Sharps, K. et al

Modelled annual average production loss due to ozone damage for four global staple crops 2010-2012

Modelled annual average production loss (thousand tonnes per 1 degree by 1 degree grid cell) due to ground-level ozone pollution is presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum), for the period 2010-2012. Data are on a global scale, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. Modelled ozone data (2010-2012) needed for production loss calculations were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Mapping the global crop production losses due to ozone highlights the impact of ozone on crops and allows areas at high risk of ozone damage to be identified, which is a step towards mitigation of the problem.

The production loss calculations were done as part of the NERC funded SUNRISE project (NEC06476) and National Capability Project NC-Air quality impacts on food security, ecosystems and health (NEC05574).

Publication date: 2020-07-15

Get the data

This dataset is available under the terms of the Open Government Licence

Format of the data: Shapefile

You must cite: Sharps, K.; Mills, G; Simpson, D. ; Pleijel, H. ; Frei, M. ; Burkey, K. ; Emberson, L. ; Uddling, J. ; Broberg, M. ; Feng, Z.; Kobayashi, K.; Agrawal, M. (2020). Modelled annual average production loss due to ozone damage for four global staple crops 2010-2012. NERC Environmental Information Data Centre.


© UK Centre for Ecology & Hydrology

© Norwegian Meteorological Institute

© University of Bonn

© Stockholm Environment Institute at York

© University of Gothenburg

© The University of Tokyo

© Banaras Hindu University


Study area
Temporal extent
2010-01-01    to    2012-12-31

Provenance & quality

A 1 degree by 1degree grid was created using ArcMap. Crop production data (0.0833 degree resolution) from the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) dataset (for the year 2000) was downloaded. Irrigated and non-irrigated production data was collected for each crop type. For each crop, total production was summed per 1° by 1° grid cell. Then average production for the period 2010-2012 for each grid cell was estimated using a conversion factor from FAO national crop production data, based on the difference between average production for the period 1999-2001 and 2010-2012. For each crop, only grid cells with greater than 500 tonnes crop production were included when mapping yield loss.

Each grid cell was classed as either irrigated (greater than 7% irrigated crop production) or non-irrigated. Grid cells were also assigned to a hemisphere (Northern or Southern) and a climate zone. For each hemisphere/climate zone combination, a 90-day growing period was set, based on the main growing season per year for each crop.

The EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16) was used to calculate daily ozone flux (POD3IAM; phytotoxic ozone dose above 3 nmol m−2 s−1, parameterized for integrated assessment modelling) for the years 2010 - 2012. For each crop, the accumulated 90-day POD3IAM was calculated per grid cell based on the climate specific growing period and the irrigation class for the cell, and an average value calculated for the period 2010-2012.

Yield loss was calculated using the ozone dose-response relationship for wheat, following the most recent methodology adopted by the Convention for Long-Range Transboundary Air Pollution (CLRTAP) in 2017. First a reference value of POD3IAM = 0.1mmol/m2 (used to represent ozone uptake at pre-industrial or natural ozone levels) was subtracted before yield loss was calculated. This value was the mean POD3IAM for the experimental conditions included in the dose-response relationship, assuming constant 10 ppb ozone throughout the 90-day period.

The equation used to calculate percentage yield loss was as follows: Percentage Yield Loss = (POD3IAM – 0.1) * 0.64
where 0.64 is the slope of the relationship between POD3IAM and percentage yield reduction and represents the percentage reduction per mmol/m2 POD3IAM.

For maize, rice and soybean, the POD3IAM values per grid cell were first used to calculate percentage yield loss using the equation for wheat. Then the relative ozone sensitivity of each crop compared to wheat was calculated by dividing the slope of the M7 (7-hour mean ozone concentration) response function for the crop by that for wheat. For each grid cell, the percentage yield loss for wheat was multiplied by the relative ozone sensitivity value, to calculate the final estimated percentage yield loss for each crop.

Production loss for each crop was then calculated per grid square using total crop production per grid cell (averaged for 2010-2012) and the estimated yield loss per grid cell, with the following equation:
Production loss (thousand tonnes) = Crop production (thousand tonnes) * (percent yield loss/100)

Production loss values were added to the 1° by 1° grid and saved as GIS shapefiles, with one file per crop.

An evaluation of EMEP model performance found a strong correlation between modelled and measured ozone data from Global Atmosphere Watch (GAW) sites. The EMEP model was found to capture spatial and temporal variations in ozone across regions.

Supplemental information

This dataset is a supplement to:

Mills, G., Sharps, K., Simpson, D., Pleijel, H., Frei, M., Burkey, K., Emberson, L., Uddling, J., Broberg, M., Feng, Z., Kobayashi, K., & Agrawal, M. (2018). Closing the global ozone yield gap: Quantification and cobenefits for multistress tolerance. Global Change Biology, 24(10), 4869–4893.

Other useful information regarding this dataset:

Mills, G., Sharps, K., Simpson, D., Pleijel, H., Broberg, M., Uddling, J., … Van Dingenen, R. (2018). Ozone pollution will compromise efforts to increase global wheat production. Global Change Biology, 24(8), 3560–3574.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., & Wind, P. (2012). The EMEP MSC-W chemical transport model – technical description. Atmospheric Chemistry and Physics, 12(16), 7825–7865.

Correspondence/contact details

Sharps, K.
UK Centre for Ecology & Hydrology


Sharps, K.
UK Centre for Ecology & Hydrology
Mills, G
UK Centre for Ecology & Hydrology
Simpson, D.
EMEP MSC‐W, Norwegian Meteorological Institute
Pleijel, H.
University of Gothenburg
Frei, M.
University of Bonn
Burkey, K.
United States Department of Agriculture – Agricultural Research Service (USDA‐ARS)
Emberson, L.
Stockholm Environment Institute, University of York
Uddling, J.
University of Gothenburg
Broberg, M.
University of Gothenburg
Feng, Z.
Research Center for Eco‐Environmental Sciences, Chinese Academy of Sciences
Kobayashi, K.
University of Tokyo
Agrawal, M.
Banaras Hindu University

Other contacts

Environmental Information Data Centre
NERC Environmental Information Data Centre
Sharps, K.
UK Centre for Ecology & Hydrology

Additional metadata

Topic categories
Environment , Farming , Climatology / Meteorology / Atmosphere
Agriculture Air pollution impact,  Glycine max Maize,  Oryza sativa Ozone,  Pollution Production loss,  Rice,  Soybean,  SUNRISE Triticum aestivum Wheat,  Wheat,  Zea mays
Environmental Monitoring Facilities
Natural Environment Research Council Award: NE/R000131/1
Spatial representation type
Spatial reference system
WGS 84
Last updated
11 May 2021 11:23