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Metadata Factsheet

1. Indicator name

Aggregated Total Applied Toxicity (ATAT)

2. Date of metadata update

2024-02-28 00:00:00 UTC

3. Goals and Targets addressed

3a. Goal

N/A

3b. Target

Headline Indicator for Target 7: Reduce pollution risks and the negative impact of pollution from all sources by 2030, to levels that are not harmful to biodiversity and ecosystem functions and services, considering cumulative effects, including: (a) by reducing excess nutrients lost to the environment by at least half, including through more efficient nutrient cycling and use; (b) by reducing the overall risk from pesticides and highly hazardous chemicals by at least half, including through integrated pest management, based on science, taking into account food security and livelihoods; and (c) by preventing, reducing, and working towards eliminating plastic pollution.

4. Rationale

Three quarters of the world's population is exposed to pesticides [1-3] and global pesticide use is increasing rapidly, with agriculture having by far the largest share [4,5]. Furthermore, at the current high levels, pesticide use and total toxicity have become decoupled from agricultural productivity across a range of spatial and temporal scales [6-8]. Monitoring data for certain types of pesticides shows that the concentrations regularly present in the environment often exceed ecotoxicological thresholds set during regulatory pesticide risk assessments [9,10]. Tang et al (2021)[3] recommend that a global strategy should be established to transition towards sustainable agriculture and sustainable living with low pesticide inputs and reduced food losses and food waste to achieve responsible production and consumption in an acceptable, profitable system. Indeed, literature and experiences from case studies with pesticides show that by increasing efficiency and/or substituting active ingredients (thus lowering toxicity) risk reductions of 20-50% can be achieved without the redesign of production systems. Furthermore, novel pesticide-free production systems can reduce risks even further without yield trade-offs while increasing farmers’ incomes [11].

As the only toxic chemicals deliberately applied in the environment with the intention to kill or disrupt living organisms, pesticides have a considerable impact on biodiversity and ecosystem functioning [12-14]. However, estimates of the regional and global pesticide impacts on biodiversity have been difficult to ascertain because: 1) information on the quantities and types of pesticides applied in the environment are often unavailable – particularly for Low and Middle-Income (LMIC) countries [15]; 2) Pesticide products vary widely in their toxicities to target and non-target organisms and, consequently, they have varying impacts on different components of ecological communities [10,16,17]; and 3) pesticide impacts are partly determined by varying levels of biodiversity exposure at local, regional and global scales. In a global context, the greatest impacts occur in crops and regions that support high numbers of unique species [14,18,19].

Several useful indicators of the effects of pesticides on human health and non-target organisms have been developed and many are routinely applied in some countries to reduce the risks from pesticide use [2,5,16,17,20-29]. Furthermore, many countries conduct some monitoring of pesticide contamination in crops and associated habitat, particularly in water bodies [30,31]. However, the quality of data on pesticide use is uneven across regions and countries, and direct measures of the impacts of pesticides on ecological communities is largely limited to case studies with low spatial and temporal coverage. In contrast, information on the toxic effects of pesticides on target and non-target organisms is generally available, particularly for newer pesticide products, from toxicity studies that have mainly been conducted in laboratories as required for pesticide registration [16,26,32].

Based on the above data limitations, any global assessment of pesticide impacts will be necessarily complex, requiring fine-grained mapping of crops and their associated biodiversity, and taking account of location-specific climate, geology and production practices. Such impact assessments have been developed and are improving [1-3,5,27,33]. Simpler risk assessments based on pesticide use and toxicity are currently available and have been used to compare potential effects on a range of non-target groups based on patterns of pesticide use in countries and over time [10,16,17]. Total Applied Toxicity (TAT) is one suitable indicator of the national, regional and global risks from pesticides to biodiversity and can be adapted to monitor trends in global pesticide-associated risks over time, with the intention of attaining or exceeding risk reduction targets set by the Kunming-Montreal Global Biodiversity Framework (e.g., 50% reduction in global risk) [34]. TATs are calculated for individual species or species groups and must be aggregated (ATAT) to present a single risk value to meet the requirement of headline indicators.

