Gridded dataset of China’s anthropogenic atmospheric mercury emissions

Mercury is a highly toxic substance that can be transported globally, threatening ecosystems and human health. We constructed a gridded dataset of anthropogenic Hg emissions in China at high spatial resolution during 1998-2014.
Published in Research Data
Gridded dataset of China’s anthropogenic atmospheric mercury emissions
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China is the largest atmospheric mercury (Hg) emitter in the world. Mercury emission inventories at national or provincial scale cannot provide a detailed description of the sources of Hg emissions in China. Population distribution data were used as the proxy for constructing many of Hg emission grid data, limiting the reliability of the data. We constructed a 1km×1km high spatial resolution Hg emission dataset for China from 1998 to 2014. This dataset includes data on Hg emissions of four sectors: agriculture, industries, services, and residents. There are 45 sub-sectors which contains 43 production sources and two household sources. The dataset estimates gridded Hg emissions of total Hg (THg), gaseous elemental Hg (Hg0), gaseous oxidized Hg (HgII), and particulate-bound Hg (HgP).

The Hg emissions from the agricultural sector are distributed using gridded land use data as the proxy. The Hg emissions from industries are distributed using information from companies in the Chinese Industrial Enterprises Database. The Hg emissions from the transportation sector are distributed using the roadmap from OpenStreetMap. The Hg emissions from the other service sectors and residents are distributed using gridded population data as the proxy.

This dataset will contribute to more reliable studies related to Hg emissions. First, the dataset can help scholars identify hotpots of Hg emissions on a fine scale, including industrial areas, populated areas, etc. Second, the dataset can be used as an input to various models to support studies on environmental impacts and human health risks. Finally, this dataset helps to identify the main economic sectors that drive Hg emissions during different periods.

The uncertainty of the dataset is related to the accuracy of the data used and the calculation methods. It can be reduced in the following ways. 1) For data calculated using the interpolation method, use more accurate grid maps of land uses and population distribution. 2) Enhance monitoring of Hg emission data and obtain more accurate data on emission factors. 3) For industrial enterprises, construct reliable bottom-up inventories of Hg emissions. 

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