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

Vertical variations of ozone transport flux at multiple altitudes and identification of major transport direction in the North China Plain

The North China Plain (NCP) frequently experiences ozone pollution events, which are generally related to cross-border transport at multiple scales. However, current methods of calculating ozone transport are insufficient to account for ozone transport at different altitudes. To further understand the characteristics of ozone transport, we applied the Weather Research and Forecasting (WRF) model and the Comprehensive Air Quality Model with Extensions (CAMx) based on flux calculation method. The results showed that the simulated flux calculation method was suitable for revealing the evolutionary trend of ozone fluxes. Monthly inflows, outflows, and total net fluxes ranged from -32985.45 to 37361.46 t/d and indicated strong transport and significant spatial and temporal variations of ozone in the urban boundary segments. Vertical distribution analysis of the net ozone fluxes demonstrated that the net fluxes varied with the altitude, and the altitude at which the corresponding peaks were located had a strong correlation with the neighborhood and season. It was noteworthy that there were three main transport directions throughout the year, namely northwest-southeast (NW-SE), southeast-northwest (SE-NW), and southwest-northeast (SW-NE). Additionally, the ozone flux was mainly affected by temperature, wind speed, and ozone concentration, with the correlation coefficient varying by season and altitude, up to 0.78. Moreover, the correlation analysis of ozone flux and wind direction in each city further verified the accuracy of the transport direction. This paper can provide scientific and technological support for the study of ozone generation mechanisms and the solution of urban/interregional ozone pollution problems.

Assessing the impact of traffic restriction interventions on school air quality: a citizen science-based modelling study

Air pollution poses a significant threat to human health, especially for the vulnerable groups such as children. Given that schools are central to their daily lives, ensuring good air quality in these environments is crucial. This study evaluates the impact of traffic restriction interventions around schools by integrating citizen science monitoring data with advanced modeling techniques. From February 4 to March 4, 2023, within the framework of a citizen science project called "NO2, No Grazie!", NO2 concentrations were measured in Milan and Rome (Italy), Italy's two most populated cities, both affected by high traffic-related pollution, using passive samplers. The spatial distribution of NO2 across entire city territories was estimated using Land Use Random Forest (LURF) models. Four traffic restriction scenarios were developed alongside a business-as-usual one; furthermore, each school was characterized by the social vulnerability of its area. In total, 486 samplers were analyzed in Milan and 407 in Rome, with NO2 levels averaging 47.1 μg/m3 and 42.6 μg/m3, respectively. LURF models explained 64 % and 53 % of the measured variability, with traffic proximity as a major predictor. Among 659 schools in Milan and 1595 in Rome, all traffic restriction scenarios led to significant NO2 reductions. The most effective scenario reduced NO2 by 2.7 μg/m3 in Milan and 1.9 μg/m3 in Rome on average, with maximum observed decreases of 11.1 μg/m3 and 16.1 μg/m3, respectively. Schools in socioeconomically deprived areas had lower NO2 levels and were less impacted by the restrictions. The study underscores the value of traffic policies in improving air quality around schools.

Assessing the contribution of urban green space landscape patterns to ozone concentration variations

The relationship between urban green space (UGS) and ozone (O3) distributions has attracted increasing attention because of its implications for urban planning and pollution management. Despite the recognized role of UGS in regulating O3 concentration levels, the specific influence of UGS landscape patterns on O3 heterogeneity across different spatiotemporal scales remains unclear. This study addresses this gap by analyzing data from 53 monitoring stations across five major cities in northern China. Employing linear mixed-effects and GeoDetector models, we investigated how UGS landscape patterns influence O3 concentrations at different scales and in different seasons. Our findings show that O3 concentrations are positively correlated with UGS area. However, the homogeneity and aggregation of UGS landscapes can reduce the O3-enhancing effects of UGS, and this efficiency is influenced by the season and scale. Seasonal variations have a greater impact on O3 concentrations than scales. Moreover, the nonlinear enhancements of UGS landscape metrics on O3 concentrations indicate that the synergistic effect of different UGS landscape patterns are crucial for understanding the spatial heterogeneity in O3 pollution. Our results highlight that a 2 km neighborhood scale is the optimal scale of the UGS landscape patterns to regulate O3 concentration, which was associated with a 2.98 ± 5.2 % reduction in the O3 concentration. The primary contribution of this study is its comprehensive analysis of the multiscale effects of UGS on O3 concentrations, providing valuable insights for urban planners and policymakers aiming to mitigate O3 pollution through strategic planning of UGS.

Evaluating the health impact of air pollution control strategies and synergies among PM2.5 and O3 pollution in Beijing-Tianjin-Hebei region, China

Since 2013, China has implemented a series of strict Air Pollution Control Strategies (APCS) to mitigate environmental and health risks associated with ambient fine particulate matter (PM2.5). However, while APCS sets clear targets for PM2.5 concentration, it lacks quantitative control over O3 levels. Most existing studies have focused on nation-wide health assessments. Therefore, by conducting a coupled framework using health assessment and decomposition method, the spatiotemporal variation in deaths attributable to PM2.5 pollution, as well as the role of APCS and the synergies between PM2.5 and O3 on PM2.5 concentration and health impacts in the Beijing-Tianjin-Hebei (BTH) region have been explored. The result showed that: (1) PM2.5 concentration in the BTH region decreased by 68.2%, with a reduction of 45,833 (95% Confidence Interval [CI]: 33,808, 50,069) deaths over the period. However, both concentrations and mortality remained high, indicating a need for faster reductions. (2) End-of-pipe control contributed the most to reducing PM2.5 concentrations and deaths, though the gaps between source control and end-of-pipe control is narrowing. (3) The synergistic effects of O3 and PM2.5 in reducing concentration and mortality have increased, becoming a significant driver of PM2.5-related health impacts. Our study emphasizes the future importance of implementing refined, diverse emission reduction measures and coordinating efforts to reduce both O3 and PM2.5 emissions, which are crucial for achieving the Sustainable Development Goals (SDGs) and advancing the "Beautiful China" and "Healthy China" initiatives.

Long-term joint exposure of outdoor air pollutants and impaired kidney function in Korean adults: A mixture analysis based on a nationwide sample (2007-2019)

We explored the association between exposure to air pollutant mixture and renal function. A nationwide sample of 69,066 Korean adults was analyzed. The 1-year moving averages of the concentrations of PM10, PM2.5, SO₂, NO₂, CO, and O₃ were estimated using the air pollution modeling. The outcome was estimated glomerular filtration rate (eGFR) value. Quantile-based G-computation analyses were performed to determine how a simultaneous increase in the air pollutant mixture by one quartile was associated with changes in eGFR levels. The mean of eGFR was 88.9 among the sample. In the quantile-based G-computation model, one-quartile increase in the levels of air pollutant mixture was linked to a decrease in eGFR by -0.85 (95 % CI: -1.14, -0.57), with CO and PM2.5 contributing 52.3 % and 37.3 %, respectively, to the negative association between the pollutant mixture and eGFR. Our results suggest that long-term exposure to air pollutant mixtures is linked to impaired renal function.

