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Magnetotelluric (MT) and audio-magnetotelluric (AMT) studies are sensitive to the geothermal fluids filling the faults and/or fracture zones of the geothermal system. In India, MT/AMT studies have been carried out in NW Himalayas, central, eastern, and western India. In other areas, detailed MT/AMT studies need to be expedited. This review paper presents the art of geothermal exploration in India by using MT/AMT techniques and identifies potential zones that can be exploited for power generation and direct application. Reservoir characteristics, carbon emissions reduction methods, and levelised cost factor are also discussed. [ABSTRACT FROM AUTHOR]

Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries' technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector's potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector. [ABSTRACT FROM AUTHOR]

In spite of the surge in solar and wind energy in the recent years, the IC engines, particularly the diesel engines may be expected to stay on for the next 30 years at least. In this context, it is imperative to find alternative fuel sources for petro diesel, at least in part. Inedible oil based biodiesels are one good option for India. There is a slight decrease in performance of a diesel engine when run with biodiesel blends. It is also feared by some that pollution from exhaust gas by using biodiesel blends may be higher. This paper summarizes the results of experiments carried out on biodiesel blends with diesel to determine the amounts and particle sizes of carbon particulate matter emissions in engine exhaust. Blends of two esterified oils, viz., Honge (Pongamia Pinnata) and Jatropha, with petro diesel were used to operate a single-cylinder, four-stroke diesel engine. Blend ratios used were 5%, 10%, 15%, and 20%. The carbon particles in exhaust were collected on an INDICA filter paper for 5 minutes. The carbon content was ascertained by the standard procedure, and the size of particles was found by microscopic examination. Further ANOVA of the data was carried out separately for the Honge and Jatropha blends. The results from the experiments are clear and interesting. Both Honge and Jatropha blends increase the amount of carbon particulates in engine exhaust when compared with diesel. Carbon particulates increase with increase in load on the engine. Increase of blend ratio generally increases the carbon in exhaust in case of Jatropha blends. The behaviour with Honge blends is different. While blend H5 has highest carbon in exhaust at low loads, at high loads, H10 has the maximum carbon in exhaust. Blending with Honge or Jatropha biodiesel increases the carbon particle size in exhaust. While the size of carbon particles with diesel is < 20 µm, it is > 20 µm with all blends, increasing with load or blend ratio. In all cases, lower loads result in finer carbon particles in exhaust. The study helps in concluding that both Honge and Jatropha blends could be used in diesel engines, Honge being superior. Though the PM level in the exhaust will be higher with blending, the particle sizes will be much larger and hence causing less health hazard. Further, idling (no load), or low loads should be avoided since these result in smaller carbon particles. [ABSTRACT FROM AUTHOR]

This paper reviews and assesses India's energy policy in the context of its commitment to achieve the target of net-zero carbon emissions by 2070. It emphasizes the central role of green electrification, particularly through the expansion of solar power capacity. It discusses policies outside the energy sector that need to be part of a strategy of achieving this target, including the use of information technology, infrastructure development, and transportation. Furthermore, it examines possible policy options for accelerating the target date to 2050, especially with the use of carbon capture to manage the transition from the current heavy use of coal. The paper also discusses the possible financial and growth implications of various strategy options, arguing that feasible external financing commitments can allow India to achieve net-zero goals without sacrificing economic growth. [ABSTRACT FROM AUTHOR]

The paper examines the impact of macroeconomic variables on CO2 emissions, very few research studies are available to estimate the asymmetric impact and causality. Because of the significance of asymmetries, this paper examines the asymmetric impact of economic growth, crude oil use, and FDI inflows on CO2 emissions in the India wherein COP (Crude oil price) is comprised as the extra variable. The implicate aggressive growth of selected variables over the period 1990–2020 is also assessed. This study uses the methodology ARDL and NARDL model to determine the macroeconomics variable's effects on CO2 emission over the period 1990-2020. Additionally, also applied the EKC (Environmental Kuznets Curve) hypothesis with an application of ARDL and NARDL model. With help of the ARDL and NARDL model, the study shows the results that a rise in economic growth would reduce CO2 (carbon dioxide) emissions while a decrease in economic growth would raise CO2 emissions which indicates an inverted U-shaped Curved relationship between economic growth and CO2 emissions. The positive and negative shockwaves in COP (crude oil prices) have a satisfactory and substantial impact on CO2 emissions as well. Besides, the crude oil consumption with positive shockwave confirmations has a positive and substantial impact on CO2 emission. In addition, the results of FDI inflows support the pollution heaven hypothesis. In light of these outcomes, this paper also recommended policy implications and future research, the policy implications are where the descending flow of FDI allows limited space to India in FDI selection; however, the existence of emission merging and implementation of carbon pricing may facilitate India in achieving its environmental targets. [ABSTRACT FROM AUTHOR]

In today's world, a situational awareness of sustainability is becoming increasingly important. Leaving a better world for future generations is becoming the main interest of many studies. It also puts pressure on managers to change production methods in most industries. Reducing carbon emissions in industry today is crucial to saving our planet. Theoretical research and practical industry requirements diverge, even though numerous researchers have tackled various strategies to handle carbon emission problems. Therefore, this work considers the carbon emission problem of the furniture manufacturing industry in Hosur, Tamilnadu, India. The case study company has a manufacturing system that resembles a hybrid flow shop (HFS) environment. As the HFS scheduling problems are NP-hard in nature, exact solution techniques could not be used to solve the problems. Hence, a sequential hybrid optimization algorithm (SHOA) has been developed in this paper to minimize the carbon footprint. In the SHOA, the pigeon-inspired optimization algorithm (PIOA) is hybridized sequentially with the firefly algorithm (FA). A computational experimental design is proposed to analyze the efficiency of the introduced strategy, and the solutions indicate that the developed approach could reduce the carbon footprint by up to 9.82%. The results motivate us to implement the proposed algorithm in the manufacturing industry to reduce the carbon footprint. [ABSTRACT FROM AUTHOR]

To become the fastest-growing large economy in the world, India has set a target growth rate of 9%, reaching an economy of $5 trillion by 2024-25. It is an immense challenge to meet the growth target and keep the CO2 emissions under control. The present paper aims to discover the determinants for explaining CO2 emissions in India by conducting a complete decomposition analysis, where the residuals are fully distributed to the determinants for the country from 1990-2018. The analysis reveals that the biggest contributor to the rise in CO2 emissions in India is the expansion of the economy (scale effect). The intensity of CO2 and the change in the composition of the economy, which nearly move in tandem, also contribute to the rise in CO2 emissions, although more slowly. A declining energy intensity of the Indian economy is responsible for a considerable reduction in CO2 emissions. As a typical result for an upcoming economy, this paper did not find evidence for an environmental Kuznets curve. This implies that continued economic growth will lead to increased CO2 emissions. [ABSTRACT FROM AUTHOR]

