Air Pollution and Cardiovascular Disease

Cardiovascular risk patterns through AI-enhanced clustering of longitudinal health data

Objectives

A major cause of death worldwide, cardiovascular disease (CVD) is largely caused by risk factors like smoking, high blood pressure, poor diets, and a lack of physical activity. To find clear trends in the dynamics of CVD risk over time, this study used an unsupervised learning approach to examine the relationship between the incidence of CVD in Iranian adults and the longitudinal trajectories of risk factors.

Methods

A total of 1872 adults aged 40-79 years, free of atherosclerotic cardiovascular disease (ASCVD) at baseline, were included in the Tehran Lipid and Glucose Study (TLGS). Longitudinal data spanning over 10 years were analyzed using clustering techniques to identify distinct trajectories of CVD risk factors. K-means clustering was applied after standardizing data using the TimeSeriesScalerMeanVariance method, and the optimal number of clusters was determined using silhouette scores.

Results

The risk factor trajectories were grouped into four different clusters. Compared to Cluster 4, which represents the low-risk group, Cluster 1, which represents the high-risk group, exhibited a significantly higher hazard of CVD events. The high-risk cluster showed a noteworthy 89% incidence of CVD during the first five years of follow-up. The results suggest that risk factor trajectories may better discriminate individuals at risk of CVD.

Conclusions

This study highlights the utility of trajectory-based clustering to identify high-risk individuals for CVD more effectively. Regular monitoring and longitudinal assessment of risk factor trajectories may improve the early identification of at-risk individuals and enable targeted prevention strategies to mitigate CVD incidence.

The Association Between Ambient Particulate Matter Exposure and Anemia in HIV/AIDS Patients

BACKGROUND

Anemia is common among HIV/AIDS patients, impacting prognosis. Particulate matter (PM) exposure is an understudied, potentially modifiable risk factor in this group.

METHODS

We gathered 36,266 hemoglobin (Hb) measurements from 6808 HIV/AIDS patients from the HIV/AIDS Comprehensive Response Information Management System from 1 January 2004 to 31 December 2021. We evaluated the relationship between Hb levels and short-term PM exposure using linear mixed-effects models. We used logistic regression to estimate the association of long-term PM exposure with baseline anemia prevalence and time-varying Cox models to estimate the association of long-term PM exposure with follow-up incidence of anemia. Mediation analysis explored the role of chronic kidney disease (CKD) in the association between PM exposure and anemia.

RESULTS

For every 5 µg/m³ increase in 28-day average PM 1 , Hb levels decreased by 0.43 g/l. For a 10 µg/m³ increase in PM 2.5 , Hb decreased by 0.55 g/l; for the same increase in PM 10, Hb decreased by 0.35 g/l. A 5 µg/m³ increase in 1-year average PM 1 corresponded to a 7% higher prevalence of anemia at baseline, a 10 µg/m³ increase in PM 2.5 to 8% higher prevalence, and a 10 µg/m³ increase in PM 10 to 6% higher prevalence. These rises in average PM concentrations during follow-up were associated with increased incident anemia by 54% (PM 1 ), 72% (PM 2.5 ), and 51% (PM 10 ). CKD partially mediated the positive associations between PM exposure and the incidence of anemia.

CONCLUSION

PM exposure was associated with lower Hb levels and higher incidence of anemia in HIV/AIDS patients and CKD with mediating estimated effects in PM-induced anemia.

Polycarbonate Nanofiber Filters with Enhanced Efficiency and Antibacterial Performance

The need for clean and safe air quality is a global priority that extends to diverse environments, including households, industrial spaces, and areas requiring respiratory personal protection. In this study, polycarbonate (PC) nanofiber filters coated with a coating containing a silver salt were prepared by the electrospinning process and a subsequent dipping-extraction method. These nanofiber filters presented the enhancement of air filtration efficiency and reinforcement of antibacterial properties. The research includes diverse PC filter structures, assessing beaded and non-beaded structures and varying areal weights. The study evaluated filtration efficiency across NaCl particle sizes (50-400 nm) and pressure drop outcomes. In addition, the antibacterial activity of the coated filters against E. coli and other coliforms was investigated by the filtration membrane method. Repetitive testing consistently yields high efficiencies, reaching 100% in thicker filters, and minimal air resistance in beaded filters, presenting an advantage over the current systems. Furthermore, the new properties of the filters will enhance environmental safety, and their time of use will be increased since they prevented the growth of bacteria, and no significant colonies were seen. Considering all these factors, these filters presented promising application in environments with harmful microorganisms, for the development of advanced industrial filtering systems or even hygienic masks.

Effect of Cu- and Fe- Isolated from Environmental Particulate Matter on Mitochondrial Dynamics in Human Colon CaCo-2 Cells

Atmospheric particulate matter (PM) is one of the most dangerous air pollutants of anthropogenic origin; it consists of a heterogeneous mixture of inorganic and organic components, including transition metals and polycyclic aromatic hydrocarbons. Although previous studies have focused on the effects of exposure to highly concentrated PM on the respiratory and cardiovascular systems, emerging evidence supports a significant impact of air pollution on the gastrointestinal (GI) tract by linking exposure to external stressors with conditions such as appendicitis, colorectal cancer, and inflammatory bowel disease. In general, it has been hypothesized that the main mechanism involved in PM toxicity consists of an inflammatory response and this has also been suggested for the GI tract. In the present study, we analyzed the effect of specific redox-active PM components, such as copper (Cu) and iron (Fe), in human intestinal cells focusing on ultrastructural integrity, redox homeostasis, and modulation of some mitochondrial-related markers. According to our results, exposure to Cu- and Fe-PM components and their combination induced ultrastructural alterations in the endoplasmic reticulum and in the mitochondria with an additive effect when combined. The increase in ROS and the loss of the mitochondrial mass in the cells exposed to PM indicates that mitochondria are a target of acute metal exposure. Furthermore, the gene expression and the protein levels of mitochondria dynamics markers were affected by the PM exposure. In particular, OPA1 increases at both gene and protein levels in all conditions while Mitofusin1 decreases significantly only in the presence of Fe. The increase in PINK expression is modulated by Fe, while Cu seems to affect mainly Parkin. Finally, a significant decrease in trans-epithelial resistance was also observed. In general, our study can confirm the correlation observed between pollution exposure areas and increased incidence of GI tract conditions.

Pathological Mechanisms of Particulate Matter-Mediated Ocular Disorders: A Review

Air pollution presents a severe risk to public health, with particulate matter (PM) identified as a significant hazardous element. However, despite the eye organ being constantly exposed to air pollution, only recently has the impact of PM on ocular health caught the attention of researchers and healthcare professionals. By compiling pertinent data, this paper aims to enhance our understanding of the underlying pathological mechanisms of PM-mediated ocular disorders and facilitate the development of effective treatment strategies. Recent data support the association between exposure to PM and the development of ocular pathologies such as dry eye syndrome, retinal atherosclerosis, and glaucoma. Based on the results of multiple studies, PM exposure can lead to oxidative stress, inflammation, autophagy, cell death, and, ultimately, the development of ophthalmic diseases. This review aims to consolidate the latest findings on PM-mediated ocular diseases by summarizing the outcomes from epidemiological, in vitro, and in vivo studies on ocular surface and retinal disorders as well as other relevant ophthalmic disorders.

Air pollution generated in an industrial region: Effect on the cardiovascular health of humans and damage caused to a plant species, Piper gaudichaudianum (Piperaceae), used for biomonitoring

Atmospheric pollution due to anthropogenic activities is a complex mixture of gasses and particulate matter (PM) that is currently one of the main causes of premature death in the world. Similarly, it is also capable of directly interfering with plant species by reducing their photosynthetic capacity and growth and killing cells. This work is about an observational study conducted in a region with two industries: a mine and an automobile parts manufacturer. Mining rocks is a source of PM in the air like that caused by other industrial activities. Twenty-five people that work or live in the industrial region cited (area A) and 25 people that live further away (area B) were selected to evaluate their vital signs and conduct a transthoracic echocardiogram. Leaves of Piper gaudichaudianum (Piperaceae), a native plant species, were also collected in both areas and evaluated in a laboratory. The PM accumulated on the leaves was evaluated using scanning electron microscopy (SEM) and inductively coupled plasma-optical emission spectrometry (ICP-OES). A statistical difference (P < 0.05) was verified for the levels of systolic blood pressure (SBP), diastolic blood pressure (DBP), and left ventricular mass index by echocardiography; the values were greater in people in area A. For the plant analysis, there was a statistical difference for all characters evaluated, chlorophyll levels, fresh mass, dry mass and leaf area were reduced, and thickness was greater in area A (P < 0.001). The PM analysis revealed a predominance of silicon, iron, and aluminum chemical elements. The present study suggests that particulate matter pollution is harmful to both humans and the flora.

