Preliminary Study on Wave Energy Plants for the Leeward Islands of Cabo Verde

This study assesses the viability of establishing offshore wave energy plants around the Leeward Islands of Cabo Verde, aiming to diversify the country's energy mix and reduce reliance on fossil fuels. The research focuses on resizing three well-known wave energy converters (AquaBuoy, Wave Dragon, and Pelamis) to determine the scale factor (?) that maximizes their Capacity Factor (CF) in the region. Key performance indicators, including CF, Levelized Cost of Energy (LCOE), Cost-Benefit ratio (C/B), Total Investment Costs (TC), and Maritime Space Utilization Efficiency (?ut), were analyzed alongside environmental considerations to identify the most suitable technology for wave power plants. The Monte Carlo method was applied to account for uncertainties in technology costs and their effect on LCOE values. The results revealed that the optimal scale factors were ? = 0.3, 0.4, and 0.5, corresponding to the highest CF values for Wave Dragon (71.5%), AquaBuoy (56.8%), and Pelamis (25.6%), respectively. At full scale (? = 1), AquaBuoy emerged as the most suitable device, offering a CF of 18.8%, an LCOE of 210 $/MWh, and maritime space utilization efficiency (?ut) ranging from 3176.4 MWh/ha to 3563.7 MWh/ha, while occupying less offshore space. However, AquaBuoy also demonstrated the most significant environmental impact, particularly on marine species in the water column. Overall, the Wave Dragon outperformed Pelamis in all evaluation parameters. The study also highlighted that a reduction in interest rates from 12$/MWh, 597 $/MWh, and 600$/MWh, respectively. Notably, AquaBuoy's LCOE (210 $/MWh) is substantially lower than the current electricity cost in Cabo Verde (330$/MWh), underscoring its potential as a viable energy source for the country

Upgradation in Physio-Chemical Characteristics and Thermal Behaviour of Thar Coal Subjected to Torrefaction

This study explores the improvement in physiochemical attributes, thermal behavior, and combustion characteristics of low-rank Thar coal through torrefaction, a thermal pretreatment process. Thar coal samples were torrefied at five temperatures (200, 225, 250, 275, and 300°C) for two residence times (30 and 60 minutes). The study assessed changes in proximate and ultimate composition, calorific value, energy density and combustion traits of untreated and torrefied coal using thermogravimetric analysis (TGA). Results indicated slight improvement at low torrefaction temperatures (200-225°C), while higher temperatures (275-300°C) significantly enhanced fuel properties. Key findings include increased fixed carbon, reduced moisture and volatile matter, and higher heating value (HHV). The TGA graph demonstrated that torrefied coal has improved fuel properties compared to raw coal samples. The derivative thermogravimetric curve (DTG) shifted upward, signifying a change in peak (Tm) and decomposition temperatures along with an increased torrefaction temperature. The samples torrefied at 300°C for 60 minutes yielded best results, showing improved ignition (Ti) and burnout temperatures (Tb) and reduced emissions. This research focuses on torrefaction as a potential technique for improving the quality of low-grade coals of Pakistan hence opening up opportunities for controlled energy production

The Understanding of Willingness to Pay for Clean Drinking Water Through Extended Version of The Theory of Planned Behaviour

This study examines how extended version of Theory of Planned Behavior (TPB) affects households Willingness to pay (WTP) for getting access to clean drinking water. In order to validate how extended version of TPB and WTP are related, it also considers people's Environmental concerns (EC) as antecedent variables to core TPB factors. The Structural Equation Modeling (SEM) is employed to validate the hypotheses of the research after recruiting 401 participants. The result of current study showed that TPB factors play a significant role in effecting households’ intention to pay (IP), which subsequently influences their WTP. Additionally, the households’ environmental concerns, as antecedent variable play a significant effect on core TPB factors i.e. attitude (ATT), subjective norm (SN) and perceived behavior control (PBC). In turn, these core factors of TPB shape households' intention to pay, which subsequently influences their WTP for getting access to clean drinking water. It gives stakeholders a chance to observe how extended version of TPB and WTP interact with one another. To increase WTP for getting access to clean drinking water, raise awareness about environmental risks. Promoting the concern for environmental can improve attitudinal and behavioural aspect of an individual. These changes then result in enhancing intention to pay (IP). Aligning messages with people's environmental values helps build support for sustainable water access. The recent study also contributes to the literature in behavioural and attitudinal contexts by examining extended TPB constructs, and community responsibility in relation to getting access to clean drinking water services

Climate Change Impacts on the Indus River Basin: Hydrology, Water Quality, and Treaty Implications

