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Road Roughness/Unevenness is an important parameter for the evaluation of the surface condition of a road. Roughness affects the vehicle operating cost, speed, riding comfort, safety, fuel consumption, and tire wear and tear. Every road user desires to have a smooth and comfortable riding. Roughness measurement is an important activity on highways based on which maintenance decisions are taken. IRC (Indian Road Congress) manual specifies roughness measurements to be taken at every 6 months on highways and based on the roughness index the functional overlay requirements are decided on highways. Roughness measurements using profilometers, namely Rod and Level, Dipstick, Merlin, Profiler, LiDAR, etc., give detailed surface profile measurements but are time-consuming. An alternative to profilometers is Response Type Road Roughness Measurement Systems (RTRRMS) which are installed on vehicles and measure how the vehicle responds to the pavement profile. A car-mounted fifth wheel Bump Integrator developed by CRRI in India is commonly used to measure roughness. The fifth wheel bump integrator system works through mechanical instruments producing 'bumps,' a binary, 'true or false' information, instead of 'range based' analog information produced by digital accelerometers commonly found in smartphones. Due to the difficulty in the calibration process, towing for longer distances, and complexity in recording, analyzing, and possible manual errors in recording the data, Cell Phone-based systems are becoming popular for their simplicity in measuring roughness using accelerometers embedded in the cell phone. RoadBounce is one such technology using Cell phone-based mobile Apps to measure roughness. This paper intends to present the findings of testing and evaluation of App-based roughness measurement technology for its accuracy and usability using different vehicles and mobile phones under different speeds, tire pressures, gradients, etc. [ABSTRACT FROM AUTHOR]

In the conditions of the spread of globalization processes, growing interdependence, and interconnectedness of countries, a significant intensification of the academic society efforts to ensure national energy security and independence is necessary. The purpose of the paper is to provide a systematic review of the scientific environment aimed at analysing the contents and features of scientific publications dealing with new trends and patterns in sustainable energy consumption. In order to create a semantic and definition basis and research the main trends of scientific publications on the subject of developing energy efficiency and sustainable consumption, the paper carried out a bibliometric analysis concerning the categories «energy efficient» and «energy consumption» using the Scopus and VOSviewer tools. The main question is, what are the main scientific and research trends and patterns in the field of energy efficiency and sustainable consumption? For this purpose, the quantity and quality tendencies of the scientific articles which are studying issues connected with energy efficiency and sustainable consumer behaviour were determined. A sample of more than 24000 scientific publications on this issue was generated from publications indexed by the Scopus database. The study period covers 2001-2021. On the global level, the analysed investigated area is represented by the countries: China, the USA, and India. VOS viewer tools were used to systemize 5 clusters of scientific articles that analysed sustainable energy consumption from different points of view. Identification of regularities in the developing of scientific approaches to energy-efficient consumption and developing sustainable energy sector was carried out using bibliometric analysis, which has made it possible to describe the dominant retrospective evolutionary and temporal tendencies in the development of this theory concerning the concepts of sustainable development, environmental management, and development of renewables. As a result, one of the most significant trends is a green brand and tendencies connected with developing green marketing and green consumer awareness. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are fast evolving and their technological advancement is taking at a rapid pace. The performance usually depends upon two basic parameters for an EV, the range of the vehicle and energy consumption per kilometre for the vehicle. Drive cycles (DCs) play a major role in designing EVs. Many DCs are currently used such as the Indian drive cycle (IDC), New European Drive Cycle (NEDC), Worldwide Harmonised Light Vehicle Test Procedure (WLTP) to check the performance of vehicle in term of their emissions and working standards. This paper compares an electric two‐wheeler scooter with these standard DCs for range and energy consumption estimation and found out that the range obtained using NEDC drive cycle was 130 km in comparison with the IDC which was about 95 km. The paper also highlights the importance of good infrastructure of roads in India to optimize the driving range of the electric vehicle and also stresses the use of good cooling techniques of batteries for range enhancement of EVs. [ABSTRACT FROM AUTHOR]

This paper uses neoclassical microeconomic theory to investigate the demand for energy and interfuel substitution in India at the sectoral level. It makes full use of the relevant economic theory and econometrics and generates inference in terms of Allen and Morishima elasticities of substitution that are internally consistent with the data and nonlinear models used. The results indicate that the interfuel substitution elasticities are consistently below unity in the household and power sectors, revealing the limited ability to substitute between major energy commodities in these two sectors. However, significant substitution relationships are found in the industrial and transportation sectors, suggesting that energy price changes in these sectors will significantly shift the demand for energy and consumption. Based on measured elasticities of substitution, we also discuss implications of energy price shocks on inflation and inflation targeting strategies by the central bank. [ABSTRACT FROM AUTHOR]

