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The present paper utilizes entropy theory and Google earth engine cloud computing technique to investigate system state and river recovery potential in two large sub-basins of the Mahanadi River, India. The cross-sectional intensity entropy (CIE) is computed for the post-monsoon season (October–March) along the selected reaches. Further, a normalized river recovery indicator (NRRI) is formulated to assess the temporal changes in river health. Finally, NRRI is related to a process-based variable-LFE (low flow exceedance) to comprehend the dominating system dynamics and evolutionary adjustments. The results highlight the existence of both threshold-modulated and filter-dominated systems based on CIE and NRRI variabilities. In addition, the gradual decline in CIE and subsequent stabilization of vegetated landforms can develop an 'event-driven' state, where floods exceeding the low-flow channel possess a direct impact on the river recovery trajectory. Finally, this study emphasizes the presence of instream vegetation as an additional degree of freedom, which further controls the hierarchy of energy dissipation and morphological continuum in the macrochannel settings. [ABSTRACT FROM AUTHOR]

The most significant development activity on the Teesta River in India is the construction of a series of cascade dams for hydropower generation in the state of Sikkim, India. Approximately 30 major hydropower projects have been planned on the Teesta River, with a planned capacity of over 5000 MW of electricity. This paper discusses hydraulic model studies conducted at Central Water and Power Research Station, Pune, India, for Teesta-IV Project in Sikkim which played an important role in enhancing the overall performance of spillway and energy dissipator by incorporating various modifications such as providing curved dam axis, tilting the dam axis anti-clockwise by about 3°, modification of breast wall profile, etc. The details of model studies conducted for improving the overall performance of spillway and energy dissipator are described in the paper. [ABSTRACT FROM AUTHOR]

The probable availability of renewable power sources is unexceptionable, and the government of India is setting high goals for the use of renewable energy. Renewable distributed generation (DG) reduces the need for fossil fuels, relieve environment change, and decrease radiations of CO2 and other perfluorocarbons. DGs and capacitors are more desirable choices to balance power demand closer to the load centres than centralized power generation. Optimal position and capacity of DGs play an essential role in enhancing the performance of distribution systems in terms of system loss mitigation, voltage profile enhancement and stability concerns. This paper introduces Harris Hawk Optimization (HHO) and Teaching Learning-Based Optimization (TLBO) approaches for efficient distribution of different types of DGs in the radial distribution system (RDS) to enhance system loss minimization, voltage profile, yearly energy savings and decreasing the greenhouse gas emissions. The aim is to depreciate system energy losses, cost of energy losses and more reliable voltage regulation within the frame-work of RDS planning. Four different cases are considered to assess the suggested algorithms. Simulations are carried out on IEEE 33-bus and 69-bus test RDSs. The preponderance of the recommended approaches has been shown by analysing the results with techniques available in the literature. The comparison is made based on the power losses and voltage profile of RDS. The outcomes reveal that a significant decrease in power loss, enrichment of the voltage profile across the network and exactness of the suggested methods. [ABSTRACT FROM AUTHOR]

Motivated by the growing significance of solar energy, the paper presents the findings of the maiden study on the long-term seasonal performance assessment of three PV module technologies—monocrystalline (m-Si), polycrystalline (p-Si), and amorphous silicon (a-Si) housed in a 1 MW solar plant installed at a local steppe climate in Gandhinagar, Gujarat, India using the key performance indicators (KPIs), daily power generation, final yield (Y f), reference yield (Y r), total energy loss (T EL) and performance ratio (PR). Notably, the am-Si PV modules were found to be the best performing technology, with an average PR of 71.26% and the lowest average total energy loss of 631 h during the monitored period. Moreover, PV systems have become more popular as a source of green, clean energy; yet, they have low base-load energy sustainability. Explainable AI (XAI) aids in understanding predictions made by the machine learning models. The importance of XAI lies in the comprehension and trust which is embedded into the results of machine learning algorithms. Therefore, the present work builds a comprehensive XAI model for predicting KPIs and assesses the performance of several learning algorithms using R-value, MAE, the number of iterations, and execution time. The Levenberg-Marquardt algorithm predicts the KPIs for p-Si, am-Si, and m-Si with prediction accuracies of 98.63%, 98.58%, and 90.09%, respectively. In summary, this study not only advances our understanding of PV module performance in a steppe climate context but also contributes to the broader field by integrating an XAI model for transparent and reliable predictions of the KPIs. [Display omitted] • Comparison of m-Si, p-Si, and a-Si PV modules in a 1 MW solar plant, Gandhinagar, India, showed long-term performance. • a-Si PV modules outperformed with a 71.26% PR and the lowest 631 hours energy loss, surpassing m-Si and p-Si technologies. • Study underscores XAI's role in ML predictions, developing a robust model to predict KPIs and evaluate learning algorithms. • Levenberg-Marquardt showed high accuracy: 98.63% for p-Si, 98.58% for a-Si, and 90.09% for m-Si PV modules. [ABSTRACT FROM AUTHOR]

