Atmospheric observations show accurate reporting and little growth in India's methane emissions

Abstract

Changes in tropical wetland, ruminant or rice emissions are thought to have played a role in recent variations in atmospheric methane (CH₄) concentrations. India has the world's largest ruminant population and produces ~ 20% of the world's rice. Therefore, changes in these sources could have significant implications for global warming. Here, we infer India's CH₄ emissions for the period 2010-2015 using a combination of satellite, surface and aircraft data. We apply a high-resolution atmospheric transport model to simulate data from these platforms to infer fluxes at sub-national scales and to quantify changes in rice emissions. We find that average emissions over this period are 22.0 (19.6-24.3) Tg yr^-1, which is consistent with the emissions reported by India to the United Framework Convention on Climate Change. Annual emissions have not changed significantly (0.2 ± 0.7 Tg yr^-1) between 2010 and 2015, suggesting that major CH₄ sources did not change appreciably. These findings are in contrast to another major economy, China, which has shown significant growth in recent years due to increasing fossil fuel emissions. However, the trend in a global emission inventory has been overestimated for China due to incorrect rate of fossil fuel growth. Here, we find growth has been overestimated in India but likely due to ruminant and waste sectors.India's methane emissions have been quantified using atmospheric measurements to provide an independent comparison with reported emissions. Here Ganesan et al. find that derived methane emissions are consistent with India's reports and no significant trend has been observed between 2010-2015.

Fig. 1

Comparison of India’s top-down CH₄ emissions and seasonal cycle with bottom-up inventories. a Indian CH₄ emissions (as Tg yr⁻¹) for the prior inventories (orange, solid line) and for the top-down estimated here (dark blue line). The prior was comprised by EDGAR₂₀₁₀ (excluding rice), Yan et al. rice and GFED v3.1 biomass burning. For comparison, the dashed orange line corresponds to EDGAR₂₀₁₀ (including rice) and GFED. The turquoise line and shading indicates a 12-month running mean of the top-down emissions (uncertainties assuming full correlation between months). The black line and grey shading correspond to 2010 emissions submitted to the UNFCCC (BUR) and uncertainties (based on percentage uncertainties for the year 2000, the last year for which uncertainties were published: 50% enteric fermentation, 8% rice, 125% fossil fuel, 150% waste). b Average prior (orange) and top-down (blue) seasonal cycle. In all panels, shading corresponds to 5th–95th percentile uncertainties. The monsoon season is highlighted in pink bars

Fig. 2

Differences in emissions between seasons. a Difference between the average summer (June–Sept) or b average winter (Jan–Feb) peak emission periods, and the average of spring/autumn minimum emission periods (March–May, October–December) in g m⁻² s⁻¹. Scaling factors to the prior flux map for each month were estimated for ~40 spatial basis functions within this domain; the prior map was scaled up or down by this factor for each basis function

Fig. 3

Prior emissions in g m⁻² s⁻¹ by source sector. a Yan et al. average rice emissions for June–September. b Yan et al., average rice emissions for March–May and October–December. c EDGAR v4.2FT2010 anthropogenic emissions excluding rice and ruminants (diffuse sources)