From 1990 to 2022, the worldwide agricultural use of pesticides steadily increased, reaching 3.69 million metric tons in 2022. This growth in pesticide usage reflects the vital role of crop protection chemicals in enhancing agricultural yield and ensuring food security amidst an array of global challenges such as anthropogenic climate change, and population growth. What is the most popular type of pesticide? Pesticides encompass a broad range of products, including herbicides, fungicides, bactericides, insecticides, plant growth regulators, and rodenticides. Of these, herbicides are the most commonly used, primarily for eradicating unwanted plants like weeds or grass. In 2022, the global use of herbicides hit 1.94 million metric tons, while the usage of other types of pesticides stayed below one million metric tons. Herbicides have a significant role in maintaining crop health and yield by controlling the growth of unwanted plants that compete with crops for nutrients, water, and sunlight. In 2022, the largest share of sales for herbicides in the European Union (EU) was attributed to organophosphorus herbicides. These organophosphorus herbicides include glyphosate, a commonly used herbicide that has been the subject of controversy due to its potential health and environmental effects. What are the impacts of pesticide use? The increased use of pesticides worldwide raises concerns about their environmental footprint. Pesticides can have harmful impacts on non-target species, including beneficial insects, birds, and aquatic organisms. They can also contaminate soil, water, and other vegetation. In addition to the direct effects on wildlife, pesticides can disrupt ecosystems by altering species composition and biodiversity. Furthermore, some pesticides have been linked to human health problems, ranging from short-term impacts such as headaches and nausea to chronic impacts like cancer, reproductive harm, and endocrine disruption. The European Food Safety Authority (EFSA) routinely monitors the levels of pesticide residues in food and whilst the majority of the food samples tested comply with legal limits, a small percentage surpass these limits, highlighting the necessity for ongoing observation and regulation. In 2021, Cyprus was the European country that had the highest proportion of import samples exceeding the MRL, with over one in six food samples from Cyprus containing excessive pesticide residue.

Code and data to generate GloPUT database. Data set description found in "Global pesticide use and trade database (GloPUT): New estimates show pesticide use trends in low-income countries substantially underestimated." (2023) Global Environmental Change.

Link to paper: https://doi.org/10.1016/j.gloenvcha.2023.102693

The Global Pesticide Grids (PEST-CHEMGRIDS) includes a comprehensive database of the 20 most-used pesticide active ingredients on 6 dominant crops and 4 aggregated crop classes at 5 arc-minute resolution (about 10 km at the equator), estimated in year 2015 and projected to 2020 and 2025. To estimate the global application rates of specific active ingredients, spatial statistical methods were used to re-analyze the U.S. Geological Survey Pesticide National Synthesis Project (USGS/PNSP) and the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) pesticide databases, along with other public inventories including global gridded data of soil physical properties, hydro-climatic variables, agricultural quantities, and socioeconomic indices. The data set also includes 200 data quality maps corresponding to each active ingredient on each crop, as well as maps of the 10 dominant crops and 4 aggregated crop classes.

The Global Pesticide Grids (PEST-CHEMGRIDS), Version 1.01 data set contains 20 of the most-used pesticide active ingredients on 6 dominant crops and 4 aggregated crop classes at 5 arc-minute resolution (about 10 km at the equator), estimated in year 2015, and then projected to 2020 and 2025. To estimate the global application rates of specific active ingredients, spatial statistical methods were used to re-analyze the U.S. Geological Survey Pesticide National Synthesis Project (USGS/PNSP) and the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) pesticide databases, along with other public inventories including globally gridded data of soil physical properties, hydro-climatic variables, agricultural quantities, and socioeconomic indices. The application rate (APR) of each active ingredient on each crop is in kilogram per hectare per year (kg/ha-year), and the harvest area of each crop is in hectare (ha). The data set also includes 200 data quality index maps corresponding to each active ingredient on each crop, as well as maps of the 10 dominant crops and 4 aggregated crop classes. Version 1.01 includes data in GeoTIFF and netCDF formats.

Three global maps are included in this data set: the first is the pesticide risk scores map showing the exposure of agricultural land to pesticide pollution, the second is the active ingredient counts map quantifying the number of active ingredients posing pollution risk to agricultural land and showing the exposure of environment to pesticide mixtures, and the third is the regions of concern map identifying areas susceptible to pesticide pollution.

A zip folder containing an example of risk score calculation is attached together with this data set. Details of the methods used to produce these maps and the tabulated data can be found in Tang F.H.M, Lenzen M., McBratney A., and Maggi F. (2021). Risk of pesticide pollution at the global scale, Nature Geoscience.