The Indus River is highly sensitive to climate variability because most of its flow depends on Himalayan snow and glacier melt as well as monsoon rains. Climate change induces shifts in precipitation patterns, accelerating glacier retreat, and increasing the frequency of floods and droughts in the basin. The objective of this study was to analyze the quality of the Indus water and to assess the effects of climate on it, i.e. how changes in climate affect the hydrological cycle, glacier dynamics and water quality in the Indus basin.  Using field data from the Kunar and Kabul rivers (tributaries of the Indus) and a review of climate impacts, significant regional differences in water quality parameters were noted and climate-induced hazards (e.g. floods, droughts, salinity intrusion, ecosystem stress) outlined. The implications of these changes for water security, agriculture and Indo-Pak water governance were studied. It was noted that the Indus Waters Treaty currently lacks provisions for climate-induced variability. Climate change is altering the Indus hydrological regime and water quality, posing challenges to sustainable water management and regional stability

Toward a Green Transition: Unravelling the Impact of Innovation, Urban Dynamics, and Economic Expansion on CO? Emissions in BRICS

Environmental degradation from growing carbon dioxide (CO?) emissions now stands as a significant worldwide issue that impacts regions undergoing quick economic expansion. The BRICS nations, which include Brazil as well as Russia, India, China and South Africa, create 45% of global CO? emissions while generating 18% of world GDP, positioning them as key participants in climate discussions at the international level. A statistical analysis evaluates the permanent and temporary relationships between technological innovation and urbanization and economic growth on CO? emission levels among BRICS nations using World Development Indicators (WDI) annual data from 1990 to 2023. Results from PMG-ARDL modelling demonstrate that both technological innovation and consumption of renewable sources actively diminish CO? emission patterns during extended periods, although economic growth helps reduce emissions when certain limitations arise. The relationship between urbanization and the environment becomes difficult to predict since it worsens emissions and demonstrates the intricate relationship between progress and sustainability. According to these results, future sustainability demands immediate implementation of advanced sustainable technologies and proper urban expansion management strategies

Agricultural Footprint Dynamics: Capturing the Influence of Renewable Energy, Urbanization, and Ecological Resources

Agriculture, a cornerstone of economic prosperity, is both a contributor to and a recipient of climate change. This study investigates the factors driving the agricultural footprint, considering land use, water use, pollution, greenhouse gas emissions, energy use, renewable energy consumption, urbanization growth rate, and ecological footprint components (fishing grounds, grazing land). Using principal component analysis, the study calculated an agricultural footprint index, weighting these factors. The study further estimated the impact of renewable energy consumption, urbanization growth rate, and ecological footprint components on the agricultural footprint. The stability of the model was assessed using CUSUM and CUSUM of squares calculations. The findings reveal that while renewable energy consumption and urbanization growth rate exert pressure on the agricultural footprint, ecological footprint components like fishing grounds, grazing land, and cropland contribute positively. To enhance the agricultural footprint and mitigate its environmental impact, the study proposed a multi-pronged approach: financial incentives, educational programs, consumer awareness campaigns, and the development of regulations and standards for sustainable agricultural practices. By implementing these strategies, society can promote a more sustainable and resilient agricultural sector that contributes to both economic prosperity and environmental protection

Flood Susceptibility Assessment Using Frequency Ratio Model: A Case Study of District Ghotki and District Kashmore, Sindh, Pakistan

In recent years, flash floods in Ghotki and Kashmore districts in Pakistan have seriously affected both people and their ways of earning a living. Addressing challenges related to flooding means utilizing a methodology that considers both the hydrology, of water, the environment, the soil, the economy and social impacts. Flood susceptibility mapping helps inform how to control and plan floods. A bivariate probability analysis employing the frequency ratio (FR) methodology was conducted during this investigation to develop flood vulnerability assessments for Ghotki and Kashmore. A map was produced using the 130 past flood locations in the two districts. To establish the models, the data from these localities were randomly divided into 70% for model development and 30% for assessment. Among the parameters incorporated in the analysis were aspect, slope, elevation, rainfall, type of soil, use of land, proximity to roadways and rivers and NDVI and NDSI figures. How each factor affects flooding was assessed by checking its relationship with previous floods. From the analysis, scientists found that approximately 18% of the study area was classified as extremely flood susceptible, 30.9% as highly flood susceptible, 20.7% as moderately flood susceptible, 20.6% as minimal flood susceptibility and 9.8% as negligible flood susceptibility. Using the metrics from the validation set, the Foul Reader showed an accurate prediction rate of 75%. Moreover, the resulting susceptibility maps were compared to the real floods of 2010 and 2022, showing that the model reliably predicts flood-prone areas. As a result, the FR model is demonstrated to support the activities of governmental organizations, administrators and policy-makers in preventing and managing floods in the region

