A novel dataset for analysing sub-national socioeconomic developments in the Indian coal industry. (28th January 2021)

• Record Type: Journal Article
• Authors: Pai, Sandeep; Zerriffi, Hisham
• Is Part Of: IOP SciNotes. Volume 2:Number 1(2021)
• Publication Date: 2021-01-28
• Subjects: coal -- India -- energy transition -- just transitions -- districts -- coal mining -- datasets; 500
• DOI: 10.1088/2633-1357/abdbbb
• Languages: English
• ISSNs: 2633-1357

Abstract

Abstract: Coal use needs to rapidly decline in the global energy mix in the next few decades in order to meet the Paris climate goals of keeping global warming well below 2-degrees Celsius. In emerging economies such as India (the second largest producer and consumer of coal) this would entail reducing long-term coal dependency. Prior work has focused on a coal transition in India from a techno-economic point of view, yet little attention has been given to the socio-economic dimensions of this transition. This is in part due to lack of availability of datasets required for such analysis. The first step in understanding the socio-economic dimensions of a coal transition in India is to understand the scale of current socio-economic dependency on coal at the sub-national level. We contribute to this literature by creating a novel dataset comprised of all 459 operational coal mines in India, using multiple Right to Information Act applications (India's Freedom of Information Act) and then combining this dataset with coal company wise employment factors to estimate direct job numbers at the district level (a sub-administrative unit). We find that coal is produced in 51 districts in 13 states in India with large variations in employment numbers among these districts. While Korba district in Chhattisgarh state is the highest coal producing district, Dhanbad district in Jharkhand state is home to the highest number of coal mining workers. This is the first attempt at understanding the socio-economic dependency on coal at a district level and future work could focus on quantifying other district level socio-economic indicators such as coal related revenues. The new dataset and the results of this paper will be useful for scholars conducting future work on coal transitions and related topics.