PEST-CHEMGRIDS is a comprehensive database of the 20 most used pesticide active ingredients on 6 dominant crops and 4 aggregated crop classes at 5 arc-min resolution (about 10 km at the equator) projected from 2015 to 2025.See attached metadata file for details on this release

This is a dataset for data generated in Tang et al. (2022). This dataset includes three Supplementary Data files, five source data files, and the georeferenced global maps of pesticide hazard loads for 175 crops. The pesticide hazard loads are defined as the total body weight (bw) of non-target organisms required to absorb pesticides accumulated in the environment at an annual intake that will not result in observable adverse effects. The pesticide hazard load maps have a unit of kg-bw. The maps and analyses refer to the pesticide use as of 2015. Details of the methods used to produce these maps and analyses can be found in Tang et al. (2022).

Tang F.H.M, Malik A., Li M., Lenzen M., and Maggi F. (2022). International demand for food and services drives environmental footprints of pesticide use. Communications Earth & Environment, 3:272, https://doi.org/10.1038/s43247-022-00601-8.

Global Pesticides Use on Crops by Country, 2023 Discover more data with ReportLinker!

Food and Agriculture Organization of the United Nations (2017). Food and Agriculture Organization Statistics: Environment - Pesticide Use | Country: Italy | Item: Pesticides | Element: Active ingredient use in Arable Land & Permanent Crops - tonnes per 1000 Ha, 1990-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 067-001-051. Dataset: Reports pesticide use on arable and permanent crop area (tonnes/1000 hectare). The time-series and cross-sectional data provided here are from the FAOSTAT database of the Food and Agriculture Organization of the United Nations. Statistics include measures related to the food supply; forestry; agricultural production, prices, and investment; and trade and use of resources, such as fertilizers, land, and pesticides. As available, data are provided for approximately 245 countries and 35 regional areas from 1961 through the present. The data are typically supplied by governments to FAO Statistics through national publications and FAO questionnaires. Official data have sometimes been supplemented with data from unofficial sources and from other national or international agencies or organizations. In particular, for the European Union member countries, with the exception of Spain, data obtained from EUROSTAT have been used. Category: Natural Resources and Environment, Agriculture and Food Source: Food and Agriculture Organization of the United Nations Established in 1945 as a specialized agency of the United Nations, the Food and Agricultural Organization’s mandate is to raise levels of nutrition, improve agricultural productivity, better the lives of rural populations, and contribute to the growth of the world economy. Staff experts in seven FAO departments serve as a knowledge network to collect, analyze, and disseminate data, sharing policy expertise with member countries and implementing projects and programs throughout the world aimed at achieving rural development and hunger alleviation goals. The Statistics Division of the Food and Agricultural Organization collates and disseminates food and agricultural statistics globally. http://www.fao.org/ Subject: Agricultural Production, Crops, Pesticides, Agriculture

This data set includes four global maps of aggregated pesticides: (1) the total pesticide content in the topsoil of global croplands expressed in the unit of mg/kg-soil; (2) the number of pesticides detected in the topsoil; (3) the pesticide leaching rate to below the root zone expressed in the unit of mg/m2/year; and (4) the number of pesticides that exceeded a leaching rate of 1 mg/m2/year. This data set also includes two zip folders containing the topsoil residue and leaching rate of individual pesticide substances in nine different cropping systems. The surface area of the nine cropping systems can be obtained from the PEST-CHEMGRIDS dataset (Maggi et al., 2019).

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zip folder containing an example of input files required to run the model is attached together with this data set. Details of the methods used to produce these maps and the tabulated data can be found in Tang F.H.M and Maggi F. (2021). Pesticide mixtures in soil: a global outlook, Environmental Research Letters.

The FAOSTAT Pesticides Use domain contains statistics on the agricultural use of major pesticide groups and of relevant chemical families. Data are disseminated by country, with global coverage, over the period 1990-2022, with annual updates.The FAOSTAT Pesticides Use domain contains information on the use of major pesticide groups:1. Insecticides (Chlorinated hydrocarbons, Organo–phosphates, Carbamates– insecticides, Pyrethroids, Botanical and biological products and Others not elsewhere classified);2. Mineral Oils;3. Herbicides (Phenoxy hormone products, Triazines, Amides, Carbamates– herbicides, Dinitroanilines, Urea derivatives, Sulfonyl urea, Bipiridils, Uracil, Others not elsewhere classified);4. Fungicides and Bactericides (Inorganic, Dithiocarbamates, Benzimidazoles, Triazoles Diazoles, Diazines Morpholines, Others not elsewhere classified);5. Plant Growth Regulators;6. Rodenticides (Anti–coagulants, Cyanide Generators, Hypercalcaemics, Narcotics, Others not elsewhere classified);7. Other Pesticides NES (not elsewhere specified).

