book describing the role of NMs in the water cycle edited by Frimmel and Niessner (2010), the review undertaken by the IPCC (2007), a recent review by Brasseur (2010) and a review presented by Pitaurd at the 2009 Euro Nano Forum. Further information was sought by undertaking internet searches to identify reports and other publications arising from EU funded (FP6 and FP7) climate research listed by DG Research (2009).

Further details are provided in Appendix A6.

2.11.2 Health impacts

Introduction

There are few studies of the impacts of engineered NMs and UFPs on human health and no studies of their impacts following exposure in ambient air. Key sources of information about the likely effects of these materials on health are:

• Studies of the effects of particulate air pollution in exposed populations; and

• Studies of health effects in industries that have traditionally handled fine powders such as carbon black and titanium dioxide pigments and workers exposed to metal fumes.

Findings of studies of effects of ambient particles

Studies of the effects of PM10 in large urban populations have found associations between PM10 and small changes in the daily death rate, the number of hospital admissions for cardiovascular and respiratory illness and increased numbers of GP consultations for respiratory illness (COMEAP, 1998; WHO 2000a). Other studies of selected panels of individuals have shown associations between PM10 and increases in respiratory symptoms, particularly in those with pre-existing respiratory illnesses such as asthma (COMEAP 1998; WHO, 2000a). In addition,

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associations have been found between variations in daily concentrations of PM10 or UFPs and various circulatory parameters that help to substantiate the association with heart disease in addition to respiratory illness (e.g. Gold et al, 2000a). The relationship between particle concentrations and daily death rate is the best established whereas the effects of PM on respiratory symptoms are relatively poorly established. This is because only small numbers of individuals can be studied in investigations of respiratory symptoms and the severity of respiratory symptoms is difficult to quantify. In addition there are a large number of other influences on respiratory health including infections and exposure to allergens which mask the relatively small impact of air pollution. These factors limit the power of epidemiological investigations to detect consistent effects. In contrast, death is an indisputable endpoint and mortality data are available for the entire population of developed countries. Although daily death rate varies in response to a number of variables including weather and seasonal variations in infection rates, the availability of large quantities of data has enabled epidemiological investigations of the effects of air pollution to take account of the wide range of confounding factors that influence death rate.

The effects of long term exposure to air pollution are more difficult to quantify than those associated with changes in daily concentrations of PM10, but are believed to be of greater importance than the effects of individual high pollution events (COMEAP, 2009; 1998; WHO 2005a). Both US and European studies have found an association between lifetime exposure to PM10 and a reduction in life expectancy (COMEAP, 2009). There is a substantial body of evidence linking exposure to PM2.5 to nonfatal adverse cardiovascular effects. Long term exposure to

PM2.5 is also associated with an increased risk of respiratory cancers (COMEAP, 2009) and the development of bronchitis (Abbey et al, 1999).

Workplace studies

Studies of workers with long term exposure to carbon black or titanium dioxide have found limited evidence of respiratory effects (section 10.3.3 above). Short term high exposures to metal fume can give rise to metal fume fever and long term exposure to metal oxide or metal fumes can give rise to respiratory illness and disease outcomes such as neurotoxicity or kidney disease that are dependent on the type of metal involved.

Inferred health effects associated with exposure to engineered nanoparticles

The outcome of studies of the effects of ambient air pollution in human populations and toxicological investigations of the effects of NMs (section 2.10) suggest that exposure to NMs is likely to be harmful to respiratory and cardiovascular health and that the adverse effects of NMs will be partly related to their small size.

As discussed above, there is some evidence that PM2.5 is more strongly associated with cardiovascular impacts and mortality than PM10 and that PM10 is more strongly associated with respiratory impacts than PM2.5 (section 2.10.3).

There is a small amount of epidemiological evidence to suggest that the very fine component of PM2.5 is of disproportionate importance (in terms of mass) in giving rise to observed effects (section 2.10.3). The toxicological data also suggest that particle size is an important influence on NM toxicity (section 2.10.4).

The adverse effects of NMs are unlikely to be solely related to particle size as there is evidence from experimental studies that particle composition and surface properties are important determinants of relative harmfulness and

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some evidence that shape, particularly aspect ratio may also be important (section 2.10.5). There is a small amount of epidemiological evidence and a substantial quantity of experimental evidence that suggests that the availability of soluble metals able to participate in redox reactions may contribute disproportionately to the adverse effects associated with exposure to ambient particles (sections 2.10.2-2.10.5). It seems likely that some engineered NMs such as CNT would have similar impacts to the CNTs in ambient air that originate in combustion emissions. Other materials like TiO2 that have little potential to release soluble metals and have a low toxicity in experimental systems (sections 2.10.3-2.10.5) would be expected to be relatively inert with a similar toxicity to the finest fraction of the soil dust that is present in ambient air. The leachable metal content of materials such as Ag, Cu, Zn and Ni metal NMs and metal oxide NMs and their ability to partake in redox reactions might confer a greater toxicity than that associated with ambient particles. The surface properties of NMs may be modified by residence in ambient air and this may lead to an enhancement or reduction of their potential harmfulness. The adsorption of genotoxic substances such as PAHs may, for example, lead to relatively greater deposition of these substances in the lung than would have occurred in the absence of the NMs.

In conclusion, atmospheric UFPs/NMs are likely to have a disproportionately greater adverse impact on human health than coarser particles within the PM2.5/PM10 size range but the toxicity of PM2.5/PM10 cannot be wholly attributed to the finest fraction. Metals play an important role in enhancing the toxic effects of inhaled particles and the toxicity of UFPs/NMs from different sources with different compositions is likely to be highly variable. The potential health impacts of engineered NMs are likely to vary substantially by particle type for a given level of exposure. The overall impact of releases of engineered NMs to the atmosphere will depend on the exposure levels and the relative abundance of different types of NMs in emissions. Although levels of exposure to engineered NMs in ambient air are currently likely to be substantially smaller than exposures to similarly sized particles generated by other processes including combustion (section 3.9.4), their relative importance in giving rise to adverse health impacts is unclear.

Conclusions

1. The toxic effects of combustion-generated particles (including NMs) are well established and it is likely that some types of engineered NMs such as carbon nanotubes could be similarly damaging to respiratory and cardiovascular health.

2. It is possible that increased levels of NMs would have an adverse impact on human health that would be disproportionately greater than would be predicted on the basis of their mass contribution to airborne particle levels.

3. NMs capable of releasing metals that could contribute to oxidative damage to the respiratory system are likely to be particularly toxic.

4. Not all NMs are likely to equally harmful and materials such as titanium dioxide NMs that have a low leachable metal content may be less damaging to health than combustion-generated particles.

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5. The absorption of other pollutants in ambient air on to the surfaces of NMs may substantially increase their toxicity.

2.11.3 Environmental Impacts

Introduction

There is a paucity of published investigations and measurement data of the impacts of NMs on environmental quality and climate. Some inferences about likely environmental impacts have been based on knowledge of the physics of particle behaviour and the results of experimental studies.

There are extensive published data describing the impacts of NMs on plants and animals in experimental systems but no data describing actual impacts observed in the wider environment.

Effects on air quality

The ENRHES (2009) report highlighted the lack of knowledge about the likely fate of NMs on release to the atmosphere and the early stage of development of predictive models. The ENRHES (2009) report highlighted a number of important factors that will influence NM behaviour in ambient air:

1. Particle diffusion is inversely proportional to particle diameter and NMs would be expected to migrate rapidly from a high concentration to a lower one, leading to rapid dispersion and the potential for NMs to travel long distances.

2. Particle agglomeration rates increase as particle size decreases and NMs tend to agglomerate rapidly, even when present at a low mass concentration. Aged NM aerosols tend to have a particle size distribution that is indistinguishable from ubiquitous background aerosol.

3. Particle deposition rates depend on particle diameter and NMs will be deposited at a much slower rate than larger particles which contributes to the potential for NMs to be transported in air over great distances.

4. Rates of re-suspension of deposited particles are a complex function of various factors including particle size, shape, charge and the energy applied to the particle. There is doubt as to whether deposited NMs are likely to be subject to re-suspension.

The ENRHES report indicates that the atmospheric fate of NMs is an area of active research and therefore it is likely that understanding of the atmospheric behaviour of NM emissions will increase in future years. A more thorough review of the atmospheric behaviour of NMs/UFPs is provided in section 2.8 of this report. NMs/UFPs are highly susceptible to removal from the atmosphere by deposition and are also removed from the fine particle fraction by agglomeration, although this may be a relatively slow process.

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Effects on water quality

There is a lack of measured data describing the behaviour and fate of NMs in natural waters which is likely to be very different from that observed in test systems. Natural waters contain a wide range of substances that may interact with NMs. Possible effects include triggering of NM agglomeration leading to a modification of particle size distributions. The extent of aggregation may dependent on salinity and the salts present in solution and also on the age of the suspension. In contrast, organic matter in aqueous environments can also promote particle dispersion as demonstrated by Yang et al (2009). Other effects include enhanced or reduced NM dissolution. Substances in natural waters may bind to or coat NM surfaces leaving to significant modification of NM surface properties. Adsorption of humic acids for example, may significantly reduce particle toxicity as demonstrated by Mahendra et al (2008).

NMs may as carriers of other types of contaminant in the aqueous environment and/or modify their toxicity. In tests with algae and Daphnids, the presence of C(60)-aggregates increased the toxicity of phenanthrene but reduced the toxicity of pentachlorophenol (Baun et al, 2008).

The following conclusions can be drawn:

• The particle size distribution of NMs in natural waters are likely to be substantially different from that of the original NM material released to the environment;

• Interactions of NM with other substances present in natural waters are likely to lead to a modification of NM toxicity giving rise to toxicities that may be significantly higher or lower than those observed in test systems, depending on the chemical and physical environment; and

• NMs may also substantially modify the toxicity of other dispersed or dissolved substances present in water.

The behaviour of NMs in aqueous systems is likely to be highly dependent on particle properties (size, composition, surface properties, and susceptibility to leaching) and the chemical and physical conditions within the aqueous environment.

Effects on soil quality

There is a lack of data describing the environmental fate and behaviour of NMs in soil. NMs would be expected to adhere to solids within soil and sediment and studies that have investigated the migration of specific NM types through porous media have reported variable degrees of retention of NMs. Soil quality is normally assessed in terms of unit mass of contaminant per kg of soil which is unlikely to be the most relevant measure in terms of NM toxicity to plants and animals. There have been no investigations of the impact on NMs on levels of chemical contamination in soil and little investigation of the potential influence of NMs on soil fertility, nutrient levels, moisture retention or other properties relevant to plant growth. There are some data that suggest that the presence of NMs in soil could have an important impact on soil function through their effects on soil microbial communities. For example, there are limited data that suggest Ag NMs are harmful to nitrifying bacteria (Choi and Hu, 2008) and

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other beneficial soil microbes (Gajjar et al, 2009) and it is possible that NMs may have disproportionately greater adverse impacts on soil fertility than larger particles (on a mass for mass comparison). The importance of any antimicrobial effects of NMs on soil microbes would depend on the extent to which NMs are able to move freely in soil and interact with soil organisms.

A number of investigators have reported adverse effects on soil organisms such as earthworms (eg Scott- Fordsmand et al, 2008) and nematodes (eg Wang et al, 2009; Roh et al, 2009; Meyer et al, 2010) exposed to NMs. It is unclear whether the toxicity observed in laboratory experiments is relevant to the real soil environment where NM properties are likely to be significantly modified in relation to the test materials used in laboratory studies.

In conclusion, the impact of NMs on soil quality is highly uncertain.

Biodiversity

There have been no investigations of the impacts of engineered NMs on natural ecosystems and biodiversity, although a number of studies have demonstrated interspecies differences in susceptibility to the effects of NMs. Griffitt et al (2008) established, for example, that filter-feeding invertebrates were markedly more susceptible to nanometal exposure compared with zebrafish. Studies of the impacts of industrial emissions to air on ecosystems have mostly focussed on the impacts of the gaseous pollutants NOx, SOx and the secondary gaseous pollutant ozone. There has been some investigation of the impacts of metals emitted from industrial processes but not in specific relation to particle effects.

The impacts of NMs on biodiversity are likely to be determined by:

• Particle composition and size which will affect their harmfulness to different types and species of organism (see sections on effects in microbes, plants and animals below);

• Environmental conditions such as salinity which may be associated with modifications of particle surface properties and size distributions that will impact on potential toxicity (see discussion of water and soil quality above and ecotoxicity below); and

• The species present in the affected ecosystem, their relative susceptibility to any adverse effects associated with NMs and the inter-relationships between these species.

The toxicity of metallic NMs on phytoplankton, for example, could lead to food shortages higher up the food chain as demonstrated by Vanhoeck et al (2009) in experiments with cerium oxide NPs. Engineered NMs that incorporate a coating such as quantum dots with a fluorescent coating, may exhibit a low level of toxicity in organisms at the bottom of the food chain, but the progressive loss of the coating as particles pass through the food chain may lead to a modification of particle toxicity and potential exposure of organisms higher up the food chain to particles of considerably greater toxicity (Bouldin et al, 2008). Interspecies differences in susceptibility to NMs (see specific discussions in relation to flora and fauna below) could lead to changes in population structure and the overall structure of the food web in affected ecosystems.

