Characterizing the regional XCO2 variability and its association with ENSO over India inferred from GOSAT and OCO-2 satellite observations.

India is primarily concerned with comprehending regional carbon source-sink response in the context of changes in atmospheric CO2 concentrations or anthropogenic emissions. Recent advancements in high-resolution satellite's fine-scale XCO2 measurements provide an opportunity to understand unprecedented details of source-sink activity on a regional scale. In this study, we investigated the long-term variations of XCO2 concentration and growth rates as well as its covarying relationship with ENSO and regional climate parameters (temperature, precipitation, soil moisture, and NDVI) over India from 2010 to 2021 using GOSAT and OCO-2 retrievals. The results show since the launch of OCO-2 in 2014, the number of monthly high-quality XCO2 soundings over India has grown nearly 100-fold compared to GOSAT, launched in 2009. Also, the discrepancy in XCO2 increase of 2.54(2.43) ppm/yr was observed in GOSAT (OCO-2) retrieval during an overlapping measurement period (2015-2021). Additionally, wavelet analysis indicated that the OCO-2 retrieval is able to capture a better frequency of local-scale XCO2 variability compared to GOSAT, owing to its high-resolution cloud-free XCO2 soundings, providing more well-defined regional-scale source-sink features. Furthermore, dominant spatial pattern of XCO2 variability observed over south and southeast of India in both satellites, with XCO2 semi-annual and annual variability more distinctly present in OCO-2 compared to GOSAT. A cross-correlation analysis suggested GOSAT XCO2 growth rate positively correlates with ENSO in different homogeneous monsoon regions of India, with ENSO leading the GOSAT XCO2 growth rate in all homogeneous regions by 3-9 months. The South Peninsular region sensitive to ENSO changes, especially during 2015-2016 ENSO event, where a decrease in CO2 uptake was observed is closely linked with precipitation, soil moisture, and temperature anomalies. However, regional climate parameters show a low correlation with XCO2 growth since CO2 is a long-lived well-mixed gas primarily having an imprint of large-scale transport in column CO2.

Spatial distribution of fossil fuel derived CO2 over India using radiocarbon measurements in crop plants.

Examining the contribution of fossil fuel CO2 to the total CO2 changes in the atmosphere is of primary concern due to its alarming levels of fossil fuel emissions over the globe, specifically developing countries. Atmospheric radiocarbon represents an important observational constraint and utilized to trace fossil fuel derived CO2 (CO2ff) in the atmosphere. For the first time, we have presented a detailed analysis on the spatial distribution of fossil fuel derived CO2 (CO2ff) over India using radiocarbon (Δ14C) measurements during three-year period. Analysis shows that the Δ14C values are varying between 29.33‰ to -34.06‰ across India in the year 2017, where highest value belongs to a location from Gujarat while lowest value belongs to a location from Chhattisgarh. Based on the Δ14C patterns, spatial distributions of CO2ff mole fractions have been determined over India and the calculated values of CO2ff mole fractions are varying between 4.85 ppm to 26.59 ppm across India. It is also noticed that the highest CO2ff mole fraction is observed as 26.59 ppm from a site in Chhattisgarh. CO2ff mole fraction values from four high altitude sites are found to be varied between 4.85 ppm to 14.87 ppm. Effect of sampling different crop plants from the same growing season and different crop plant organs (grains, leaves, stems) on the Δ14C and CO2ff have been studied. Annual and intra seasonal variations in the Δ14C and CO2ff mole fractions have also been analyzed from a rural location (Dholpur, Rajasthan).

Understanding the spatiotemporal variability and trends of surface ozone over India.

With rising anthropogenic activities, surface ozone levels have increased across different parts of the world including India. Previous studies have shown that surface ozone shows distinct characteristics across India but these results are based on isolated locations and any comprehensive and spatiotemporally consistent study about surface ozone variability lacks thus far. Keeping these facts in mind, we utilize ground-based observations and reanalysis datasets to investigate spatiotemporal variations of surface ozone and its linkages with meteorology and precursors over Indian region. A validation exercise shows that the Copernicus Atmosphere Monitoring Service Reanalysis (CAMSRA) reasonably compares against the ground-based observations showing better correlations (> 0.7) over southern regions and relatively lesser (> 0.5) correlations over northern and eastern regions. We have further quantified this agreement in terms of range, mean absolute error (MAE), and root mean square error (RMSE). A time series analysis shows that the CAMSRA captures seasonal variations irrespective of location. Spatial distribution of surface ozone shows higher (lower) concentrations of about 40-60 ppb (15-20 ppb) during pre-monsoon (monsoon) months over northern and western parts and peninsular India. A prominent increase during May is noted over the northern region, especially over the Indo-Gangetic Plains (IGP). These seasonal variations are linked to solar radiation (SR), temperature, low-level circulation, and boundary layer height (BLH). CAMSRA-based surface ozone shows increasing trends across all four regions (north, east, west, and south India) and also India as a whole (0.069 ppb year-1, p = 0.001) with highest trends over the eastern region. Furthermore, principal component analysis (PCA) reveals that the first (second) mode shows a high percentage variance explained, ranging between 30 and 50% (10-20%). The corresponding PC-1 time series exhibits a notable increase in the surface ozone over south and central India, which corroborates the trend obtained through the area averaged time series. The second mode (PC-2) indicates prominent interannual variability over the IGP (southern India) in the pre-monsoon (post-monsoon). During the monsoon season, an interesting dipole pattern is noticeable, which closely resembles the active and break spell patterns of the Indian summer monsoon. Further, we quantify the weightage of precursors and meteorological parameters on surface ozone concentrations. The analysis suggests that PC1 of surface ozone is strongly influenced by CO and NOx (the precursors) while meteorology seems to dominate the PC2 during the pre-monsoon season. Overall, the results indicate that changes in the precursors or meteorological conditions have significant influences on the surface ozone concentrations across India.