Multicriteria mathematical modeling is an analytical framework for formally describing real‐life problems involving multiple and conflicting objectives. In the past decade, multicriteria decision‐making techniques have been applied in almost every area of the decision‐making including energy‐economic planning and sustainable development. Various mathematical and analytical models have been presented for the sustainable development planning and their assessment. In this paper, we discuss an approach related to multicriteria decision‐making and apply it for the assessment of the sustainable development goals of India by the year 2030. In the INDC report submitted to United Nations Framework Convention on Climate Change (2015, http://www..unfccc.int/submissions/INDC/Published%20Documents/India/1/INDIA%20INDC%20TO%20UNFCCC.pdf), India has identified many goals related to the sustainable development like energy consumption, greenhouse gas emissions, GVA growth, and an increase in the employment by the year 2030. This paper overcomes the energy resource allocation problem in related literature due to the lack of sectorial data for the same year by calculating the estimates for each sector for the year 2030. We presented a multicriteria decision‐making model which allocates public labor force in the key economic sectors of India. The presented model is validated with the data of the key economic sectors and their contribution in the identified goals. The paper provides a decision support for the better management of future sustainable policies by assessing the efficiencies of the current policies toward future sustainable goals. We evaluated the identified goals using the multicriteria decision‐making approaches so that the strategic planning can be implemented by the policy makers and to present a quantitative justification of planning strategies. [ABSTRACT FROM AUTHOR]

Green Panchayat means powering the rural Indian households by harnessing the renewable sources of energy. India has set target of achieving Net-Zero emission by 2070 and the set target cannot be achieved without the inclusion of the rural households as more than half of our country population lives in rural areas. Rural electrification is considered the backbone of the rural economy but it has come up with many challenges such as availability of 24x7 power supply, power wastages due to subsidized electricity and losses to State Discoms. The paper illustrates the case study of energy consumption pattern of villages Amro, Kochwa and Budgada and it proposes a solution to provide reliable power using PV-micro-grid and solar roof top installation on public buildings.Further, detail sizing (battery, inverter, panels) of the proposed PV system to meet the energy demand (1196.91 kWh/day) of the considered villages is also determined. The economic analysis is also shown in terms of payback period to reflect the project feasibility. The paper also illustrates the energy conservation measures to be taken up in the rural households to achieve the energy savings by use of energy-efficient appliances. In a nutshell, this paper will be helpful to the power system planners and decision makers for possible implementation of Rural Electrification project which has a vital role in achieving Net-Zero emissions and sustainable development [ABSTRACT FROM AUTHOR]

India is a dynamically developing country in which 60% to 65% of the industry consumes electricity. Many Indian firms are improving their technology, so the demand and supply of electricity is growing. With the help of energy audits, it can reduce the gap between energy demand and supply as much as possible, which is good for all sectors and it can manage the maximum demand for energy in companies and improve the power factor by reducing energy losses and improving energy efficiency. This paper is a preliminary investigation by Vandana Global Limited, Raipur. Comprehensive load study of industries with 7000 KVA monthly contract demand, new loads have been introduced in this industry, highlighting the need for significant energy conservation measures. To evaluate the savings, a full energy audit must be carried out. After energy analysis of the monthly electricity bill, the four-month average power factor is 0.92, therefore the grid power factor can be increased as inductive loads are fewer. It can use the automatic reactive control panel to improving to the grid power factor by adjusting the required reactive power from the grid connected alternator. The system is effective due to cost savings, return on investment and profit. Time of Day (TOD) and conserve energy meter readings were used to measure demand control. Energy Audit energy efficiency solutions reduce energy waste and energy costs. In general, special attention was paid to reduce demand losses and energy costs. This paper recommends using genuine energy in the right place and organizing the use of energy through an energy audit. [ABSTRACT FROM AUTHOR]

Hydrogen is the new age alternative energy source to combat energy demand and climate change. Storage of hydrogen is vital for a nation's growth. Works of literature provide different methods for storing the produced hydrogen, and the rational selection of a viable method is crucial for promoting sustainability and green practices. Typically, hydrogen storage is associated with diverse sustainable and circular economy (SCE) criteria. As a result, the authors consider the situation a multi-criteria decision-making (MCDM) problem. Studies infer that previous models for hydrogen storage method (HSM) selection (i) do not consider preferences in the natural language form; (ii) weights of experts are not methodically determined; (iii) hesitation of experts during criteria weight assessment is not effectively explored; and (iv) three-stage solution of a suitable selection of HSM is unexplored. Driven by these gaps, in this paper, authors put forward a new integrated framework, which considers double hierarchy linguistic information for rating, criteria importance through inter-criteria correlation (CRITIC) for expert weight calculation, evidence-based Bayesian method for criteria weight estimation, and combined compromise solution (CoCoSo) for ranking HSMs. The applicability of the developed framework is testified by using a case example of HSM selection in India. Sensitivity and comparative analysis reveal the merits and limitations of the developed framework. [ABSTRACT FROM AUTHOR]

A robust assessment of water used in agriculture, including livestock production systems and supply chains, is critical to inform diversification and the development of productivity and sustainable food production systems. This paper presents a detailed analysis of water used and consumed in nine dairy milk processing plants spread across Punjab, India's leading dairy milk-producing state. Over the five years (2015–2019), the direct water use (DWU) was quantified at 3.31 L of groundwater per kg of milk processed. Only about 26% of the direct water used was consumed, including evaporative losses in various milk processing operations, while the remaining 74% was returned as effluent discharges. The average total water footprint (TWF), accounting for both direct and indirect water consumption, was quantified at 9.0 L of water per kg of milk processed. The majority share (~89%) of the total water footprint was contributed by the indirect water footprint associated with the consumption of electricity (energy) in dairy milk processing activities. The plant's milk processing capacity and processing products mix also affected significant seasonal and annual variations in the direct and indirect water footprints of dairy milk processing. The analysis also found an inverse relationship between the average total water footprint and the average monthly amount of milk processed in the study plants. Therefore, efforts to reduce the indirect water footprint (associated with energy consumption), the treatment and recycling of effluent discharges, and the optimization of milk processing capacity, the dairy processing product mix, and the locations of dairy processing plants are expected to help reduce the water footprint of dairy processing in the state. [ABSTRACT FROM AUTHOR]

