Trends in urban air pollution over the last two decades: A global perspective

Air pollution in Białowieża forest: Analysis of short-term trends from 2014 to 2021

Air pollution caused by sulphur dioxide (SO2) and nitrogen oxides (NOx) has negative impacts on forest health and can initiate forest dieback. Long-term monitoring and analysis of these pollution are carried out in Białowieża Forest in NE Poland due to the threats from abiotic, biotic and anthropogenic factors. The main objective of our study was to monitor the levels and trends of air pollutant deposition in Białowieża Forest. During a short-term monitoring period over six years (2014-2021), the concentration of SO2 in the air decreased significantly (from 2.03 μg m-3 in December 2015 to 0.20 μg m-3 in July 2016), while the concentration of NO2 in the air showed a non-significant decrease (from 8.24 μg m-3 in December 2015 to 1.61 μg m-3 May 2016). There was no significant linear trend in the wet deposition of S-SO4 anions. Mean monthly S-SO4 deposition varies between 4.54 and 94.14 mg m-2month-1. Wet nitrogen deposition, including oxidized nitrogen (N-NO3) and reduced nitrogen (N-NH4), showed a non-significant increase. Mean monthly precipitation of N-NO3 and N-N H4 ranged from 1.91 to 451.73 mg m-2month-1. Neither did total sulphur deposition nor total nitrogen deposition exceed the mean deposition values for forests in Europe (below 6 ha-1yr-1 and 3-15 ha-1yr-1, respectively). Our results indicate that air pollutants originate from local sources (households), especially from the village of Białowieża, as demonstrated by the level and spatial distribution of air pollutant deposition. This indicates that air pollutants from the village of Białowieża could spread to other parts of Białowieża Forest in the future and may have a negative impact on forest health and can initiate forest dieback. It is therefore important to continue monitoring air pollution to assess the threats to this valuable forest ecosystem.

Glycerophospholipid metabolism changes association with ozone exposure

Exposure to ozone (O3) has been associated with cardiovascular outcomes in humans, yet the underlying mechanisms of the adverse effect remain poorly understood. We aimed to investigate the association between O3 exposure and glycerophospholipid metabolism in healthy young adults. We quantified plasma concentrations of phosphatidylcholines (PCs) and lysophosphatidylcholines (lysoPCs) using a UPLC-MS/MS system. Time-weighted personal exposures were calculated to O3 and co-pollutants over 4 time windows, and we employed orthogonal partial least squares discriminant analysis to discern differences in lipids profiles between high and low O3 exposure. Linear mixed-effects models and mediation analysis were utilized to estimate the associations between O3 exposure, lipids, and cardiovascular physiology indicators. Forty-three healthy adults were included in this study, and the mean (SD) time-weighted personal exposures to O3 was 9.08 (4.06) ppb. With shorter exposure durations, O3 increases were associated with increasing PC and lysoPC levels; whereas at longer exposure times, the opposite relationship was shown. Furthermore, two specific lipids, namely lysoPC a C26:0 and lysoPC a C17:0, showed significantly positive mediating effects on associations of long-term O3 exposure with pulse wave velocity and systolic blood pressure, respectively. Alterations in specific lipids may underlie the cardiovascular effects of O3 exposure.

Breathing in danger: Understanding the multifaceted impact of air pollution on health impacts

Air pollution, a pervasive environmental threat that spans urban and rural landscapes alike, poses significant risks to human health, exacerbating respiratory conditions, triggering cardiovascular problems, and contributing to a myriad of other health complications across diverse populations worldwide. This article delves into the multifarious impacts of air pollution, utilizing cutting-edge research methodologies and big data analytics to offer a comprehensive overview. It highlights the emergence of new pollutants, their sources, and characteristics, thereby broadening our understanding of contemporary air quality challenges. The detrimental health effects of air pollution are examined thoroughly, emphasizing both short-term and long-term impacts. Particularly vulnerable populations are identified, underscoring the need for targeted health risk assessments and interventions. The article presents an in-depth analysis of the global disease burden attributable to air pollution, offering a comparative perspective that illuminates the varying impacts across different regions. Furthermore, it addresses the economic ramifications of air pollution, quantifying health and economic losses, and discusses the implications for public policy and health care systems. Innovative air pollution intervention measures are explored, including case studies demonstrating their effectiveness. The paper also brings to light recent discoveries and insights in the field, setting the stage for future research directions. It calls for international cooperation in tackling air pollution and underscores the crucial role of public awareness and education in mitigating its impacts. This comprehensive exploration serves not only as a scientific discourse but also as a clarion call for action against the invisible but insidious threat of air pollution, making it a vital read for researchers, policymakers, and the general public.

Green-gray imbalance: Rapid urbanization reduces the probability of green space exposure in early 21st century China

Green space exposure provides greater beneficial effects on residents compared to unnatural spaces, commonly referred to as "gray spaces". However, during rapid urbanization, gray spaces expand more quickly than green spaces, often encroaching upon and overtaking these natural environments. This unchecked growth leads to detrimental impacts on the human habitat and overall environmental quality. Consequently, it is essential to meticulously assess the spatial and temporal patterns of residents' exposure levels, as well as to thoroughly investigate the underlying driving mechanisms behind these changes. This study used population-weighted exposure level measurements to assess gray and green space exposure in Chinese cities in the early 21st Century (2000-2019). Additionally, the Gray-Green space Exposure Ratio (GER) was calculated, and the spatiotemporal driving mechanism of GER by each factor was analyzed by geostatistical modeling. The results show that gray space exposure is generally increasing in China, especially in eastern parts of China. The probability of exposure to gray spaces exceeds that of green spaces in some high urbanization rate cities. This trend will continue, albeit at a slower rate. Urban sprawl, built-up area density, and increased electricity consumption were the main drivers of rising GER, whereas greenspace integrity contributed to lower GER; the driving mechanisms for GER changes were spatiotemporal heterogeneous. This study provides a reliable reference for restoring the green space exposure to promote the living environment constructing and residents' access to nature.

Effects of ambient air pollution on the risk of small- and large-for-gestational-age births: an analysis using national birth data in Japan

OBJECTIVES

Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births are major adverse birth outcomes related to newborn health. In contrast, the association between ambient air pollution levels and SGA or LGA births has not been investigated in Japan; hence, the purpose of our study is to investigate this association.

METHODS

We used birth data from Vital Statistics in Japan from 2017 to 2021 and municipality-level data on air pollutants, including nitrogen dioxide (NO2), sulfur dioxide (SO2), photochemical oxidants, and particulate matter 2.5 (PM2.5). Ambient air pollution levels throughout the first, second, and third trimesters, as well as the whole pregnancy, were calculated for each birth. The association between SGA/LGA and ambient levels of the air pollutants was investigated using crude and adjusted log-binomial regression models. In addition, a regression model with spline functions was also used to detect the non-linear association.

RESULTS

We analyzed data from 2,434,217 births. Adjusted regression analyses revealed statistically significant and positive associations between SGA birth and SO2 level, regardless of the exposure period. Specifically, the risk ratio for average SO2 values throughout the whole pregnancy was 1.014 (95% confidence interval [CI] 1.009, 1.019) per 1 ppb increase. In addition, regression analysis with spline functions indicated that an increase in risk ratio for SGA birth depending on SO2 level was linear. Furthermore, statistically significant and negative associations were observed between LGA birth and SO2 except for the third trimester.

CONCLUSIONS

It was suggested that ambient level of SO2 during the pregnancy term is a risk factor for SGA birth in Japan.