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Whilst evidence is limited, it cannot be ruled out that NMs might have important effects on biodiversity in some environments depending on the types of NMs, environmental levels of these materials and specific attributes of the environment such as aqueous chemistry and existing species mix and populations.

Flora

Experimental studies have reported widely variable findings following the exposure of different aquatic plants to different NMs. Relatively few studies have reported adverse effects that appear directly attributable to the particulate form of NMs. The toxicity of ZnO or Ag NMs to algae and other phytoplankton, for example, appears to be related to solubilised metal ions rather than the particulate form of these substances (Miller et al, 2010, Franklin et al, 2007; Aruoja et al, 2009;Miao et al, 2009). There are limited data demonstrating that TiO2 NMs are toxic to some forms of Algae (Auroja et al, 2009; Hartman al, 2010) but another study reported TiO2 NMs to be non-toxic to four species of marine phytoplankton (Miller et al, 2010) and a further study reported marked differences in the apparent toxicity of different TiO2 preparations (Hund-Rinke and Simon, 2006). .

A number of studies have demonstrated that exposure to NMs adversely affects germination and growth of terrestrial plants. Seed germination appears to less affected by NMs than subsequent growth (Stampoulis et al, 2009, López-Moreno et al, 2010; Lee et al, 2008). Adverse effects have been reported for a wide range NMs including Zn, ZnO, Cu, silicon dioxide, magnetite, zero valent iron, Ag, multi-walled CNTs (MWCNTs), 5-10 nm- sized Pd particles and CeO (Lin and Xing, 2007; Lee et al, 2008; Stampoulis et al, 2009; Lee et al, 2010; El- Temsah and Joner, 2010; Speranza et al, 2010; Lopez-Moreno et al, 2010). Several studies have demonstrated through comparison with ionic metals solutions that metal dissolution could not account for the observed toxicity of NPs, for example, for ZnO (Lee et al 2010, Lin and Xing, 2008), Cu (Stampoulis et al, 2009; Lee et al, 2008) and Ag (Stampoulis et al, 2009; Navarro et al 2008). Other particle types have been reported to have no impact on plant germination and growth including Ni(OH)2 NPs (Parsons et al, 2010) and Al2O3 (Lee et al, 2010) or germination including Au and Ag, Fe203 (Barrena et al 2009). Whereas there is clear evidence that toxicity varies by NM type, there has been little investigation of the impact of particle size and there is currently no evidence that it has an important influence on toxicity.

Studies of the uptake of NMs by plants have given inconsistent results. Several studies have found NMs in roots, shoots and leaves of plants but in some cases NMs were confined to the roots (Lin and Xing, 2008) or to shoots (López-Moreno et al, 2010). In some cases plants had biotransformed the NMs, for example, converting ZnO to an organic complex of zinc. Several studies have demonstrated interspecies differences in plant susceptibility (Lee et al, 2008; Lin and Xing, 2007; López-Moreno, 2010).

Soil conditions would be expected to modify NM toxicity. There are limited data that suggest for Ag and zero valent iron NMs, toxicity appeared to be reduced in the presence of soils and was less in clay soils than in sandy soils (El-Temsah and Joner, 2010).

In conclusion the toxic effects of NMs to plants vary by:

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• Type of NM;

• Plant species with different species showing differing levels of susceptibility;

• Growth stage with germination being less affected by NMs than subsequent growth; and

• Growing conditions with the availability of metals to plants being reduced by certain soil types.

Microbial organisms

A wide range of NM types have been shown to be toxic in bacterial tests including Al2O3, Ag, iron oxide, Cu- doped TiO2, CuO, MWCNT and ZnO (Sadiq et al, 2009, Jiang et al 2009; Rispoli et al, 2010; Suresh et al, 2010, Sinha et al, 2010, Ivask et al, 2010; Schwegmann et al, 2010; Wu et al, 2010; Simon et al, 2009). The antimicrobial properties of nanosized Ag, for example, have been employed in the use of nanosized Ag in clothing to reduce the potential for microbial interactions with perspiration to produce malodour. TiO2 appears to be less toxic to bacteria than other commonly tested NM types (Ivask et al, 2010). In some experiments the toxicity of inorganic NMs has been reduced by the formation of small aggregates in the growth media. Different bacterial species show differing levels of susceptibility to NMs; for example, Ag and ZnO NMs caused greater toxicity to Gram negative bacteria than Gram positive cells which have a thicker peptidoglycan layer (Sinha et al, 2010). The results of other studies suggest that environmental parameters such as pH, temperature and NM concentration may have important modifying effects on apparent toxicity (Rispoli et al, 2010).

Surface interactions appear to be important in driving NM toxicity. In a review, Neal (2008) reported that the majority of studies suggest that nanoparticles cause disruption to bacterial membranes, probably by production of reactive oxygen species. This toxicity requires contact between the nanoparticle and bacterial membrane probably arising from interfacial forces such as electrostatic interactions although the toxicity of free metal ions originating from the nanoparticles cannot be discounted. The passage of nanoparticles across intact membranes was considered unlikely and the commonly observed accumulation of NMs within cytoplasm was attributed to membrane disruption.

Fauna

Fish A number of studies have demonstrated the uptake of NMs by fish and fish embryos (eg Scown et al, 2009; 2010; Lee et al., 2007; Fent et al, 2010; Browning et al, 2009; Kashiwada, 2006). Most studies have found accumulations of NMs in the gills but NMs have also been detected in the brain, testis, liver, kidney and blood.

Toxic effects have been reported in fish following exposure to various NM types. A small number of studies have reported acute effects in adult fish exposed to Ag NMs and TiO2 with the gills and liver being particularly sensitive organs (eg Kim et al, 2010; Federici et al, 2007; Hao et al, 2007). A larger number of studies have demonstrated adverse effects on embryos exposed to Ag NMs, particularly the development of oedema but also spinal

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abnormalities, finfold abnormalities, heart malformations and eye defects (eg Laban et al, 2010; Lee et al, 2007;

Wu et al, 2010; Zhu et al, 2009). Effects appear to be concentration-dependant for Ag and TiO2 and increase with duration of exposure (Laban et al, 2010; Lee et al 2007; Hao et al, 2009; Wu et al, 2010).

The adverse effects of some metal NMs appear to be partly due to the presence of dissolved metal ions (Griffitt et al, 2008; 2009; Kim et al, 2010). The toxicity of nCu or nAg in female zebrafish, for example, was equivalent to that of the concentration of soluble Cu or Ag that was released during NM exposure and dissolution has also been reported to account for most of the toxicity observed with nickel NMs. Other studies have found that the effects of Cu, Ni or Ag NMs are greater than can be explained simply through metal dissolution (eg Zhu et al, 2009; Laban et al, 2010; Griffit et al, 2007). One study reported that 30, 60, and 100 nm Ni NMs are equal to or less toxic than soluble nickel in zebrafish embryos while aggregated 60 nm entities with a dendritic structure were more toxic. The defects induced by the Ni NMs differed from those of soluble nickel (Ispas et al, 2009).

The influence of particle size on NM toxicity in fish is unclear with conflicting findings reported by Bar-Ilan et al (2009), Kim et al (2010) and Ispas et al (2009). In contrast, there are clear differences in the toxicity of NMs of different composition, although direct comparison is often limited by factors such as differences in particle size. A number of studies have demonstrated that ZnO and Ag NMs are relatively toxic, whereas Au and TiO2 are less toxic (eg Zhu et al, 2008; Bar-Ilan et al, 2009; Farkas et al, 2010, Browning et al, 2010). Surface coatings and surface properties of NMs can significantly modify their toxicity. The toxicity of CdSe(core)/ZnS(shell) quantum dots to zebrafish embryos was reduced by coating with either poly-L-lysine or poly(ethylene glycol) terminated with methoxy, carboxylate, or amine groups (King-Heiden et al, 2009). In addition, the toxicity of NMs can be modified by environmental conditions, for example, the acute toxicity of latex NMs to medaka eggs has been shown to be salinity dependent (Kashiwada, 2006).

Daphnia A large number of investigations have reported toxic effects in Daphnia as a result of exposure to a wide range of NMs including, for example, Ag NMs, fullerene, Au and Au-Ag bimetallic particles, SWNTs, CuO, ZnO, CdSe quantum dots and TiO2 (Allen et al, 2010; Kim et al, 2010; Li et al, 2010; Klapper et al, 2009; Lovern and Klapper, 2006; Heinlaan et al, 2008 a and b; Blinova et al, 2010; Jackson et al, 2009; Pace et al, 2010; Zhu et al, 2010;

Wiench et al, 2009). The toxicity of nano TiO2 appears to be much less than for other particle types (eg Heinlaan et al 2008).

There is some evidence that the acute toxicity of ZnO is due to dissolved zinc (Wiench et al, 2009; Heinlaan et al, 2008) and Cu dissolution contributes to the toxicity of CuO NMs but does not account for all of the observed toxicity (Heinlaan et al, 2008). The toxicity of CdSe quantum dots can be reduced by coating with polyethylene oxide (PEO) to increase stability or increased by 11-mercaptoundecanoic acid (MUA) which accelerates dissolution and the release of Cd (Pace et al, 2010).

Particle surface properties play a key role in determining toxicity and in natural waters, dissolved organic carbon (DOC) may greatly lower the toxicity of engineered NMs (Blinova et al, 2010).

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Only a small number of investigations of the role of particle size in determining toxicity have been undertaken and these have not shown clear evidence of an (Kim et al, 2010; Li et al, 2010; Pace et al, 2010, Wiench et al 2009). Wiench et al reported that particle aggregation did not impact on toxicity whereas other authors have speculated that aggregation may reduce toxicity (Li et al, 2010; Jackson et al, 2009).

Exposure-response relationships appear to be complex. In one study for example, fullerene, showed increased toxicity at low concentrations (Lovern and Klapper, 2006).

Exposure time may be an important influence on NM toxicity with toxicity increasing as exposure time increases (Zhao and Wang, 2010, Zhu et al, 2010).

Other invertebrates Adverse effects have also been reported in molluscs (Canesi et al, 2008; 2009; Ringwood et al, 2009; Tedesco et al, 2010), midge larvae (Nair et al, 2010), lugworm (Galloway et al, 2010) and zoo plankton (Mortimer et al, 2010; Snell et al, 2009) exposed to various NMs.

Summary The experimental data indicate that

• Certain NMs may have adverse effects on a wide range of organisms.

• NMs show a range of toxicities with Ag, Zn, Cu, ZnO and CuO NMs and quantum dots with Cd cores being relatively toxic to aquatic organisms. There is limited evidence that Au NMs are less toxic than Ag NMs and TiO2 NMs appear to be considerably less toxic than most other NMs that have been tested.

• There are interspecies differences in susceptibility to effects.

• Soluble Zn, Cu and Ag ions appear to play an important role in the toxicity of NMs able to release these substances, but it is clear that the particulate form of NMs accounts for a component of their toxicity.

• The toxicity of NMs is likely to be significantly modified by environmental conditions that affect their surface properties and the degree of aggregation.

Waste

The growing use of Ag NMs as bactericides suggests that these NMs could potentially have adverse effects on the microbial communities employed in waste water treatment. There is evidence from the use of bacterial test systems that a wide range of other NMs are likely to have anti-microbial properties. The results of preliminary studies have not confirmed, however, that NMs will adversely affect wastewater treatment (Blaser et al, 2008; Nyberg et al, 2008). There are limited data that confirm that silver NMs released from consumer products are reaching the waste water stream and waste water treatment works (Kim et al, 2010). There has also been some limited consideration of

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the potential release of silver to the wider environment in discharges from wastewater treatment works. In a modelling exercise, Blaser et al (2008) demonstrated that likely levels of discharge of nano-silver in 2010 could lead to environmental exposures to silver that could exceed predicted no effect concentrations for freshwater ecosystems and sediments.

Conclusions

1. There are substantial data indicating that NMs can cause adverse effects in aquatic and terrestrial organisms.

2. The relative toxicity of NMs varies substantially by particle type, particle size and whether particles have modified surfaces.

3. The relevance of experimental systems to the prediction of effects in the wider environment is uncertain as NM properties are likely to be substantially modified by interactions with substances present in natural waters and soil.

4. It seems plausible that NMs in the environment could adversely affect biodiversity and indirectly affect water and soil quality through their toxicity to micro-organisms in soil, natural waters and during waste water treatment.

2.11.4 Climate forcing potential

Potential Effects

Atmospheric particles originate from natural sources such as windblown dust, volcanic ash and particles formed from reactions of biogenic substances such as turpenes and man-made sources including soot from combustion and secondary particles formed from gaseous pollutants. Engineered NMs are likely to have a negligible impact on overall atmospheric particle loadings (at current emission levels) whereas UFPs emitted from combustion processes may have a significant impact on particle loadings and potentially on climate.