Tracking air pollution and CO2 emissions in 13,189 urban areas worldwide using large geospatial datasets

Air pollution and climate change are urgent global concerns, with urban areas contributing heavily to both air pollutants and greenhouse gas emissions. Here we calculate fine particulate matter, nitrogen dioxide, and ozone concentrations and fossil-fuel carbon dioxide emissions per capita in 13,189 urban areas worldwide from 2005 to 2019 and analyze correlations between trends for these pollutants, leveraging recently-developed global datasets. Globally, we found significant increases in ozone (+6%) and small, non-significant changes in fine particulate matter (+0%), nitrogen dioxide (-1%), and fossil-fuel carbon dioxide emissions (+4%). Also, over 50% of urban areas showed positive correlations for all pollutant pairs, though results varied by global region. High-income countries with strong mitigation policies experienced decreases in all pollutants, while regions with rapid economic growth had overall increases. This study shows the impacts of urban environmental initiatives in different regions and provides insights for reducing air pollution and carbon dioxide emissions simultaneously.

Uncovering key sources of regional ozone simulation biases using machine learning and SHAP analysis

Atmospheric chemical transport models (CTMs) are widely used in air quality management, but still have large biases in simulations. Accurately and efficiently identifying key sources of simulation biases is crucial for model improvement. However, traditional approaches, such as sensitivity and uncertainty analyses, are computationally intensive and inefficient, as they require numerous model runs. In this study, we explored the use of machine learning, specifically XGBoost combined with SHAP analysis, as an efficient diagnostic tool for analyzing simulation biases, focusing on ozone modeling in Guangdong Province as a case study. We used the bias of model inputs as features and excluded a dataset that was more susceptible to observational uncertainties to better target bias sources. Results reveal that biases in concentrations of NO2, NO and PM2.5, temperature and biogenic emissions are important sources that lead to O3 simulation biases. Notably, NOx emissions were identified as the primary cause, particularly in VOC-limited regimes during autumn and winter. Additionally, underestimated NOx emissions caused the model to misrepresent the NO2-O3 relationship, leading to an underestimation of the spatial extent of VOC-limited regimes in the PRD. This study demonstrates that enhancing NOx emission estimates reduces O3 simulation biases in the PRD by 34% and enhances the representation of the NO2-O3 relationship.

Ozone exposure induced kidney damage in diabetic mice: The key role of lipid metabolism and water-electrolyte homeostasis

Ozone (O3) is an important environmental pollutant that has garnered growing public concern. Epidemiological studies indicate that exposure to O3 is associated with an elevated risk of kidney disease, a common complication of diabetes. However, the harmful effects of O3 on the kidneys remain unconfirmed. Herein, we established models of non-diabetic and diabetic mice exposed to 0.5 ppm O3 for 28 days (4 h/day). We evaluated O3-induced renal injury and potential mechanisms through analyzing biochemical markers related to renal function, along with histopathology and transcriptomic sequencing of the kidneys. The results showed that O3 exposure caused glomerular hypertrophy in both non-diabetic and diabetic mice, with mesangial hypercellularity and kidney function impairment specifically in diabetic mice. Furthermore, renal levels of free fatty acids and cholesterol were significantly elevated in O3-exposed diabetic mice. The important roles of lipid and water-electrolyte metabolism related pathways in O3-induced kidney damage were found by transcriptome sequencing analysis. The mRNA and/or protein expressions of some genes involved in β-ENaC and AQP2 pathways, which are related to renal water and sodium retention, were changed in diabetic mice following O3 exposure by real-time quantitative PCR, immunofluorescence staining, and Western blotting. Overall, diabetic mice exhibited a higher vulnerability to adverse effects in the kidney after O3 exposure than non-diabetic mice. Dysregulation of lipid metabolism and imbalance in water-electrolyte homeostasis have been discovered as key contributing mechanisms. This study offers valuable insights into mechanisms through which ambient O3 poses renal health risks to both the general subjects and susceptible individuals.

Assessment of disease burden and mortality attributable to air pollutants in northwestern Iran using the AirQ+ software

It is well known that one of the main causes of mortality and reduced life expectancy is air pollution, which carries the highest burden of diseases attributed to environmental factors. The poor air quality in Iranian cities leads to a wide range of acute and chronic health effects. This study estimates the natural deaths, ALRI, COPD, lung cancer, IHD, and strokes caused by air pollutants in Bukan, a southern city in West Azerbaijan Province, from 2011 to 2019. Population data was obtained from government organizations, and pollutant data for 2011-2019 was collected from the Bukan Environmental Protection Organization. Analyses were performed using Excel, and the data was subsequently entered into the WHO's AirQ+ model to extract the results. The study found that long-term exposure to PM10, PM2.5, NO2, and O3 resulted in an estimated 316, 241, 14, and 52 deaths, respectively. By comparing the air quality over the 8-year period, it was determined that the air quality in Bukan city is not in good condition, with particulate matter levels exceeding relevant standards. Given the increasing trend of air pollution and associated health impacts, it is essential to implement effective control policies to improve the city's air quality. This information provides a crucial step for city managers, policymakers, and health officials to mitigate the health effects caused by air pollution.

Plasma-Treated Nanostructured Resistive Gas Sensors: A Review

Resistive gas sensors are among the most widely used sensors for the detection of various gases. In this type of gas sensor, the gas sensing capability is linked to the surface properties of the sensing layer, and accordingly, modification of the sensing surface is of importance to improve the sensing output. Plasma treatment is a promising way to modify the surface properties of gas sensors, mainly by changing the amounts of oxygen ions, which have a central role in gas sensing reactions. In this review paper, we focus on the role of plasma treatment in the gas sensing features of resistive gas sensors. After an introduction to air pollution, toxic gases, and resistive gas sensors, the main concepts regarding plasma are presented. Then, the impact of plasma treatment on the sensing characteristics of various sensing materials is discussed. As the gas sensing field is an interdisciplinary field, we believe that the present review paper will be of significant interest to researchers with various backgrounds who are working on gas sensors.

Perceived-air pollution and self-reported health status: a study on air pollution-prone urban area of Bangladesh

Air pollution is a serious health concern in rapidly developing countries like Bangladesh. This study investigates the correlation between self-reported health issues related to air pollution and perceived air pollution among adult Bangladeshis. A face-to-face questionnaire was conducted with 398 adult residents who had lived in their current location for at least 3 years. The survey assessed self-reported health using 13 specific air pollution-related health problems. A linear regression model was then used to analyze factors affecting air pollution-related health status. Our findings reveal correlations between perceived air pollution and health issues. 90% of respondents reported air-polluted environments in their area, with the majority citing multiple sources (42%) of air pollution. Construction activities emerged as a predominant concern, identified by 31% of participants as a primary source of air pollution. Demographic factors play a crucial role in contributing to air pollution-related health problems. Notably, older age groups reported significantly higher health issues compared to their younger counterparts. Residents of Mirpur's residential neighborhood experienced fewer health problems related to air pollution, indicating the influence of urban planning on public health. This interdisciplinary approach offers a comprehensive view of Bangladesh's air pollution crisis, combining environmental science and public health perspectives. The findings emphasize the need for targeted policy interventions, including stricter regulations on construction activities to mitigate their impact on air quality, tailored public health interventions for vulnerable populations (especially older adults), and urban planning strategies that reduce exposure to air pollution in residential areas. Future research should investigate the long-term health impacts of chronic air pollution exposure and evaluate the effectiveness of various mitigation strategies. Addressing these issues can help create healthier, more resilient urban environments.

