The contribution of outdoor air pollution sources to premature mortality on a global scale

Assessment of the Relationship Between Genetic Determinants of Obesity, Unhealthy Eating Habits and Chronic Obstructive Pulmonary Disease: A Mendelian Randomisation Study

Background: Clinical studies have shown that the onset and exacerbation of chronic obstructive pulmonary disease (COPD) are related to obesity and dietary behaviours, but the genetic relationship between them is not clear.Aims: To investigate the relationship between the genetic determinants of obesity, dietary habits (alcohol consumption, intake of sweets, salt intake) and COPD.Methods: Exposure and outcome datasets were obtained from the IEU Open GWAS project. The exposure dataset includes dietary habits (Salt added to food, Sweets intake, Alcohol consumption), obesity level (represented by body mass index (BMI) and body fat percentage (BFP) data sets.). The outcome dataset includes COPD and acute COPD admissions. The collected data were imported into the RStudio software and conducted Mendelian randomisation analysis. Additionally, heterogeneity and horizontal pleiotropy tests were conducted on the data to ensure the veracity of the results.Results: The results showed that BMI was positively correlated with the risk of acute COPD admission (OR = 1.74, 95% CI 1.39-2.18) and COPD (OR = 1.81, 95%CI 1.41-2.33). In addition, BFP was also a risk factor for COPD (OR = 1.98, 95% CI 1.42-2.77) and acute exacerbation of COPD admission (OR = 1.99, 95%CI 1.43-2.77). The increase of salt, sugar and alcohol consumption will not increase the risk of COPD and the risk of hospitalisation due to COPD.Conclusion: Therefore, we should strengthen the guidance of diet and living habits of obese patients. For patients with heavier weight and higher body fat rate, they should be instructed to lose weight and fat to prevent the occurrence of COPD. For obese patients with COPD, more attention should be paid to prevent the occurrence of acute exacerbation of COPD in advance.

Health risks and sources of trace elements and black carbon in PM2.5 from 2019 to 2021 in Beijing

A comprehensive health risk assessment of PM2.5 is meaningful to understand the current status and directions regarding further improving air quality from the perspective of human health. In this study, we evaluated the health risks of PM2.5 as well as highly toxic inorganic components, including heavy metals (HMs) and black carbon (BC) based on long-term observations in Beijing from 2019 to 2021. Our results showed that the relative risks of chronic obstructive pulmonary disease, lung cancer, acute lower respiratory tract infection, ischemic heart disease, and stroke decreased by 4.07%-9.30% in 2020 and 2.12%-6.70% in 2021 compared with 2019. However, they were still at high levels ranging from 1.26 to 1.77, in particular, stroke showed the highest value in 2021. Mn had the highest hazard quotient (HQ, from 2.18 to 2.56) for adults from 2019 to 2021, while Ni, Cr, Pb, As, and BC showed high carcinogenic risks (CR > 1.0×10-6) for adults. The HQ values of Mn and As and the CR values of Pb and As showed constant or slight upwards trends during our observations, which is in contrast to the downward trends of other HMs and PM2.5. Mn, Cr, and BC are crucial toxicants in PM2.5. A significant shrink of southern region sourcesof HMs and BCshrank suggests the increased importance of local sources. Industry, dust, and biomass burning are the major contributors to the non-carcinogenic risks, while traffic emissions and industry are the dominant contributors to the carcinogenic risks in Beijing.

Biogenic volatile organic compounds dominated the near-surface ozone generation in Sichuan Basin, China, during fall and wintertime

The complex air pollution driven by both Ozone (O3) and fine particulate matter (PM2.5) significantly influences the air quality in the Sichuan Basin (SCB). Understanding the O3 formation during autumn and winter is necessary to understand the atmospheric oxidative capacity. Therefore, continuous in-site field observations were carried out during the late summer, early autumn and winter of 2020 in a rural area of Chongqing. The total volatile organic compounds (VOCs) concentration reported by a Proton-Transfer-Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS) were 13.66 ± 9.75 ppb, 5.50 ± 2.64 ppb, and 9.41 ± 5.11 ppb in late summer, early autumn and winter, respectively. The anthropogenic VOCs (AVOCs) and biogenic VOCs (BVOCs) were 8.48 ± 7.92 ppb and 5.18 ± 2.99 ppb in late summer, 3.31 ± 1.89 ppb and 2.19 ± 0.93 ppb in autumn, and 6.22 ± 3.99 ppb and 3.20 ± 1.27 ppb in winter. A zero-dimensional atmospheric box model was employed to investigate the sensitivity of O3-precursors by relative incremental reactivity (RIR). The RIR values of AVOCs, BVOCs, carbon monoxide (CO), and nitrogen oxides (NOx) were 0.31, 0.71, 0.09, and -0.36 for late summer, 0.24, 0.59, 0.22, and -0.38 for early autumn, and 0.30, 0.64, 0.33 and -0.70 for winter, and the results showed that the O3 formation of sampling area was in the VOC-limited region, and O3 was most sensitive to BVOCs (with highest RIR values, > 0.6). This study can be helpful in understanding O3 formation and interpreting the secondary formation of aerosols in the winter.

Protective effects of astaxanthin on particulate matter 2.5‑induced senescence in HaCaT keratinocytes via maintenance of redox homeostasis

Particulate matter 2.5 (PM2.5) imposes a heavy burden on the skin and respiratory system of human beings, causing side effects such as aging, inflammation and cancer. Astaxanthin (ATX) is a well-known antioxidant widely used for its anti-inflammatory and anti-aging properties. However, few studies have investigated the protective effects of ATX against PM2.5-induced senescence in HaCaT cells. In the present study, the levels of reactive oxygen species (ROS) and antioxidant enzymes were measured after treatment with PM2.5. The results revealed that PM2.5 generated excessive ROS and reduced the translocation of nuclear factor erythroid 2-related factor 2 (NRF2), subsequently reducing the expression of antioxidant enzymes. However, pretreatment with ATX reversed the ROS levels as well as the expression of antioxidant enzymes. In addition, ATX protected cells from PM2.5-induced DNA damage and rescued PM2.5-induced cell cycle arrest. The levels of senescence-associated phenotype markers, such as interleukin-1β, matrix metalloproteinases, and β-galactosidase, were increased by exposure to PM2.5, however these effects were reversed by ATX. After interfering with NRF2 mRNA expression and exposing cells to PM2.5, the levels of ROS and β-galactosidase were higher compared with siControl RNA cells exposed to PM2.5. However, ATX inhibited ROS and β-galactosidase levels in both the siControl RNA and the siNRF2 RNA groups. Thus, ATX protects HaCaT keratinocytes from PM2.5-induced senescence by partially inhibiting excessive ROS generation via the NRF2 signaling pathway.

Quantifying the impacts of Canadian wildfires on regional air pollution networks

Wildfire smoke greatly impacts regional atmospheric systems, causing changes in the behavior of pollution. However, the impacts of wildfire smoke on pollution behavior are not easily quantifiable due to the complex nature of atmospheric systems. Air pollution correlation networks have been used to quantify air pollution behavior during ambient conditions. However, it is unknown how extreme pollution events impact these networks. Therefore, we propose a multidimensional air pollution correlation network framework to quantify the impacts of wildfires on air pollution behavior. The impacts are quantified by comparing two time periods, one during the 2023 Canadian wildfires and one during normal conditions with two complex network types for each period. In this study, the value network represents PM2.5 concentrations and the rate network represents the rate of change of PM2.5 concentrations. Wildfires' impacts on air pollution behavior are captured by structural changes in the networks. The wildfires caused a discontinuous phase transition during percolation in both network types which represents non-random organization of the most significant spatiotemporal correlations. Additionally, wildfires caused changes to the connectivity of stations leading to more interconnected networks with different influential stations. During the wildfire period, highly polluted areas are more likely to form connections in the network, quantified by an 86 % and 19 % increase in the connectivity of the value and rate networks respectively compared to the normal period. In this study, we create novel understandings of the impacts of wildfires on air pollution correlation networks, show how our method can create important insights into air pollution patterns, and discuss potential applications of our methodologies. This study aims to enhance capabilities for wildfire smoke exposure mitigation and response strategies.

Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements

Fine particulate matter (PM2.5) causes millions of premature deaths each year worldwide. Oxidative potential (OP) has been proposed as a better metric for aerosol health effects than PM2.5 mass concentration alone. In this study, we report for the first time online measurements of PM2.5 OP in wintertime Beijing and surroundings based on a dithiothreitol (DTT) assay. These measurements were combined with co-located PM chemical composition measurements to identify the main source categories of aerosol OP. In addition, we highlight the influence of two distinct pollution events on aerosol OP (spring festival celebrations including fireworks and a severe regional dust storm). Source apportionment coupled with multilinear regression revealed that primary PM and oxygenated organic aerosol (OOA) were both important sources of OP, accounting for 41 ± 12 % and 39 ± 10 % of the OPvDTT (OP normalized by the sampled air volume), respectively. The small remainder was attributed to fireworks and dust, mainly resulting from the two distinct pollution events. During the 3.5-day spring festival period, OPvDTT spiked to 4.9 nmol min-1 m-3 with slightly more contribution from OOA (42 ± 11 %) and less from primary PM (31 ± 15 %). During the dust storm, hourly-averaged PM2.5 peaked at a very high value of 548 μg m-3 due to the dominant presence of dust-laden particles (88 % of total PM2.5). In contrast, only mildly elevated OPvDTT values (up to 1.5 nmol min-1 m-3) were observed during this dust event. This observation indicates that variations in OPvDTT cannot be fully explained using PM2.5 alone; one must also consider the chemical composition of PM2.5 when studying aerosol health effects. Our study highlights the need for continued pollution control strategies to reduce primary PM emissions, and more in-depth investigations into the source origins of OOA, to minimize the health risks associated with PM exposure in Beijing.

Deployment-related toxic exposures are associated with worsening mental and physical health after military service: Results from a self-report screening of veterans deployed after 9/11

Exposure to toxins-such as heavy metals and air pollution-can result in poor health and wellbeing. Recent scientific and media attention has highlighted negative health outcomes associated with toxic exposures for U.S. military personnel deployed overseas. Despite established health risks, less empirical work has examined whether deployment-related toxic exposures are associated with declines in mental and physical health after leaving military service, particularly among the most recent cohort of veterans deployed after September 11, 2001. Using data from 659 U.S. veterans in the VISN 6 MIRECC Post-Deployment Mental Health Study, we tested whether self-reported toxic exposures were associated with poorer mental and physical health. At baseline, veterans who reported more toxic exposures also reported more mental health, β = 0.14, 95% CI [0.04, 0.23], p = 0.004, and physical health symptoms, β = 0.21, 95% CI [0.11, 0.30], p < 0.001. Over the next ten years, veterans reporting more toxic exposures also had greater increases in mental health symptoms, β = 0.23, 95% CI [0.15, 0.31], p < 0.001, physical health symptoms, β = 0.22, 95% CI [0.14, 0.30], p < 0.001, and chronic disease diagnoses, β = 0.15, 95% CI [0.07, 0.23], p < 0.001. These associations accounted for demographic and military covariates, including combat exposure. Our findings suggest that toxic exposures are associated with worsening mental and physical health after military service, and this recent cohort of veterans will have increased need for mental health and medical care as they age into midlife and older age.

Emissions from plastic incineration induce inflammation, oxidative stress, and impaired bioenergetics in primary human respiratory epithelial cells

Inhalation exposure to plastic incineration emissions (PIEs) is a problem of increasing human relevance, as plastic production and waste creation have drastically increased since mainstream integration during the 20th century. We investigated the effects of PIEs on human nasal epithelial cells (HNECs) to understand if such exposures cause damage and dysfunction to respiratory epithelia. Primary HNECs from male and female donors were cultured at air-liquid interface (ALI), and 16HBE cells were cultured on coverslips. Smoke condensates were generated from incineration of plastic at flaming (640°C) and smoldering (500°C) temperatures, and cells were subsequently exposed to these materials at 5-50 μg/cm2 concentrations. HNECs were assessed for mitochondrial dysfunction and 16HBE cells for glutathione oxidation in real-time analyses. HNEC culture supernatants and total RNA were collected at 4-h postexposure for cytokine and gene expression analysis, and results show that PIEs can acutely induce inflammation, oxidative stress, and mitochondrial dysfunction in HNECs, and that incineration temperature modifies biological responses. Specifically, condensates from flaming and smoldering PIEs significantly increased HNEC secretion of cytokines IL-8, IL-1β, and IL-13, as well as expression of xenobiotic metabolism pathways and genes such as CYP1A1 and CYP1B1 at 5 and 20 μg/cm2 concentrations. Only 50 μg/cm2 flaming PIEs significantly increased glutathione oxidation in 16HBEs, and decreased respiration and ATP production in HNEC mitochondria. Impact Statement: Our data reveal the impact of incineration temperatures on biological outcomes associated with PIE exposures, emphasizing the importance of temperature as a factor when evaluating respiratory disease associated with PIEs exposure.

Insight Study of Trace Elements in PM2.5 During Nine Years in Delhi, India: Seasonal Variation, Source Apportionment, and Health Risks Assessment

This study investigated the concentrations, seasonal variations, sources, and human health risks associated with exposure to heavy elements (As, Al, Pb, Cr, Mn, Cu, Zn, and Ni) of PM2.5 at an urban location of Delhi (28° 38' N, 77° 10' E; 218 m amsl), India, from January 2013 to December 2021. The average mass concentration of PM2.5 throughout the study period was estimated as 127 ± 77 µg m-3, which is exceeding the National Ambient Air Quality Standards (NAAQS) limit (annual: 40 µg m-3; 24 h: 60 µg m-3). The seasonal mass concentrations of PM2.5 exhibited at the order of post-monsoon (192 ± 110 µgm-3) > winter (158 ± 70 µgm-3) > summer (92 ± 44 µgm-3) and > monsoon (67 ± 32 µgm-3). The heavy elements, Al (1.19 µg m-3), Zn (0.49 µg m-3), Pb (0.43 µg m-3), Cr (0.21 µg m-3), Cu (0.21 µg m-3), Mn (0.07 µg m-3), and Ni (0.14 µg m-3) exhibited varying concentrations in PM2.5, with the highest levels observed in the post-monsoon season, followed by winter, summer, and monsoon seasons. Six primary sources throughout the study period, contributing to PM2.5 were identified by positive matrix factorization (PMF), such as dust (paved/crustal/soil dust: 29.9%), vehicular emissions (17.2%), biomass burning (15.4%), combustion (14%), industrial emissions (14.2%), and Br-rich sources (9.2%). Health risk assessments, including hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR), were computed based on heavy elements concentrations in PM2.5. Elevated HQ values for Cr and Mn linked with adverse health impacts in both adults and children. High carcinogenic risk values were observed for Cr in both adults and children during the winter and post-monsoon seasons, as well as in adults during the summer and monsoon seasons. The combined HI value exceeding one suggests appreciable non-carcinogenic risks associated with the examined elements. The findings of this study provide valuable insights into the behaviour and risk mitigation of heavy elements in PM2.5, contributing to the understanding of air quality and public health in the urban environment of Delhi.

Adopting electric school buses in the United States: Health and climate benefits

Electric school buses have been proposed as an alternative to reduce the health and climate impacts of the current U.S. school bus fleet, of which a substantial share are highly polluting old diesel vehicles. However, the climate and health benefits of electric school buses are not well known. As they are substantially more costly than diesel buses, assessing their benefits is needed to inform policy decisions. We assess the health benefits of electric school buses in the United States from reduced adult mortality and childhood asthma onset risks due to exposure to ambient fine particulate matter (PM2.5). We also evaluate climate benefits from reduced greenhouse-gas emissions. We find that replacing the average diesel bus in the U.S. fleet in 2017 with an electric bus yields $84,200 in total benefits. Climate benefits amount to $40,400/bus, whereas health benefits amount to $43,800/bus due to 4.42*10-3 fewer PM2.5-attributable deaths ($40,000 of total) and 7.42*10-3 fewer PM2.5-attributable new childhood asthma cases ($3,700 of total). However, health benefits of electric buses vary substantially by driving location and model year (MY) of the diesel buses they replace. Replacing old, MY 2005 diesel buses in large cities yields $207,200/bus in health benefits and is likely cost-beneficial, although other policies that accelerate fleet turnover in these areas deserve consideration. Electric school buses driven in rural areas achieve small health benefits from reduced exposure to ambient PM2.5. Further research assessing benefits of reduced exposure to in-cabin air pollution among children riding buses would be valuable to inform policy decisions.

