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AGRICULTURAL EMISSION FACTORS OF PARTICULATE MATTER AND NON-METHANE VOLATILE ORGANIC COMPOUNDS FOR SWITZERLAND

Part.5 Inventories and environmental assessment

AGRICULTURAL EMISSION FACTORS OF PARTICULATE MATTER AND NON-METHANE VOLATILE ORGANIC COMPOUNDS FOR SWITZERLAND

BÜHLER, M.1, KUPPER, T.1

1 Bern University of Applied Sciences School of Agricultural, Forest and Food Sciences, Switzerland

ABSTRACT: Within the framework of the Gothenburg Protocol of the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP), Switzerland is committed to report the current emissions. The EMEP/EEA air pollutant emission inventory Guidebook 2016 provides a basis for the calculation. For the section 3.B (Manure Management), we conducted a literature study on emissions of particulate matter (PM) and non-methane volatile organic compounds (NMVOC). Based on the results, we present an overview on recently published PM emission factors (EFs) for dairy cattle and a procedure for deriving EFs for total suspended particles (TSP), PM10 and PM2.5 which includes gap filling where the data basis is incomplete. The suggested EFs for the PM fractions are up to eleven times smaller than the values listed in the Guidebook. Furthermore, we discuss questions arising with currently used EFs for PM and NMVOC.

Keywords: Emission Factors, Particulate Matter, NMVOC, Dairy Cattle, Inventory

INTRODUCTION: European countries are committed to report their current emissions within the framework of the Gothenburg Protocol of the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). In the scope of the review 2016, the EMEP emission centre CEIP made miscellaneous suggestions to improve Switzerland’s inventory, especially in the agricultural sector. Therefore, we were commissioned to suggest appropriate emission factors (EFs) for the inventory section 3.B Manure Management. The parameters to be included are non-methane volatile organic compounds (NMVOC) and particulate matter (PM) with the fractions total suspended particles (TSP), PM10 and PM2.5. Here, we suggest updated EFs for dairy cows based on a literature review and a method to derive EFs based on published data in case of gaps therein. Further, we shortly list open questions related to the EFs of NMVOC.

2. RESULTS AND DISCUSSION: Based on a review of selected peer review papers and reports, we present current experimental data with a focus on PM and suggest a procedure on the determination of (TSP, PM10, PM2.5) where the data basis exhibits gaps.

It cannot be considered as an exhaustive review which includes all publications potentially contributing to the topic.

Particulate Matter: An overview of studies providing EFs from seven different countries categorised according to housing systems is given in Table 1. We discovered limits, gaps or inconsistencies in most of the studies. For example, Takai et al. (1998) simply measured TSP and respirable dust and some measurements were conducted during winter only. Moreover, the results were not background corrected and might therefore be too high. Schrade et al. (2017) produced the unique measurements results for Switzerland. This study included six different houses where diurnal and seasonal variations were assessed. However, only PM10 was measured. Mosquera et al. (2010)

Inventories and environmental assessment

measured all size fractions of interest but the TSP values were not background corrected. The findings from Winkel et al. (2015) are based on the measurements of Mosquera et al. (2010) but for unknown reason the emission factors differ by a factor of up to four. Due to time issues, no quality assignment was done for Hinz et al. (2007) and Heidenreich et al. (2008). The findings from Schmidt et al. (2002), Goodrich et al. (2002, 2003), Henseler-Passmann (2010) and Joo et al. (2013) were excluded since they were conducted in housing systems or under climatic conditions which were not comparable to Switzerland.

Table 1. Overview of the literature reporting emission factors (EFs) for particulate matter (PM). TSP (Total Suspended Particle), TH (Tied-housings), LH (Loose-housings), CS (Cubicles with a production of slurry),

CSSM (Cubicles with a production of slurry and solid manure), DL (Deep litter).

Housing

Henseler-Passmann 2010 cited in Schrade et al., - 0.076* -

Schrade et al., 2017 - 0.234 -

* EFs were provided as per livestock unit (500 kg life weight). For the conversion to animal head 650 kg life weight per dairy cow was used.