Understanding the long‐term effects of population and GDP changes requires a multisectoral and regional understanding of the coupled human‐Earth system, as the long‐term evolution of this coupled system is influenced by human decisions and the Earth system. This study investigates the impact of compounding economic and population growth uncertainties on long‐term multisectoral outcomes. We use the Global Change Analysis Model (GCAM) to explore the influence of compounding and feedback between future GDP and population growth on four key sectors: final energy consumption, water withdrawal, staple food prices, and CO2 emissions. The results show that uncertainties in GDP and population compound, resulting in a magnification of tail risks for outcomes across sectors and regions. Compounding uncertainties significantly impact metrics such as CO2 emissions and final energy consumption, particularly at the upper tail at both global and regional levels. However, the impact of staple food prices and water withdrawal depends on regional factors. Additionally, an alternative low‐carbon transition scenario could compound uncertainties and increase tail risk, particularly in staple food prices, highlighting the influence of emergent constraints on land availability and food‐energy competition for land use. The findings underscore the importance of considering and adequately accounting for compounding uncertainties in key drivers of multisectoral systems to enhance our comprehensive understanding of the complex nature of multisectoral systems. The paper provides valuable insights into the potential implications of compounding uncertainties. Plain Language Summary: Understanding how future population and economic growth changes could impact our energy, water, food, and environment requires looking across multiple sectors and regions. This is because these systems are all connected. For example, increasing population drives higher food demand but requires more energy and water to grow food. At the same time, reducing greenhouse gas emissions from energy through increased biofuel consumption can compete with food production for land resources. This study explored how uncertainties in future population and GDP growth could compound and interact to affect future energy use, water withdrawal, staple food prices, and carbon dioxide emissions. Using a model that connects all these systems, the study found that combined uncertainties in population and GDP lead to more significant risks of extreme outcomes than individually looking at those uncertainties. There are substantial regional differences in future outcomes, like higher uncertainty in food prices for India and West Africa compared to other regions. We highlight the need to consider multisector and multisystem interactions between uncertainties across different regions. Accounting for these compounding uncertainties provides valuable insights into potential risks, like higher extreme projections for food prices or water use. These insights are essential for long‐term planning in our connected human‐Earth system. Key Points: Long‐term implications of population and GDP changes on the coupled human‐Earth system focusing on multisectoral and regional understandingUncertainties in GDP and population growth can compound, resulting in more extreme outcomes for multisectoral systemsCompounding uncertainties differ by region and metrics; staple food prices and water withdrawal show significant regional variability [ABSTRACT FROM AUTHOR]

This paper examines the impact of structural change, economic growth, hydro energy consumption, and coal energy consumption on ecological footprint, in the case of India. We employ a novel dynamic autoregressive distributed lag (DYNARDL) method to improve the existing studies' limitations and weaknesses. Thus, the current research contributes empirically and methodological to the literature. The study used the newly proposed DYNARDL simulation method and frequency domain causality using data from 1970–2017 to inspect the impact of structural change, economic growth, hydro energy consumption, and coal energy consumption on ecological footprint in the case of India. Empirical results reveal that institutional structural change decreases ecological footprint in the short and long term, whereas hydropower usage decreases ecological footprint only in the long term. Conversely, economic growth positively affects ecological footprint in both the short and long term. Likewise, coal energy usage increases ecological footprint in the long term. In addition, the findings confirm the validity of the environment Kuznets curve (EKC) hypothesis in India. Furthermore, the results of the frequency domain causality test revealed that structural change, hydro-energy usage, and coal consumption could predict ecological footprint in the long term. In contrast, economic growth can predict the medium- and long-term ecological footprint. We observed that as India's production level continues to surge, so does environmental deterioration, which is associated with the scale effect. [ABSTRACT FROM AUTHOR]

In recent times, the virtual power plant (VPP) is gaining more attention in power system engineering due to its tremendous potential in enhancing sustainable urbanism, in which, it supplies clean energy from distributed generators. Electricity is deemed a basic requirement for future automotive and ultra-modern technologies. The deficiency of traditional energy resources and their complex generation process make the production cost of electricity increase dramatically. Moreover, traditional power distribution systems are encountering issues in distributing electrical energy to fulfill customer demands. Therefore, this paper proposes a novel power management system named 'the hybrid genetic local binary knowledge (HGLBK) algorithm' to manage power distribution in the transmission lines and to optimize the total operation cost of the network. The hybrid optimization algorithm effectively controls the load by supplying the surplus power load to the adjacent feeders thereby optimally selecting and placing the distributed energy resource (DER). The proposed concept is implemented at Kayathar, Tamil Nadu in India, and their real-time data are utilized for modeling the VPP. The proposed VPP concept is implemented in the IEEE-9 bus system and the performance of VPP is simulated using the MATLAB software. The performance of the proposed HGLBK algorithm is assessed by comparing its effectiveness with the existing approaches. [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]