Analysis of the global burden of cardiovascular diseases linked to exposure to ambient particulate matter pollution from 1990 to 2019

Background

This research endeavors to scrutinize the temporal trends and global burden of cardiovascular diseases (CVDs) associated with ambient particulate matter (PM) pollution spanning from 1990 to 2019.

Methods

Age-standardized death rates (ASDRs) and age-standardized disability-adjusted life years (DALYs) for CVDs, as well as their estimated annual percentage changes (EAPCs), were calculated using data from the Global Burden of Disease Study 2019 (GBD 2019).

Results

The global ASDR and age-standardized DALYs due to CVDs associated with PM pollution increased from 1990 to 2019, with a higher increase in males. The burden was higher among middle-aged and older adults. The ASDR and DALYs increased in low-Socio-demographic Index (SDI), low-middle-SDI, and middle-SDI countries, while they decreased in high-SDI countries. The highest burden was observed in Central Asia, North Africa, the Middle East, East Asia, and South Asia. The highest burdens were reported in Iraq, Egypt, and Uzbekistan at the national level.

Conclusion

The burden of CVDs linked to PM pollution has grown significantly from 1990 to 2019, with variations across regions and countries, highlighting the need for targeted prevention and pollution management strategies.

Ambient Air Pollution and Incident Cardiovascular Disease in People With Type 2 Diabetes Mellitus: A Cohort Study

OBJECTIVES

We aimed to assess the effect of air pollution on incident cardiovascular disease (CVD) in people with type 2 diabetes mellitus (T2DM).

METHODS

We tracked 486 T2DM patients from 2012 to 2021. Cox regression models were applied to assess the hazard of exposure to particulate matter, carbon monoxide (CO), ozone, nitrogen dioxide, and sulfur dioxide (SO 2 ) on incident CVD, revealing hazard ratios (HRs).

RESULTS

CVD incidents occurred in 73 individuals. Among men, each 1-ppm increase in CO levels raised the risk of CVD (HR: 2.66, 95% CI: 1.30-5.44). For women, a 5-ppb rise in SO 2 increased CVD risk (HR: 1.60, 95% CI: 1.11-2.30). No notable impact of particulate pollutants was found.

CONCLUSIONS

Persistent exposure to gaseous air pollutants, specifically CO and SO 2 , is linked to the development of CVD in men and women with T2DM.

The climate change-pollution-aerobiome nexus: A 'systems thinking' mini-review

The interrelationship between climate change, pollution and the aerobiome (the microbiome of the air) is a complex ecological dynamic with profound implications for human and ecosystem health. This mini-review explores the multifaceted relationships among these factors. By synthesising existing research and integrating interdisciplinary perspectives, we examine the mechanisms driving interactions within the climate change-pollution-aerobiome nexus. We also explore synergistic and cascading effects and potential impacts on human health (including both communicable and non-communicable diseases) and that of wider ecosystems. Based on our mini-review results, climate change influences air pollution and, independently, air pollution affects the composition, diversity and activity of the aerobiome. However, we apply a 'systems thinking' approach and create a set of systems diagrams to show that climate change likely influences the aerobiome (including bacteria and fungi) via climate change-pollution interactions in complex ways. Due to the inherent complexity of these systems, we emphasise the importance of holistic and/or interdisciplinary approaches and collaborative efforts in understanding this nexus to safeguard planetary health in an era of rapid environmental change.

Susceptible Detection of Organic Molecules Based on C3B/Graphene and C3N/Graphene van der Waals Heterojunction Gas Sensors

Constructing van der Waals (vdW) heterostructures is a prospective approach that is essential for developing a new generation of functional two-dimensional (2D) materials and designing new conceptual nanodevices. Using density-functional theory combined with a nonequilibrium Green's function approach allows for the theoretical and systematic exploration of the electronic structure, transport properties, and sensitivity of organic small molecules adsorbed on 2D C3B/graphene (Gra) and C3N/Gra vdW heterojunctions. Calculations show the metallic properties of C3B/Gra and C3N/Gra after the formation of heterojunctions. Interestingly, the heterojunctions C3B/Gra (C3N/Gra) for the adsorption of small organic molecules (C2H2, C2H4, CH3OH, CH4, and HCHO) at the C3B (C3N) side are sensitive to the chemisorption of C2H2 and C2H4. Similarly, the Gra/C3B is chemisorbed for both C2H2 and C2H4 when adsorbed on Gra side, while it is only chemisorbed for C2H2 in Gra/C3N. Interestingly, all heterojunctions on different sides are physisorbed for CH3OH, CH4, and HCHO. Furthermore, the calculated I-V curves demonstrate that the devices based on the adsorption of C2H2 and C2H4 at each side of the heterojunction have remarkable anisotropy, in with the current being considerably greater in the zigzag direction than in the armchair direction. More specifically, with C2H2 adsorbed on the Gra side, the sensitivity along the armchair direction is up to 85.0% for Gra/C3B and close to 100% for Gra/C3N. This study reveals that C3B/Gra (C3N/Gra) heterojunctions with high selectivity, high anisotropy, and excellent sensitivity are highly prospective 2D materials for applications, which further contributes new insights into the development of future electronic nanodevices.

Long-term exposure to air pollution, greenness and temperature and survival after a nonfatal myocardial infarction

BACKGROUND

Little is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI).

OBJECTIVE

The goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI.

METHODS

We used data from the US-based Nurses' Health Study to construct an open cohort of survivors of a nonfatal MI 1990-2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM2.5) and nitrogen dioxide (NO2), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification.

RESULTS

Among 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO2 increase and suggestive positive associations were observed for PM2.5, lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO2, PM2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature.

CONCLUSION

We observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures.

Examining air pollution exposure dynamics in disadvantaged communities through high-resolution mapping

This study bridges gaps in air pollution research by examining exposure dynamics in disadvantaged communities. Using cutting-edge machine learning and massive data processing, we produced high-resolution (100 meters) daily air pollution maps for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California for 2012-2019. Our findings revealed opposite spatial patterns of NO2 and PM2.5 to that of O3. We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019, although the most disadvantaged communities saw the largest NO2 and PM2.5 reductions and the advantaged neighborhoods experienced greatest rising O3 concentrations. Further, day-to-day exposure variations decreased for NO2 and O3. The disparity in NO2 exposure decreased, while it persisted for O3. In addition, PM2.5 showed increased day-to-day variations across all communities due to the increase in wildfire frequency and intensity, particularly affecting advantaged suburban and rural communities.

Affective Sensitivity to Air Pollution (ASAP): Person-specific associations between daily air pollution and affective states

Individuals' sensitivity to climate hazards is a central component of their vulnerability to climate change. In this paper, we introduce and outline the utility of a new intraindividual variability construct, affective sensitivity to air pollution (ASAP)-defined as the extent to which an individual's affective states fluctuate in accordance with daily changes in air quality. As such, ASAP pushes beyond examination of differences in individuals' exposures to air pollution to examination of differences in individuals' sensitivities to air pollution. Building on known associations between air pollution exposure and adverse mental health outcomes, we empirically illustrate how application of Bayesian multilevel models to intensive repeated measures data obtained in an experience sampling study (N = 150) over one year can be used to examine whether and how individuals' daily affective states fluctuate with the daily concentrations of outdoor air pollution in their county. Results indicate construct viability, as we found substantial interindividual differences in ASAP for both affect arousal and affect valence. This suggests that repeated measures of individuals' day-to-day affect provides a new way of measuring their sensitivity to climate change. In addition to contributing to discourse around climate vulnerability, the intraindividual variability construct and methodology proposed here can help better integrate affect and mental health in climate adaptation policies, plans, and programs.

Water-soluble organic compounds (WSOC) from atmospheric aerosols in Bou-Ismail (Algeria)

In this contribution, we report the study of nuclear resonance magnetic spectroscopy techniques (1H-NMR, 13C-NMR, and 2D-NMR) efficiency in the characterisation of the functional composition of water-soluble organic compounds (WSOC) from atmospheric aerosols. The chosen site was our scientific and technical center of research (CRAPC) situated in Algerian Bou-Ismail city. where the concentrations of PM10 were found to be between 15.66 and 142.19 µg.m-3. As results, 1H-NMR analysis showed the coexistence of biological material and emissions from urban and biomass burning. The dominant source was identified by quantitative integration of each 1H NMR spectral region. By using the HSQC technique, many peaks are revealed in biogenic samples including biomass burning. On the other hand, the identification of the source of various organic compounds and their functional composition is possible through specific NMR spectra, which can also be used to adjust the surrounding organic aerosol sources.

Delayed effects of air pollution on public bike-sharing system use in Seoul, South Korea: A time series analysis

BACKGROUND

As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution.

METHOD

To assess the short-term impact of daily exposure to multiple air pollutants (PM2.5, PM10, NO2, and O3) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018-2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19.

