Pesticides are widely used to protect food production and meet global food demand but are also ubiquitous environmental pollutants, causing adverse effects on water quality, biodiversity and human health. Here we use a global database of pesticide applications and a spatially explicit environmental model to estimate the world geography of environmental pollution risk caused by 92 active ingredients in 168 countries. We considered a region to be at risk of pollution if pesticide residues in the environment exceeded the no-effect concentrations, and to be at high risk if residues exceeded this by three orders of magnitude. We find that 64% of global agricultural land (approximately 24.5 million km2) is at risk of pesticide pollution by more than one active ingredient, and 31% is at high risk. Among the high-risk areas, about 34% are in high-biodiversity regions, 5% in water-scarce areas and 19% in low- and lower-middle-income nations. We identify watersheds in South Africa, China, India, Australia and Argentina as high-concern regions because they have high pesticide pollution risk, bear high biodiversity and suffer from water scarcity. Our study expands earlier pesticide risk assessments as it accounts for multiple active ingredients and integrates risks in different environmental compartments at a global scale.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Ambio Open Access 17 November 2022
Communications Earth & Environment Open Access 07 November 2022
Environmental Sciences Europe Open Access 05 July 2022
Subscribe to Nature+
Get immediate online access to Nature and 55 other Nature journal
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Oerke, E. C. Crop losses to pests. J. Agric. Sci. 144, 31–43 (2006).
FAOSTAT: Database Collection of the Food and Agriculture Organization of the United Nations (FAO, 2019); http://www.fao.org/faostat/en/#data
Beketov, M. A., Kefford, B. J., Schäfer, R. B. & Liess, M. Pesticides reduce regional biodiversity of stream invertebrates. Proc. Natl Acad. Sci. USA 110, 11039–11043 (2013).
Nicolopoulou-Stamati, P., Maipas, S., Kotampasi, C., Stamatis, P. & Hens, L. Chemical pesticides and human health: the urgent need for a new concept in agriculture. Front. Public Health 4, 148 (2016).
Tilman, D. et al. Forecasting agriculturally driven global environmental change. Science 292, 281–284 (2001).
Bouwman, A., Boumans, L. & Batjes, N. Modeling global annual N2O and NO emissions from fertilized fields. Glob. Biogeochem. Cycles 16, 1080 (2002).
Cordell, D., Drangert, J. O. & White, S. The story of phosphorus: global food security and food for thought. Glob. Environ. Change 19, 292–305 (2009).
Ippolito, A. et al. Modeling global distribution of agricultural insecticides in surface waters. Environ. Pollut. 198, 54–60 (2015).
Silva, V. et al. Pesticide residues in European agricultural soils—a hidden reality unfolded. Sci. Total Environ. 653, 1532–1545 (2019).
Stehle, S. & Schulz, R. Agricultural insecticides threaten surface waters at the global scale. Proc. Natl Acad. Sci. USA 112, 5750–5755 (2015).
Maggi, F., la Cecilia, D., Tang, F. H. M. & McBratney, A. The global environmental hazard of glyphosate use. Sci. Total Environ. 717, 137167 (2020).
Li, Y. F., Scholtz, M. T. & Van Heyst, B. J. Global gridded emission inventories of β-hexachlorocyclohexane. Environ. Sci. Technol. 37, 3493–3498 (2003).
Shunthirasingham, C. et al. Spatial and temporal pattern of pesticides in the global atmosphere. J. Environ. Monit. 12, 1650–1657 (2010).
Gassert, F., Luck, M., Landis, M., Reig, P. & Shiao, T. Aqueduct Global Maps 2.1: Constructing Decision-Relevant Global Water Risk Indicators (World Resources Institute, 2014).
Bird Species Distribution Maps of the World v.2019.1 (BirdLife International and Handbook of the Birds of the World, 2019); http://datazone.birdlife.org/species/requestdis
IUCN & CIESIN Gridded Species Distribution: Global Mammal Richness Grids, 2015 Release (NASA SEDAC, 2015); https://doi.org/10.7927/H4N014G5
IUCN & CIESIN Gridded Species Distribution: Global Amphibian Richness Grids, 2015 Release (NASA SEDAC, 2015); https://doi.org/10.7927/H4RR1W66
Roll, U. et al. The global distribution of tetrapods reveals a need for targeted reptile conservation. Nat. Ecol. Evol. 1, 1677 (2017).
Trevisan, M., Di Guardo, A. & Balderacchi, M. An environmental indicator to drive sustainable pest management practices. Environ. Model. Softw. 24, 994–1002 (2009).
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. Sci. Data 6, 170 (2019).
Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycles 22, GB1022 (2008).
Zhan, Y. & Zhang, M. PURE: A web-based decision support system to evaluate pesticide environmental risk for sustainable pest management practices in California. Ecotoxicol. Environ. Safe. 82, 104–113 (2012).
Maloney, E., Morrissey, C., Headley, J., Peru, K. & Liber, K. Can chronic exposure to imidacloprid, clothianidin, and thiamethoxam mixtures exert greater than additive toxicity in Chironomus dilutus? Ecotoxicol. Environ. Safe. 156, 354–365 (2018).
