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. 2022 Aug 5;194(9):647.
doi: 10.1007/s10661-022-10323-1.

Regional estimation of methane emissions over the peninsular India using atmospheric inverse modelling

Anjumol Raju  1   2 , S Sijikumar  3 , Vinu Valsala  4 , Yogesh K Tiwari  4 , Santanu Halder  4 , I A Girach  1   5 , Chaithanya D Jain  6 , M Venkat Ratnam  6
Affiliations

Regional estimation of methane emissions over the peninsular India using atmospheric inverse modelling

Anjumol Raju et al. Environ Monit Assess. .

Abstract

Accurate renditions of country-scale methane (CH4) emissions are critical in understanding the regional CH4 budget and essential for adapting national climate mitigation policies to curtail the atmospheric build-up of this greenhouse gas with high warming potential. India housing 30% of the Asian population is currently appraised as a region of CH4 source based on the inventories. To date, there have not been many reported efforts to estimate the regional CH4 emissions using direct measurements of boundary layer CH4 concentrations at multiple locations over India. Here, 2 years (2017-2018) of in situ CH4 observations from three distantly placed stations over the peninsular India is combined with state-of-the-art inversion using a Lagrangian particle dispersion model for the estimation of CH4 emission. This study updates CH4 emission over the peninsular India (land area south of 21.5°N) as ~ 10.63 Terra gram (Tg) CH4 year-1, which is 0.13 Tg CH4 year-1 higher than the existing inventory-based emission. On seasonal scale, the changes from the existing CH4 emission inventories are 0.12, 0.05, 0.055 and 0.28 Tg CH4 year-1 during winter, pre-monsoon, monsoon and post-monsoon seasons respectively. Spatial distributions of seasonal variability of posterior emissions suggest an enhancement over the eastern region of peninsular India compared to the western part. The study with observations from three stations over the peninsular India provides an update on the inventory-based estimation of CH4 emissions and urges the importance of more observations over the Indian region for the accurate estimation of fluxes.

Keywords: Bayesian inversion; CH4; Greenhouse gas fluxes; Lagrangian dispersion model.

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