RESULTS

We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM2.5, 0.89% (0.85% to 0.94%) for PM10, 0.87% (0.82% to 0.91%) for O3, and 0.92% (0.87% to 0.98%) for NO2, reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants.

CONCLUSIONS

Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured.

Validity of Mobility-Based Exposure Assessment of Air Pollution: A Comparative Analysis with Home-Based Exposure Assessment

Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.

Optimal decision-making in relieving global high temperature-related disease burden by data-driven simulation

The rapid acceleration of global warming has led to an increased burden of high temperature-related diseases (HTDs), highlighting the need for advanced evidence-based management strategies. We have developed a conceptual framework aimed at alleviating the global burden of HTDs, grounded in the One Health concept. This framework refines the impact pathway and establishes systematic data-driven models to inform the adoption of evidence-based decision-making, tailored to distinct contexts. We collected extensive national-level data from authoritative public databases for the years 2010-2019. The burdens of five categories of disease causes - cardiovascular diseases, infectious respiratory diseases, injuries, metabolic diseases, and non-infectious respiratory diseases - were designated as intermediate outcome variables. The cumulative burden of these five categories, referred to as the total HTD burden, was the final outcome variable. We evaluated the predictive performance of eight models and subsequently introduced twelve intervention measures, allowing us to explore optimal decision-making strategies and assess their corresponding contributions. Our model selection results demonstrated the superior performance of the Graph Neural Network (GNN) model across various metrics. Utilizing simulations driven by the GNN model, we identified a set of optimal intervention strategies for reducing disease burden, specifically tailored to the seven major regions: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa. Sectoral mitigation and adaptation measures, acting upon our categories of Infrastructure & Community, Ecosystem Resilience, and Health System Capacity, exhibited particularly strong performance for various regions and diseases. Seven out of twelve interventions were included in the optimal intervention package for each region, including raising low-carbon energy use, increasing energy intensity, improving livestock feed, expanding basic health care delivery coverage, enhancing health financing, addressing air pollution, and improving road infrastructure. The outcome of this study is a global decision-making tool, offering a systematic methodology for policymakers to develop targeted intervention strategies to address the increasingly severe challenge of HTDs in the context of global warming.

Healthcare sustainability in cardiothoracic surgery

BACKGROUND

Climate change is the greatest threat to human health. Cardiothoracic patients suffer direct consequences from poor environmental health and we have a vested interest to address this in our practice. As leaders of complex high-end surgery, we are uniquely positioned to effect practical and immediate changes to significantly pare down emissions within the operating theatre, outside the operating theatre and beyond the confines of the hospital.

METHODS

We aim to spotlight this pressing issue, take stock of our current efforts, and encourage fellow specialists to drive this agenda.

RESULTS

Sustainability in healthcare needs to be formalized as part of the core curriculum in surgical training and awareness generated via carbon audits and life cycle analyses. Practical actions such as reducing unnecessary equipment usage, choosing reusable equipment over single use disposables, judicious use of investigations rooted in clinical reasoning and sharing of resources across services and health systems help reduce the carbon output of our specialty.

CONCLUSION

The 'Triple Bottom Line' serves as a good template to calibrate efforts that balance quality against environmental costs. More can be done to advocate for and find solutions for sustainable healthcare with cardiothoracic surgery.

Nature and human well-being: The olfactory pathway

The world is undergoing massive atmospheric and ecological change, driving unprecedented challenges to human well-being. Olfaction is a key sensory system through which these impacts occur. The sense of smell influences quality of and satisfaction with life, emotion, emotion regulation, cognitive function, social interactions, dietary choices, stress, and depressive symptoms. Exposures via the olfactory pathway can also lead to (anti-)inflammatory outcomes. Increased understanding is needed regarding the ways in which odorants generated by nature (i.e., natural olfactory environments) affect human well-being. With perspectives from a range of health, social, and natural sciences, we provide an overview of this unique sensory system, four consensus statements regarding olfaction and the environment, and a conceptual framework that integrates the olfactory pathway into an understanding of the effects of natural environments on human well-being. We then discuss how this framework can contribute to better accounting of the impacts of policy and land-use decision-making on natural olfactory environments and, in turn, on planetary health.

Quantifying uncertainty: Air quality forecasting based on dynamic spatial-temporal denoising diffusion probabilistic model

Air pollution constitutes a substantial peril to human health, thereby catalyzing the evolution of an array of air quality prediction models. These models span from mechanistic and statistical strategies to machine learning methodologies. The burgeoning field of deep learning has given rise to a plethora of advanced models, which have demonstrated commendable performance. However, previous investigations have overlooked the salience of quantifying prediction uncertainties and potential future interconnections among air monitoring stations. Moreover, prior research typically utilized static predetermined spatial relationships, neglecting dynamic dependencies. To address these limitations, we propose a model named Dynamic Spatial-Temporal Denoising Diffusion Probabilistic Model (DST-DDPM) for air quality prediction. Our model is underpinned by the renowned denoising diffusion model, aiding us in discerning indeterminacy. In order to encapsulate dynamic patterns, we design a dynamic context encoder to generate dynamic adjacency matrices, whilst maintaining static spatial information. Furthermore, we incorporate a spatial-temporal denoising model to concurrently learn both spatial and temporal dependencies. Authenticating our model's performance using a real-world dataset collected in Beijing, the outcomes indicate that our model eclipses other baseline models in terms of both short-term and long-term predictions by 1.36% and 11.62% respectively. Finally, we conduct a case study to exhibit our model's capacity to quantify uncertainties.

Burden of cardiovascular disease attributed to air pollution: a systematic review

BACKGROUND

Cardiovascular diseases (CVDs) are estimated to be the leading cause of global death. Air pollution is the biggest environmental threat to public health worldwide. It is considered a potentially modifiable environmental risk factor for CVDs because it can be prevented by adopting the right national and international policies. The present study was conducted to synthesize the results of existing studies on the burden of CVDs attributed to air pollution, namely prevalence, hospitalization, disability, mortality, and cost characteristics.

METHODS

A systematic search was performed in the Scopus, PubMed, and Web of Science databases to identify studies, without time limitations, up to June 13, 2023. Exclusion criteria included prenatal exposure, exposure to indoor air pollution, review studies, conferences, books, letters to editors, and animal and laboratory studies. The quality of the articles was evaluated based on the Agency for Healthcare Research and Quality Assessment Form, the Newcastle-Ottawa Scale, and Drummond Criteria using a self-established scale. The articles that achieved categories A and B were included in the study.

RESULTS

Of the 566 studies obtained, based on the inclusion/exclusion criteria, 92 studies were defined as eligible in the present systematic review. The results of these investigations supported that chronic exposure to various concentrations of air pollutants, increased the prevalence, hospitalization, disability, mortality, and costs of CVDs attributed to air pollution, even at relatively low levels. According to the results, the main pollutant investigated closely associated with hypertension was PM2.5. Furthermore, the global DALY related to stroke during 2016-2019 has increased by 1.8 times and hospitalization related to CVDs in 2023 has increased by 8.5 times compared to 2014.

CONCLUSION

Ambient air pollution is an underestimated but significant and modifiable contributor to CVDs burden and public health costs. This should not only be considered an environmental problem but also as an important risk factor for a significant increase in CVD cases and mortality. The findings of the systematic review highlighted the opportunity to apply more preventive measures in the public health sector to reduce the footprint of CVDs in human society.

Air pollution, cardiorespiratory fitness and biomarkers of oxidative status and inflammation in the 4HAIE study

The aim of this study was to investigate the associations between cardiorespiratory fitness (CRF), long-term air pollution exposure and biochemical markers of oxidative status and inflammation. This is a cross-sectional investigation focusing on biochemical markers of oxidative status and inflammation. Participants were Caucasian (N = 1188; age 18-65 years) who lived for at least 5 years in a high air-polluted (Moravian-Silesian; MS) or low air-polluted (South Bohemia; SB) region of the Czech Republic. Healthy runners and inactive individuals were recruited. A multiple regression analysis was used to explain the relationship between multiple independent variables (CRF, trunk fat mass, sex, socioeconomic status, and region (MS region vs. SB region) and dependent variables (oxidative status, inflammation). CRF, trunk fat mass, age and sex significantly predicted almost all selected markers of oxidative status and inflammation (except GSSG, GSH/GSSG and BDNF). Participants living in the MS region presented significantly higher GPx (by 3.1%) and lower BDNF values (by 4.5%). All other investigated biochemical markers were not significantly influenced by region. We did not find meaningful interactions between long-term air-pollution exposure versus markers of oxidative status and inflammation. However, we showed various significant interactions with sex, age, CRF and body composition. The significant association of living in the high air polluted MS region with the BDNF level warrants further attention.

