Explore the vast range of titles available.

Background A pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions. Methods Here, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 – 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM 2.5 ), sulphur dioxide (SO 2 ), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors. Results Across provinces, we found that past increases in CO, SO 2, and PM 2.5 concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors. Conclusions By developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale.

The planetary boundary layer (PBL) governs the vertical transport of mass, momentum, and moisture between the surface and the free atmosphere, and thus the determination of PBL height (BLH) is recognized as crucial for air quality, weather, and climate analysis. Although reanalysis products can provide important insight into the global view of BLH in a seamless way, the BLH observed in situ on a global scale remains poorly understood due to the lack of high-resolution (1 or 2 s) radiosonde measurements. The present study attempts to establish a near-global BLH climatology at synoptic times (00:00 and 12:00 UTC) and in the daytime using high-resolution radiosonde measurements over 300 radiosonde sites worldwide for the period 2012 to 2019, which is then compared against the BLHs obtained from four reanalysis datasets, including ERA5, MERRA-2, JRA-55, and NCEP-2. The variations in daytime BLH exhibit large spatial and temporal dependence, and as a result the BLH maxima are generally discerned over the regions such as the western United States and western China, in which the balloon launch times mostly correspond to the afternoon. The diurnal variations in BLH are revealed with a peak at 17:00 local solar time (LST). The most promising reanalysis product is ERA5, which underestimates BLH by around 130 m as compared to radiosondes released during daytime. In addition, MERRA-2 is a well-established product and has an underestimation of around 160 m. JRA-55 and NCEP-2 might produce considerable additional uncertainties, with a much larger underestimation of up to 400 m. The largest bias in the reanalysis data appears over the western United States and western China, and it might be attributed to the maximal BLH in the afternoon when the PBL has risen. Statistical analyses further indicate that the biases of reanalysis BLH products are positively associated with orographic complexity, as well as the occurrence of static instability. To our best knowledge, this study presents the first near-global view of high-resolution radiosonde-derived boundary layer height and provides a quantitative assessment of the four frequently used reanalysis products.

Exposure to air pollution and excessive heat during hot‐and‐polluted episodes (HPEs) may synergistically cause higher health risks globally. Nevertheless, long‐term global spatiotemporal characteristics of HPEs and their health impacts remain unclear. Herein, we conducted statistical analyses using reanalysis data of fine particulate matter (PM2.5) and climate together with our derived concentration‐response function for HPEs to assess global HPE variations from 1990 to 2019, and to estimate the PM2.5‐associated premature mortality during HPEs. Our results reveal that HPE frequency increased significantly globally. HPE PM2.5 intensity in the Global North continuously increased, overpassing the Global South after 2010, indicating a recurred risk of air pollution under climate change in the Global North after several years of emission control endeavors. Globally, we estimated approximately 694,440 (95% CI: 687,996–715,311) total mortalities associated with acute PM2.5 exposure during HPEs from 1990 to 2019, with the Global South accounting for around 80% of these deaths. Among the most vulnerable 15 countries, India had by far the highest mortality burden, and the United States, Russia, Japan, and Germany were particularly highlighted as having higher burdens within the Global North. Our findings highlight the importance of considering environmental inequality between the Global North and the Global South, and co‐benefits of air pollution‐climate change mitigation during policymaking processes. Plain Language Summary Exposure to air pollution and heat during hot‐and‐polluted episodes (HPEs) can combine to increase health risks worldwide. However, we still do not fully understand the long‐term global patterns of HPEs or their health effects. This study analyzed global data on air pollution (PM2.5) and climate from 1990 to 2019 to understand how HPEs have changed over time. We also estimated the number of premature deaths linked to PM2.5 during HPEs using the concentration‐response function we developed. Results show HPEs have become more frequent across the world. In the Global North, PM2.5 levels during HPEs have steadily increased, surpassing levels in the Global South after 2010. This trend suggests a return of PM2.5 risks in the Global North despite years of efforts to reduce emissions. We estimated that PM2.5 during HPEs caused about 694,440 premature deaths globally between 1990 and 2019. Around 80% of these deaths occurred in the Global South, highlighting unequal health burdens. Among the most affected countries, India had the highest number of deaths, while the U.S., Russia, Japan, and Germany stood out in the Global North. These results emphasize the need to address global environmental inequality and to combine efforts to tackle both air pollution and climate change. Key Points HPE frequency and PM2.5 intensity during HPEs have increased globally, with the Global North surpassing the Global South after 2010 Acute PM2.5 exposure during HPEs caused around 694,440 premature deaths globally from 1990 to 2019, with 80% occurring in the Global South Environmental inequality highlights the need to integrate air pollution and climate change mitigation in policymaking

Convective overshooting significantly influences atmospheric material and energy cycles and can cause severe social impacts; nevertheless, aerosol effects on its microphysical structure and associated extreme weather remain unclear. Using a more accurate algorithm of detecting convective overshooting and 10 years of high‐resolution data, this paper investigated how aerosols affect convective overshooting, focusing on its long‐term patterns, three‐dimensional microphysical structure of precipitation such as particle size and concentration, as well as the relationship with extreme weather. Results show that convective overshooting occurred more frequently and intensely in the Maritime Continent, exhibiting a significant increasing trend. Aerosols exerted a stronger influence on convective overshooting during water vapor sufficient seasons, and polluted conditions produced larger but sparser raindrops, with raindrop diameters increasing by 1.2–1.76 times while concentration decreased by 20%. Moreover, aerosols enhanced convective overshooting impact on rain rates and lightning by approximately 50% and 30%, respectively, nearly doubling the spatial influence area.