Energy and waste management sectors are considered important for the country's progress towards adopting sustainable consumption and production (SCP) practices and achieving Sustainable Development Goals. However, the rapid pace of urbanization, energy-intensive growth approaches, and generation of large quantities of waste have led to severe environmental degradation of cities in India. While the government has taken several initiatives for increasing resource efficiency, limited research has been done in an Indian context to explore the policy and institutional factors. The paper focuses on challenges relating to policy enablers within the energy management in buildings and construction and demolition waste sectors; 28 semi-structured interviews were conducted with stakeholders associated with both these sectors. The findings indicate that though India has been integrating climate change measures into its national policies and enhancing the domestic market's readiness for a circular economy, successful implementation of policy framework(s) urgently requires lifestyle and behavioural changes in the society. The study further identified the role of key stakeholders including government, businesses, and consumers, for transition to a low-carbon economy for both these sectors. This paper presents a bottom-up approach to understand the changes required in the enabling environment for the uptake of SCP practices that can be adapted by other emerging economies in the Asia Pacific region for building resource efficiency. The importance of soft factors relating to institutional capacities and governance structure is raised by the analysis in this paper. [ABSTRACT FROM AUTHOR]

Nowadays, to achieve sustainable development and avoid devastating impacts on the environment, India is making rapid and broad changes to green energy technology. In order to provide long-term energy security with lower emissions, renewable energy sources are essential. It is well known that renewable energy technologies, or RETs, have the capacity to significantly meet the demand for electricity while lowering pollution levels. The nation has set up an ecologically friendly energy route in recent years. In this paper, we apply multi-criteria decision making (MCDM) models to determine the best renewable energy technology for India. We use the MULTIMOORA model to identify the best technology under the pythagorean neutrosophic fuzzy set (PNFS) and the FUCOM to obtain the criteria weights. In this study, we investigate sources of renewable energy using the newly developed idea of the PNFS and recommend the best renewable energy source for India. [ABSTRACT FROM AUTHOR]

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Cogeneration is preferred mostly in process industries where both thermal and electrical energies are required. Cogeneration plants are more efficient than utilizing the thermal and electrical energies independently. Present government policies in India made renewable energy generation mandatory in order to minimize fossil fuels consumption and to protect the environment. Hence, many cogeneration plants have been integrated with renewable energy generation. However, post-integration effects increase and introduce inefficiencies in the operation of cogeneration systems. In this paper, a case study of an identified typical cogeneration plant where renewable energy is integrated is considered. Post operational effects on the plant due to integration of renewable energy (solar) are studied and by practical experimentation through cost-benefit analysis the break-even point beyond which renewable energy generation introduces inefficiencies is estimated. Next, a systematic methodology is developed based on the heuristic forward-chaining approach technique to establish the breakeven point. An algorithm/flow chart is developed using an iterative method and executed through MATLAB using practical data from the industry. Suggestions for suitable energy storage devices to store renewable energy beyond the breakeven point, based on a techno-economic analysis of energy storage technologies, are made. Further, the battery energy storage system is designed and the capacity is estimated based on the practical solar irradiance data. A rule-based algorithm is developed to control the charge and discharge cycles of battery storage based on predefined conditions. The payback period is estimated based on the expected monetary benefits of proposed energy storage and the economy of the proposed system is ensured. The post-operational issues are resolved by introducing energy storage. The methodology presented in this paper can be a guiding tool for optimization of various renewable-energy-integrated cogeneration systems. [ABSTRACT FROM AUTHOR]

This paper investigates the role of nuclear energy in promoting ecological sustainability in India, focusing on three ecological indicators: ecological footprint (EF), CO2 emissions (CO2), and load capacity factor (LF). In addition to nuclear energy, the study considers the influence of gas consumption and other drivers of ecological sustainability using data spanning from 1970 to 2018. The analysis also takes into account the impact of the 2008 global financial crisis on the model, employing the autoregressive distributed lag (ARDL) and frequency domain causality approaches to assess the relationships. Unlike previous studies, this research evaluates both the Environmental Kuznets Curve (EKC) and load capacity curve (LCC) hypotheses. The ARDL results support the validity of both the EKC and LCC hypotheses in the Indian context. Furthermore, the findings reveal that nuclear energy and human capital contribute positively to ecological quality, while gas consumption and economic growth have a negative impact on ecological sustainability. The study also highlights the increasing effect of the 2008 global financial crisis on ecological sustainability. Additionally, the causality analysis demonstrates that nuclear energy, human capital, gas consumption, and economic growth can serve as predictors of long-term ecological sustainability in India. Based on these findings, the research presents policy recommendations that can guide efforts towards achieving SDGs 7 and 13. [ABSTRACT FROM AUTHOR]