5. Definitions, concepts and classifications

5a. Definition:

Aggregated Total Applied Toxicity (ATAT) is defined as the risk to ecological communities based on the combined risks to key species groups from the annual outdoor, agricultural, forestry and public health use of total pesticides in active ingredients for the following categories of pesticides: fungicides, bactericides, herbicides, insecticides, molluscicides, plant growth regulators, seed treatment fungicides, seed treatment insecticides, mineral oils, rodenticides, disinfectants, and other pesticides (not elsewhere specified); and normalized by the area of cropland (which is the sum of arable land and land under permanent crops), sprayed forests, and reported areas applied for vector control (i.e., outdoor public health). Microbial biopesticides will not be considered among pesticide types.

ATAT indicates large-scale temporal trends in how changes in pesticide use and associated toxicities are reflected in different species groups. The ATAT at least amalgamates the risks from applied pesticides to individual species groups as a single community effect. It is proposed that this would also be weighted based on species richness and proportional endemicities within each species group considered.

5b. Method of computation

The ATAT is computed as follows:

Total Applied Toxicity (TAT) was presented by Schultz et al [10,16,17] as the mass (m) of pesticide (s) applied within a given time period (t = one year) within a country (x), divided by the regulatory threshold level (RTL) that relates to the applied pesticide s and the species group sp. The pesticide product s refers to one of n number of pesticide active ingredients applied in outdoor agriculture, with n encompassing all registered active ingredients by country. The species groups include fish, birds, mammals, aquatic invertebrates, terrestrial arthropods (excluding pollinators), pollinators, aquatic plants and terrestrial plants. The ATAT intends to extend TAT to calculate a single indicator of risk, by weighting RTLs using a factor that represents species group prominence (b) by incorporating species richness and/or endemicity; and by normalizing each country’s ATATs by agricultural and forestry areas and major areas applied during national campaigns for vector control (a) to allow proportional representation by country prior to global aggregation. The equation for ATAT is:


(equation 1)

The equation for global aggregation of the ATATs is: (equation 2)

Related risk reductions can be assessed through yearly comparisons with estimated baseline risks. Because ATAT requires a protocol that can be applied by all countries, and requires standardization of key inputs across countries, then the functioning and feasibility of including some components for the calculation of ATAT remain to be verified through testing. In particular, issues around the normalization of applied areas that include forestry and areas applied for vector control requires testing; the effects of weighting by species richness and endemicity for each test group requires testing; and the adaptation of ATAT to track risk-reduction targets need to be defined. Furthermore, because RTLs are not complete for all active ingredients, approaches for handling missing data and standardizing computation across countries is required. A method can be developed for estimating RTL equivalents where data is unavailable [35].

5c. Data collection method

Each country can calculate yearly Aggregated TAT (ATAT) values using national statistics on pesticides sales or use and open-source information on pesticide properties that include toxicity values for a range of species. Baseline ATAT values can be calculated for 2011-2020 using historical data on pesticide trade, sales or usage and applying publicly available toxicity values and respective weightings.

Data on pesticide use based on farmer or producer reporting to governments is made available on an annual basis by some countries, whereas data on pesticide sales is available for others. These two parameters can be related to calculate TAT and ATAT. Sales/use data should be disaggregated by active ingredients and expressed as mass (Kg of active ingredient or pesticide product). In the absence of sales and usage data, pesticide trade (import/export) and national production data can be used with annual usage estimated based on crop (including forests) and livestock production and recommended application rates together with areas and products applied for vector control. Trade data is normally available through customs authorities and trade ministries. Agricultural areas and production, disaggregated by crop or livestock species, are normally collected on an annual basis by agricultural or trade ministries; in some cases, these are submitted to FAOSTAT [36] by area, tonnage and/or value.

Toxicity values must be derived from recommended open-sources based on criteria that best match national circumstances (e.g., toxicity for tropical fish versus temperate fish species). The weighting of toxicities for species groups could be based on species richness and reported endemicity for each group in each country. Weighting should include species and endemics that are normally exposed to agricultural pesticides based on an established protocol to be developed and shared across countries.

To facilitate reporting of ATAT, countries can streamline their pesticide reporting infrastructure using inventory systems and automated reporting to centralized authorities or data storage and reporting systems (such as FAOSTAT, USGS, etc.). Enabling legal, structural and technical environments need to be developed in some countries to operationalize the indicator (including component TATs for different species groups, standardized data sources, etc.), this requires some attention to capacity building.

