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Wetlands provide numerous ecological and economic services to mankind. The soils of wetlands are one of the largest sinks of carbon (C) among the terrestrial ecosystems and can play an important role in offsetting the emission of C as a greenhouse gas (GHG) to the atmosphere. India is bestowed with enriched wetland ecosystems that support diverse and unique habitats. The potential of the wetlands in terms of C capture and sequestration has not been quantified. Therefore, in the present paper, an assessment of C capture from different sources and its ultimate deposition in soils leading to sequestration has been done in three different types of wetlands, one created sewage-fed and two natural floodplain oxbow lakes, in the West Bengal state of India. Multiple seasonal sampling of water, macrophytes, and soil was done to assess the primary productivity, dissolved C, and deposition of C in soils of the wetlands in comparison to reference upland sites. All these wetlands are productive ecosystems as indicated by the physicochemical parameters of water and soil. The quantity of C accumulated up to 0.3 m depth in the oxbow lakes was to the tune of 144–166 Mg/ha, which was 3.43–4.78 times higher than that in the corresponding reference upland sites. In the sewage-fed wetland, the C accumulation estimated as 50 Mg/ha was 1.27 times higher than its corresponding upland site. So, the wetland ecosystems, particularly the floodplains, are highly efficient in accumulating C in their soils and thus can somewhat negate the GHG emission. [ABSTRACT FROM AUTHOR]

Wetlands provide a great ecological service by accumulating and sequestering carbon in their soils and thus help in mitigating climate change caused due to global warming. However, the capacity and efficiency of different types of wetlands vary considerably depending upon the nature of the wetland, hydrology, biogeochemistry, climatic condition, and many other factors. In the present paper, we have studied the carbon accumulation and sequestration in three different wetlands, one sewage fed, and two floodplain oxbow lakes in the West Bengal state of India. The selected wetlands vary in terms of ecological regimes such as water volume, depth, link channel, agricultural runoffs, primary productivity, macrophyte coverage, and fishery. The carbon accumulation in the wetlands, which varied from 48.53 to 143.17 Mg/ha up to 30-cm depth of soil, was much higher than that in the corresponding upland sites. The difference was much higher in the floodplain wetlands. So the study revealed that wetlands are better carbon sinks than the corresponding reference sites and the carbon sequestration potential varies according to the type of wetlands. A positive correlation was also observed between macrophyte coverage and the amount of C stored in the wetlands. [ABSTRACT FROM AUTHOR]

Carbon fluxes from agroecosystems contribute to the variability of the carbon cycle and atmospheric [CO 2 ]. This study is a follow-up to Gahlot et al. (2020), which used the Integrated Science Assessment Model (ISAM) to examine spring wheat production and its drivers. In this study, we look at the carbon fluxes and their drivers. ISAM was calibrated and validated against the crop phenology at the IARI wheat experimental site in Gahlot et al. (2020). We extended the validation of the model on a regional scale by comparing modeled leaf area index (LAI) and yield against site-scale observations and regional datasets. Later, ISAM-simulated carbon fluxes were validated against an experimental spring wheat site at IARI for the growing season of 2013–2014. Additionally, we compared with the published carbon flux data and found that ISAM captures the seasonality well. Following that, regional-scale runs were performed. The results revealed that fluxes vary significantly across regions, primarily owing to differences in planting dates. During the study period, all fluxes showed statistically significant increasing trends (p<0.1). Gross primary production (GPP), net primary production (NPP), autotrophic respiration (Ra), and heterotrophic respiration (Rh) increased at 1.272, 0.945, 0.579, 0.328, and 0.366 TgC yr -2 , respectively. Numerical experiments were conducted to investigate how natural forcings such as changing temperature and [CO 2 ] levels as well as agricultural management practices such as nitrogen fertilization and water availability could contribute to the rising trends. The experiments revealed that increasing [CO 2 ], nitrogen fertilization, and irrigation water contributed to increased carbon fluxes, with nitrogen fertilization having the most significant effect. [ABSTRACT FROM AUTHOR]

