This study examines the impact of in utero exposure to ambient particulate matter (PM) on neonatal health outcomes, utilizing comprehensive population-level birth records from South Korea for pregnancies between 2016 and 2019. To address potential endogeneity concerns, the analysis adopts wind direction as an instrumental variable for prenatal PM exposure. The findings indicate that exposure to PM during the first trimester significantly increases the likelihood of preterm birth, and this effect remains robust across a range of model specifications. Because PM2.5 and PM10 co-move, we interpret the estimates as effects of broader particulate pollution rather than PM2.5 alone. Moreover, the estimated impacts are consistent across different socioeconomic strata. These results highlight the critical importance of environmental health during early pregnancy and suggest that in low-fertility, late-childbearing societies such as South Korea, environmental protection efforts should be closely aligned with maternal health policies.

This study examines the association between air pollution exposure and health using a representative survey sample from Siddharthanagar municipality of Nepal. Our data on household characteristics, spatial locations and individual lung function allow us to understand heterogeneity in exposure and respiratory health. We examine exposure differential through three potential mechanisms – occupation, residence and exposure avoidance. We employ a simultaneous equations model to account for the endogenous choice of avoidance and spatial error models to control for the spatial spillover of health outcomes. We find that outdoor workers and those residing near brick kilns have lower lung function. Exposure avoidance positively correlates with lung function. Exposure avoidance, however, is low among marginalized outdoor workers and individuals residing in polluted areas, further exacerbating the exposure gap among socioeconomic subgroups. The study advances the case of environmental inequity through the ‘triple jeopardy’ of low socioeconomic status, exposure differences and poor health.

As a major metropolitan city, London faces persistent road congestion and severe air pollution. To address these issues, static electronic road pricing (ERP) models have been implemented. While effective, these are inherently limited in flexibility. This paper explores dynamic ERP models to improve upon static pricing by minimizing air pollution and traffic congestion within the Congestion Charge Zone. The problem is formulated as a multi-stakeholder multi-objective optimization problem, incorporating the perspectives of three stakeholders—the government, vehicle owners, and environmental organizations—and three objectives: air pollution, traffic congestion, and price. The NSGA-II optimization algorithm was applied on a representative day and demonstrated substantial improvements. The concentration of PM$ {}_{2.5} $—the more harmful pollutant—was reduced by up to 23%, while NO2 levels fell by 2–3%. Traffic flow, used as a proxy for congestion, decreased by approximately 3–4% during peak hours. These improvements were achieved with only a modest increase in the mean price to £12.51 (from a baseline of £11.50), with a standard deviation of £1.59 and a variance of £2.43 across hourly prices. These results suggest that targeted dynamic pricing—when aligned with environmental and behavioural incentives—can deliver measurable gains in urban air quality and congestion without imposing a significant cost burden on drivers. A core novelty of this work lies in its practical, stakeholder-inclusive problem formulation. While the approach assumes infrastructure for automated price deduction and routing, this limitation can be addressed in future work through advances in vehicle–infrastructure communication systems.

We estimate the causal effects of local officials’ growth preferences on air pollution. Leveraging the unprecedented and uneven economic shocks caused by COVID-19, which resulted in substantial changes in gross domestic product growth rankings, we analyse variations in growth preferences. Our findings reveal that a 10-unit change in growth rankings leads to significant increases in Air Quality Index and ambient pollutant concentrations. Key predictors of this increased pollution include factors sensitive to governmental influence, such as fixed investments, industrial activities and registration requirements for polluting companies. Finally, we characterize the cautious behaviours of local officials in balancing economic and environmental objectives within China's context of multiple, yet unequally weighted, tasks. Our study illuminates how growth preferences contribute to environmental consequences and underscores the strategic responses with political motivations to meet dual conflicting targets set by higher authorities.