Groundwater depletion in India is a result of water, energy, and food policies that have given rise to a nexus where growth in agriculture has been supported by unsustainable trends in water and energy use. This nexus emanates from India's policy of providing affordable calories to its large population. This requires that input prices are kept low, leading to perverse incentives that encourage groundwater overexploitation. The paper argues that solutions to India's groundwater problems need to be embedded within the current context of its water‐energy‐food nexus. Examples are provided of changes underway in some water‐energy‐food policies that may halt further groundwater depletion. [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]

Using plant-level data for 2008-2017, we examine the impact of the adoption of ISO 14000 by Indian manufacturing plants on their energy intensity. The propensity-score-matching difference-in-difference (PSM-DID) estimator is used to assess the effect. Our results show that the adoption of ISO 14000 tends to reduce energy intensity in Indian manufacturing plants, especially among the low and low-medium technology industries. ISO 14000 lowers energy intensity in industrial plants in energy-intensive industries, and the effect is stronger for the group of such industries covered under the Perform–Achieve–Trade (PAT) scheme of the Indian government, a market-based compliance mechanism for energy efficiency improvement. [ABSTRACT FROM AUTHOR]

The emergence of Electric Vehicles (EVs) is a turning point in decarbonizing the road transport sector. In spite of the various apprehensions of the customers, such as range anxiety, long charging times, higher costs, and the lack of charging infrastructures, EVs have managed to considerably penetrate into the market. Appreciable subsidies in EV purchase and possibilities of renewable energy-based local charging equipment have encouraged more and more people to own EVs. Electrifying road transport also calls for scaling up of all stages of the supply chain as it involves a lot of raw materials and critical metals used for battery technology. One of the most important factors determining the range of an EV is the energy density of the battery, which has reached over 300 Wh/kg, from 100-150 Wh/kg a decade ago. This clearly means that the same vehicle can travel double the distance with the same mass. Understanding and modeling the energy consumption in an EV is quintessential in alleviating the fear of range anxiety. This paper presents a detailed mathematical equation-based energy consumption analysis of a particular EV model for Indian roads. Very few researchers have worked on drive cycles suitable for India. The novelty of the current work is that the energy consumption calculation can be worked out for any EV model or vehicle type through simple mathematical equations. [ABSTRACT FROM AUTHOR]

The massive growth in power demand and the sharp decay in the availability of conventional energy sources forces society to move toward renewable power consumption. The rise in renewable energy utilization is one of the greatest strategies involved in making the environment clean, green, and emission-free. The investment cost is slightly high for this kind of resource, but their running costsare very minimal, which encourages power producers to invest in renewable power plants. Power producers always focus on their economic profit and possible feasibilities before the investment in a new power plant setup. Wind, small hydro, and solar photovoltaics have been considered the foremost efficient and feasible renewable sources. In 2021, the worldwide renewable power capacity had grown to 17%, despite supply chain disturbances and surges in prices. The renewable power market set a target of achieving a 95% increment in global power capacity by 2026. Hence, humankind should consider wind, hydro, and solar photovoltaics as the main energy sources, and there is a need to increase use of such sources. This paper highlights the latest developments, enormous technologies, and upcoming aspects of wind power, hydropower, and solar photovoltaics in India, as well as around the globe. The present status of renewable energy can motivate global power producers to spend their money on the installation of a new renewable power plant to obtain more economic benefits and give societal economic and environmental payback to humans. [ABSTRACT FROM AUTHOR]

Environmental sustainability encompasses various problems, including clean air, renewable energy, climate change, safe environments, and the capacity to live in a healthy community. One possible strategy for addressing these global problems is the circular bio-economy. Cleaner and lower-carbon environments may be fostered via the production of bioenergy and biomaterials, which can also help to maintain the energy-environment connection. To improve sustainability and the state of the planet, scientists are looking at renewable energy sources like ethanol. Compared to gasoline, ethanol has a reduced carbon footprint and a greater energy density, making it a viable alternative fuel. This study gives an overview of ethanol as a possible alternative fuel for flex-powered power generators in India to meet the goals of the circular bio-economy. This paper details the results of flex-fuel testing conducted on a light-duty power generator using an ethanol-gasoline mix. The findings reveal improved thermal efficiency and lower fuel consumption rates than basic fuel. The emissions of both carbon monoxide and unburned hydrocarbons were shown to be reduced. [ABSTRACT FROM AUTHOR]

As the exhaust rate of the conventional sources has geared up already, this is compelling the power industries to install the power plants based on the non-conventional sources so that future demand of the energy supply can be fulfilled. Among the various sources of renewable energy like wind, hydro, tidal etc., solar energy is the most easily accessible and available renewable energy source. Ensuring the feasibility of any energy source not only technical but also the economical perspective is the most important criteria. This paper has incorporated both the perspective and has done the techno-economic analysis to determine the optimum combination of the PV array size and battery size to minimize the overall electricity generation per unit. In this paper, a standalone solar PV system has been analyzed for the location of Jamshedpur, where an effort has been done to choose the optimum combination of the solar array and battery size within the desired range of LLP so that the electricity generation cost per unit can be minimized. The overall duration of the analysis has been done for a year and the outcome of the research has been verified with the help of MATLAB software. [ABSTRACT FROM AUTHOR]