5d. Accessibility of methodology

The methodology for calculating TAT for species groups is available as supplementary information in Schulz et al [29]. The method has been applied to compare trends in environmental toxicity for key species groups across countries and years [10,16,17]. The method needs updating and testing to introduce robust diversity weighting (i.e., weighting of toxicities for individual species or species groups by species richness or endemicity) and allow aggregation of estimates across regions and globally. An updated methodology will be available before 2025.

5e. Data sources

TAT calculations require pesticide sales and/or usage data. Furthermore, this data must be disaggregated by pesticide active ingredient. Disaggregated, open-source, national statistics on pesticide sales and usage are not accessible in many countries; however, data are generally recorded on an annual basis by all countries, if not publicly reported. Data on pesticide use are reported in an aggregated form (by pesticide classes by country) to FAOSTAT and some countries publicly report on sales and/or use. Where necessary, national biodiversity coordinators can source information on pesticide usage from relevant ministries.

Data on pesticide properties are available through a range of open-source databases. Among these is the the Pesticide Properties DataBase (PPDB) that holds data for ca 2500 pesticide active substances and over 700 metabolites, with ca 320 parameters (e.g., toxicity, biodiversity risk assessments, etc.) stored for each substance [32]. The PPDB is publicly available [37] and is used worldwide to support pesticide risk assessments, models and indicators, policy focused monitoring exercises, and general research. To avoid differences in the parameters used during calculation of ATATs and thereby, possible biases in reporting, countries will need to apply a standard set of toxicity results as deemed suitable for the global indicator; the PPDB may be updated to highlight this set of data. Furthermore, because the PPDB is a dynamic database, the selected toxicities should be designed for application across countries and each year – including for the baseline data. Acute and, if available, chronic toxicity data should be used for the groups of organisms (based on laboratory studies using OECD guidelines) and applying respective regulatory threshold levels (=RTL). Chronic metrics can be adjusted using algorithms as applied for the Danish and UK PLIs using substance LD50s thereby accounting for persistence in the environment (soil and water). Means of RTLs for each compound and species group should be calculated – this would result in ca 15 acute and chronic RTL values for 400-600 pesticides.

Data on crop production (crop types, crop acreage, yields) are available for most countries from FAOSTAT [36]. Since FAOSTAT receives its data from national sources, any data that are reported through FAOSTAT are also available through national reporting authorities, often is a more disaggregated form.

National biodiversity inventories are frequently available as a component of open-source databases at national levels. Inventories will generally include data on estimated endemicities among the selected species’ groups. In the absence of open-source data, national inventory records or global assessments of regional species richness and endemicities are available for each of the species’ groups. The methods used during biodiversity inventories will need to be screened to avoid sampling biases that avoid agricultural landscapes.

Data will be validated by the individual parties to the CBD and data ownership and distribution on national pesticide trade, sales, usage and properties, as well as crop production data, will be at the discretion of the parties. Protocols for data curation, validation and quality control will be developed with parties during testing.

5f. Availability and release calendar

The ATAT indicator was accepted by a group of technical and policy experts at a dedicated meeting in FAO (Rome) in January 2024 as the most parsimonious indicator to meet the criteria for mapping risk reduction to biodiversity from pesticides. Whereas TAT is already available for use as an indicator of pesticide risks, it requires further development and testing to be used as a headline indicator (i.e., with a single value for each country) that provides a single global risk value. Furthermore, a methodology to report the indicator in terms of addressing proposed targets for risk reduction is still under development. Development and testing of the indicator will be addressed by academic and policy experts in 2024/25 and an updated methodology with test results is expected in 2025.

5g. Time series

The 2011-2020 baseline should be provided during initial reporting with comparative risks and risk reductions for each year reported from 2022 to 2030. To avoid biases, all parameters used to calculate baseline values will need to be continued as standards during the calculation of annual ATATs. For some countries, highly toxic pesticides used after 2011 but now de-registered may skew TAT values for certain species or species groups to produce disproportionate estimates of risk reductions when compared to other countries that de-registered the same products before 2011. Procedures to mitigate against such potential artifacts are required.