Artificial intelligence: A key fulcrum for addressing complex environmental health issues

Environmental health (EH) is a complex and interdisciplinary field dedicated to the examination of environmental behaviours, toxicological effects, health risks, and strategies for mitigating harmful environmental factors. Traditional EH research investigates correlations between risk factors and health outcomes through control variables, but this route is difficult to address complex EH issue. Artificial intelligence (AI) technology not only has accelerated the innovation of the scientific research paradigm but also has become an important tool for solving complex EH problems. However, the in-depth and comprehensive implementation of AI in the field of EH still faces many barriers, such as model generalizability, data privacy protection, algorithm transparency, and regulatory and ethical issues. This review focuses on the compound exposures of EH and explores the potential, challenges, and development directions of AI in four key phases of EH research: (1) data collection, fusion, and management, (2) hazard identification and screening, (3) risk modeling and assessment and (4) EH management. It is not difficult to see that in the future, artificial intelligence technology will inevitably carry out multidimensional simulation of complex exposure factors through multi-mode data fusion, so as to achieve accurate identification of environmental health risks, and eventually become an efficient tool for global environmental health management. This review will help researchers re-examine this strategy and provide a reference for AI to solve complex exposure problems.

Effects of elevated atmospheric ozone concentration on biomass and non-structural carbohydrates allocation of cherry radish

Regional increases in atmospheric O3 have phytotoxicity due to its strong oxidizing properties. Cherry radish (Raphanus sativus L.), with its sensitivity to O3 and rapid growth cycle, serves as an excellent model for investigating the effects of elevated O3 on plant physiological responses. To determine the response of cherry radish to elevated O3 levels, we used nine open-top chambers with three O3 concentrations (Ambient-LO; 70 ppb O3 above ambient-MO; 140 ppb O3 above ambient-HO) in Beijing, China to examine the MDA, chlorophyll contents, biomass, soluble sugar, and starch contents in response to O3 exposure. The results showed that: 1) elevated O3 (EO3) did not affect leaf chlorophyll contents but increased carotenoid contents; (2). The total biomass, hypocotyl biomass and hypocotyl size were significantly decreased by 41% and 49%, 51% and 37%, 53% and 40% by MO and HO, respectively. The above-to-below-ground biomass ratio (A/B) increased by 49% and 61% under MO and HO treatments; (3). HO and MO significantly increased leaf fructose, sucrose, and glucose contents by 192% and 79%, 40% and 37%, 110% and 45%, respectively; (4). leaf soluble sugar biomass proportion increased by 75% and 99% under HO and MO mainly contributed by fructose biomass proportion increase; (5). radish plant allocated more soluble sugar, starch and NSC biomass proportion to leaf but not hypocotyl under EO3. In conclusion, radishes exposed to O3 allocate more nonstructural carbohydrates (NSC) to the leaf at the expense of a great loss of hypocotyl biomass. This is possible mainly due to compensation of O3-induced damage via the sugar transport pathways, where transport is blocked so that the inefficient conversion of soluble sugars into starch can lead to reduced biomass accumulation and ultimately lower crop yields of radish. The role of radish fructose in protecting against or responding to O3 risks may be underestimated as it affects the overall sugar metabolism and transport within the plant.

dilp2-Mediated Insulin Signaling Pathway Was Involved in O3-Induced Multigenerational Effects of Shortened Lifespan in Drosophila melanogasters

As a long-standing atmospheric pollutant, ozone (O3) exerts enduring effects on biological health. However, experimental research on its impact on organism lifespan and generational effects is limited. This study exposed three generations of fruit flies (Drosophila melanogaster) to O3, revealing a shortened lifespan across generations. Specifically, after O3 exposure, the lifespan of the F2 generation was significantly reduced compared with F0 and F1 generations, indicating a cumulative multigenerational effect. Transcriptome analysis unveiled significant disruptions in metabolic pathways, notably the insulin signaling pathway. Subsequent qRT-PCR analysis showed elevated mRNA levels of insulin pathway-related genes (dilp2, dilp3, dilp5, InR, and TOR), alongside decreased expression levels of FOXO, 4E-BP, and Atg5 in flies exposed to O3. Notably, knocking down dilp2, rather than dilp3, dilp5, and InR, rescued the O3-induced lifespan shortening. Overall, O3 exposure triggered activation of the dilp2-mediated InR-FOXO/TOR-4E-BP-Atg5 signaling pathway, potentially contributing to shortened lifespan with cumulative effects. This study highlights the viability of employing fruit flies as a model to evaluate the multigenerational toxicity of environmental pollutants, particularly atmospheric pollutants.

Ozone concentration, physical activity, and emotional and behavioral problems in children and adolescents

BACKGROUND

No prior study has examined the mutual association of long-term outdoor ozone (O3) concentration and physical activity (PA) with emotional and behavioral problems (EBPs) in children and adolescents. This study aims to investigate the association between long-term outdoor O3 concentration and the risk of EBPs in children and adolescents and further explore whether increased PA levels modify this association.

METHODS

Data were obtained from the 2020 wave follow-up examination of an ongoing prospective cohort study (COHERENCE project) in Guangzhou, China. A total of 419,033 children aged 6-17-year-old were included. Annual average outdoor O3 concentrations were obtained from the China High Air Pollutants (CHAP) dataset based on participants' residential addresses. PA levels were identified using the International Physical Activity Questionnaire Short Form (IPAQ). EBPs were assessed by the Chinese Parent-Report Strengths and Difficulties Questionnaire (SDQ-P).

RESULTS

Each interquartile range (IQR) increase in outdoor O3 concentration was associated with an increased odds ratio (OR) for abnormal emotional problems (OR: 1.024, 95% CI: 1.010-1.038), conduct problems (OR: 1.015, 95% CI: 1.002-1.029), peer relationship problems (OR: 1.029, 95% CI: 1.006-1.052), prosocial behavior (OR: 1.023, 95% CI: 1.012-1.034), total difficulties (OR: 1.024, 95% CI: 1.010-1.038), and internalizing behavior (OR: 1.039, 95% CI: 1.026-1.053), in fully adjusted models. The highest OR for abnormal EBPs was observed in children with low PA levels, in combination with high O3 concentration.

CONCLUSION

This study identified that long-term outdoor O3 concentration is associated with an increased risk of EBPs in children and adolescents, with higher PA levels attenuating these risks.

Disentangling Multiannual Air Quality Profiles Aided by Self-Organizing Map and Positive Matrix Factorization

The evaluation of air pollution is a critical concern due to its potential severe impacts on human health. Currently, vast quantities of data are collected at high frequencies, and researchers must navigate multiannual, multisite datasets trying to identify possible pollutant sources while addressing the presence of noise and sparse missing data. To address this challenge, multivariate data analysis is widely used with an increasing interest in neural networks and deep learning networks along with well-established chemometrics methods and receptor models. Here, we report a combined approach involving the Self-Organizing Map (SOM) algorithm, Hierarchical Clustering Analysis (HCA), and Positive Matrix Factorization (PMF) to disentangle multiannual, multisite data in a single elaboration without previously separating the sites and years. The approach proved to be valid, allowing us to detect the site peculiarities in terms of pollutant sources, the variation in pollutant profiles during years and the outliers, affording a reliable interpretation.