Pape‐Lindstrom, P. A. & Lydy, M. J. Synergistic toxicity of atrazine and organophosphate insecticides contravenes the response addition mixture model. Environ. Toxicol. Chem. 16, 2415–2420 (1997).
Davidson, C., Shaffer, H. B. & Jennings, M. R. Spatial tests of the pesticide drift, habitat destruction, UV‐B, and climate‐change hypotheses for California amphibian declines. Conserv. Biol. 16, 1588–1601 (2002).
Köhler, H. R. & Triebskorn, R. Wildlife ecotoxicology of pesticides: can we track effects to the population level and beyond? Science 341, 759–765 (2013).
Lenzen, M. et al. International trade drives biodiversity threats in developing nations. Nature 486, 109–112 (2012).
Ansara-Ross, T. M., Wepener, V., Van den Brink, P. J. & Ross, M. J. Pesticides in South African fresh waters. Afr. J. Aquat. Sci. 37, 1–16 (2012).
Li, J., Li, F. & Liu, Q. Sources, concentrations and risk factors of organochlorine pesticides in soil, water and sediment in the Yellow River estuary. Mar. Pollut. Bull. 100, 516–522 (2015).
van Vliet, M. T., Flörke, M. & Wada, Y. Quality matters for water scarcity. Nat. Geosci. 10, 800–802 (2017).
Deutsch, C. A. et al. Increase in crop losses to insect pests in a warming climate. Science 361, 916–919 (2018).
McBratney, A., Field, D. J. & Koch, A. The dimensions of soil security. Geoderma 213, 203–213 (2014).
Möhring, N. et al. Pathways for advancing pesticide policies. Nat. Food 1, 535–540 (2020).
Kudsk, P., Jørgensen, L. N. & Ørum, J. E. Pesticide load—a new Danish pesticide risk indicator with multiple applications. Land Use Policy 70, 384–393 (2018).
Wendling, Z. A. et al. 2020 Environmental Performance Index (Yale Center for Environmental Law & Policy, 2020).
Baker, N. T. Estimated Annual Agricultural Pesticide Use by Major Crop or Crop Group for States of the Conterminous United States, 1992–2016 (USGS, 2018); https://doi.org/10.5066/F7NP22KM
Gutsche, V. & Rossberg, D. SYNOPS 1.1: a model to assess and to compare the environmental risk potential of active ingredients in plant protection products. Agric. Ecosyst. Environ. 64, 181–188 (1997).
Röpke, B., Bach, M. & Frede, H. DRIPS – a decision support system estimating the quantity of diffuse pesticide pollution in German river basins. Water Sci. Technol. 49, 149–156 (2004).
Waitz, M., Freijer, J., Kreule, P. & Swartjes, F. The VOLASOIL Risk Assessment Model Based on CSOIL for Soils Contaminated with Volatile Compounds RVIM Report No. 715810014, 1–189 (National Institute of Public Health and The Environment, 1996).
European Chemicals Bureau Technical Guidance Document on Risk Assessment in Support of Commission Directive 93/67/EEC on Risk Assessment for New Notified Substances, Commission Regulation (EC) No 1488/94 on Risk Assessment for Existing Substances, and Directive 98/8/EC of the European Parliament and of the Council Concerning the Placing of Biocidal Products on the Market (Institute for Health and Consumer Protection, 2003).
Lewis, K. A., Tzilivakis, J., Warner, D. J. & Green, A. An international database for pesticide risk assessments and management. Hum. Ecol. Risk. Assess. 22, 1050–1064 (2016).
European Commission. Directive 2006/118/EC of the European Parliament and of the Council of 12 December 2006 on the protection of groundwater against pollution and deterioration. Off. J. Eur. Union L 372, 19–31 (2006).
Nagai, T. Ecological effect assessment by species sensitivity distribution for 68 pesticides used in Japanese paddy fields. J. Pestic. Sci. 41, 6–14 (2016).
Hengl, T. et al. SoilGrids250m: global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).
Global Soil Data Products CD-ROM Contents (IGBP-DIS) Data Set (Oak Ridge National Laboratory Distributed Active Archive Center, 2014); https://doi.org/10.3334/ORNLDAAC/565
Dai, Y. et al. A global high‐resolution dataset of soil hydraulic and thermal properties for land surface modeling. J. Adv. Model. Earth Syst. 11, 2996–3023 (2019).
Brooks, R. H. & Corey, A. T. Properties of porous media affecting fluid flow. J. Irrig. Drain. Div. 92, 61–90 (1966).
Fan, Y., Li, H. & Miguez-Macho, G. Global patterns of groundwater table depth. Science 339, 940–943 (2013).
Pelletier, J. et al. Global 1-km Gridded Thickness of Soil, Regolith, and Sedimentary Deposit Layers (Oak Ridge National Laboratory Distributed Active Archive Center, 2016); https://doi.org/10.3334/ORNLDAAC/1304
NOAA/OAR/ESRL PSD CPC Global Unified Precipitation Dataset (Physical Sciences Laboratory, 2019); https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html
Zhang, Y. et al. Monthly global observation-driven Penman-Monteith-Leuning (PML) evapotranspiration and components v2. CSIRO Data Collection https://doi.org/10.4225/08/5719A5C48DB85 (2016).