5h. Data providers

National governments; International Union of Pure and Applied Chemistry/IUPAC and University of Hertfordshire; FAO

5i. Data compilers

FAO will compile the data

5j. Gaps in data coverage

  • The indicator is non-cumulative and not dynamic in time—that is, it does not consider the effects of accumulated pesticides and their degradation products in the environment over time, and thus may not fully capture the pervasiveness of certain active ingredients. The PPDB has data for key metabolites, which are then used instead of the parent properties. A similar approach is recommended for the ATAT.
  • The indicator does not account for the synergistic or antagonistic effects of pesticide mixtures, which are currently poorly documented and for which useful toxicity data is largely unavailable.
  • The indicator omits illegally traded and illegally used pesticides for which information is largely unavailable, in particular, the indicator cannot include non-reported usage of banned pesticides – many of which have severe impacts on key indicator groups.
  • The indicator does not include the detrimental effects of obsolete pesticide stocks in nations; these are often inadequately stored and can have severe adverse effects on biodiversity and ecosystems.
  • The indicator does not include adjuvants, solvents and industrial contaminants despite detrimental effects of some of these on non-target organisms, including prevalent effects in some formulations for widely used chemicals such as glyphosate; some adjuvants are considered highly hazardous, but these are difficult to quantify based on product labels.
  • The indicator does not address risk mitigation measures such as avoiding pesticide drift, avoiding riverine habitats, avoiding bird and fish breeding seasons, maintaining distances from water bodies, etc.; it assumes that pesticide run-off is ubiquitous over wide areas sprayed.
  • The indicator does not incorporate cascade effects whereby pesticide impacts on one species or a group of species has detrimental effects on other community components (species or species groups) despite minimal direct pesticide impacts on the latter (e.g., herbicide effects on flowering weeds affects specialized pollinators or pesticide effects on chironomid larvae affects fish).
  • The indicator does not account for rare or endangered species that are not endemic to specific countries.
  • Biodiversity inventories generally underrepresent certain taxa, including plants, arthropods, microbiota; relations between species richness and ecosystem function are poorly understood
  • The indicator does not include coastal and marine habitats and possible detrimental effects to marine organisms.
  • The indicator does not include sub-lethal effects on non-target species that might alter behaviors and, consequently, affect ecosystem services.
  • The indicator does not link regionally varying exposures based on biodiversity gradients to national ATATestimates – this can be included to more accurately calculate ATAT values for large nations, but is not necessarily reported by countries and can inhibit adequate risk-mitigation measures.

5k. Treatment of missing values

For some countries, pesticide sales or use data are not widely available or are held-up at ministries; and data is made available only gradually with time lags that can be greater than 5 years. Where sales/use data is unavailable, countries can use trade data (which is more commonly available) to estimate usage based on crop types and areas. Using trade and production data (i.e., availability), pesticide usage can be estimated based on crop composition (up to 100 main crops or at least crop groups), pesticide label information (application rates, etc.), and basing usage on data form similar countries. A standard methodology will be defined to convert trade and sales data into usage; to ensure this is done in a consistent manner by different countries.

Some substances may not have all the data needed for the indicator. The UK PLI has a protocol for plugging gaps which includes using data for related substances or using an average value for the type of pesticide (i.e., insecticide, herbicide, fungicide, etc.) (an alternative is to use a worst-case value, i.e., 95th percentile). The UK PLI also has an exclusion protocol, to remove substances where substantial data are missing; any substances with less than 60% of the required data are excluded. A similar protocol will be defined for the GATAT to ensure transparency.

In the absence of trade data, estimates of pesticide usage in crops can be generated by using PEST-CHEMGRIDS and CROPGRIDS and applying the related published protocols. These use crop production data by area and infer pesticide usage based on typical application rates for the same or similar crops based on registered sales from data rich countries [5,33].

Non reporting or late reporting of ATATs by countries will delay estimates of global risks and risk reductions. This will be more prevalent during the initial years of indicator operationalization and become less prevalent over time, particularly where capacity building is put in place to support countries to evaluate and report pesticide associated risks. For real-time reporting, estimates can be made to fill data gaps based on countries with similar socioecological and agricultural conditions. Gap-fill estimates could be corrected retrospectively when more accurate data and risk estimates are available.