Purpose: The present study is a novel attempt to measure the impact of population growth, natural resource depletion, non-renewable energy consumption, growth of national income, remittances inflow and industrial output on carbon dioxide emissions in India during the period of 1980–2018. Design/methodology/approach: Autoregressive distributive lag (ARDL) is used to achieve the objective. The application of FMOLS (fully modified ordinary least squares), DOLS (dynamic ordinary least squares) and CCR (canonical cointegrating regression) techniques illustrate statistical robustness. Findings: The long-run ARDL results confirm that increase in population, national income and energy consumption have a positive and significant impact on pollution levels in India. In contradiction to this, long run results further reveal that the increase in natural resource depletion, industrial output and remittances inflow have insignificant and negative impact on pollution levels in India. Further, the empirical findings did not find any evidence for the applicability of the environmental Kuznets curve (EKC) in India during the study period. Research limitations/implications: The study is confined to only a few important determinants of CO2 emissions in India. However, there is a large chunk of studies that have incorporated other determinants of CO2 emissions. Specifying a few determinants of CO2 emissions in India is itself a lacuna in the present study. Moreover, taking the time period from 1980 to 2018 is also one of the limitations of the study. Practical implications: Plenty of research has been devoted to the causal relationship between the environment and its various determinants. However, not much attention has been paid to investigating the association between population growth, natural resource depletion, energy consumption, GDP per capita, remittances inflow, industry and carbon dioxide emissions in India. Since, CO2 emissions are one of the widely accepted and applied emissions in EKC applications, which the present study intends to test. Moreover, the study employs advanced econometric techniques including ARDL framework, FMOLS, DOLS and CRR methodologies to achieve robust results. Such an investigation will potentially allow policymakers to frame efficient environmental and fiscal policies to achieve the desired results. Originality/value: The continuous increase of CO2 emissions in India has compelled policy makers to prioritize this issue as soon as possible and formulate national environmental policy for reducing the share of carbon dioxides emissions in climate change. The study could constitute the focus of future research. [ABSTRACT FROM AUTHOR]

Land uses are pivotal in global carbon cycles. The native forest lands possess a greater potential to sequester higher carbon, which can directly address soil quality and climate change problems. Unfortunately, the rapid conversion of forests to other land use over the past few decades has significantly declined the concentration of carbon in the soils. Therefore, in order to estimate the impact of land-use change (LUC) on soil carbon status, this present study was attempted under major ecosystems (Forest (FOR), cropland (CRP), tea plantation (TEA)) of Conoor. Results from findings revealed that total organic carbon (TOC) concentration and carbon pools were significantly (p<0.05) higher in FOR than in CRP and TEA. TOC (0-45 cm) recorded in FOR, CRP and TEA was 32.88, 11.87 and 18.84 g kg-1 and it decreased along the depth increment. Carbon stock (t ha-1) in FOR, CRP and TEA (0-45cm) was 68.10, 26.04, 42.42. Microbial biomass carbon (MBC) was higher in FOR (283.08 mg kg-1) followed by TEA (94.64 mg kg-1) and CRP (76.22 mg kg-1). The microbial biomass nitrogen (MBN) followed; FOR > TEA > CRP. These results clearly indicate that the LUC has inflicted a greater impact on soil carbon status and its extent was quantified using the land degradation index (LDI). The LDI (0-45 cm) recorded in CRP (-38.65) and TEA (-61.75) signals the need for immediate implementation of carbon management strategies in the CRP and TEA ecosystem to keep the soils of Conoor alive and prevent land degradation. [ABSTRACT FROM AUTHOR]

