Fine particulate matter (PM_2.5) is a persistent air-quality problem in Dhaka, Bangladesh, and its severity and temporal variability calls for a long-term assessment. The present study reviewed PM_2.5 pollution between 2015 and 2024 and investigated the seasonal, interannual, and meteorological correlation. Daily air-quality and meteorological data were analysed with descriptive statistics, air-quality benchmark comparison, general linear model, Spearman correlation and linear regression for three monitoring stations. A total of 7,943 station-day observations were processed, with 6,268 having good daily PM_2.5 observations. Annual mean concentrations varied from 77.24 μg/m³ in 2017 to 108.74 μg/m³ in 2021, well above the annual guideline of 5 μg/m³ set by the World Health Organization. The concentrations differed significantly between seasons (p < 0.001) with higher levels found in winter season compared to monsoon season. The general linear model also indicated an interannual difference (p = 0.033), but no significant linear trend was observed by the linear regression (p = 0.797). Bivariate correlations were negative for temperature, relative humidity and wind speed, but none of these variables were statistically significant in the adjusted model. The findings indicate persistently high PM_2.5 concentrations and pronounced seasonal variation. To improve air quality in Dhaka, sustained emission controls, uniform monitoring and coordinated air quality management is required.

Exposure to wildfire smoke has been a growing public health issue with the increasing effects of climate change. The increasing frequency and severity of wildfires fueled by higher global temperatures and shifting climate change patterns have left more people exposed to smoke for longer periods. This exposure is primarily driven by fine particulate matter (PM_2.5) and carbon monoxide (CO) and other toxic gases, causing harmful health impacts, particularly to the respiratory system and cardiovascular system. The potential to reduce health effects is dependent on the adaptive capacity of individuals, households, and communities in anticipating, responding to, and recovering from smoke events. Social vulnerability factors, including socioeconomic status, race/ethnicity, housing quality, and healthcare access, greatly influence how well individuals or communities can prepare for and respond to the effects of wildfire smoke exposure. Although simple protective steps are often possible, more expensive solutions are usually out of reach for the most marginalized groups, showing that the ability to adapt depends on the resources people have. This review aims to analyze the convergence of wildfire smoke exposure, social vulnerability, and adaptive capacity in vulnerable communities with specific reference to approaches to building community resilience. This study adopts a narrative integrative review approach to synthesize current interdisciplinary evidence on the health impacts of wildfire smoke, associated social inequities, and adaptive capacity strategies, while introducing an integrated conceptual framework linking social vulnerability, adaptive capacity, and community resilience. The findings of this review substantiate the necessity of integrated, equity-oriented adaptation responses, such as enhanced risk communication, sustainable climate change mitigation strategies, and improved access to healthcare and infrastructure. In conclusion, strengthening community resilience to wildfire smoke requires confronting structural social inequities while simultaneously enhancing the adaptive capacity of resource-constrained communities.