TRNSYS-Based Performance Study of Solar-Assisted Single-Effect Absorption Cooling in Peshawar, Pakistan

This study presents a detailed techno-economic and thermal performance evaluation of a solar-assisted absorption cooling system optimized for the climatic conditions of Peshawar, Pakistan. Through dynamic simulations conducted over the summer season (May to September), the performance of key subsystems, including the solar collector array, auxiliary heater, thermal storage, and absorption chiller, was analyzed. Simulation results demonstrate that the system successfully maintains the chilled water outlet temperature at 7°C, with consistent cooling water and hot water temperatures of 28°C and 95°C, respectively. The system exhibits steady-state flow rates of 650 kg/hr (cooling), confirming effective hydraulic control. Under variable load conditions, the auxiliary heater responded through frequent pulsed flow patterns, achieving peak flow rates up to 49,000 kg/hr without compromising outlet temperature. Parametric analysis revealed that the optimal tilt angle for solar collectors is approximately 15°, maximizing solar fraction (SF) for both flat plate collectors (FPC) and evacuated tube collectors (ETC). For ETCs, primary energy savings (PES) (fsav,shc) of 0.49 were achieved using 560 m² of collector area and 14.9 m³ of thermal storage. The ideal storage volume was found to be 25 L/m², beyond which auxiliary energy consumption increased. Seasonal simulations revealed strong diurnal variations in cooling demand, peaking around 1.6 MW, while heating loads remained negligible, reinforcing the cooling-dominated nature of the operational period. The system's average seasonal solar collector efficiency was calculated at 0.188 for FPCs and 0.52 for ETCs, underscoring the superior thermal performance of ETCs at higher driving temperatures (111°C). A minimum of 400 m² collector area was required to achieve 50% primary energy savings. These findings validate the hybrid solar-auxiliary configuration’s suitability for high-demand cooling applications in arid climates and offer design insights for optimizing collector area, storage volume, and control strategies. The results not only optimize system design for local climatic conditions but also underscore the broader potential of solar cooling technologies to mitigate urban heat, lower electricity demand, and enhance energy resilience in developing regions. These perceptions provide valuable guidance for renewable infrastructure planning and policy constitution across the same climatic regions

Economic Growth, Access to Clean Fuels & Technologies for Cooking, and Renewable Energy Consumption: Case of South Asian Economies

Economic growth—through growth affordability, growth investments, and growth-awareness associations—may lead to increased access to clean fuel and technologies for cooking (ACF&T). The current paper presents the trend and comparative analyses regarding GDP per capita, access to clean fuels and technologies for cooking, and renewable energy consumption (REC) in the South Asian economies. The data from Bangladesh, India, and Pakistan between 2000 and 2020 shows a strong positive correlation between GDP per capita and access to clean cooking technologies. India has made the most significant improvements, followed by Pakistan and Bangladesh. All three economies negatively correlate GDP per capita and renewable energy consumption. Bangladesh shows the steepest decline, followed by India and Pakistan, indicating a more pronounced shift towards nonrenewable energy sources as economic prosperity increases. The study concludes that economic development often involves transitioning from traditional renewable energy sources (such as biomass) to more modern, nonrenewable energy sources (such as fossil fuels), often more efficient and reliable for industrial and large-scale energy needs. Hence, developing infrastructure and industrial sectors might lead to higher consumption of nonrenewable energy sources. This points to a potential challenge for sustainable development, as increased economic prosperity might be accompanied by more significant environmental impact unless there are concerted efforts to promote renewable energy sources

Effect of Energy Utilization on Pakistan’s Economic Development: A Time Series Analysis

The present research has been conducted to study the causal relation among GDP, electricity utilization, exports, real capital and labor force for Pakistan. Time dependent data for the mentioned parameters have been used for the time period of 1980 to 2022. Inter-relations among the above-mentioned variables have been studied in this work by the method of cointegration using bounds test. The results illustrate that there is an existence of long run relation among the parameters where GDP has been taken into consideration as the dependent variable. Granger causation analysis has also been performed for the variables. Results show that Granger causality between GDP and electricity utilization runs in both directions. Moreover, the study discloses that Electricity utilization granger cause exports and per capita real capital. Exports granger cause per capita real capital. Per capita real capital granger cause GDP. Labor force granger cause GDP and exports. The long run relation equation of GDP, Electricity utilization, exports, real capital and labor force has also been examined for parameter stability. The parameters are found to be stable with the significance level of 5%. The research also suggests some significant strategy recommendations