The southwestern shelf water of India (eastern Arabian Sea) experiences high seasonality. This area is one of the understudied regions in terms of phytoplankton response to the projected ocean acidification, particularly, during the summer monsoon when phytoplankton abundance is high. Here we present the results of a short-term simulated ocean acidification experiment (ambient CO2 424 µatm; high CO2, 843, 1138 µatm) on the natural phytoplankton assemblages conducted onboard (R. V. Sindhu Sadhana) during the summer monsoon (Aug 2017). Among the dissolved inorganic nutrients, dissolved silicate (DSi) and nitrate + nitrite levels were quite low (< 2 µM). Phytoplankton biomass did not show any net enhancement after the incubation in any treatment. Both marker pigment analysis and microscopy revealed the dominance of diatoms in the phytoplankton community, and a significant restructuring was noticed over the experimental period. Divinyl chlorophylla (DVChla) containing picocyanobacteria and 19'-hexanoyloxyfucoxanthin (19′HF) containing prymnesiophytes did not show any noticeable change in response to CO2 enrichment. A CO2-induced positive growth response was noticed in some diatoms (Guinardia flaccida, Cylindrotheca closterium, and Pseudo-nitzschia sp.) and dinoflagellates (Protoperidinium sp. and Peridinium sp.) indicating their efficiency to quickly acclimatize at elevated CO2 levels. This is important to note that the positive growth response of toxigenic pennate diatoms like Pseudo-nitzschia as well as a few dinoflagellates at elevated CO2 levels can be expected in the future-ocean scenario. The proliferation of such non-palatable phytoplankton may impact grazing, the food chain, and carbon cycling in this region. [ABSTRACT FROM AUTHOR]

Simple Summary: We present a systematic investigation of the distribution of microbial communities in arid and semi-arid regions of Thar Desert Rajasthan, India. Their responses in multiple environmental stresses, including surface soil, surface water and underground water were evaluated. We further assess the biotechnological potential of native microorganisms and discover functional species with results providing a detailed understanding of the abundance of microbial communities in these regions, associated with various stress-related biogeochemical and biotechnological processes. We hope our work will facilitate the development of effective future strategies for the use of extremophiles in complex environments. The arid and semi-arid regions of Rajasthan are one of the most extreme biomes of India, possessing diverse microbial communities that exhibit immense biotechnological potential for industries. Herein, we sampled study sites from arid and semi-arid regions of Thar Desert, Rajasthan, India and subjected them to chemical, physical and metagenomics analysis. The microbial diversity was studied using V3–V4 amplicon sequencing of 16S rRNA gene by Illumina MiSeq. Our metagenomic analyses revealed that the sampled sites consist mainly of Proteobacteria (19–31%) followed by unclassified bacteria (5–21%), Actinobacteria (3–25%), Planctomycetes (5–13%), Chloroflexi (2–14%), Bacteroidetes (3–12%), Firmicutes (3–7%), Acidobacteria (1–4%) and Patescibacteria (1–4%). We have found Proteobacteria in abundance which is associated with a range of activities involved in biogeochemical cycles such as carbon, nitrogen, and sulphur. Our study is perhaps the first of its kind to explore soil bacteria from arid and semi-arid regions of Rajasthan, India. We believe that the new microbial candidates found can be further explored for various industrial and biotechnological applications. [ABSTRACT FROM AUTHOR]

Accurate estimates of spatial above ground biomass (AGB) in tropical forests are important in understanding the global carbon cycle. Microwave and optical remote sensing datasets have been used extensively for AGB estimation, but their uses are restricted due to saturation in high biomass region. To overcome saturation issues of single sensor based models, the current paper uses a non-parametric Random Forest based approach to spatially estimate biomass over Indian forests using field inventory data in combination with optical (MODIS) and Microwave (L-band ALOS-PALSAR) images along with other bio-climatic parameters (e.g., rainfall, temperature) which significantly influence the biomass accumulation in an ecosystem. Plot level biomass estimates for 6678 sample plots (0.1 ha size), inventoried as part of robustly designed National Forest Inventory (NFI), are computed using volumetric equations, wood density and biomass expansion factors. Spatial above ground biomass estimates were generated using random forest model over two scenarios. Firstly, a single nation-wide model using all the available plot data and secondly, physiographic zone (14 zones over India) wise models with plot data over respective zones. AGB stored in Indian forest is estimated as 7952.3 million tonnes (Carbon equivalent: 3737.58 TgC) with a root mean square error (RMSE) of 31.2% using national level model. Physiographic zone level models estimated the country's biomass as 7597.45 million tonnes (Carbon equivalent: 3570.8 TgC). The above ground biomass estimates from our study indicates that the estimation error in physiographic zone model varies from 25.24% to 54.15% depending upon the sample size and biomass range. We observed that L-band microwave saturated in 140–160 Mg ha−1 range and currently available microwave wavelengths alone is not sufficient to predict entire range of biomass over Indian forests. Inclusion of multisource data using random forest regression model increase the saturation range to 350 Mg ha−1 which is a significant improvement as 94.7% of Indian forests are covered in this range. Model estimation error reduces to 25.6% in AGB range up to 350 Mg ha−1. • L-band ALOS PALSAR backscatter saturates in biomass range140–160 Mg ha−1. • Inclusion of multi source data improved the saturation point to ~350 Mg ha−1. • 94.7% of Indian forest cover is covered in AGB range below 350 Mg ha−1. • Biomass stored in Indian forest estimated as 7952.3 Mt. (carbon equivalent: 3737.58 TgC). [ABSTRACT FROM AUTHOR]