6. Scale

6a. Scale of use

Scale of application: Global, Regional, National

Scale of data disaggregation/aggregation:Aggregated by pesticide active ingredients, species and species groups, and crop production areas (including forestry and pastures) or application areas (in the case of public health pesticides)

Global/ regional scale indicator can be disaggregated to national level: Yes

National data is collated to form global indicator: Yes

6b. National/regional indicator production

Indicator characteristics and calculations are available for national authorities in papers published by Schulz et al (2021) [16], Bub et al (2022)[17] and Wolfram et al (2023) [10]. Data to calculate the indicator is available at national levels including, in many cases, to calculate the baseline indicator (2011-2020) using historical data. Extensions of the TAT for community weighting are not yet published; however, until the methodology is published, national authorities can report component indicators (i.e., 15 or more acute of chronic RTL values for all pesticides combined) with community weighting adjusted retrospectively. Component indicators will include TAT estimates for each species and species group and ATAT estimates for each country. PLIs for key species or species groups [26] are recommended as useful complementary indicators.

6c. Sources of differences between global and national figures

ATAT is calculated individually for each country. Since the data is aggregated at the global level, there should be no differences.

6d. Regional and global estimates & data collection for global monitoring

6d.1 Description of the methodology

The methodology for TAT and its application in comparing environmental toxicities between regions and over time is published by Schulz et al (2021) [16]

6d.2 Additional methodological details

Details for estimating pesticide use based on PEST-CHEMGRIDS and subsequent applications are available in publications by Maggi et al (2019)[5]

6d.3 Description of the mechanism for collecting data from countries

Pesticide trade and usage data will be reported to FAO with pesticides disaggregated by active ingredient.

Pesticide properties are available and continually updated on the Pesticide Properties DataBase [37].

The ATAT will be reported by national biodiversity officers to the CBD using the Online Reporting Tool. Countries may seek support during reporting from FAO.

7. Other MEAs, processes and organisations

7a. Other MEA and processes

ATAT complements SDG 6 and SDG 15, which currently has an emphasis on protected lands and waters; directly contributes to monitoring hazardous pesticide risk reduction under the Global Framework on Chemicals (GFC) target A7 and supports related targets (A5, B6 and D5); IPBES (global and regional assessments, thematic assessments and sustainability); contributes to monitoring implementation of Stockholm, Rotterdam, Basel and Minamata Conventions and the Montreal Protocol. The component indicator further supports the Globally Harmonized System of classification and labelling of chemicals, the Codex Alimentarius and the World Health Organization’s pre-qualification of vector control products - among other key international agreements and mechanisms that address pesticide management.

7b. Biodiversity Indicator Partnership

No

8. Disaggregation

The headline indicator can be disaggregated by pesticide types (herbicide, insecticide, molluscicide, fungicide, etc.) and toxicities to non-target organisms. Disaggregation by nationally listed highly hazardous pesticides (e.g., those listed under international agreements or with human carcinogenic, mutagenic and adverse effects of reproduction) and safer alternatives will also be possible. Disaggregation by sector (agriculture, forestry, public health) may be achieved based on the types of pesticide products.

9. Related indicators

The ATAT will complement monitoring of Goal B and the implementation of targets 9, 10, 11, 15, and 18 of the Kunming-Montreal GBF and indicators 10.2 progress towards sustainable forest management and 18.2 Value of subsidies and other incentives harmful to biodiversity, that have been eliminated, phased out or reformed.

10. Data reporter

10a. Organisation

Food and Agriculture Organization (FAO)

10b. Contact person(s)

Kim-Anh Tempelman (kimanh.tempelman@fao.org)

11. References

Website

Regional Seas website: https://www.unenvironment.org/explore-topics/ocean...

References

1. Maggi, F.; la Cecilia, D.; Tang, F.H.M.; McBratney, A. The global environmental hazard of glyphosate use. Science of The Total Environment 2020, 717, 137167, doi:https://doi.org/10.1016/j.scitotenv.2020.137167.

2. Maggi, F.; Tang, F.H.M.; Black, A.J.; Marks, G.B.; McBratney, A. The pesticide health risk index - An application to the world's countries. Science of The Total Environment 2021, 801, 149731, doi:https://doi.org/10.1016/j.scitotenv.2021.149731.

3. Tang, F.H.M.; Lenzen, M.; McBratney, A.; Maggi, F. Risk of pesticide pollution at the global scale. Nature Geoscience 2021, 14, 206-210, doi:10.1038/s41561-021-00712-5.

