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Devising effective national-level climate action plans requires a more detailed understanding of the regional distribution of sources and sinks of greenhouse gases. Due to insufficient observations and modelling capabilities, India's current carbon source–sink estimates are uncertain. This study uses a high-resolution Lagrangian transport model to examine the potential of available CO 2 observations over India for inverse estimation of regional carbon fluxes. We use four different sites in India that vary in the measurement technique, frequency and spatial representation. These observations exhibit substantial seasonal (7.5 to 9.2 ppm) and intra-seasonal (2 to 12 ppm) variability. Our modelling framework, a high-resolution Weather Research and Forecasting Model combined with the Stochastic Time-Inverted Lagrangian Transport model (WRF–STILT), performs better in simulating seasonal (R2=0.50 to 0.96) and diurnal (R2=0.96) variability (for the Mohali station) of observed CO 2 than the current-generation global models (CarboScope, CarbonTracker and ECMWF EGG4). The seasonal CO 2 concentration variability in Mohali, associated with crop residue burning, is largely underestimated by the models. WRF–STILT captures the seasonal biospheric variability over Nainital better than the global models but underestimates the strength of the CO 2 uptake by crops. The choice of emission inventory in the modelling framework alone leads to significant biases in simulations (5 to 10 ppm), endorsing the need for accounting for emission fluxes, especially for non-background sites. Our study highlights the possibility of using the CO 2 observations from these Indian stations for deducing carbon flux information at regional (Nainital) and suburban to urban (Mohali, Shadnagar and Nagpur) scales with the help of a high-resolution model. On accounting for observed variability in CO 2 , the global carbon data assimilation system can benefit from the measurements from the Indian subcontinent. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO 2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO 2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (<15%) uncertainties. However, as the constellation of CO 2 -observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources. [ABSTRACT FROM AUTHOR]

Energy and energy services are the backbone of growth and development in India and is increasingly dependent upon the use of fossil based fuels that lead to greenhouse gases (GHG) emissions and related concerns. Algal biofuels are being evolved as carbon (C) -neutral alternative biofuels. Algae are photosynthetic microorganisms that convert sunlight, water and carbon dioxide (CO) to various sugars and lipids Tri-Acyl-Glycols (TAG) and show promise as an alternative, renewable and green fuel source for India. Compared to land based oilseed crops algae have potentially higher yields (5-12 g/m/d) and can use locations and water resources not suited for agriculture. Within India, there is little additional land area for algal cultivation and therefore needs to be carried out in places that are already used for agriculture, e.g. flooded paddy lands (20 Mha) with village level technologies and on saline wastelands (3 Mha). Cultivating algae under such conditions requires novel multi-tier, multi-cyclic approaches of sharing land area without causing threats to food and water security as well as demand for additional fertilizer resources by adopting multi-tier cropping (algae-paddy) in decentralized open pond systems. A large part of the algal biofuel production is possible in flooded paddy crop land before the crop reaches dense canopies, in wastewaters (40 billion litres per day), in salt affected lands and in nutrient/diversity impoverished shallow coastline fishery. Mitigation will be achieved through avoidance of GHG, C-capture options and substitution of fossil fuels. Estimates made in this paper suggest that nearly half of the current transportation petro-fuels could be produced at such locations without disruption of food security, water security or overall sustainability. This shift can also provide significant mitigation avenues. The major adaptation needs are related to socio-technical acceptance for reuse of various wastelands, wastewaters and waste-derived energy and by-products through policy and attitude change efforts. [ABSTRACT FROM AUTHOR]

India has the largest dairy industry in the world and accounts for a significant share of the global emission of livestock methane ( CH 4 ), a potent greenhouse gas (GHG). While previous works have examined the large-scale livestock CH 4 emissions in India, bottom-up studies are essential to account for the diverse farm conditions and practices across the subcontinent. We developed a Methane Calculator for Indian livestock sector using the Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology for estimating methane emissions from enteric fermentation and manure management. Using this calculator, we undertook a study of emissions from four dairy farms in the tropical coastal district of Thiruvananthapuram, Kerala, in June 2019. Livestock population and milk production data were collected from the four farms, to compute a mean CH 4 emission of 0.7183 kg CO 2 equivalents/kg of fat and protein corrected milk (kg CO 2 e/kg FPCM), with a notable farm-to-farm variability (63.3%). Having implemented the latest available guidelines outlined by the IPCC, our results are a valuable new addition to the existing body of knowledge in the measurement of dairy farm GHG emissions. We present this as a pilot study, demonstrating a simple method to perform bottom-up investigations of dairy GHG emissions and further formulate policy interventions and mitigation strategies at the farm level. [ABSTRACT FROM AUTHOR]

• Establishment-level analysis to put a price on greenhouse gas emission in freight transport sector. • Latent class analysis to divide establishments based on fleet-ownership patterns. • Examines the determinants of freight transport emission disaggregated by fleet segments. • Gross emitters in each fleet ownership segment are modeled for targeted policy interventions. • Implications for designing carbon tax and trading programs in developing economies like India. Concerns over transport energy consumption and greenhouse gas emissions have lately prompted significant attention towards vehicle ownership patterns and the distributional implications of climate mitigation policies. This paper contributes to freight transport literature by examining how establishments can be meaningfully grouped using their fleet ownership pattern (size and composition) and how these segments vary in their freight travel pattern and CO 2 emission levels. The analysis performed using an establishment-based freight survey dataset from Kerala, a coastal state in India, revealed five latent classes of fleet ownership. The determinants of freight transport emissions and the gross emitters in fleet segments are presented subsequently by analyzing how the establishment-level characteristics (employment, business age, industry sector, value density, and relative location) explain the variation in CO 2 emissions. The study findings offer insights for designing effective carbon policy instruments and incentive schemes to regulate the establishment-level freight travel pattern and control transport emissions. [ABSTRACT FROM AUTHOR]