The terrestrial biosphere plays a pivotal role in removing carbon from the atmosphere. The removal processes are primarily affected by the presence of extreme temperature in the atmosphere. Little information is available on carbon removal response by the terrestrial biosphere during extreme temperature events over the Indian region. India has witnessed frequent and intense heatwaves in the recent past, and future projections about the frequency of heatwave occurrence suggest a further increase in the changing climate scenario. This study used surface CO2 flux observations and satellite retrieved columnar and mid-tropospheric CO2 concentrations to understand atmospheric CO2 variability and its transport patterns with anomalously high-temperature events such as heatwave conditions over India. Intensification of temperature up to 32 °C has increased the atmosphere-biosphere CO2 fluxes (carbon sink). But further intensification in temperature (> 32–33 °C), like those observed during heatwaves, tends to drive the ecosystem to act as a CO2 source into the atmosphere due to reduced ability to absorb atmospheric CO2. Such excess CO2 fluxes may lead to change in the atmospheric CO2 concentration via atmospheric circulation or the vertical transport of the air masses from the near-surface to the upper levels in the atmosphere. The satellite observed CO2 concentration is elevated by 2–3 ppm during the heatwave conditions over India. The impact of extreme temperature on the biospheric sink capability in the carbon cycle, leading to an increase in the atmospheric CO2 concentration, is one of the significant outcomes of this study. [ABSTRACT FROM AUTHOR]

Mapping and quantifying above ground carbon (AGC) Stocks reflect significant dynamics in the terrestrial carbon cycle and cascade climate change. Estimation of such key driver was performed for the dominant species (Bamboo, Eucalyptus and Teak) over Coimbatore and Nilgiris Biosphere (2006 − 2018 quadruple interval) of Tamilnadu, India with the developed global stepwise multiple linear regression (SMLR) and local geographically weighted regression (GWR) models using multi-dynamic variables. Evapotranspiration (ET) developed using Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) model for the region was analysed with the best-fitted AGC estimation model to understand AGC—ET synergistic pertinence dynamics. The study compared and validated the estimation by the models and indicated that AGC estimation using SMLR exhibiting a high degree of accuracy ( R 2 = 0.84 , RMSE = 5.67 , MAE = 4.61 Mg ha − 1 ) with nominal negative bias in the estimation ranging from 0.13 − 146.34 Mg ha − 1 with amplification of 1.87 ± 1.2 % year − 4. GWR prediction indicted positive bias with comparatively least mean accuracy ( R 2 = 0.59 , RMSE = 13.72 , MAE = 12.85 Mg ha − 1 ). The ET—AGC reciprocity for the dominant species resulted that, bamboo with lower AGC ∼ 25 Mg ha − 1 correlated with higher ET ∼ 3 mm day − 1 tailed by teak with higher AGC ∼ 45 Mg ha − 1 and ET ∼ 2.5 mm day − 1 and eucalyptus with relatively higher AGC and lower ET ∼ 50 Mg ha − 1 and ∼ 3 mm day − 1 , respectively. The analysis resulted in minimal biasness in AGC mapping using SMLR, and both the model signifies that the region can potentially be considered a long-term carbon sink. [ABSTRACT FROM AUTHOR]