Using the synthetic difference-in-differences method, this study evaluates the comprehensive effects of the ‘coal-to-gas’ policy in China following its complete implementation in 2017. We propose four channels through which the policy could affect the air quality in untreated cities. The findings reveal a significant decrease in air pollution levels, as measured by PM10, in both the treated and untreated areas. However, the net spillover effect in the treated and untreated areas exhibits heterogeneous spatial distribution patterns due to different mechanisms. These differences could be related to the political economy and natural geography of China.

Climate change is increasingly recognized as a public health challenge, with emerging evidence linking climate-related factors to suicidality. A search was conducted in PubMed, Scopus, PsycINFO, Web of Science and Google Scholar following the PRISMA guidelines. The studies that assessed the association between climate indicators and suicidality were included, and risk of bias was assessed using MMAT and ROBINS-E. A total of 43 studies met the inclusion criteria, covering various geographic regions and populations. Rising ambient temperatures were the climate variable most frequently studied, with multiple studies showing a significant increase in suicide rates linked to higher temperatures, particularly during the summer months, especially among females. Seasonal variations, including heatwaves and extreme cold, were associated with increased suicidality. Additionally, extreme weather events such as floods, droughts and storms correlated with higher suicide risks, particularly in vulnerable populations, including older adults and individuals with pre-existing mental health conditions. Air pollution, particularly exposure to PM2.5, NO2 and SO2, was also found to contribute to suicidality. Most of the studies originated in high-income countries, highlighting a gap in research from low- and middle-income countries (LAMICs), where the impacts of climate change may be more severe but remain understudied. Although two studies examined suicidal ideation, the overwhelming majority of the evidence focused on suicide mortality, underscoring the marked under-representation of non-fatal suicidality outcomes in the existing literature. The findings suggest that climate change plays an important role in suicidality, with increasing temperatures, extreme weather and air pollution acting as key risk factors. As climate stressors grow, it is crucial to integrate them into mental health and suicide-prevention policies. More research, especially in underrepresented regions, is needed to guide effective interventions.

Poor air quality has been affecting the Chinese people for many years due to the country’s speedy industrialization and urbanization. However, very few initiatives had been taken by civil society until 2011. The air pollution campaign between October 2011 and March 2012 initiated on a Chinese microblogging website, mobilized millions of citizens and effected policy change. It is often seen as a milestone in the chronology of public participation in China. Using process tracing, participant observations, framing analysis and in-depth interviews, the article analyses this campaign by revealing its major actors and frames mobilizing issue entrepreneurs and environmental publics. Our analysis generates two findings: first, microblogging platforms can greatly expand the networks of Chinese environmental activists by involving public figures and governmental agencies; second, the frame which links air pollution to health and appreciates governmental efforts is critical to the success of civic participation in China’s environmental governance.

Air pollution remains a major challenge, especially in developing countries, requiring joint efforts from governments and society. This study examines how mass media, through its emotional tone, functions as an informal regulator of air pollution in China’s “war on air pollution”. Using daily data on media sentiment, air quality and related variables across Chinese cities, we find that negative emotional tones in environmental news are significantly associated with lower pollution levels. We identify mechanisms through which media influence public awareness, trigger government responses and pressure firms to reduce emissions. Our findings highlight the media’s role beyond information dissemination to shape agendas and social norms, even in contexts with restricted press freedom. This study offers new insights into how emotional framing in mass media contributes to environmental governance in developing countries.

Despite the substantial evidence linking particulate matter exposure to adverse health outcomes, a large portion of the global population, particularly in low-income countries, continues to rely on highly polluting fuels, such as wood, for cooking and heating. This study evaluates the immediate effects of wood-burning restrictions, which are triggered by air quality warnings, on levels of fine (PM2.5) and coarse (PM10) particulate matter in southern Chile. Using a difference-in-differences design that incorporates pre-policy data, we provide plausible causal estimates indicating that wood-burning restrictions lead to significant reductions in hourly PM10 and PM2.5 concentrations during the most severe air quality warning. Additional analyses, including a regression discontinuity design, further support these findings. While our analysis suggests that wood-burning restrictions are effective, they may not be sufficient to reduce air pollution concentrations to levels that are considered safe for public health.