PestLCI 2.0: a second generation model for estimating emissions of pesticides from arable land in LCA
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The spatial dependency of pesticide emissions to air, surface water and groundwater is illustrated and quantified using PestLCI 2.0, an updated and expanded version of PestLCI 1.0.
PestLCI is a model capable of estimating pesticide emissions to air, surface water and groundwater for use in life cycle inventory (LCI) modelling of field applications. After calculating the primary distribution of pesticides between crop and soil, specific modules calculate the pesticide’s fate, thus determining the pesticide emission pattern for the application. PestLCI 2.0 was developed to overcome the limitations of the first model version, replacement of fate calculation equations and introducing new modules for macropore flow and effects of tillage. The accompanying pesticide database was expanded, the meteorological and soil databases were extended to include a range of European climatic zones and soil profiles. Environmental emissions calculated by PestLCI 2.0 were compared to results from the risk assessment models SWASH (surface water emissions), FOCUSPEARL (groundwater via matrix leaching) and MACRO (groundwater including macropore flow, only one scenario available) to partially validate the updated model. A case study was carried out to demonstrate the spatial variation of pesticide emission patterns due to dependency on meteorological and soil conditions.
Compared to PestLCI 1.0, PestLCI 2.0 calculated lower emissions to surface water and higher emissions to groundwater. Both changes were expected due to new pesticide fate calculation approaches and the inclusion of macropore flow. Differences between the SWASH and FOCUSPEARL and PestLCI 2.0 emission estimates were generally lower than 2 orders of magnitude, with PestLCI generally calculating lower emissions. This is attributed to the LCA approach to quantify average cases, contrasting with the worst-case risk assessment approach inherent to risk assessment. Compared to MACRO, the PestLCI 2.0 estimates for emissions to groundwater were higher, suggesting that PestLCI 2.0 estimates of fractions leached to groundwater may be slightly conservative as a consequence of the chosen macropore modelling approach. The case study showed that the distribution of pesticide emissions between environmental compartments strongly depends on local climate and soil characteristics.
PestLCI 2.0 is partly validated in this paper. Judging from the validation data and case study, PestLCI 2.0 is a pesticide emission model in acceptable accordance with both state-of-the-art pesticide risk assessment models. The case study underlines that the common pesticide emission estimation practice in LCI may lead to misestimating the toxicity impacts of pesticide use in LCA.
KeywordsEmission modelling LCI Life cycle inventory modelling Pesticide PestLCI
The authors would like to thank the project ‘Development of genetically modified cereals adapted to the increased CO2 levels of the future’ funded by the Danish Ministry of Food, Agriculture and Fisheries for funding of the research supporting this paper.
- Alterra (2009). SWASH 3.1.1: Surface Water Scenarios Help. Alterra, WageningenGoogle Scholar
- Boesten J, Helweg A, Businelli M, Bergstrom L, Schäfer H, Delmas A, Kloskowski R, Walker A, Travis K, Smeets L, Jones R, Vanderbroeck V, Van der Linden A, Broerse S, Klein M, Layton R, Jacobsen O-S, Yon D (1996) FOCUS report—soil persistence and EU registration—EU document 7617/VI/96, EU, BrusselsGoogle Scholar
- Communities E (2003) Technical guidance document on risk assessment. Part II. European Commission Joint Research Centre, IspraGoogle Scholar
- European Communities (2007) PV-GIS estimation utility. http://sunbird.jrc.it/pvgis/apps/pvest.php?europe. Accessed 29 July 2011
- FOCUS (2000) FOCUS groundwater scenarios in the EU review of active substances. Report of the FOCUS Groundwater Scenarios Workgroup, EC Document reference Sanco/321/2000 rev.2, 202 ppGoogle Scholar
- FOCUS (2001) FOCUS surface water scenarios in the EU evaluation process under 91/414/EEC—report of the FOCUS working group on surface water scenarios, EU, BrusselsGoogle Scholar
- Geodata (2011) Daily weather climate data statistics—Tune/Roskilde: http://www.geodata.us/weather/place.php?usaf=061700&uban=99999&c=Denmark&y=2011. Accessed 29 July 2011
- Hiederer R, Jones RJA, Daroussin J (2006) Soil Profile Analytical Database for Europe (SPADE): Reconstruction and validation of the measured data (SPADE/M). Geografisk Tidsskrift, Danish Journal of Geography 106(1):71–85Google Scholar
- Hollis JM, Jones RJA, Marshall, CJ, Holden A, Van de Veen JR, Montanarella L (2006) SPADE-2: The soil profile analytical database for Europe, version 1.0. Office for official publications of the European Communities, LuxembourgGoogle Scholar
- Holterman HJ, Van de Zande JC (2003) IMAG drift calculator v1.1: User manual. http://www.toxswa.pesticidemodels.eu/download/IDCmanual.pdf. Accessed 29 July 2011
- Jarvis N (2001) The MACRO model, version 4.3 (Technical description). SLU, UppsalaGoogle Scholar
- Klein Tank AMG, Wijngaard JB, Können GP, Böhm R, Demarée G, Gocheva A, Mileta M, Pahiardis S, Jejkrlik L, Kern-Hansen C, Heino R, Bessemoulin P, Müller-Westermeier G, Tzanakou M, Szalai S, Pálsdóttir T, Fitzgerald D, Rubin S, Capaldo M, Maugeri M, Leitass A, Bukantis A, Aberfeld R, Van Engelen AFV, Forland E, Mietus M, Coelho F, Mares C, Razuvaev V, Nieplova E, Cegnar T, Antonio López J, Dahlström B, Moberg A, Kirchhofer W, Ceylan A, Pachaliuk O, Alexander LV, Petrovic P (2002) Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. Int J Climatol 22:1441–1453CrossRefGoogle Scholar
- Larsbo M, Jarvis N (2003) MACRO 5.0 Model of water flow and solute transport in macroporous soil. Technical description. Uppsala, Swedish University of Agricultural SciencesGoogle Scholar
- Lumina Decision Support (2010) Analytica user guide. Lumina Decision Support, Inc, Los GatosGoogle Scholar
- Nemecek T, Kägi T (2007) Life cycle inventories of Swiss and European agricultural production systems. Final report ecoinvent v2.o No 15a. Zürich and Dübendorf, Agroscope Reckenholz-Taenikon Research Station. www.ecoinvent.ch Accessed 16 December 2011
- RIVM, PBL, Alterra (2011) FOCUSPEARL 4.4.4. RIVM, Bilthoven, PBL, Bilthoven, Alterra, WageningenGoogle Scholar
- Rosenbaum RK, Bachmann TK, Gold LS, Huijbregts MAJ, Jolliet O, Juraske R, Koehler A, Larsen HF, MacLeod M, Margni M, McKone TE, Payet J, Schuhmacher M, Van de Meent D, Hauschild MZ (2008) USEtox: The UNEP/SETAC-consensus model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int J Life Cycle Assess 13(7):532–546CrossRefGoogle Scholar
- Swiss Centre for Life Cycle Inventories (2011) ecoinvent v. 2.2. Swiss Centre for Life Cycle Inventories, St-GallenGoogle Scholar
- Van Leeuwen CJ, Hermens JLM (eds) (1995) Risk assessment of chemicals: an introduction, 1st edn. Kluwer Academic Publishers, DordrechtGoogle Scholar