In this study, CO2 exchange over sugarcane and wheat growing season was quantified by continuous measurement of CO2 fluxes using eddy covariance (EC) system from January 2014 to June 2015. We also elaborated on the response of CO2 fluxes to environmental variables. The results show that the ecosystem has seasonal and diurnal dynamics of CO2 with a distinctive U-shaped curve in both growing seasons with maximal CO2 absorption reaching up to −8.94 g C m−2 day−1 and −6.08 g C m−2 day−1 over sugarcane and wheat crop, respectively. The ecosystem as a whole acted as a carbon sink during the active growing season while it exhibits a carbon source prior to sowing and post-harvesting of crops. The cumulative net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco) were −923.04, 3316.65, and 2433.18 g C m−2 over the sugarcane growing season while the values were −192.30, 621.47, and 488.34 g C m−2 over the wheat growing season. The sesbania (green manure) appeared to be a carbon source once it is incorporated into soil. The response of day-time NEE to photosynthetically active radiation (PAR) under two vapor pressure deficit (VPD) sections (0–20 h Pa and 20–40 h Pa) seems more effective over sugarcane (R2 = 0.41–0.61) as compared to the wheat crop (R2 = 0.25–0.40). A decrease in net CO2 uptake was observed under higher VPD conditions. Similarly, night-time NEE was exponentially related to temperature at different soil moisture conditions and showed higher response to optimum soil moisture conditions for sugarcane (R2 = 0.87, 0.33 ≤ SWC < 0.42 m3 m−3) and wheat (R2 = 0.75, 0.31 ≤ SWC < 0.37 m3 m−3) crop seasons. The response of daily averaged NEE to environmental variables through path analysis indicates that PAR was the dominant predictor with the direct path coefficient of −0.65 and −0.74 over sugarcane and wheat growing season, respectively. Satellite-based GPP products from Moderate Resolution Imaging Spectroradiometer (GPPMOD) and Vegetation Photosynthetic model (GPPVPM) were also compared with the GPP obtained from EC (GPPEC) technique. The seasonal dynamics of GPPEC and GPPVPM agreed well with each other. This study covers the broad aspects ranging from micro-meteorology to remote sensing over C4-C3 cropping system [ABSTRACT FROM AUTHOR]

Scenarios avoiding global warming greater than 1.5 or 2 ∘ C, as stipulated in the Paris Agreement, may require the combined mitigation of anthropogenic greenhouse gas emissions alongside enhancing negative emissions through approaches such as afforestation–reforestation (AR) and biomass energy with carbon capture and storage (BECCS). We use the JULES land surface model coupled to an inverted form of the IMOGEN climate emulator to investigate mitigation scenarios that achieve the 1.5 or 2 ∘ C warming targets of the Paris Agreement. Specifically, within this IMOGEN-JULES framework, we focus on and characterise the global and regional effectiveness of land-based (BECCS and/or AR) and anthropogenic methane (CH4) emission mitigation, separately and in combination, on the anthropogenic fossil fuel carbon dioxide (CO2) emission budgets (AFFEBs) to 2100. We use consistent data and socio-economic assumptions from the IMAGE integrated assessment model for the second Shared Socioeconomic Pathway (SSP2). The analysis includes the effects of the methane and carbon–climate feedbacks from wetlands and permafrost thaw, which we have shown previously to be significant constraints on the AFFEBs. Globally, mitigation of anthropogenic CH4 emissions has large impacts on the anthropogenic fossil fuel emission budgets, potentially offsetting (i.e. allowing extra) carbon dioxide emissions of 188–212 Gt C. This is because of (a) the reduction in the direct and indirect radiative forcing of methane in response to the lower emissions and hence atmospheric concentration of methane and (b) carbon-cycle changes leading to increased uptake by the land and ocean by CO2 -based fertilisation. Methane mitigation is beneficial everywhere, particularly for the major CH4 -emitting regions of India, the USA, and China. Land-based mitigation has the potential to offset 51–100 Gt C globally, the large range reflecting assumptions and uncertainties associated with BECCS. The ranges for CH4 reduction and BECCS implementation are valid for both the 1.5 and 2 ∘ C warming targets. That is the mitigation potential of the CH4 and of the land-based scenarios is similar for regardless of which of the final stabilised warming levels society aims for. Further, both the effectiveness and the preferred land management strategy (i.e. AR or BECCS) have strong regional dependencies. Additional analysis shows extensive BECCS could adversely affect water security for several regions. Although the primary requirement remains mitigation of fossil fuel emissions, our results highlight the potential for the mitigation of CH4 emissions to make the Paris climate targets more achievable. [ABSTRACT FROM AUTHOR]