Advanced statistical analysis of air quality and its health impacts in India: Quantifying significance by detangling weather-driven effects

Air quality has emerged as a significant concern due to its direct impact on human health. Over recent decades, India has witnessed a marked deterioration in air quality due to rising anthropogenic emissions and climate change. The COVID-19 lockdown offered a unique opportunity to examine air pollutant reductions under restricted human activities. This study conducted a long-term analysis of air quality in five major Indian cities-Delhi, Kolkata, Bengaluru, Hyderabad, and Visakhapatnam-by analysing variations in PM2.5, PM10, NOx, NH3, SO2, CO, and O3, incorporating a de-weathering strategy to isolate meteorological influences. In Delhi, we observed significant reductions in PM10 (92.50-136.70 μg/m³), NOx (62.13-151.91 ppb), and CO (0.53-0.88 mg/m³), which shifted health risks from the 'extreme' to 'low' category. Visakhapatnam also experienced notable declines in NOx levels (7.50-17.13 ppb). Conversely, Hyderabad exhibited no significant reductions, and AQHI increased (+0.97) due to rising NOx concentrations. Ozone concentrations showed a significant increase across cities, attributed to VOC-limited effects. The analysis revealed that meteorological variability and long-range transport of airmass played critical roles in shaping pollutant concentrations. These findings highlight the complexity of urban air quality dynamics and underscore the benefits of emission reductions for public health.

Estimating the Risk of Women Anemia Associated with Ozone Exposure Across 123 Low- and Middle-Income Countries: A Multicenter Epidemiological Study

Anemia in women of reproductive age (WRA) presents a pressing global public health issue, particularly in low- and middle-income countries (LMICs). Yet, the potential impact of ozone (O3) exposure on anemia remains uncertain. The study included 1,467,887 eligible women from 83 surveys of 45 LMICs between 2004 to 2020. Monthly O3 exposure was estimated using machine learning, with the year preceding the survey as the primary exposure window. Fixed-effects models evaluated the association between O3 and anemia. An exposure-response function (ERF) was constructed using a varying-coefficient regression model, and then extrapolated to estimate the anemia burden in relation to O3 in 123 LMICs. In the fully adjusted regression model, each 10 ppb increase in annual O3 concentration was associated with an 8% elevation in anemia risk. The nonlinear ERF indicated a threshold effect of O3 on anemia at approximately 47.2 ppb. In 2020, more than 7.6 million anemic WRA (1.58%) in 123 LMICs were associated with O3 exposure. The potentially attributable burden has generally decreased from 2004 to 2020, notably in South Asia. Our findings highlight the importance of air pollution mitigation in LMICs to address anemia disparities among women.

Association of short-term air pollution with risk of major adverse cardiovascular event mortality and modification effects of lifestyle in Chinese adults

BACKGROUND

Previous evidence showed that ambient air pollution and cardiovascular mortality are related. However, there is a lack of evidence towards the modification effect of long-term lifestyle on the association between short-term ambient air pollution and death from cardiovascular events.

METHOD

A total of 14,609 death from major adverse cardiovascular events (MACE) were identified among the China Kadoorie Biobank participants from 2013 to 2018. Ambient air pollution exposure including particulate matter 2.5 (PM2.5), SO2, NO2, CO, and O3 from the same period were obtained from space-time model reconstructions based on remote sensing data. Case-crossover design and conditional logistic regression was applied to estimate the effect of short-term exposure to air pollutants on MACE mortality.

RESULTS

We found MACE mortality was significantly associated with PM2.5 (relative percent increase 2.91% per 10 µg/m3 increase, 95% CI 1.32-4.53), NO2 (5.37% per 10 µg/m3 increase, 95% CI 1.56-9.33), SO2 (6.82% per 10 µg/m3 increase, 95% CI 2.99-10.80), and CO (2.24% per 0.1 mg/m3 increase, 95% CI 1.02-3.48). Stratified analyses indicated that drinking was associated with elevated risk of MACE mortality with NO2 and SO2 exposure; physical inactivity was associated with higher risk of death from MACE when exposed to PM2.5; and people who had balanced diet had lower risk of MACE mortality when exposed to CO and NO2.

CONCLUSIONS

The study results showed that short-term exposure to ambient PM2.5, NO2, SO2, and CO would aggravate the risk of cardiovascular mortality, yet healthy lifestyle conduct might mitigate such negative impact to some extent.

Chromatin Immunoprecipitation Assays of Histone Modifications in Daphnia magna

Daphnia magna is a widely distributed freshwater planktonic crustacean that has been extensively used as a model organism in ecotoxicological studies, due to its sensitivity to environmental pollutants. It has recently received enough attention as a model organism to study transgenerational epigenetic mechanisms, owing to its ability to reproduce via parthenogenesis. This unique ability of D. magna to generate clonal offspring makes it an ideal model organism to study how environmental cues-including environmental pollutants-can affect the epigenome of future generations. This is important since several of these cues can have a profound impact on behavior and other phenotypes such as disease mechanisms in mammals. Chromatin immunoprecipitation (ChIP) assays have proved to be essential tools in the field of epigenetics, namely, for their ability to study in a quantitative fashion the genomic localization of numerous chromatin epigenetic marks such as histone posttranslational modifications and histone variants. However, there are few studies that document the use of ChIP assays in D. magna. Here, we describe in detail an optimized protocol for ChIP assays in whole Daphnia organisms that is suitable to study histone posttranslational modifications as well as several potential epigenetic regulators.Running title: ChIP in Daphnia magna.

Comprehensive health risk assessment of urban ambient air pollution (PM2.5, NO2 and O3) in Ghana

Urbanization and industrialization have drastically increased ambient air pollution in urban areas globally from vehicle emissions, solid fuel combustion and industrial activities leading to some of the worst air quality conditions. Air pollution in Ghana causes approximately 28,000 premature deaths and disabilities annually, ranking as a leading cause of mortality and disability-adjusted life years. This study evaluated the annual concentrations of PM2.5, NO2 and O3 in the ambient air of 57 cities in Ghana for two decades using historical and forecasted data from satellite measurements. The study assessed urban air quality and evaluated both carcinogenic and non-carcinogenic health risks associated with human exposure to ambient air pollutants. Alarmingly, our findings revealed the yearly median PM2.5 concentrations (50.79-67.97 µg m-3) to be significantly higher than the WHO recommendation of 5 µg m-3. Tropospheric ozone concentrations (72.21-92.58 µg m-3 ) also exceeded the WHO annual standard of 60 µg m-3. Furthermore, NO2 concentrations (3.65-12.15 µg m-3 ) surpassed the WHO threshold of 10 µg/m³ in multiple cities. Hazard indices indicated that PM2.5 and O3 pose significant non-carcinogenic health risks for younger age groups for a daily exposure duration of three hours and beyond. According to the Air Quality Life Index (AQLI) in our study, exposure to PM2.5 shortens life expectancy by 4.5-6.2 years. The ambient air of the majority (98 %) of the cities was unhealthy for sensitive groups. This study reveals the urgent need for comprehensive air quality policies in Ghanaian cities. It emphasizes the significance of robust real-time monitoring of air pollutants and the investigation of seasonal dust storm effects, to fill data gaps in Ghana and West Africa, facilitating evidence-based interventions that improve urban air quality and public health outcomes.

