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.

No abstract

[1] Large-scale carbon sources and sinks can be estimated by combining atmospheric CO 2 concentration data with atmospheric transport inverse modeling. This approach has been limited by sparse spatiotemporal tropospheric sampling. CO 2 estimates from space using observations on recently launched satellites (Atmospheric Infrared Sounder (AIRS)), or platforms to be launched (Infrared Atmospheric Sounding Interferometer (IASI), Orbiting Carbon Observatory (OCO)) have the potential to fill some of these gaps. Here we assess the realism of initial AIRS-based mid-to-upper troposphere CO 2 estimates from European Centre for Medium-Range Weather Forecasts by comparing them with simulations of two transport models (TM3 and Laboratoire Meteorologie Dynamique Zoom (LMDZ)) forced with one data-based set of surface fluxes. The simulations agree closer with one another than with the retrievals. Nevertheless, there is good overall agreement between all estimates of seasonal cycles and north-south gradients within the latitudinal band extending from 30°S to 30°N, but not outside this region. At smaller spatial scales, there is a contrast in the satellite-based retrievals above continents versus above oceans that is absent in the model predictions. Hovmoeller diagrams indicate that in the models, high Northern Hemisphere winter CO 2 concentrations propagate toward the tropical upper troposphere via Northern Hemisphere high latitudes, while in retrievals, elevated winter CO 2 appears instantaneously throughout the Northern Hemisphere. This raises questions about lower-to-upper troposphere transport pathways. Prerequisites for use of retrievals to provide an improved constraint on surface fluxes are therefore further improvements in retrievals and better understanding/validation of lower-to-upper troposphere transport and its modeling. This calls for more independent upper troposphere transport tracer data like SF 6 and CO 2 .

Abstract. We present shipborne measurements of surface ozone (O 3 ), carbon monoxide (CO), and methane (CH 4 ) over the Bay of Bengal (BoB), the first time such measurements have been performed during the summer monsoon season, as a part of the Continental Tropical Convergence Zone (CTCZ) experiment during 2009. O 3 , CO, and CH 4 mixing ratios exhibited significant spatial and temporal variability in the ranges of 8-54 nmol mol −1 , 50-200 nmol mol −1 , and 1.57-2.15 µmol mol −1 , with means of 29.7 ± 6.8 nmol mol −1 , 96 ± 25 nmol mol −1 , and 1.83 ± 0.14 µmol mol −1 , respectively. The average mixing ratios of trace gases over BoB in air masses from central/northern India (O 3 : 30 ± 7 nmol mol −1 ; CO: 95 ± 25 nmol mol −1 ; CH 4 : 1.86 ± 0.12 µmol mol −1 ) were not statistically different from those in air masses from southern India (O 3 : 27 ± 5 nmol mol −1 ; CO: 101 ± 27 nmol mol −1 ; CH 4 : 1.72 ± 0.14 µmol mol −1 ). Spatial variability is observed to be most significant for CH 4 with higher mixing ratios in the air masses from central/northern India, where higher CH 4 levels are seen in the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) data. O 3 mixing ratios over the BoB showed large reductions (by ∼ 20 nmol mol −1 ) during four rainfall events. Temporal changes in the meteorological parameters, in conjunction with O 3 vertical profile, indicate that these low-O 3 events are associated with downdrafts of free-tropospheric O 3 -poor air masses. While the observed variations of O 3 and CO are successfully reproduced using the Weather Research and Forecasting model with Chemistry (WRF-Chem), this model overestimates mean concentrations by about 6 and 16 % for O 3 and CO, respectively, generally overestimating O 3 mixing ratios during the rainfall events. An analysis of modelled O 3 along air mass trajectories show mean en route O 3 production rate of about 4.6 nmol mol −1 day −1 in the outflow towards the BoB. Analysis of the various tendencies from model simulations during an event on 10 August 2009, reproduced by the model, shows horizontal advection rapidly transporting O 3 -rich air masses from near the coast across the BoB. This study fills a gap in the availability of trace gas measurements over the BoB and, when combined with data from previous campaigns, reveals large seasonal amplitude (∼ 39 and ∼ 207 nmol mol −1 for O 3 and CO, respectively) over the northern BoB.