The current study presents the oxidative potential (OP) along with a wide range of chemical speciation of particulate matter with an aerodynamic diameter less than 10 μm (PM 10) at five sites representing different environments in Ahmedabad, a big city in western India. On an average, PM 10 concentrations were 116 ± 36, 228 ± 43, 133 ± 29, 101 ± 21, and 70 ± 20 μg m−3; volume-normalized OP (OP V) were 2.51 ± 0.71, 5.62 ± 0.68, 2.69 ± 0.76, 2.14 ± 0.41, and 1.55 ± 0.51 nmol DTT min−1 m−3; and mass-normalized OP (OP M) were 22 ± 3, 25 ± 5, 21 ± 6, 21 ± 2, and 22 ± 3 pmol DTT min−1 μg−1 over Bapunagar (backward residential area), Narol (industrial), Paldi (bus transport hub), Income Tax (huge running traffic) and Science City (posh residential area), respectively. Overall, OP V showed a significant linear correlation with PM 10 , whereas OP M showed near uniformity with increasing PM 10. Although the OP M values were similar, the site-to-site variability in PM 10 concentration reflects the corresponding health risks associated with PM 10 exposure for the people living in these areas. Further, a noticeable temporal variation in OP M at Narol and Paldi suggests that species with diverse OP M contributed to PM 10 on different days. A strong linear relationship between the ratio of OP V to the mass concentration of organic carbon (OP OC) and the ratio of m/z 43 signal to total water-soluble organic aerosols (WSOA) signals (f43) suggests that the fossil-fuel combustion derived WSOA have higher OP. Furthermore, the relationships of OP with water-soluble trace metals and brown carbon are also investigated and discussed in this paper. Nitrogenous organic compounds particularly emitted from the traffic-related sources in Paldi and Income Tax have higher OP OC than those emitted from other sources over Bapunagar, Narol, and Science City. Image 1 • Oxidative potential (OP) cannot be determined by PM 10 mass alone. • Volume-normalized OP shows a significant spatial variability over Ahmedabad. • Nitrogenous organics from the traffic-related sources have higher OP. [ABSTRACT FROM AUTHOR]

The Northern Indian Ocean hosts two Oxygen Minimum Zones (OMZ), one in the Arabian Sea and the other in the Bay of Bengal. 16S rRNA gene amplicon sequencing was used to understand the total bacterial diversity in, the surface sediment off Goa within the OMZ of the Arabian Sea, and off Paradeep within the OMZ of the Bay of Bengal. Functional profiling was carried out to pinpoint the occurrence of specific bacterial operational taxonomic units (OTUs) which have been previously described to harbour certain genes/enzymes relevant to biogeochemical cycling of carbon, nitrogen, and sulfur compounds. The dominant phyla identified included Firmicutes (33.08%) and Proteobacteria (32.59%) from the Arabian Sea, and Proteobacteria (52.65%) and Planctomycetes (9.36%) from the Bay of Bengal. Only 30% of OTUs were shared between the sites which make up three-fourth of the Bay of Bengal OMZ bacterial community, but only one-fourth of the Arabian Sea OMZ sediment bacterial community. Statistical analysis indicated the bacterial diversity from sediments of the Bay of Bengal OMZ is ∼48% higher than the Arabian Sea OMZ. The community analysis combined with a predictive functional profiling of 16S rRNA amplicons revealed some major differences regarding sediment nitrogen fixation and carbon recycling, and identified a distinct bacterial community structure within the two shallow OMZ sites lying in the east coast and west coast of the peninsular India. [ABSTRACT FROM AUTHOR]