Reducing Soil-Emitted Nitrous Acid as a Feasible Strategy for Tackling Ozone Pollution

Severe ozone (O3) pollution has been a major air quality issue and affects environmental sustainability in China. Conventional mitigation strategies focusing on reducing volatile organic compounds and nitrogen oxides (NOx) remain complex and challenging. Here, through field flux measurements and laboratory simulations, we observe substantial nitrous acid (HONO) emissions (FHONO) enhanced by nitrogen fertilizer application at an agricultural site. The observed FHONO significantly improves model performance in predicting atmospheric HONO and leads to regional O3 increases by 37%. We also demonstrate the significant potential of nitrification inhibitors in reducing emissions of reactive nitrogen, including HONO and NOx, by as much as 90%, as well as greenhouse gases like nitrous oxide by up to 60%. Our findings introduce a feasible concept for mitigating O3 pollution: reducing soil HONO emissions. Hence, this study has important implications for policy decisions related to the control of O3 pollution and climate change.

High spatial-resolved source-specific exposure and risk in the city scale: Influence of spatial interrelationship between PM2.5 sources and population on exposure

Research on High Spatial-Resolved Source-Specific Exposure and Risk (HSRSSER) was conducted based on multiple-year, multiple-site synchronous measurement of PM2.5-bound (particulate matter with aerodynamic diameter<2.5 μm) toxic components in a Chinese megacity. The developed HSRSSER model combined the Positive Matrix Factorization (PMF) and Land Use Regression (LUR) to predict high spatial-resolved source contributions, and estimated the source-specific exposure and risk by personal activity time- and population-weighting. A total of 287 PM2.5 samples were collected at ten sites in 2018-2020, and toxic species including heavy metals (HMs), polycyclic aromatic hydrocarbons (PAHs) and organophosphate esters (OPEs) were analyzed. The percentage non-cancer risk were in the order of traffic emission (48 %) > industrial emission (22 %) > coal combustion (12 %) > waste incineration (11 %) > resuspend dust (7 %) > OPE-related products (0 %) ≈ secondary particles (0 %). Similar orders were observed in cancer risk. For traffic emission, due to its higher source contributions and large population in central area, non-cancer and cancer risk fraction increased from 23 % to 48 % and 20 % to 46 % after exposure estimation; while for industrial emission, higher source contributions but small population in suburb area decreased the percentage non-cancer and cancer risk from 38 % to 22 % and 39 % to 24 %, respectively.

Influence of topography and synoptic weather patterns on air quality in a valley basin city of Northwest China

To clarify the mechanism underlying the effects of weather patterns and topography on air pollution, this study conducted the obliquely rotated principal component analysis in the T-mode to analyze ERA5 reanalysis data and categorize typical weather patterns at a 700-hPa geopotential height from 2015 to 2022. The probability of worsened air pollution attributable to weather patterns was quantitatively assessed using a generalized additive model. The results indicated that due to the influence of topography, Lanzhou was affected by an extended period of downdraft (with weak convective intensity) and the delayed formation of a convective boundary layer during the daytime by 1-2 h relative to other areas. Under the combined effect of low trough patterns (south low pressure type [SL] and south low weak pressure type [SL-]) and topography, the formation of a stable layer above the planetary boundary layer (PBL) would weaken the vertical exchange of the local airflow and inhibit the development of the PBL. The type of SL led to the most severe pollution, causing a 61.9 % (95 % confidence interval [CI]: 46.3 %-79.3 %) increase in PM2.5 concentration. For southwest high pressure patterns (south high [SH], southwest weak high [SWH-], southwest high [SWH], and southwest strong high [SWH+] pressure types), the prevailing northwest wind was the main transport path for pollutants. For the high pressure patterns (north high [NH] and northwest high [NWH] pressure types) and south wind patterns (southeast weak high [SEH-], southeast high [SEH], and northeast high [NEH] pressure types), the enhancement of vertical convection, deepening of the PBL, and reduction of pollution transport led to improved air quality. The NH, NWH, and NEH pressure types caused PM2.5 concentration to decrease by 18.4 % (95 % CI: 8.8 %-27.1 %), 14.9 % (95 % CI: 4.7 %-24.0 %), and 35.9 % (95 % CI: 9.7 %-54.6 %), respectively.

Fungal community shows more variations by season and particle size than bacteria

The global concern regarding the health risk associated with airborne microorganisms has prompted research in this field. However, there is a lack of systematic investigation into the particle-size distribution of airborne bacterial and fungal communities associated with seasons, which determines where they are deposited in the human respiratory tract. To address this gap, we conducted a study in Nanchang, located in central China, where we collected both coarse and fine particles during summer and winter seasons. The results demonstrated that microbial community exhibited obvious seasonal and particle-size variations except bacterial community in fine particles. Certain taxa (e.g., Bacteroidales, Ktedonobacterales, Capnodiales) displayed either seasonal and/or particle-size preferences. Furthermore, airborne microorganisms in coarse particles were more sensitive to season and particle size compared to those in fine particles, with fungal community being more susceptible than bacterial community. The susceptibility can be attributed to their high vulnerability to air pollutants and meteorological conditions, primarily PM2.5 and PM10. Additionally, a greater relative abundance of pathogenic fungi was observed in fine particles, even though microbial diversity in coarse particles was noticeably higher than that in fine particles. Furthermore, some predominant pathogens such as Alternaria, Nigrospora, and Escherichia-Shigella not only had particle size and/or seasonal preferences, but also were strongly correlated with environmental factors. This study advances our understanding of atmospheric pathogenic microorganisms and highlights the fungal health threat.

Regulatory Insights for On-Board Monitoring of Vehicular NOx Emission Compliance

Nitrogen oxide (NOx) emissions from heavy-duty diesel vehicles (HDDVs) have adverse effects on human health and the environment. On-board monitoring (OBM), which can continuously collect vehicle performance and NOx emissions throughout the operation lifespan, is recognized as the core technology for future vehicle in-use compliance, but its large-scale application has not been reported. Here, we utilized OBM data from 22,520 HDDVs in China to evaluate their real-world NOx emissions. Our findings showed that China VI HDDVs had a 73% NOx emission reduction compared with China V vehicles, but a considerable proportion still faced a significant risk of higher NOx emissions than the corresponding limits. The unsatisfactory efficiency of the emission treatment system under disadvantageous driving conditions (e.g., low speed or ambient temperature) resulted in the incompliance of NOx emissions, especially for utility vehicles (sanitation/garbage trucks). Furthermore, the observed intertrip and seasonal variability of NOx emissions demonstrated the need for a long-term continuous monitoring protocol instead of instantaneous evaluation for the OBM. With both functions of emission monitoring and malfunction diagnostics, OBM has the potential to accurately verify the in-use compliance status of large-scale HDDVs and discern the responsibility of high-emitting activities from manufacturers, vehicle operators, and driving conditions.

The key characteristics of cardiotoxicity for the pervasive pollutant phenanthrene

The key characteristic (KCs) framework has been used previously to assess the carcinogenicity and cardiotoxicity of various chemical and pharmacological agents. Here, the 12 KCs of cardiotoxicity are used to evaluate the previously reported cardiotoxicity of phenanthrene (Phe), a tricyclic polycyclic aromatic hydrocarbon (PAH), and major component of fossil fuel-derived air pollution. Phe is a semi-volatile pollutant existing in both the gas phase and particle phase through adsorption onto or into particulate matter (PM). Phe can translocate across the airways and gastrointestinal tract into the systemic circulation, enabling body-wide effects. Our evaluation based on a comprehensive literature review, indicates Phe exhibits 11 of the 12 KCs for cardiotoxicity. These include adverse effects on cardiac electromechanical performance, the vasculature and endothelium, immunomodulation and oxidative stress, and neuronal and endocrine control. Environmental agents that have similarly damaging effects on the cardiovascular system are heavily regulated and monitored, yet globally there is no air quality regulation specific for PAHs like Phe. Environmental monitoring of Phe is not the international standard with benzo[a]pyrene being frequently used as a proxy despite the two PAH species exhibiting significant differences in sources, concentration variations and toxic effects. The evidence summarised in this evaluation highlights the need to move away from proxied PAH measurements and develop a monitoring network capable of measuring Phe concentration. It also stresses the need to raise awareness amongst the medical community of the potential cardiovascular impact of PAH exposure. This will allow the production of mitigation strategies and possibly the development of new policies for the protection of the societal groups most vulnerable to cardiovascular disease.