The data included in Data360 is a subset of the data available from the source. Please refer to the source for complete data and methodology details.

This collection includes only a subset of indicators from the source dataset.

The Global Pesticide Grids (PEST-CHEMGRIDS) includes a comprehensive database of the 20 most-used pesticide active ingredients on 6 dominant crops and 4 aggregated crop classes at 5 arc-minute resolution (about 10 km at the equator), estimated in year 2015 and projected to 2020 and 2025. To estimate the global application rates of specific active ingredients, spatial statistical methods were used to re-analyze the U.S. Geological Survey Pesticide National Synthesis Project (USGS/PNSP) and the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) pesticide databases, along with other public inventories including global gridded data of soil physical properties, hydro-climatic variables, agricultural quantities, and socioeconomic indices. The data set also includes 200 data quality maps corresponding to each active ingredient on each crop, as well as maps of the 10 dominant crops and 4 aggregated crop classes.

The research carried out by the World Bank in the summer of In 2003 used structured questionnaires to collect information on pesticide use and practices, risk perceptions, knowledge, precautions and damage averting behavior, and health effects from 1,078 farmers (175 owners, 132 applicators & 771 owner+applicator), randomly selected. The survey was designed and supervised by the World Bank team, and conducted by the Development Policy Group in Bangladesh. The survey, by design, focused on major pesticide intensive crops such as Boro (winter rice), potato, bean, eggplant, cabbage, sugarcane and mango. To provide greater depth, 68 randomly-selected farmers who currently use Integrated Pest Management (IPM) were also interviewed. The sample was geographically stratified among 11 districts of Bangladesh as: Bogra, Chapainawabganj, Rajshahi, and Rangpur districts in the Rajshahi division (Northwest); Chittagong and Comilla in the Chittagong division (East); Jessore in the Khulna division (West); and Kishoreganj, Munshiganj, Narsingdi, and Mymensingh in the Dhaka division. To minimize reporting bias, the survey was implemented under the agreement that the team would not reveal the identity of the farms surveyed or the respondents who participated.

Pesticides continue to pose a significant threat to the environment, endangering both aquatic and terrestrial ecosystems. However, effectively targeting and reducing pesticide toxicity in the environment faces several challenges. These challenges include evaluating toxicity over large areas, obtaining precise spatiotemporal data on pesticide use, assessing cumulative toxicity, and identifying the health and economic impacts of pesticide application sites. To address these challenges, we present the Environmental Release Tool, a sub-tool of the Pesticide Mitigation Prioritization Model. This tool aims to advance the understanding in these four areas and facilitate pesticide management by promoting collaboration between experts and non-experts. It employs a framework that generates user-friendly graphical and tabular summaries of pesticide impact information, contextualized within management opportunities.

While the Pesticide Mitigation Prioritization Model can be applied across the United States, its utility is particularly valuable in California. This is because the California Department of Pesticide Regulation (CDPR) hosts the most comprehensive pesticide use data globally. The CDPR's Pesticide Use Reports (PUR) database records agricultural pesticide applications on a daily time step and at the scale of one square mile (2.6 square kilometers) per application site. Leveraging this extensive database, we have integrated it directly into the Pesticide Mitigation Prioritization Model. This integration enables us to rapidly quantify the applied pesticide toxicity by chemical, source, and watershed across California, typically within seconds to minutes.

This new release of PEST-CHEMGRIDS (version 2.01, beta) delivers updated application rates for up to 115 individual Pesticide Active Substances (PAS) covering 6 individual major crops and 4 aggregated crops at a global spatial resolution of 0.05 degree/grid cell (approximately 5.5 km at the equator). This update includes new datasets used for estimates construction, an improved method of spatialization as compared to PEST-CHEMGRIDSv1.01, and a wider validation. We have also included updates of national bans on specific PAS and a wider set of nationally approved GMOs and PAS. The estimates in PEST-CHEMGRIDS v2.01beta provide “high” and “low” application rates in 2015 and 2018.

Data in this release were collected and computed to evaluate the occurrence of pesticides in shallow groundwater in the state of Alabama. Additionally, these data support interpretation in Gill (2023) for a cooperative project between the U.S. Geological Survey and the Alabama Department of Agriculture and Industries. During 2009-2020, samples were collected from twenty-four wells located near agricultural land use in Alabama and evaluated for concentrations of agricultural pesticides and pesticide degradates. Most data produced from the sampling effort are available from the publicly accessible USGS National Water Information System (NWIS; U.S. Geological Survey, 2023). For certain pesticide compounds, data were combined from multiple analytical methods to provide a longer period of record in order to evaluate changes in concentrations and occurrence through time. All groundwater quality data used in Gill (2023), including supporting quality assurance datasets, are included in this data release. References: Gill, A.C., 2023, Pesticide occurrence in shallow groundwater near areas of agricultural land use in Alabama, 2009-2020: U.S. Geological Survey Scientific Investigations Report 2023-xxxx, xx p., https://doi.org/xxxx. U.S. Geological Survey, 2023, National Water Information System data available on the World Wide Web (USGS Water Data for the Nation), accessed April 21, 2023, at http://dx.doi.org/10.5066/F7P55KJN.

