Estimating emissions of chemical pesticides used in agriculture is an essential component in evaluating the potential toxicity-related impacts on humans and ecosystems in various comparative risk and ...impact assessment frameworks, such as life cycle assessment, environmental footprinting, absolute environmental sustainability assessment, chemical substitution, and risk prioritization. Emissions related to drift deposition—usually derived from drift experiments—can reach non-target areas, and vary as a function of crop characteristics and application technique. We derive cumulative drift deposition fractions for a wide range of experimental drift functions for use in comparative and mass-balanced approaches. We clarify that cumulative drift deposition fractions require to integrate the underlying drift functions over the relevant deposition area and to correct for the ratio of deposition area to treated field area to arrive at overall mass deposited per unit mass of applied pesticide. Our results show that for most crops, drift deposition fractions from pesticide application are below 0.03 (i.e. 3% of applied mass), except for grapes and fruit trees, where drift fractions can reach 5% when using canon or air blast sprayers. Notably, aerial applications on soybeans can result in significantly higher drift deposition fractions, ranging from 20% to 60%. Additionally, varying the nozzle position can lead to a factor of five differences in pesticide deposition, and establishing buffer zones can effectively reduce drift deposition. To address remaining limitations in deriving cumulative drift deposition fractions, we discuss possible alternative modelling approaches. Our proposed approach can be implemented in different quantitative and comparative assessment frameworks that require emission estimates of agricultural pesticides, in support of reducing chemical pollution and related impacts on human health and the environment.
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•Comparative impact assessments require cumulative estimates of pesticide emissions.•Drift fraction integrates crop-application method-specific drift curves from experiments.•Validity ranges of drift functions and spray nozzle position need to be considered.•Various drift reduction techniques are considered.•Alternative drift modelling approaches may address prevailing limitations.
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.
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•Crop growth stages and foliar interception were defined for various tropical crops.•Tropical drift deposition curves were introduced in pesticide emission modeling.•Environmental emission fractions for tropical crops were quantified for use in LCA.•Emissions differ substantially for some crops as compared to temperate conditions.
Purpose
Current field emission modelling and toxicity characterisation of pesticides suffer from several shortcomings like mismatches between LCI databases and LCIA methods, missing characterisation ...factors, missing environmental compartments, and environmental impact pathways. The OLCA-Pest project was implemented to address these aspects and to operationalise the assessment of pesticides in LCA. Based on this effort, we propose an approach to integrate pesticide emissions into LCI databases.
Methods
The PestLCI Consensus Model has been developed in order to estimate emission fractions to different environmental compartments. The initial distribution fractions should be linked to the compartments air, agricultural soil, natural soil, and freshwater. Emissions to off-field surfaces are hereby distributed between agricultural soil, natural soil, and freshwater by using surface cover data. Deposition on the crop surface should be recorded in an emission compartment crop with 13 sub-compartments for crop archetypes for both food and non-food uses. Default emission fractions are provided to calculate the emission fractions for different pesticide application scenarios.
Results and discussion
A sensitivity analysis shows the effects of the application technique, drift reduction, crop and development stage, field width, and buffer zone on the initial distribution fractions of field-applied pesticides. Recommendations are given for the implementation of a set of default initial distribution fractions into LCI databases, for the organisation of metadata, and for the modelling of pesticide residues in food along the supply chain (processing, storage). Priorities for further research are: improving the modelling of pesticide secondary emissions, further extending emission modeling (e.g. additional application techniques, including cover crops), considering metal-based pesticides in emission models, and systematically assessing human health impacts associated with pesticide residues in food crops.
Conclusions
The proposed approach allows to preserve the mass balance of the pesticide emitted after application, to make a consistent assessment of ecotoxicity and human toxicity, to define a clear and consistent interface between the LCI and LCIA phases, to estimate initial emission distribution fractions based on existing data, to document metadata transparently and efficiently within crop datasets, and to model the removal of pesticide residues in food during processing.
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