Air quality and cancer risk in the All of Us Research Program

INTRODUCTION

The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks.

MATERIALS AND METHODS

This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA's Earth Observing System Data and Information Center and assigned using participants' 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships.

RESULTS

A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2007 to 2016 was 8.90 μg/m3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09-1.25), endometrial cancer (OR 1.33, 95% CI 1.09-1.62) and ovarian cancer (OR 1.20, 95% CI 1.01-1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer.

CONCLUSIONS

We found evidence of an association of PM2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.

Fine-tuning the use of moss transplants to map pollution by Potentially Toxic Elements (PTEs) in urban areas

Mosspheres are a kind of moss transplants which offer a novel approach for detecting atmospheric pollution using devitalized mosses, as they reflect the atmospheric deposition of certain elements and polycyclic hydrocarbons. However, due to the unique features of the mosspheres such as the low elemental concentrations in the cultured material, the data treatment needs to be different from that of conventional biomonitoring studies. In this article, our objectives are to identify the best parameter for expressing the levels of chemical elements accumulated by mosspheres, and to apply a recently developed method to assess the probability of pollution of each sample and of the study area. To do this, we used data from a study in which 81 mosspheres were exposed in a medium-sized city in southwestern Europe. Comparing different pollution indices, we selected the enrichment rate (ER) as the most useful, as it is resilient to fluctuations in the initial concentrations and takes into account the time factor, allowing for greater comparability among studies. Then, we determined that the statistical distribution of the ERs of most elements fitted a normal distribution, showing that most samples did not differ significantly from the background concentrations for these elements. On the other hand, for Ni, Pb and Zn there was a subpopulation of samples above background values. In these cases, we determined the probability of pollution of each sample. Finally, we used indicator kriging to calculate the probability of pollution across the study area, identifying the polluted areas, which for some elements match the distribution of the main industries and highways, indicating that this is a suitable protocol to map elemental pollution in urban areas.

Can the aerosol pollution extreme events be revealed by global reanalysis products?

Extreme aerosol pollution poses significant risks to the climate, environment, and human health. To investigate the formation and impacts of aerosol pollution extreme events (APEE), the reanalysis product presents meticulous spatiotemporal information on the three-dimensional distribution of aerosols. However, there is a lack of comprehensive evaluation and information regarding the data quality of reanalysis products employed in APEE research, as well as limited understanding of their spatial and temporal distribution, variation, and long-term trends. To address this scientific gap, we conducted a global study for distribution and variation patterns of APEE using two widely-used reanalysis products, MERRA-2 (Modern-Era Retrospective Analysis for Research-2) and CAMS (Copernicus Atmospheric Monitoring Service). The APEE was defined here as a day when the daily aerosol optical depth (AOD) exceeding its 90th percentile for a given station and month. Eleven distinct land regions worldwide were selected for evaluation by comparing both reanalysis products with MODIS satellite products and ground-based observations in terms of frequency, intensity, and temporal trends of APEE. The analysis indicates that MERRA-2 and CAMS exhibit high matching rates (70 % and 80 %, respectively) in terms of occurrence timeline for APEE at monthly and seasonal scales, while also exhibiting strong monthly correlation coefficients (>0.65) with ground-based observations over selected regions. The total AOD (-0.002 ∼ -0.123 decade-1), APEE AOD (-0.004 ∼ -0.293 decade-1), and APEE frequency (-0.264 ∼ -1.769 day month-1 decade-1) of both observations and reanalysis products in most regions showed a decreasing trend with various magnitude, except for some regions such as South Asia where the trend is increasing. Based on the aforementioned evaluation, it is evident that reanalysis products are effective and useful in identifying the temporal trends associated with APEE.

The role of environmental tax on the environmental quality in EU counties: evidence from panel vector autoregression approach

This study intends to analyze the influence of environmental taxes on pollution in EU-27 nations. Furthermore, energy from renewable sources consumption and urbanization are employed to clarify CO2 emissions in this study that tests the EKC hypothesis. According to the findings, an increase in environmental taxes reduces CO2 emissions by 0.14%. Also, the data supported the validity of the EKC concept. The findings of the causality test demonstrated that there is a bidirectional causal link between CO2 emissions and environmental taxes. These results reflect that environmental tax revenues contribute to sustainability as an effective policy tool in EU countries. Policies regarding environmental tax enforcement come to the fore in terms of both keeping the balance in economic activities and serving sustainability.

Exploring efficient strategies for air quality improvement in China based on its regional characteristics and interannual evolution of PM2.5 pollution

Fine particulate matter (PM2.5) harms human health and hinders normal human life. Considering the serious complexity and obvious regional characteristics of PM2.5 pollution, it is urgent to fill in the comprehensive overview of regional characteristics and interannual evolution of PM2.5. This review studied the PM2.5 pollution in six typical areas between 2014 and 2022 based on the data published by the Chinese government and nearly 120 relevant literature. We analyzed and compared the characteristics of interannual and quarterly changes of PM2.5 concentration. The Beijing-Tianjin-Hebei region (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) made remarkable progress in improving PM2.5 pollution, while Fenwei Plain (FWP), Sichuan Basin (SCB) and Northeast Plain (NEP) were slightly inferior mainly due to the relatively lower level of economic development. It was found that the annual average PM2.5 concentration change versus year curves in the three areas with better pollution control conditions can be merged into a smooth curve. Importantly, this can be fitted for the accurate evaluation of each area and provide reliable prediction of its future evolution. In addition, we analyzed the factors affecting the PM2.5 in each area and summarize the causes of air pollution in China. They included primary emission, secondary generation, regional transmission, as well as unfavorable air dispersion conditions. We also suggested that the PM2.5 pollution control should target specific industries and periods, and further research need to be carried out on the process of secondary production. The results provided useful assistance such as effect prediction and strategy guidance for PM2.5 pollution control in Chinese backward areas.

Greenspaces And Cardiovascular Health

Accumulating evidence suggests that living in areas of high surrounding greenness or even brief exposures to areas of high greenery is conducive to cardiovascular health, which may be related to the environmental, social, psychological, and physiological benefits of greenspaces. Recent data from multiple cross-sectional, longitudinal, and cohort studies suggest that living in areas of high surrounding greenness is associated with a lower risk of all-cause and cardiovascular mortality. High levels of neighborhood greenery have been linked also to a decrease in the burden of cardiovascular disease risk factors as reflected by lower rates of hypertension, dyslipidemia, and diabetes. Those who live in greener environments report better mental health and more frequent social interactions, which can benefit cardiovascular health as well. In this narrative review, we discuss evidence linking greenspaces to cardiovascular health as well as the potential mechanisms underlying the beneficial effects of greenspaces, including the impact of vegetation on air, noise and light pollution, ambient temperature, physical activity, mental health, and biodiversity. We review literature on the beneficial effects of acute and chronic exposure to nature on cardiovascular disease risk factors, inflammation and immune function, and we highlight the potential cardiovascular effects of biogenic volatile organic compounds that are emitted by trees and shrubs. We identify current knowledge gaps in this area and underscore the need for additional population studies to understand more clearly and precisely the link between greenness and health. Such understanding is urgently needed to fully redeem the promise of greenspaces in preventing adverse environmental exposures, mitigating the effects of climate change, and creating healthier living environments.