Determination of the sensing properties of the fluorescence-based sensor for atmospheric NO2 gas

Air pollution in urban areas poses a serious threat to human health and therefore the studies about the development of low cost and sensitive sensors to monitor the air quality with high spatial and low temporal resolution continue to be an extensive area in literature. In this study, oxime modified poly(4-(1-pyrenyl) styrene) (P(PySt)-NOX) probes were synthesized to use as a sensor to detect NO2 gas in ambient air. The structural characterization results showed that the probe was successfully synthesized. The sensitivity, selectivity, repeatability, and aging tests were performed during the study, and it was observed that P(PySt)-NOX loaded sensor is sensitive to NO2 for concentrations below 100 ppb. The selectivity measurements were performed against O3 and SO2 which are common interfering gases in ambient air, and it was shown that the sensor is selective to NO2. Additionally, according to the aging tests performed in laboratory for 23 days, it was observed that the sensor is stable in this time interval. The studies showed the sensor synthesized and designed in this study is suitable for NO2 concentration measurements in ambient air where the concentration levels of NO2 is below 100 ppb.

Spatio-temporal variability and trends of air pollutants in the Metropolitan Area of Curitiba

Monitoring air pollutants over time is essential for identifying and addressing trends, which may help improve air quality management and safeguard public health. This study investigates the spatio-temporal variability of air quality in the Metropolitan Area of Curitiba (MAC), Brazil, focusing on six pollutants (SO2, NO2, NOx, O3, CO, and PM10) measured at eight monitoring stations from 2003 to 2017. We conducted statistical analyses, including diurnal cycles, seasonal variability, spatio-temporal correlations, conditional bivariate probability functions, Theil-Sen trend analysis, and comparison with national quality standards (NAQS) and World Health Organization (WHO) guidelines. The analyses revealed large variations in pollutant concentrations across the study area. For instance, stations strongly impacted by industrial emissions presented the highest mean annual SO2 (20-28 μg/m3) and PM10 (32-34 μg/m3) concentrations, while those mostly impacted by traffic showed elevated NO2 (31-39 μg/m3), NOx (63-86 μg/m3) and CO (0.6-0.8 mg/m3) concentrations. The two residential stations recorded the highest O3 concentrations (annual mean of 30-32 μg/m3). Seasonal and diurnal patterns varied by pollutant, with winter experiencing higher concentrations and O3 peaking in spring. SO2 concentrations presented no clear seasonal or diurnal cycle patterns, and showed the highest spatial variability. Significant decreasing annual trends were observed for SO2 (-5.9%), NO2 (-2.6%), NOx (-2.6%), CO (-5.4%), and PM10 (-3.7%), which suggests the success of emission reduction programs implemented in the road transportation and industrial sectors. However, O3 concentrations increased at most stations (+3.3%/yr), likely due to reduced NOx emissions, increased emissions of volatile organic compounds from on-road transport biofuels, and regional O3 transport. Although exceedances of NAQS decreased over time, concentrations of most pollutants remained above WHO guidelines, except for CO. These results highlight the importance of targeted emission control strategies for both industrial and vehicular sources to improve local air quality and inform future policy decisions.

A Review of Urban Planning Approaches to Reduce Air Pollution Exposures

PURPOSE OF REVIEW

With only 12% of the human population living in cities meeting the air quality standards set by the WHO guidelines, there is a critical need for coordinated strategies to meet the requirements of a healthy society. One pivotal mechanism for addressing societal expectations on air pollution and human health is to employ strategic modeling within the urban planning process. This review synthesizes research to inform coordinated strategies for a healthy society. Through strategic modeling in urban planning, we seek to uncover integrated solutions that mitigate air pollution, enhance public health, and create sustainable urban environments.

RECENT FINDINGS

Successful urban planning can help reduce air pollution by optimizing city design with regard to transportation systems. As one specific example, ventilation corridors i.e. aim to introduce natural wind into urban areas to improve thermal comfort and air quality, and they can be effective if well-designed and managed. However, physical barriers such as sound walls and vegetation must be carefully selected following design criteria with significant trade-offs that must be modeled quantitatively. These tradeoffs often involve balancing effectiveness, cost, aesthetics, and environmental impact. For instance, sound walls are highly effective at reducing noise, provide immediate impact, and are long-lasting. However, they are expensive to construct, visually unappealing, and may block views and sunlight. To address the costly issue of sound walls, a potential solution is implementing vegetation with a high leaf area index or leaf area density. This alternative is also an effective method for air pollution reduction with varying land-use potential. Ultimately, emission regulations are a key aspect of all such considerations. Given the broad range of developments, concerns, and considerations spanning city management, ventilation corridors, physical barriers, and transportation planning, this review aims to summarize the effect of a range of urban planning methods on air pollution considerations.

Ozone trends and their sensitivity in global megacities under the warming climate

Tropospheric ozone formation depends on the emissions of volatile organic compounds (VOC) and nitrogen oxides (NOx). In megacities, abundant VOC and NOx sources cause relentlessly high ozone episodes, affecting a large share of the global population. This study uses data from the Ozone Monitoring Instrument for formaldehyde (HCHO) and nitrogen dioxide (NO2) as proxy data for VOC and NOx emissions, respectively, with their ratio serving as an indicator of ozone sensitivity. Ground-level ozone (O3) reanalysis from the Copernicus Atmosphere Monitoring is used to assess the O3 trends. We evaluate changes from 2005 to 2019 and their relationship with the warming environment in 41 megacities worldwide, applying seasonal Mann-Kendall, trend decomposition methods, and Pearson correlation analysis. We reveal significant increases in global HCHO (0.1 to 0.31 × 1015 mol cm-2 year-1) and regionally varying NO2 (-0.22 to 0.07 × 1015 mol cm-2 year-1). O3 trends range from -0.31 to 0.70 ppb year-1, highlighting the relevance of precursor abundance on O3 levels. The strong correlation between precursor emissions and increasing temperature suggests that O3 will continue to rise as climate change persists.

Estimation of plant pollution removal capacity based on intensive air quality measurements

This study investigated the role of present vegetation in improving air quality in Bucharest (Romania) by analyzing six years of air quality data (PM10 and NO2) from multiple monitoring stations. The target value for human health protection is regularly exceeded for PM10 and not for NO2 over time. Road traffic has substantially contributed (over 70%) to ambient PM10 and NO2 levels. The results showed high seasonal variations in pollutant concentrations, with a pronounced effect of vegetation in reducing PM10 and NO2 levels. Indeed, air quality improvements of 7% for PM10 and 25% for NO2 during the growing season were reported. By using Principal Component Analysis and pollution data subtraction methodology, we have disentangled the impact of vegetation on air pollution and observed distinct annual patterns, particularly higher differences in PM10 and NO2 concentrations during the warm season. Despite limitations such as a lack of full tree inventory for Bucharest and a limited number of monitoring stations, the study highlighted the efficiency of urban vegetation to mitigate air pollution.

Differences of stomatal ozone uptake in leaves of mature trees and seedlings of Zelkova serrata

Ozone uptake through the stomata in tree leaves is an important process for improving air quality by urban trees. Stomatal conductance (gs) is a key determinant of stomatal ozone uptake. The parameterization of gs models for estimating stomatal ozone uptake of trees has mainly been carried out using gs data measured in seedling leaves although the leaf traits may differ between mature trees and seedlings. In the present study, we compared stomatal ozone uptake estimated by gs models parameterised with data from mature trees and seedlings of Zelkova serrata. We measured gs in leaves of mature trees and seedlings of Z. serrata using a leaf porometer for 3-4 growing seasons. The Jarvis-type gs model was parameterised with data from mature trees and seedlings, separately. The maximum gs, and the functions of the seedling gs estimation model regarding the response to air temperature, vapour pressure deficit and atmospheric ozone concentration were the factors inducing lower stomatal ozone uptake. In contrast, the function of the seedling gs estimation model regarding the response to irradiance resulted in a higher estimated stomatal ozone uptake. The estimated stomatal ozone uptake for one growing season (April-September) by the seedling gs estimation model was 27% lower than that by the mature tree gs estimation model. These results indicate that leaf gas exchange traits of Z. serrata were different between mature trees and seedlings, and that estimating ozone uptake in mature tree leaves using a model based on seedling gs measurements results in an underestimation.

