Accurate wind speed and direction data are vital for coastal engineering, renewable energy, and climate resilience, particularly in regions with sparse observational datasets. This study evaluates the ERA5 reanalysis model’s performance in predicting wind speeds and directions at ten coastal and offshore stations in Kuwait from 2010 to 2017. This analysis reveals that ERA5 effectively captures general wind speed patterns, with offshore stations demonstrating stronger correlations (up to 0.85) and higher Perkins Skill Score (PSS) values (up to 0.94). However, the model consistently underestimates wind variability and extreme wind events, especially at coastal stations, where correlation coefficients dropped to 0.35. Wind direction analysis highlighted ERA5’s ability to replicate dominant northwest wind patterns. However, it reveals notable biases and underrepresented variability during transitional seasons. Taylor diagrams and error metrics further emphasize ERA5’s challenges in capturing localized dynamics influenced by land-sea interactions. Enhancements such as localized calibration using high-resolution datasets, hybrid models incorporating machine learning techniques, and long-term monitoring networks are recommended to improve accuracy. By addressing these limitations, ERA5 can more effectively support engineering applications, including coastal infrastructure design and renewable energy development, while advancing Kuwait’s sustainable development goals. This study provides valuable insights into refining reanalysis model performance in complex coastal environments.

Ambient air pollution in terms of fine and coarse particulate matter (PM_2.5 and PM₁₀) has been shown to increase adult and infant mortalities. Most studies have estimated the risk of mortalities through attributable proportions and number of excess cases with no reference to the time lost due to premature mortalities. Disability adjusted life years (DALYs) are necessary to measure the health impact of Ambient particulate matter (PM) over time. In this study, we used life-tables for three years (2014–2016) to estimate the years of life lost (YLL), a main component of DALYs, for adult mortalities (age 30+ years) and postneonatal infant mortalities (age 28+ days–1 year) associated with PM_2.5 exposure and PM₁₀ exposure, respectively. The annual average of PM_2.5 and PM₁₀ concentrations were recorded as 87.9 μg/m³ and 167.5 μg/m³, which are 8 times greater than the World Health Organization (WHO) air quality guidelines of 10 μg/m³ and 20 μg/m³, respectively. Results indicated a total of 252.18 (95% CI: 170.69–322.92) YLL for all ages with an increase of 27,474.61 (95% CI: 18,483.02–35,370.58) YLL over 10 years. The expected life remaining (ELR) calculations showed that 30- and 65-year-old persons would gain 2.34 years and 1.93 years, respectively if the current PM_2.5 exposure levels were reduced to the WHO interim targets (IT-1 = 35 μg/m³). Newborns and 1-year old children may live 79.81 and 78.94 years, respectively with an increase in average life expectancy of 2.65 years if the WHO PM₁₀ interim targets were met (IT-1 = 70 μg/m³). Sensitivity analyses for YLL were carried out for the years 2015, 2025, and 2045 and showed that the years of life would increase significantly for age groups between 30 and 85. Life expectancy, especially for the elderly (≥60 years), would increase at higher rates if PM_2.5 levels were reduced further. This study can be helpful for the assessment of poor air quality represented by PM_2.5 and PM₁₀ exposures in causing premature adult mortalities and postneonatal infant mortalities in developing countries with high ambient air pollution. Information in this article adds insights to the sustainable development goals (SDG 3.9.1 and 11.6.2) related to the reduction of mortality rates attributed to ambient air levels of coarse and fine particulate matter.

The climatic conditions in Kuwait necessitate almost all buildings to be centrally air-conditioned with the latest HVAC system to provide the comfortable thermal environment for occupants. Mosques are used five times a day for a maximum time span of about half an hour or less for regular prayers. The study period was selected in the month of November when the ambient temperatures are moderate and cooling or heating is not required. The influence of natural draft through doors and other indoor/outdoor air exchange sites was examined for indoor air quality, degree of comfort, and different sorts of satisfaction during prayers. The indoor air quality is of major concern for mental, spiritual, and social satisfaction of the chaotic lifestyle of the present-day community. A weeklong study was conducted to measure temperature, humidity, carbon dioxide, and over 70 volatile organic compounds indoors and in the ambient air in the vicinity of the selected mosque.

Identifying the sources of atmospheric pollutants is essential for effective air quality management. This study assesses the diagnostic value of SO₂/NO₂ and CO/NO₂ ratios in distinguishing between major emission sources, including vehicular traffic, industrial activity, and biomass burning. A global literature review was conducted to establish typical ratio thresholds associated with different sources. These thresholds were then applied in a case study of Kuwait, a representative Gulf Cooperation Council country with intense vehicular traffic and industrial activity. To complement the ratio-based diagnostics, directional pollution source identification was performed using the Conditional Bivariate Probability Function (CBPF) plots, linking elevated pollutant concentrations to prevailing wind speeds/directions. Results indicate that Al-Fahaheel exhibits a distinct SO₂/NO₂ ratio toward the south-southeast due to industrial activities, and a pronounced CO/NO₂ ratio toward the east, reflecting contributions from mixed urban and traffic-related sources. The observed ratios at the Al-Fahaheel air quality monitoring station—very low CO/NO₂ and moderate to high SO₂/NO₂—are inconsistent with vehicular emissions and are more indicative of industrial emissions from stationary sources. Directional CBPF plots reinforce these associations by clearly linking industrial activities and vehicular traffic sources to the southeastern and western sectors, respectively.