Nitrate formation mechanisms causing high concentration of PM2.5 in a residential city with low anthropogenic emissions during cold season

During the cold season in South Korea, NO3- concentrations are known to significantly increase, often causing PM2.5 to exceed air quality standards. This study investigated the formation mechanisms of NO3- in a suburban area with low anthropogenic emissions. The average PM2.5 was 25.3 μg m-3, with NO3- identified as the largest contributor. Ammonium-rich conditions prevailed throughout the study period, coupled with low atmospheric temperature facilitating the transfer of gaseous HNO3 into the particulate phase. This result indicates that the formation of HNO3 played a crucial role in determining particulate NO3- concentration. Nocturnal increases in NO3- were observed alongside increasing ozone (O3) and relative humidity (RH), emphasizing the significance of heterogeneous reactions involving N2O5. NO3- concentrations at the study site were notably higher than in Seoul, the upwind metropolitan area, during a high concentration episode. This difference could potentially attributed to lower local NO concentrations, which enhanced the reaction between O3 and NO2, to produce NO3 radicals. High concentrations of Cl- and dust were also identified as contributors to the elevated NO3- concentrations.

Detection of morphological and eco-physiological traits of ornamental woody species to assess their potential Net O3 uptake

Urban greening can improve cities' air quality by filtering the main gaseous pollutants such as tropospheric ozone (O3). However, the pollutant removal capacity offered by woody species strongly depends on eco-physiological and morphological traits. Woody species with higher stomatal conductance (gs) can remove more gases from the atmosphere, but other species can worsen air quality due to high O3 forming potential (OFP), based on their emitting rates of biogenic volatile organic compounds (bVOCs) and Leaf Mass per Area (LMA). Presently, there is a lack of data on eco-physiological (gs, bVOCs emissions) and foliar traits (LMA) for several ornamental species used in urban greening programs, which does not allow assessment of their O3 removal capacity and OFP. This study aimed to (i) parameterize gs, assess bVOCs emissions and LMA of 14 ornamental woody species commonly used in Mediterranean urban greening, and (ii) model their Net O3 uptake. The gs Jarvis model was parameterized considering various environmental conditions alongside isoprene and monoterpene foliar bVOCs emission rates trapped in the field and quantified by gas chromatography-mass spectrometry. The results are helpful for urban planning and landscaping; suggesting that Catalpa bignonioides and Gleditsia triacanthos have excellent O3 removal capacity due to their high maximum gs (gmax) equal to 0.657 and 0.597 mol H2O m-2 s-1. Regarding bVOCs, high isoprene (16.75 μg gdw-1 h-1) and monoterpene (13.12 μg gdw-1 h-1) emission rates were found for Rhamnus alaternus and Cornus mas. In contrast, no bVOCs emissions were detected for Camellia sasanqua and Paulownia tomentosa. In conclusion, 11 species showed a positive Net O3 uptake, while the use of large numbers of R. alaternus, C. mas, and Chamaerops humilis for urban afforestation planning are not recommended due to their potential to induce a deterioration of outdoor air quality.

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014

Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the surface ozone concentration from CMIP6 climate model, and the long-term and large-scale surface ozone concentration of China during 1950-2014 is obtained. The long-term evolutions and trends of ozone and meteorological effects on interannual ozone variations are further analyzed. The results reveal that CMIP6 historical simulations have a large underestimation in ozone concentrations and their trends. The XGB-derived ozone are closer to observations, with R2 value of 0.66 and 0.74 for daily and monthly retrievals, respectively. Both the concentrations and exceedances of ozone in most parts of China have shown increasing trends from 1950 to 2014. The daily mean ozone concentration without climate change effects is estimated to be 117 ppb in the year 1950 averaged over China. It indicates that the increase in anthropogenic emissions of China has a significant contribution to ozone enhancement between 1950 and 2014. The higher ozone growth rates of XGB retrievals than those from the model indicate a regional surface ozone penalty due to the warming climate. The relatively significant increment in ozone are estimated in the Central and Western China. Seasonally, the ozone enhancement is largest in spring, indicating a shift in seasonal variation of ozone. Given the uncertainty in simulating historical ozone by climate model, we show that machine learning approaches can provide improved assessment of evolution in surface ozone, along with valuable information to guide future model development and formulate future ozone pollution prevention and control policies.

Stable O3 Decomposition by Layered Double Hydroxides: The Pivotal Role of NiOOH Transformation

Because ozone (O3) is a significant air pollutant, advanced O3 elimination technologies, particularly those under high-humidity conditions, have become an essential research focus. In this study, a nickel-iron layered double hydroxide (NiFe-LDH) was modified via intercalation with octanoate to develop an effective hydrophobic catalyst (NiFe-OAa-LDH) for O3 decomposition. The NiFe-OAa-LDH catalyst sustained its O3 decomposition rate of >98% for 48 h under conditions of 90% relative humidity, 840 L/(g·h) space velocity, and 100 ppm inlet O3 concentration. Moreover, it maintained a decomposition rate of 90% even when tested at a higher airflow rate of 2500 L/(g·h). Based on the changes induced by the Ni-OII to Ni-OIII bonds in NiFe-OAa-LDH during O3 treatment, catalytic O3 decomposition was proposed to occur in two stages. The first stage involved the reaction between the hydroxyl groups and O3, leading to the breakage of the O-H bonds, formation of NiOOH, and structural changes in the catalyst. This transformation resulted in the formation of abundant and stable hydrogen vacancies. According to density functional theory calculations, O3 can be effectively decomposed at the hydrogen vacancies with a low energy barrier during the second stage. This study provides new insights into O3 decomposition.

A GIS-based approach to determining optimal location for decentralized inner city smart filters: Toward net zero cities

Climate change has already begun to take visible effect globally in recent years. Given the climate change paradox and urbanization trends, cities' success would not only depend on smartness and sustainability, but also resilience to all forthcoming economic, environmental, or behavioral changes. Numerous technologies have surfaced and proved effective in CO2 removal from the local environment. However, the optimal placement of these smart filters is a complex task and require logical and strategic decision-making. Determining the optimal location is one of the key factors for establishing a network of smart air filters. This study used a GIS-based suitability analysis for identifying optimal locations for smart filters based on pollution hotspots (population and spatial proximity to industry, commercial centers, roads, high-traffic areas, and intersections). The spatial analysis involves the determination and preparation of input layers, ranking layers, assigning weights to each criterion, and generation of a suitability map. The sites with a higher suitability score (7 or above) are optimum sites for air filters. The sites are spatially distributed over different regions. The findings revealed that GIS-based suitability analysis can be an effective technique for placing smart filters within an urban environment. These findings can help decision-makers to prioritize the location considering environmental constraints. The proposed solution aims to pave the way for fostering resilient, smart, and sustainable cities through a community sensing platform targeting hotspots within spatial variations.