The long-term electricity demand forecast of the consumer utilization is essential for the energy provider to analyze the future demand and for the accurate management of demand response. Forecasting the consumer electricity demand with efficient and accurate strategies will help the energy provider to optimally plan generation points, such as solar and wind, and produce energy accordingly to reduce the rate of depletion. Various demand forecasting models have been developed and implemented in the literature. However, an efficient and accurate forecasting model is required to study the daily consumption of the consumers from their historical data and forecast the necessary energy demand from the consumer's side. The proposed recurrent neural network gradient boosting regression tree (RNN-GBRT) forecasting technique allows one to reduce the demand for electricity by studying the daily usage pattern of consumers, which would significantly help to cope with the accurate evaluation. The efficiency of the proposed forecasting model is compared with various conventional models. In addition, by the utilization of power consumption data, power theft detection in the distribution line is monitored to avoid financial losses by the utility provider. This paper also deals with the consumer's energy analysis, useful in tracking the data consistency to detect any kind of abnormal and sudden change in the meter reading, thereby distinguishing the tampering of meters and power theft. Indeed, power theft is an important issue to be addressed particularly in developing and economically lagging countries, such as India. The results obtained by the proposed methodology have been analyzed and discussed to validate their efficacy. [ABSTRACT FROM AUTHOR]

In the present paper, spatio-temporal variability in surface radiative energy fluxes has been estimated for snow/ice-covered Beas River basin, lower Western Himalaya, India using remote sensing technology and evaluated with wireless sensor network (WSN) collected data at various elevation levels. Surface energy fluxes are derived using Landsat-8 satellite images and digital elevation model (DEM) at fine spatial resolution (~30-m) during clear-sky days of the year 2016–2017. RMSE have been estimated in incoming shortwave, incoming longwave, outgoing longwave, net shortwave and net radiation flux and observed to be ~5%, ~ 6.3%, ~2.4%, ~18.9%, and ~28.3% of the respective mean values. Landsat-8 images in conjunction with DEM have shown the potential to retrieve variability in surface radiative energy fluxes at fine resolution in mountain terrain. Additionally, temporal variability in radiative radiation fluxes have also been explored on different elevation ranges and aspects slopes. The high energy fluxes have been estimated on southern slopes during analysis as compared to northern slopes in the present study. The paper appears to be the first for reporting net radiation flux for Himalayan snow cover at 30-m spatial resolution. The satellite-derived energy fluxes may be valuable in various applications associated with climatology, hydrology, wet-snow avalanche detection, land use land cover, mass balance, ecology, etc., especially in the absence of in situ data. [ABSTRACT FROM AUTHOR]

[Display omitted] • Maize production due to its many climate friendly properties have been center of research and development in terms of yield, water per hectare requirement, and so forth. • Out of agricultural stubble waste, corncob showed highest potential for beneficiation amongst traditional cash crops. Corncob beneficiation products and their applications span from bio fuels to mattress, with over 3500 products. • With processes such as gasification, pyrolysis, combustion and so forth, we can use this agricultural waste product for energy generation. • With applications such as bio-oil, ethanol blending, poultry feed, bio char, methanol, and so on maize was found to be the answer to many global problems. Increased global energy consumption and energy generation constraints using non-renewable energy sources have stressed countries and major industries to practice and develop cleaner, sustainable, readily available and predictable source of energy. On the other hand, agricultural waste or stubble burning presents a major problem for developing countries like India as it alone produces 516 million tons of agricultural waste in the year 2017-2018, out of which 116 million tons waste was burnt producing 176.1 Mt Carbon dioxide, 10 Mt of Carbon monoxide, and other harmful greenhouse gases. Though 13% of India's total energy is produced by the biomass, a lot of scope and potential in waste biomass is still left unexplored. Research and development in biomass (agricultural waste) conversion to energy is the potential solution to both problems. Out of all agricultural waste biomass, corncob was the center of research for this review paper. This review paper covers global and Indian scenario in the generation of corn cob, its beneficiation and uses in multiple industries, characteristics of corn cob, technologies available and used for the biomass conversion, limitations faced by the industry in corn cob's beneficiation, future potential developments, pledged goals and projected targets. [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]

Indus Valley Civilization flourished in India and Pakistan owing to its technological advancements dating back to the 3rd millennium BC. The present paper aims to trace the emergence of pyrotechnology through documenting the industrial settlements that have been excavated in recent years, as well as locating the potential trading network for the craft items being produced at these small settlements on the outskirts of major Harappan cities such as Harappa, Mohenjo-daro and others. The paper focuses on the excavated Harappan sites with special reference to the site of Binjor - 4MSR in India's Ghaggar riverbed region. The reconstruction of kilns and furnaces based on the excavated remains was considered through the experimental study, such as wheel motion and the quantification of fuel consumption in the production of pottery, including terracotta figurines, bead and metal objects. During the research, the author has documented more than 50 furnaces, attempting to find parallels between Harappan heat treatment and modern potters and smiths located on ancient mounds. The ethnographic similarities between Harappans and the contemporary villagers who continue to inhabit the archaeological mound have been emphasised. The research also examines whether the technology utilised by the Harappans has changed or not, ranging from pottery manufacture to metal smelting, and what can be deduced from these experimental approaches to comprehend the technological prowess of their artisans. [ABSTRACT FROM AUTHOR]

