Coal mine methane emissions quantification based on vehicle-based monitoring

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Coal mine methane emissions quantification based on vehicle-based monitoring

Journal Title: Energy Environmental Protection - Year 2023, Vol 37, Issue 1

Abstract

Obtaining accurate emissions of methane (CH_4), one of the most important non-carbon-dioxide greenhouse gases, is the basis for formulating and validating emission reduction policies. In terms of shortcomings from the "bottom-up" approach, this study combined the vehicle-based monitoring and the AERMOD atmospheric dispersion modeling system to derive the emission rates and emission factors of main CH_4 sources in one demonstration coal mine in Jincheng city, Shanxi province. After systematically considering the topography, meteorological conditions, and infrastructure distribution of the coal mine, both the mobile and downwind stationary monitoring alternatives were adopted, using a platform equipped with a high-precision greenhouse gas analyzer. Results showed that the simulated CH_4 emission rate of a single ventilation shaft under non-production condition (763 kg/h) was about 15.9% lower than the data provided by the enterprise in production. If ignoring the fugitive emissions, the derived CH_4 emission factor of the coal mine was 15.09 m^3/t, which was 13.8% smaller than that in " bottom-up" inventory, indicating that the working conditions of the coal mine played a large role in CH_4 emissions. One ventilation shaft and two vent stacks in the gas gathering station were the main point sources, and six coal silos were the fugitive sources, the emission factors of which were 8.6 m^3/t( 43%), 6.49 m^3/t (33%) and 4.87 m^3/t (24%), respectively. The traditional "bottom-up" accounting without consideration of fugitive emissions, resulted in a nearly 24% under estimation of CH_4 emissions even under non-production conditions, which could be compensated by the methane quantification method based on vehicle-based monitoring.

Authors and Affiliations

GAO Lan|State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, China, MAO Huiqin|Satellite Environment Application Center, Ministry of Ecology and Environment, China, LU Xi*|State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, China, Institute for Carbon Neutrality, Tsinghua University, China, Beijing Laboratory of Environmental Frontier Technologies, Tsinghua University, China

Keywords

EP ID EP737800
DOI 10.20078/j.eep.20230204
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