The conclusions of recent reviews of the potential impact of emissions of NMs to the atmosphere on climate developed under the GENNESYS programme (Brasseur, 2010) and by the Climate Change Unit at JRC (Petaud, 2010) indicate that NMs may potentially contribute to warming or cooling effects and to cloud formation and condensation to form rain. The behaviour of NMs in the atmosphere and their potential impact on weather and climate is dependent on the size, chemistry and surface properties of particles, the temperature, pressure and humidity of the environment and the nature and concentrations of the gases and vapours present. Natural emissions such as volcanic sulphate and biogenic vapours and aerosols and the formation of secondary particles have an important influence on overall particle concentrations in the atmosphere.

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Most NMs emitted to the atmosphere are too small to act as condensation nuclei (section 3.8.2) but will coalesce with other particles to form larger particles of about 200 – 600 nm (Brasseur, 2009; Petaud, 2010) at rates that are determined by total particle concentrations (section 3.8.2). These larger aerosol particles together with soil dust, volcanic aerosol, particles emitted from combustion processes including biomass burning and secondary particles formed from organic vapours including biogenic emissions and/or oxidised sulphur and nitrogen species in the atmosphere interact with energy from the sun and reflected energy from the ground (Brassuer, 2010; Petaud, 2010). Particles absorb, reflect and scatter light with the relative importance of these processes being dependent on the particle type and size. Absorption of solar radiation is possible for particles of less than 10 nm diameter but this absorption increases in efficiency as particles increase in size to about 1 µm whereas scattering and reflection is possible only at diameters greater than about 40 nm. Scattering is greatest for particles with diameters about 500- 800 nm and reflection drops sharply for particles greater than about 2 µm in size (Petaud, 2010). Particles for which absorbance is particularly important such as those based largely on carbon, may contribute to atmospheric warming similar to that associated with greenhouse gases. In contrast, sulphate particles scatter more light than they absorb and are associated with cooling. NMs also have an indirect impact on climate forcing through their role in cloud formation and cloud stability. Interactions between NMs may lead to the formation of larger submicron particles that may act condensation nuclei leading to cloud formation. At high particle concentrations the formation of larger water droplets may be inhibited by the presence of a large number of condensation nuclei and cloud albedo will increase (Brasseur, 2010). This may be offset by evaporation of cloud droplets due absorption of solar energy and/or the formation of more ice nuclei (Brasseur, 2010).

Engineered NMs that are insoluble and hydrophobic are unlikely to activate condensation under natural conditions and would have a prolonged residence in the atmosphere unless they coalesce with wettable or hygroscopic particles. The resistance of insoluble, hydrophobic particles to being rained out will contribute to their potential to cause warming or cooling as a result of prolonged atmospheric residence (Niessner, 2010). Particle shape may modify the hydroscopic properties of nanosized particles of some soluble salts (Park et al, 2009).

There is a considerable volume of ongoing European research into the sources and characteristics of atmospheric particles based on observational studies. The FP6 initiative ACCENT - Atmospheric Composition Change: A European Network - has played an important role in co-ordinating European research on atmospheric chemistry, although much of the work is focussed on gaseous pollutants. The FP7 project CITYZEN27 - megaCITY - Zoom for the Environment - for example, has focussed on improving emissions estimates for air pollution and measuring atmospheric composition. There is also considerable ongoing research into better understanding the heating and cooling effects associated with current levels of atmospheric particles that employs both observation and modelling. The FP6 project EUCAARI - European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions – was focussed on improving understanding of the impact of aerosol particles on climate and the relationship between anthropogenic aerosol particles and regional air quality. The findings suggest that aerosol emissions have had an important effect in counteracting greenhouse gas induced global warming during the industrial period. The EUCARRI team have concluded that the aerosol cooling effect is likely to be strongly

27 http://www.cityzen-project.eu/

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reduced by 2030, as air pollution abatements are implemented worldwide and the presently available advanced control technologies are utilized leading to a predicted increase in global mean temperature of about 1oC.

The MEGAPOLI28 - Megacities: Emissions, urban, regional and Global Atmospheric Pollution and climate effects and Integrated tools for assessment and mitigation – project has integrated both modelling and observation to examine the impacts of global megacities (not specifically EU cities) on climate. The results demonstrate that, while carbonaceous particles may be associated with a small warming effect in terms of radiative forcing, secondary sulphate and other noncarbonaceous particles may be associated with substantial cooling effects that outstrip the warming effects of particles (Folberth et al, 2010). The model outcomes indicate that emissions of sulphur dioxide could have a particularly important influence on global climate due to the formation of secondary particulate, although it is likely that sulphur dioxide emissions were over-estimated in the modelling exercise. The combined total annual mean raditive forcing from megacity pollutants is calculated to amount to -8.0±1.6 mW/m2 with a +6.3±0.4 mW/m2, -1.0±0.5 mW/m2, -15.3±0.6 mW/m2 and +2.0±0.1 mW/m2 contribution from a change in the ozone burden, the methane lifetime, the aerosol shortwave all-sky top of atmosphere and the aerosol long-wave clear-sky top of atmosphere radiative forcing, respectively. The impact of megacities on climate at present-day conditions, however, is small compared to the forcing resulting from emissions of long-lived greenhouse gases such as carbon dioxide, methane and nitrous oxide. The impacts of particles on cloud formation and the indirect impacts on climate were not considered. An ongoing Cyprian project C829 - Consistent Computation of the Chemistry Cloud Continuum and Climate Change in Cyprus - has a much narrower geographical scope but may provide some improvements in the understanding of the relationship between aerosols, cloud formation, precipitation and climate formation. It aims to investigate how cloud and precipitation formation are influenced by atmospheric chemical composition changes and how haze and cloud formation in polluted air affects weather and climate.

There are also some more experimentally based ongoing studies. The ATMNUCLE - Atmospheric Nucleation: from Molecular to Global Scale – project aims to link the output of molecular simulations and laboratory measurements undertaken to understand nucleation and aerosol thermodynamic processes to measurements of nanoparticles and atmospheric clusters in order to study feedbacks and interactions between climate and biosphere.

In conclusion, the current state of knowledge does not appear to be sufficient to allow confident prediction of how changes in NM/UFP emissions, changes in gaseous emissions and indirect human impacts on biological systems will impact on atmospheric particle concentrations, cloud formation and climate forcing potential. Climate research has focussed on the role of greenhouse gases in global warming, but there may be important cooling effects associated with atmospheric aerosols. The results of several studies suggest that particles have significantly slowed the rate of greenhouse warming to date. The relative importance of warming versus cooling may change substantially in response to changing emissions patterns and the associated changes in atmospheric chemistry as

28 http://megapoli.info/

29 http://www.cyi.ac.cy/C8

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different reactions and processes become more or less important. It has been suggested that the cooling effects of particles may be greatly reduced by 2030 because of emissions reductions strategies (particularly in relation to sulphur dioxide), although this is not a consensus view among all climate scientists. Climate change is a very active area of current research and the results of ongoing observational, experimental and modelling studies are likely to play an important role in future understanding of the relationships between human activities, atmospheric particle loadings and the impact on climate.

Conclusions

1. UFPs/NMs have direct impacts on the atmospheric absorbance of heat (e.g. carbon-based particles) or reflection (e.g. sulphate particles).

2. Atmospheric particles have indirect impacts on temperature through promoting the formation and, depending on concentration, the persistence of clouds. UFPs/NMs may contribute to these indirect effects through their interactions with other particles, vapours and gases in the atmosphere that lead to the formation of condensation nuclei.

3. UFP/NM emissions may, therefore, have important impacts on weather and climate but the overall impact in terms of warming or cooling and impact on precipitation patterns is uncertain. The relative importance of engineered NMs, UFPs of primary combustion origin, UFPs of secondary anthropogenic origin and naturally-formed UFPs in giving rise to impacts on weather and climate is also uncertain.

2.11.5 Sources of uncertainty

Sources of uncertainty in the prediction of human health effects arising from exposure to atmospheric nanoparticles include the paucity of information about human exposure to atmospheric NMs and the nature of NMs that are present in ambient air, including the extent to which NMs are present as aggregates. These factors are likely to be important determinants of the harmfulness of atmospheric NMs. In addition, there is uncertainty about how surface-adsorbed species such as polyaromatic hydrocarbons may modify the potential for atmospheric NMs to give rise to adverse effects. The fate and toxicity of inhaled aggregates of NMs are not well understood and may be different from similarly sized single particles. Other sources of uncertainty include those described under topic 10 (Section 2.10) in relation to the difficulty of comparison of the relative toxicity of different particle types and the absence of information about observed effects of NMs in humans.

The major source of uncertainty in predicting the environmental impacts of NMs is the lack of data and the limited utility of models or experiments in the prediction of impacts in highly complex natural systems. Research into the following would improve understanding of the environmental impacts of NMs:

• The fate of NMs in air, water, soil and during waste handling and characterisation of the actual exposures experienced by natural ecosystems;

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• The impact of changes in NMs during environmental transport on their ecotoxicity; and

• The extent to which effects observed in simple laboratory experiments are reproduced when experiments are conducted within more complex systems that are more similar to real environments.

There are also uncertainties in interpreting the results of laboratory investigations of toxicity in plants and aquatic organisms. Research into the following would improve understanding of toxicity of NMs:

• The role of particle size as well as composition in determining toxicity;

• The impact of particle aggregation on toxic potential; and

• The modification of the toxic potential of particles through interactions with other substances that are typical present in natural environments.

Major sources of uncertainty in the prediction of climate impacts of NMs include a limited understanding of the fate of NMs emitted to the atmosphere and the complex factors that determine whether NMs contribute to the formation of condensation nuclei and cloud formation. Gaseous emissions also have an important influence on atmospheric particle concentrations arising from secondary particle concentrations as well as particles formed in response to biogenic emissions that may vary as an indirect response to human activities. There is a lack of knowledge about the relative importance of absorption, scattering and reflection of solar radiation that may be associated with future atmospheric particle loadings. Further research into the relationship between emissions, particle loadings and impacts on heat transmission through the atmosphere would help to improve understanding.

2.11.6 Conclusions

1. UFP/NMs are likely to be damaging to human health giving rise to similar effects to those associated

with PM10/PM2.5, although their relative potency is likely to vary by particle type and size.

2. There is a paucity of information about the environmental fate of NMs, their actual impacts on environmental quality and the likely levels of exposure of organisms in natural ecosystems.

3. NM emissions are likely to influence environmental quality and impact on microbial communities, aquatic life and potentially soil health and terrestrial plants and animals.

4. There are interspecies differences in susceptibility to NMs and this could to lead to modification of ecosystem functioning leading to adverse impacts on biodiversity as well as affecting agriculture.

5. Although the impacts of NMs on plants and animals have been extensively investigated in experimental test systems, the results of these investigations are likely to be of limited relevance to predicting impacts in natural systems where the size distribution and surface properties of NMs are likely to be substantially modified by the environmental conditions.

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6. The impact of UFP/NM emissions on weather and climate are highly uncertain but potentially important and could contribute significantly to global climate change but not necessarily to warming.

2.12 Topic 12: NMs and UFPs metric(s) (particle mass, surface, number) most appropriate to describe dose-effect relationships

2.12.1 Information Sources

This task was based on the information reviewed under topics 10 and 11.

Further details are provided in Appendix A7.

2.12.2 Epidemiological Studies

The earliest measurements of workplace exposure to particles assessed concentrations in terms of particles per cubic foot. The measurement of particle number concentrations was, however, superseded by the measurement of mass concentrations of most aerosol exposures. Studies in UK coal mines confirmed findings from elsewhere that mass concentration of respirable dust was a better measure of dose than particle number counts and that the use of mass concentrations gave consistent exposure-response relationships for coal mine dust that had not been previously observed when dose had been expressed as particle number (Jacobsen et al, 1971). Workplace epidemiology studies established exposure-response relationships for a wide range of particulate substances that linked effects to mass concentrations including most notably coal mine dust, but also quartz and metals such as manganese, nickel, hexavalent chromium and arsenic. These epidemiological studies identified the importance of the respirable fraction in giving rise to serious lung disease. These studies also established that coal mine dust or quartz from different places appeared to have differing levels of potency (NIOSH, 1995, 2002). This led to work examining the importance of surface properties in modifying the toxicity of airborne particles. The main exception to the use of mass concentrations in investigations of particle toxicity was in the measurement of exposure to asbestos which was based on fibre concentrations, although this is largely a reflection of the practicality of measurement30.

Exposure-response relationships from epidemiological studies describe the empirical link between exposure and effect rather than being mechanistically based. There are generally substantial uncertainties in the exposure data and the shape of the exposure-response function is influenced by the approach taken to modelling the relationship between exposure and response. Exposure-response relationships from different workplace environments show very different relationships between exposure and response for different substances and, in some circumstances, the same substance. Differences in the exposure-response relationships reported for individual substances are, in some

30 Fibre counting allows specific measurement of fibre concentrations as opposed to mixed dust

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circumstances, likely to reflect differences in the surface properties of particles. For example, freshly cut quartz is believed to be considerably more toxic than quartz particles with aged surfaces (NIOSH 2002). It is possible that other differences in the exposure-response relationships reported by different studies are due to differences in particle size distribution and particle surface area but this has not been widely investigated. Another key factor affecting the apparent potency of a single substance under different circumstances is concurrent exposure to other substances in workplace air.