Spatiotemporal characteristics analysis of multi-factorial air pollution in the Jing-Jin-Ji region based on improved sequential ICI method and novel grey spatiotemporal incidence models

Air pollution shares the attributes of multi-factorial influence and spatiotemporal complexity, leading to air pollution control assistance models easily falling into a state of failure. To address this issue, we design a framework containing improved data fusion method, novel grey incidence models and air pollution spatiotemporal analysis to analyze the complex characteristics of air pollution under the fusion of multiple factors. Firstly, we improve the existing data fusion method for multi-factor fusion. Subsequently, we construct two grey spatiotemporal incidence models to examine the spatiotemporal characteristics of multi-factorial air pollution in network relationships and changing trends. Furthermore, we propose two new properties that can manifest the performance of grey incidence analysis, and we provide detailed proof of the properties of the new models. Finally, in the Jing-Jin-Ji region, the novel models are used to study the network relationships and trend changes of air pollution. The findings are as follows: (1) Two highly polluted belts in the region require attention. (2) Although the air pollution network under multi-factorial fusion obeys the first law of geography, the network density and node density exhibit significant variations. (3) From 2013 to 2021, all pollutants except O3 show improvement. (4) Recommendations for responses are presented based on the above-mentioned results. (5) The parameter analyses, model comparisons, Monte Carlo experiments and model feature summaries illustrate that the proposed models are practical, interpretable and considerably outperform various prevailing competitors with remarkable universality.

Fires as a source of annual ambient PM2.5 exposure and chronic health impacts in Europe

Chronic exposure to ambient PM2.5 is the largest environmental health risk in Europe. We used a chemical transport model and recent exposure response functions to simulate ambient PM2.5, contribution from fires and related health impacts over Europe from 1990 to 2019. Our estimation indicates that the excess death burden from exposure to ambient PM2.5 declined across Europe at a rate of 10,000 deaths per year, from 0.57 million (95 % confidence intervals: 0.44-0.75 million) in 1990 to 0.28 million (0.19-0.42 million) in the specified period. Among these excess deaths, approximately 99 % were among adults, while only around 1 % occurred among children. Our findings reveal a steady increase in fire mortality fractions (excess deaths from fires per 1000 deaths from ambient PM2.5) from 2 in 1990 to 13 in 2019. Notably, countries in Eastern Europe exhibited significantly higher fire mortality fractions and experienced more pronounced increases compared to those in Western and Central Europe. We performed sensitivity analyses by considering fire PM2.5 to be more toxic as compared to other sources, as indicated by recent studies. By considering fire PM2.5 to be more toxic than other PM2.5 sources results in an increased relative contribution of fires to excess deaths, reaching 2.5-13 % in 2019. Our results indicate the requirement of larger mitigation and adaptation efforts and more sustainable forest management policies to avert the rising health burden from fires.

Air pollutant emissions caused by receiving international industrial transfer in Southeast Asian developing countries from 1990 to 2018

Receiving international industrial transfer (mainly foreign direct investment, FDI) is extremely important for economic development but also brings negative environmental impacts for Southeast Asian developing countries (SEADCs). Due to relatively low labor costs and large market potential, SEADCs have become an attractive destination for industrial transfer after China, while studies were far from sufficient on the associated air pollutant emissions that would worsen air quality and threaten human health. We develop an exploratory framework to estimate the long-term trends of relevant air pollutant emissions in eight major SEADCs, including Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. During 1990-2018, the emissions generally show a fluctuating upward trend and increased significantly in Cambodia, Laos, Philippines, and Vietnam. The total emissions of CO, NMVOC, SO2, NOX, PM2.5, and NH3 from the eight SEADCs increased from 19.0, 4.3, 3.6, 1.5, 0.5, and 0.4 kilotons (kt) to 391.6, 260.9, 271.1, 182.4, 48.4, and 12.2 kt, respectively. The emission growth in almost all SEADCs accelerated after 2008 and faster than FDI growth. The disparities in emissions among SEADCs basically grew first and then declined to a level lower than that of 1990, but generally exceeded the disparities in FDI. Productivity gain and emission intensity decrease primarily caused the emission growth and reduction, respectively. Relatively small reductions in emission intensity are found for NOX and SO2. In general, most SEADCs have utilized FDI for economic development without sufficient efforts on air pollutant emission controls. Our outcomes can inform the formulation and optimization of relevant policies reconciling economic development and air quality improvement in SEADCs.

Effects of ambient PM2.5 on non-accidental death: a time-series study in Shenzhen, China during 2014-2019

This study aims to investigate the impact of PM2.5 on non-accidental death of residents. The single-pollutant model revealed that the influence of PM2.5 on non-accidental death was significant at lag0 and lag4-6, and was greatest at lag5. A 10 µg/m3 increase in PM2.5 was related with a 1.31% increase in non-accidental deaths. The connection between PM2.5 and non-accidental death was stronger in femalesthan males, in people aged ≥ 65 years than people aged < 65 years, and in people below high school education than people with high school education or above. Two-pollutant model revealed that the influence of PM2.5 on non-accidental death was essentially unchanged when CO, SO2, and O3 were included and reduced when NO2 was included. The multiple-pollutant model showed that the effect of ambient PM2.5 on non-accidental death was reduced. An increase in PM2.5 concentrations may cause an increase in non-accidental death.

Trichome-Like Biomimetic Air Filters via Templated Silicone Nanofilaments

Air pollution threats to human health have increased awareness of the role of filter units in air cleaning applications. As an ideal energy-saving strategy for air filters, the slip effect on nanofiber surfaces can potentially overcome the trade-off between filtration efficiency and pressure drop. However, the potential of the slip effect in nanofibrous structures is significantly limited by the tight nanofiber stacks. In this study, trichome-like biomimetic (TLB) air filters with 3D-templated silicone nanofilaments (average diameter: ≈74 nm) are prepared based on an in situ chemical vapor deposition (CVD) method inspired by plant purification. Theoretical modeling and experimental results indicate that TLB air filters make significant use of the slip effect to overcome the efficiency-resistance tradeoff. The selectable filter class (up to U15, ≈99.9995%) allows TLB air filters to meet various requirements, and their integral filtration performance surpasses that of most commodity air filters, including melt-blown cloth, ePTFE membranes, electrospun mats, and glass fiber paper. The proposed strategy directly transforms commercial filter media and filters into TLB air filters using a bottom-up, one-step approach. As a proof-of-concept, reusable N95 respirators and air purifiers equipped with TLB air filters are fabricated, overcoming the limitations of existing filter designs and fabrication methods.

Global health impacts of ambient fine particulate pollution associated with climate variability

Air pollution is a key global environmental problem raising human health concern. It is essential to comprehensively assess the long-term characteristics of air pollution and the resultant health impacts. We first assessed the global trends of fine particulate matter (PM2.5) during 1980-2020 using a monthly global PM2.5 reanalysis dataset, and evaluated their association with three types of climate variability including El Niño-Southern Oscillation, Indian Ocean Dipole and North Atlantic Oscillation. We then estimated PM2.5-attributable premature deaths using integrated exposure-response functions. Results show a significant increasing trend of ambient PM2.5 during 1980-2020 due to increases in anthropogenic emissions. Ambient PM2.5 caused a total of ∼ 135 million premature deaths globally during the four decades. Occurrence of air pollution episodes was strongly associated with climate variability, which were associated with up to 14 % increase in annual global PM2.5-attributable premature deaths.

Pathogenesis of PM2.5-Related Disorders in Different Age Groups: Children, Adults, and the Elderly

The effects of PM2.5 on human health fluctuate greatly among various age groups, influenced by a range of physiological and immunological reactions. This paper compares the pathogenesis of the disease caused by PM2.5 in people of different ages, focusing on how children, adults, and the elderly are each susceptible to it because of differences in their bodies. Regarding children, exposure to PM2.5 is linked to many negative consequences. These factors consist of inflammation, oxidative stress, and respiratory problems, which might worsen pre-existing conditions and potentially cause neurotoxicity and developmental issues. Epigenetic changes can affect the immune system and make people more likely to get respiratory diseases. On the other hand, exposures during pregnancy can change how the cardiovascular and central nervous systems develop. In adults, the inhalation of PM2.5 is associated with a wide range of health problems. These include respiratory difficulties, reduced pulmonary function, and an increased susceptibility to illnesses such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. In addition, exposure to PM2.5 induces systemic inflammation, cardiovascular diseases, insulin resistance, and neurotoxic consequences. Evident disturbances in the immune system and cognitive function demonstrate the broad impact of PM2.5. The elderly population is prone to developing respiratory and cardiovascular difficulties, which worsen their pre-existing health issues and raise the risk of cognitive decline and neurological illnesses. Having additional medical conditions, such as peptic ulcer disease, significantly increases the likelihood of being admitted to hospital.

