Understanding carbon sequestration trends using model and satellite data under different ecosystems in India.

This study discusses carbon sequestration variability in different ecosystems of India. Four different biosphere regions, each over 0.5° × 0.5° area, have been selected considering the geospatial and climatic variability of these regions expanding from Central India (CI), the Northeast region (NER), the Western Ghats (WG), and the Western Himalayan region (WHNI). The climatic conditions of these four regions are different so are the biosphere constituents of these regions. We expect the Gross Primary Productivity (GPP) to enhance during the all India summer monsoon rainfall season but in varied magnitudes suggesting a role of climatic parameters and flora in these regions. The GPP from FLUXCOM for the duration of 2001 to 2019 (19 years) and satellite-derived vegetation indices like the Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Leaf Area Index (LAI) are used in this study to understand the response of regional vegetation to this variability. EVI seems to be better related to GPP in comparison to NDVI in the preliminary analysis. Further analysis suggests LAI correlates better to GPP than EVI and NDVI in different seasons in these four regions. Also, meteorological parameters like surface temperature, rainfall, soil water, and other derived parameters like Vapor Pressure Deficit (VPD) are studied. It is also observed that the year-to-year variability in the climatic conditions could also have a role to play in the observed features. It is proven that the climate around the world is experiencing changes. Vegetation is one of the potent markers to monitor the impact of climate change. These long-term data and trends were studied to understand if there is any significant impact of the changing climatic conditions on the vegetation in these regions. Our study shows that there is an increasing (positive) trend in GPP at these locations though at different rates. WG and WHNI have shown a significant high rate of increase (6.44 and 5.36 gCm-2 y-1, respectively) in GPP over the last two decades.

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

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.

Methane sources from waste and natural gas sectors detected in Pune, India, by concentration and isotopic analysis.

Methane (CH4) is a potent greenhouse gas and also plays a significant role in tropospheric chemistry. High-frequency (sub-hourly) measurements of CH4 and carbon isotopic ratio (δ13CH4) have been conducted at Pune (18.53°N, 73.80°E), an urban environment in India, during 2018-2020. High CH4 concentrations were observed, with a mean of 2100 ± 196 ppb (1844-2749 ppb), relative to marine background concentrations. The δ13CH4 varied between -45.11 and -50.03 ‰ for the entire study period with an average of -47.41 ± 0.94 ‰. The diurnal variability of CH4 typically showed maximum values in the morning (08:00-09:00 local time) and minimum in the afternoon (15:00 local time). The deepest diurnal amplitude of ~500 ppb was observed during winter (December-February), which was reduced to less than half, ~200 ppb, during the summer (March-May). CH4 concentration at Pune showed a strong seasonality (470 ppb), much higher than that at Mauna Loa, Hawaii. On the other hand, δ13CH4 records did not show distinct seasonality at Pune. The δ13CH4 values revealed that the significant sources of CH4 in Pune were from the waste sector (enhanced during the monsoon season; signature of depleted δ13CH4), followed by the natural gas sector with a signature of enriched δ13CH4. Our analysis of Covid-19 lockdown (April to May 2020) effect on the CH4 variability showed no signal in the CH4 variability; however, the isotopic analysis indicated a transient shift in the CH4 source to the waste sector (early summer of 2020).

Benefits of satellite XCO2 and newly proposed atmospheric CO2 observation network over India in constraining regional CO2 fluxes.

Top-down modeling estimates are among the most reliable information available on the CO2 fluxes of the earth system. The inadequate coverage of CO2 observing stations over the tropical regions adds a limitation to this estimate, especially when the satellite XCO2 is strictly screened for cloud contamination, aerosol, dust, etc. In this study, we investigated the potential benefit of a global ground-based observing station network, 17 newly proposed stations over India, and global satellite XCO2 in reducing the uncertainty of terrestrial biospheric fluxes of Tropical Asia-Eurasia in TransCom cyclo-stationary inversion. The data from selected 80 global ground-based CO2 observation stations, together with two additional stations from India (i.e., Cape Rama and Sinhagad) and satellite XCO2, helps to reduce the temperate Eurasian terrestrial flux uncertainty by 23.8%, 26.4%, and 36.2%, respectively. This further improved to 54.7% by adding the newly proposed stations over India into the inversion. By separating the Indian sub-continent from temperate Eurasia (as inspired by the heterogeneity in the terrestrial ecosystems, prevailing meteorological conditions, and the orography of this vast region), the inversion evinces the capacity of existing CO2 observations to reduce the Indian terrestrial flux uncertainty by 20.5%. The largest benefit (70% reduction of annual mean uncertainty) for estimating Indian terrestrial fluxes could be achieved by combining these global observations with data from the newly proposed stations over India. The existing two stations from India suggest Temperate Eurasia as a mild source of CO2 (0.33 ± 0.57 Pg C yr-1), albeit with prominent anthropogenic influences visible in these two stations during the dry seasons. This implies that the proposed new stations should be cautiously placed to avoid such effects. The study also finds that the newly proposed stations over India also have an impact in constraining nearby oceanic CO2 fluxes.

Diurnal and seasonal variability of CO2 and CH4 concentration in a semi-urban environment of western India.