Association of ambient ozone exposure and greenness exposure with hemorrhagic stroke mortality at different times: A cohort study in Shandong Province, China

Evidence on the association between long-term ozone exposure and greenness exposure and hemorrhagic stroke (HS) is limited, with mixed results. One potential source of this inconsistency is the difference in exposure time metrics. This study aimed to investigate the association between long-term exposure to ambient ozone, greenness, and mortality from HS using exposure metrics at different times. We also examined whether greenness exposure modified the relationship between ozone exposure and mortality due to HS. The study population consisted of 45771 participants aged ≥40 y residing in 20 counties in Shandong Province who were followed up from 2013 to 2019. Ozone exposure metrics (annual mean and warm season) and the normalized difference a measure of greenness exposure, were calculated. The relationship between environmental exposures (ozone and greenness exposures) and mortality from HS was assessed using time-dependent Cox proportional hazards models, and the modification of greenness exposure was examined using stratified analysis with interaction terms. The person-years at the end of follow-up were 90,663. With full adjustments, the risk of death from hemorrhagic stroke increased by 5% per interquartile range increase in warm season ozone [hazard ratio =1.05; 95 % confidence interval: 1.01-1.08]. No clear association was observed between annual ozone and mortality HS. Both the annual and summer NDVI were found to reduce the risk of HS mortality. The relationships were influenced by age, sex, and residence (urban or rural). Furthermore, greenness exposure was shown to have a modifying effect on the relationship between ozone exposure and the occurrence of HS mortality (P for interaction = 0.001). Long-term exposure to warm season O3 was positively associated with HS mortality, while greenness exposure was inversely associated with HS mortality. Greenness exposure may mitigate the negative effects of warm season ozone exposure on HS mortality.

The impact of mobility costs on cooperation and welfare in spatial social dilemmas

From over-exploitation of resources to urban pollution, sustaining well-being requires solving social dilemmas of cooperation. Often such dilemmas are studied assuming that individuals occupy fixed positions in a network or lattice. In spatial settings, however, agents can move, and such movements involve costs. Here we investigate how mobility costs impact cooperation dynamics. To this end, we study cooperation dilemmas where individuals are located in a two-dimensional space and can be of two types: cooperators-or cleaners, who pay an individual cost to have a positive impact on their neighbours-and defectors-or polluters, free-riding on others' effort to sustain a clean environment. Importantly, agents can pay a cost to move to a cleaner site. Both analytically and through agent-based simulations we find that, in general, introducing mobility costs increases pollution felt in the limit of fast movement (equivalently slow strategy revision). The effect on cooperation of increasing mobility costs is non-monotonic when mobility co-occurs with strategy revision. In such scenarios, low (yet non-zero) mobility costs minimise cooperation in low density environments; whereas high costs can promote cooperation even when a minority of agents initially defect. Finally, we find that heterogeneity in mobility cost affects the final distribution of strategies, leading to differences in who supports the burden of having a clean environment.

Impact of aerosol-boundary layer interactions on PM2.5 pollution during cold air pool events in a semi-arid urban basin

Global emission reductions still must address winter fine particulate matter (PM2.5) pollution in urban basins with enclosed terrains and frequent cold air pool (CAP) events when the temperatures within the basin are colder than above it. The effects of urban basin aerosol-boundary layer interactions on PM2.5 pollution during CAP events remain unclear. Intensive boundary layer observations in January 2021 and numerical models were used to investigate this issue in the semi-arid urban Lanzhou Basin of China. The results showed that CAPs formed because of the synoptic weather system that exacerbated the warming over the basin. The CAPs in this experiment were characterized by stronger temperature inversion (TI) layers in the vertical direction and lower relative humidity, lower wind speed, and weaker turbulence at the bottom of the basin compared to other conditions. The strong TI layers below the top of the basin inhibited the vertical dispersion of pollutants in the basin and concentrated the PM2.5 within a height of 0.3 km from the bottom of the basin. During CAP events, the proportion of elemental carbon in PM2.5 increased, whereas that of secondary inorganic species decreased. Aerosol absorption increased faster than scattering during CAP events. Therefore, the mean single scattering albedo decreased from 0.85 during non-CAP periods to 0.81 during CAP events. Radiosonde-sounding observations and numerical simulations indicated that aerosols accumulating in the lower basin heated the atmosphere during the daytime and facilitated boundary layer development via the "stove effect" (absorption aerosol heats lower atmosphere to promote boundary layer development). No significant "dome effect" (absorption aerosol heats the upper boundary layer to suppress boundary layer development) occurred during the two CAP events. These findings provide a theoretical basis for scientifically-guided PM2.5 pollution control in winter in isolated urban basins.

Experimental analysis of PM2.5 reduction characteristics between Korean red pine (Pinus densiflora) and sawtooth oak (Quercus acutissima) saplings under different densities and arrangement structures

As global air pollution, particularly fine particulate matter (PM2.5), has become a major environmental problem, various PM2.5 mitigation technologies including green infrastructure have received significant attention. However, owing to spatial constraints on urban greening, there is a lack of management plans for urban forests to efficiently mitigate PM2.5. In this study, we assessed the PM2.5 reduction capabilities of Pinus densiflora (Korean red pine) and Quercus acutissima (sawtooth oak) by measuring the changes of PM2.5 concentrations using an experimental chamber system. In addition, the PM2.5 reduction efficiency in 90 min (PMRE90) and the amount of PM2.5 reduction per leaf area (PMRLA) were compared based on arrangement structures and density levels. The results showed that the PM2.5 reduction by plants was significantly greater than that of the control experiment without any plants, and an additional reduction effect of approximately 1.38 times was induced by a 1.5 m s-1 air flow. The PMRE90 of Korean red pine was the highest at medium density. In contrast, the PMRE90 of sawtooth oak was the highest at high density. The PMRLA of both species was highest at low densities. The different responses of the species to total reduction were well explained by total leaf area (TLA). The PMRE90 of both species was positively correlated with TLA. The PMRLA of sawtooth oak was approximately 2.3 times greater than that of Korean red pine. However, there were no significant differences in both PMRE90 and PMRLA between the arrangement structures. Our findings reveal the potential mechanisms of vegetation in reducing PM2.5 according to arrangement structure and density. This highlights the importance of efficiently using urban green spaces with spatial constraints on PM2.5 mitigation in the future.

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Long-term trends in British Columbia lower mainland air quality: Criteria air pollutants and VOC

The lower mainland of British Columbia is a geographic region that comprises the districts of Metro Vancouver and the Lower Fraser Valley. It is situated in a complex topographical and coastal location in southwestern British Columbia. Metro Vancouver is Canada's third largest population center. Accessing the Canadian National Air Pollution Surveillance Program (NAPS) database we calculated air pollutant statistics using the Canadian Ambient Air Quality Standards (CAAQS) averaging times, numerical forms, and numerical levels for the years 2001to 2020. Man Kendall and Sen statistical methods were used to test for the presence of trends and the slope of those trends in fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and volatile organic compound (VOC) ambient air concentrations. We did not determine a significant trend in 98th percentile of the daily 24-hr average PM2.5 concentrations. We did determine significant negative trends in the annual average of the daily 24-hr average PM2.5 concentrations at 6 of the 9 locations. Episodic, multi-day duration elevated PM2.5 concentrations related to forest fires were a significant influence on PM2.5 ambient concentrations. Annual 4th highest daily maximum 8-hr average O3 concentrations showed no trend at 14 of 18 locations, declined at 3 locations, and increased at one location. We determined statistically significant declines in peak and average NO2 and SO2 concentrations, and in time-integrated annual VOC concentrations.Implications: This non-parametric, statistical analysis determines 20-year trends in British Columbia lower mainland ambient air quality for PM2.5, O3, NO2, SO2 and VOC, assesses air quality against Canadian Ambient Air Quality Standards, and highlights the importance of event-based wildfire-sourced PM2.5.

