Introducing ground cover management in pesticide emission modeling.

Ground cover management (GCM) is an important agricultural practice used to reduce weed growth, erosion and runoff, and improve soil fertility. In the present study, an approach to account for GCM is proposed in the modeling of pesticide emissions to evaluate the environmental sustainability of agricultural practices. As a starting point, we include a cover crop compartment in the mass balance of calculating initial (within minutes after application) and secondary (including additional processes) pesticide emission fractions. The following parameters were considered: (i) cover crop occupation between the rows of main field crops, (ii) cover crop canopy density, and (iii) cover crop family. Two modalities of cover crop occupation and cover crop canopy density were tested for two crop growth stages, using scenarios without cover crops as control. From that, emission fractions and related ecotoxicity impacts were estimated for pesticides applied to tomato production in Martinique (French West Indies) and to grapevine cultivation in the Loire Valley (France). Our results demonstrate that, on average, the presence of a cover crop reduced the pesticide emission fraction reaching field soil by a factor of 3 compared with bare soil, independently of field crop and its growth stage, and cover crop occupation and density. When considering cover exported from the field, ecotoxicity impacts were reduced by approximately 65% and 90%, compared with bare soil for grapevine and tomato, respectively, regardless of the emission distribution used. Because additional processes may influence emission distributions under GCM, such as runoff, leaching, or preferential flow, further research is required to incorporate these processes consistently in our proposed GCM approach. Considering GCM in pesticide emission modeling highlights the potential of soil cover to reduce pesticide emissions to field soil and related freshwater ecotoxicity. Furthermore, the consideration of GCM as common farming practice allows the modeling of pesticide emissions in intercropping systems. Integr Environ Assess Manag 2022;18:274-288. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Quantifying pesticide emission fractions for tropical conditions.

The inventory model 'PestLCI Consensus', originally developed for temperate conditions, estimates initial pesticide emission fractions to air, to off-field surfaces by drift deposition, and to field crop and field soil surfaces according to crop foliar interception characteristics. Since crop characteristics and application techniques differ in tropical conditions, these aspects need to be included in the model in support of evaluating pesticide emissions under tropical conditions. Based on published literature, a consistent set of crop foliar interception fractions was developed as function of crop characteristics and spraying techniques for tropical crops. In addition, we derived drift deposition fractions from published drift experiments specifically conducted under tropical conditions. Finally, we compiled a consistent set of pesticide emission fractions for application in life cycle assessment (LCA). Foliar interception fractions are strongly influenced by the spraying technique, particularly for hand-operated applications. Drift deposition fractions to off-field surfaces were derived for air blast sprayer on papaya and coffee, for boom sprayer on bean and soybean, for aerial application on soybean, sorghum, millet, corn and cotton, and for hand-operated application on cotton. Emission fractions vary for each combination of crop and application method. Drift deposition curves for missing crop-application method combinations can only partly be extrapolated from the set of considered combinations. Overall, our proposed foliar interception fractions and drift deposition fractions for various crops grown under tropical conditions allow to estimate pesticide emissions in support of assessing the environmental performance of agrifood systems in LCA with focus on tropical regions.

Spatialised fate factors for nitrate in catchments: modelling approach and implication for LCA results.

The challenge for environmental assessment tools, such as Life Cycle Assessment (LCA) is to provide a holistic picture of the environmental impacts of a given system, while being relevant both at a global scale, i.e., for global impact categories such as climate change, and at a smaller scale, i.e., for regional impact categories such as aquatic eutrophication. To this end, the environmental mechanisms between emission and impact should be taken into account. For eutrophication in particular, which is one of the main impacts of farming systems, the fate factor of eutrophying pollutants in catchments, and particularly of nitrate, reflects one of these important and complex environmental mechanisms. We define this fate factor as: the ratio of the amount of nitrate at the outlet of the catchment over the nitrate emitted from the catchment's soils. In LCA, this fate factor is most often assumed equal to 1, while the observed fate factor is generally less than 1. A generic approach for estimating the range of variation of nitrate fate factors in a region of intensive agriculture was proposed. This approach was based on the analysis of different catchment scenarios combining different catchment types and different effective rainfalls. The evolution over time of the nitrate fate factor as well as the steady state fate factor for each catchment scenario was obtained using the INCA simulation model. In line with the general LCA model, the implications of the steady state fate factors for nitrate were investigated for the eutrophication impact result in the framework of an LCA of pig production. A sensitivity analysis to the fraction of nitrate lost as N(2)O was presented for the climate change impact category. This study highlighted the difference between the observed fate factor at a given time, which aggregates both storage and transformation processes and a "steady state fate factor", specific to the system considered. The range of steady state fate factors obtained for the study region was wide, from 0.44 to 0.86, depending primarily on the catchment type and secondarily on the effective rainfall. The sensitivity of the LCA of pig production to the fate factors was significant concerning eutrophication, but potentially much larger concerning climate change. The potential for producing improved eutrophication results by using spatially differentiated fate factors was demonstrated. Additionally, the urgent need for quantitative studies on the N(2)O/N(2) ratio in riparian zones denitrification was highlighted.