Amongst all the anthropogenically produced greenhouse gases (GHGs), carbon dioxide (CO2) and methane (CH4) are the most important, owing to their maximum contribution to the net radiative forcing of the Earth. India is undergoing rapid economic development, where fossil fuel emissions have increased drastically in the last three decades. Apart from the anthropogenic activities, the GHGs dynamics in India are governed by the biospheric process and monsoon circulation; however, these aspects are not well addressed yet. Towards this, we have measured CO2 and CH4 concentration at Sinhagad, located on the Western Ghats in peninsular India. The average concentrations of CO2 and CH4 observed during the study period are 406.05 ± 6.36 and 1.97 ± 0.07 ppm (µ ± 1σ), respectively. They also exhibit significant seasonal variabilities at this site. CH4 (CO2) attains its minimum concentration during monsoon (post-monsoon), whereas CO2 (CH4) reaches its maximum concentration during pre-monsoon (post-monsoon). CO2 poses significant diurnal variations in monsoon and post-monsoon. However, CH4 exhibits a dual-peak like pattern in pre-monsoon. The study suggests that the GHG dynamics in the western region of India are significantly influenced by monsoon circulation, especially during the summer season.

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

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.

Variability in AIRS CO2 during active and break phases of Indian summer monsoon.

Due to human activities, the atmospheric concentration of Carbon Dioxide (CO2) has been rising extensively since the Industrial Revolution. Indian summer monsoon (ISM) has a dominant westerly component from ocean to land with a strong tendency to ascend and hence may have role in CO2 distribution in lower and middle troposphere over Indian sub-continent. A substantial component of ISM variability arises from the fluctuations on the intra-seasonal scale between active and break phases which correspond to strong and weak monsoon circulation. In view of the above, an attempt is made in this study to examine the AIRS/AQUA satellite retrieved CO2 distribution in response to atmospheric circulation with focus on active and break phase. Correlation analysis indicates the increase in AIRS CO2 linked with strong monsoon circulation. Study also reveals that anomalous circulation pattern during active and break phase show resemblance with high and low values of AIRS CO2. Homogeneous monsoon regions of India show substantial increase in CO2 levels during active phase. Hilly regions of India show strong contrast in CO2 and vertical velocity during active and break phases.

Influence of monsoons on atmospheric CO2 spatial variability and ground-based monitoring over India.

This study examines the role of Asian monsoons on transport and spatial variability of atmospheric CO2 over the Indian subcontinent, using transport modeling tools and available surface observations from two atmospheric CO2 monitoring sites Sinhagad (SNG) and Cape Rama (CRI) in the western part of peninsular India. The regional source contributions to these sites arise from the horizontal flow in conduits within the planetary boundary layer. Greater CO2 variability, greater than 15 ppm, is observed during winter, while it is reduced nearly by half during summer. The SNG air sampling site is more susceptible to narrow regional terrestrial fluxes transported from the Indo-Gangetic Plains in January, and to wider upwind marine source regions from the Arabian Sea in July. The Western Ghats mountains appear to play a role in the seasonal variability at SNG by trapping polluted air masses associated with weak monsoonal winds. A Lagrangian back-trajectory analysis further suggests that the horizontal extent of regional sensitivity increases from north to south over the Indian subcontinent in January (Boreal winter).

AIRS retrieved CO2 and its association with climatic parameters over India during 2004-2011.

Atmospheric Infrared Sounder (AIRS) retrieved mid-tropospheric Carbon Dioxide (CO2) have been used to study the variability and its association with the climatic parameters over India during 2004 to 2011. The study also aims in understanding transport of CO2 from surface to mid-troposphere over India. The annual cycle of mid-tropospheric CO2 shows gradual increase in concentration from January till the month of May at the rate ~0.6 ppm/month. It decreases continuously in summer monsoon (JJAS) at the same rate during which strong westerlies persists over the region. A slight increase is seen during winter monsoon (DJF). Being a greenhouse gas, annual cycle of CO2 show good resemblance with annual cycle of surface air temperature with correlation coefficient (CC) of +0.8. Annual cycle of vertical velocity indicate inverse pattern compared to annual cycle of CO2. High values of mid-tropospheric CO2 correspond to upward wind, while low values of mid-tropospheric CO2 correspond to downward wind. In addition to vertical motion, zonal winds are also contributing towards the transport of CO2 from surface to mid-troposphere. Vegetation as it absorbs CO2 at surface level, show inverse annual cycle to that of annual cycle of CO2 (CC-0.64). Seasonal variation of rainfall-CO2 shows similarities with seasonal variation of NDVI-CO2. However, the use of long period data sets for CO2 at the surface and at the mid-troposphere will be an advantage to confirm these results.

On understanding the land-ocean CO2 contrast over the Bay of Bengal: a case study during 2009 summer monsoon.

Ship-based observations of atmospheric carbon dioxide (CO2) concentration over the Bay of Bengal (BoB) between 17 July 2009 and 17 Aug 2009 offered an excellent opportunity to evaluate the land-ocean contrast of surface CO2 and facilitated its comparison with model simulated CO2 concentrations. Elevated values of CO2 with large variability near the coastal region and relatively low values with correspondingly lower variability over the open ocean suggest that this observed CO2 variability over the ocean essentially captures the differences in terrestrial and oceanic CO2 fluxes. Although the region under investigation is well known for its atmospheric intraseasonal oscillations of Indian summer monsoon during July and August, the limited duration of observations performed from a moving ship in a research cruise, is not able to capture any high-frequency variability of atmospheric CO2 concentrations. But band-passed sea surface temperature and wind anomalies do indicate strong intraseasonal variability over the study region during the observational period. The synoptic data, albeit quite short in duration, thus offer a clear benchmark for abrupt variability of CO2 concentration between land and ocean.