Abstract: Attractive economic performance of energy systems is important for their long term sustainability. In this paper, a cost benefit analysis (CBA), standard thermoeconomic analysis, and a new method that combines the two was applied to seven modelled candidate decentralised energy systems for small Indian rural villages. By including elements of CBA in standard thermoeconomics, economic inefficiencies at the component level and revenue adjusted costs of exergy for each stream were ascertained. The analysed systems all produced household and irrigation electricity as well as a secondary product or service, which in some cases utilised waste heat from the electricity generation process. The system that produced distilled water as a secondary product was the most economically sustainable out of those modelled. While the standard thermoeconomic electricity cost remained around 0.5 USD/kWh for all analysed systems, the benefit to cost ratios varied from 0.29 to 0.97, demonstrating differing appeal to outside investment. By incorporating CBA into standard thermoeconomics the accounted revenue produced a larger spread in exergetic costs than standard thermoeconomics (for example, an electricity cost range of 0.217–0.507 USD/kWh), thus providing a better comparison of systems with different energy end uses. [Copyright &y& Elsevier]

The transition towards a modern cleaner energy pathway has been receiving global attention recently. Although nuclear energy has emerged as an alternative cleaner energy source and is receiving immense policy attention, however, the role of nuclear energy in the environmental degradation mitigation remains inconclusive in the extant literature. Therefore, this study examines the dynamic linkages between gross domestic product, foreign direct investment inflows, nuclear energy consumption, trade openness, and CO2 emissions for India within the environmental Kuznets curve framework over the period 1978–2019 through various robust econometric models that takes into consideration the presence of structural break in the data. The present study confirms the existence of an "inverted N shape" environmental Kuznets curve, a phenomenon rarely observed in environmental Kuznets curve literature for India. Besides, the predicted turnaround points of environmental Kuznets curve highlight that India has already reached the positive peak approximately by the year 2015. The empirical findings also confirm the existence of a J-shaped relationship between foreign direct investment inflows and CO2 emissions, which indicates that India is in the transient phase moving from pollution halo towards pollution heaven with progressive foreign direct investment development. Trade openness is also found to have a beneficial effect on environmental quality implying the trade policy of India encourages green trade activities to safeguard the environment. The empirical results also reveal the beneficial effect of nuclear energy consumption on air quality, thereby suggesting an accelerated adoption of nuclear energy in the Indian energy mix. The results also highlight that nuclear energy adoption in this booming phase can facilitate a "tunnelling effect" for sustainable economic growth for India. Hence, these findings may provide key policy recommendations regarding energy transition and environmentally sustainable economic growth. [ABSTRACT FROM AUTHOR]

Purpose: Due to large amounts of coal burning, huge carbon dioxide emission and poor environmental quality, it is important to identify whether environmental Kuznets curve exists in China and India since in downward period of environmental Kuznets curve, economic growth in these countries will largely contribute to world environmental quality. Further, it helps to make a comparative analysis between China and India on how economic growth will contribute to the environmental quality in both upward and downward period of environmental Kuznets curve due to energy consumption. Design/methodology/approach: This study uses the data of carbon dioxide emission, per capita GDP and energy consumption from 1972 to 2017 to identify individual and panel-level environmental Kuznets curve of China and India. Before going to regression and causality analysis, unit root and cointegration tests are performed. Findings: This study finds the existence of environmental Kuznets curve in China and India at both individual and panel level. Further, due to high energy consumption, environmental quality in China will deteriorate at a lower rate in the long run than that of India. Next, the increase in economic growth or per capita GDP in the long run will deteriorate environmental quality at a lower rate in China than that of India. Besides, with the zero level of energy consumption and per capita GDP, the environmental quality of China will be worse than that of India. However, increase in per capita GDP after threshold level will improve environmental quality in India at a higher rate than that of China. Research limitations/implications: It helps to formalize the comparative relationship between the two large Asian economies by knowing the influence of economic growth on environmental degradation due to energy consumption. However, this study cannot conclude exactly when China and India can avail the downturn in environmental Kuznets curve. Originality/value: It firstly establishes a link among energy consumption, economic growth and environmental quality between China and India including comparative pace in both upward and downward period of environmental Kuznets curve. [ABSTRACT FROM AUTHOR]