Real-time application and modelling of the NOx-sorption reaction on a particulate calcium carbonate surface-flow filter exposed to combustion exhaust

Of major interest, especially in city environments, and increasingly inside vehicles or industrial plants, is the drive to reduce human exposure to nitrogen oxides (NOx). This trend has drawn increasing attention to filtration, which has developed remarkably owing to the capabilities of recently developed mathematical models and novel filter concepts. This paper reports on the study of the kinetic modelling of adsorption of nitrogen dioxide (NO2), collected from the tailpipe of a diesel engine, reacting to calcium nitrate salt (Ca(NO3)2) on a surface flow filter consisting of a coating of fine ground limestone or marble (CaCO3) in combination with micro-nanofibrillated cellulose (MNFC) acting as binder and humectant applied onto a multiply recycled newsprint substrate. The coating and substrate are both porous, but on different pore size scales, with the coating having significantly lower permeability. To maximise gas-coating contact, therefore, the coating deposition is pixelated, achieved by pin coating. An axially dispersed gaseous plug flow model (dispersion model) was used to simulate the transport within the coating pore network structure, following earlier flow modelling studies, and a kinetic reaction model was used to examine NO2 to NO3- conversion in correlation with experimental results. Modelling results indicate a 60.38% conversion of exposed NO2 gas to Ca(NO3)2 under the specific conditions applied, with an absolute relative error between the predicted and experimentally estimated value being 0.81%. The model additionally enabled a prediction of effects of changing parameters over a limited perturbation range, thus assisting in predicting filter element consumption, with attention given to the active component CaCO3 surface as a function of particle size in relation to the gas contact exchange, promoting the reaction over time. It is intended that the Ca(NO3)2 formed from the reaction can go on to be used as a value-added fertiliser, thus contributing to circular economy.

Modulatory effects of dietary saturated fatty acids on platelet mitochondrial function following short-term exposure to ambient Particulate Matter (PM2.5)

Exposure to ambient fine particulate matter (PM2.5) was found to produce vascular injury, possibly by activating platelets within days after exposure. The aim of this study was to investigate the modulatory effects of dietary saturated fatty acids on platelet mitochondrial respiratory parameters following short-term inhalational exposure to PM2.5. A total of 22 healthy male volunteers were recruited from the Research Triangle area of North Carolina. Platelets were isolated from fresh whole blood samples and mitochondrial respiratory parameters were measured using an extracellular flux analyzer. Intake of saturated fat was averaged from multiple 24-hr dietary recalls. Daily ambient PM2.5 concentrations were obtained from ambient air quality monitoring stations. Correlation and ANOVA were used in data analyses, along with the pick-a-point method and the Johnson-Neyman technique for probing moderation. After controlling for age and omega-3 index, the intake of dietary saturated fatty acids after reaching 9.3% or higher of the total caloric intake significantly moderated the associations between PM2.5 exposure and several platelet mitochondrial respiratory parameters. In conclusion, dietary saturated fatty acids above 9.3% of total caloric intake influenced the relationship between short-term PM2.5 exposure and platelet mitochondrial respiration. Further research is needed to understand these associations and their implications for cardiovascular health.

Nature-Inspired Regenerative Fine-Dust-Catching Coatings to Improve Air Quality

Increased particulate matter (PM) concentrations in our ambient air are the cause of various life-threatening diseases and consequently need to be reduced to nonhazardous levels. The natural PM removal capabilities of leaves inspired the development of a low-cost coating technology that exploits natural weather phenomena for its PM catching and removal processes. The herein presented coating is based on microparticle-filled silicone with optimized chemical and physical surface properties. Its surface roughness was tuned using differently sized spray-dried particles, and its surface contact angle was adjusted through silicone tensides, polar ether groups incorporated in the silicon backbone, and the used amount of spray-dried particles. In such a way, optimized silicone coatings showed in laboratory experiments improved catching abilities (>300% relative to glass surfaces), a full retention of adsorbed PM during wind events, and the formation of large PM aggregates. Upon (simulated) rain events, these coatings were regenerated, and the content of harmful PM of various sizes dispersed in water was reduced between ∼73 and 100%. Furthermore, an outdoor test over 100 days showed the functioning of the coating under real-world conditions. These regenerative coatings are readily applicable on diverse surfaces and do not require any further technical infrastructure. Thus, they present an extension of the toolbox for PM reduction technologies.

Disentangling impacts of multiple pollutants on acute cardiovascular events in New York city: A case-crossover analysis

BACKGROUND

Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide.

OBJECTIVES

We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk.

METHODS

We used conditional logistic regression in a case-crossover design - inherently controlling for all confounders not varying within case month - to examine associations between spatio-temporal nitrogen dioxide (NO2), fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone (O3) in New York City, 2005-2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction].

RESULTS

We found significant same-day associations between NO2 and risk of overall CVD, IHD, and HF - and between PM2.5 and overall CVD or HF event risk - robust to all adjustments and multiple comparisons. Results were comparable by sex and race - though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO2 were comparable for adults younger or older than 69 years, though PM2.5 associations were stronger among older adults.

DISCUSSION

Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility.

A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin

The profound impacts of severe air pollution on human health, ecological balance, and economic stability are undeniable. Precise air quality forecasting stands as a crucial necessity, enabling governmental bodies and vulnerable communities to proactively take essential measures to reduce exposure to detrimental pollutants. Previous research has primarily focused on predicting air quality using only time-series data. However, the importance of remote-sensing image data has received limited attention. This paper proposes a new multi-modal deep-learning model, Res-GCN, which integrates high spatial resolution remote-sensing images and time-series air quality data from multiple stations to forecast future air quality. Res-GCN employs two deep-learning networks, one utilizing the residual network to extract hidden visual information from remote-sensing images, and another using a dynamic spatio-temporal graph convolution network to capture spatio-temporal information from time-series data. By extracting features from two different modalities, improved predictive performance can be achieved. To demonstrate the effectiveness of the proposed model, experiments were conducted on two real-world datasets. The results show that the Res-GCN model effectively extracts multi-modal features, significantly enhancing the accuracy of multi-step predictions. Compared to the best-performing baseline model, the multi-step prediction's mean absolute error, root mean square error, and mean absolute percentage error increased by approximately 6%, 7%, and 7%, respectively.

Association between Ambient Particulate Air Pollution and Soluble Biomarkers of Endothelial Function: A Meta-Analysis

BACKGROUND

The burden of cardiovascular diseases caused by ambient particulate air pollution is universal. An increasing number of studies have investigated the potential effects of exposure to particulate air pollution on endothelial function, which is one of the important mechanisms for the onset and development of cardiovascular disease. However, no previous study has conducted a summary analysis of the potential effects of particulate air pollution on endothelial function.

OBJECTIVES

To summarize the evidence for the potential effects of short-term exposure to ambient particulate air pollution on endothelial function based on existing studies.

METHODS

A systematic literature search on the relationship between ambient particulate air pollution and biomarkers of endothelial function including endothelin-1 (ET-1), E-selectin, intercellular cell adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1) was conducted in PubMed, Scopus, EMBASE, and Web of Science up to 20 May 2023. Subsequently, a meta-analysis was conducted using a random effects model.

RESULTS

A total of 18 studies were included in this meta-analysis. A 10 μg/m3 increase in short-term exposure to ambient PM2.5 was associated with a 1.55% (95% CI: 0.89%, 2.22%) increase in ICAM-1 and a 1.97% (95% CI: 0.86%, 3.08%) increase in VCAM-1. The associations of ET-1 (0.22%, 95% CI: -4.94%, 5.65%) and E-selectin (3.21%, 95% CI: -0.90% 7.49%) with short-term exposure to ambient PM2.5 were statistically insignificant.

CONCLUSION

Short-term exposure to ambient PM2.5 pollution may significantly increase the levels of typical markers of endothelial function, including ICAM-1 and VCAM-1, suggesting potential endothelial dysfunction following ambient air pollution exposure.