Purpose: The study attempts to capture the comprehensive accounting framework of the inverted U-shaped Environmental Kuznets Curve (EKC) hypothesis relevant for an emerging economy based on an emission-growth decoupling approach. The paper intends to re-examine and analyze the roles of influential production- and consumption-based drivers for the prominently observable increasing pattern of the energy-related carbon dioxide (CO2) emissions from the Indian Territory. Design/methodology/approach: The study adopted an annual time series structural decomposition analysis (SDA) based on a single-country input-output framework for the period 2000–2014 to identify and elaborate the contribution of the responsible drivers to the production-based carbon emission of India. The study further proceeded to analyze a decoupling index to explore the features of economic growth and carbon emissions comovement over time. Findings: The results from the empirical exercise reflect a pattern of consistently developing relative decoupling character for most of the production-based drivers. The paper produces insightful results on the pattern of energy-related CO2 emissions from the perspective of the EKC hypothesis and highlights the importance of consumption-based drivers as substantial contributors to the economy-wide CO2 emissions to be controlled for effective decoupling of the aggregate production-based CO2 from the volume of aggregate production to enhance the opportunities for sustainable economic development. Originality/value: The study uniquely correlates the declining trend of the emission intensity of India's gross domestic product (GDP) and the inclining trend of the overall emissions due to ever-increasing gross output in the form of a comprehensive accounting relationship. [ABSTRACT FROM AUTHOR]

The cement industry's carbon emissions present a major global challenge, particularly the increase in atmospheric carbon dioxide (CO2) levels. The concrete industry is responsible for a significant portion of these emissions, accounting for approximately 5-9% of the total emissions. This underscores the urgent need for effective strategies to curb carbon emissions. In this work, we propose to use artificial intelligence (AI) to predict future emission trends by performing a detailed analysis of cement industry's CO2 emissions data. The AI predictive model shows a significant increase in overall carbon emissions from the cement sector which is attributed to population growth and increased demand for housing and infrastructure. To address this issue, we propose a framework that emphasizes on implementing carbon sequestration through reuse of construction and demolition (C&D) waste by using recycled aggregates. The paper proposes a framework addressing carbon sequestration through use of C&D waste. The framework is applied specifically to Maharashtra State in India to calculate the potential reduction in carbon emissions by construction industry resulting from recycled aggregates. The study reveals a projected saving of 24% in carbon emissions by adopting the suggested framework. The process and outcomes of the study aim to address the concerns of climate change through reduced carbon emissions in the construction industry promoting recycle and reuse of construction waste. [ABSTRACT FROM AUTHOR]

In this paper, the BASIC (Brazil, South Africa, India, and China) countries, which play an increasingly significant role in combating climate change, are selected as the research objects. First, we investigate the driving factors of the evolution of carbon emissions in the BASIC group from 2000 to 2016. Second, we use the Monte Carlo simulation to analyze the potential evolution trend of carbon emissions in the benchmark scenario, optimization scenario, and enhanced scenario in the BASIC group from 2017 to 2030 to judge whether the countries can achieve their own autonomous contribution goals. Third, we evaluate whether the BASIC INDC can provide practical support for making the global temperature control goals described in the Paris Agreement. The results show that first, the contribution rate of the energy consumption structure and population size to the carbon emissions of the BASIC are low, and the contributions of R&D efficiency, R&D intensity, and investment intensity to the carbon emission change in the BASIC group are more prominent. Second, under the benchmark scenario, Brazil, South Africa, India, and China from the difference between the complete INDC targets respectively is 265.50 Mt, 207.86 Mt, 1034.70 Mt, and 4660.82 Mt. Under the optimization scenario, China could meet the INDC goals. The gap between Brazil, South Africa, and India is 60.06 Mt, 9.50 Mt, and 413.74 Mt, respectively. Under the enhanced scenario, China and South Africa could meet the INDC target, while Brazil and India are 15.69 Mt and 228.28 Mt away from the INDC target, respectively. Third, although the INDC goals of Brazil and India can achieve the carbon reduction allocated under the 2 °C targets, the INDC targets submitted by the BASIC are not enough to reach the carbon reduction allocated under the global 1.5 °C destination; Brazil, South Africa, India, and China's gap is 64.14 Mt, 246.15 Mt, 236.84 Mt, 3399.64 Mt, respectively. Fourth, Brazil, South Africa, and China should increase its R&D on energy-saving and emission reduction technologies, and India should develop reasonable population policies and green economic development policies. [ABSTRACT FROM AUTHOR]

Global warming caused by CO2 emissions will directly harm the health and quality of life of people. Accurate prediction of CO2 emissions is highly important for policy-makers to formulate scientific and reasonable low-carbon environmental protection policies. To accurately predict the CO2 emissions of the world's major economies, this paper proposes a new fractional grey Bernoulli model (FGBM(1,1, t α )). First, this paper introduces the modeling mechanism and characteristics of the FGBM(1,1, t α ) model. The new model can be transformed into other grey prediction models through parameter adjustment, so the new model exhibits high adaptability. Second, this paper employs four carbon emission datasets to establish a grey prediction model, calculates model parameters with three optimization algorithms, adopts two evaluation criteria to evaluate the accuracy of the model results, and selects the optimization algorithm and model results that yield the highest model accuracy, which verifies that the FGBM(1,1, t α ) model is more feasible and effective than the other six grey models. Finally, this paper applies the FGBM(1,1, t α ) model to predict the CO2 emissions of the USA, India, Asia Pacific, and the world over the next 5 years. The forecast results reveal that from 2020 to 2024, the CO2 emissions of India, the Asia Pacific region, and the world will gradually rise, but that in USA will slowly decline over the next 5 years. [ABSTRACT FROM AUTHOR]

In this paper, we examine whether geopolitical risk influences environmental degradation, while controlling for non-renewable energy consumption, economic growth and trade openness, using a quarterly dataset from 1985Q1 to 2019Q4. The choice of India as a case study is based on a number of reasons. India is a developing country, which produces approximately 3.2% of global GDP. Also, India produces almost 17.7% of the world population. The country also emits about 6.8% of global carbon emissions, and according to the 2020 report of the consulting firm Eurasia, India is ranked fifth in terms of geopolitical risk. This study adds to the existing literature by using the quantile-on-quantile (QQR) regression to examine the effect of geopolitical risk on environmental degradation, as well as highlighting the implications of geopolitical risk on environmental sustainability. Based on empirical estimation, we find that geopolitical risk increases and decreases carbon emissions in India. That is, geopolitical risk increases environmental degradation at middle quantiles and decreases environmental degradation at lower and higher quantiles. In addition, we find that non-renewable energy consumption, economic growth and trade openness impede environmental quality in India. Thus, we are of the opinion that policymakers, when making policy decisions on environmental quality, should factor in geopolitical risk in two areas, mitigation and channel of escalation, among other policy suggestions. [ABSTRACT FROM AUTHOR]