Exposure response relationships for air pollution have been almost entirely derived for particulate mass in different size fractions. Both PM2.5 and PM10 appear to be of health relevance and there is a growing body of data suggesting the PM1 may also be a health-relevant metric of particle concentrations. Few studies that have examined the health effects of ambient pollutants have compared particle mass and particle numbers as metrics of exposure. The results of several studies, however, suggest that particle number may be a more sensitive marker of exposure in relation to health effects. Atkinson et al (2010) investigated associations of a range of particle metrics (PM10, PM2.5, and

PM(10-2.5), particle number concentration and particle composition (carbon, sulfate, nitrate and chloride) measured at a single site with daily deaths and hospital admissions in London. Particle number concentration was associated with daily mortality and admissions, whereas secondary pollutants, particularly secondary PM2.5, nitrate and sulphate, were more important for respiratory outcomes. The authors identified a need for further investigation with more comprehensive exposure data.

In a small study of 27 non-smoking asthmatics, Peters et al (1997) reported that respiratory symptoms were more strongly associated with particle counts than PM10. Most (73%) particles were less than 0.1 µm in diameter, whereas most of the mass (82%) was attributable to particles in the size range of 0.1 to 0.5 µm, implying that respiratory health was more strongly associated with the ultrafine fraction than with larger particles. Hertel et al (2010) assessed systemic inflammatory response to air pollution through the analysis of high-sensitivity C-reactive protein (hs-CRP) levels in 3,999 people in the Ruhr Area in Germany. After adjustment for meteorology, season, time trend, and personal characteristics, a positive association between particle number and hs-CRP was observed for single day lags and for averaged PN concentrations with higher estimates for longer averaging times. The highest hs-CRP-increase of 7.1% was found for the 21-day average. No effect was observed with PM2.5.

Branis et al (2010) investigated the association of particle number and PM2.5 concentrations with mortality and cardiorespiratory hospital admissions in Prague. The strongest association was found between the number of accumulation mode particles (median diameter 346 nm) and cardiovascular and respiratory admissions for a 7-day moving average. Associations were also found between both cardiovascular and respiratory admissions and the number of accumulation mode particles for lags of 0, 1 and 2 days (not for respiratory admissions), and the 4-day moving average. For total particle number counts and the number of particles with a median diameter of 128 nm, significant associations were also found for both cardiovascular and respiratory admissions at lag 0, lag 1, and lag 2

(not for respiratory admissions) for the 4-day and 7-day moving average. The association between the PM2.5 and daily cardiovascular hospital admissions was significant at 2-day lag and for a 4-day average for respiratory admissions for a 7-day average. No association was found between the studied air pollution variables and daily mortality. The particle count data provide more information about which components of the particle mix are important to health than the mass metric of exposure and appears to be a marginally more sensitive marker of

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effects given that positive associations were found on the same day and the two days following exposure that were not detected when exposure was assessed in terms of PM2.5.

In a study of cardio-respiratory mortality in Erfurt, Germany, Stolzel et al (2007) reported statistically significant associations between elevated UFP (0.01-0.1 µm) numbers and total as well as cardio-respiratory mortality, each with a 4 days lag whereas no association between fine particle mass concentration and mortality was found. In a related investigation of the association of ambient air pollution and daily mortality over a 10.5-year period after the German unification, Breitner et al (2009) demonstrated that cumulative exposure to UFP number counts was associated with increased mortality whereas no statistically significant relationships were found between mortality and mass concentrations of PM2.5 or PM10 (see also longer report by Peters et al, 2009).

Not all studies that have compared particle number count and mass concentration have, however, found stronger associations between number count and effects than between mass concentration and effects. Park et al (2005) investigated heart rate variability (HRV) in 497 men from the Normative Aging Study in greater Boston,

Massachusetts and reported significant associations between measures of HRV and PM2.5 averaged over 48 hours but not between HRV and particle number count (averaged over 4 hours, 24 hours or 48 hours). A small number of studies have only reported particle concentrations in terms of number count. These studies provide evidence that particle numbers are a health-relevant dose metric but are not informative in terms of discriminating between particle number and particle mass in terms of relevance to health. Examples include a study of changes in biomarkers of pulmonary and systematic inflammation in a group of healthy volunteers who cycled for about 20 minutes in traffic near a major bypass road (road test; mean UFP exposure: 28,867 particles per cm3) in Antwerp and in a laboratory with filtered air (clean room; mean UFP exposure: 496 particles per cm3; Jacobs et al, 2010). Overall, there is a growing body of data that suggests that particle number count may be a more sensitive dose metric than PM2.5. This may partly be because particle number counts are dominated by particles in the submicron size range that may be of greater relevance to health, particularly cardiovascular effects and mortality, than larger particles in the PM10 size range (see section 2.10.3).

Based on the limited epidemiological data and the findings of epidemiological studies, many experts believe that particle number is likely to be the most relevant dose metric for UFP (Hoek et al, 2010).

The key knowledge gaps relevant to developing a better dose metric are the paucity of epidemiological studies comparing concentration-response functions derived for a variety of dose metrics and a paucity of side by side monitoring data for different particle metrics. Better knowledge of the inter-relationships between different measures of dose would enable some evaluation of whether the observed mass-based concentration response functions for PM2.5 and PM10 could also reflect relationships between particle number or surface area and effect.

In conclusion:

1. There are growing epidemiological data that suggest that particle number may be a more health- relevant metric of fine particle exposure than mass but there is insufficient data to conclusively demonstrate this.

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2. The variability in concentration-response relationships for ambient PM in different studies partly reflects the uncertainty in exposure measurement, but is also likely to reflect differences in the composition and size distribution of ambient PM at different locations.

3. There are also some data suggesting that toxicity of ambient PM varies by size and composition, although reported effects are not consistent between different studies.

4. It would be premature, given the limited data available, to replace the current system of mass measurements of ambient PM with measurement of surface area or particle number. It would be appropriate to increase the extent to which alternative metrics of PM are measured including surface

area and particle number. There may also be value in measuring PM1 and PM0.1.

5. In order to improve the quality and consistency of the evidence base, there is a need for more epidemiological investigations of health effects that are linked to side-by-side measurements of

concentrations of PM2.5/PM10 and other PM dose metrics.

6. In practical terms, in order to be able to perform effective epidemiological comparisons of different PM dose metrics, there is a need for continuous runs of measurement data for alternative PM metrics over several years at locations relevant to the estimation of population exposure.

2.12.3 Toxicology

Inhalation experiments in animals have established exposure-response relationships for a wide range of particles. The traditional measure of dose is mass concentration but, during the 1990s, several studies demonstrated that particle surface area is a more appropriate measure of dose. Specifically, dose-response relationships for different low toxicity dusts were found to coincide when concentrations were re-expressed in terms of particle surface area (Tran et al, 1999). This was interpreted in terms of the specific impacts of inhaled particles on respiratory health that are independent of particle composition. It was found that exposure-response functions for toxic dusts remained distinct from those of low toxicity dusts even when re-expressed in terms of particle surface area.

Inhalation experiments involving NMs have provided some evidence to support either the use of particle numbers or surface area of particles as an appropriate metric of dose but there are inconsistencies in reported data. Particle surface reactivity is an important modifier of effects and it might be appropriate in the future to develop a dose metric that incorporated surface reactivity. Other complicating factors in the development of a common dose metric for NMs are the role of particle shape and leachable metal content. It has been suggested by Donaldson et al, (2006) and Tran et al, (2008) that high aspect ratio NMs (e.g. CNTs) may have some similarities to asbestos and may be more toxic than would be predicted on the basis of particle surface area or surface properties. There is also evidence that the toxicity of some metal and metal oxide NMs is related to the release of metal into solution which is likely to be governed in part by particle size (smaller particles have larger surface area to mass ratios and dissolve more readily) but also to surface structure.

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The relevance of surface area as a measure of dose for NMs has been confirmed by the findings of experiments that have exposed animals to NMs by intratracheal instillation. Sager and Castronova (2009) exposed rats by intratracheal instillation to various doses of ultrafine and fine carbon black giving rise to a dose dependent but transient inflammatory and cytotoxic response. On a mass basis, the response to the ultrafine CB was significantly (65 fold) greater than for fine sized carbon black but when doses were equalized based on surface area of particles given, the ultrafine carbon black particles were only slightly (non-significantly) more inflammogenic and cytotoxic compared to the fine sized carbon black. Duffin et al (2007) reported that the inflammation associated with the instillation of a number of low-toxicity dusts of various particle sizes into rat lungs was a function of the surface area dose instilled whereas the high specific surface toxicity of DQ12 quartz gave rise to a much greater response than would have been predicted on the basis of surface area.

The importance of particle surface area as a determinant of effects has also been confirmed in a number of cell- based studies. Monteiller et al (2007) reported that the potency of ultra-fine cobalt and nickel was similar to that of

TiO2 NMs for similar surface-area doses. Dose-response relationships observed in the in vitro assays were reported to be directly comparable with dose-response relationships in vivo when with a threshold in dose at around 1-10 cm2/cm2 measured as surface area of particles relative to the surface area of the exposed cells. In a study of eight distinct NM types, Rushton et al (2010) found that the findings of in vitro assays were significantly correlated with in vivo results when effects were expressed in terms of chemical (cell-free) or biological (cells; in vivo) activity per unit particle surface area. The results of experiments with mesoporous SiO2 suggest that the “cell contactable” surface area of particles is more relevant than total surface area (Maurer-Jones et al, 2010).

Not all studies have provided consistent evidence that particle surface area is the best dose metric. Wittmaack

(2007) reviewed published dose-response data on acute lung inflammation in rats and mice after instillation of TiO2 particles and six types of carbon NMs. The number of particles, the joint length (the product of particle number and mean size) and one measure of surface area were found to be reasonable dose metrics whereas the particle size- based surface area did not appear to be a good dose metric. Linear dose-response relationships were identified at low doses, with no evidence of a threshold dose.

In conclusion:

1. The results of a number of toxicological investigations suggest that particle surface area is an appropriate dose metric for a wide range of particle types in a range of experimental systems.

2. Surface area may not be the best metric for particles with significant internal porosity or for high aspect ratio particles where shape may be an important modifier of toxicity.

3. There are insufficient data to confirm that surface area is the best dose metric for describing particle exposure in experimental systems and some data that indicate that other measures of dose such as particle number count may be better for some types of particle in some experimental systems.

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2.12.4 Conclusions

1. The factors that govern NM toxicity include particle surface area with modifying factors for surface reactivity, leachable metal content and particle shape.

2. A complex exposure metric incorporating all these factors would be highly impracticable to measure and any exposure metric developed for NMs would have to recognise the variable toxicity of particles of differing size, shape and composition.

3. The results of a number of toxicological investigations suggest that particle surface area is a health relevant measure of NM concentration, for a range of particle types.

4. There are limited epidemiological data that suggest particle number counts may be a more health relevant measure of dose than mass, although numerous studies have demonstrated dose-response

relationships based on mass concentrations of PM2.5 and PM10.

5. Information about particle size is important and it would be desirable to measure exposure to different

size categories e.g. PM0.1, PM1, PM2.5 and PM10.

6. The gravimetric determination of PM1 would provide useful information about NM exposure, even in the absence of particle number counts.

7. There is a need for more epidemiological investigations of health effects that are linked to side by

side measurements of concentrations of PM2.5/PM10 and other PM dose metrics.

8. The size distribution and particle surface properties of NMs are likely to be modified by residence in air and the particle population at any location would include particles of a range of size and composition from a range of sources. These factors would not be readily captured by any measure of dose.

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3. Data assessment [Task 4]

3.1 Introduction

This section provides an assessment of the information gathered for each of the topics as presented in the previous section.

3.2 Assessment

In line with the project specification, the data has been assessed for:

• Comprehensiveness – data gaps and obstacles for a comprehensive description of NMs and UFPs releases from industrial sources and their impact on human health and the environment should be identified together with options to address the problems; and

• Quality – are findings consistent and do they allow the development of a coherent picture?

The assessment is summarised in the table on the following page.

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Table 3.1 Data assessment matrix

Key:

Comprehensiveness Quality

Significant data gaps and/or Significant inconsistencies obstacles remain identified

Some data gaps and/or Some inconsistencies obstacles identified identified

No (or very limited) data gaps No (or very limited) and/or obstacles identified inconsistencies identified

Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

Topic 1a: Information on UFP size distribution, composition Limited UFP data specific to industrial sources Limited literature on UFPs from industrial sources, Composition, size and morphology from several industrial sources. has been obtained, but when combined with but when combined with general information on distribution & shape generic information, provides an adequate UFPs provides a broadly consistent picture. of atmospheric overview of the size distribution, chemical releases UFPs from composition and morphology. industrial sources.

Topic 1b: Information on NMs is generalised as no Information on NMs is generic, but is wide Data on NMs is still at the generic level with data Composition, size measurement data available. ranging, which provides good coverage. There being derived from theoretical studies, rather than distribution & shape are several databases which list NMs on the measurement. So whilst inconsistencies are limited, of atmospheric market providing an indication of real world NM the quality of the data is still rated as being poor, releases of NMs usage information. because very little measurement/quantitative data from industrial are available. sources.