Background: Mangroves are important tropical carbon sinks, and their role in mitigating climate change is well documented across the globe. However, the ecosystem carbon stocks in the mangroves of India have not been studied comprehensively. Data from this region is very limited for providing sufficient insights and authentic evaluation of carbon stocks on a regional scale. In this study, we evaluated the ecosystem carbon stock and its spatial variation in mangroves of Kerala, southwest coast of India. Results: The mean biomass stored in mangrove vegetation of Kerala is 117.11 ± 1.02 t/ha (ABG= 80.22 ± 0.80, BGB =36.89 ± 0.23 t/ha). Six mangrove species were found distributed in the study area. Among the different species, Avicennia marina had the highest biomass (162.18 t/ha) and least biomass was observed in Sonneratia alba (0.61 t/ha). The mean ecosystem carbon stock of mangrove systems in Kerala was estimated to be 139.82 t/ha, equivalent to 513.13 t CO2 e/ha with the vegetation and soil storing 58.56 t C/ha and 81.26 t C/ha respectively. Conclusion: The present study reveals that Kerala mangroves store sizable volume of carbon and therefore need to be preserved and managed sustainably, to retain along with the increase in carbon storage. This features the need of broadening mangrove cover as well as restoring deteriorated land in the past 50 years. Although mangrove forests in this region are protected by the Kerala Forest Department, they have been frequently facing illegal encroachment, prawn cultivation, and coastal erosion. [ABSTRACT FROM AUTHOR]

Mangroves are halophytic vegetation comprising the tropics. Bhitarkanika Wildlife Sanctuary, being a local hotspot of mangrove, acts as carbon sink for mitigating increased CO2 level in the atmosphere. The study estimated total biomass and total carbon in five selected stations of this Wildlife Sanctuary in reference to relevant ambient parameters of water (temperature, pH, and salinity) and soil (temperature, pH, electrical conductivity, bulk density, organic carbon, organic matter, and texture) seasonally. The average values for total biomass and total carbon measured in this study are 866.67 ± 166.10 t ha−1 and 444.68 ± 83.70 t ha−1, respectively. The average soil organic carbon recorded was 3.73 ± 2.10 t ha−1 and average litter carbon was 0.59 ± 0.20 t ha−1, respectively. Among the components, above-ground biomass constitutes 55–70% of total biomass and total carbon. Significant positive relationship between biomass (above-ground biomass, below-ground biomass, litter biomass, total biomass) and carbon (above-ground carbon, below-ground carbon, litter carbon, soil organic carbon, and total carbon) was obtained with respect to selected physico-chemical variables which proved the significant effect of change in biomass and carbon to changing parameters of the ambient media in the study area. The analysis of variance computed between season and station has also proved the above phenomenon. The study revealed the mangrove carbon storage potential of 21 mangrove species, which is at par with the biomass of South-east Asia and South west Pacific countries. Hence, mangrove conservation programs like REDD+ can be adopted in this wildlife sanctuary being the 2nd largest mangrove patch of India after Sundarbans. [ABSTRACT FROM AUTHOR]