In rural areas with higher agricultural energy consumption, ensuring low-carbon transformation and rapid penetration is crucial; therefore, the importance of rural energy system in energy transformation is even more prominent. In order to better understand the research progress of rural integrated energy system, the existing structure of rural energy system and design method are briefly introduced, and the bibliometric method is applied to analyze publications from 2013 to 2023. Based on the Scopus database, 915 publications have been retrieved. These publications are analyzed from the perspective of citation, author, address, and published journal. It is concluded that existing researches mostly use conventional energy technologies to achieve power supply in rural areas, lacking analysis of the potential application of emerging energy technologies and research on multi-energy demand. Furthermore, the review reveals the economy of grid-connected rural energy system is mainly related to geographical location, system configuration, and resource endowment. The bibliometric analysis indicated that these publications are mainly from India and China; the average citation is 24.98, and each article is co-published by 3.66 authors, 2.26 institutes, and 1.46 countries. This work is helpful for scholars to understand the research status on the rural integrated energy system. [ABSTRACT FROM AUTHOR]

This paper intends to know the impact of information and communication technology (ICT) on the economic progress and renewable energy consumptions in two Asian economic giants namely India and China. To achieve the objectives, generalised method of moments (GMM) and pooled ordinary least square (OLS), fixed effect and random effect models have been applied using yearly panel data of individuals using internet as ICT, growth rate of gross domestic product (GDP) as economic progress, electric power consumption as energy consumptions and foreign direct investment (FDI). This study observes significantly positive impact of ICT on renewable energy consumptions while negative and insignificant impact on the economic progress in India and China. It is observed that countries are similar in renewable energy expansion, time spent on internet, electricity generation and policy support for renewable energy generation while they significantly differ in the number of internet subscribers, internet-based entrepreneurships and sources of renewable energy. This study proposes to apply ICT in all possible sectors to boost-up economic growth as well as to enhance the demand for renewable energy consumptions. [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]

India is severely affected by the COVID-19 pandemic and is facing an unprecedented public health emergency. While the country's immediate measures focus on combating the coronavirus spread, it is important to investigate the impacts of the current crisis on India's renewable energy transition and air quality. India's economic slowdown is mainly compounded by the collapse of global oil prices and the erosion of global energy demand. A clean energy transition is a key step in enabling the integration of energy and climate. Millions in India are affected owing to fossil fuel pollution and the increasing climate heating that has led to inconceivable health impacts. This paper attempts to study the impact of COVID-19 on India's climate and renewable energy transitions through machine learning algorithms. India is observing a massive collapse in energy demand during the lockdown as its coal generation is suffering the worst part of the ongoing pandemic. During this current COVID-19 crisis, the renewable energy sector benefits from its competitive cost and the Indian government's must-run status to run generators based on renewable energy sources. In contrast to fossil fuel-based power plants, renewable energy sources are not exposed to the same supply chain disruptions in this current pandemic situation. India has the definite potential to surprise the global community and contribute to cost-effective decarbonization. Moreover, the country has a good chance of building more flexibility into the renewable energy sector to avoid an unstable future. [ABSTRACT FROM AUTHOR]

While the association between income inequality and environmental degradation has been researched extensively by various scholars, the impact of income inequality on the consumption of renewable energy, however, remains unanswered in the existing literature, the reason why the investigation of the same has been attempted through this study. Apart from income inequality, this paper also explores the impact of per capita income, consumption of nonrenewable energy and human capital development on the consumption of renewable energy, using a Nonlinear Auto-Regressive Distributed Lag (NARDL) model on the data pertaining to India for the period 1980–2016. This study concludes that while the increased income inequality results into reduction in the renewable energy consumption, the increased per capita income and human capital development, on the contrary, lead to an increase in the renewable energy consumption. Similarly, the impact of decrease in per capita income on renewable energy consumption was found to be negative and significant. Lastly, the nonrenewable energy consumption, showing the characteristics of a substitute, was found to have an inverse & significant relationship with renewable energy consumption in both upward as well as downward direction. [ABSTRACT FROM AUTHOR]