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Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

Topic 2a: Relative Fractionation profiles and data from national Some data gaps are evident in national PM10 The PM10 emissions data use different reporting contribution of emission inventories has been manipulated to input datasets. Whilst these have been structures, and a complex methodology has been UFPs to overall PM produce UFP emissions and analysed to highlight addressed with standard gap filling procedures, needed to assign activity data to the point source releases. main sources of emissions. substantial improvements could be made. dataset and allow them to be presented with the Industrial PM point source data has good same reporting format as the national emissions 10 datasets (NFR). coverage, but the lack of accompanying activity data requires assumptions to be made and NFR sub-category analysis is difficult when only introduces uncertainty. generalised PM10 fractionation profiles are available. The largest source of uncertainty remains the very limited PM10 fractionation profile data that is available.

Topic 2b: Relative Main applications of NMs identified with some NM use can be estimated with reasonable Uncertainties associated with estimating the use of contribution of NMs qualitative data available. Lacking quantitative data sectoral coverage based on available product NMs are very high - to the extent that even to overall PM on emissions from all sources. inventories. However with no information on providing qualitative information would be very releases. emission potential, neither quantitative nor uncertain. qualitative estimates have been possible.

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Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

Topic 3: Analytical A number of measurement techniques have been Techniques applicable for measuring NMs and Information comes largely from experimental tools for monitoring identified that can measure releases of NMs and UFPs releases have only been applied in a laboratory work. of NMs & UFPs UFPs including ELPI, MOUDI, SMPS and DMA. limited number of industrial settings. Majority of There is little information on reliability and release Techniques are often applied in combination. investigations have been dedicated to traffic repeatability of testing, as well as complications sources. Conditions at industrial installations present associated with monitoring where certain limitations for monitoring NMs and UFPs i.e. high Limitations arise from the approaches adopted abatement techniques are applied e.g. wet temperatures, semi volatile flue gas components for monitoring, generally conducted with scrubbers. and dynamic physicochemical processes conventional hot stack gas sampling, with no (nucleation, coagulation and condensation) and information available on the potential effects on chemistry. particle number concentrations of particle nucleation and/or condensation phenomena, Limited instances of monitoring of NM and UFP emissions from industrial sources and no examples arising from semi-volatile flue gas components and driven by atmospheric dilution. of its use in a regulatory context. Real-time measuring instruments are essential, however studies have used techniques with a time-weighted average basis. Little information available on the costs of monitoring equipment.

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Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

Topic 4: Analytical A number of different characteristics of NM/UFP Lack of a comprehensive understanding of how The data available are relatively sparse so it is not tools to trace NMs have been identified that could, in principle, be the properties of industrial emissions sources possible to draw firm conclusions. and UFPs to their used to trace them to their (industrial) sources. affect the properties of NM/UFPs. However, there seem to be some differences source Some studies available which suggest that Knowledge of environmental fate/behaviour of amongst studies as to the effect that different (fingerprinting) characteristics of industrial (and other) sources can specific NM/UFP and tools to estimate the sources have on factors such as particle size affect the properties of emitted NM/UFP (“source relative contributions of different sources to distribution (uni/bi/tri-modal, etc.) signatures”). environmental concentrations (e.g. receptor models). Analytical tools to identify and characterise NM/UFP in releases and in the wider environment Does not currently seem to be clear which seem to be better developed than the knowledge of properties of NM/UFP are likely to be of most how sources affect the properties of NM/UFP use in fingerprinting. In practice, it is likely emitted and than the effects of environmental fate / combined information on various properties behaviour on concentrations and properties. would be needed. Limited instances of fingerprinting having been Little information available on the costs of using applied in practice and little or no examples of its fingerprinting. use in a regulatory context.

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Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

Topic 5: Abatement A number of widely used particulate abatement Commonly used particulate abatement The limited availability of information on the NM and techniques for NMs measures have been identified that may abate measures are focused on controlling emissions UFP abatement efficiency of different measures has and UFPs emissions of NMs/UFPs although often this is at of PM2.5 and larger particles. restricted the ability to compare data sets to lower abatement efficiencies than for coarser establish a consensus or to evaluate consistency More advanced or specialist measures aimed fractions. These include: between sources. at controlling emissions of smaller particle size • Cyclones have only been identified as being used in a limited number of commercial installations or • Wet scrubbers are still under development. • Fabric filters Therefore, in both cases, there is limited • ESPs information available about the efficiency of these measures for abating NMs and UFPs. Advanced and hybrid versions of these measures, as well as other methods including impactors and particle injection/coagulation, which offer improved emissions reductions are under development or entering the market.

Topics 6, 7 & 9: There are a number of processes affecting UFPs Very few direct measurements available Reactivity of different particle types is highly Processes affecting emitted to the atmosphere – including evaporation, relating to manufactured NMs. Majority of focus variable. NMs and UFPs in condensation, coagulation, chemical reactions and in the scientific community to date has been on Unclear if treatment of UFPs in the same way as the air deposition – all of which will affect their fate. road traffic emissions which will not be fine particles (e.g. PM ) in atmospheric chemistry representative of most manufactured NMs. 2.5 transport models is adequate. Limited consideration of emissions from industrial sources in the literature.

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Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

Topic 8: Estimation Limited measurement data describing size Little measurement data describing population NMs/UFPs emitted from different sources will of human exposure distribution and composition of ambient PM exposure to PM0.1 disperse differently and the proximity of population to NMs & UFPs provides some information about population to different sources differs. No modelling of population exposure to PM exposure to different fractions of PM, including very 0.1 from different sources has been identified. Oversimplification of approach to estimation of limited data for PM 0.1 NP/UFP exposure is likely to significantly These data also provide limited information on the misrepresent relative importance of different NP relative importance of different types of PM source sources. in contributing to total exposure levels. Understanding relative contribution of different NP Readily available information about population sources to human exposure would require a major exposure to PM10 and PM2.5 (EURODELTA) and modelling exercise including a more robust some information available regarding contribution underlying emissions inventory. of different sources of PM0.1, PM2.5 and PM10 to total PM emissions. Possible to estimate approximate population exposure to PM0.1 on basis of emissions and comparison with emissions and exposure information available for PM10.

10. Risk Harmfulness of ambient PM well established. Few experimental comparisons of engineered Wide range of experimental protocols employed. vs ambient PM. assessments of Adverse effects not confined to smallest particles. Poor description of experimental materials. NMs & UFPs Engineered PM varies hugely in toxicity. Ambient Almost no epidemiological information Difficult to compare across studies. PM may be relatively toxic because of leachable describing effects of engineered NPs in metals and toxic organics. humans. Uncertainty about relevance of experimental test systems to prediction of human health effects. Toxicity generally increases with decreasing Relationship between particle size and toxicity particle size when dose is expressed in mass not consistent. Uncertainty about particle properties in ambient air terms. Surface properties important influence on compared with those of particles employed in toxicity. experimental systems.

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Comprehensiveness Quality Topic Summary of data available Assessment Data gaps/obstacles Assessment Issues/inconsistencies

11. Impact of NMs UFPs generally more harmful to health than larger Limited understanding of relevance of Wide range of factors affect NM/UFP toxicity and & UFPs on human particles (based on equivalent mass doses). experimental test systems to risk assessment the relative harmfulness of different types of health, the of human health. Little information about nature engineered NMs and UFPs will vary substantially in Combustion generated NMs/UFPs particularly comparison with ambient PM. environment & damaging to health relative to other sources. of environmental or workplace exposure to relevance to climate NPs/UFPs in humans and the associated Wide range of ecotoxicity assays have been forcing Leachable metal content may have a substantial impacts on health. impact on PM toxicity. Pollutants such as PAHs undertaken with NMs/UFPs but these employ may greatly increase toxicity of NPs/UFPs. Little information about environmental fate and simplified test systems that are substantially behaviour of NPs/UFPs. In the natural different from natural waters or soils. It is likely that UFPs damaging to a range of organisms in environment they are likely to be differently the degree of particle aggregation and particle experimental systems and could have significant dispersed and have different surface properties surface properties differ substantially between the adverse effects on biodiversity with consequences to those used in test systems. idealised conditions of test systems versus the for water and soil quality. NPs may have substantial impacts on natural environment. This substantially limits the predictive power of laboratory assays for Atmospheric UFPs may directly affect atmospheric atmospheric warming or cooling, cloud understanding toxic effects in the wider absorbance or reflection of heat (depending on formation and rainfall but there is no consensus environment. type). They can have indirect temperature effects as to the likely net effect of atmospheric through promoting cloud formation and affecting NMs/UFPs on climate. Models of weather and climate are extremely cloud persistence. complex. It is not possible to include all possible variables that may influence weather and climate and small variations in input variables may lead to substantially different predictions of the nature, rate and size of potential climate change.

12. NMs & UFPs Data from epidemiological studies indicating that Paucity of relevant human data. Test materials used in experimental systems not metric(s) (particle mass concentration is a suitable dose metric for Difficulty of separating the relative importance fully described or described in a consistent fashion mass, surface, airborne PM – but not specifically NMs/UFPs. across different studies. of different factors that give rise to toxicity – number) most Limited evidence from epidemiological studies that particle size, surface area, surface properties, Not clear whether particle surface area is an appropriate to particle number concentration may be a suitable, leachable metals content etc – on the basis of appropriate dose metric for all NMs/UFPs. describe dose- possibly better, dose metric. current knowledge. effect relationships Factors governing NP toxicity include surface area, Data from toxicological studies largely suggests surface reactivity, leachable metals and particle particle surface area is an appropriate dose-metric shape and relative harmfulness of different particle but with marked exceptions. types depends on the dose metric employed.

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3.3 Summary

As the table above demonstrates, there are currently a significant number of data gaps preventing the development of a comprehensive description of releases of NMs and UFPs, their environmental behaviour/fate and impacts on health and the environment. The key gaps identified include:

• Very limited data are available on emissions of NMs from industrial sources.

• Limited data are available on emissions of UFPs from industrial sources; the fractionation data used in this study is based on a very small number of sources and there are uncertainties associated with the impacts of different abatement techniques, fuels and processes amongst other factors.

• The behaviour and ultimate fate of these particles in the environment is uncertain.

• There is limited data on the exposure of the population to NMs/UFPs and associated impacts on health and the environment.

Possible options to address these gaps were discussed with stakeholders at the project workshop (June 2011). Remaining gaps and uncertainties as well as possible options for addressing them in the future are presented in Section 5.2. These have been categorised according to the significance of the issue (i.e. how critical is it to understanding the impacts of NMs and UFPs) as well as the ownership (i.e. who should take them forward), timescales, feasibility and possible cost implications.

It should be noted that there is a significant volume of work currently underway in this area which may help to fill some of these gaps. For example, there a wide range of research projects currently underway such as those funded under the Sixth Framework Programme FP6 and Seventh Framework Programme FP731 (see the table below) as well as a significant number supported by EU Member States.

Table 3.2 Ongoing nanomaterial projects funded under the Sixth Framework Programme FP6 and Seventh Framework Programme FP7

Project title Aims and objectives

Engineered Nanoaparticle Impact on Aquatic The aim is to study and relate the structure and functionality of well characterised Environments: Structure, Activity and engineered nanoparticles to their biological activity in the aquatic environment, taking into Toxicology (ENNSATOX) account the impact of the nanoparticles on environmental systems from their initial release to uptake by organisms.

Risk Assessment of Engineered NanoParticles The ENPRA project is a major European Framework 7 project to develop and implement a (ENPRA) novel integrated approach for engineered nanoparticle (ENP) risk assessment.

Engineered Nanoparticles: Review of Health The ENRHES project performed a comprehensive and critical scientific review of the and Safety (ENRHES) health and environmental safery of fullerenes, carbon nanotubes (CNTs), metale and metal oxide nanomaterials.

31 Available from: http://www.nanosafetycluster.eu/home/european-nanosafety-cluster-compendium.html

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Project title Aims and objectives

Health Impact of Engineered Metal and Metal The work of the HINAMOX consortium focuses on metal and metal oxide NPs as Oxide Nanoparticles: Response, Bioimaging potentially dangerous to biological organisms. This project addresses aspects concerning and Distribution at Cellular and Body Leve hazard characterization, human exposure, occupational exposure, and the inflammatory (HINAMOX) and toxicological response to NPs.

Intestinal, Liver and Endothelial Nanoparticle The objective of InLiveTox is to develop a novel modular microfluidics-based in vitro test Toxicity - development and evaluation of a system modelling the response of cells and tissues to the ingestion of NPs. novel tool for high-throughput data generation (InLiveTox)

Development of Exposure Scenarios for The aim of the NANEX project is to develop a catalogue of generic and specific Manufactured Nanomaterials (NanEx) (occupational, consumer and environmental release) exposure scenarios for MNMs taking account of the entire lifecycle of these materials. NANEX will collect and review available exposure information, focussing on three very relevant MNMs: (1) high aspect ratio nanomaterials- HARNs) (e.g. carbon nanotubes); (2) mass-produced nanomaterials (e.g. ZnO, TiO2, carbon black); and (3) specialised nanomaterials that are currently only produced on a small scale (e.g. Ag).