Strategies to reduce air pollution emissions from urban residential buildings

As cities continue to grow, developing mitigation strategies is crucial to minimize the corresponding increase in air pollutants. One source of potentially controllable air pollution is the emissions from residential buildings. We conducted a literature review to systematically examine air pollution emissions from residential buildings in urban areas, identifying pollutants and their sources; investigated mitigation-aimed intervention types by field of application or study, and finally listed and discussed strategies to reduce the concentration of air pollutants in residential buildings. Our compilation shows that among the nature-based solutions, green walls offered the highest relative reduction of air pollution (-15 % NO2 and -23 % PM10). Of the construction-based solutions, already-available photocatalytic paint can achieve reductions of 25 % NO, 23 % NOx and 19 % NO2 as is. Industrial-based solutions promise high levels of reduction, but these must be adapted to residential buildings. The integration of various existing and potentially adapted mitigation solutions may achieve even higher pollution reduction rates in urban areas.

Spatial associations of daily PM2.5 concentration with cardiovascular and pulmonary morbidity in Korea

Air pollution, particularly fine particulate matter less than 2.5 μm in diameter (PM2.5), contributes to respiratory and cardiovascular diseases and poses significant public health risks worldwide. This study evaluated the short-term effects of PM2.5 on hospital admissions for cardiovascular and respiratory diseases, with additional analyses to identify vulnerable populations based on regional characteristics. The present study analyzed data from 249 Korean communities between 2006 and 2021. Data on daily hospital admissions for cardiovascular and respiratory diseases were obtained from the National Health Insurance Service. Data on PM2.5 concentrations were sourced from air quality modeling. Additional data on regional characteristics, including the regional deprivation index, proportion of elderly residents, education levels, and greenness levels, were also collected. We used case time series analysis to assess the associations between PM2.5 concentrations and hospital admissions for cardiovascular and respiratory diseases and explored effect modification by regional characteristics with stratified analyses. The mean numbers of daily cardiovascular admissions and respiratory admissions were 5.68 ± 5.46 and 6.46 ± 8.03, respectively. The mean PM2.5 concentrations were 23.58 ± 13.66 μg/m3. A10 μg/m³ increment in daily PM2.5 concentration was associated with increase of cardiovascular and respiratory hospitalization by 0.94% (95% CI: 0.84%, 1.04%) and 1.43% (95% CI: 1.34%, 1.52%), respectively. Regional characteristics analysis showed significant disparities, with higher risks for hospital admissions in areas with lower deprivation and low greenness. This study highlights the significant short-term health impacts of PM2.5 on respiratory and cardiovascular hospital admissions in Korean communities. The findings underscore the critical role of regional and demographic factors in modulating these effects, identifying socio-economic areas, age structure of the population, lower education levels, and low greenness as key vulnerability factors.

Scalable pilot production of highly efficient 5-ply respiratory masks enhanced by bacterial cellulose nanofibers

This study presents the pilot-scale production of highly efficient real respiratory masks enhanced by bacterial cellulose nanofibers (BCNFs). The BCNFs suspension was deposited onto tissue paper substrates using fog spray technique with three BCNFs grammage levels of 0.5, 1, and 2 g/m2, followed by freeze drying. Also, two continuous and batch welding processes have been used to construct the core structure of the masks. Field emission scanning electron microscopy (FE-SEM) confirmed the uniform distribution and size of fog-sprayed BCNFs and their pore networks. With increase in BCNFs grammage, the adsorption efficiency of masks increased in both continuous and batch production methods. The mask produced through batch processing showed the highest efficiency of 99.2 % (N99) for the particulate matter of 0.3 μm, while the maximum corresponding efficiency value in continuous processing was 95.4 % (N95). The pressure drops of the masks increased with the increase in BCNFs grammage in both methods. The maximum pressure drops of N95 and N99 masks obtained were 112 ± 10 Pa and 128 ± 8 Pa, respectively. Notably, the filtration efficacy of masks was preserved when subjected to relative humidity fluctuations ranging from 30 % to 70 %. The successful findings of this study offer significant promise for future air filtration applications.

Analyzing and forecasting air pollution concentration in the capital and Southern Thailand using a lag-dependent Gaussian process model

The air pollution problem has now amassed worldwide attention due to its multifaceted harm to human health. Exploring the concentration of air pollution and improving forecast have important consideration worldwide. In this research, we analyze the air pollution concentration of Southern Thailand and compare it with the central region. Also, we proposed a methodology based on the lag-dependent Gaussian process (LDGP), a Bayesian non-parametric machine learning model, with a stable optimization approach, which is a cluster-based multi-starter technique based on the Nelder-Mead optimizer. This model also provides the confidence band for forecasted values. We also used autoregressive deep neural network (AR-DNN), autoregressive random forest (AR-RF), gradient boosting (GB), and K-nearest neighbors (KNN) models. A comparison of the proposed methodology was performed on the daily air pollution data collected from the southern provinces and also from the capital of Thailand from 1 January 2018 to 31 December 2022. We used well-established performance evaluation measures to compare the performance of the models. To evaluate the bias due to overfit, we performed a tenfold cross-validation for all the pollutants in each region and compared the models to choose the best one. Moreover, we explored the concentration of air pollution in these regions. Results of descriptive analysis revealed that Bangkok had a much higher concentration of air pollution as compared to the southern region. However, the southern region had higher exposure to PM air pollutants as per WHO recommendations and also had higher exposure to O3 and CO levels. The proposed LDGP model outperformed the other machine learning models for forecasting all air pollutants. Hence, it is recommended to be used by experts for further research and studies with different kernel functions. This research is also expected to contribute to local government planning and prevention and worldwide use of the same methodology for the sustainability of public health.

A co-created citizen science project on the short term effects of outdoor residential woodsmoke on the respiratory health of adults in the Netherlands

BACKGROUND AND AIM

Woodsmoke from household fireplaces contributes significantly to outdoor air pollution in the Netherlands. The current understanding of the respiratory health effects of exposure to smoke from residential wood burning is limited. This study investigated the association between short-term changes in outdoor woodsmoke exposure and lung function, respiratory symptoms, and medication use in adults in the Netherlands.

METHODS

This study was co-created with citizen scientists and other relevant stakeholders. A panel study was conducted with repeated observations in 46 adults between February and May 2021 in four Dutch towns. Participants recorded their symptoms and medication use in daily diaries, and conducted morning and evening home spirometry measurements. Woodsmoke exposure was characterized by measuring levoglucosan (most specific marker for woodsmoke exposure), black/brown carbon, fine and ultrafine particulate matter at central monitoring sites. Individual woodsmoke perception (smell) was recorded in daily diaries. Linear and logistic regression models were used to investigate the association between respiratory health and woodsmoke exposure. Models were adjusted for time-varying confounders and accounted for repeated observations within participants.