By 2040, India hopes to have completed its energy supply to fulfill the country's rising energy demands. Renewable and conventional sources must be used in an environmentally acceptable manner to achieve sustainable growth. India must enhance its use of renewable and clean energy sources, including geothermal, wind, and solar, to satisfy its growing demand. While solar and wind energy output has increased significantly, geothermal energy has yet to be fully harnessed. Among the many forms of geothermal energy found on the surface are volcanoes, fumaroles, erupting geysers, steaming fields, and hot springs. A total of about 340 geothermal springs may be found in India, spread throughout both orogenic (in the Himalayas) and non-orogenic (in the Peninsula). There were 31 places extensively evaluated, and deep drilling was performed in sixteen of them. Average temperatures range from 35.0°C to the boiling point of water in these springs. Medium (100.0–200.0°C) and low (100°C) enthalpy geothermal energy resources/systems are found in India, with the latter being the most abundant. The essential component of a geothermal system is understanding the heat source and harnessing it. Studies so far have indicated that some geothermal areas have sufficient geothermal potential for direct heat usage and power generation. If the Puga (J&K) field is explored to a depth of at least 500 m, reservoir simulation studies have shown that it might produce more than 3 MW of power. India's diverse geothermal sites and the current status of exploration for future research are discussed in the paper. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have emerged as a fast-growing industry not only in India but all over the world due to their environment friendly and economic properties. Moreover, it is being seen as a future replacement for fast depleting fossil fuels. But still, the international vehicle market cannot accept EVs as a ubiquitous vehicle manufacturing standard due to their short cruising range and underdeveloped charging infrastructure. Therefore, as an immediate and cost-effective solution to a problem subject to limited battery capacity, the EV route regularization, i.e., optimum energy usage route selection becomes utmost important. To accomplish this objective, this paper proposes a meta-heuristic routing model based on the principles of Artificial Bee Colony (ABC). The proposed model has been designed to consider prominent energy consumption influencing parameters like speed, battery health, road elevation, etc. Moreover, tractive effort modeling on different road surfaces like dry, wet, snow, and icy is also embedded in the design of EV route modeling. The simulation of the proposed model has been done to quantify its performance bys utilizing route maps as well as real-time information of vehicles' location by the Warrigal project as input. The analysis of obtained results has revealed the traces of saving in EVs' energy consumption of about 7.1% in comparison with Google maps if the route suggested by the proposed model is followed. [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 rising price and demand for energy are significant issues for the food sector, which consumes a substantial amount of energy throughout the supply chain. Hence, improving energy efficiency has become an essential priority for the food sector. However, most food businesses have limited awareness of the recent technological advancements in real‐time energy monitoring. Thus, the concept of "Internet of Things" (IoT) has been investigated to increase the visibility, transparency, and awareness of various energy usage levels. This paper presents a case study of a beverage factory where the implementation of an IoT‐enabled sensing technology based on the embodied product energy (EPE) model helped to reduce the energy consumption. This arrangement made provision for the collection of real‐time energy data within a food production system to support informed and energy‐aware operational decisions, which lead to optimized energy consumption and significant savings of approximately 163,000 kWh in the year 2017. Practical applications: Given the importance of energy efficiency and Internet of Things (IoT), especially in the food manufacturing industry, this research reports a baseline application at a beverage company in India. The results allowed the company to use energy more efficiently to have an advantage over its competitors and better market positioning. More data could be incorporated into the energy management system with the use of IoT. The availability and accuracy of such valuable data would help managers to make better energy‐efficient decisions. [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]

India, being a developing country with a fast-growing economy, experiences ever increasing electrical energy demand. Industrial and economic development in rural India is impeded by inadequate, erratic and unreliable grid supply. This has resulted in underperformance of smallscale manufacturing and service industries. Dependency on fossil fuel-based sources as an alternative increases the operation costs and carbon emissions. Migration to cleaner energy ensures sustainable solution and addresses the issues of depleting fossil fuels, global warming and environmental hazards. In this regard, hybrid renewable energy systems have gained wide acceptance as optimum solution. Hence, authors have optimally designed hybrid energy system for power deprived rural Indian villages. Authors have heeded to the vital element of incremental load growth over years while designing the microgrid to sustain the increasing load demand of emerging economy of developing country. HOMER Pro Software is utilized to accomplish system size optimization and authors have gained comprehensive insights into techno-financial feasibility for different dispatch strategies of the proposed energy system. The levelized cost of electricity of the optimal off-grid system catering to multiyear incremental load growth is 0.14$/kWh indicating that proposed system is promising in terms of commercial efficacy. The study performs a detailed analysis of the results obtained during different phases of the project to ensure robustness and supply continuity of the proposed system. The paper also includes comparison of the carbon footprint in the proposed system with that of existing system. [ABSTRACT FROM AUTHOR]

Sugarcane is one of the most important cash crops in India. India being a major consumer of sugar occupies the second place in sugarcane production, next to Brazil. In recent times, sugarcane has become a preferred crop for renewable and eco-friendly energy production. Excepted rise in demand for energy has improved the scope of sugarcane production. In this backdrop, the study focuses on the trend and growth of production area, production and productivity of sugarcane crop in India for the period 2001-02 to 2017-18. The relationship between harvested area and production is tested with the help of a regression model. Apart from that, the study analyzes the state wise growth rate of sugarcane sector. The study is based on secondary data collected from various government reports and publications. The result highlights that all the three variables under consideration witness positive growth rate. About 65% of the production comes from two states, Uttar Pradesh and Maharashtra. Comparatively states falling under tropical region have higher yield per hectare than states of sub-tropical region. Finally, to an extent, this paper suggests ways to improve sugarcane productivity. [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]

This paper aims to investigate the interactions between CO2 emissions, economic growth and energy consumption in India for 1970– 2017 within the time–frequency domain using wavelet techniques. The results show that the interaction between energy consumption and CO2 emissions is strong and varies significantly across time– frequency bands, indicating that the energy consumption leads to environmental degradation. The negative effect of economic growth on CO2 emissions is only statistically significant in the short run. In addition, the findings reveal a positive association between economic growth and energy consumption across time– frequency bands, demonstrating energy consumption increases economic growth, which in turn heightens the CO2 emissions. There should be improved energy use and reduced CO2 emissions. [ABSTRACT FROM AUTHOR]