4. Bernhardt, E.S.; Rosi, E.J.; Gessner, M.O. Synthetic chemicals as agents of global change. Frontiers in Ecology and the Environment 2017, 15, 84-90.

5. Maggi, F.; Tang, F.H.M.; la Cecilia, D.; McBratney, A. PEST-CHEMGRIDS, global gridded maps of the top 20 crop-specific pesticide application rates from 2015 to 2025. Scientific Data 2019, 6, 170, doi:10.1038/s41597-019-0169-4.

6. Lechenet, M.; Dessaint, F.; Py, G.; Makowski, D.; Munier-Jolain, N. Reducing pesticide use while preserving crop productivity and profitability on arable farms. Nature plants 2017, 3, 1-6.

7. Schreinemachers, P.; Tipraqsa, P. Agricultural pesticides and land use intensification in high, middle and low income countries. Food Policy 2012, 37, 616-626, doi:https://doi.org/10.1016/j.foodpol.2012.06.003.

8. Gaba, S.; Gabriel, E.; Chadœuf, J.; Bonneu, F.; Bretagnolle, V. Herbicides do not ensure for higher wheat yield, but eliminate rare plant species. Scientific Reports 2016, 6, 30112, doi:10.1038/srep30112.

9. Stehle, S.; Schulz, R. Pesticide authorization in the EU—environment unprotected? Environmental Science and Pollution Research 2015, 22, 19632-19647, doi:10.1007/s11356-015-5148-5.

10. Wolfram, J.; Bub, S.; Petschick, L.L.; Schemmer, A.; Stehle, S.; Schulz, R. Pesticide occurrence in protected surface waters in nature conservation areas of Germany. Science of The Total Environment 2023, 858, 160074, doi:https://doi.org/10.1016/j.scitotenv.2022.160074.

11. Möhring, N.; Finger, R. Pesticide-free but not organic: Adoption of a large-scale wheat production standard in Switzerland. Food Policy 2022, 106, 102188, doi:https://doi.org/10.1016/j.foodpol.2021.102188.

12. Beketov, M.A.; Kefford, B.J.; Schäfer, R.B.; Liess, M. Pesticides reduce regional biodiversity of stream invertebrates. Proceedings of the National Academy of Sciences 2013, 110, 11039-11043, doi:doi:10.1073/pnas.1305618110.

13. Geiger, F.; Bengtsson, J.; Berendse, F.; Weisser, W.W.; Emmerson, M.; Morales, M.B.; Ceryngier, P.; Liira, J.; Tscharntke, T.; Winqvist, C.; et al. Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland. Basic and Applied Ecology 2010, 11, 97-105, doi:https://doi.org/10.1016/j.baae.2009.12.001.

14. Sánchez-Bayo, F.; Wyckhuys, K.A.G. Worldwide decline of the entomofauna: A review of its drivers. Biological Conservation 2019, 232, 8-27, doi:https://doi.org/10.1016/j.biocon.2019.01.020.

15. van den Berg, H.; Gu, B.; Grenier, B.; Kohlschmid, E.; Al-Eryani, S.; da Silva Bezerra, H.S.; Nagpal, B.N.; Chanda, E.; Gasimov, E.; Velayudhan, R.; et al. Pesticide lifecycle management in agriculture and public health: Where are the gaps? Science of The Total Environment 2020, 742, 140598, doi:https://doi.org/10.1016/j.scitotenv.2020.140598.

16. Schulz, R.; Bub, S.; Petschick, L.L.; Stehle, S.; Wolfram, J. Applied pesticide toxicity shifts toward plants and invertebrates, even in GM crops. Science 2021, 372, 81-84.

17. Bub, S.; Wolfram, J.; Petschick, L.L.; Stehle, S.; Schulz, R. Trends of total applied pesticide toxicity in German agriculture. Environmental Science and Technology 2022, 57, 852-861.

18. Larsen, A.E.; Farrant, D.N.; MacDonald, A.J. Spatiotemporal overlap of pesticide use and species richness hotspots in California. Agriculture, Ecosystems and Environment 2020, 289, 106741, doi:https://doi.org/10.1016/j.agee.2019.106741.

