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| Last Updated: :05/02/2020

BIBLIOGRAPHY

Title : Assessment of the contribution of in-situ combustion of coal to greenhouse gas emission; based on a comparison of Chinese mining information to previous remote sensing estimates
Subject : Coal Geology
Volume No. : 86
Issue No. : 
Author : Paul van Dijk, Jianzhong Zhang, Wang Jun, Claudia Kuenzer, Karl-Heinz Wolf
Printed Year : 2011
No of Pages  : 12: 108–119
Description : 

Greenhouse gas (GHG) emission from geological sources such as volcanic activity, seabed gas hydrate release, hydrocarbon seepage as well as uncontrolled combustion of fossil fuels is erratic and difficult to quantify. In this paper we assess the GHG emission due to spontaneous combustion of in-situ coal deposits (‘coal fires’). This problem is aggravated by human intervention (mining activities) which on the other hand allows better constrained estimations and improved reduction strategies, provided modern mining practices are employed. In this study we present three case studies on coal fire-related GHG emission quantification on provincial scale in China, and we propose an integrated quantification aimed at the joint analyses of local knowledge, geophysical data, and remote sensing data with the objective to retrieve unbiased numbers. As a first estimate, we conclude that the emissions of GHGs from coal fires in China account for well less than 0.22% of all global fossil fuel related CO2 emissions, most likely even less than 0.1%. This is much less than the previously estimated 2–3%.


Title : Assessment of the contribution of in-situ combustion of coal to greenhouse gas emission; based on a comparison of Chinese mining information to previous remote sensing estimates
Subject : Remote Sensing and GIS
Volume No. : 86
Issue No. : 
Author : Paul van Dijk, Jianzhong Zhang, Wang Jun, Claudia Kuenzer, Karl-Heinz Wolf
Printed Year : 2011
No of Pages  : 108–119
Description : 

Assessment of the contribution of in-situ combustion of coal to greenhouse gas emission; based on a comparison of Chinese mining information to previous remote sensing estimates