The rapid expansion of data centers, driven by the proliferation of 5G and cloud technologies, has intensified environmental concerns, particularly related to water consumption and energy use. Data centers consume billions of liters of water daily for cooling, with wet cooling towers accounting for the majority of this usage. Despite various efforts, effective strategies to reduce water consumption in these systems remain limited. This study proposes the use of hygroscopic solutions as alternative cooling media in wet cooling towers to address this challenge. An experimental system was developed to evaluate this technology's performance. The results demonstrate a significant reduction in water consumption of up to 84.72% while maintaining comparable thermal performance to traditional systems. For data center operators, especially those in water-stressed regions, this technology offers a viable path to drastically lower operational water costs and reduce environmental impact, supporting compliance with increasingly stringent sustainability regulations. The water-saving mechanisms are further explored through an analysis of the interactions between the hygroscopic solution and moist air, utilizing physical properties and enthalpy-humidity charts. This research contributes to sustainable cooling strategies essential for adapting to water stress and environmental demands in an era of accelerating technological growth.

This article analyzes the evolution of public attitudes toward climate change in France. In the context of a challenging economic environment, the climate crisis continues to be a significant concern for the French populace, a concern that is exacerbated by the increasing frequency of climate-related disasters globally. Utilizing a logit model applied to four waves of a longitudinal survey conducted in 2000, 2010, 2019, and 2021, our findings indicate a noteworthy decline in climate skepticism. This reduction is correlated with an enhanced recognition of the scientific consensus on climate change and a broader adoption of environmentally responsible behaviors. Our analysis reveals significant associations between political orientation and climate skepticism: individuals who voted for far-right parties demonstrate a higher propensity for skepticism, whereas those who supported environmentalist parties exhibit a lower likelihood of skepticism. These findings highlight the critical need for ongoing efforts to communicate climate science effectively, promote pro-environmental behaviors, and acknowledge the pivotal role of political actors in mitigating climate skepticism.

Precipitation plays a critical role in the global water cycle, with its spatial distribution and variations significantly impacting both the environment and socio-economic systems, making it central to climate change research. This study investigates the spatiotemporal evolution of rainfall intensity and frequency in central Guizhou, China, using monthly data from 56 rain gauge stations (1965–2016). The analysis employs the Precipitation Anomaly Index (PAI) and P-III distribution to examine rainfall patterns across time scales of 3 to 12 months. Key findings include: (1) Rainfall intensity shows an "N-shaped" trend, with an increase from the 1960s to 1980s, followed by a decline and gradual recovery through the 2010s. The proportion of wet years peaked in the 1970s (47.55%), rising to 69.39% by the 2010s. (2) Rainfall frequency was highest during normal years (62.8%), with medium-frequency events becoming more dominant over time. (3) Significant differences in rainfall intensity were most pronounced at 9-month and 12-month scales, with rainfall frequency exhibiting significant variability across all time scales. This research highlights the multi-scale nature of rainfall patterns in central Guizhou, offering valuable insights for hydrological management and climate adaptation in karst regions.

Access to adequate cooling is essential for health, well-being, and livelihoods. However, in Malaysia, there remains a significant gap in understanding cooling access and thermal comfort, particularly among women home-based workers and women who spend the majority of their time at home. Despite global recognition of cooling disparities, limited research has focused on this demographic. Addressing this gap is vital for promoting gender equality and enhancing quality of life for women, especially in rural and lower-income settings. This study investigates thermal comfort and access to cooling in villages across five Malaysian states: Selangor, Melaka, Perak, Kedah, and Perlis, where village houses represent over 50% of occupied housing. Semi-structured interviews were conducted with women who either work from home or spend most of their time at home, assessing their thermal comfort, daily cooling needs, and household practices. Findings reveal that thermal discomfort peaks between 2 PM and 5 PM, and while most households have access to cooling systems, 66% of respondents reported high electricity bills as the main reason for not using air-conditioning. An additional 29% cited financial inability to afford the system, indicating that cost-related factors are the dominant barriers to cooling access. A chi-square goodness-of-fit test focusing on village house respondents revealed that heat due to house structure was the statistically significant cause of discomfort (χ² = 27.91 p < 0.001), suggesting structural issues such as poor insulation and solar heat gain as key contributors. To propose feasible solutions, TRNSYS simulations were conducted on a typical rural house model. Results showed that enhancing roof insulation was the most effective strategy, reducing cooling loads by approximately 10%, with an estimated load of 3.39 kWh. This study concludes that structural improvements, particularly roof insulation, are essential for reducing cooling needs and improving thermal comfort for women at home. Tackling both technical and financial barriers through affordable passive cooling strategies can significantly improve living conditions while enhancing women’s health, productivity, and economic participation, contributing to a more inclusive and sustainable future.

The urgent need for sustainable energy solutions has intensified research into biodiesel as a viable alternative to fossil fuels. With rising concerns over greenhouse gas emissions and energy security, biodiesel derived from renewable feedstocks presents a promising pathway toward low-carbon development. However, the selection of optimal feedstocks and efficient extraction techniques remains critical to enhancing its economic viability and environmental sustainability. This review explores biodiesel production from both vegetative and animal-based feedstocks, focusing on their potential as renewable energy sources. Key extraction techniques, including mechanical, solvent, and advanced methods are critically examined for their effectiveness in lipid extraction. The review further evaluates five biodiesel production methods: transesterification, supercritical transesterification, pyrolysis, blending, and micro-emulsification, with a particular focus on transesterification due to its efficiency and favorable outcomes. The study emphasizes the physicochemical properties of biodiesel, ensuring compliance with ASTM 6751 and EN 14214 standards. By providing a comprehensive assessment of feedstock availability, process efficiency, and sustainability considerations, this review contributes to advancing the role of biodiesel in the transition toward climate-friendly energy solutions. The findings reinforce the role of biodiesel in mitigating climate change by reducing dependency on fossil fuels and promoting circular bioeconomy practices.