This study provides experimental validation of a previously published optimal design theory for photovoltaic (PV)-powered electrodialysis reversal (EDR) desalination systems. The prior work describes the co-optimization of PV and EDR subsystems, and flexible operation to accommodate daily and annual solar irradiance variability, significantly reducing water cost. This study presents the fabrication of a PV-EDR pilot system designed using the co-optimization theory and field testing results from the rural village of Chelluru, India. Testing in the field enabled observation and evaluation of real-world factors on system performance, resulting in updates to the previous theory to include unaccounted factors that affect costs, including: filling and draining of water tanks, salt and water accumulation in tanks from prior batches, unexpected energy losses due to locally purchased converters, and scaling in the ED stack. Therefore, water cost in the PV-EDR pilot system was updated from previous estimates based on field performance. The estimated capital cost and lifetime cost of the Chelluru system are 34% and 45% lower, respectively, than the corresponding costs if the PV-EDR system was designed using conventional design practice. The theory and experimental insights presented in this paper will enable desalination engineers to better design and optimize PV-EDR systems. • This study validated previous published optimal design theory of PV-EDR systems. • A pilot-scale co-optimized PV-EDR system was built and tested in rural India. • Testing in the field enabled accounting real-world factors in future PV-EDR design. • 34% and 45% reductions of LCOW and capital cost are achieved by the pilot system. [ABSTRACT FROM AUTHOR]

The rate of degradation of kresoxim methyl and its effect on soil extra-cellular (acid phosphatase, alkaline phosphatase and β-glucosidase) and intra-cellular (dehydrogenase) enzymes were explored in four different soils of India. In all the tested soils, the degradation rate was faster at the beginning, which slowed down with time indicating a non-linear pattern of degradation. Rate of degradation in black soil was fastest followed by saline, brown and red soils, respectively and followed 1st or 1st + 1st order kinetics with half-life ranging between 1–6 days for natural soil and 1–19 days for sterile soils. The rate of degradation in natural against sterilized soils suggests that microbial degradation might be the major pathway of residue dissipation. Although small changes in enzyme activities were observed, kresoxim methyl did not have any significant deleterious effect on the enzymatic activity of the various test soils in long run. Simple correlation studies between degradation percentage and individual enzyme activities did not establish any significant relationships. The pattern and change of enzyme activity was primarily due to the effect of the incubation period rather than the effect of kresoxim methyl itself. [ABSTRACT FROM AUTHOR]

In this study, energy and exergy analysis of a coal fired steam power plant in India was carried out and the effects of varying the reference ambient temperature, stack gas temperature and the percentage of excess combustion air on this analysis were examined through computer simulation. The combustion process in the boiler was analyzed in detail considering the actual composition and condition of atmospheric air and variation of specific heat of gases with temperature. Maximum energy loss was found in the condenser (62.02%) followed by the boiler (13.03%) while maximum destruction of fuel exergy was found in the boiler system (63.02%) followed by the turbine (9.35%), and then the condenser (3.24%). Significant potential to improve plant efficiency, therefore, exists through reducing irreversibility in the boiler system. The ambient temperature was found to have its highest effect on the changes of the irreversibility rate in the boiler as compared to that in other components. To examine the effects of stack gas temperature and the excess combustion air on the irreversibility rate of the boiler system, the stack gas temperature was varied from the existing 134.3°C to 90°C and the excess air percentage was varied from 25% to 5%. The results showed that decreasing either the percentage of excess combustion air or the exhaust gas temperature or both, causes the irreversibility rate in the boiler to decrease. [ABSTRACT FROM PUBLISHER]

An efficiency loss such as heat loss across bare pipe surfaces reduces the available energy to end-uses and increases the burden on boilers to meet the demand. Energy losses create additional stress on the system that accelerates wear and leads to overloading on the system for which it is not originally designed. In the present study, calculations for heat loss and cost of different insulating materials for varied thicknesses were performed for typical location in Jammu and Kashmir, India. The detailed analysis of the heat loss from bare steam pipes was performed with a view to suggest suitable type of insulation to lower the heat loss to acceptable limits, thereby reducing the cost of fuel. The present work provides the detailed study on the heat conduction analysis of steam pipes for different diameters. This analysis includes the heat loss from steam pipes and cost of insulation for different thicknesses of mineral wool, cement and lead, which can be used as the insulating material. The economics of each insulation type is studied, and the analysis indicates that there is an appreciable fuel saving in terms of thermal units. [ABSTRACT FROM PUBLISHER]

Dissipation of β-cyfluthrin and imidacloprid was studied following three applications of a combination formulation of Solomon 300 OD (β-cyfluthrin 9% + imidacloprid 21%) @ 60 and 120 g a.i. ha−1 at 7 days interval. Samples of brinjal were collected at 0, 1, 3, 5, 7, 10 and 15 days after the last application and residues of β-cyfluthrin and imidacloprid were estimated on gas liquid chromatography (GLC) and high performance liquid chromatography (HPLC), respectively. Half-life periods for β-cyfluthrin were found to be 1.74 and 1.39 days and for imidacloprid these values were observed to be 2.31 and 2.18 days, respectively, at single and double the application rate. β-Cyfluthrin residues dissipated below the limit of quantification (LOQ) of 0.01 mg kg−1 after 5 and 7 days, respectively, at single and double the application dosages whereas imidacloprid residues took 10 days for both the dosages. Soil samples collected after 15 days after the last application did not show the presence of β-cyfluthrin and imidacloprid at their detection limit of 0.01 mg kg−1. [ABSTRACT FROM AUTHOR]