This paper presents the assessment of solar resources, investigation of performance, and estimation of normalized performance indices of a 1 kWp Solar PV system in India's climatology of an isolated hilly area. The monthly and yearly mean normalized performance indices are estimated. The annual mean values of the daylight hours, cell temperature, and ambient temperature are 12.7 h/d, 10.89°C, and 1.25°C, respectively. The yearly mean values and corresponding ranges of monthly mean values of capacity factor, performance ratio, array yield, reference yield, final yield, array capture loss and system loss are obtained as 23.60%, 59.82%, 2.83 h/d, 4.63 h/d, 2.69 h/d, 1.8 h/d, 0.14 h/d and (17.56–29.07)%, (47.93–75.55)%, (2.24–3.42) h/d, (2.85–6.1) h/d, (2.13–3.25) h/d, (0.60–2.99) h/d and (0.11–0.17) h/d, respectively. The Levelized Cost of energy is reduced to 85% and 68.22% by using the proposed solar PV/ battery system compared to DG and DG/Battery systems. A saving of 14.8 kl of diesel and the corresponding reduction of emissions of carbon monoxide (244.22 kilograms), unburned hydrocarbons (10.66 kg), particulates (1.48 kg), and nitrogen Oxides (229.42 kg) have also been achieved per year. These findings effectively provide optimal power solution strategies for policymakers in the concerned area. [ABSTRACT FROM AUTHOR]

World has been shifting towards cleaner and safer sources of energy. Reducing the carbon footprint is the need of the hour. Industries all over the globe are researching on reducing the pollution causing emissions and trying to improve in terms of using sustainable sources of energy and saving the environment. This paper would analyse the low carbon energy assessors (LCEA) in the construction industry. A detailed study has been conducted using primary and secondary research to determine the carbon emissions at different stages of construction. The study would help us in identifying the main phases and activities and components, contributing the majority of the carbon footprints. The need of this age is to work on this area and minimise the pollution and harm to the environment. The construction sites chosen are diverse and consist of all types of building in the southern part of India. The highest carbon emission component in building construction is the cement as a large amount of CO2 emission takes place during the manufacturing process of the cement. The minimum carbon emission that takes place due to the components from the building are labour, sand, MS steel and stainless steel. The study would give a high level idea about the impact of low carbon energy assessors (LCEA) in the construction industry. [ABSTRACT FROM AUTHOR]

Slow tourism is looked upon as a means of achieving green & sustainable tourism and is seen as an alternative to mass tourism. It is becoming popular amongst tourists, destination managers and tourism service providers. Slow tourism is an integrative concept that promotes sustainability in all aspects of a travelling journey. Advertisers and tourism service providers are marketing different features of slow tourism. Local Government bodies and state tourism development corporations are also promoting slow tourism through various social media and promotional campaign. The present research tries to explore the perception and preferences of Indian travellers regarding the concept of slow tourism. Methodology: This an exploratory research intending to study the perception and preferences of Indian travellers towards slow tourism. Semi structured interviews of tourists, destination managers and tourism service providers from India will be used to collect the data. Thematic apperception test will be used to evaluate the respondents' patterns of thoughts, emotional responses & attitudes towards slow tourism. Principal of saturation will be used to determine the sample size. Findings/Outcomes/Results: As an outcome of this paper the researchers propose to develop a model framework through which slow tourism can be embedded in the existing tourism practices of tourists, destination managers and tourism service providers. Implication: Through this research the researchers intend to create awareness about slow tourism and help to reduce the increasing environmental threats of fast tourism. It is also proposed to understand the perceived challenges in adapting slow tourism and to provide probable solutions to overcome this perception of the tourist. [ABSTRACT FROM AUTHOR]

Calcium sulfoaluminate (CSA) cement is a low-CO2 binder exhibiting useful properties, such as shrinkage compensation and rapid hardening, which can be achieved by altering its phase composition. In this paper, a hypothetical scenario of CSA cement manufacturing at an existing Indian cement plant is investigated for the environmental consequences (that is, CO2 emissions and energy consumed) using the life cycle assessment methodology. Thirteen laboratory-scale studies from the literature were selected for potential upscaling to industrial level production. The analysis showed that the manufacturing of CSA clinker could result in a 15 to 55% reduction in the CO2 emissions without a significant change in energy consumption when compared to ordinary portland cement. The impacts of CSA cement manufacturing were comparable to those of blended cements, such as those with slag and fly ash. [ABSTRACT FROM AUTHOR]

This paper mainly dealt with the technical and economic feasibility of an off-grid hybrid power generation system for a remote rural Turtuk village of Ladakh, located in the northern part of India. The study showed that the proposed configured renewable integrated hybrid system, using Hybrid Optimization of Multiple Energy Resources (HOMER) software, efficiently met the energy demand, exhibiting optimum performance with low investment. The proposed PV(115 kW)/Wind(1 kW)/Battery(164 strings of 6 V each)/DG(50 kW) hybrid system was a highly commendable, feasible solution preferred from a total of 133,156 available solutions resulting from HOMER simulations. The net present cost and energy cost of the proposed configuration were $278,176 and $0.29/kWh, respectively. The proposed hybrid configuration fulfilled local load, with 95.97% reduced dominant harmful carbon dioxide emission, as compared to the sole us of a diesel generator power supply system. The technical performance of the hybrid system was ensured, with advantages including the highest renewable penetration and least unmet load. Furthermore, the analysis exclusively evaluated the impact of the system's economic parameters (namely, its expected inflation rate, nominal discount rate, and project lifetime) on the net present cost and cost of energy of the system using a noble single fix duo vary approach. [ABSTRACT FROM AUTHOR]

This paper investigates the time-varying effects of fossil fuel consumption on CO2 emissions in India utilizing the time-varying cointegration test, allowing for multivariate long-run time-varying cointegration parameter developed by Bierens and Martins (2010) and the time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005). The long-run time-varying coefficients reveal that GDP has a positive and increasing impact on CO2 emissions over time. Moreover, results confirm the polluting effects of all fossil fuels. Besides, the TVP-VAR model findings also demonstrate that changes in income and fossil fuel consumption have a positive and significant impact on environmental degradation. Coal is found to be the most polluting fuel, followed by oil consumption. Furthermore, the time-varying responses show that increased natural gas consumption has the least influence when compared to other fossil fuels on CO2 emissions. [ABSTRACT FROM AUTHOR]