In India, large quantities of organic amendments such as crop residues (550 mt yr-1), municipal solid waste (48 mt yr-1), animal manures (182 mt yr-1) and other sources are produced. Recycling these organic amendments in agriculture has several beneficial effects such as improving plant growth, yield, soil carbon content, and microbial biomass and activity. Nevertheless, organic amendment applications have some disadvantages such as nutrient eutrophication and greenhouse gas (GHG) emission. Agriculture sector emits substantial quantities of GHGs (carbon dioxide-CO2, methane-CH4, and nitrous oxide-N2O). Though quantity wise CH4 and N2O emissions are less than CO2, they have higher global warming potential. Although there have been studies on the role of chemical fertilizer application on GHG emission, there have been very few studies on the effect of organic amendments application on GHG emission in agricultural soils. We reviewed quantification of various organic amendments used in agriculture that include manures, municipal solid waste, green manuring, crop residues and other miscellaneous organic amendments, major processes for GHG emission, and impact of organic amendment application on GHG emission from soil. The article aims to highlight the management practices to mitigate the emission and the future research needs in relation to nitrogen and carbon dynamics in soil for judicious use of organic amendments in agriculture to maintain soil health with minimum impact on GHG emission from agriculture. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Urbanization, industrialization and human population explosion not only increased the global power demand, but also led to global warming, pollution and climate change. This encouraged production of power from renewable sources, and thus, hydropower development has been focused. Today, there is more than 1300 GW of installed hydropower across the world, and most of the hydroelectric projects (HEPs) are multi-purpose which includes irrigation, flood and drought mitigation and tourism. Although credited as cheap, clean and green, recent studies demonstrate that the reservoirs of HEPs produce enormous quantities of greenhouse gases (GHGs), including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). A large number of estimates on the amount of GHGs from HEPs are available from across the globe. India is next only to USA and China in terms of number of large dams, and thousands of new dams are being planned or constructed, especially in the northeastern part. However, none of these projects have been analyzed in terms of production of GHGs, which is an essential prerequisite for developing such projects and to determine whether carbon emission reduction credits can be accorded or not. The present study was conducted to determine greenness of some of the HEPs of Northeast India in terms of emission of GHGs, and eligibility of the projects for carbon emission reduction credits. Further, the emission of different GHGs through various processes from the Tipaimukh HEP (Manipur) was estimated. In view of the findings, we have provided recommendations, which may be helpful in decision-making process. [ABSTRACT FROM AUTHOR]

Cities across the globe are considered as major anthropogenic sources of greenhouse gases (GHG), yet very few efforts has been made to monitor ambient concentration of GHG in cities, especially in a developing country like India. Here, variations in the ambient concentrations of carbon dioxide (CO) and methane (CH) in residential, commercial, and industrial areas of Delhi are determined from fortnightly daytime observations from July, 2008 to March, 2009. Results indicate that the average daytime ambient concentration of CO varied from 495 to 554 ppm in authorized residential areas, 503 to 621 ppm in the slums or jhuggies in the unauthorized residential areas, 489 to 582 ppm in commercial areas, and 512 to 568 ppm in industrial areas with an average of 541 ± 27 ppm. CH concentration varied from 652 to 5,356 ppbv in authorized residential areas, 500 to15,220 ppbv in the unauthorized residential areas, 921 to 11,000 ppbv in the commercial areas, and 250 to 2,550 ppbv in the industrial areas with an average of 3,226 ± 1,090 ppbv. A low mid-afternoon CO concentration was observed at most of the sites, primarily due to strong biospheric photosynthesis coupled with strong vertical mixing. [ABSTRACT FROM AUTHOR]

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Evapotranspiration (ET) is likely to be greatly affected by global warming because of the dependence of ET on surface temperature. The increasing atmospheric concentration of carbon dioxide (CO2) and other greenhouse gases is expected to increase precipitation and evaporation proportionally. However, a few studies have shown a decreasing trend for evaporation over the last 50 years globally. In India, earlier works showed that there was a significant increasing temporal trend in surface temperature and a decreasing trend in grass reference ET (ETo). To study the temporal trend of ETo along with its regionwise spatial variation, 32 years (1971–2002) monthly meteorological data were collected for 133 selected stations evenly distributed over different agro-ecological regions (AERs) of India. ETo was estimated by the globally accepted Food and Agriculture Organization (FAO) Penman Monteith (PM) method (FAO-56 PM). These ETo values were then analyzed by a nonparametric Mann–Kendall (MK) test (with modified effective sample size approach for serially correlated data) and Sen slope to determine the existence and magnitude of any statistically significant trend over the time period considered in this study. The same analysis was also performed on governing meteorological variables to identify the cause of existence of such trend in ETo. A significant decreasing trend was found in ETo all over India during the study period, which was mainly caused by a significant increase in the relative humidity and a consistent significant decrease in the wind speed throughout the country. However, a general increase in rainfall was not found in recent years. [ABSTRACT FROM AUTHOR]