Associations between exposure to air pollution and sex hormones during the menopausal transition

Menopause is a significant milestone in a woman's life, characterized by decreasing estradiol (E2) and increasing follicle-stimulating hormone (FSH) levels. Growing evidence suggests that air pollution may affect reproductive health and disrupt hormone profiles, yet the associations in women undergoing menopausal transition (MT) remains underexplored. We examined the associations between annual air pollutant exposures and repeated measures of E2 and FSH in 1365 women with known final menstrual period (FMP) date from the Study of Women's Health Across the Nation. Air pollution was calculated as the annual averages of 24-h average PM2.5 levels, daily one-hour maximum NO2 levels, and daily 8-h maximum O3 levels. Linear mixed models with piece-wise linear splines were used to model non-linear trajectories of E2 and FSH in three distinct time periods: up to 2 years before the FMP (early MT), within 2 years before and 2 years after FMP (transmenopause), and >2 years post-FMP (postmenopause). In the transmenopausal period, an interquartile (5 μg/m3) increase in PM2.5 was associated with a significant decrease in E2 levels (-15.7 %, 95 % CI: -23.7, -6.8), and a 10 ppb increase in NO2 was associated with a significant decrease in E2 levels (-9.2 %, 95 % CI: -16.2, -1.7). A higher PM2.5 was also associated with an accelerated rate of decline in E2. Regarding FSH, a 10 ppb increase in NO2 was associated with decline in FSH levels (-11.7 %, 95 % CI: -21.8, -0.1) in the early MT and accelerated rates of decline in the postmenopause (-1.1 % per year, 95 % CI: -2.1, -0.1). Additionally, inverse associations between O3 and FSH were observed in the transmenopause and postmenopause. Our study suggests that increases in PM2.5, NO2, and O3 exposures are linked to significant declines in E2 and FSH levels across menopausal stages, suggesting the detrimental impact of air pollutants on women's reproductive hormones.

The effect of haze pollution on rural-to-urban migrants' long-term residence intentions

Severe haze pollution in China threatens human health, and its negative effect hampers rural-to-urban migrants' settlement intentions in destination cities. Using the 2017 China Migrants Dynamic Survey Data (CMDS), the satellite data of PM2.5, and city-level data, this study investigates the impact of haze pollution on rural migrants, long-term residence intentions in Chinese context with IV-probit model, and mediating effect model. Overall, we find an inverted U-shaped relationship between the level of haze pollutants and rural migrants' long-term settlement intentions. Robustness check using multi-measures and thermal inversion as the instrumental variable supports this conclusion. The mediating effect model shows haze pollution plays its role through two opposite mechanisms: signal effect and health effect. When the size of signal effect is larger than health effect, rural migrants are inclined to settle down in their host cities; otherwise, they show lower settlement willingness. The turning point appears when PM2.5 concentration reaches 38.5 μg/m3; migrants have the highest long-term residence intentions. Currently, the national average PM2.5 concentration is 40.98 μg/m3, indicating that China is at the stage where the health effect of haze pollution holds a dominant position. Haze pollution has heterogeneous impacts on migrants' residence intentions. From the individual level, the younger generation, female, and higher-educated migrants have a higher tolerance for polluted air. From the city level, migrants who work in the city with 5 to 10 million dwellers have the highest long-term residence intention and are less sensitive to haze pollution. Thus, we propose stringent environmental regulations and more inclined public service policies to migrants.

Residential Greenness and Long-term Mortality Among Patients Who Underwent Coronary Artery Bypass Graft Surgery

BACKGROUND

Studies have reported inverse associations between exposure to residential greenness and mortality. Greenness has also been associated with better surgical recovery. However, studies have had small sample sizes and have been restricted to clinical settings. We investigated the association between exposure to residential greenness and all-cause mortality among a cohort of cardiac patients who underwent coronary artery bypass graft (CABG) surgery.

METHODS

We studied this cohort of 3,128 CABG patients between 2004 and 2009 at seven cardiothoracic departments in Israel and followed patients until death or 1st May 2021. We collected covariate information at the time of surgery and calculated the patient-level average normalized difference vegetation index (NDVI) over the entire follow-up in a 300 m buffer from the home address. We used Cox proportional hazards regression models to estimate associations between greenness and death, adjusting for age, sex, origin, socioeconomic status, type of hospital admission, peripherality, air pollution, and distance from the sea.

RESULTS

Mean age at surgery was 63.8 ± 10.6 for men and 69.5 ± 10.0 for women. During an average of 12.1 years of follow-up (37,912 person-years), 1,442 (46%) patients died. A fully adjusted Cox proportional hazards model estimated a 7% lower risk of mortality (HR: 0.93, 95% CI = [0.85, 1.00]) per 1 interquartile range width increase (0.04) in NDVI. Results were robust to the use of different buffer sizes (100 m-1,250 m from the home) and to the use of average NDVI exposure during the first versus the last 2 years of follow-up.

CONCLUSIONS

Residential greenness was associated with lower risk of mortality in CABG patients.

Associations of long-term particulate matter exposure with cardiometabolic diseases: A systematic review and meta-analysis

BACKGROUND

This review aimed to establish a holistic perspective of long-term PM exposure and cardiometabolic diseases, identify long-term PM-related cardiovascular and metabolic risk factors, and provide practical significance to preventative measures.

METHOD

A combination of computer and manual retrieval was used to search for keywords in PubMed (2903 records), Embase (2791 records), Web of Science (5488 records) and Cochrane Library (163 records). Finally, a total of 82 articles were considered in this meta-analysis. Stata 13.0 was accustomed to inspecting the studies' heterogeneity and calculating the combined effect value (RR) by selecting the matching models. The subgroup analysis, sensitivity analysis and publication bias tests were also performed.

RESULTS

Meta-analysis figured an association between PM and cardiometabolic diseases. PM2.5 (per 10 μg/m3 increase) boosted the risk of hypertension (RR = 1.14, 95 % CI: 1.09-1.19), coronary heart disease (CHD) (RR = 1.21, 95 % CI: 1.08-1.35), diabetes (RR = 1.16, 95 % CI: 1.11-1.21) and stroke (including ischemic stroke and hemorrhagic stroke). PM10 (per 10 μg/m3 increase) elevated the incidence of hypertension (RR = 1.11, 95 % CI: 1.07-1.16) and diabetes (RR = 1.26, 95 % CI: 1.08-1.47). PM1 (per 10 μg/m3 increase) exposure increased the risk of total dyslipidemia, yielding the RR of 1.10 (95 % CI: 1.01-1.18). Furthermore, the elderly, overweight and higher background pollutant level were potentially susceptible to related diseases.

CONCLUSION

There was a virtual connection between long-term exposure to PM and cardiometabolic diseases. PM2.5 or PM10 (per 10 μg/m3) increased the risk of hypertension, CHD, diabetes, stroke and dyslipidemia, causing cardiovascular "multimorbidity" in high-risk populations.

Associations between residential greenness and air pollution and the incident metabolic syndrome in a Thai worker cohort

Increasing air pollution and decreasing exposure to greenness may contribute to the metabolic syndrome (MetS). We examined associations between long-term exposure to residential greenness and air pollution and MetS incidence in the Bangkok Metropolitan Region, Thailand. Data from 1369 employees (aged 52-71 years) from the Electricity Generating Authority of Thailand cohort from 2002 to 2017 were analyzed. The greenness level within 500 m of each participant's residence was measured using the satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The kriging approach was used to generate the average concentration of each air pollutant (PM10, CO, SO2, NO2, and O3) at the sub-district level. The average long-term exposure to air pollution and greenness for each participant was calculated over the same period of person-time. Cox proportional hazards models were used to analyze the greenness-air pollution-MetS associations. The adjusted hazard ratio of MetS was 1.42 (95% confidence interval (CI): 1.32, 1.53), 1.22 (95% CI: 1.15, 1.30), and 2.0 (95% CI: 1.82, 2.20), per interquartile range increase in PM10 (9.5 μg/m3), SO2 (0.9 ppb), and CO (0.3 ppm), respectively. We found no clear association between NDVI or EVI and the incidence of MetS. On the contrary, the incident MetS was positively associated with NDVI and EVI for participants exposed to PM10 at concentrations more than 50 μg/m3. In summary, the incidence of MetS was positively associated with long-term exposure to air pollution. In areas with high levels of air pollution, green spaces may not benefit health outcomes.

Integrating 4-D light-sheet fluorescence microscopy and genetic zebrafish system to investigate ambient pollutants-mediated toxicity

Ambient air pollutants, including PM2.5 (aerodynamic diameter d ~2.5 μm), PM10 (d ~10 μm), and ultrafine particles (UFP: d < 0.1 μm) impart both short- and long-term toxicity to various organs, including cardiopulmonary, central nervous, and gastrointestinal systems. While rodents have been the principal animal model to elucidate air pollution-mediated organ dysfunction, zebrafish (Danio rerio) is genetically tractable for its short husbandry and life cycle to study ambient pollutants. Its electrocardiogram (ECG) resembles that of humans, and the fluorescent reporter-labeled tissues in the zebrafish system allow for screening a host of ambient pollutants that impair cardiovascular development, organ regeneration, and gut-vascular barriers. In parallel, the high spatiotemporal resolution of light-sheet fluorescence microscopy (LSFM) enables investigators to take advantage of the transparent zebrafish embryos and genetically labeled fluorescent reporters for imaging the dynamic cardiac structure and function at a single-cell resolution. In this context, our review highlights the integrated strengths of the genetic zebrafish system and LSFM for high-resolution and high-throughput investigation of ambient pollutants-mediated cardiac and intestinal toxicity.