Green hydrogen is gaining popularity as a clean fuel, and India is one of the countries that is exploring its potential. The paper analyzes the factors contributing to the adoption of green hydrogen in India. The government's policies to encourage usage of clean energy and cut down carbon dioxide emissions are a key factor driving the adoption of green hydrogen in India. Additionally, with the accessibility of renewable energy resources, the growing demand for hydrogen in various industrial applications, and the development of supportive infrastructure and policies are also contributing to the expansion of the green hydrogen sector. The study did a comprehensive literature survey to determine 21 variables that contribute to the green hydrogen development in India, which have been categorized under 4 blocks, namely, varied incentives, government support measures, R&D landscape, and green mandate. These blocks can be utilized to articulate and upgrade the green hydrogen policy. [ABSTRACT FROM AUTHOR]

India's sustainable development goals consist of higher economic growth through large investments on the one hand and ambitious carbon emission reduction plans through increased renewables on the other. It needs to be seen if the two policies related to capital formation and energy transitioning to renewables complement each other or if they have been divergent in the case of India. This paper studies the dynamic association between carbon dioxide emissions, economic growth, renewable energy (RE) consumption, and gross capital formation and tests for the existence of Environmental Kuznets Curve (EKC) hypothesis for India over the time period 1970–2018. It also tries to see if there is any possible conflict between the economic and energy goals of the country by augmenting the interaction term between renewable energy consumption and gross capital formation in the EKC framework. The empirical results not only confirm long-run relationship among the underlying variables but also indicate an "N"-shaped EKC in the long run for India which is a departure from the traditional inverted U-shaped EKC hypothesis. Renewable energy consumption is found to reduce emissions, whereas gross capital formation and the interaction term between renewable energy consumption and gross capital formation are found to raise emissions in the long run. The study concludes that India needs to align its economic policy of "Make in India" with its energy policy so that investments under the former facilitate extensive penetration, adaptation, and usage of renewable energy. A policy dichotomy between the two goals may defeat India's Intended Nationally Determined Contribution (INDC) objective of drastic reduction in carbon dioxide emissions through increased renewables by 2030. [ABSTRACT FROM AUTHOR]

The construction sector is responsible for the 40% of consumed resources, 40% of CO2 emissions, and approximately 40% of construction and demolition waste. For the assessment of the building, there exists a standardized method, life cycle assessment (LCA), however, the process requires time, cost, and most importantly expertise. In this paper, a method is proposed and analyzed for the life cycle assessment of the building for the embodied carbon in the three stages, construction, operation, and demolition. Moreover, the result of the analysis is considered as the base result, and de-carbonization strategies identified through literature study for the three stages of construction, operation, and demolition are assessed with the same method to know how much each strategy will be effective in minimizing the embodied carbon. For the base case, a high-rise residential building in an urban region of India is analyzed, based on existing conditions through the building information modeling (BIM) method. The carbon emission of the selected building comes out to be 414 kg CO2e/m2/year, and assessing different decarbonization strategies, considering the first analysis as the baseline, it can be minimized to 135 kg CO2e/m2/year. [ABSTRACT FROM AUTHOR]

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO2) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO2 emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO2 emissions; correspondingly, this study builds a model for CO2 emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO2 emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO2 emissions. Finally, this study forecasted a CO2 emission trend, with a slowdown predicted in China by 2022; however, CO2 emission's reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO2 emissions without harming economic development. [ABSTRACT FROM AUTHOR]

This research study is one of the significant to offer an inclusive investigation of the impact of green finance correlated policies by applying text analysis approach and panel data from 28 states and 8 union territories between 2010 and 2020. The paper uses the SDID and illustrates that overall, India's green finance associated with policies have directed a substantial decrease in industrial CO 2 emissions during the study period. Furthermore, the paper determined that the Fintech growth pays to the reduction of SO 2 (sulfur dioxide) emissions and positively influences environmental safety and investment enterprises. India is a great competitor worldwide in green finance strategy operation, and controllers need to accelerate the design of green finance products and boost the volume of financial institutions to provide green credit facilities. Though minimalizing the risk fintech stances, policymakers should inspire fintech's to take part in environmental quality protection inventiveness that encourages green consumption actively. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries (LIBs) pose a significant threat to the environment due to hazardous heavy metals in large percentages. That is why a great deal of attention has been paid to recycling of LIBs to protect the environment and conserve the resources. India is the world's second-most populated country, with 1.37 billion inhabitants in 2019, and is anticipated to grow by 273 million people by 2050, according to the United Nations. The biggest obstacles for India's sustainable development will be reducing CO 2 emissions and satisfying the energy requirements of such densely populated country. The electric vehicle (EV) and renewable energy sectors have benefited as a result of this. Indian government wants to achieve 100 percent electric transportation by 2030, and the country's EV battery market is estimated to expand by $300 billion between 2017 and 2030. Batteries, on the other hand, are linked to a slew of difficulties, including their disposal as municipal solid hazardous waste at the end of their useful lives. Waste batteries, when properly utilised, can create several beneficial economic opportunities as well as jobs. This paper highlights India's lithium-ion battery market current scenario, potential, opportunities and various challenges associated with recycling procedures. The study of foreign market regulatory structures on recycling and management of lithium-ion battery waste is also being done, and few regulatory guidelines are being suggested that would improve the Indian battery recycling industry. [ABSTRACT FROM AUTHOR]

This paper compares four prediction methods, namely random forest regressor (RFR), SARIMAX, Holt-Winters (H-W), and the support vector regression (SVR), to forecast the total CO2 emission from the paddy crop in India. The major objective of this study is to compare these four models and suggest an effective model for the prediction of total CO2 emission. Data from 1961 to 2018 has been categorised into two parts: training and test data. The study forecasts total CO2 emission from paddy crops in India from 2019 to 2025. A comparison of mean absolute percentage error (MAPE) and the mean square error (MSE) highlights the differences in accuracy among the four models. The mean absolute percentage eror (MAPE) and the mean square error (MSE) for the four methods are RFR (MAPE: 5.67; MSE: 549,900.02), SARIMAX (MAPE: 1.67; MSE:70,422.35), H-W (MAPE:0.75; MSE:16,648.58), and SVR (MAPE: 0.91; MSE: 17,832.4). The values of MAPE and MSE with the Holt-Winters (H-W) and the support vector regression (SVR) are relatively low as compared to SARIMAX and RFR. Based on these results, it can be inferred that H-W and SVR were found suitable models to forecast the total CO2 emission from paddy crops. Holt-Winters model predicted 14,364.97 for the year 2025, and SVR predicted 13,696.67 for the year 2025. The decision-maker can use these predictions to build a suitable policy for the future. This approach can be contrasted with other forecasting methods, such as the neural network, and train the model to achieve better forecast accuracy. [ABSTRACT FROM AUTHOR]

