Research Data Leeds Repository

Citation

Silver, Ben J. and Conibear, Luke and Reddington, Carly L. and Knote, Christoph and Arnold, Stephen R. and Spracklen, Dominick V. (2020) Data for 'Pollutant emission reductions deliver decreased PM2.5-caused mortality across China during 2015–2017'. University of Leeds. [Dataset] https://doi.org/10.5518/878

Dataset description

This dataset accompanies the paper 'Pollutant emission reductions deliver decreased PM2.5-caused mortality across China during 2015–2017.' This paper used the WRF-Chem model to simulate air quality over China during 2015-2017. Two model runs are performed, one with changing emissions, and the other with fixed emissions. The data for PM2.5, Ozone, NO2 and SO2 are analysed. The model data generated was compared with a comprehensive set of measurements collected by the China National Environmental Monitoring Centre (CNEMC). Using the TheilSen estimator, trends in that data collected at each station are calculated. Time series are extracted by interpolation at the locations of the measurement stations from the model fields, and the trend in this modelled data is calculated using the same method. The comparison of the trends from the measurements and both model runs is used to determine whether trends were driven primarily by emissions changes or meteorological variability. This dataset contains the calculated trend at each station from the measurements and each model run. It also contains measurement data time series for each station in the CNEMC network. This has been updated with the latest data and now covers the period 2014-05-13 to 2020-06-06.

The measurement data is attributed to Xiaolei Wang (https://quotsoft.net/)

Divisions:	Faculty of Environment > School of Earth and Environment
Related resources:	Location Type https://doi.org/10.5194/acp-2019-1141 Publication https://doi.org/10.5194/acp-20-11683-2020 Publication https://eprints.whiterose.ac.uk/165654/ Publication https://quotsoft.net/ Dataset https://openaq.org/ Dataset
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	24 Aug 2020 11:14
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/735
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Silver, Ben J. https://orcid.org/0000-0003-0395-0637 University of Leeds https://ror.org/024mrxd33 ror Conibear, Luke https://orcid.org/0000-0003-2801-8862 University of Leeds https://ror.org/024mrxd33 ror Reddington, Carly L. https://orcid.org/0000-0002-5990-4966 University of Leeds https://ror.org/024mrxd33 ror Knote, Christoph https://orcid.org/0000-0001-9105-9179 University of Leeds https://ror.org/024mrxd33 ror Arnold, Stephen R. https://orcid.org/0000-0002-4881-5685 University of Leeds https://ror.org/024mrxd33 ror Spracklen, Dominick V. https://orcid.org/0000-0002-7551-4597 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Contributors: Contribution Name ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Data collector Wang, Xiaolei Publication date: 2020 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: eebjs@leeds.ac.uk Last Modified: 02 Sep 2024 09:58

Files

Documentation

readme [1kB] readme [1kB] readme [1kB] Security: Anyone File name: readme.txt Content type: Documentation Mime-Type: text/plain File size: 1kB

Data

measured trends [608kB] measured trends [608kB] measured trends [608kB] Security: Anyone File name: trends_meas.csv Content type: Data Mime-Type: text/csv File size: 608kB

modelled trends (varying emissions) [587kB] modelled trends (varying emissions) [587kB] modelled trends (varying emissions) [587kB] Security: Anyone File name: trends_mod_ctl.csv Content type: Data Mime-Type: text/csv File size: 587kB

modelled trends (fixed emissions) [586kB] modelled trends (fixed emissions) [586kB] modelled trends (fixed emissions) [586kB] Security: Anyone File name: trends_mod_ce.csv Content type: Data Mime-Type: text/csv File size: 586kB

measurement_data [88MB] measurement_data [88MB] measurement_data [88MB] Security: Anyone File name: measurement_data.zip Content type: Data Description: The measurement data is attributed to Xiaolei Wang (https://quotsoft.net/) Mime-Type: application/zip File size: 88MB