In Nigeria, it is common to design buildings first for gravity loads and then assess the structure's suitability for safety against lateral loads. It is well known that lateral loads influence the design of multi-story buildings, hence the designer's first priority should be to ensure that the structure is sufficiently safe from lateral loads. Nigeria has a large number of RC frame building that are not designed to resist seismic load because of the belief that Nigeria does not have area that are prone to earthquake, but Nigeria is no longer free from earthquake due to the occurrence of earth tremors in Nigeria in the past. This study focused on the design of RC shear wall in three storey building that assume to be place in seismic prone area in Nigeria which is capable of resisting Earthquake. The data of the magnitudes of earth tremors that have occurred in Nigeria was collected from Centre of Geodesy and Geodynamic to determine the seismic load to EC8 specification. Extended Three-Dimensional Analysis of Building System (ETABS) was used to analyze and design the shear wall. ETABS 2016 software was incorporated with all the major analysis engines that is static, dynamic, Linear and non-linear, etc. This tool was used for the modeling, analyses and design of RC shear wall for three storey building to resist Earthquake load. Hence, providing shear walls at adequate locations substantially reduce structural vulnerability and absorb Earthquake energy through inelastic deformation and prevent collapse and lose of lives.

When agricultural land is unequally distributed, the land lease market can be essential in balancing factor endowments among agrarian families. With this backdrop, the study explores the economic and environmental sustainability of tenant farming among the Mishing tribe in Majuli, the biggest river island. The primary objectives are to compare the economic benefits of tenant versus owner farmers and to assess the resilience of the Mishing community to environmental challenges. Utilising purposive sampling, data were collected from the UjaniMajuli Block. Analytical methods include the Lekart scale, independent t-tests, and cost-benefit ratio analysis to evaluate economic benefits, complemented by field observations to assess resilience indicators. Results reveal that tenant farmers achieve a higher benefit-cost ratio than owner farmers for red and winter paddy, attributed to more efficient resource utilisation and adaptive agricultural practices. Despite strong resilience through traditional adaptive measures, there is a need for enhanced infrastructure and awareness programs. The study emphasises the necessity for targeted policy interventions and support mechanisms to enhance tenant farmers’ economic stability and resilience in Majuli.

Transformational advances in environmental sensing have been made possible by the convergence of Cloud Computing and the Internet of Things (IoT). The potential for these technologies is to work together and improve environmental monitoring data analytics. Integrating IoT in the cloud creates a robust environment for advanced analytics by overcoming previous hurdles in data granularity, real-time monitoring, and geographical coverage. These developments aren’t without their own set of difficulties, however, including data security, interoperability, and ethical concerns. This paper explores integrating Cloud IoT with environmental sensing. The paper addresses these issues and emphasises the need to establish ethical data-gathering methods, implement standardised communication protocols, and address privacy concerns. The study concludes by examining the challenges, concerns, and potential of integrating Cloud IoT. The integration of Cloud Computing and IoT not only transforms environmental sensing but also provides a solid foundation for collaborative research, data-driven decision-making, and environmentally conscious management.

Cloud IoT helps in efficient utilization of resources for climate calamity response and recovery operations by integrating data through IoT sensors, cloud-based platforms, etc., to optimize requirements in the place of incident and it is cost effective as well. In the changing climate scenarios, climate-smart agricultural practices are needed for the farmers to enhance the food security, livelihood etc., to mitigate and adapt to human induced impacts for the sustainable and resilient agricultural activities especially in developing countries. Generative Adversarial Networks are used for filling the missing wind data and generate realistic outcomes to address data gaps for improving the accuracy and quality of datasets and also help in improving the performance of various models. Google Earth Engine provides a wide array of satellite imagery datasets and tools for processing and analyzing flood data involving satellite imagery and hydrological models to detect and monitor recent and future flood events. This issue covers these important aspects in its seven articles from various parts of the globe. We hope readers will get an insight into these important developments. Happy reading.

The cumulative effects of seasonal Earth processes in different places and times in the atmosphere, hydrosphere, and cryosphere essentially and inevitably shape global climate conditions. Therefore, the article investigates the possibilities for modelling the periodicity of the observable seasonal climate processes. The starting assumption of the study is that the seasonal climate processes are representable by two-phase linear periodic models based on observed data. A numerical algorithm elaborated in the sequel makes it possible to accumulate the seasonal effects of two successively progressive and regressive process phases of periodic climate changes in time. The model first tackles the reported seasonal growth of the atmospheric CO2 concentration. Next, it considers the observed seasonal cryospheric melting and freezing processes of the Antarctica and Greenland ice sheets and of the Arctic sea ice. It also elaborates on the reported seasonal sea level rise. Finally, the article summarises the interactions of periodic climate processes and the global climate conditions in time scale. The reports on global temperature rise are only on an annual basis. The article also emphasises the importance of control over the seasonal worsening and recovery scenarios for more appropriate projections of climate policies to 2100.