This paper investigates the association among energy consumption, carbon‐dioxide emission, and India's economic growth along with supplemental variables including foreign direct investment, population density, inflation, and agricultural land. An autoregressive distributive lag model is applied over annual time‐series data from 1985 to 2019. Further, the robustness and novelty of the model are confirmed by applying fully modified ordinary‐least‐square, dynamic ordinary‐least‐square, canonical co‐integrating regression, variance decomposition, and impulse response function. The analysis results indicate that a cointegration association exists among variables. In the short run, the profound determinants of economic development are energy consumption, carbon‐dioxide emission, inflation, and agricultural land. In the long run, both inflation and agricultural land significantly negatively influence economic growth while carbon emission drives a positive impact. Interestingly, a one‐way Granger causality runs from economic growth towards energy consumption, carbon emission, and agricultural land. The new research presents a comprehensive understanding of economic growth indicators, aiding policymakers, and advancing existing literature. Consequently, as a recommendation, the policymakers should constitute explicit goals for renewable energy consumption to stimulate sustainable economic growth with carbon emission reduction. [ABSTRACT FROM AUTHOR]

In this paper, we examined the relationship between renewable and non‐renewable energy consumption on CO2 emissions in India by taking disaggregated data from 1965 to 2018. In order to determine the effect of long‐run elasticity of independent variables on dependent variables, we have used ARDL bound testing approach. The directions of causality of the variables are investigated by Toda–Yamamoto Granger causality test. The long‐run results reveal that hydro energy consumption has a positive impact on CO2 emissions but not significant. However, nuclear energy consumption indicates that there is a negative effect on CO2 emissions. It reveals that all non‐renewable energy consumption sources have positive and significant effect on CO2 emissions. [ABSTRACT FROM AUTHOR]

This paper scrutinizes the asymmetric impact of education and education expenditure on clean energy consumption and CO2 emissions in the BRICS economies using annual data for the period 1991–2019. The analysis employs a nonlinear autoregressive distributed lag (ARDL) framework. Findings unfold that a positive change in education contributes to increasing clean energy consumption in Brazil, Russia, India, and China. This finding implies that a negative change in education contributes to reducing clean energy consumption in Brazil, Russia, and India in the long run. Nonetheless, a positive change in education expenditure increased the clean energy consumption in Brazil, Russia, and India, while it has decreased in South Africa. On the dark side, a negative change in education expenditure degrades clean energy consumption in India, China, and South Africa in the long run. The asymmetric empirical results of CO2 emissions are mixed, economy-specific, and vary across group countries in the long run. We find that the education and education expenditure has long-run asymmetric effects in BRICS industries. Thus empirical findings give us robust policy implications for BRICS economies. [ABSTRACT FROM AUTHOR]

This paper re-examines the relationships between night-time light (NTL) and gross domestic product (GDP), population, road networks, and carbon emissions in China and India. Two treatments are carried out to those factors and NTL, which include simple summation in each administrative region (total data), and summation normalized by region area (density data). A series of univariate regression and multiple regression experiments are conducted in different countries and at different scales, in order to find the changes in the relationship between NTL and every parameter in different situations. Several statistical metrics, such as R2, Mean Relative Error (MRE), multiple regression weight coefficient, and Pearson's correlation coefficient are given special attention. We found that GDP, as a comprehensive indicator, is more representative of NTL when the administrative region is relatively comprehensive or highly developed. However, when these regions are unbalanced or undeveloped, the representation of GDP becomes weak and other factors can have a more important influence on the multiple regression. Differences in the relationship between NTL and GDP in China and India can also be reflected in some other factors. In many cases, regression after normalization with the administrative area has a higher R2 value than the total regression. But it is highly influenced by a few highly developed regions like Beijing in China or Chandigarh in India. After the scale of the administrative region becomes fragmented, it is necessary to adjust the model to make the regression more meaningful. The relationship between NTL and carbon emissions shows obvious difference between China and India, and among provinces and counties in China, which may be caused by the different electric power generation and transmission in China and India. From these results, we can know how the NTL is reflected by GDP and other factors in different situations, and then we can make some adjustments. [ABSTRACT FROM AUTHOR]

Increasing penetration of renewable electricity in the power systems coupled with reduction in its cost has resulted in increased interest in green hydrogen globally. Industry has been using fossil fuel-based hydrogen as an input for several decades. This paper makes an assessment of existing hydrogen production capacities in petroleum refineries and ammonia synthesis units in India along with estimating the potential for installing solar photovoltaic (SPV) powered alkaline electrolysers for producing green hydrogen and SPV capacity required for this purpose. Levelised cost of hydrogen production in these industries in India has been analysed and found to be competitive. The paper also discusses about water requirement, land requirement for SPV power plants, CO 2 emissions avoided and likely investment to be made for establishing infrastructure for green hydrogen production. With launching of national hydrogen mission in India, a transition to green hydrogen by the industry appears to be a near term possibility. • Hydrogen production capacities assessed for petroleum refineries and ammonia synthesis units in India. • Capacities of electrolysers and solar photovoltaic system to be installed for replacing existing hydrogen systems estimated. • Values for levelised cost of hydrogen estimated for such a combination of technologies. • Estimation made for water and land requirement for green hydrogen production, CO 2 emission avoided and investment needed. [ABSTRACT FROM AUTHOR]

India is the third-largest contributor to global energy-use and anthropogenic carbon emissions. India's urban energy transitions are critical to meet its climate goals due to the country's rapid urbanization. However, no baseline urban energy-use dataset covers all Indian urban districts in ways that align with national totals and integrate social-economic-infrastructural attributes to inform such transitions. This paper develops a novel bottom-up plus top-down approach, comprehensively integrating multiple field surveys and utilizing machine learning, to model All Urban areas' Energy-use (AllUrE) across all 640 districts in India, merged with social-economic-infrastructural data. Energy use estimates in this AllUrE-India dataset are evaluated by comparing with reported energy-use at three scales: nation-wide, state-wide, and city-level. Spatially granular AllUrE data aggregated nationally show good agreement with national totals (<2% difference). The goodness-of-fit ranged from 0.78–0.95 for comparison with state-level totals, and 0.90–0.99 with city-level data for different sectors. The relatively strong alignment at all three spatial scales demonstrates the value of AllUrE-India data for modelling urban energy transitions consistent with national energy and climate goals. Measurement(s) electrical energy • fossil fuel • energy use Technology Type(s) machine learning • statistical method Factor Type(s) end-use energy by activity sectors in cities Sample Characteristic - Environment city Sample Characteristic - Location India Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13516925 [ABSTRACT FROM AUTHOR]