Toward Better and Healthier Air Quality: Global PM2.5 and O3 Pollution Status and Risk Assessment Based on the New WHO Air Quality Guidelines for 2021

To reduce the high burden of disease caused by air pollution, the World Health Organization (WHO) released new Air Quality Guidelines (AQG) on September 22, 2021. In this study, the daily fine particulate matter (PM2.5) and surface ozone (O3) data of 618 cities around the world is collected from 2019 to 2022. Based on the new AQG, the number of attainment days for daily average concentrations of PM2.5 (≤ 15 µg m-3) and O3 (≤ 100 µg m-3) is approximately 10% and 90%, respectively. China and India exhibit a decreasing trend in the number of highly polluted days (> 75 µg m-3) for PM. Every year over 68% and 27% of cities in the world are exposed to harmful PM2.5 (> 35 µg m-3) and O3 (> 100 µg m-3) pollution, respectively. Combined with the United Nations Sustainable Development Goals (SDGs), it is found that more than 35% of the world's cities face PM2.5-O3 compound pollution. Furthermore, the exposure risks in these cities (China, India, etc.) are mainly categorized as "High Risk", "Risk", and "Stabilization". In contrast, economically developed cities are mainly categorized as "High Safety", "Safety", and "Deep Stabilization." These findings indicate that global implementation of the WHO's new AQG will minimize the inequitable exposure risk from air pollution.

Photochemical oxidation of VOCs and their source impact assessment on ozone under de-weather conditions in Western Taiwan

The application of statistical models has excellent potential to provide crucial information for mitigating the challenging issue of ozone (O3) pollution by capturing its associations with explanatory variables, including reactive precursors (VOCs and NOX) and meteorology. Considering the large contribution of O3 in degrading the air quality of western Taiwan, three-year (2019-2021) hourly concentration data of VOC, NOX and O3 from 4 monitoring stations of western Taiwan: Tucheng (TC), Zhongming (ZM), Taixi (TX) and Xiaogang (XG), was evaluated to identify the effect of anthropogenic emissions on O3 formation. Owing to the high-ambient reactivity of VOCs on the underestimation of sources, photochemical oxidation was assessed to calculate the consumed VOC (VOCcons) which was followed by the source identification of their initial concentrations. VOCcons was observed to be highest in the summer season (16.7 and 22.7 ppbC) at north (TC and ZM) and in the autumn season (17.8 and 11.4 ppbC) in southward-located stations (TX and XG, respectively). Results showed that VOCs from solvents (25-27%) were the major source at northward stations whereas VOCs-industrial emissions (30%) dominated in south. Furthermore, machine learning (ML): eXtreme Gradient Boost (XGBoost) model based de-weather analysis identified that meteorological factors favor to reduce ambient O3 levels at TC, ZM and XG stations (-67%, -47% and -21%, respectively) but they have a major role in accumulating the O3 (+38%) at the TX station which is primarily transported from the upwind region of south-central Taiwan. Crucial insights using ML outputs showed that the finding of the study can be utilized for region-specific data-driven control of emission from VOCs-sources and prioritized to limit the O3-pollution at the study location-ns as well as their accumulation in distant regions.

Population exposure to multiple air pollutants and its compound episodes in Europe

Air pollution remains as a substantial health problem, particularly regarding the combined health risks arising from simultaneous exposure to multiple air pollutants. However, understanding these combined exposure events over long periods has been hindered by sparse and temporally inconsistent monitoring data. Here we analyze daily ambient PM2.5, PM10, NO2 and O3 concentrations at a 0.1-degree resolution during 2003-2019 across 1426 contiguous regions in 35 European countries, representing 543 million people. We find that PM10 levels decline by 2.72% annually, followed by NO2 (2.45%) and PM2.5 (1.72%). In contrast, O3 increase by 0.58% in southern Europe, leading to a surge in unclean air days. Despite air quality advances, 86.3% of Europeans experience at least one compound event day per year, especially for PM2.5-NO2 and PM2.5-O3. We highlight the improvements in air quality control but emphasize the need for targeted measures addressing specific pollutants and their compound events, particularly amidst rising temperatures.

Rational Design of a Necklace-like ZIF-67/Poly(vinylidene fluoride) Electrospun Nanofiber Hybrid Membrane for Simultaneous Removal of PM0.3 and SO2

Growing concerns over poor air quality, especially in urban and industrial regions, have led to increased global demands for advanced air-purification technologies. However, the stability and airborne pollutant control abilities of the available air-purification materials under diverse environmental conditions are limited. Thus, the advanced development of filtration materials that can effectively control different types of pollutants, such as particulate matter (PM) and gaseous pollutants, simultaneously has attracted attention. The zeolitic imidazolate framework (ZIF), a type of porous metal-organic framework (MOF), is a promising material for capturing weakly acidic toxic gases such as SO2 owing to its excellent adsorption performance and high thermal and chemical stability. In this study, we successfully developed an ultrastable necklace-like multifunctional hybrid membrane via the cetyltrimethylammonium bromide-assisted in situ growth of zeolitic imidazolate framework (ZIF)-67 crystals on electrospun Co2+-doped poly(vinylidene fluoride) nanofibers (70 nm) that can be used in different moisture environments to achieve sustainable air-filtration performance. The hybrid nanocomposite membrane demonstrated excellent performance for the simultaneous control of intractable fine PM0.3 (filtration efficiency, 99.461%) and SO2 (adsorption capacity, 1476.5 mg g-1) under different humidity conditions. This study contributes to the optimal synergistic integration of the advanced metal-organic framework (MOF)-nanofiber nanocomposite membranes and can guide the rational design and conceptualization of a facile and novel membrane for various applications in the environmental science and energy fields.

A bibliometric analysis of research on the health impacts of ozone air pollution

Ground-level ozone (O3) is one of the major air pollutants. A large body of literature has linked O3 air pollution to various adverse human health effects. The objective of this study is to attain a comprehensive and in-depth understanding of the progress and frontiers of research on O3 and human health. We used bibliometric methods to summarize publications on O3 air pollution and public health between 1990 and 2022 obtained from the Web of Science Core Collection database. VOSviewer and R software were used for bibliometric analysis and visualization. A total of 4501 relevant papers were included in the analysis. There has been a significant increase in the number of publications since 2013, with the USA being the major contributor, followed by China and England. Harvard University was the most prolific research institution, followed by the US Environmental Protection Agency and the University of North Carolina System. Professor Joel Schwartz was the most published author and has established a complex network of national and international collaborations. Co-occurrence analysis of keywords suggested evolving research hotspots, from toxicological studies to population-based epidemiological studies and from the respiratory system to the extra-pulmonary system. Research on O3 and its human health effects has progressed rapidly over the past few decades, but academic disparities still persist between developed and developing countries. There is an urgent need to strengthen international cooperation to address the public health challenges posed by rising O3 air pollution in the future.

2D MXenes and their composites; design, synthesis, and environmental sensing applications

Novel 2D layered MXene materials were first reported in 2011 at Drexel University. MXenes are widely used in multidisciplinary applications due to their anomalous electrical conductivity, high surface area, and chemical, mechanical, and physical properties. This review summarises MXene synthesis and applications in environmental sensing. The first section describes different methods for MXene synthesis, including fluorinated and non-fluorinated methods. MXene's layered structure, surface terminal groups, and the space between layers significantly impact its properties. Different methods to separate different MXene layers are also discussed using various intercalation reagents and commercially synthesized MXene without compromising the environment. This review also explains the effect of MXene's surface functionalization on its characteristics. The second section of the review describes gas and pesticide sensing applications of Mxenes and its composites. Its good conductivity, surface functionalization with negatively charged groups, intrinsic chemical nature, and good mechanical stability make it a prominent material for room temperature sensing of environmental samples, such as polar and nonpolar gases, volatile organic compounds, and pesticides. This review will enhance the young scientists' knowledge of MXene-based materials and stimulate their diversity and hybrid conformation in environmental sensing applications.

