Preprints
https://doi.org/10.5194/acp-2020-1330
https://doi.org/10.5194/acp-2020-1330

  28 Jan 2021

28 Jan 2021

Review status: this preprint is currently under review for the journal ACP.

Development of New Emission Reallocation Method for Industrial Nonpoint Source in China

Yun Fat Lam1, Chi Chiu Cheung2, Xuguo Zhang3, Joshua S. Fu4, and Jimmy Chi Hung Fung3 Yun Fat Lam et al.
  • 1Department of Geography, University of Hong Kong, HKSAR, China
  • 2ClusterTech Limited, HKSAR, China
  • 3Institute for the Environment, Hong Kong University of Science and Technology, HKSAR, China
  • 4Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, USA

Abstract. 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 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 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 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.

Yun Fat Lam et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2020-1330', Anonymous Referee #1, 14 Mar 2021
  • RC2: 'Comment on acp-2020-1330', Anonymous Referee #2, 15 Apr 2021

Yun Fat Lam et al.

Yun Fat Lam et al.

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Short summary
In recent years, air pollution forecast has become an important municiple service of government. In this study, a new spatial allocation method based on satellite remote sensing and GIS techniques was developed to address the spatial deficiency of non-point source emissions in China, providing substantial improvement on NO2 and PM2.5 forecast for the Pearl River Delta/Greater Bay Area.
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