This paper quantifies the carbon emissions embodied in the bilateral trade between India from the non-Annex-I country list under the Kyoto Protocol (1997) with two of its biggest trade partners from the Annex-II country list, the USA and the UK, by applying the input–output modelling during the years of 2011 to 2014, to evaluate and analyse the conjecture around the carbon leakage. After the calculation of the embodied carbon in these bilateral exports and imports, the study further inspects the roles of important drivers those are influencing the calculated emission imbalances in trade. This study addresses a high emission-intensive energy consumption pattern of India relative to both the USA and the UK which is confirming the possibility of carbon leakage from Indian commodity production sectors and inducing a huge contribution from these bilateral trades into the global emissions. Finally, this study provides evidence from a spatial decomposition analysis that the differences among the emission-intensity of output between India and its major developed country trade partners create the maximum impact on the implied emission imbalances in the bilateral trades. With the anticipation of increased India–USA and the India–UK bilateral trade, this study proposes suggestion to reduce India's emission intensity of output through fuel switching to the less emission-intensive energy options and relieve the pressure on the global environment. [ABSTRACT FROM AUTHOR]

This paper studies the environmental impacts of trade liberalisation in India. The period of analysis is 1991 - 2018. For this study, the carbon dioxide emissions are taken as a proxy variable to air pollution and the pollution is divided into scale effect, composition effect and technique effect. The Auto Regressive Distributed Lag Model is applied in order to check out the long run association of the variables. The results suggest that the trade is positively related to carbon dioxide emission and are statistically significant. The results suggest that the scale effect is responsible for increasing carbon emissions in India. The technique effect is statistically significant and is negatively related to carbon dioxide emissions. After looking at error correction, it has also been established that the long-run equilibrium relationship between the variables is valid. According to the ECM, 84 percent of the adjustment happens gradually over time. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions and PM2.5 pollution from vehicular exhausts and the consequent negative externalities underline the urgency of investigating low-carbon pathways for the freight sector. This paper undertakes a comprehensive analysis to determine the implications of a modal shift in the freight sector for the environment, energy systems and the economy. Stakeholder consultations are used to develop the qualitative narratives that are further used to set the parameters in energy-economy optimization models for deriving quantitative pathways. Our analysis includes four scenarios: Current Policy (CPS), Road Focused (FROAD), Rail Technology (TRAIL) and Harmonized Multimodal (HMML). The HMML scenario follows a balanced approach harmonizing the twin goals of reducing imported fuels and carbon emissions that can simultaneously assist in achieving development and decarbonization targets. Our results show that the HMML scenario based on the multimodal approach of creating a level playing field for all modes can reduce fossil fuel imports by 87.6% and CO 2 emissions by 96%, relative to CPS in 2050. The HMML scenario also envisages significant macroeconomic benefits – the cost of logistics as a percentage of GDP falls to 11%, and there are cumulative foreign exchange savings of 3.8 trillion USD from 2016 to 2050. However, electrification, the leading technology for the respective decarbonizing modes, will need policies that enhance research and innovation on batteries and infrastructure investments for charging along national and state highways. The main policy insight from our analysis is that multimodal logistics policy needs to be designed in alignment with clean energy-based electrification policy and national rail plans so that uniform rules from the origin govern all modes to the destination of goods transport. • Modelling energy economy to analyse implications of modal shift. • Combining stakeholder consultations with quantitative evaluations. • Multimodal approach achieves development and mitigation goals at the same time. • Over 80% of savings on imports of fossil fuels are possible by 2050 relative to the current policy scenario. • Cumulative foreign exchange savings of 3.8 trillion USD can be achieved from 2016 to 2050. [ABSTRACT FROM AUTHOR]

Summary: The concept of green computing is a step toward advanced information technology‐related data computations. There is an urgent need to develop sustainable mobile telecommunication networks subscribed by Telecommunication Regulatory Authority of India (TRAI). This paper aims at deploying major recommendations and directions in computing systems directed by regulating authorities. Green computing–based power‐saving policies include virtualization technique, power‐saving method, and recycling technique‐type solution components that we tried to embed in existing systems. The energy‐efficient green computing reserves the reliability and power of information‐driven technology. This research paper provides a comprehensive approach toward applying green mechanism by spotting the difference between energy consumption of current academic scenario and after embedding power‐saving policies of green computing. Moreover, an account has been maintained about the amount of energy preservation. The extraordinary energy‐ and cost‐saving features of green computing make environment sustainable and lively for future generations. [ABSTRACT FROM AUTHOR]

Abstract Physical, Regulatory and Brand value risks due to climate change challenges are foreseen by businesses globally. This paper is oriented towards these challenges and prepared a comprehensive Greenhouse gases (GHG) footprint plan and identification of mitigation opportunities for ONGC, a fortune 500 and national oil company of India. Internationally recognized standards and guidelines like Greenhouse Gas Protocol, ISO-14064, and American Petroleum Institute compendium have been referred for quantifying carbon emissions in nearly real 400 + operation control facilities. The GHG inventory is based on Operational Control approach to identify the boundary for which emissions are to be quantified and two significant scopes of emissions viz Direct Emissions and Indirect Emissions are identified and quantified. The quantification concluded that GHG emission footprint for the year 2016–17 is in the range of 9 million tons of CO 2 equivalent. GHG emissions mainly account due to stationary combustion, fugitive emissions and wastewater treatment, which share the around 56% of total emissions. Another 24–26% of emissions are contributed due to flaring, processes by glycol dehydrator, acid gas removal units, and by electricity purchased from the grid. As a result, it has been found that ONGC emits 187 kg CO 2 e emissions per tonne throughput and also compared with its global peer organizations. At the organization level, "Key Industrial Sites" have been identified as contributing higher GHG emissions and accordingly key "hot-spots," a list of 15 GHG mitigation opportunities have been proposed in the paper. Two GHG mitigation initiatives based on solar energy and bioenergy application undertaken at ONGC has also been briefed on case studies. Highlights • Comprehensive carbon footprint plan and identification of mitigation opportunities for Oil and Natural Gas Corporation (ONGC), a fortune 500 and national oil company of India. • Guidelines like Greenhouse Gas Protocol, ISO-4064 and American Petroleum Institute compendium are referred for quantifying carbon emissions from direct and indirect sources. • Green policy, incentives and mandatory compliance. • CO2e emissions per tonne throughput and also compared with its peer global organisations. • Key hot-spots, with a list of 15 GHG mitigation opportunities. [ABSTRACT FROM AUTHOR]

This paper forecasts the growth of freight transport emissions in India's trucking sector until 2050. We use the ARIMAX time series model to project the commercial vehicle population under various economic growth scenarios. CO 2 emissions are estimated using emission factors, distance traveled, and the projected commercial vehicle population. We use the validated forecasting model to investigate how emissions can be curbed through vehicle scrappage policies or fleet electrification to realign with the 2015 Paris Agreement's targets. Compared to the business-as-usual (BAU) scenario, 10-year and 15-year vehicle scrappage policies are estimated to reduce freight emissions by 6–11% and 1–2%, respectively. Fleet electrification has more pronounced effects as it results in a 35% and 70% reduction in carbon emissions for heavy and light goods vehicles in 2050, respectively, compared to the BAU scenario. These findings provide crucial insights for devising policies to mitigate greenhouse gas emissions in India's trucking industry. [ABSTRACT FROM AUTHOR]