Spatiotemporal patterns of surface ozone exposure inequality in China

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 μg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 μg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

Spatiotemporal patterns and drivers of the urban air pollution island effect for 2273 cities in China

Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban-rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM2.5 and PM10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM2.5 and PM10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control.

Molecular modelling of fullerene C60 functionalized by nitric oxide for use in biological environment

The unique potential of fullerene C60 for various biological applications has ignited significant interest. However, its inherent non-polarity poses a critical challenge for its effective integration within biological systems. This study delves into the intricate physicochemical characteristics of the innovative [C60 + NO] complex using density functional theory and time-dependent density functional theory. The computational analyses encompass molecular charge, surface electrostatic potential, and dipole moment evaluations. Impressively, the dipole moment of the [C60 + NO] complex significantly increases to 12.92 D. Meticulous surface analysis reveals a subtle interplay between molecular structures, indicating weak interactions. The analysis of the absorption spectrum unveils a noteworthy red-shift of 200 nm subsequent to complex formation. To elucidate the electron transfer mechanisms, we explore photo-induced electron transfer through CAM-B3LYP. This exploration elucidates intricate pathways governing electron transfer, with complementary insights gleaned from Marcus theory's outputs, especially the Gibbs free energy of electron transfer. Changes in the physicochemical properties of approaching C60 and NO molecules reveal interesting results compared to separate molecules. These findings resonate profoundly in the context of potential biological and pharmaceutical utilization. With implications for the biomedical area, the outcomes linked to the [C60 + NO] complex kindle optimism for pioneering biomedical applications.

Community Health Risk Awareness and Knowledge of Air Pollution in Annadale, Polokwane Local Municipality, Limpopo Province, South Africa

Background

Exposure to air pollution has detrimental effects on the elderly, women, people with pre-existing medical conditions, people living in poverty and children. The aim of the study was to investigate the extent of community awareness and knowledge on the health risks associated with exposure to air pollution. The study was conducted at Annadale residential area locally known as Ladanna surrounded by industrial areas and located in Polokwane Local Municipality under Capricorn District Municipality in Limpopo Province, South Africa.

Methods

A cross-sectional study design was used for the study, using self-administered questionnaires. The questionnaire was pre-tested on 10 respondents at Emdo Park (Extension 29) in Polokwane from 02 to 06 February 2021 and another fifteen respondents were pre-tested at Lesedi Park. A simple random sampling technique was used to select 376 respondents. Systematic sampling method was applied to select the households. SPSS version 26 was used to analyze data. Data was presented in the form of frequencies and percentages. Spearman rank correlation was used to measure the degree of association between 2 variables. A Chi-square test was used to compare the groups between the categorical variables. Multivariate Logistic Regression Model was used to assess associations of knowledge/awareness outcomes and sociodemographic characteristics with odds ratios (ORs) and 95% confidence intervals (Cls) presented.

Results

Of 376 respondents, 221 (59%) were males and 154 (41%) females. The majority 113 (70%) of respondents were those between the age group 23 and 47 years and 353 (94%) were aware that if they don't protect themselves against polluted air, they may get sick, with age and educational status associated with their awareness (P < .05). About 361 (96%) knew what air pollution is and 188 (50%) think the air they breathe in Annadale is moderate. A total number of 278 (74%) said they feel sick/uncomfortable when the quality of air is bad. About 293 (78%) knew that people are exposed to air pollution by breathing contaminated air and 237 (63%) identified sewage smell as the main cause of air pollution. Internet 199 (53%) and television 177 (47%) were identified as the main source of information Those who were not aware of actions implemented to reduce air pollution were 180 (48%). Based on the results of the study, respondents' level of knowledge in Annadale was poor (71%) and their awareness was good (87%).

Conclusions

It is crucial that air pollution risk communication strategies be implemented to empower residents and improve the level of knowledge on the dangers of exposure to polluted air.

Residential Wood Combustion in Germany: A Twin-Site Study of Local Village Contributions to Particulate Pollutants and Their Potential Health Effects

Residential wood combustion contributing to airborne particulate matter (PM10) was studied for 1 year at two sites in the village of Melpitz. Significant excess pollution was observed at the Melpitz center compared to that at the TROPOS research station Melpitz reference site, situated only 700 m away. Local concentration increments at the village site for the combustion PM constituents organic carbon, elemental carbon, levoglucosan, and benzo[a]pyrene were determined under appropriate wind directions, and their winter mean values were 0.7 μg m-3, 0.3 μg m-3, 0.1 μg m-3, and 0.4 ng m-3, representing relative increases over the regional background concentration of 24, 70, 61, and 107%, respectively. Yearly, weekly, and diurnal profiles of village increments suggest residential heating as the dominant source of this excess pollution, mainly originating from wood combustion. Receptor modeling using positive matrix factorization quantified 4.5 μg m-3 wood combustion PM at the village site, representing an increment of 1.9 μg m-3 and an increase of ∼75% over the 2.6 μg m-3 regional background wood combustion PM. This increment varied with season, temperature, and boundary layer height and reached daily mean values of 4-6 μg m-3 during unfavorable meteorological conditions. Potential health effects were estimated and resulted in an all-cause mortality from short-term exposure to wood combustion PM of 2.1 cases per 100,000 inhabitants and year for areas with similar wood smoke levels as observed in Melpitz. The excess cancer risk from the concentrations of polycyclic aromatic hydrocarbons was 6.4 per 100,000. For both health metrics, the very local contributions from the village itself were about 40-50%, indicating a strong potential for mitigation through local-scale policies. A compilation of literature data demonstrates wood combustion to represent a major source of PM pollution in Germany, with average winter-time contributions of 10-20%. The present study quantifies the negative impacts of heating with wood in rural residential areas, where the continuous monitoring of air quality is typically lacking. Further regulation of this PM source is warranted in order to protect human health.

Achievements and challenges in improving air quality in China: Analysis of the long-term trends from 2014 to 2022

Due to the implementation of air pollution control measures in China, air quality has significantly improved, although there are still additional issues to be addressed. This study used the long-term trends of air pollutants to discuss the achievements and challenges in further improving air quality in China. The Kolmogorov-Zurbenko (KZ) filter and multiple-linear regression (MLR) were used to quantify the meteorology-related and emission-related trends of air pollutants from 2014 to 2022 in China. The KZ filter analysis showed that PM2.5 decreased by 7.36 ± 2.92% yr-1, while daily maximum 8-h ozone (MDA8 O3) showed an increasing trend with 3.71 ± 2.89% yr-1 in China. The decrease in PM2.5 and increase in MDA8 O3 were primarily attributed to changes in emission, with the relative contribution of 85.8% and 86.0%, respectively. Meteorology variations, including increased ambient temperature, boundary layer height, and reduced relative humidity, also contributed to the reduction of PM2.5 and the enhancement of MDA8 O3. The emission-related trends of PM2.5 and MDA8 O3 exhibited continuous decrease and increase, respectively, from 2014 to 2022, while the variation rates slowed during 2018-2020 compared to that during 2014-2017, highlighting the challenges in further improving air quality, particularly in simultaneously reducing PM2.5 and O3. This study recommends reducing NH3 emissions from the agriculture sector in rural areas and transport emissions in urban areas to further decrease PM2.5 levels. Addressing O3 pollution requires the reduction of O3 precursor gases based on site-specific atmospheric chemistry considerations.