Novel Concepts, Methods, and Technologies NANODEVICE will provide new information on the physico-chemical properties of for the Production of Portable, Easy-to-Use engineered nanoparticles (ENP) and information about their toxicology. Also a novel Devices for the Measurement and Analysis of measuring device will be developed to assess the exposure to ENP´s from workplace air. Airborne Engineered Nanoparticles in The purpose of the project is also to promote the safe use of ENP through guidance, Workplace Air (NANODEVICE) standards and education, implementing of safety objectives in ENP production and handling, and promotion of safety related collaborations through an international nanosafety forum.

Nanoparticle Fate Assessment and Toxicity in This project will investigate the fate and effects of engineered nanoparticles (ENPs) in the the Environment (NanoFate) environment. It will examine post-production life cycles of key nanoparticles, from their entry into the environmental as ‘used products’, through the full range of waste treatment processes to their final fates (destinations in the environment or in organisms) and potential toxic effects.

NANOfutures European initiative for NANOfutures will identify the key nodes in strategic nano-activities and develop strategies sustainable development by Nanotechnologies to address nanotechnology challenges with an intersectorial approach. This will be (NANOFutures) achieved by a close interaction between horizontal working groups, which will address cross-sectorial horizontal issues, and sectorial group representatives (i.e. ETP representatives).

Cycle of Nanoparticle-based products used in This project aims at promoting a responsible and sustainable development of house coating (NanoHouse) nanomaterials in building industry through a Life Cycle Thinking approach.

European Network on the Health and NanoImpactNet is a multidisciplinary European network on the health and environmental Environmental Impact of Nanomaterials impact of nanomaterials. NanoImpactNet will create a scientific basis to ensure the safe (NanoImpactNet) and responsible development of engineered nanoparticles and nanotechnology-based materials and products, and will support the definition of regulatory measures and implementation of legislation in Europe.

Comprehensive Assessment of Hazardous The aim is to establish a panel of read-out systems for the prediction of the toxic potential Effects of Engineered Nanomaterials on the of existing and emerging ENs. Overall, the NANOMMUNE results will enhance the Immune System (NANOMMUNE) understanding of possible adverse effects of nanomaterials and will hopefully contribute to a continuous and sustainable growth of the nanotechnologies.

Toxicological impact of nanomaterials derived The main objective of NANOPOLYTOX is the monitoring of the life cycle of three families from processing, weathering and recycling of of nanomaterials (carbon nanotubes, nanoclays and metal oxide nanoparticles) when polymer nanocomposites used in various embedded in selected polymeric hosts. The project will include monitoring of the chemical industrial applications (NanoPolyTox) and physical properties of the nanomaterials and their toxicity from the synthesis, processing, aging, and recycling to their disposal, covering their migration and/or release during their life cycle.

The Reactivity and Toxicity of Engineered NanoReTox is a 4 year project which started in December 2008. The objectives are to Nanoparticles: Risks to the Environment and identify the potential risks to the environment and human health posed by free engineered Human Health (NanoReTox) (i.e. manmade) nanomaterials.

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Project title Aims and objectives

Development of sustainable solutions for The goal of NanoSustain is to explore, examine and develop new solutions for the Nanotechnology-based products based on sustainable design, use, re-use, recycling and final treatment and/or disposal of specific hazard characterization and LCA nanomaterials and associated products. This will be based on a comprehensive hazard (NanoSustain) characterization and impact assessment of selected environmentally and economically relevant materials products.

Nanomaterials Related Environmental Pollution The main objective of the Project is to identify and rate important forms of Nanotechnology and Health Hazards Throughout their Life Cycle related environmental pollution and health hazards that could result from activities (Nephh) involved in the life cycle of Silicon-based polymer nanocomposites currently used in a variety of industrial sectors and also to suggest means that might reduce or eliminate these impacts.

Do nanoparticles induce neurodegenerative To determine if engineered nanoparticles present a significant neuro-toxicological risk to diseases? Understanding the origin of reactive humans. To assess nanoparticle impacts on oxidative stress and protein fibrillation. To oxidative species and protein aggregation and correlate nanoparticle access to the brain with induction of oxidative stress and/or protein mis-folding phenomena in the presence of fibrillation. To develop a simple screening and risk assessment matrix for nanoparticles in nanoparticles (NeuroNano) neurodegenerative diseases.

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4. Review of relevant EU legislation and supporting documents [Task 5]

4.1 Background

The aim of this review was to assess whether the current legislation related to industrial emissions appropriately addresses the prevention and control of NM and UFP emissions from industrial sources. Specific attention was given to the categories of installations covered, relevant emission limit values (ELVs) and Best Available Techniques Associated Emission Levels (BAT-AELs) from the BREFs and associated metrics.

The specific legislation covered is the Industrial Emissions Directive (IED, 2010/75/EU). This incorporates the previous IPPC Directive (2008/1/EC), as well as other sectoral Directives on industrial emissions, particularly the large combustion plant and waste incineration directives. Consideration has also been given to the BREF documents.

On the basis of this review, a number of possible policy options were identified, which were subsequently discussed with stakeholders at the workshop in June 2011.

4.2 Approach

The approach to the analysis was as follows:

• Using the data developed as part of this study, mapping the levels of emissions from relevant sectors against the activities included in Annex I of the IED to identify the extent of coverage at a sector level or within sectors and any significant gaps in coverage due to sectors not being covered at all or being only partially covered due to the capacity thresholds in the IED.

• In cases where the IED does cover relevant sectors, investigation of whether current and/or proposed future ELVs would also lead to reductions in emissions of NMs and UFPs due to the abatement options expected to be used to comply with these limits. The metrics used for the limits have also been considered.

• A similar approach has been applied, for some of the most significant emitting sectors, in terms of the BAT-AELs within the relevant BREFs.

• Based on the above, a number of possible policy options were identified and discussed with stakeholders at the workshop in June 2011.

• The options were subsequently revised based on feedback received from stakeholders.

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4.3 Coverage of relevant emissions sources by the IED

The table below sets out the estimated emissions from relevant sectors covered under Task 2 and details of any IED activities (Annex I) that may cover these emissions.

Table 4.1 Coverage of main industrial emission sources of NM/UFP by the IED

Emission source Corresponding IED activities Commentary on degree of coverage / gaps (and % share of PM0.1 emission from industrial sources)

Heat and electricity 1.1 Combustion of fuels in installations with a total ELVs for dust set out in IED. production (20%) rated thermal input of 50 MW or more BAT-AELs set out in LCP BREF. Excludes installations below threshold.

5.2 Disposal or recovery of waste in waste ELVs for dust set out in IED. incineration plants or in waste co-incineration plants: BAT-AELs set out in WI BREF. (a) for non-hazardous waste with a capacity Excludes installations below threshold. exceeding 3 tonnes per hour; (b) for hazardous waste with a capacity exceeding 10 tonnes per day.

Petroleum refining 1.1 Combustion of fuels in installations with a total ELVs for dust set out in IED. (5%) rated thermal input of 50 MW or more BAT-AELs set out in LCP BREF. Excludes installations below threshold.

1.2 Refining of mineral oil and gas BAT-AELs for dust set out in refineries BREF.

Iron and steel 1.1 Combustion of fuels in installations with a total ELVs for dust set out in IED. rated thermal input of 50 MW or more production (20%) of BAT-AELs set out in LCP BREF. which: Excludes installations below threshold. Combustion = 8% Process = 12% 2.1 Metal ore (including sulphide ore) roasting or BAT-AELs for dust set out in BREFs on: sintering • Ferrous metals processing. 2.2 Production of pig iron or steel (primary or • Iron and steel production. secondary fusion) including continuous casting, with a capacity exceeding 2,5 tonnes per hour • Smitheries and Foundries. 2.3 Processing of ferrous metals Excludes installations below thresholds. 2.4 Operation of ferrous metal foundries with a production capacity exceeding 20 tonnes per day

Chemical production 1.1 Combustion of fuels in installations with a total ELVs for dust set out in IED. rated thermal input of 50 MW or more (3%), majority of which BAT-AELs set out in LCP BREF. is from combustion Excludes installations below threshold.

4.1 Production of organic chemicals BAT-AELs for particulates set out in BREFs on: • Large volume organic chemicals. • Manufacture of organic fine chemicals. Coverage limited to activities specified in Annex I of IED.

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Emission source Corresponding IED activities Commentary on degree of coverage / gaps (and % share of PM0.1 emission from industrial sources)

4.2 Production of inorganic chemicals BAT-AELs for particulate matter set out in BREFs on: • Chlor-alkali manufacturing industry. • Large volume inorganic chemicals - Ammonia, Acids and Fertilisers. • Large volume inorganic chemicals - Solids and others industry. • Speciality inorganic chemicals. Coverage limited to activities specified in Annex I of IED.

4.3 Production of phosphorous-, nitrogen- or BAT-AELs for dust set out in BREF on: potassium-based fertilisers (simple or compound Large volume inorganic chemicals - Ammonia, Acids and fertilisers) Fertilisers.

4.4 Production of plant protection products or of biocides 4.5 Production of pharmaceutical products including intermediates 4.6 Production of explosives

Pulp and paper (and 1.1 Combustion of fuels in installations with a total ELVs for dust set out in IED. print) (11%) of which: rated thermal input of 50 MW or more BAT-AELs set out in LCP BREF. Combustion = 8% Excludes installations below threshold. Process = 2% 6.1 Production in industrial installations of: BAT-AELs for dust set out in BREF on: (a) pulp from timber or other fibrous materials; • Pulp and paper industry. (b) paper or card board with a production capacity Coverage limited to activities specified in Annex I of IED. exceeding 20 tonnes per day; (c) one or more of the following wood-based panels: oriented strand board, particleboard or fibreboard with a production capacity exceeding 600 m3 per day.

Food Processing, 6.4 (a) Operating slaughterhouses with a carcass Suggested techniques as BAT in the BREF on: Beverages and production capacity greater than 50 tonnes per day • Slaughterhouses Tobacco (4%) of which: 6.4 (b) Treatment and processing, other than BAT-AELs for dust in the BREF on: exclusively packaging, of [various] raw materials, Combustion = 2% • Food, drink and milk industries. whether previously processed or unprocessed, Process = 2% intended for the production of food or feed.6.4 (c) Treatment and processing of milk only, the quantity of milk received being greater than 200 tonnes per day (average value on an annual basis).

Minerals and others (34%), of which:

Combustion = 20% 1.1 Combustion of fuels in installations with a total ELVs for PM set out in IED. rated thermal input of 50 MW or more BAT-AELs set out in LCP BREF. Excludes installations below threshold.

Process emissions 3.1 Production of cement, lime and magnesium BAT-AELs set out in BREF on cement and lime oxide: from lime production = Excludes installations below threshold 1% (b) production of lime in kilns with a production capacity exceeding 50 tonnes per day;

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Emission source Corresponding IED activities Commentary on degree of coverage / gaps (and % share of PM0.1 emission from industrial sources)

Road paving with None Not covered asphalt = 12%

Metals (4%) of which: 1.1 Combustion of fuels in installations with a total ELVs for PM set out in IED. rated thermal input of 50 MW or more NFM combustion = 2% BAT-AELs set out in LCP BREF. Process emissions Excludes installations below threshold. from aluminium production = 2% 2.5 Processing of non-ferrous metals BAT-AEL for dust in BREF on non-ferrous metals industries Excludes installations below threshold.

Emission sources are based on data from Task 2, as described in Section 2.3.

Based on the above, there generally appears to be fairly good coverage of the types of industries responsible for emissions (putting actual control of NM/UFP emissions to one side for now) by the industrial emissions legislation. Areas where there are noticeable gaps include:

• Installations below the relevant thresholds in Annex I of the IED. There is insufficient information to estimate the proportion of emissions that may come from such installations.

• Whilst there are BAT-AELs for dust/PM for a wide range of sectors (which are to be used by Competent Authorities as the basis for setting permit limit values for individual installations), there are only binding minimum ELVs for large combustion plants and for waste incinerators, although the former at least may be present at installations undertaking various other activities, as is shown above.

• It must be remembered that the IED contains a certain level of flexibility so that in certain cases emissions may be higher than BAT-AELs. Details are provided under Article 15(4) of the Directive.

• Road paving with asphalt seems to be a significant source based on the emissions inventory and one which is not covered by the IED.

• There are also several emissions sources where there is insufficient information to reliably estimate the level of coverage, particularly where the emission source covers a wide range of different industry types that are not specified in the source data (such as in the mineral industry).

4.4 Coverage of emissions by ELVs and BAT-AELs for sectors where the IED does apply

4.4.1 ELVs, BAT-AELs and compliance techniques

Based on the data in the previous section, the table below sets out the relevant ELVs in the IED as well as some of the relevant BAT-AELs (which are to be used by Competent Authorities as the basis for setting permit limit values for individual installations) for the sectors contributing most to total industrial emissions of PM0.1 (over 5% from

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the table above). It also includes examples of the types of techniques typically used to comply with the ELVs and BAT-AELs. Following the table, some commentary is provided on the extent to which these limits are expected to lead to reductions in emissions of NMs and UFPs.