Current study aims in finding the combined effect of using rectangular fins, gravels (G) and phase change material (PCM) on the performance of pyramid solar still. Two solar stills, one of conventional type (CSS) and other of modified solar still (MSS) which uses fins and PCM inside the basin, are fabricated. Experiments are conducted at Greater Noida (28°28′N, 77°30′E) of Uttar Pradesh, India, during May 2023. The influence of solar still design modifications (CSS and MSS) and adding gravels (CSS + G and MSS + G) on the performance of solar stills is investigated in terms of productivity, energy, exergy, economic, and environmental parameters. Experimental results show an enhancement of about 84 %, 38 % and 32 % in daily productivity for MSS + G, CSS + G and MSS, respectively, than CSS. The MSS + G shows the highest improvement in energy (81.1 %) and exergy efficiency (273 %) with significant reduction in costs per liter of yield produced (29.2 %) and payback period (29 %) when compared with CSS. About 76 % rise in carbon credits earned is observed for MSS + G than CSS while mitigating the CO 2 emission of 19.14 tons. Conclusively, the innovative design (MSS + G) not only offers cost-effective yield production but also plays a crucial role in promoting environmental sustainability by reducing CO 2 emissions. • This paper develops and tests a modified solar still that uses PCM and fins. • The combined effect of fins, gravels and PCM is investigated. • The experiments conducted in Greater Noida, India, during May 2023. • MSS + G improved daily productivity by 84 %. • MSS + G reduces costs/l of water by 29 % and mitigates CO 2 emissions by 19.14 tons. [ABSTRACT FROM AUTHOR]

The paper presents extensive monitoring, detailed long term operational performance and on-field degradation measurement of utility scale grid connected 10 MW solar photovoltaic (PV) plant in real operating conditions. Different performance indices are evaluated incorporating IEC standard 61724 guidelines based on actual plant monitoring data (incident solar irradiation, ambient and module temperature and generated electrical energy) from January 2016 to December 2020 (period of five years). The annual average reference, array and final yield, performance ratio, capacity utilization factor, array capture and system losses, PV array and system efficiency of the plant were found to be 6–6.7 h/day, 4.83–5.1 h/day, 4.69–4.86 h/day, 72–74%, 19–20%, 1.02–1.33 h/day, 0.15–0.156 h/day, 12% and 11% respectively. Degradation of fielded modules is assessed by visual inspection and I-V curve tracing. Correlation of I-V characterization with electrical parameters of visually degraded installed PV modules is also presented. The calculated linear degradation rates varied from 0.97 to 1.52%/year in modules with considerable bird dropping, 1.33 to 1.61%/year in modules with light EVA discoloration, 1.6 to 1.86%/year in modules with glass breakage, 2.31 to 3.94%/year in modules with glass breakage and dark EVA discoloration, and 2.97 to 5.8%/year in modules with glass breakage and cell cracks. The annual linear degradation rates were found to be in the range of 0.9 to 1.1%/year for normal fielded modules with no visible degradation and 0.97 to 2.9%/year for visually degraded modules with mean and median values of 1.8%/year and 1.6%/year with six years operational period. The levelized cost of electricity, simple and discounted payback period and return on investment were found to be 4.05 Rs, 5.5 years, 11 years and 62.22% respectively. Annual CO 2 savings of the plant is around 16,000 tons and CO 2 emission reduction potential of installed pc-Si technology is found to be 1.6 tons/kW p. • Prolonged operational performance of utility scale 10 MW PV plant is evaluated based on real time plant monitoring. • Extensive degradation investigation is presented based on on-field experimental measurement in hot semi-arid climate. • Correlation of identified degradation modes and failures with electrical performance of degraded PV modules is presented. • Detailed financial and environmental analysis is presented in terms of LCOE, SPP, DPP, NPV, ROI & cumulative CO 2 savings. • Results provide important insights on PV plant operation in hot climate and in in improved operation of future PV plants [ABSTRACT FROM AUTHOR]

Carbon mitigation and net-zero targets have an important place on the political agenda for all countries. Countries have been seeking to decouple economic growth and carbon emissions to achieve decarbonization. However, there is a cost of the decarbonization of economies, which can be called as Green Sacrifice Ratio (GSR), and this is critical for developing countries because they have been in the growing stage. By considering the critical role of GSR in achieving net-zero emissions by decarbonizing economies, the study comparatively examines how much environmental quality should be sacrificed for per capita economic growth in China and India. In line with this purpose, the study uses the Fourier-Shin cointegration test and various time series estimators with Fourier approximations for the period from 1989/Q1 to 2022/Q4. Estimation results are as follows: (i) all variables follow the non-stationary process, (ii) the long-run relationship exists between variables, and (iii) Estimation results show that GSR is 0.65% for China and 0.78% for India. Therefore, China and India sacrifice a significant amount of environmental quality for a 1% increase in per capita income level. Also, the ecological cost of increasing economic welfare in India is higher with regard to China. Besides, the results are robust according to the alternative method. Thus, the study recommends that both Chinese and Indian policymakers should revise the economic expansion structure with green growth strategies to prevent irreversible environmental degradation due to higher economic growth. [ABSTRACT FROM AUTHOR]

This paper investigates the nexus between CO2 emissions (CO2E), GDP, energy use (ENU), and population growth (PG) in India from 1980–2018 by comparing the "vector error correction" model (VECM) and "auto regressive distributed lag" (ARDL). We applied the unit root test, Johansen multi-variate cointegration, and performed a Variance decomposition analysis using the Cholesky approach. The VECM and ARDL-bound testing approaches to cointegration suggest a long-term equilibrium nexus between GDP, energy use, population growth and CO2E. The empirical outcomes show the existence of a long-term equilibrium nexus between the variables. The Granger causality results show that short-term bi-directional causality exists between GDP and ENU, while a uni-directional causality between CO2E and GDP, CO2E and ENU, CO2E and PG, and PG and ENU. Evidence from variance decomposition indicates that 58.4% of the future fluctuations in CO2E are due to changes in ENU, 2.8% of the future fluctuations are due to changes in GDP, and 0.43% of the future fluctuations are due to changes in PG. Finally, the ARDL test results indicate that a 1% increase in PG will lead to a 1.4% increase in CO2E. Our paper addresses some important policy implications. [ABSTRACT FROM AUTHOR]