Air pollution in major Polish cities in the period 2005-2021: Intensity, effects and attempts to reduce it

Air quality in Poland is among the lowest in Europe due to high emissions of harmful substances. This causes the development of diseases and leads to a high number of premature deaths. Particularly high pollution occurs in parts of urban areas. The most serious problem is unregulated emissions from buildings and vehicles. That is why it is so important to take action to improve air quality at the local level. The study assessed changes in the concentrations of NO2, O3, PM10, PM2.5 and benzo(a)pyrene in 11 major Polish cities between 2005 and 2021. In 2021 average levels were: NO2 - 25 μg/m3, O3 - 45 μg/m3, PM10 - 26 μg/m3, PM2.5 -17 μg/m3, benzo(a)pyrene - 2.1 ng/m3. The highest exceedances of WHO standards over the studied period were for PM2.5, followed by NO2 and PM10. The annual average levels fell by 17% for NO2 and by 18% for PM10 between 2005 and 2021, and by 34% for PM2.5 and 27% for benzo(a)pyrene between 2010 and 2021. The most polluted cities are Kraków, Katowice and Łódź. The highest concentrations of pollutants typically occurred in 2006 and 2011, the lowest in 2020. Strategic documents and programmes that formulate objectives for reducing emissions and improving air quality were evaluated. Policy documents enable numerous measures to improve air quality. Plans are not always effectively implemented due to a lack of formal tools and financial resources.

Increase in summertime ambient temperature is associated with decreased sick leave risk in Helsinki, Finland

OBJECTIVES

Climate change has increased attention to the health effects of high ambient temperatures and heatwaves worldwide. Both cause-specific mortality and hospital admissions are studied widely, mainly concentrating on warmer climates, but studies focusing on more subtle health effects and cold climates lack. This study investigated the effect of summertime daily ambient temperatures and heatwaves on sick leaves in the employed population in Helsinki, Finland, a Nordic country with a relatively cold climate.

METHODS

We obtained from the City of Helsinki personnel register data on sick leaves for the summer months (June-August) of 2002-2017. We estimated the overall cumulative association of all and short (maximum 3-day) sick leaves with daily mean temperature over a 21-day lag period using a negative binomial regression model coupled with a penalized distributed lag non-linear model (penalized DLNM). The association of sick leaves with heatwaves (cut-off temperature 20.8 °C), and prolonged heatwaves, was estimated using a negative binomial regression model coupled with DLNM. We adjusted the time series model for potential confounders, such as air pollution, relative humidity, time trends, and holidays.

RESULTS

Increasing daily temperature tended to be associated with decreased overall cumulative risk of sick leaves and short sick leaves over a 21-day lag period. In addition, heatwaves and prolonged heatwaves were associated with decreased overall cumulative risk of sick leaves compared to all other summer days: RR 0.87 (95 % CI 0.78 to 0.97) and RR 0.83 (95 % CI 0.70 to 0.98), respectively.

CONCLUSIONS

This research suggests that summertime daily temperatures that are high for this northern location have protective effects on the health of the working population.

Circadian rhythm disturbances involved in ozone-induced glucose metabolism disorder in mouse liver

Ozone (O3) is a key environmental factor for developing diabetes. Nevertheless, the underlying mechanisms remain unclear. This study aimed to investigate alterations of glycometabolism in mice after O3 exposure and the role of circadian rhythms in this process. C57BL/6 male mice were randomly assigned to O3 (0.5 ppm) or filtered air for four weeks (4 h/day). Then, hepatic tissues of mice were collected at 4 h intervals within 24 h after O3 exposure to test. The results showed that hepatic circadian rhythm genes oscillated abnormally, mainly at zeitgeber time (ZT)8 and ZT20 after O3 exposure. Furthermore, detection of glycometabolism (metabolites, enzymes, and genes) revealed that O3 caused change in the daily oscillations of glycometabolism. The serum glucose content decreased at ZT4 and ZT20, while hepatic glucose enhanced at ZT16 and ZT24(0). Both G6pc and Pck1, which are associated with hepatic gluconeogenesis, significantly increased at ZT20. O3 exposure disrupted glycometabolism by increasing gluconeogenesis and decreasing glycolysis in mice liver. Finally, correlation analysis showed that the association between Bmal1 and O3-induced disruption of glycometabolism was the strongest. The findings emphasized the interaction between adverse outcomes of circadian rhythms and glycometabolism following O3 exposure.

Data Gap: Air Quality Networks Miss Air Pollution from Concentrated Animal Feeding Operations

In the U.S., the agricultural sector is the largest controllable source of several air pollutants, including ammonia (NH3), which is a key precursor to PM2.5 formation. Livestock waste is the dominant contributor to ammonia emissions. In contrast to most controllable air pollutants, satellite records show ammonia mixing ratios are rising. The number of confined animal feeding operations (CAFOs) that generate considerable livestock waste is also increasing. Spatial and temporal trends in USDA-reported animal numbers normalized by county area at medium and large CAFOs provide plausible explanations for patterns in satellite-derived NH3 over the contiguous U.S. (CONUS). The correlation between summertime ammonia derived from the European Space Agency's (ESA) Infrared Atmospheric Sounding Interferometer (IASI) and CAFO animal unit density in 2017 is positive and significant (r = 0.642; p ≈ 0). The temporal changes from 2002 to 2017 in animal unit density and NH3 derived from NASA's Atmospheric Infrared Sounder (AIRS) are spatially similar. Trends and ambient concentrations of PM2.5 mass in agricultural regions are difficult to assess relative to those of urban population centers given the sparseness of rural monitors in regulatory surface networks. Results suggest that in agricultural areas where ammonia concentrations and animal density are highest, air quality improvement lags behind the national average.

Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

Applications of remote sensing vis-à-vis machine learning in air quality monitoring and modelling: a review

Environmental contamination especially air pollution is an exponentially growing menace requiring immediate attention, as it lingers on with the associated risks of health, economic and ecological crisis. The special focus of this study is on the advances in Air Quality (AQ) monitoring using modern sensors, integrated monitoring systems, remote sensing and the usage of Machine Learning (ML), Deep Learning (DL) algorithms, artificial neural networks, recent computational techniques, hybridizing techniques and different platforms available for AQ modelling. The modern world is data-driven, where critical decisions are taken based on the available and accessible data. Today's data analytics is a consequence of the information explosion we have reached. The current research also tends to re-evaluate its scope with data analytics. The emergence of artificial intelligence and machine learning in the research scenario has radically changed the methodologies and approaches of modern research. The aim of this review is to assess the impact of data analytics such as ML/DL frameworks, data integration techniques, advanced statistical modelling, cloud computing platforms and constantly improving optimization algorithms on AQ research. The usage of remote sensing in AQ monitoring along with providing enormous datasets is constantly filling the spatial gaps of ground stations, as the long-term air pollutant dynamics is best captured by the panoramic view of satellites. Remote sensing coupled with the techniques of ML/DL has the most impact in shaping the modern trends in AQ research. Current standing of research in this field, emerging trends and future scope are also discussed.

