Updated greenhouse gas inventory estimates for Indian underground coal mining based on the 2019 IPCC refinements

Singh, Ajay Kumar; Singh, Udayan; Panigrahi, Durga Charan; Singh, Jayant K.

doi:10.1016/j.isci.2022.104946

Cited by 14 publications

(5 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If you look at the author list of the Global Methane Budget, 3 it is impossible to have methane budget research without interdisciplinarity. The budget involves experts on atmospheric methane observations from stations and satellites, anthropogenic methane emissions from the socioeconomic angle (e.g., two accepted papers in this special issue 5 , 6 ), and satellite/airborne observations, natural emissions from land surface modeling groups and observations for wetlands, termites and permafrost, 1 , 7 atmospheric chemistry for sinks, soil microbial uptake, and atmospheric inversions. 8 Modeling methane-climate feedback in an earth system model is also a large interdisciplinary community making efforts to predict future methane budget.…”

Section: First Impressionsmentioning

confidence: 99%

Challenges and opportunities in the global methane cycle

Peng

2023

iScience

View full text Add to dashboard Cite

Section: First Impressionsmentioning

confidence: 99%

Challenges and opportunities in the global methane cycle

Peng

2023

iScience

View full text Add to dashboard Cite

“…В работе индийских исследователей представлены обновленные оценки запасов парниковых газов для подземной добычи угля в Индии на основе уточнений Межправительственной группы экспертов по изменению климата (МГЭИК). Исследование устраняет пробелы в отчетности по парниковым газам за счет количественной оценки выбросов на угольных шахтах [11].…”

Section: обзор литературыunclassified

Assessment of Sources of Greenhouse Gas Emissions From Coal Mining Operations

Nagaitsev

2023

Bulletin of the SibSIU

View full text Add to dashboard Cite

Аннотация. Приведен один из механизмов государственного экономического регулирования работы организаций-природопользователей. Для предприятий, осуществляющих хозяйственную деятельность, предусмотрена плата за негативное воздействие на выбросы в окружающую среду. Деятельность угледобывающих предприятий характеризуется значительными выбросами метана (газа), являющегося загрязняющим веществом, за которое предусмотрена плата. Произведен расчет платы за выбросы метана, проведен анализ полученных значений. Сделаны выводы, что предприятия, использующие технологии по снижению выбросов метана, сокращают операционные затраты и впоследствии способны управлять рисками, связанными с увеличением платы за негативное воздействие на окружающую среду. Отмечено, что помимо экономической нагрузки на предприятия, выбросы метана оказывают негативное возденйствие (парниковый эффект), приводящее к изменениям климата. Приведены мировые и российские научные исследования по направлению актуализации учета и снижения выбросов парниковых газов в горнодобывающей отрасли. Актуальность направления углеродного регулирования и снижения парниковых выбросов подтверждается развитием законодательной базы в Российской Федерации, обязательной отчетностью о выбросах парниковых газов для предприятий и реализующимся пилотным проектом системы торговли квотами на выбросы парниковых газов на Сахалине. Показаны основные источники выбросов парниковых газов на угольных шахтах: горные выработки и трубопроводы, предназначенные для отвода метана из шахты; факельные установки для сжигания метана; выбросы от сжигания топлива на котельных для обогрева горных выработок и административно-бытовых помещений; выбросы от сжигания топлива транспортными средствами на предприятии. Сделаны выводы, что выбросы метана составляют наибольшую часть выбросов парниковых газов на угольных шахтах. Управление этими выбросами позволит предприятиям соответствовать курсу страны на декарбонизацию экономики и реализацию механизмов углеродного регулирования (система торговли квотами) по всей стране.

show abstract

“…The Tier 1 approach requires that countries choose from a global average range of emission factors and use country-specific activity data to calculate total emissions, resulting in high levels of uncertainty and large representation error (a factor of 2 or more). The Tier 2 approach uses country-or basinspecific emission factors that represent the average values over the coal mines considered, resulting in emissions with moderate amounts of error (at least 50 %-75 %), including representation errors associated with variance in coal mine size, operations, and CH 4 geology (William Irving, 2000;Hiller et al, 2014;Maasakkers et al, 2016;Peng et al, 2016;Sheng et al, 2017;Hoesly et al, 2018;Mcduffie et al, 2020;Scarpelli et al, 2020Scarpelli et al, , 2022Deng et al, 2022;Sadavarte et al, 2022;Singh et al, 2022). Presently, most countries produce coal mine CH 4 inventories following one of these two approaches.…”

Section: Introductionmentioning

confidence: 99%

Individual coal mine methane emissions constrained by eddy covariance measurements: low bias and missing sources

Qin,

Hu,

et al. 2024

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. China's Shanxi Province accounts for 12 % of global coal output and therefore is responsible for a very large fraction of the total global methane (CH4) emissions, as well as being a large source of uncertainty due to the lack of in situ and field measurements. This work introduces the first comprehensive attempt to compute the coal mine methane (CMM) emissions throughout Shanxi, using a mixture of bottom-up and top-down approaches. First, public and private data from 636 individual coal mines in Shanxi Province were analyzed following the IPCC Tier 2 approach, using three to five sets of observed emission factors and rank information based on methods issued by the National Coal Mine Safety Administration and the National Energy Administration, to compile a range of bottom-up CMM on a mine-by-mine basis. An eddy covariance tower is set up near the output flue of a well-characterized high-rank coal mine in Changzhi and used to produce an average observed CH4 flux over two 2-month-long periods (Winter 2021 and Autumn 2022). The observed half-hourly CH4 flux variability is found to be roughly stable over the entire observed time and is subsequently used to produce a set of scaling factors (ratio correction) to update the preliminary bottom-up coal mine methane emissions to account for both bias and high-frequency temporal variability. The resulting emissions dataset has been compared against commonly used global CMM datasets including EDGAR and GFEI v2, and there are three unique scientific conclusions. First, their total CH4 emissions over Shanxi lie between this work's 50th percentile and 70th percentile range, meaning they are slightly high. Second, both datasets have a very large amount of emissions which occur where there are no coal mines and no CH4-emitting industry, indicating that there are significant spatial disparities, with the overlapped portion of CMM emissions where mines exist consistently close to the 30th percentile of this work's emissions, meaning they underestimate CMM in general on a mine-by-mine basis. Third, some of the mines have average emissions values which are more than the 90th percentile of the computed mine-by-mine emissions, while many are far below the 10th percentile, showing that there is a significant issue with the sampling not capturing the observed temporal variability. It is hoped that this mine-by-mine and high-frequency approximation of CMM emissions can both improve top-down observation campaigns and provide quantitative support and identification of mitigation opportunities.

show abstract

Updated greenhouse gas inventory estimates for Indian underground coal mining based on the 2019 IPCC refinements

Cited by 14 publications

References 29 publications

Challenges and opportunities in the global methane cycle

Challenges and opportunities in the global methane cycle

Assessment of Sources of Greenhouse Gas Emissions From Coal Mining Operations

Individual coal mine methane emissions constrained by eddy covariance measurements: low bias and missing sources

Contact Info

Product

Resources

About