Substantially reducing global PM2.5-related deaths under SDG3.9 requires better air pollution control and healthcare

The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP.

The emerging role of hypoxia and environmental factors in inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic and debilitating disorder characterized by inflammation of the gastrointestinal tract. Despite extensive research, the exact cause of IBD remains unknown, hampering the development of effective therapies. However, emerging evidence suggests that hypoxia, a condition resulting from inadequate oxygen supply, plays a crucial role in intestinal inflammation and tissue damage in IBD. Hypoxia-inducible factors (HIFs), transcription factors that regulate the cellular response to low oxygen levels, have gained attention for their involvement in modulating inflammatory processes and maintaining tissue homeostasis. The two most studied HIFs, HIF-1α and HIF-2α, have been implicated in the development and progression of IBD. Toxicological factors encompass a wide range of environmental and endogenous agents, including dietary components, microbial metabolites, and pollutants. These factors can profoundly influence the hypoxic microenvironment within the gut, thereby exacerbating the course of IBD and fostering the progression of colitis-associated colorectal cancer. This review explores the regulation of hypoxia signaling at the molecular, microenvironmental, and environmental levels, investigating the intricate interplay between toxicological factors and hypoxic signaling in the context of IBD, focusing on its most concerning outcomes: intestinal fibrosis and colorectal cancer.

Impacts of the aerosol mixing state and new particle formation on CCN in summer at the summit of Mount Tai (1534m) in Central East China

In this study, the aerosol size distributions, cloud condensation nuclei (CCN) number concentration (NCCN), single-particle chemical composition and meteorological data were collected from May 12 to June 8, 2017, at the summit of Mt. Tai. The effects of new particle formation (NPF) events and aerosol chemical components on CCN at Mt. Tai were analyzed in detail. The results showed that, NPF events significantly enhanced the CCN population, and the enhancement effect increased with increasing supersaturation (SS) value at Mt.Tai. NCCN at SS ranging from 0.1 to 0.9 % on NPF days was 10.9 %, 36.5 %, 44.6 %, 53.5 % and 51.5 % higher than that on non-NPF days from 10:00-13:00 as NPF events progressed. The effect of chemical components on CCN activation under the influence of NPF events was greater than that in the absence of NPF events. The correlation coefficients of EC-Nitrate particles (EC-Sulfate particles) and CCN at all SS levels on NPF days were 1.31-1.59 times (1.17-1.35 times) higher than those on non-NPF days. Nitrate particles promoted CCN activation but sulfate particles inhibited activation at Mt. Tai. There are differences or even opposite effects of the same group of particles on CCN activation under the influence of NPF events in different air masses. EC-Sulfate particles inhibited CCN activation at all SS levels for type I but weakly promoted activation at lower SS ranging from 0.1 to 0.3 % and weakly inhibited it at higher 0.9 % SS for type II. OCEC particles significantly inhibited CCN activation for type II, and this effect decreased with increasing SS. OCEC particles only weakly inhibited activation at SS ranging from 0.5 to 0.7 % for type I. OCEC particles only weakly inhibited this process at 0.1 % SS, while they very weakly promoted activation for SS > 0.1 %. This reveals that the CCN activity is not only related to the chemical composition of the particles, but the mixing state also has an important effect on the CCN activity.

Urban ozone variability using automated machine learning: inference from different feature importance schemes

Tropospheric ozone is an air pollutant at the ground level and a greenhouse gas which significantly contributes to the global warming. Strong anthropogenic emissions in and around urban environments enhance surface ozone pollution impacting the human health and vegetation adversely. However, observations are often scarce and the factors driving ozone variability remain uncertain in the developing regions of the world. In this regard, here, we conducted machine learning (ML) simulations of ozone variability and comprehensively examined the governing factors over a major urban environment (Ahmedabad) in western India. Ozone precursors (NO2, NO, CO, C5H8 and CH2O) from the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis and meteorological parameters from the ERA5 (European Centre for Medium-Range Weather Forecast's (ECMWF) fifth-generation reanalysis) were included as features in the ML models. Automated ML (AutoML) fitted the deep learning model optimally and simulated the daily ozone with root mean square error (RMSE) of ~2 ppbv reproducing 84-88% of variability. The model performance achieved here is comparable to widely used ML models (RF-Random Forest and XGBoost-eXtreme Gradient Boosting). Explainability of the models is discussed through different schemes of feature importance, including SAGE (Shapley Additive Global importancE) and permutation importance. The leading features are found to be different from different feature importance schemes. We show that urban ozone could be simulated well (RMSE = 2.5 ppbv and R2 = 0.78) by considering first four leading features, from different schemes, which are consistent with ozone photochemistry. Our study underscores the need to conduct science-informed analysis of feature importance from multiple schemes to infer the roles of input variables in ozone variability. AutoML-based studies, exploiting potentials of long-term observations, can strongly complement the conventional chemistry-transport modelling and can also help in accurate simulation and forecast of urban ozone.

Uneven PM2.5 dispersion pattern across an open-road vegetation barrier: Effects of planting combination and wind condition

The increased traffic-induced emissions contribute to the exacerbation of airborne particulate matter (PM) pollution. The vegetation barrier (VB) provides a means of reducing the traffic-induced pollutants. However, the effects of VB configuration and local environment on PM dispersion and reduction remain unclear, and thereby needs further advancement on VB design and characteristics. This study constructed a 3D numerical model based on field survey in an open-road VB of Shanghai urban area, and then simulated PM2.5 dispersion under various VB configurations and wind conditions. The results consolidated that the presence of the VB reduced PM2.5 concentration by over 15 % across the VB. A greater bush coverage (2/3 and more) reduces over 14 % more PM2.5 pollution across the VB than that for a greater arbor coverage, and reduces 6 % more PM2.5 pollution in the sidewalk canyon. Given a certain bush planting coverage, planting bushes in the windward area is beneficial to the overall PM2.5 reduction by approximately 4-14 %. The wind directions determine the overall pattern of PM2.5 dispersion across the VB plot, decreasing trends for perpendicular winds but fluctuating curves for parallel winds Wind velocities largely contribute to the changing rates of PM2.5 concentration, the increased wind speed from 1 m/s to 7 m/s accumulated 5-11 % more PM2.5 pollution across the VB plot. This study provides practical insights for effective VB designs in order to mitigate the PM pollution and the human's exposure to PM2.5 in urban open-road environments.

The Challenges and Opportunities for TiO2 Nanostructures in Gas Sensing

Chemiresistive gas sensors based on metal oxides have been widely applied in industrial monitoring, medical diagnosis, environmental pollutant detection, and food safety. To further enhance the gas sensing performance, researchers have worked to modify the structure and function of the material so that it can adapt to different gas types and environmental conditions. Among the numerous gas-sensitive materials, n-type TiO2 semiconductors are a focus of attention for their high stability, excellent biosafety, controllable carrier concentration, and low manufacturing cost. This Perspective first introduces the sensing mechanism of TiO2 nanostructures and composite TiO2-based nanomaterials and then analyzes the relationship between their gas-sensitive properties and their structure and composition, focusing also on technical issues such as doping, heterojunctions, and functional applications. The applications and challenges of TiO2-based nanostructured gas sensors in food safety, medical diagnosis, environmental detection, and other fields are also summarized in detail. Finally, in the context of their practical application challenges, future development technologies and new sensing concepts are explored, providing new ideas and directions for the development of multifunctional intelligent gas sensors in various application fields.