Impacts of net zero policies on air quality in a metropolitan area of the United Kingdom: Towards world health organization air quality guidelines

Climate change and air pollution are closely interlinked since carbon dioxide and air pollutants are co-emitted from fossil fuel combustion. Net Zero (NZ) policies aiming to reduce carbon emissions will likely bring co-benefits in air quality and associated health. However, it is unknown whether regional NZ policies alone will be sufficient to reduce air pollutant levels to meet the latest 2021 World Health Organisation (WHO) guidelines. Here, we carried out high resolution air quality modelling for in the West Midlands region, a typical metropolitan area in the UK, to quantify the effects of different NZ policies on air quality. Results show that NZ policies will significantly improve air quality in the West Midlands, with up to 6 μg m-3 (21%) reduction in annual mean NO2 (mostly through the electrification of vehicle fleet, EV) and up to 1.4 μg m-3 (12%) reduction in annual mean PM2.5 projected for 2030 relative to levels under a "business as usual" (BAU) scenario. Under BAU, 2030 PM2.5 concentrations in most wards would be below 10 μg m-3 whilst under the Net Zero scenario, those in all wards would be below 10 μg m-3. This means that the ward averages in the West Midlands would meet the UK PM2.5 of 10 μg m-3target a decade early under the Net Zero scenario. However, no ward-level-averaged annual mean PM2.concentrations meet the 2021 WHO Air Quality guideline level of 5 μg m-3 under any scenario. Similarly for NO2 only 18 wards (8% of the region's population) are predicted to have NO2 concentrations below the 2021 WHO guideline level (10 μg m-3). Decarbonisation policies linked to Net Zero deliver substantial regional air quality benefits, but are not in isolation sufficient to deliver clean air with air pollutant levels low enough to meet the 2021 WHO guidelines.

China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment

Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.

Summertime tropospheric ozone source apportionment study in the Madrid region (Spain)

The design of emission abatement measures to effectively reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions, and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditions and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQ v5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.

Surface ozone risk to human health and vegetation in tropical region: The case of Thailand

Tropospheric ozone (O3) is a threat to vegetation and human health over the world, in particular in Asia. Knowledge on O3 impacts on tropical ecosystems is still very limited. An O3 risk assessment to crops, forests, and people from 25 monitoring stations across the tropical and subtropical Thailand during 2005-2018 showed that 44% of sites exceeded the critical levels (CLs) of SOMO35 (i.e., the annual Sum Of daily maximum 8-h Means Over 35 ppb) for human health protection. The concentration-based AOT40 CL (i.e., sum of the hourly exceedances above 40 ppb for daylight hours during the assumed growing season) was exceeded at 52% and 48% of the sites where the main crops rice and maize are present, respectively, and at 88% and 12% of the sites where evergreen or deciduous forests are present, respectively. The flux-based metric PODY (i.e., Phytotoxic Ozone Dose above a threshold Y of uptake) was calculated and was found to exceed the CLs at 1.0%, 1.5%, 20.0%, 1.5%, 0% and 68.0% of the sites where early rice, late rice, early maize, late maize, evergreen forests, and deciduous forests can grow, respectively. Trend analysis indicated that AOT40 increased over the study period (+5.9% year-1), while POD1 decreased (- 5.3% year-1), suggesting that the role of climate change in affecting the environmental factors that control stomatal uptake cannot be neglected. These results contribute novel knowledge on O3 threat to human health, forest productivity, and food security in tropical and subtropical areas.

Climate change and mortality rates of COPD and asthma: A global analysis from 2000 to 2018

BACKGROUND

Climate change plays a significant role in global health threats, particularly with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma, but the long-term global-scale impact of climate change on these diseases' mortality remains unclear.

OBJECTIVE

This study aims to investigate the impact of climate change on the age-standardized mortality rates (ASMR) of COPD and asthma at national levels.

METHODS

We used Global Burden of Disease (GBD) data of ASMR of COPD and asthma from 2000 to 2018. The climate change index was represented as the deviance percentage of temperature (DPT) and relative humidity (DPRH), calculated based on 19-year temperature and humidity averages. Annual temperature, RH, and fine particulate matter (PM2.5) levels in 185 countries/regions were obtained from ERA5 and the OECD's environmental statistics database. General linear mixed-effect regression models were used to examine the associations between climate change with the log of ASMR (LASMR) of COPD and asthma.

RESULTS

After adjusting for annual PM2.5, SDI level, smoking prevalence, and geographical regions, a 0.26% increase in DPT was associated with decreases of 0.016, 0.017, and 0.014 per 100,000 people in LASMR of COPD and 0.042, 0.046, and 0.040 per 100,000 people in LASMR of asthma for both genders, males, and females. A 2.68% increase in DPRH was associated with increases of 0.009 and 0.011 per 100,000 people in LASMR of COPD. We observed a negative association of DPT with LASMR for COPD in countries/regions with temperatures ranging from 3.8 to 29.9 °C and with LASMR for asthma ranging from -5.3-29.9 °C. However, we observed a positive association of DPRH with LASMR for both COPD and asthma in the RH range of 41.2-67.2%.

CONCLUSION

Climate change adaptation and mitigation could be crucial in reducing the associated COPD and asthma mortality rates, particularly in regions most vulnerable to temperature and humidity fluctuations.

Air quality health index (AQHI) based on multiple air pollutants and mortality risks in Taiwan: Construction and validation

The currently used air quality index (AQI) is not able to capture the additive effects of air pollution on health risks and reflect non-threshold concentration-response relationships, which has been criticized. We proposed the air quality health index (AQHI) based on daily air pollution-mortality associations, and compared its validity in predicting daily mortality and morbidity risks with the existing AQI. We examined the excess risk (ER) of daily elderly (≥65-year-old) mortality associated with 6 air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) in 72 townships across Taiwan from 2006 to 2014 by performing a time-series analysis using a Poisson regression model. Random effect meta-analysis was used to pool the township-specified ER for each air pollutant in the overall and seasonal scenarios. The integrated ERs for mortality were calculated and used to construct the AQHI. The association of the AQHI with daily mortality and morbidity were compared by calculating the percentage change per interquartile range (IQR) increase in the indices. The magnitude of the ER on the concentration-response curve was used to evaluate the performance of the AQHI and AQI, regarding specific health outcomes. Sensitivity analysis was conducted using coefficients from the single- and two-pollutant models. The coefficients of PM2.5, NO2, SO2, and O3 associated with mortality were included to form the overall and season-specific AQHI. An IQR increase in the overall AQHI at lag 0 was associated with 1.90%, 2.96%, and 2.68% increases in mortality, asthma, and respiratory outpatient visits, respectively. The AQHI had higher ERs for mortality and morbidity on the validity examinations than the current AQI. The AQHI, which captures the combined effects of air pollution, can serve as a health risk communication tool to the public.

Machine learning model to predict vehicle electrification impacts on urban air quality and related human health effects

Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (-34% to -55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (-1 to -4% change in annual means of PM_2.5 and PM₁₀), 3) heterogeneous responses in ground-level ozone concentrations (-2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO₂-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.

Source-apportionment and spatial distribution analysis of VOCs and their role in ozone formation using machine learning in central-west Taiwan

This study assessed the machine learning based sensitivity analysis coupled with source-apportionment of volatile organic carbons (VOCs) to look into new insights of O₃ pollution in Yunlin County located in central-west region of Taiwan. One-year (Jan 1 to Dec 31, 2021) hourly mass concentrations data of 54 VOCs, NO_X, and O₃ from 10 photochemical assessment monitoring stations (PAMs) in and around the Yunlin County were analyzed. The novelty of the study lies in the utilization of artificial neural network (ANN) to evaluate the contribution of VOCs sources in O₃ pollution in the region. Firstly, the station specific source-apportionment of VOCs were carried out using positive matrix factorization (PMF)-resolving six sources viz. AAM: aged air mass, CM: chemical manufacturing, IC: Industrial combustion, PP: petrochemical plants, SU: solvent use and VE: vehicular emissions. AAM, SU, and VE constituted cumulatively more than 65% of the total emission of VOCs across all 10 PAMs. Diurnal and spatial variability of source-segregated VOCs showed large variations across 10 PAMs, suggesting for distinctly different impact of contributing sources, photo-chemical reactivity, and/or dispersion due to land-sea breezes at the monitoring stations. Secondly, to understand the contribution of controllable factors governing the O₃ pollution, the output of VOCs source-contributions from PMF model along with mass concentrations of NO_X were standardized and first time used as input variables to ANN, a supervised machine learning algorithm. ANN analysis revealed following order of sensitivity in factors governing the O₃ pollution: VOCs from IC > AAM > VE ≈ CM ≈ SU > PP ≈ NO_X. The results indicated that VOCs associated with IC (VOCs-IC) being the most sensitive factor which need to be regulated more efficiently to quickly mitigate the O₃ pollution across the Yunlin County.