Aviation emissions impact surface air quality at multiple scales-from near-airport pollution peaks associated with airport landing and take off (LTO) emissions, to intercontinental pollution attributable to aircraft cruise emissions. Previous studies have quantified aviation's air quality impacts around a specific airport, in a specific region, or at the global scale. However, no study has assessed the air quality and human health impacts of aviation, capturing effects on all aforementioned scales. This study uses a multi-scale modeling approach to quantify and monetize the air quality impact of civil aviation emissions, approximating effects of aircraft plume dynamics-related local dispersion (∼1 km), near-airport dispersion (∼10 km), regional (∼1000 km) and global (∼10 000 km) scale chemistry and transport. We use concentration-response functions to estimate premature deaths due to population exposure to aviation-attributable PM2.5 and ozone, finding that aviation emissions cause ∼16 000 (90% CI: 8300-24 000) premature deaths per year. Of these, LTO emissions contribute a quarter. Our estimate shows that premature deaths due to long-term exposure to aviation-attributable PM2.5 and O3 lead to costs of ∼$21 bn per year. We compare these costs to other societal costs of aviation and find that they are on the same order of magnitude as global aviation-attributable climate costs, and one order of magnitude larger than aviation-attributable accident and noise costs.

Previous studies provide empirical evidence for the connection between air pollution and tourism. However, many of them take the nexus as a linear one. It remains unexplored whether any thresholds are required for the nexus to materialize. This study systematically investigates whether PM 2.5 concentrations–an essential indicator of air pollution–affect tourism in China at various tourism development levels. We analyze 284 Chinese cities from 2008 to 2018 using the Unconditional Quantile Regression method. Our statistical results reveal that air pollution positively influences tourism (regarding tourist visits and tourism revenue) in areas with low tourism development levels. However, a complex correlation between air pollution and tourism emerges when tourism development has reached a certain level. The correlation is initially negative, then positive, and finally disappears. But, the overall correlation remains negative. The effects of the interaction between air pollution and tourism resources on tourism are inverted U-shaped, implying that tourism resources can mitigate the negative effects of air pollution on tourism only when tourism development has reached a certain level. Based on the above findings, the associated policy implications are discussed.

Manufacturing mergers and acquisitions (M&A) represent a market-driven mechanism for corporate restructuring that facilitates technology transfer, resource reallocation, and the exchange of management knowledge between heterogeneous corporate owners. Unlike complex multi-departmental carbon policies, M&A networks may offer a more manageable pathway for diffusing cleaner production methods across urban systems. This study examines how manufacturing M&A network centrality affects urban carbon emissions using data from 284 Chinese cities (2004–2018). We uncover an inverted U-shaped relationship between M&A network centrality and emissions, indicating that initial network integration increases emissions before deeper connections enable reductions through operational efficiency improvements and the adoption of clean technologies. Using Apple suppliers as an instrumental variable, we establish that M&A network centrality causally reduces carbon emissions. However, unconditional quantile regression reveals striking heterogeneity: emission reductions occur primarily in cities with low to moderate baseline emissions, while high-emission cities show no significant response. The temporal analysis confirms that M&A effects materialize quickly but diminish over time. These findings suggest that for cities with moderate emissions and substantial network integration, facilitating manufacturing M&A offers a cost-effective complement to traditional environmental policies. However, high-emission cities require more direct interventions beyond market-driven restructuring. This evidence highlights the need for tailored policy approaches that harness spontaneous market mechanisms while taking into account both emission contexts and network positions.

Identifying high-risk individuals, especially during their initial encounters in clinics and hospital emergency services, is crucial to provide timely effective treatment. [...]the timely risk stratification of COVID-19 patients in the emergency room can greatly benefit both infected individuals and healthcare professionals. [...]logistic regression was used to establish the prediction model. Given the substantial clinical burden during the pandemic, the need to triage patients for home care vs. hospital care and stratifying admitted patients into intensive care units or low-risk beds is highly desirable. [...]a prediction model of CRPS with five clinical and biochemical parameters and a simplified version

Understanding long-term precipitation changes in Southeast Asia (SEA) is important because the region is highly vulnerable to precipitation-related disasters. This study examines typhoon and non-typhoon heavy precipitation over SEA during 1960–2024 using a typhoon track dataset and three high-resolution precipitation products. Results show a significant decrease in typhoon-precipitation contribution to total precipitation across the entire SEA, both in its continental and maritime regions, especially during the boreal summer half-year. This trend persists under heavy precipitation conditions (95th and 99th percentiles). In contrast, based on tracking results, non-typhoon heavy precipitation shows increases in precipitation area but decreases in lifespan intensity, yielding more total precipitation per event. Our findings indicate a shifting hazard regime: a decrease in typhoon-related rainfall is being offset by a spatial expansion of non-typhoon heavy precipitation, introducing a new regional risk. The findings provide critical insights into the change of regional precipitation patterns and have implications for disaster management and adaptation in SEA.

This research employs China’s steel restriction policy as a backdrop to investigate environmental policies’ unintended and counterproductive effects. Using high-resolution satellite-derived data and panel Difference-in-Differences regression, we found that the air pollution concentration in cities implementing the steel restriction policy is 5.688 μ g/m 3 higher than in control group cities. Additionally, the growth rate of air pollution in these cities is 6.577% faster. This quantitative evidence substantiates the backfire effect of the anticipation of environmental policy, where the delay between a policy’s announcement and its enforcement leads to a short-term surge in pollution levels. For China and other emerging economies, the development of a thorough and deliberate intergovernmental cooperation strategy is critical when formulating environmental policies. It involves synchronizing the efforts of different government levels in applying pollution controls and diminishing the interval of potential intense pollution in the pre-implementation phase.