Used to calculate transformation factor for PM2.5 from PM10.

Used to calculate transformation factor for TSP from PM10.

The EFs listed in the Guidebook are the average of the two EFs from Takai et al. (1998) and for the conversion from livestock unit to animal head an average weight of 600 kg per dairy cow was used. As described above, Takai et al. 1998 provided TSP values only

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in a loose-housing and conflict with the measurements of Takai et al. (1998). The share provided by Seedorf and Hartung (2001) of 30% of PM2.5 relative to TSP is equal to the respirable dust (PM5) share of TSP measured in Takai et al. (1998), which is implausible.

Other conversions should not be used as they contain EFs that are not background corrected (e.g. Mosquera et al., 2010, Winkel et al., 2015).

As we were commissioned to do derive a set of EFs for dairy cattle in Switzerland, we present a possible solu—on: we used the average of selected shares (see footnote † and

‡ in Table 1) which resulted in a transforma—on factor of 3.34 from PM10 to TSP and of 0.23 from PM10 to PM2.5. Our derived EFs for loose-housings based on the PM10 value from Schrade et al. (2017) were used to generate EFs for tied-housings. This was done using a transformation factor of 0.43 which is based on the measurements of Takai et al.

(1998) and a conversion given in Vonk et al. (2016). The EFs for loose-housings and tied-housings were then aggregated according to their occurrence for dairy cattle in Switzerland in the year 2010. Our calculations resulted in an EF of 0.53, 0.16 and 0.04 kg head-1 a-1 for TSP, PM10 and PM2.5, respectively. The derived EFs are four to eleven times smaller than those listed in the EMEP/EEA Guidebook 2016. The question arises which option is more adequate for the calculation national emission inventories: (i) adoption of EFs as given in the Guidebook or (ii) determination of country specific EFs as shown here.

Non-methane volatile organic compounds: Data from our literature study suggest that the data basis on EFs for NMVOC is scarcer than for PM. Individual compounds investigated in the studies varied widely. This is due to the complexity of analytical issues which required for a selection of compounds according to the availability of analytical methods applicable at the investigating institutes. Most of the studies were carried out at a laboratory scale instead of investigations at a field scale. Also, the focus of most studies was rather on odour and odorous emissions than on total NMVOC emissions. Therefore, we see at the moment no other option than to adopt the EFs listed in the Guidebook for the calculation of a national emission inventory.

3. CONCLUSION: Our literature study revealed that the data basis for EFs of PM and NMVOC is scarce in general. It includes gaps and inconsistencies and the reported EFs differ widely between studies and countries. We derived EFs based on data for PM10

measured in Switzerland being at 0.53, 0.16 and 0.04 kg head- 1a-1 for TSP, PM10 and PM2.5, respectively. These EFs are lower by a factor of four to eleven than those listed in the Guidebook. We think that the numbers in the Guidebook are at the high end of reported values. It can be discussed, whether it is best practise to use country specific EFs as shown here or to apply the EFs listed in the Guidebook in spite of the identified inconsistencies

Acknowledgements. The Federal Office for the Environment for their financial support.

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EMEP/EEA Guidebook: EMEP/EEA air pollutant emission inventory guidebook 2016:

Technical guidance to prepare national emissions inventories Part B - sectoral

Inventories and environmental assessment

guidance chapters, 3.B Manure management 2016, 21st ed., European Environment Agency EEA, Copenhagen, Denmark, 2016.

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Schrade, S., Zeyer, K., Emmenegger, L., and Keck, M.: Konzentrationen und Emissionen von PM10 aus sechs freigelüfteten Milchviehställen mit Liegeboxen und Laufhof, LANDTECHNIK - Agricultural Engineering, 72, 101–119, doi:10.15150/lt.2017.3157, 2017.

Seedorf, J. and Hartung, J.: Ein Vorschlag für die Berechnung staubförmiger Partikelemissionen aus Stallen der Nutztierhaltung, DTW. Deutsche tierärztliche Wochenschrift, 108, 307–310, 2001.

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