Sociodemographic inequalities in long-term exposure to air pollution, road traffic noise, and greenness: A population-based cohort study of women

Background

Recent evidence suggests environmental health inequalities both within and between European countries and socially deprived groups may be more susceptible to pollution. However, evidence is still inconclusive and additional studies are warranted. This study aims to investigate sociodemographic inequalities in long-term residential exposure to air pollution, road traffic noise, and greenness, taking lifestyle and degree of urbanization into account.

Methods

In total 20,407 women, born 1914-48 residing in Uppsala County, Sweden, were followed between 1997 and 2017. Time-varying sociodemographic variables were obtained from registers, and questionnaires provided lifestyle information. Generalized estimating equations were used to compute beta-coefficients (β) and 95% confidence intervals (95% CI) for associations between sociodemographic and lifestyle variables and spatial-temporal modeled particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), road traffic noise and greenness. All models were additionally stratified by urbanization type.

Results

Urban area residency was the most important predictor of high exposure to air pollution and noise, and to low greenness. For instance, β for NO2 was -2.92 (95% CI = -3.00, -2.83) and -3.10 (95% CI = -3.18, -3.01) µg/m3 in suburban and rural areas, respectively, compared with urban areas. For greenness, the opposite held true with corresponding β of 0.059 (95% CI = 0.056, 0.062) and 0.095 (95% CI = 0.092, 0.098). Within urban areas, elderly, unmarried and well-educated women had the highest environmental burden. However, less pronounced, and even reversed associations were found in suburban and rural areas.

Conclusion

This study provides evidence of a mixed pattern of environmental health inequalities across sociodemographic groups in urban areas.

Adjuvant effect of inhaled particulate matter containing free radicals following house-dust mite induction of asthma in mice

INTRODUCTION

Exposures to particulate matter (PM) from combustion sources can exacerbate preexisting asthma. However, the cellular and molecular mechanisms by which PM promotes the exacerbation of asthma remain elusive. We used a house dust mite (HDM)-induced mouse model of asthma to test the hypothesis that inhaled DCB230, which are PM containing environmentally persistent free radicals (EPFRs), will aggravate asthmatic responses.

METHODS

Groups of 8-10-week-old C57BL/6 male mice were exposed to either air or DCB230 aerosols at a concentration of 1.5 mg/m3 4 h/day for 10 days with or without prior HDM-induction of asthma.

RESULTS

Aerosolized DCB230 particles formed small aggregates (30-150 nm). Mice exposed to DCB230 alone showed significantly reduced lung tidal volume, overexpression of the Muc5ac gene, and dysregulation of 4 inflammation related genes, Ccl11, Ccl24, Il-10, and Tpsb2. This suggests DCB230 particles interacted with the lung epithelium inducing mucous hypersecretion and restricting lung volume. In addition to reduced lung tidal volume, compared to respective controls, the HDM + DCB230-exposed group exhibited significantly increased lung tissue damping and up-regulated expression of Muc5ac, indicating that in this model, mucous hypersecretion may be central to pulmonary dysfunction. This group also showed augmented lung eosinophilic inflammation accompanied by an up-regulation of 36 asthma related genes. Twelve of these genes are part of IL-17 signaling, suggesting that this pathway is critical for DCB230 induced toxicity and adjuvant effects in lungs previously exposed to HDM.

CONCLUSION

Our data indicate that inhaled DCB230 can act as an adjuvant, exacerbating asthma through IL-17-mediated responses in a HDM mouse model.

Short-term exposure to ultrafine and fine particulate matter with multipollutant modelling on heart rate variability among seniors and children from the CorPuScula (coronary, pulmonary, sanguis) longitudinal study in Germany

Background

Short-term exposure particulate matter with a diameter of 10 µm or less (PM10) and fine particulate matter (PM2.5) has been associated with heart rate variability (HRV), but exposure to ultrafine particles (UFP) has been less well examined. We investigated the associations between the HRV outcomes and short-term exposure to UFP, PM10 and PM2.5 among school-aged children and seniors.

Methods

CorPuScula (Coronary, Pulmonary and Sanguis) is a longitudinal, repeated-measure panel study conducted in 2000-2002 in Munich, Germany including 52 seniors (58-94 years old) with 899 observations and 50 children (6-10 years old) with 925 observations. A 10-min resting electrocardiogram was performed to assess resting HRV outcomes [Standard Deviation of Normal to Normal Intervals (SDNN), Root Mean Square of Successive Differences between Normal Heartbeats (RMSSD), Low Frequency power (LF), High Frequency power (HF), ration between low and high frequency (LF/HF)]. UFP and PM exposures were measured near the care home and school yard for seniors and children, respectively. Mean exposures during the day of examination (9-21 h) as well as 3-h, 12-h, 24-h, one-day, and two-day lags were assessed. Linear mixed-effect models were used to investigate the associations between short-term air pollution and HRV outcomes separately in children and seniors. The models were adjusted for sex, age, weather conditions (temperature, precipitation, and water vapor pressure), BMI, lifestyle and medical information. Two and multipollutant models adjusted for NO2 and O3 were performed.

Results

Among seniors, we observed increases in SDNN, LF, HF and LF/HF ratio after short-term exposure to UFP (hourly and daily lags) in contrast to decreases in SDNN and RMSSD after exposure to PM10. Associations were generally robust to two- and multipollutant adjustment. Among children, we observed increases of the LF/HF ratio after short-term exposures to UFP at lags 12 and 24 h. In contrast, we observed decreases of the ratio after exposure to PM2.5 and PM10. Results were largely unchanged for multipollutant modelling, however we found a more pronounced increase in SDNN and LF/HF (UFP lag 12 and 24 h) after adjusting for NO2.

Conclusions

Overall, among seniors, we observed associations of UFP and PM10 exposure with sympathetic responses of the ANS, which play an important role in sudden heart attacks or arrhythmia. Among children we found more inconsistent associations between UFP and a delayed increase in HRV. Adjusting for co-pollutants including NO2 and O3 yielded robust results.

Global Air Pollutant Phenanthrene and Arrhythmic Outcomes in a Mouse Model

BACKGROUND

The three-ringed polycyclic aromatic hydrocarbon (PAH) phenanthrene (Phe) has been implicated in the cardiotoxicity of petroleum-based pollution in aquatic systems, where it disrupts the contractile and electrical function of the fish heart. Phe is also found adsorbed to particulate matter and in the gas phase of air pollution, but to date, no studies have investigated the impact of Phe on mammalian cardiac function.

OBJECTIVES

Our objectives were to determine the arrhythmogenic potential of acute Phe exposure on mammalian cardiac function and define the underlying mechanisms to provide insight into the toxicity risk to humans.

METHODS

Ex vivo Langendorff-perfused mouse hearts were used to test the arrhythmogenic potential of Phe on myocardial function, and voltage- and current-clamp recordings were used to define underlying cellular mechanisms in isolated cardiomyocytes.

RESULTS

Mouse hearts exposed to ∼ 8 μ M Phe for 15-min exhibited a significantly slower heart rate (p = 0.0006 , N = 10 hearts), a prolonged PR interval (p = 0.036 , N = 8 hearts), and a slower conduction velocity (p = 0.0143 , N = 7 hearts). Whole-cell recordings from isolated cardiomyocytes revealed action potential (AP) duration prolongation (at 80% repolarization; p = 0.0408 , n = 9 cells) and inhibition of key murine repolarizing currents-transient outward potassium current (I to ) and ultrarapid potassium current (I Kur )-following Phe exposure. A significant reduction in AP upstroke velocity (p = 0.0445 , n = 9 cells) and inhibition of the fast sodium current (I Na ; p = 0.001 , n = 8 cells) and calcium current (I Ca ; p = 0.0001 ) were also observed, explaining the slowed conduction velocity in intact hearts. Finally, acute exposure to ∼ 8 μ M Phe significantly increased susceptibility to arrhythmias (p = 0.0455 , N = 9 hearts).

DISCUSSION

To the best of our knowledge, this is the first evidence of direct inhibitory effects of Phe on mammalian cardiac electrical activity at both the whole-heart and cell levels. This electrical dysfunction manifested as an increase in arrhythmia susceptibility due to impairment of both conduction and repolarization. Similar effects in humans could have serious health consequences, warranting greater regulatory attention and toxicological investigation into this ubiquitous PAH pollutant generated from fossil-fuel combustion. https://doi.org/10.1289/EHP12775.

