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Supplementary material to "Development of New Emission Reallocation Method for Industrial Nonpoint Source in China"

An accurate emission inventory is a crucial part of air pollution management and is essential for air quality modelling. One source in an emission inventory, a nonpoint source, has been known with high uncertainty. In this study, a new industrial 10 nonpoint source (NPS) reallocation method based on blue-roof industrial buildings was developed to replace the conventional method of using population density for emission development in China. The new method utilized the zoom level 14 satellite imagery (i.e., Google®) and processed it with Hue, Saturation, Value (HSV)-based colour classification to derive new spatial surrogates for province-level reallocation, providing more realistic spatial patterns of industrial PM2.5 and NO2 emissions. The WRF-CMAQ based PATH-2016 model system was then applied with the new NPS emissions processed emission input in the 15 MIX inventory to simulate air quality in the Greater Bay Area (GBA) area (formerly called Pearl River Delta (PRD)). In the study, significant RMSE improvement was observed in both summer and winter scenarios in 2015 when compared with the population-based approach. The average RMSE reductions (i.e., 76 stations) of PM2.5 and NO2 were found to be 11 μg/m3 and 3 ppb, respectively. This research demonstrates that the blue-roof industrial allocation method can effectively identify scattered industrial sources in China and is capable of downscaling the industrial NPS emissions from regional to local levels (i.e., 27 20 km to 3 km resolution), overcoming the technical hurdle of ~10 km resolution from the top-down emission approach under the unified framework of emission calculation.