Long-term exposure to air pollution and risk of stroke by ecoregions: The REGARDS study

Several cohort studies have found associations between long-term exposure to air pollution and stroke risk. However, it is unclear whether the surrounding ecology may modify these associations. This study evaluates associations of air pollution with stroke risk by ecoregions, which are areas of similar type, quality, and quantity of environmental resources in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. We assessed the incidence of stroke in 26,792 participants (45+ yrs) from the REGARDS study, a prospective cohort recruited across the contiguous United States. One-yr and 3-yr means of PM2.5, PM10, O3, NO2, SO2, and CO were estimated at baseline using data from the Center for Air, Climate, & Energy Solution, and assigned to participants at the census block group level. Incident stroke was ascertained through September 30, 2020. Relations of air pollutants with the risk of incident stroke were estimated using Cox proportional hazards models, adjusting for relevant demographics, behavioral risk factors, and neighborhood urbanicity. Models were stratified by EPA designated ecoregions. A 5.4 μg/m3 (interquartile range) increase in 1-yr PM10 was associated with a hazard ratio (95 %CI) for incident stroke of 1.07 (1.003, 1.15) in the overall study population. We did not find evidence of positive associations for PM2.5, O3, NO2, SO2, and CO in the fully adjusted models. In our ecoregion-specific analysis, associations of PM2.5 with stroke were stronger in the Great Plains ecoregion (HR = 1.44) than other ecoregions, while associations for PM10 were strongest in the Eastern Temperate Forests region (HR = 1.15). The associations between long-term exposure to air pollution and risk of stroke varied by ecoregion. Our results suggests that the type, quality, and quantity of the surrounding ecology can modify the effects of air pollution on risk of stroke.

Real-world emission characteristics of carbonyl compounds from on-road vehicles in Beijing and Zhengzhou, China

Carbonyl compounds have a profound role in atmospheric chemistry, which can cause the formation of ozone and secondary organic aerosols. On-road vehicle emissions are an important source of carbonyl compounds, but systematic knowledge of real-world emission characteristics is still scarce. In this study, a total of 181 on-road vehicles of 16 types in Beijing and Zhengzhou, China, were tested using portable emission measurement system under real-world driving conditions. The total carbonyl compound emission factors of gasoline vehicles, diesel vehicles, motorcycles, and agricultural transport vehicles were 24.9 ± 11.4 mg/km, 42.5 ± 21.5 mg/km, 20.4 ± 6.8 mg/km, and 78.3 ± 34.3 mg/km, respectively. Vehicles fueled with E10 ethanol gasoline had significantly higher carbonyl compound emission factors compared to E0 gasoline vehicles. It was observed that the continuous tightening of emission standards has effectively reduced the emissions of carbonyl compounds from on-road vehicles. The carbonyl compound emission factors on highways were 1.3-1.9 times lower than those on general roads. The total carbonyl compound emissions from on-road vehicles in Beijing and Zhengzhou in 2019 were estimated to be 3.5 kt and 3.1 kt, with corresponding ozone formation potentials of 24.4 kt and 21.4 kt, respectively. Formaldehyde, acetaldehyde, propionaldehyde and acetone were the most significant contributors to total carbonyl compound emissions, and among them, formaldehyde, acetaldehyde and propionaldehyde were the main contributors to total ozone formation potential. Our results provide updated and supplementary information on on-road vehicle emission factors for carbonyl compounds and can facilitate the improvement of emission inventories and help in the development of control strategies to improve air quality.

In praise of fossil fuel subsidies (for cooking)

Households that burn biomass in inefficient open fires - a practice that results in $1.6 trillion in global damages from health impacts and climate-altering emissions yearly - are often unable to access cleaner alternatives, like gas, which is widely available but unaffordable, or electricity, which is unattainable for many due to insufficient supply and reliability of electricity services. Governments are often reluctant to make gas affordable. We argue that condemnation of all fossil fuel subsidies is short-sighted and does not adequately consider subsidizing gas for cooking as a potential strategy to improve public health and reduce greenhouse gas emissions.

Implications for new particle formation in air of the use of monoethanolamine in carbon capture and storage

Alkanolamines are currently being deployed in carbon capture and storage (CCS) technology worldwide, and atmospheric emissions have been found to coincide with locations exhibiting elevated concentrations of methanesulfonic acid (MSA). It is thus critical to understand the fate and potential atmospheric reactions of these chemicals. This study reports the characterization of sub-10 nm nanoparticles produced through the acid-base reaction between gas phase monoethanolamine (MEA) and MSA, a product of organosulfur compound oxidation in air, using a flow reactor under dry and humid (up to ∼60% RH) conditions. Number size distribution measurements show that MEA is even more efficient than methylamine in forming nanoparticles on reaction with MSA. This is attributed to the fact that the MEA structure contains both an -NH2 and an -OH group that facilitate hydrogen bonding within the clusters, in addition to the electrostatic interactions. Due to this already strong H-bond network, water has a relatively small influence on new particle formation (NPF) and growth in this system, in contrast to MSA reactions with alkylamines. Acid/base molar ratios of unity for 4-12 nm particles were measured using thermal desorption chemical ionization mass spectrometry. The data indicate that reaction of MEA with MSA may dominate NPF under some atmospheric conditions. Thus, the unique characteristics of alkanolamines in NPF must be taken into account for accurate predictions of impacts of CCS on visibility, health and climate.

Quantification and Characterization of Fine Plastic Particles as Considerable Components in Atmospheric Fine Particles

The negative effects of air pollution, especially fine particulate matter (PM2.5, particles with an aerodynamic diameter of ≤2.5 μm), on human health, climate, and ecosystems are causing significant concern. Nevertheless, little is known about the contributions of emerging pollutants such as plastic particles to PM2.5 due to the lack of continuous measurements and characterization methods for atmospheric plastic particles. Here, we investigated the levels of fine plastic particles (FPPs) in PM2.5 collected in urban Shanghai at a 2 h resolution by using a novel versatile aerosol concentration enrichment system that concentrates ambient aerosols up to 10-fold. The FPPs were analyzed offline using the combination of spectroscopic and microscopic techniques that distinguished FPPs from other carbon-containing particles. The average FPP concentrations of 5.6 μg/m3 were observed, and the ratio of FPPs to PM2.5 was 13.2% in this study. The FPP sources were closely related to anthropogenic activities, which pose a potential threat to ecosystems and human health. Given the dramatic increase in plastic production over the past 70 years, this study calls for better quantification and control of FPP pollution in the atmosphere.

The importance of teaching climate-health literacy in psychotherapeutic training and continuing education

Climate-health literacy is the ability to find, access, understand, interpret, evaluate, and communicate information about the impact of climate change on human health and to make decisions and act accordingly to that information. Climate change affects people's health in numerous ways, both directly and indirectly, e.g., by increasing the risks of cardiovascular disease, infections, depression, anxiety disorders, and trauma. It is important for health professionals to understand the complex interaction between climate change and health. A teaching concept is presented that incorporates the core elements of climate-health literacy. On a first level, physical and climatological basics are taught, direct and indirect impacts of climate change on human health, climate protective measures, the psychological background of climate-protective behavior, and professional ethics. Furthermore, via self-awareness and self-reflection, the impact of climate change on the student's mental health should be evaluated. In an advanced level, the direct and indirect impacts of climate change on mental health are taught, coping strategies, resilience, and vulnerability, as well as the role of health-care professionals in the climate crisis. In expert-level lectures, the knowledge can be deepened, and special content like activist burnout can be addressed.

BREATH-Net: a novel deep learning framework for NO2 prediction using bi-directional encoder with transformer

Air pollution poses a significant challenge in numerous urban regions, negatively affecting human well-being. Nitrogen dioxide (NO2) is a prevalent atmospheric pollutant that can potentially exacerbate respiratory ailments and cardiovascular disorders and contribute to cancer development. The present study introduces a novel approach for monitoring and predicting Delhi's nitrogen dioxide concentrations by leveraging satellite data and ground data from the Sentinel 5P satellite and monitoring stations. The research gathers satellite and monitoring data over 3 years for evaluation. Exploratory data analysis (EDA) methods are employed to comprehensively understand the data and discern any discernible patterns and trends in nitrogen dioxide levels. The data subsequently undergoes pre-processing and scaling utilizing appropriate techniques, such as MinMaxScaler, to optimize the model's performance. The proposed forecasting model uses a hybrid architecture of the Transformer and BiLSTM models called BREATH-Net. BiLSTM models exhibit a strong aptitude for effectively managing sequential data by adeptly capturing dependencies in both the forward and backward directions. Conversely, transformers excel in capturing extensive relationships over extended distances in temporal data. The results of this study will illustrate the proposed model's efficacy in predicting the levels of NO2 in Delhi. If effectively executed, this model can significantly enhance strategies for controlling urban air quality. The findings of this research show a significant improvement of RMSE = 9.06 compared to other state-of-the-art models. This study's primary objective is to contribute to mitigating respiratory health issues resulting from air pollution through satellite data and deep learning methodologies.