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E. & Houston, T. G. An overview of the global historical climatology network-daily database. J. Atmos. Ocean. Technol. 29, 897–910 (2012).
Fischer, G. et al. Harmonized World Soil Database v1.2 (GAEZ, IIASA & FAO, 2008); http://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12/en/
Pesticide Fact Sheet, Aminopyralid Report No. 7501C (United States Office of Prevention, Pesticides Environmental Protection and Toxic Substances Agency, 2005).
Herner, A. E. The USDA-ARS pesticide properties database: a consensus data set for modelers. Weed Technol. 6, 749–752 (1992).
Mao, L., Zhang, L., Zhang, Y. & Jiang, H. Ecotoxicity of 1, 3-dichloropropene, metam sodium, and dazomet on the earthworm Eisenia fetida with modified artificial soil test and natural soil test. Environ. Sci. Pollut. Res. 24, 18692–18698 (2017).
National Institutes of Health, Health & Human Services ChemIDplus (US National Library of Medicine, 2019); https://chem.nlm.nih.gov/chemidplus/
Public Release Summary on the Evaluation of the New Active Saflufenacil in the Product SHARPEN WG HERBICIDE (Previously Heat Herbicide) APVMA Product Number 62853 (APVMA, 2012).
Pesticide Fact Sheet, Saflufenacil Report No. 7505P (United States Office of Prevention, Pesticides Environmental Protection and Toxic Substances Agency, 2009).
Tang, F. H. M., Lenzen, M., McBratney, A. & Maggi, F. Global pesticide pollution risk data sets. Figshare https://doi.org/10.6084/m9.figshare.10302218 (2021).
Ramankutty, N., Evan, A. T., Monfreda, C. & Foley, J. A. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob. Biogeochem. Cycles 22, GB1003 (2008).
Dell’Oca, A., Riva, M. & Guadagnini, A. Moment-based metrics for global sensitivity analysis of hydrological systems. Hydrol. Earth Syst. Sci. 21, 6219–6234 (2017).
Hvězdová, M. et al. Currently and recently used pesticides in Central European arable soils. Sci. Total Environ. 613, 361–370 (2018).
Fenner, K., Canonica, S., Wackett, L. P. & Elsner, M. Evaluating pesticide degradation in the environment: blind spots and emerging opportunities. Science 341, 752–758 (2013).
Deneer, J. W. Toxicity of mixtures of pesticides in aquatic systems. Pest Manag. Sci. 56, 516–520 (2000).
This work was supported by the University of Sydney through the SREI2020 EnviroSphere research programme. F.M. was also supported by the SOAR Fellowship awarded by the University of Sydney. We thank G. Porta for the discussion and advice on the uncertainty analysis. We acknowledge the Sydney Informatics Hub and the University of Sydney’s high-performance computing cluster Artemis for providing the high-performance computing resources that contributed to the results reported within this work. We acknowledge the use of the National Computational Infrastructure (NCI) which is supported by the Australian Government, and accessed through the Sydney Informatics Hub HPC Allocation Scheme supported by the Deputy Vice-Chancellor (Research), the University of Sydney and the ARC LIEF, 2019: Smith, Muller, Thornber et al., Sustaining and strengthening merit-based access to National Computational Infrastructure (LE190100021). We thank R. Hough and M. Liess for constructive comments on this manuscript.
The authors declare no competing interests.
Peer review information Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editors: Clare Davis, Rebecca Neely.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
a, The land area subject to low quantity and high variability of water supply and high risk of pollution by pesticide mixtures (that is, RS > 3 and AI count > 1). b, The land area bearing high biodiversity and subject to high risk of pollution by pesticide mixtures (that is, RS > 3 and AI count > 1). c, The land area inhabited by at least one endangered or critically endangered amphibian species and subject to pollution risk by pesticide mixtures (RS > 0 and AI count > 1).
Extended Data Fig. 2 The extent of pesticide pollution risk in groundwater, surface water, soil, and atmosphere expressed as percent agricultural land.
For example, surface water within 74% of global agricultural land is at some risk of pesticide pollution. High water risk regions refer to places suffering from low quantity and high variability of water supply defined as in AQUEDUCT-v2.1 database.
About this article
Cite this article
Tang, F.H.M., Lenzen, M., McBratney, A. et al. Risk of pesticide pollution at the global scale. Nat. Geosci. 14, 206–210 (2021). https://doi.org/10.1038/s41561-021-00712-5
This article is cited by
Kinetics and mechanism of photocatalytic degradation of rhodamine B on nanorod bismuth ferrite perovskite prepared by hydrothermal method
Research on Chemical Intermediates (2023)
Environmental Sciences Europe (2022)
Nanomaterials and nanotechnology for the delivery of agrochemicals: strategies towards sustainable agriculture
Journal of Nanobiotechnology (2022)
Nature Food (2022)