19. Schiesari, L.; Waichman, A.; Brock, T.; Adams, C.; Grillitsch, B. Pesticide use and biodiversity conservation in the Amazonian agricultural frontier. Philosophical Transactions of the Royal Society B: Biological Sciences 2013, 368, 20120378, doi:10.1098/rstb.2012.0378.

20. Brown, C.; Hart, A.; Lewis, K.; Dubus, I. p-EMA (I): simulating the environmental fate of pesticides for a farm-level risk assessment system. Agronomie 2003, 23, 67-74.

21. Cornell College of Agricultural and Life Sciences. Environmental Impact Quotient: EIQ—A Method to Measure the Environmental Impact of Pesticides. Available online: https://cals.cornell.edu/new-york-state-integrated-pest-management/risk-assessment/eiq#:~:text=The%20Environmental%20Impact%20Quotient%20(EIQ,decisions%20regarding%20their%20pesticide%20selection (accessed on 15 March 2024)

22. Danish Environmental Protection Agency. The Agricultural Pesticide Load in Denmark 2007–2010. Environmental Review 2 2012.

23. Hart, A.; Brown, C.; Lewis, K.; Tzilivakis, J. p-EMA (II): evaluating ecological risks of pesticides for a farm-level risk assessment system. Agronomie 2003, 23, 75-84.

24. Kudsk, P.; Jørgensen, L.N.; Ørum, J.E. Pesticide Load—A new Danish pesticide risk indicator with multiple applications. Land Use Policy 2018, 70, 384-393.

25. Lewis, K.; Brown, C.; Hart, A.; Tzilivakis, J. p-EMA (III): overview and application of a software system designed to assess the environmental risk of agricultural pesticides. Agronomie 2003, 23, 85-96.

26. Lewis, K.; Rainford, J.; Tzilivakis, J.; Garthwaite, D. Application of the Danish Pesticide Load Indicator to UK arable agriculture. Journal of Environmental Quality 2021, 50, 1110-1122.

27. Maggi, F.; Tang, F.H.M.; Tubiello, F.N. Agricultural pesticide land budget and river discharge to oceans. Nature 2023, 620, 1013-1017, doi:10.1038/s41586-023-06296-x.

28. Möhring, N.; Gaba, S.; Finger, R. Quantity based indicators fail to identify extreme pesticide risks. Science of The Total Environment 2019, 646, 503-523, doi:https://doi.org/10.1016/j.scitotenv.2018.07.287.

29. Trevisan, M.; Di Guardo, A.; Balderacchi, M. An environmental indicator to drive sustainable pest management practices. Environmental Modelling and Software 2009, 24, 994-1002, doi:https://doi.org/10.1016/j.envsoft.2008.12.008.

30. Centanni, M.; Ricci, G.; De Girolamo, A.; Romano, G.; Gentile, F. A review of modeling pesticides in freshwaters: Current status, progress achieved and desirable improvements. Environmental pollution 2023, 316, 120553.

31. Stehle, S.; Schulz, R. Agricultural insecticides threaten surface waters at the global scale. Proceedings of the National Academy of Sciences 2015, 112, 5750-5755.

32. Lewis, K.A.; Tzilivakis, J.; Warner, D.J.; Green, A. An international database for pesticide risk assessments and management. Human and Ecological Risk Assessment: An International Journal 2016, 22, 1050-1064.

33. Tang, F.H.; Nguyen, T.H.; Conchedda, G.; Casse, L.; Tubiello, F.N.; Maggi, F. CROPGRIDS: A global geo-referenced dataset of 173 crops circa 2020. Earth System Science Data Discussions 2023, 2023, 1-22.

34. Convention on Biodiversity. Decision adopted by the Conference of the Parties to the Convention on Biodiversity: 15/4 Kunming-Montreal Global Biodiversity Framework. Available online: https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.... (accessed on 15 February 2024)

35. Petschick, L.L.; Schulz, R.; Stehle, S. RTLE-A New Model to Predict Regulatory Threshold Level Equivalents for Pesticides from the Open Literature. 2018.

36. Food and Agriculture Organization of the United Nations. FAOSTAT. https://www.fao.org/faostat/en/ (accessed on 15 February 2024).

37. International Union of Pure and Applied Chemistry. IUPAC Pesticides Properties DataBase. Available online: https://sitem.herts.ac.uk/aeru/iupac/index.htm (accessed on 15 February 2024)

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