Data for 'Pollutant emission reductions deliver decreased PM2.5-caused mortality across China during 2015–2017'

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/)