The present study investigates the long-run impact of financial development, energy consumption and economic growth on greenhouse gas emissions for India, in the presence of endogenous structural breaks, over the period 1971–2013. The autoregressive distributed lag bounds testing procedure (ARDL) and Hatemi-J threshold cointegration technique were used to test the variables for cointegration. ARDL bounds test did not confirm any cointegrating relationship between the variables. The threshold cointegration test establishes the presence of long-run impact of financial development, energy use and economic growth on greenhouse gas emissions in India. The results reveal that the long-run relationship between the variables has witnessed two regime shifts, in 1978 and 2002. The empirical evidence shows that financial sector development and energy consumption in India degrade the environment. Unlike previous studies, this paper finds no statistical evidence of a long-run relationship between economic growth and environmental deterioration. The study also challenges the existence of an environmental Kuznets curve in India. [ABSTRACT FROM AUTHOR]

The procurement of food grains from farmers is one of the biggest challenges under the COVID-19 outbreak due to country-wise lockdowns. The present study aims to reconfigure the existing food grain supply chain network. The study advances the extant literature by proposing a novel mathematical model that considers the government guidelines issued to procure food grains from farmers under the COVID-19 situation. The model includes personal distancing, a key parameter relevant in the COVID-19 crisis, and has remained unaddressed in the existing literature. The proposed model is tested in India. The effect of different parameters like personal distancing cost, carbon emission cost, fixed cost, and transportation cost is also investigated under a given set of procurement centers. Finally, the procurement schedule for each procurement center is generated, which is especially useful for managing its activities and is also helpful to farmers to streamline the process. Results indicate that the proposed model is highly effective under pandemic emergencies like the current COVID-19 crisis. Policymakers and the government will find this model helpful in drafting relevant policies regarding food grain procurement under emergencies such as the COVID-19 outbreak. The distribution segment of the supply chain network is not part of the present research work. In future studies, this part could be then added to the whole of the procurement process, and both procurement and distribution can be assessed together again. [ABSTRACT FROM AUTHOR]

Energy efficiency gains are advocated to be a plausible strategy to mitigate rising carbon emissions in the Indian transportation sector. This study, thus, estimates the energy efficiency across transportation modes in India for 2000–2014, employing the panel stochastic frontier approach. Further, the long-run effect of energy efficiency gains on carbon emissions is also examined by employing the panel fully modified least square (FMOLS) and panel dynamic ordinary least square (DOLS) estimators. The empirical findings indicate an inverted U-shaped trend in energy efficiency for land transportation and a substantial rise for air transportation with higher volatility. However, the trend in energy efficiency for water transportation only shows a minor uptick with nearly stable movement. The long-run effect reveals that a 1% increase in energy efficiency will reduce carbon emissions in the transportation sector by more than 1%, between 1.343 (FMOLS) and 1.665% (DOLS). Based on such findings, a few implications are discussed to achieve a low-carbon energy system. [ABSTRACT FROM AUTHOR]

• Advanced clean coal technologies and CCS could provide promising solutions for reducing CO 2 emissions up to 45% in comparison to BAU by 2050. • Coal demand changes to 1100-1400 Mt in 2030 and 1132-2200 Mt in 2050 under alternate future scenarios • CO 2 emissions from coal changes to 45-69% in 2030 and 34-67% of the total emissions in 2050 under alternate future scenarios. • Mitigation measures first decarbonize the power sector due to availability of flexible choices. Simultaneously it decarbonizes the other economic sectors. • Analysis shows that energy security and deep GHG emission mitigation is possible. Rapid shift from traditional energy intensive pathways is required to pace-up economic growth before exhausting remaining carbon budget under 2 °C global stabilization target. Within this larger context, in this paper we have used AIM/End-use, a bottom-up, techno-economic model to analyze India's energy security and greenhouse gas (GHG) emissions from the year 2000 to 2050 with a focus on possibilities of coal continuance in India. Our analysis shows that by adopting advanced coal technologies and carbon dioxide capture and sequestration (CCS) options, up to 45% CO 2 emission reduction can be achieved over business-as-usual scenario (BAU) by 2050. This is possible even when coal use would increase to nearly 2200 Mt in 2050 as against 870 Mt in 2017-18. Without CCS, coal use could peak at 1200 Mt with 22% CO 2 reduction over BAU in 2050 but in that case nuclear and renewable energy would become pivotal in meeting energy demand. The paper concludes that a win-win integration of energy security and deep GHG emission mitigation is possible through a large-scale integration of advanced coal technologies and CCS in Indian energy systems. We have also provided a brief PESTLE analysis for finding the enabling environment necessary for achieving the results discussed in various scenarios. [ABSTRACT FROM AUTHOR]

The agroforestry system is the best option to achieve the net zero carbon emissions target for India. Keeping this view, carbon sequestration and credit potential of gamhar based agroforestry system has been assessed. The experiment was carried out in randomized block design in seven different treatments with five replications. Gamhar tree biomass accumulation was higher in gamhar based agroforestry system compared to sole gamhar. Among different tree components, stem contributed a maximum to total gamhar tree biomass followed by roots, leaves and branches. The average contributions of stems, roots, leaves and branches in total tree biomass in two annual cycles (2016–17 and 2017–18) varied between 50 and 60, 19.8 and 20, 19.2 and 20, and 10.7 and 12.7 percent, respectively. In case of crops, above ground, below ground and total biomass was significantly higher in sole intercrops than gamhar based agroforestry system. Total (Tree + interrops + Soil) carbon stock, carbon sequestration, carbon credit and carbon price were significantly affected by treatments, and was maximum in Sole Greengram-Mustard. Net carbon emission was also recorded lowest in Sole Greengram-Mustard for which the values were 811.55% and 725.24% and 760.69% lower than Sole Gamhar in 2016–17, 2017–18 and in pooled data, respectively. [ABSTRACT FROM AUTHOR]

Motivation: Tea, derived from the Camellia sinensis plant, holds the position of being the most widely consumed manufactured beverage globally. Its cultivation necessitates specific agro-climatic conditions, leading to its production being confined to select regions, notably including India. India contributes about 20.81% to the world's tea output. The production and processing of tea leaves to final product consume energy in terms of machinery, fertilizer, irrigation etc. The energy consumption involved in tea production is a pressing concern, given the associated high costs and CO2 emissions resulting from fossil fuel usage. To achieve a net-zero carbon balance, there is need to pay attention towards promoting renewable energy technologies as a means to mitigate the CO2 emissions stemming from fossil fuels in India's tea sector. Objectives: Aligned with the objective of sustainability through the integration of renewable energy sources, a pilot study was conducted in the primary teagrowing regions of northeastern India during 2021-22. The primary aims of this study were twofold: to gauge the quantity of CO2 emissions originating from conventional energy sources and to explore the feasibility of incorporating renewable energy sources as viable substitutes. Data and methods: Data on various inputs used in tea production were collected from Assam and West Bengal states of India by using a stratified random sampling method with equal probability and without replacement. Results: The findings of this investigation underscore a noteworthy potential for the adoption of renewable energy, particularly solar energy, within the tea estates situated in the north eastern region of India. Such a transition would yield benefits for both the tea estates themselves and the overall environment. [ABSTRACT FROM AUTHOR]