Table 4.2 Extent to which IED emission limit values are likely to cover NM/UFP emissions for main sectors

Sector ELV / BAT-AEL Examples of compliance techniques

Heat and electricity production (and ELVs = 5-30 mg/m3 depending on ESPs various other sources as set out in Table LCP and fuel type (Annex V of Fabric filters 4.1) IED) Combined with wet FGD in some cases. 1.1 Combustion of fuels in installations with a BAT-AEL = 5 - 30 mg/m3 total rated thermal input of 50 MW or more depending on LCP and fuel type. Preventative measures such as primary engine measures, low-ash and low-sulphur fuel in some cases

5.2 Disposal or recovery of waste in waste ELVs = 0-30 mg/m3 (0-50 mg/m3 Overall flue-gas treatment system, combined with the incineration plants or in waste co-incineration for co-incineration) installation as a whole. plants BAT-AELs = 1-20 mg/m3 Fabric filters to give the lower levels within these ranges. Effective maintenance of dust control systems.

Petroleum refining BAT-AEL = 5-50 mg/m3 depending ESPs on process 1.2 Refining of mineral oil and gas Fabric filters Wet scrubbing Cyclones Preventative/primary measures (e.g. covered conveyors, enclosed loading areas, reduced fuel consumption, increased use of gas)

Iron and steel production BAT-AELs = 1-50 mg/m3 Fabric filter 2.1. Metal ore (including sulphide ore) Ceramic filter roasting or sintering installations. Wet ESP

2.2 Installations for the production of pig iron BAT-AELs = 0-20 mg/m3 Fabric filter or steel (primary or secondary fusion) Cyclones including continuous casting, with a capacity exceeding 2,5 tonnes per hour. ESPs / wet ESPs Covered runners, fume suppression, capture displaced air during loading, wetting of storage heaps, etc.

2.3. Installations for the processing of ferrous BAT-AELs = 0-50 mg/m3 Fabric filters metals Recycling collected dust Enclosed equipment, extraction hoods Good housekeeping

2.4 Ferrous metal foundries with a BAT-AELs = 5-20 mg/m3 Enclosed equipment production capacity exceeding 20 tonnes per day.

Pulp and paper (and print) BAT-AELs = ESP 6.1 Production in industrial installations of (a) 0.03-0.5 kg/tonne product pulp from timber or other fibrous materials; 0-40 mg/m3

6.1 Production in industrial installations of (b) BAT-AELs = 0-40 mg/m3 ESP paper or card board with a production capacity exceeding 20 tonnes per day;

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Sector ELV / BAT-AEL Examples of compliance techniques

Minerals and others BAT-AELs = 0-20 mg/m3 Dry exhaust gas cleaning with a filter 3.1. Installations for the production of cement Fabric filter clinker in rotary kilns with a production ESP capacity exceeding 500t/day or lime in rotary kilns with a production capacity exceeding Wet scrubber 50t/day or in other furnaces with a production capacity exceeding 50t/day.

3.3. Installations for the manufacture of glass BAT-AELs = 0-50 mg/m3 Cutting under liquid including glass fibre with a melting capacity Electrical melting exceeding 20 tonnes per day. Bag filters Wet scrubbing Wet ESP Stone wool filter Minimising loss of coating products Various other techniques

3.4. Installations for melting mineral BAT-AELs = 0-50 mg/m3 Wet ESP substances including the production of Bag filter mineral fibres with a melting capacity exceeding 20 tonnes per day. Raw material modifications Electric melting

3.5. Installations for the manufacture of BAT-AELs = 0-50 mg/m3 Bag filters ceramic products by firing, in particular Cascade-type packed bed adsorbers roofing tiles, bricks, refractory bricks, tiles, stoneware or porcelain with production Use of low ash fuels capacity >75t/d, and/or with kiln capacity Minimising dust formation caused by changing of ware to >4m3 and setting density/kiln >300kg/m3 be fired in kiln Cyclones ESPs

It is clear from the above that the levels at which BAT-AELs are typically set are generally fairly similar across the various industry sectors and emission sources. Likewise, the compliance techniques used to comply with ELVs or to achieve the BAT-AELs are typically similar across the different sectors, although there are some sector/process- specific techniques that also apply.

It is then important to consider whether the techniques expected to be applied to reduce emissions under the industrial emissions legislation are also expected to be effective in reducing emissions of NMs and UFPs. The effectiveness of a range of emissions abatement techniques was considered in Section 2.7 and Appendix A4 of this report. Taking some of the most frequently occurring measures from the table above, the following broad conclusions can be drawn.

• There are various primary/preventative measures that are expected to be employed, such as low ash/sulphur fuels, enclosed systems, wet cutting/processing and reduced fuel consumption. It seems reasonable to assume that these will generally act to reduce UFP emissions as well as coarser fractions.

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• Fabric filters can have efficiencies of 99% by mass for particulates in general. Efficiency generally drops with decreasing particle size, although the UFP collection efficiency of fabric filters as a function of size is not known.

• Electrostatic precipitator (ESP) abatement efficiencies range from 90% to 99.9%. Collection efficiency is significantly lower for UFP (e.g. reduction of 10μm particles is typically at least an order of magnitude greater than for 0.1 to 1.0μm particles). Most significant penetration (reduced abatement) has been observed for particles smaller than 50 nm. However, wet ESP – which is BAT for several sectors – can reportedly precipitate both fine and ultrafine particulate matter (with reductions reported at around 90% down to around 50nm, but declining below that diameter). Several manufacturers report achieving abatement efficiency over 99% on particles down to 10 nm.

• Wet scrubbers tend to have a reduction in abatement efficiency below around 5μm but the level of abatement is still substantial at many size ranges down to the ultrafine level. Abatement efficiency also seems to vary according to the type of wet scrubber used. Charged wet scrubbers – which are used commercially in a number of sectors – have reportedly been shown to be capable of removing particles between 100 and 2,500 nm at efficiencies of >99% and UFPs as small as 10 nm can be effectively treated.

• The collection efficiency of cyclones generally drops for particles below 100 nm, though very high speed or low pressure cyclones may reportedly be used for collection of NMs. Advanced cyclones can reportedly be more effective at reducing emissions, such as axial flow cyclones operated at low pressures, which can reportedly achieve efficiencies close to 100% for 100 nm size range, with a 50% cut-off size of 50 nm.

Based on the above, it seems that, for sectors where industrial emissions legislation covers the sectors/sources responsible for emissions, there are generally techniques that are expected to be applied – to achieve ELVs or BAT – that, whilst targeted at dust in general, are also likely to have an effect on NMs and UFPs. For some of the techniques, it seems that the abatement efficiency for UFPs is somewhat lower than that for coarser particles, although the extent of this varies amongst the techniques. It also appears that there is increasing use of more advanced abatement techniques – such as wet ESPs and charged wet scrubbers – which seem to have more comparable abatement efficiencies for smaller particles.

As set out in Appendix A4, there are also various other techniques that are at earlier stages in their development and deployment which would be capable of achieving further reductions in NM/UFP emissions.

4.4.2 Coverage within the BREFs

There is currently limited coverage of NM/UFP in the majority of the BREFs, although there are some instances in which there is mention of relevant issues, including:

• The 2009 draft of the cement, lime and magnesium oxide BREF and also the LCP BREF mention that ESPs are very efficient devices for collecting UFPs (<0.5µm) providing the particles have the ability to agglomerate.

• The 2009 draft of the glass manufacturing industry BREF makes reference to advanced ESP capable of reducing emissions of particles below 2,000nm. The EIPPCB indicate that the issue of NM and

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UFP is not specifically/explicitly addressed in the BREF and that no distinction has been made between different size particles.

• The waste incineration BREF mentions that ionisation wet scrubbers have high deposition efficiency for particulates in the submicron as well as the micron range and indicates that fabric filters’ efficiencies are reduced at particle sizes below 0.1 microns, but the fraction of these that exist in the flue-gas flow from waste incineration plants is relatively low.

• The mineral oil and gas refineries BREF indicates that ESP are capable of collecting very fine particulates (<2 μm) at efficiencies of 95%.

• The smitheries and foundries BREF mentions that bag filters can achieve good efficiencies for controlling fine PM from melting operations with sub-micron particles also being separated.

The EIPPCB has indicated that there are no specific provisions in a number of BREFs for NM/UFP (pulp and paper; tanneries; refineries and LCPs).

Overall, the current level of coverage of NM and UFP within the BREFs is limited, although there is some mention of the effectiveness of techniques in reducing sub-micron size particles. However, this is perhaps not surprising given that there has been no regulatory focus in contrast to the broader size fractions (PM2.5, PM10) and given the level of available evidence on differences in health effects at lower size fractions compared to effects from broader size fractions.

4.4.3 Metrics

Based on the information in Table 4.2, it is clear that the ELVs and BAT-AELs are almost all based on units of mass concentration (mg/m3), with a small number based on mass emissions per unit of production. As discussed in Section 2.12, a metric based on mass concentration may not necessarily be the most appropriate for monitoring NM/UFP emissions although this is primarily linked to the ability to consider population exposure and health impacts. Any attempt to set limits for releases of NMs/UFPs from industrial sources in the future would have to consider this further.

4.5 Identified gaps in coverage

4.5.1 Sector coverage

In general, based on the inventory of emissions produced for this study, there appears to be good coverage of the major industrial sources of NM/UFP emissions by the IED.

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Another significant gap could be for combustion installations where the directive only includes installations with a capacity greater than 50MW32. A study for the Commission developed to support the revision of the IPPC

Directive found that plants <50MW contributed 18% of total PM10 emissions from industrial combustion across Europe (EU25 at the time)33. Whilst the Commission’s original proposal for the IED included a change in the threshold from 50MW to 20MW this was removed during the co-decision process. However, a clause was included under Article 73(2)(a) requesting the Commission to review the need to control emissions from these activities.

Furthermore, despite there being a good level of disaggregation of sectors within the inventory, there remains some uncertainty as to the proportions of emissions that occur from within specific sub-sets of the sources concerned (for example, within the category of ‘other mineral products’ from above). This is a limitation on identifying the degree of coverage of emissions by current industrial emissions legislation.

4.5.2 Gaps in coverage based on techniques applied

This aspect relates to whether, for those sources of emissions where industrial emissions legislation does apply, the practical steps taken to reduce emissions will have an impact on reducing emissions of NM/UFP.

32 Although some of these installations (and units) may already be covered by the Directive where the aggregated capacity on site is more than 50 MW or if they are "directly associated activities with a technical connection" to other IPPC activities.

33 AEAT (2004): Costs and environmental effectiveness of options for reducing air pollution from small-scale combustion installations, Final report to the European Commission, November 2004.

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4.6 Policy options

Within the scope of this project, an assessment of policy options was undertaken to address any potential gaps in the coverage of industrial emissions legislation as concerns emissions of NM/UFP, specifically in relation to factors such as activities not covered and the metrics and levels at which ELVs/BAT-AELs are set. A shortlist of possible options was developed and presented at the stakeholder workshop for discussion. This included:

• Extending the coverage of the industrial emissions legislation to activities below the current thresholds so as to capture additional emissions of NM/UFP. This includes combustion installations with a rated thermal input below 50 MW but could also include other sectors with thresholds such as iron and steel; pulp and paper; and minerals. In this context, the uncertainties in the current estimates of emissions from each of these sectors should be taken into account (i.e. it is not currently known whether installations below the thresholds contribute a significant amount to total emissions).

• Ensuring specific consideration within the BREF review process of NM/UFP, including their emissions, what constitutes BAT in reducing such emissions and techniques to reduce those emissions.

• Including additional binding minimum ELVs within the IED (and/or BAT-AELs in the BREFs) to address those sectors where there are potentially significant emissions of NM/UFP, specifically based on metrics that are appropriate for NM/UFP, as opposed to the mass-based metrics currently used. This could cover sectors where ELVs are already in place (mainly LCPs and waste incinerators) or other sectors where there are no EU-wide ELVs but which constitute a significant source of NM/UFP emissions.

4.7 Conclusions

Stakeholders agreed at the workshop that the evidence gaps and uncertainties are currently too high to consider making any changes to the legislation in the short term e.g. introducing ELVs for NMs/UFPs. Key knowledge gaps and/or uncertainties relate to the level of emissions of UFPs from different sources including the impacts of abatement technology, the ability to accurately and consistently monitor these emissions in industrial sites as well as the fate of these particles in the environment. These need to be better understood before considering any legislative changes.

At this stage, it was agreed that an appropriate way forward could be for the BREF review process to consider the inclusion of information regarding impacts of techniques on PM10, PM2.5 and PM0.1 emissions, where available and appropriate. Whilst this has already been done in some instances, it has not been required as such and therefore has not been considered more widely. This would presumably only apply where techniques to reduce dust emissions are already reported.

As the knowledge base improves there may be a need to revisit the current scope and effectiveness of the legislation with respect to NMs/UFPs.