Pesticides as covered in the project include acaricides, biological pesticides (bacteria, viruses), defoliants, dessicants, fumigants, fungicides, herbicides, insecticides, molluscicides, nematicides, rodenticides and synergists. Pesticides included are those used in plant protection, in animal health (products for external use only), in human health programmes and for urban pest control.This is the second edition of "Pesticide use in the South Pacific. " The first edition was issued by the South Pacific Regional Environment Programme (SPREP) entitled "Pesticide use in the South Pacific" preliminary printing. October 1986.|Kept in the Vertical File and available onlineCall Number: VF 1619 [EL],363.17 MOW,REG,PESPhysical Description: [various pagings] ; 29 cm.

The files include all three scripts and databases used in the statistical analysis perofrmed in the manuscript titled "Widespread triazole pesticide use affects infection dynamics of a global amphibian pathogen"

Ponds epoxiconazole dataset contains the site name, sampling period, numer of infected animals, number of not infected animals, epoxiconazole concentration, and epoxiconazole concentration log_transformed.

The R script with the same name contains the code with which the analysis described in the manuscript relative to the fieldwork were run.

Tadpoles epoxiconazole database includes the sample name, the sample group, infection status, body length (BL) of the animal sampled, Infection load (GE_load) of the sample, body lenght*1000 (BL1000), and infection load log_transformed (GE_load_trans). The dataset is relative to an infection and exposure trial where tadpoles were exposed to the triqzole fungicide epoxiconazole and infected with Batrachochytrium dendrobatidis. The experiment is described in depth in the manuscript.

The R script with the same name contains the code with which the analysis included in the manuscript were run.

Tadpoles epoxiconazole 2 databse includes the treatment and the infection status of the sampled animal.They refer to the same experiment described above for the database "tadpoles_epoxiconazole_db"

The R script with the same name contains the code with which the analysis included in the manuscript were run.

The ever-increasing use of pesticides in response to the rising agricultural demand has threatened the existence of nontarget organisms like avian species, disrupting the global ecological integrity. Therefore, it is critical to protect and restore different endangered bird species from the perspective of ecosystem safety. In the present work, we have developed regression-based two-dimensional quantitative structure toxicity relationship (2D QSTR) and quantitative structure toxicity–toxicity relationship (QSTTR) models to estimate the toxicity of pesticides on five different avian species following the Organization for Economic Co-operation and Development (OECD) guidelines. Rigorous validation has been performed using different statistical internal and external validation parameters to ensure the robustness and interpretability of the developed models. From the developed models, it can be stated that the presence of electronegative and lipophilic features greatly enhance pesticide toxicity, whereas the hydrophilic characters are shown to have a detrimental impact on the toxicity of pesticides. Moreover, the developed QSTTR models have been employed to the in silico toxicity prediction of 124, 154, and 250 pesticides against bobwhite quail, ring-necked pheasant, and mallard duck species, respectively, extracted from the Office of Pesticides Program (OPP) Pesticide Ecotoxicity Database. The information obtained from the modeled descriptors might be used for pesticide risk assessment in the future, with the added benefit of providing an early caution of their possible negative impact on birds for regulatory purposes.

The research carried out by the World Bank in the summer of In 2003 used structured questionnaires to collect information on pesticide use and practices, risk perceptions, knowledge, precautions and damage averting behavior, and health effects from 1,078 farmers (175 owners, 132 applicators & 771 owner+applicator), randomly selected. The survey was designed and supervised by the World Bank team, and conducted by the Development Policy Group in Bangladesh. The survey, by design, focused on major pesticide intensive crops such as Boro (winter rice), potato, bean, eggplant, cabbage, sugarcane and mango. To provide greater depth, 68 randomly-selected farmers who currently use Integrated Pest Management (IPM) were also interviewed. The sample was geographically stratified among 11 districts of Bangladesh as: Bogra, Chapainawabganj, Rajshahi, and Rangpur districts in the Rajshahi division (Northwest); Chittagong and Comilla in the Chittagong division (East); Jessore in the Khulna division (West); and Kishoreganj, Munshiganj, Narsingdi, and Mymensingh in the Dhaka division. To minimize reporting bias, the survey was implemented under the agreement that the team would not reveal the identity of the farms surveyed or the respondents who participated.