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PEST-CHEMGRIDS, global gridded maps of the top 20 crop-specific pesticide application rates from 2015 to 2025
- Source :
- Scientific Data, Vol 6, Iss 1, Pp 1-20 (2019), Scientific Data
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Available georeferenced environmental layers are facilitating new insights into global environmental assets and their vulnerability to anthropogenic inputs. Geographically gridded data of agricultural pesticides are crucial to assess human and ecosystem exposure to potential and recognised toxicants. However, pesticides inventories are often sparse over time and by region, mostly report aggregated classes of active ingredients, and are generally fragmented across local or government authorities, thus hampering an integrated global analysis of pesticide risk. Here, we introduce PEST-CHEMGRIDS, 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. To estimate the global application rates of specific active ingredients we use spatial statistical methods to re-analyse the USGS/PNSP and FAOSTAT pesticide databases along with other public inventories including global gridded data of soil physical properties, hydroclimatic variables, agricultural quantities, and socio-economic indices. PEST-CHEMGRIDS can be used in global environmental modelling, assessment of agrichemical contamination, and risk analysis.<br />Design Type(s)modeling and simulation objective • data integration objective • statistical analysis and modeling objectiveMeasurement Type(s)crop • pesticideTechnology Type(s)statistical data analysis • computational modeling techniqueFactor Type(s)soil • hydroclimate • agricultural feature • Socioeconomic IndicatorSample Characteristic(s)United States of America • agriculture • Earth (Planet) • pasture • Europe Machine-accessible metadata file describing the reported data (ISA-Tab format)
- Subjects :
- Statistics and Probability
Data Descriptor
010504 meteorology & atmospheric sciences
Agrochemical
Pesticide application
Vulnerability
010501 environmental sciences
Library and Information Sciences
01 natural sciences
Education
Risk analysis (business)
Ecosystem
lcsh:Science
0105 earth and related environmental sciences
business.industry
Environmental resource management
Biogeochemistry
Pesticide
Computer Science Applications
Environmental sciences
Metadata
Agriculture
Environmental science
lcsh:Q
Statistics, Probability and Uncertainty
business
Information Systems
Subjects
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- Scientific Data
- Accession number :
- edsair.doi.dedup.....3742c60624096848ff8a084d4c9aecc6
- Full Text :
- https://doi.org/10.1038/s41597-019-0169-4