RESULTS

Consistent positive associations were found between levoglucosan and shortness of breath (SOB) during rest and extra respiratory medication use. Odds ratios for current day exposure to levoglucosan were 1.12 (95% CI: 0.97, 1.30) for SOB during rest and 1.19 (95% CI: 1.07, 1.33) for extra medication use, expressed per interquartile range of levoglucosan concentrations (69.16 ng/m3). Positive non-significant associations were found between levoglucosan and nasal symptoms, cough and waking up with SOB. No consistent association was found between levoglucosan and lung function. Associations found between woodsmoke markers, SOB during rest and extra medication use remained after the inclusion of PM2.5 and UFP in two-pollutant models.

CONCLUSIONS

Adults experienced more SOB during rest, nasal symptoms and used more medication to treat respiratory symptoms on days with higher levels of outdoor woodsmoke concentrations.

Investigating the Synergistic Effect of Decoration and Doping in Silver/Strontium Titanate for Air Remediation

Strontium titanate (STO) and its variants have emerged as leading materials in photocatalysis, particularly for degrading nitrogen oxides (NOx), due to their non-toxic nature, structural adaptability, and exceptional thermal stability. Although the one-pot sol-gel method leads to high-quality photocatalysts, areas remain for improvement. This study examines the impact of ethanol as a cosolvent in STO synthesis, focusing on optimizing the water-to-ethanol volume ratio. The findings reveal that a 1:3 ratio significantly enhances macropore formation and photocatalytic efficiency, achieving 42% NOx degradation under LED within three hours. Furthermore, incorporating 8.0 wt.% Ag into STO substantially improves visible light absorption and enables complete NOx elimination, thanks to enhanced charge separation and localized surface plasmon resonance. Even at high temperatures (1100 °C), the Ag-STO photocatalyst maintains partial activity, despite exceeding silver's melting point. These results highlight the potential of STO-based materials for industrial applications, positioning them as a promising solution for effective NOx mitigation.

Individual and joint associations of air pollutants exposure with semen quality: A retrospective longitudinal study in Wenzhou, China

PURPOSE

The impact of air pollution on semen quality has been confirmed, yet the joint effect remains unclear. We evaluate the individual and joint associations of particulate (PM2.5 and PM10) and gaseous pollutants (NO2, SO2, O3 and CO) with semen quality.

METHODS

We included 5,114 men in this study from 2014 to 2022. The individual and joint associations were measured by multiple linear regression models.

RESULTS

Sperm motility and semen volume were inversely associated with pollutant concentrations during every stage of sperm development, especially at lag days 0-9 and 10-14 (all P < 0.05). Stratified analyses showed that the study pollutants (except CO) had a positive effect on semen concentration during the stage of sperm development, especially in spring and autumn, while a decreased total sperm number was associated with CO (all P < 0.05). However, joint associations of particulate and gaseous pollutants with semen quality parameters were not statistically significant (all P > 0.05).

CONCLUSIONS

During all stages of sperm development, particulate and gaseous pollutants had individual negative impacts on sperm motility and semen volume, and these impacts were less pronounced in spring and autumn. Our findings highlight the importance and necessity of reducing the exposure to pollutants especially in the critical stage of sperm development to improve semen quality.

Long term analysis of air quality parameters for Ludhiana, India: sources, trends and health impact

Ludhiana, a pollution hot spot in North India, has seen a rapid deterioration in air quality over the years due to urbanization and industrialization. This study interprets the variations of particulate matter (PM) and gaseous pollutants (Nitrogen oxide, Nitrogen dioxide, NOX, Sulphur dioxide, Carbon monoxide, Benzene, Toluene, Ozone, and Ammonia) for the data observed from 2017 to 2023 in Ludhiana. This also covers the analysis focused on capturing the changes that occurred at the times of lockdown imposed during the Coronavirus Disease (COVID-19). The maximum 24-h averaged mass concentration values exceeded the National Ambient Air Quality Standards (NAAQS) of 100 µg/m3 for PM10 concentration and 60 µg/m3 for PM2.5 concentration in 2018 by the factor of 5 and 8. With the onset of the COVID-19 lockdown in 2020 year, PM10 and PM2.5 reached the minimum level while CO, T, O3, and NO2 increased by the factor of 3.9, 1.9, 1.4, and 1.3 from their previous year. This NO2 is a precursor of ozone formation, a higher NO2 to NO ratio observed during the lockdown, confirms the role of nitrogen compounds in the higher ozone formation rate. Based on the NO2/NO ratio, the probability rate of ozone formation determined using survival analysis is observed to be 94% from 2017 to 2023. The local sources' contribution to these air pollutants during Pre-Lockdown, Lockdown, and Post-Lockdown are analyzed using principal component analysis. The impact of the lockdown on ozone concentration sources has been observed. During the Pre- and Post-Lockdown phases, three sources (PC1, PC2, and PC3) were positively identified. Ozone levels are linked to PC3 in these phases, but during the lockdown, a negative loading in PC3 and positive loadings in PC1 and PC2 indicate a decrease in ozone from reduced emissions and an increase from secondary reactions involving nitrogen compounds. Moreover, the Toluene to Benzene concentration ratio is > 2, indicating the source of their origin from industrial emission or other non-traffic sources. Health assessment for the years 2017-2019 reveals a significant decrease in the number of cases of all-cause mortality, ischemic heart disease, stroke, and chronic obstructive pulmonary disease associated with reducing PM2.5 concentrations to national and international standards.

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.

Synergistic PM2.5 and O3 control to address the emerging global PM2.5-O3 compound pollution challenges

In recent years, the issue of PM2.5-O3 compound pollution has become a significant global environmental concern. This study examines the spatial and temporal patterns of global PM2.5-O3 compound pollution and exposure risks, firstly at the global and urban scale, using spatial statistical regression, exposure risk assessment, and trend analyses based on the datasets of daily PM2.5 and surface O3 concentrations monitored in 120 cities around the world from 2019 to 2022. Additionally, on the basis of the common emission sources, spatial heterogeneity, interacting chemical mechanisms, and synergistic exposure risk levels between PM2.5 and O3 pollution, we proposed a synergistic PM2.5-O3 control framework for the joint control of PM2.5 and O3. The results indicated that: (1) Nearly 50% of cities worldwide were affected by PM2.5-O3 compound pollution, with China, South Korea, Japan, and India being the global hotspots for PM2.5-O3 compound pollution; (2) Cities with PM2.5-O3 compound pollution have exposure risk levels dominated by ST + ST (Stabilization) and ST + HR (High Risk). Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries, with unequal exposure characteristics; (3) The selected cities showed significant positive spatial correlations between PM2.5 and O3 concentrations, which were consistent with the spatial distribution of the precursors NOx and VOCs; (4) During the study period, 52.5% of cities worldwide achieved synergistic reductions in annual average PM2.5 and O3 concentrations. The average PM2.5 concentration in these cities decreased by 13.97%, while the average O3 concentration decreased by 19.18%. This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low-carbon transition.