Does environmental regulation caused by air pollution reduce shadow banking for non-financial companies? Based on the exit perspective of implicit government guarantee

As China's economy enters the stage of high-quality development, the sustainability of development becomes increasingly important. Therefore, this study takes air quality index as the explanatory variable, the level of shadow banking as the explained variable, and environmental regulation as the intermediary variable to empirically study whether environmental regulation caused by air pollution will affect the shadow banking of non-financial enterprises. The findings suggest that air pollution is likely to strengthen environmental regulation, thereby reducing the level of shadow banking, as air pollution strengthens environmental regulation, leading to the reduction of implicit government guarantees, while enterprises tend to abandon or minimize reliance on these guarantees and reduce leverage. The mechanism test shows that the ESG performance of non-financial firms weakens the process by which air pollution reduces the degree of shadow banking of non-financial firms, while the short-sightedness of management enhances this process. Heterogeneity analysis shows that this process is more significant under the effect of market-driven environmental regulation and in private enterprises and enterprises in regions with large industrial scale. Therefore, the policy implication is that government should continue to strengthen environmental law enforcement in future supervision, as this can not only reduce pollution levels but also reduce systemic financial risks. Enterprises should also increase their sense of social responsibility.

The association between polluted fuel use and self-reported insomnia symptoms among middle-aged and elderly Indian adults: a cross-sectional study based on LASI, wave 1

BACKGROUND

Insomnia predisposes the aging population to reduced quality of life and poor mental and physical health. Evidence of the association between polluted fuel use and insomnia symptoms is limited and is non-existent for the Indian population. Our study aimed to explore the link between polluted fuel use and insomnia symptoms in middle-aged and older (≥ 45 years) Indian populations.

METHODS

We utilized data from nationally representative Longitudinal Aging Study in India (LASI) Wave 1. Participants with complete information on fuel use, insomnia symptoms, and covariates were included. Insomnia symptoms were indicated by the presence of at least one of three symptoms: difficulty in initiating sleep (DIS), difficulty in maintaining sleep (DMS), or early morning awakening (EMA), ≥ 5 times/week. Survey-weighted multivariable logistic regression analyses were conducted to evaluate the association between polluted fuel use and insomnia symptoms. We also assessed the interaction of association in subgroups of age, gender, BMI, drinking, and smoking status.

RESULTS

Sixty thousand five hundred fifteen participants met the eligibility criteria. Twenty-eight thousand two hundred thirty-six (weighted percentage 48.04%) used polluted fuel and 5461 (weighted percentage 9.90%) reported insomnia symptoms. After full adjustment, polluted fuel use was associated with insomnia symptoms (OR 1.16; 95%CI 1.08-1.24) and was linked with DIS, DMS, and EMA (OR 1.14; 95%CI 1.05-1.24, OR 1.12; 95%CI 1.03-1.22, and OR 1.15; 95%CI 1.06-1.25, respectively). No significant interactions for polluted fuel use and insomnia symptoms were observed for analyses stratified by age, sex, BMI, drinking, or smoking.

CONCLUSIONS

Polluted fuel use was positively related to insomnia symptoms among middle-aged and older Indians. Suggestions are offered within this article for further studies to confirm our results, to explore underlying mechanisms, and to inform intervention strategies.

The impact of the synergistic effect of SO2 and PM2.5/PM10 on obstructive lung disease in subtropical Taiwan

Background

Chronic Obstructive lung diseases (COPD) are complex conditions influenced by various environmental, lifestyle, and genetic factors. Ambient air pollution has been identified as a potential risk factor, causing 4.2 million deaths worldwide in 2016, accounting for 25% of all COPD-related deaths and 26% of all respiratory infection-related deaths. This study aims to evaluate the associations among chronic lung diseases, air pollution, and meteorological factors.

Methods

This cross-sectional study obtained data from the Taiwan Biobank and Taiwan Air Quality Monitoring Database. We defined obstructive lung disease as patients with FEV1/FVC < 70%. Descriptive analysis between spirometry groups was performed using one-way ANOVA and the chi-square or Fisher's exact test. A generalized additive model (GAM) was used to evaluate the relationship between SO2 and PM2.5/PM10 through equations and splines fitting.

Results

A total of 2,635 participants were enrolled. Regarding environmental factors, higher temperature, higher relative humidity, and lower rainfall were risk factors for obstructive lung disease. SO2 was positively correlated with PM10 and PM2.5, with correlation coefficients of 0.53 (p < 0.0001) and 0.52 (p < 0.0001), respectively. Additionally, SO2 modified the relative risk of obstructive impairment for both PM10 [β coefficient (β) = 0.01, p = 0.0052] and PM2.5 (β = 0.01, p = 0.0155). Further analysis per standard deviation (per SD) increase revealed that SO2 also modified the relationship for both PM10 (β = 0.11, p = 0.0052) and PM2.5 (β = 0.09, p = 0.0155). Our GAM analysis showed a quadratic pattern for SO2 (per SD) and PM10 (per SD) in model 1, and a quadratic pattern for SO2 (per SD) in model 2. Moreover, our findings confirmed synergistic effects among temperature, SO2 and PM2.5/PM10, as demonstrated by the significant associations of bivariate (SO2 vs. PM10, SO2 vs. PM2.5) thin-plate smoothing splines in models 1 and 2 with obstructive impairment (p < 0.0001).

Conclusion

Our study showed high temperature, humidity, and low rainfall increased the risk of obstructive lung disease. Synergistic effects were observed among temperature, SO2, and PM2.5/PM10. The impact of air pollutants on obstructive lung disease should consider these interactions.

Long-Term Exposure of Nitrogen Oxides Air Pollution (NO2) Impact for Coronary Artery Lesion Progression-Pilot Study

BACKGROUND

The potentially harmful effects of air pollution on the human health have been already presented in epidemiological studies, suggesting a strong association with increased morbidity and mortality. The aim of the study was to evaluate a possible relationship between coronary artery lesion progression related to habitation place (cities vs. villages) and air pollution.

METHODS

There were 148 (101 men and 47 women) patients with a median age of 70 (63-74) years enrolled into retrospective analysis based on the coronary angiography results and their habitation place. Patients with stable coronary syndrome, who underwent repeated percutaneous coronary interventions were enrolled into the analysis based on demographical and clinical characteristics combined with annual exposure to air pollution (PM2.5, PM10, and NO2).

RESULTS

The results of multivariable regression analysis showed a significant relationship between coronary artery lesion progression requiring percutaneous intervention and NO2 chronic exposure in patients living in cities of Poland (OR 2.00, 95% CI: 0.41-9.62, p < 0.001). The predictive value of air pollution exposure at habitation place for coronary artery lesion progression requiring percutaneous intervention was evaluated by receiver-operator curve analysis, which revealed an area under the curve of 0.939, yielding a sensitivity of 87.1% and specificity of 90.7%.

CONCLUSIONS

Coronary artery lesion progression can be related to chronic exposure to NO2 air pollution in patients living in cities in Poland.

Hypertension and Stroke as Mediators of Air Pollution Exposure and Incident Dementia

Importance

Fine particulate matter air pollution (PM2.5) has been consistently associated with cardiovascular disease, which, in turn, is associated with an increased risk of dementia. As such, vascular dysfunction might be a mechanism by which PM2.5 mediates dementia risk, yet few prior epidemiological studies have examined this potential mechanism.

Objective

To investigate whether hypertension and stroke serve as mediators and modifiers of the association of PM2.5 with incident dementia.

Design, Setting, and Participants

As part of the Environmental Predictors of Cognitive Health and Aging (EPOCH) Project, this cohort study used biennial survey data collected between 1998 and 2016 from respondents of the Health and Retirement Study (HRS), a nationally representative, population-based, cohort in the US. Eligible participants were those over 50 years of age who were free of dementia at baseline and had complete exposure, mediator, outcome, and demographic data from the HRS. Data analysis was conducted from August to November 2022.

Exposures

Exposure to PM2.5, calculated for the 10 years preceding each person's baseline examination according to residential histories and spatiotemporal models.

Main Outcomes and Measures

Incident dementia was identified using a validated algorithm based on cognitive testing and informant reports. The 4-way decomposition causal mediation analysis method was used to quantify the degree to which hypertension and stroke mediated or modified the association of PM2.5 with incident dementia after adjustment for individual-level and area-level covariates.

Results

Among 27 857 participants (mean [SD] age at baseline, 61 [10] years; 15 747 female participants [56.5%]; 19 249 non-Hispanic White participants [69.1%]), 4105 (14.7%) developed dementia during the follow-up period (mean [SD], 10.2 [5.6] years). Among participants with dementia, 2204 (53.7%) had a history of hypertension at baseline and 386 (9.4%) received a diagnosis of hypertension during the follow up. A total of 378 participants (9.2%) had a history of stroke at baseline and 673 (16.4%) developed stroke over the follow-up period. The IQR of baseline PM2.5 concentrations was 10.9 to 14.9 μg/m3. In fully adjusted models, higher levels of PM2.5 (per IQR) were not associated with increased risk of incident dementia (HR, 1.04; 95% CI, 0.98 to 1.11). Although there were positive associations of prevalent stroke (HR, 1.67; 95% CI, 1.48 to 1.88) and hypertension (HR, 1.15; 95% CI, 1.08 to 1.23) with incident dementia compared with those free of stroke and hypertension during follow-up, there was no statistically significant association of PM2.5 with stroke (odds ratio per IQR increment in PM2.5, 1.08; 95%CI, 0.91 to 1.29) and no evidence of an association of PM2.5 with hypertension (odds ratio per IQR increment in PM2.5, 0.99; 95%CI, 0.92 to 1.07). Concordantly, there was no evidence that hypertension or stroke acted as mediators or modifiers of the association of PM2.5 with incident dementia. Although the nonmediated interaction between PM2.5 and hypertension accounted for 39.2% of the total excess association (95% CI, -138.5% to 216.9%), the findings were not statistically significant.