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5. Conclusions

5.1 Conclusions

Emissions

Literature on emissions of UFPs is dominated by studies undertaken on road transport activities, and there is currently limited information in emissions from specific industrial sources. Quantitiative estimates of PM0.1 have been made using data for PM10 and PM2.5 (from LRTAP and E-PRTR) and fractionation data from a range of sources. Industrial combustion was found to be more important than industrial processes in terms of total UFP emissions, but dividing industrial emissions into combustion and process emissions is uncertain due to the quality of PM10 emissions reporting under the LRTAP Convention.

An estimated breakdown of industrial sources of UFP emissions (expressed as PM0.1) suggested that minerals; iron and steel; heat and electricity production; and paper and pulp are likely to be the most significant industrial sources. Whilst it has been possible to collate and present emissions information, variations in the particle size distribution between industrial sectors and activities are high in uncertainty. Recommendations are provided in the section below which would help to improve the accuracy of PM0.1 emissions estimates.

It was not possible to develop quantitative estimates of atmospheric releases of (engineered) NMs due to insufficient data in the literature. However, an overview of industrial source sectors likely to be the largest users of NMs found that: coating and adhesives; food packaging and catalytic converters all use over 10,000 tonnes of NMs per year. Information on the potential for emission from the different uses of NMs is limited, largely because in-situ monitoring of NMs is very limited. As a consequence, most information on emissions potential is theoretical rather than measurement-based.

Abatement

In terms of abating dust emissions there exists a wide range of abatement techniques. Whilst these are, in a regulatory context, focussed on removing coarser fractions, they also appear to have a significant effect in reducing emissions of NM/UFP, albeit with varying levels of efficiency.

Techniques including fabric filters, electrostatic precipitators and scrubbers – some of which are BAT according to the BREFs – have been shown to abate emissions of NM/UFP. There are a number of advanced or more specialist techniques – for instance the Cloud Chamber Scrubber – that are aimed specifically at controlling emissions of smaller particle size and have been shown to achieve higher levels of emissions reduction (~90%). So far, these have been used in a limited number of commercial installations or are still under development.

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Processes affecting NM/UFPs in air

Several processes have been identified as exerting an influence on UFPs after they are emitted to the atmosphere, including: evaporation, condensation, coagulation, chemical reactions and deposition. These processes will affect their environmental fate (refer to Section 2.8 for further details). There are very few direct measurements available relating to engineered NMs as the majority of focus so far has been on road traffic emissions which will not necessarily be representative of engineered NMs or of emissions from industrial sources.

Metrics

The factors that govern NM toxicity include particle surface area with modifying factors for surface reactivity, leachable metal content and particle shape, amongst others. A complex exposure metric incorporating all these factors would be highly impracticable to measure and any exposure metric developed for NMs would have to recognise the variable toxicity of particles of differing size, shape and composition.

The results of a number of toxicological investigations suggest that particle surface area is a health-relevant measure of NM concentration, for a range of particle types. There are limited epidemiological data that suggest particle number counts may be a more health-relevant measure of dose than mass, although numerous studies have demonstrated dose-response relationships based on mass concentrations of PM2.5 and PM10. Information about particle size is important and measuring exposure to different size categories e.g. PM0.1, PM1, PM2.5 and PM10 would help to further understand the risks.

The gravimetric determination of PM1 would provide useful information about UFP exposure, even in the absence of particle number counts. Further epidemiological investigations of health effects that are linked to side-by-side measurements of concentrations of PM2.5/PM10 and other PM dose metrics would also significantly enhance understanding in this area.

The size distribution and particle surface properties of NMs are likely to be modified by residence in air and the particle population at any location would include particles of a range of size and composition from a range of sources. These factors would not be readily captured by any standard measure of dose.

Measurement techniques and “fingerprinting”

There are well established techniques for measuring UFPs and NMs such as ELPI, MOUDI and SMPS. However, there is currently little or no routine monitoring of NMs and UFPs taking place at industrial installations. Most measurements to date have been conducted in laboratory settings and many of the techniques are not yet suitable for the realisation of systematic on-line monitoring. However, this is a rapidly developing area and further refinements are likely to occur in the near future.

It is important to recognise that there are certain characteristics that must be taken into account in the measurement of nanoparticulate materials (such as particle morphology and chemical composition). These characteristics may often be determined – or at least affected – by their source. The apportioning of emissions to particular sources is described in this report as “fingerprinting”. Whilst there are some examples of individual plants determining the contribution of UFP to ambient levels nearby, significant additional work would be required to use fingerprinting

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operationally in a regulatory context. In particular, better understanding of the environmental fate and behaviour or NMs/UFPs would be needed if such an approach were to be adopted.

Human Exposure to NMs/UFPs

There are few measurement data describing the exposure of the EU population to UFPs in ambient air and no information about potential exposure to engineered NMs has been identified. Projects undertaken within the EU Framework Programmes 6 and 7 and to support the development of air quality policy within the EU have played an important role in developing understanding between emissions sources and population exposure to PM10 and PM2.5 in Europe, but these initiatives have not specifically considered population exposure to UFPs/NMs to date.

Based on existing atmospheric modelling and monitoring it is clear that emissions from elevated stacks at industrial sources affect ground-level concentrations over a wide area but that these have a relatively small influence on ground-level concentrations at any location. In contract, vehicle emissions have a disproportionately greater impact on ground level concentrations in urban areas in relation to the total particle mass emitted. In addition, based on the emission estimates produced as part of this study, PM0.1 emissions from road transport and other mobile machinery appear to contribute significantly more to total PM0.1 emissions than PM10 emissions (as a proportion of total emissions). It therefore seems likely that population exposure to UFPs in ambient air is dominated by primary and secondary particles originating from traffic emissions rather than industrial sources.

An attempt has been made to crudely estimate population exposure to UFPs across Europe based on the emissions estimates developed as part of this study, combined with existing data on exposure to PM10. These are described in Section 2.9. However, it should be noted that there are considerable uncertainties in these estimates.

Health and environmental impacts of NMs and UFPs

There are few studies of the impacts of engineered NMs and UFPs on human health and no (identified) studies of their impacts following exposure in ambient air. Atmospheric UFPs/NMs are likely to have a disproportionately greater adverse impact on human health than coarser particles within the PM2.5/PM10 size range but the toxicity of

PM2.5/PM10 cannot be wholly attributed to the finest fraction. Metals play an important role in enhancing the toxic effects of inhaled particles and the toxicity of UFPs/NMs from different sources with different compositions is likely to be highly variable.

The potential health impacts of engineered NMs are likely to vary substantially by particle type for a given level of exposure. The overall impact of releases of engineered NMs to the atmosphere will depend on the exposure levels and the relative abundance of different types of NMs in emissions. The review of available literature has highlighted a number of gaps in knowledge that limit the extent to which the human health effects of exposures to UFPs/NMs in ambient air can be predicted. These are outlined in Sections 2.10 and 2.11 and discussed further in the section below.

In terms of environmental impacts, there are substantial data indicating that engineered NMs can cause adverse effects in aquatic and terrestrial organisms in experimental systems. The relative toxicity of NMs varies substantially by particle type, particle size and whether particles have modified surfaces. The relevance of

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experimental systems to the prediction of effects in the wider environment is uncertain as NM properties are likely to be substantially modified by interactions with substances present in natural waters and soil. It seems plausible that NMs in the environment could adversely affect biodiversity and indirectly affect water and soil quality through their toxicity to micro-organisms in soil, natural waters and during waste water treatment. The impact of UFP/NM emissions on weather and climate are highly uncertain but potentially important and could contribute significantly to global climate change but not necessarily to warming. There are significant obstacles in predicting the environmental impacts of NMs, however there is a large body of work currently being conducted in this area (see Section 2.11).

Industrial Emissions Directive Review

A review of the Industrial Emissions Directive and BREF documents was undertaken to identify potential gaps in coverage with respect to emissions of NMs/UFPs. A series of potential policy options were developed based on the outputs of this review. The potential policy options (see Section 4.6) were presented to stakeholders at the project workshop in June 2011. Discussions with stakeholders led to the conclusion that, in light of the significant uncertainties and data gaps that currently exist, it is not appropriate to make any changes to the legislation at this stage.

As the knowledge base improves there may be a need to revisit the current scope and effectiveness of the legislation with respect to NMs/UFPs.

5.2 Key uncertainties/limitations and options for further work

This section provides an assessment of the key uncertainties/ limitations identified during the study and presents possible options for further work. These have then been prioritised according to:

• Significance – how significant are the data gaps/obstacles in terms of understanding emissions of NMs and UFPs and their impact on human health and the environment as well as potential for achieving improved control of risks; and

• Feasibility – bearing in mind possible cost implications, timescales for implementations and current status of research developments, how feasible are the options?

The assessment is summarised in the table on the following page.

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Table 5.1 Assessment matrix

Key:

Overall Significance Priority Significance Feasibility L M H

H High significance Highly feasible L Low Low Medium

M Medium significance Potentially feasible M Low Medium High

L Low significance Not currently feasible Feasibility H Medium High High

Uncertainties/ limitations Possible options to address issues Overall Significance Feasibility Level of effort Ownership priority

Limited data are available on emissions of UFPs Undertake a programme to determine the variability High. from industrial sources; the fractionation data of PM fractionation across stationary combustion This would require a European used in this study is based on a small number of sources using the same fuel type Commission, H H High sizeable and high studies and there are uncertainties associated quality measurement MSs, research with the impacts of different abatement campaign to be institutions techniques, fuels and processes amongst other undertaken.

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Uncertainties/ limitations Possible options to address issues Overall Significance Feasibility Level of effort Ownership priority factors. Undertake a programme of co-ordinated Very high. measurement and modelling to evaluate the size This would require a fractionation of PM10 from a range of process sizeable source and European emissions Commission, H M High ambient measurement campaign to be MSs, research undertaken, and the co- institutions ordination with modelling capabilities.

Very limited data are available on emissions of Conduct theoretical and measurement-based H M NMs from industrial sources assessments of the emission potential for the This is the next Feasible, but industrial processes identified in this report. This step required would be high in information can then be combined with activity data European to generate uncertainty and for each of the sectors to arrive at emissions Medium (modelling and Commission, some first, would required High estimates desk-based study) MSs, research indicative, tailored institutions emission techniques to estimates of specific NMs. engineered NMs

There are well established measurement Trial existing measurement techniques in industrial Medium – a lot of work Industry / MSs / techniques but most are not suitable for installations H H High is going on in this area European systematic, on-line, continous monitoring already Commission

The limited availability of information on the NM Encourage further work and dissemination of M and UFP abatement efficiency of different results on efficiency of abatement techniques This will measures has restricted the ability to compare depend on data sets to establish a consensus or to evaluate recommendati Medium – some work is Industry / MSs / consistency between sources. ons resulting H High going on in this area European from more already Commission detailed emissions measurements

There is limited data on the exposure of the The acquisition of measurement data to enable European Medium – some work is population to NMs/UFPs characterisation of exposure of the EU population Commission, H H High going on in this area to NMs/UFPs MSs, research already institutions

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Uncertainties/ limitations Possible options to address issues Overall Significance Feasibility Level of effort Ownership priority

The combination of measurement and modelling European studies to better understand the link between Commission, H H High High emission sources and exposure. MSs, research institutions

There are a number of gaps in knowledge that More experimental data would help to better limit the extent to which the human health effects understand: of exposures to NMs in ambient air can be • The role of particle aggregation in modifying predicted toxicity; • The effects of absorption of species typically present in ambient air on particle toxicity; Resarch H M High Medium institutions • The relationship between particle size, shape and composition and toxicity, particularly in relation to ambient PM; and • The relative toxicity of different types of widely used NMs in relation to different fractions of ambient PM.

More epidemiological data would help to better understand: • The differences in potency and effects associated with different fractions of ambient PM and to better Resarch separate the effects of size versus composition; H M High High institutions and • The relationship between potency and particle size when dose is expressed in metrics of surface area or particle number count as opposed to mass.

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Uncertainties/ limitations Possible options to address issues Overall Significance Feasibility Level of effort Ownership priority

The major source of uncertainty in predicting the Further research into: environmental impacts of NMs is the lack of data • The fate of NMs in air, water, soil and during and the limited utility of models or experiments in waste handling and characterisation of the actual the prediction of impacts in highly complex exposures experienced by natural ecosystems; natural systems Resarch • The impact of changes in NMs during H L Medium High environmental transport on their ecotoxicity; and institutions • The extent to which effects observed in simple laboratory experiments are reproduced when experiments are conducted within more complex systems that are more similar to real environments.

There are uncertainties in interpreting the results Further research into: of laboratory investigations of toxicity in plants • The role of particle size as well as composition in and aquatic organisms determining toxicity; Resarch • The impact of particle aggregation on apparent M M Medium Medium toxicity; and institutions • The modification of the toxic potential of particles through interactions with other substances that are typical present in natural environments

Major sources of uncertainty in the prediction of Continuing research into the relationship between climate impacts of NMs include a limited emissions, particle loadings and impacts on heat understanding of the fate of NMs emitted to the transmission through the atmosphere Resarch atmosphere and the complex factors that H L Medium High institutions determine whether NMs contribute to the formation of condensation nuclei and cloud formation

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