Tijuca forest contribution to the improvement of air quality and wellbeing of citizens in the city of Rio de Janeiro, Brazil

The Tijuca Forest, one of the largest urban forests in the world, is a protected area of the Brazilian Atlantic Forest, one of the world's biodiversity hotspots. The forest and the Metropolitan Region of Rio de Janeiro coexist and interact, but their mutual influence regarding air quality is still not well known and a more detailed study is needed. Here, air samples were collected inside the forest, in Tijuca National Park (TNP) and Grajaú State Park (GSP) and in two representative urban areas (Tijuca and Del Castilho Districts). Sampling was performed using stainless steel canisters, and ozone precursor hydrocarbons (HCs) were analyzed with the aid of heart-cutting multidimensional gas chromatography. The sampling points within the forest are currently visited by hundreds of people. Total HC concentrations within the green area were clearly lower than in the urbanized districts, in spite of the anthropogenic impact of visitors and the proximity of the urban area. Median values were 21.5, 35.5, 57.9 and 148.6 μg m^-3 at TNP, GSP, Tijuca and Del Castilho, respectively. Total HC concentrations were Del Castilho > Tijuca > GSP > TNP. The kinetic reactivity and ozone-forming potential of individual HCs were evaluated, as well as the intrinsic reactivity of air masses. The air masses in the urbanized area showed a higher average reactivity in all scales. In fact, in spite of the forest's contribution to isoprene emissions, its net contribution to ozone formation was lower than that of urbanized air masses, owing to a reduction in HC concentration, particularly for alkenes and monoaromatic compounds. It is not clear if the forest plays a role in the adsorption of pollutants or if it acts as a physical natural barrier to air masses carrying pollutants. Nonetheless, improving air quality within Tijuca Forest is essential to the welfare of citizens.

Coagulation effect of atmospheric submicron particles on plant leaves: Key functional characteristics and a comparison with dry deposition

Submicron particles have become a new focus in research on air pollution control. The abilities of urban tree species to retain particles can be used to alleviate urban haze pollution. However, research has focused mostly on plants and environmental conditions rather than on particle itself. Particle migration and transformation at the leaf-air interface are the key to dust retention. Submicron particles coagulate when they are retained by leaves. In this study, NaCl was used to simulate submicron particles. The average sizes of the particles on the leaves of 10 greening tree species in Shanghai in different seasons were measured using the sweep-resuspension method to characterize the coagulation effect. Thereafter, the effects of leaf characteristics were investigated and analyzed in relation to dry deposition velocity. The results indicated that the particles on the leaves of Ginkgo biloba, Osmanthus fragrans, Sabina chinensis (L.) Ant. "Kaizuca," Cinnamomum camphora, and Metasequoia glyptostroboides were large. The seasonal variability of the sizes of the particles on the leaves of different tree species varied. The average particle size was positively correlated with wax content and negatively correlated with single leaf area; however, the other factors correlated with particle size varied by season. For example, in April, the average particle size was positively correlated with tensile strength, wind resistance, adaxial epidermal roughness, and water potential, whereas the effects of stomatal conductance were more complex. Non-significant correlation was identified between coagulation and dry deposition although both were positively correlated with roughness and wax content. This study explored the effects of leaf characteristics on coagulation. The results may serve as a theoretical foundation for explaining the microscopic process underlying dust retention in plants and may provide a clearer scientific basis for the prevention and control of submicron particle pollution and the selection of urban greening tree species.

The impact of pre-adulthood urbanicity on hippocampal subfield volumes and neurocognitive abilities in young adults

BACKGROUND

Urbanicity refers to the conditions that are particular to urban areas and is a growing environmental challenge that may affect hippocampus and neurocognition. This study aimed to investigate the effects of the average pre-adulthood urbanicity on hippocampal subfield volumes and neurocognitive abilities as well as the sensitive age windows of the urbanicity effects.

PARTICIPANTS AND METHODS

We included 5,390 CHIMGEN participants (3,538 females; age: 23.69 ± 2.26 years, range: 18-30 years). Pre-adulthood urbanicity of each participant was defined as the average value of annual night-time light (NL) or built-up% from age 0-18, which were extracted from remote-sensing satellite data based on annual residential coordinates of the participants. The hippocampal subfield volumes were calculated based on structural MRI and eight neurocognitive measures were assessed. The linear regression was applied to investigate the associations of pre-adulthood NL with hippocampal subfield volumes and neurocognitive abilities, mediation models were used to find the underlying pathways among urbanicity, hippocampus and neurocognition, and distributed lag models were used to identify sensitive age windows of urbanicity effect.

RESULTS

Higher pre-adulthood NL was associated with greater volumes in the left (β = 0.100, 95%CI: [0.075, 0.125]) and right (0.078, [0.052, 0.103]) fimbria and left subiculum body (0.045, [0.020, 0.070]) and better neurocognitive abilities in information processing speed (-0.212, [-0.240, -0.183]), working memory (0.085, [0.057, 0.114]), episodic memory (0.107, [0.080, 0.135]), and immediate (0.094, [0.065, 0.123]) and delayed (0.087, [0.058, 0.116]) visuospatial recall, and hippocampal subfield volumes and visuospatial memory showed bilateral mediations for the urbanicity effects. Urbanicity effects were greatest on the fimbria in preschool and adolescence, on visuospatial memory and information processing from childhood to adolescence and on working memory after 14 years.

CONCLUSION

These findings improve our understanding of the impact of urbanicity on hippocampus and neurocognitive abilities and will benefit for designing more targeted intervention for neurocognitive improvement.

Preliminary Air Quality and Microclimatic Conditions Study in the Santuario della Beata Vergine dei Miracoli in Saronno (VA)

In the present work, the microclimatic conditions (temperature (T), relative humidity (RH), and illuminance (I)), together with the air quality (both aerosol particulate matter (PM) and gaseous pollutants), were monitored to evaluate the environmental conditions inside the Santuario della Beata Vergine dei Miracoli in Saronno (VA), a masterpiece of the Italian Renaissance. For this purpose, dataloggers were used to carry out the T, RH, and I measurements, whereas an optical particle counter (OPC) was employed to perform the particle count and determine the concentration of the aerosol PM. Finally, diffusive passive samplers were used to determine the concentration of nitrogen dioxide (NO2) and BTEX (benzene, toluene, ethylbenzene, and xylenes). To identify possible spatial variations, the studies were conducted at different sites and different heights in the Sanctuary. Particular focus was given to the Easter week during which liturgical services attracting large numbers of people were carried out. Additionally, a comparison with the outdoor values was performed to highlight the accumulation phenomena and other variations in the concentrations of the species. Despite the indoor concentrations of pollutants and variations in the thermohygrometric parameters being generally lower compared to the outdoors (e.g., 5.2-15.0 µg m-3 versus 17.7-45.3 µg m-3 for NO2), the microclimatic conditions were often not in line with the Italian legislation and technical standards.