Spatial spillover effect and driving factors of urban carbon emissions in the Yellow River Basin using nighttime light data

Yellow River Basin (YRB) is a pivotal region for energy consumption and carbon emissions (CEs) in China, with cities emerging as the main sources of regional CEs. This highlights their critical role in achieving regional sustainable development and China's carbon neutrality. Consequently, there is a pressing need for a detailed exploration of the urban spillover effects and an in-depth analysis of the complex determinants influencing CEs within the YRB. Remote sensing data provide optimal conditions for conducting extensive studies across large geographical areas and extended time periods. This study integrates DMSP/OLS and NPP/VIIRS nighttime light datasets for a longitudinal analysis of urban CEs in the YRB. Using a harmonized dataset from DMSP/OLS and NPP/VIIRS nighttime light from 2007 to 2021, this study quantifies CEs of 58 prefecture-level cities in the YRB. By combining ESDA, STIRPAT model and spatial econometric model, this investigation further clarifies empirically the spatial spillover effects and driving factors of urban CEs. The analysis delineates a phase-wise augmentation in urban CEs, converging towards a distinct spatial distribution characterized by "lower reach > middle reach > upper reach". The spatial autocorrelation tests unravel a complex interplay between agglomeration and differentiation patterns within urban CEs, underscored by pronounced spatial lock-in phenomena. Significantly, this study demonstrates that urbanization, economic development, energy consumption structure, green coverage rate, industrial structure, population, technological progress, and FDI each exhibit varied direct and indirect effect on urban CEs. Furthermore, it elaborates on potential policy implications and future research directions, offering crucial insights for formulating CEs mitigation strategies to advance sustainable development.

Multi-component liquid-infused systems: a new approach to functional coatings

Antifouling liquid-infused surfaces have generated interest in multiple fields due to their diverse applications in industry and medicine. In nearly all reports to date, the liquid component consists of only one chemical species. However, unlike traditional solid surfaces, the unique nature of liquid surfaces holds the potential for synergistic and even adaptive functionality simply by including additional elements in the liquid coating. In this work, we explore the concept of multi-component liquid-infused systems, in which the coating liquid consists of a primary liquid and a secondary component or components that provide additional functionality. For ease of understanding, we categorize recently reported multi-component liquid-infused surfaces according to the size of the secondary components: molecular scale, in which the secondary components are molecules; nanoscale, in which they are nanoparticles or their equivalent; and microscale, in which the additional components are micrometer size or above. We present examples at each scale, showing how introducing a secondary element into the liquid can result in synergistic effects, such as maintaining a pristine surface while actively modifying the surrounding environment, which are difficult to achieve in other surface treatments. The review highlights the diversity of fabrication methods and provides perspectives on future research directions. Introducing secondary components into the liquid matrix of liquid-infused surfaces is a promising strategy with significant potential to create a new class of multifunctional materials. Keywords: Active surfaces; Antimicrobial; Antifouling; Interfaces; Sensing surfaces.

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.

Predicting tropospheric nitrogen dioxide column density in South African municipalities using socio-environmental variables and Multiscale Geographically Weighted Regression

Atmospheric nitrogen dioxide (NO2) pollution is a major health and social challenge in South African induced mainly by fossil fuel combustions for power generation, transportation and domestic biomass burning for indoor activities. The pollution level is moderated by various environmental and social factors, yet previous studies made use of limited factors or focussed on only industrialised regions ignoring the contributions in large parts of the country. There is a need to assess how socio-environmenral factors, which inherently exhibit variations across space, influence the pollution levels in South Africa. This study therefore aimed to predict annual tropospheric NO2 column density using socio-environmental variables that are widely proven in the literature as sources and sinks of pollution. The environmental variables used to predict NO2 included remotely sensed Enhanced Vegetation Index (EVI), Land Surface Temperature and Aerosol Optical Depth (AOD) while the social data, which were obtained from national household surveys, included energy sources data, settlement patterns, gender and age statistics aggregated at municipality scale. The prediction was accomplished by applying the Multiscale Geographically Weighted Regression that fine-tunes the spatial scale of each variable when building geographically localised relationships. The model returned an overall R2 of 0.92, indicating good predicting performance and the significance of the socio-environmental variables in estimating NO2 in South Africa. From the environmental variables, AOD had the most influence in increasing NO2 pollution while vegetation represented by EVI had the opposite effect of reducing the pollution level. Among the social variables, household electricity and wood usage had the most significant contributions to pollution. Communal residential arrangements significantly reduced NO2, while informal settlements showed the opposite effect. The female proportion was the most important demographic variable in reducing NO2. Age groups had mixed effects on NO2 pollution, with the mid-age group (20-29) being the most important contributor to NO2 emission. The findings of the current study provide evidence that NO2 pollution is explained by socio-economic variables that vary widely across space. This can be achieved reliably using the MGWR approach that produces strong models suited to each locality.

Environmental remediation of emerging contaminants using subcritical water: A review

The continuous rise of emerging contaminants (ECs) in the environment has been a growing concern due to their potentially harmful effects on humans, animals, plants, and aquatic life, even at low concentrations. ECs include human and veterinary pharmaceuticals, hormones, personal care products, pesticides, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organic dyes, heavy metals (HMs), and others. The world's growing population contributes to the release of many kinds of chemicals into the environment, which is estimated to be more than 200 billion metric tons annually and results in over 9 million deaths. The removal of these contaminants using conventional physical, chemical, and biological treatments has proven to be ineffective, highlighting the need for simple, effective, inexpesive, practical, and eco-friendly alternatives. Thus, this article discusses the utilization of subcritical water oxidation (SBWO) and subcritical water extraction (SBWE) techniques to remove ECS from the environment. Subcritical water (water below the critical temperature of 374.15 °C and critical pressure of 22.1 Mpa) has emerged as one of the most promising methods for remediation of ECs from the environment due to its non-toxic properties, simplicity and efficiency of application. Furthermore, the impact of temperature, pressure, treatment time, and utilization of chelating agents, organic modifiers, and oxidizing agents in the static and dynamic modes was investigated to establish the best conditions for high ECs removal efficiencies.

Yearly change in air pollution and brain aging among older adults: A community-based study in Taiwan

BACKGROUND

Air pollution is recognized as a modifiable risk factor for dementia, and recent evidence suggests that improving air quality could attenuate cognitive decline and reduce dementia risk. However, studies have yet to explore the effects of improved air quality on brain structures. This study aims to investigate the impact of air pollution reduction on cognitive functions and structural brain differences among cognitively normal older adults.

METHODS

Four hundred and thirty-one cognitively normal older adults were from the Epidemiology of Mild Cognitive Impairment study in Taiwan (EMCIT), a community-based cohort of adults aged 60 and older, between year 2017- 2021. Annual concentrations of PM2.5, NO2, O3, and PM10 at participants' residential addresses during the 10 years before enrollment were estimated using ensemble mixed spatial models. The yearly rate of change (slope) in air pollutants was estimated for each participant. Cognitive functions and structural brain images were collected during enrollment. The relationships between the rate of air pollution change and cognitive functions were examined using linear regression models. For air pollutants with significant findings in relation to cognitive function, we further explored the association with brain structure.

RESULTS

Overall, all pollutant concentrations, except O3, decreased over the 10-year period. The yearly rates of change (slopes) in PM2.5 and NO2 were correlated with better attention (PM2.5: r = -0.1, p = 0.047; NO2: r = -0.1, p = 0.03) and higher white matter integrity in several brain regions. These regions included anterior thalamic radiation, superior longitudinal fasciculus, inferior longitudinal fasciculus, corticospinal tract, and inferior fronto-occipital fasciculus.

CONCLUSIONS

Greater rate of reduction in air pollution was associated with better attention and attention-related white matter integrity. These results provide insight into the mechanism underlying the relationship between air pollution, brain health, and cognitive aging among older adults.

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.

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.

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.

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.

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.