Drought Variabilities in Saudi Arabia: Unveiling Spatiotemporal Trends through Observations and Projections

Abstract In the Kingdom of Saudi Arabia (KSA), meteorological drought leads to significant water scarcity and triggers profound social, economic, and environmental challenges. The main aim of this paper is to quantify spatiotemporal variability in drought using precipitation data from 28 meteorological stations (1985–2023) and produce future projections. Drought is expressed in terms of the […]

Sand and Dust Storms Impact on Photovoltaic Panels in Saudi Arabia

Abstract This research aims to assess the spatial potential of solar energy in Saudi Arabia by estimating the total sum and analyzing the spatial variability of solar radiation to determine the best sites for solar energy generation that are least affected by sandstorms in the country. It also explores the effects of sandstorms on solar […]

Community-Level Practice Checklists for Health Protection During Cold Spells in China

Abstract Communities play a crucial role in protecting the health of vulnerable populations such as the elderly, low-income groups, and high-risk individuals during cold spells. However, current strategies for responding to cold spells primarily consist of programmatic policies that lack practicality, specificity, and detailed implementation guidelines for community workers. Therefore, this study aims to identify […]

Assessing the role of socio-economic factors in shaping the temperature-mortality exposure-response relationship in China

Abstract Non-optimal temperatures significantly influence public health. However, the role of socio-economic factors in modulating health risks associated with non-optimal temperatures varies geographically and among different populations. Thus, the meteorological, air quality, health data, and socio-economic indicators were obtained from 23 districts in North and 48 districts in East China, respectively. Employing a two-stage meta-analysis, […]

Investigating Two-dimensional Horizontal Mesh Grid Effects on the Eulerian Atmospheric Transport Model Using Artificial Neural Network

Abstract The complexity of monitoring is compounded by the environmental and health impacts linked to air pollution. The elevated expenses and intricate execution involved in measurements prompt the integration of modeling as a complementary approach alongside monitoring and surveillance efforts. Transport chemistry models like CHIMERE operate deterministically, utilizing meteorological factors, emissions data, boundary conditions, and […]

An intercomparison of SEMARA high-resolution AOD and MODIS operational AODs

Abstract SEMARA is a high-resolution aerosol optical depth (AOD) retrieval algorithm that incorporates two algorithms, Simplified and Robust Surface Reflectance Estimation Method (SREM) for estimating surface reflectance and the Simplified Aerosol Retrieval Algorithm (SARA) for retrieving AOD. This study used SEMARA approach for retrieving AOD utilizing data obtained from Aqua-MODIS in the green channel. The algorithm had […]

Unveiling the impact of firm-characteristics on sustainable development goals disclosure: A cross-country study on non-financial companies in Asia

Keywords: Sustainable development goalsFirm-specificsSDGs practices Abstract This study examines the practices of the UN Sustainable Development Goals (SDGs) in Asian countries with special reference to listed firms in China, India, Indonesia, Japan, Malaysia, Singapore, and Saudi Arabia. Further, it evaluates the impact of firms’ specific factors on SDGs practices. The original sample consists of 1462 […]

The Role of Machine Learning in Enhancing Particulate Matter Estimation: A Systematic Literature Review

Keywords: machine learning; MERRA2; dust; air quality; PM10; PM2.5   Abstract As urbanization and industrial activities accelerate globally, air quality has become a pressing concern, particularly due to the harmful effects of particulate matter (PM), notably PM2.5 and PM10. This review paper presents a comprehensive systematic assessment of machine learning (ML) techniques for estimating PM concentrations, […]