We examined methane (CH4) variability over different regions of India and the surrounding oceans derived from thermal infrared (TIR) band observations (TIR CH4) by the Thermal and Near-infrared Sensor for carbon Observation—Fourier Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observation SATellite (GOSAT) for the period 2009–2014. This study attempts to understand the sensitivity of the vertical profile retrievals at different layers of the troposphere and lower stratosphere, on the basis of the averaging kernel (AK) functions and a priori assumptions, as applied to the simulated concentrations by the MIROC4.0-based Atmospheric Chemistry-Transport Model (MIROC4-ACTM). We stress that this is of particular importance when the satellite-derived products are analyzed using different ACTMs other than those used as retrieved a priori. A comparison of modeled and retrieved CH4 vertical profiles shows that the GOSAT/TANSO-FTS TIR instrument has sufficient sensitivity to provide critical information about the transport of CH4 from the top of the boundary layer to the upper troposphere. The mean mismatch between TIR CH4 and model is within 50 ppb, except for the altitude range above 150 hPa, where the sensitivity of TIR CH4 observations becomes very low. Convolved model profiles with TIR CH4 AK reduces the mismatch to less than the retrieval uncertainty. Distinct seasonal variations of CH4 have been observed near the atmospheric boundary layer (800 hPa), free troposphere (500 hPa), and upper troposphere (300 hPa) over the northern and southern regions of India, corresponding to the southwest monsoon (July–September) and post-monsoon (October–December) seasons. Analysis of the transport and emission contributions to CH4 suggests that the CH4 seasonal cycle over the Indian subcontinent is governed by both the heterogeneous distributions of surface emissions and the influence of the global monsoon divergent wind circulations. The major contrast between monsoon, and pre- and post-monsoon profiles of CH4 over Indian regions are noticed near the boundary layer heights, which is mainly caused by seasonal change in local emission strength with a peak during summer due to increased emissions from the paddy fields and wetlands. A strong difference between seasons in the middle and upper troposphere is caused by convective transport of the emission signals from the surface and redistribution in the monsoon anticyclone of upper troposphere. TIR CH4 observations provide additional information on CH4 in the region compared to what is known from in situ data and total-column (XCH4) measurements. Based on two emission sensitivity simulations compared to TIR CH4 observations, we suggest that the emissions of CH4 from the India region were 51.2 ± 4.6 Tg year−1 during the period 2009–2014. Our results suggest that improvements in the a priori profile shape in the upper troposphere and lower stratosphere (UT/LS) region would help better interpretation of CH4 cycling in the earth's environment. [ABSTRACT FROM AUTHOR]

Land cover is a crucial component in assessment of biodiversity and ecosystem services. In arid regions, land cover is mostly composed of aeolian structures which exhibit fragile environmental scenario. The major challenge in this highly dynamic landscape was conversion of desertic land to intensive land use such as agricultural farmlands. To overcome this challenge Indira Gandhi Canal (IGC) and its branches were extended over this district. The main interest of this research was to investigate net primary productivity (NPP) changes using multi-temporal satellite imagery and meteorological datasets within the timeframe of 30 years from 1982 to 2012 over this region. This study was taken up to assess the impact of canal in and around IGC command area in Jaisalmer District to understand the consequence on desertic environment. Analysis of three decades terrestrial NPP over IGC command area in Jaisalmer District, India, shows significant increase in NPP. The satellite data-based analysis of NPP as well as validation with the optical data in the study region revealed that this increasing trend in NPP is basically associated to increase in canal networks. The water supply from the canal gradually led to expansion of irrigation in the agricultural fields leading to change in dynamics of the area. This systematic and long-term NPP analysis will be useful to strengthen our understanding for the role of regional land cover types and impact of their change in the national and global carbon cycle for understanding land degradation and desertification scenario in the study area. [ABSTRACT FROM AUTHOR]

A multi-model-based assessment is made to assess the trends and variability in the land carbon uptake in India during the period 1901–2010. Data from nine models, used in a recent land surface model inter-comparison project called TRENDY, are used for this purpose. Our analysis is focused on the trends and variability in the net primary productivity (NPP), net ecosystem productivity (NEP) and net ecosystem exchange (NEE). The multi-model mean NPP shows a positive trend of 2.03% per decade during this period. The NEP, which is the difference between NPP and heterotrophic respiration, has a mean value of - 0.138 ± 0.086 Pg C yr - 1 over this region. According to our analysis of TRENDY multi-models, the inter-annual variation in NPP and NEP is strongly driven by precipitation, but remote drivers such as El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) do not have a strong influence. The water use efficiency (WUE) shows an increase of about 25% over the 110-yr period. Our multi-model-based estimate of the cumulative NEE is 0.613 ± 0.1 Pg C during 1901–2010, indicating that the Indian terrestrial ecosystem was neither a strong source nor a significant sink during this period. However, we caution that our conclusion is based on a limited set of offline land models, and the results presented here have large uncertainties due to model resolution and parameterisation of various land surface processes, the inadequate validation procedures and the use of limited number of models and land use change data sets. Further investigations using more observational data, rigorous validation using extensive observational data sets and a set of comprehensive coupled models that include several feedbacks between land, atmosphere, ocean and the cryosphere are needed to assess the robustness of our results. [ABSTRACT FROM AUTHOR]