A High-Voltage-Specialized Direct-Current Triboelectric Nanogenerator for Air Purification

Human health and the environment face significant challenges of air pollution, which is predominantly caused by PM2.5 or PM10 particles. Existing control methods often require elevated energy consumption or bulky high-voltage electrical equipment. To overcome these limitations, a self-powered, convenient, and compact direct current high-voltage triboelectric nanogenerator based on triboelectrification and electrostatic breakdown effects is proposed. By optimizing the structure-design of the direct current triboelectric nanogenerator and corresponding output voltage, it can easily achieve an output voltage of over 3 kV with a high charge density of 320 µC m-2 . A power management circuit is designed to overcome the influence of third domain self-breakdown, optimize 92.5% amplitude of voltage shake, and raise 5% charge utilization ratio. With a device size as tiny as 2.25 cm3 , it can continuously drive carbon nanowires to generate negative ions that settle dust within 300 s. This compact, simple, efficient, and safe high-voltage direct current triboelectric nanogenerator represents a promising sustainable solution. It offers efficient dust mitigation, fostering cleaner environments, and enhancing overall health.

Health risks from extreme heat in China: Evidence from health insurance

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change.

Household fuel and direct carbon emission disparity in rural China

Universal access to clean fuels in household use is one explicit indicator of sustainable development while currently still billions of people rely on solid fuels for daily cooking. Despite of the recognized clean transition trend in general, disparities in household energy mix in different activities (e.g. cooking and heating) and historical trends remain to be elucidated. In this study, we revealed the historical changing trend of the disparity in household cooking and heating activities and associated carbon emissions in rural China. The study found that the poor had higher total direct energy consumption but used less modern energy, especially in cooking activities, in which the poor consumed 60 % more energy than the rich. The disparity in modern household energy use decreased over time, but conversely the disparity in total residential energy consumption increased due to the different energy elasticities as income increases. Though per-capita household CO2 and Black Carbon (BC) emissions were decreasing under switching to modern energies, the disparity in household CO2 and BC deepened over time, and the low-income groups emitted ∼ 10 kg CO2 more compared to the high-income population. Relying solely on spontaneous clean cooking transition had limited impacts in reducing disparities in household energy and carbon emissions, whereas improving access to modern energy had substantial potential to reduce energy consumption and carbon emissions and its disparity. Differentiated energy-related policies to promote high-efficiency modern heating energies affordable for the low-income population should be developed to reduce the disparity, and consequently benefit human health and climate change equally.

Variability of ambient air ammonia in urban Europe (Finland, France, Italy, Spain, and the UK)

This study addressed the scarcity of NH3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH3 concentration across sites reached 8.0 ± 8.9 μg/m3. Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 μg/m3), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 μg/m3, respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 μg/m3, with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH3 concentrations in urban Europe, contributing to future efforts in benchmarking NH3 pollution control in urban areas.

Quantifying source contributions to ambient NH3 using Geo-AI with time lag and parcel tracking functions

Ambient ammonia (NH3) plays an important compound in forming particulate matters (PMs), and therefore, it is crucial to comprehend NH3's properties in order to better reduce PMs. However, it is not easy to achieve this goal due to the limited range/real-time NH3 data monitored by the air quality stations. While there were other studies to predict NH3 and its source apportionment, this manuscript provides a novel method (i.e., GEO-AI)) to look into NH3 predictions and their contribution sources. This study represents a pioneering effort in the application of a novel geospatial-artificial intelligence (Geo-AI) base model with parcel tracking functions. This innovative approach seamlessly integrates various machine learning algorithms and geographic predictor variables to estimate NH3 concentrations, marking the first instance of such a comprehensive methodology. The Shapley additive explanation (SHAP) was used to further analyze source contribution of NH3 with domain knowledge. From 2016 to 2018, Taichung's hourly average NH3 values were predicted with total variance up to 96%. SHAP values revealed that waterbody, traffic and agriculture emissions were the most significant factors to affect NH3 concentrations in Taichung among all the characteristics. Our methodology is a vital first step for shaping future policies and regulations and is adaptable to regions with limited monitoring sites.

Improving consistency in estimating future health burdens from environmental risk factors: Case study for ambient air pollution

Future changes in exposure to risk factors should impact mortality rates and population. However, studies commonly use mortality rates and population projections developed exogenously to the health impact assessment model used to quantify future health burdens attributable to environmental risks that are therefore invariant to projected exposure levels. This impacts the robustness of many future health burden estimates for environmental risk factors. This work describes an alternative methodology that more consistently represents the interaction between risk factor exposure, population and mortality rates, using ambient particulate air pollution (PM2.5) as a case study. A demographic model is described that estimates future population based on projected births, mortality and migration. Mortality rates are disaggregated between the fraction due to PM2.5 exposure and other factors for a historic year, and projected independently. Accounting for feedbacks between future risk factor exposure and population and mortality rates can greatly affect estimated future attributable health burdens. The demographic model estimates much larger PM2.5-attributable health burdens with constant 2019 PM2.5 (∼10.8 million deaths in 2050) compared to a model using exogenous population and mortality rate projections (∼7.3 million), largely due to differences in mortality rate projection methods. Demographic model-projected PM2.5-attributable mortality can accumulate substantially over time. For example, ∼71 million more people are estimated to be alive in 2050 when WHO guidelines (5 µg m-3) are achieved compared to constant 2019 PM2.5 concentrations. Accounting for feedbacks is more important in applications with relatively high future PM2.5 concentrations, and relatively large changes in non-PM2.5 mortality rates.

Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model

Based on the panel data of 227 prefecture-level and above cities in China from 2002 to 2018, a panel linkage equation model is constructed to explore the bidirectional influence relationship between haze pollution and urban sprawl, and the results of the study find that, firstly, there is a bidirectional promotion of causality between haze pollution and urban sprawl. That is, PM2.5 not only has a significant positive effect on urban sprawl, but also urban sprawl has a significant positive correlation with haze pollution, which is further strengthened by adding the air flow coefficient instrumental variable. Second, the heterogeneity analysis yields that haze pollution has different effects on urban sprawl in different regions. Under the sub-regional samples, haze pollution and urban sprawl have a bi-directional significant negative impact relationship in the eastern region, none of the haze pollution and urban sprawl have a bi-directional significant impact relationship in the western region, but both the central region and the northeastern region have a significant positive impact relationship. Under different city sizes, haze pollution and urban sprawl in large, medium and small cities have a bi-directional significant positive impact relationship, and from the numerical size, the degree of influence of haze pollution on urban sprawl in large cities is greater than that in small and medium cities; while the degree of influence of urban sprawl on haze pollution in medium cities is greater than that in large and small cities. Accordingly, it is proposed that urban governance should be adapted to local conditions, focus on innovative technologies to reduce energy consumption, and utilize big data to manage cities.

A multi-scale lifecycle and technoeconomic framework for higher education fleet electrification

Transportation accounts for one-quarter of all energy related greenhouse gas emissions. As it pertains to transport electrification, higher education institutions-such as universities-can model solutions that affect broader society. Despite this, higher education's role in fleet electrification adoption has been understudied. We, therefore, modeled an archetypical higher education institution to analyze the carbon and economic payback periods of three electrification scenarios (Business-as-Usual, Targeted Electrification, and Full Electrification) using a cradle-to-grave lifecycle and technoeconomic approach. Given the archetypical higher education institution fleet of 368 vehicles, results show an economic ratio plateau point of about 8 years at 20 fuel-based cars replaced by electric vehicles and a carbon payback period peak of roughly 10 months at 50 fuel-based cars replaced. We then performed a multi-scalar analysis by leveraging implementation theory. We find that higher education institutions that adhere to the tenets of implementation theory are poised to be pro-environmental change agents in many regions and countries. The methods and findings herein can be adapted to other institutions, regardless of fleet size, and can bolster relevant decision-making outcomes now.