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PEST-CHEMGRIDS, global gridded maps of the top 20 crop-specific pesticide application rates from 2015 to 2025

Authors :
Federico Maggi
Fiona H. M. Tang
Daniele la Cecilia
Alex B. McBratney
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)

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