Conclusions and Relevance

These findings suggest that although hypertension may enhance the susceptibility of individuals to air pollution, hypertension and stroke do not significantly mediate or modify the association of PM2.5 with dementia, indicating the need to investigate other pathways and potential mediators of risk.

The effect of living environmental factors on cardiovascular diseases in Chinese adults: results from a cross-sectional and longitudinal study

AIMS

This study aimed to investigate the association between multiple living environmental factors and cardiovascular diseases (CVDs).

METHODS AND RESULTS

This study was conducted on the China Health and Retirement Longitudinal Study (CHARLS), with 12 489 subjects in the cross-sectional study and 7932 subjects in the 7-year follow-up. Living environmental factors included ambient fine particulate matter (PM2.5), indoor fuel use, tap water use, and residence type. Logistic regression and Cox proportional hazard regression models were applied to explore the association between living environmental risk factors and CVD events in a cross-sectional and a cohort analysis, respectively. Compared with subjects in the low-risk groups, those in the middle-risk (odd ratio [OR], 95% confidence interval [CI]: 1.203, 0.943-1.534) and high-risk groups (OR, 95% CI: 1.616, 1.259-2.074) showed increased risks of CVD prevalence when considering the combined effects of their living environment. During the follow-up, similar associations were observed (hazard ratio [HR], 1.541, 95% CI [1.142-2.080] for the high-risk group; HR 1.296, 95% CI [0.968-1.736] for the middle-risk group); P for trend = 0.003).

CONCLUSION

An overall poor living environmental quality is a potential risk factor for CVD. Future studies should focus more on the effects of exposure to multiple factors.

Particulate Matter Pollution Remains a Threat for Cardiovascular Health: Findings From the Global Burden of Disease 2019

Background Particulate matter (PM) pollution is a significant risk factor for cardiovascular diseases, causing substantial disease burden and deaths worldwide. This study aimed to investigate the global burden of cardiovascular diseases attributed to PM from 1990 to 2019. Methods and Results We used the GBD (Global Burden of Disease) study 2019 to investigate disability-adjusted life-years (DALYs), years of life lost (YLLs), years lived with disability (YLDs), and deaths attributed to PM as well as its subgroups. It was shown that all burden measures' age-standardized rates for PM were in the same decreasing trend, with the highest decline recorded for deaths (-36.7%). However, the all-age DALYs increased by 31%, reaching 8.9 million in 2019, to which YLLs contributed the most (8.2 million [95% uncertainty interval, 7.3 million-9.2 million]). Men had higher deaths, DALYs, and YLLs despite lower years lived with disability in 2019 compared with women. There was an 8.1% increase in the age-standardized rate of DALYs for ambient PM; however, household air pollution from solid fuels decreased by 65.4% in the assessed period. Although higher in men, the low and high sociodemographic index regions had the highest and lowest attributed YLLs/YLDs ratio for PM pollution in 2019, respectively. Conclusions Although the total age-standardized rate of DALYs for PM-attributed cardiovascular diseases diminished from 1990 to 2019, the global burden of PM on cardiovascular diseases has increased. The differences between men and women and between regions have clinical and policy implications in global health planning toward more exact funding and resource allocation, in addition to addressing inequity in health care access.

Does air pollution exposure affect semen quality? Evidence from a systematic review and meta-analysis of 93,996 Chinese men

Background

Air pollution may impair male fertility, but it remains controversial whether air pollution affects semen quality until now.

Objectives

We undertake a meta-analysis to explore potential impacts of six pollutants exposure during the entire window (0-90 days prior to ejaculation) and critical windows (0-9, 10-14, and 70-90 days prior to ejaculation) on semen quality.

Methods

Seven databases were retrieved for original studies on the effects of six pollutants exposure for 90 days prior to ejaculation on semen quality. The search process does not limit the language and search date. We only included original studies that reported regression coefficients (β) with 95% confidence intervals (CIs). The β and 95% CIs were pooled using the DerSimonian-Laird random effect models.

Results

PM2.5 exposure was related with decreased total sperm number (10-14 lag days) and total motility (10-14, 70-90, and 0-90 lag days). PM10 exposure was related with reduced total sperm number (70-90 and 0-90 lag days) and total motility (0-90 lag days). NO2 exposure was related with reduced total sperm number (70-90 and 0-90 lag days). SO2 exposure was related with declined total motility (0-9, 10-14, 0-90 lag days) and total sperm number (0-90 lag days).

Conclusion

Air pollution affects semen quality making it necessary to limit exposure to air pollution for Chinese men. When implementing protective measures, it is necessary to consider the key period of sperm development.

Association of hypothyroidism during pregnancy with preconception and early pregnancy exposure to ambient particulate matter

BACKGROUND

Limited research has been conducted on the association between preconception exposure to ambient particulate matter (PM) and hypothyroidism. This study aimed to investigate the relationship between preconception PM exposure and hypothyroidism.

METHODS

A retrospective case-control study at China-Japan Friendship Hospital was performed. Fine particulate matter (PM2.5) and inhalable particulate matter (PM10) were obtained from the China High Air Pollution Dataset. Buffer analysis methods were used to calculate the exposure of pregnant women to PM in a circular area of 250, 500, and 750 m in diameter at preconception and in early pregnancy. Logistic regression models were used to assess the relationship between PM and hypothyroidism. Odd ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the effect of PM on the risk of hypothyroidism.

RESULTS

A total of 3,180 participants were studied, and they comprised 795 hypothyroid patients and 2,385 matched controls. The mean age was 31.01 years (standard deviation: 3.66) in the control group and 31.16 years (standard deviation: 3.71) in the case group. Logistic regression analysis showed that exposure to PM2.5 and PM10 in the 60-day period before the last menstrual period month (LMPM), 30-day period before the LMPM, and LMP, across all distance buffers, was associated with an increased risk of hypothyroidism (all P < 0.05). The most pronounced effect was observed during the LMPM, with PM2.5 (OR: 1.137, 95% CI: 1.096-1.180) and PM10 (OR: 1.098, 95% CI: 1.067-1.130) in the 250-m buffer. Subgroup analysis in the Changping District yielded consistent results with the main analysis.

CONCLUSION

Our study shows that preconception PM2.5 and PM10 exposure increases the risk of hypothyroidism during pregnancy.

Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey

INTRODUCTION

Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.

METHODS

This was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.

RESULTS

A total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.

CONCLUSION

Long-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions.

Temporal evolution of PM2.5, PM10, and total suspended particles (TSP) in the Ciuc basin (Transylvania) with specific microclimate condition from 2010 to 2019

Modern societies are characterized by increased air pollution, and particulate matter (PM) is one of the most significant air pollutants and is a major environmental health problem. Therefore, long- and short-term exposure via inhalation, ingestion, and dermal absorption of particulate matter may cause series health issues, such as cardio pulmonary and lung cancer disease. Air pollutants accumulation is significantly higher in closed regions or basins characterized by strong thermal inversions, especially during the cold period such in case of the Ciuc basin. The aim of this study was to carry out the time series analysis of PM_2.5, PM₁₀ and TSP in the Ciuc basin for the period 2010-2019, in order to decipher the main characteristics of air pollution in this region.The data obtained were analyzed on a daily, monthly and annual basis by different statistical methods. The average monthly concentration of TSP (60.03 µg m^-3), PM₁₀ (19.21 µg m^-3) and PM_2.5 (14.73 µg m^-3) particulate matter in the studied regions varied between 29.84-134.79 µg m^-3, 4.38-63.51 µg m^-3 and 4.01-54.41 µg m^-3, respectively. Regarding the ratio of PM_2.5 and PM₁₀ in the total particulate matter (TPM) was 0.25 and 0.33. Due to meteorological factors and emission fluctuations, particulate matter exhibits high seasonal variations, therefore the highest concentrations were recorded during the cold period, while the lowest values were observed in summer. The percentage of PM₁₀ exceedances (50 µg m^-3) represents 24.8% in winter, meanwhile in autumn and spring a significantly lower exceedances percentage was observed, 2.6% and 1.7%, respectively. The correlation analysis revealed that the correlation level of the studied pollutants varied between 0.73-0.78.