Health Effects of Long-Term Exposure to Ambient PM2.5 in Asia-Pacific: a Systematic Review of Cohort Studies

Impact of Air Pollution and Allergic Status on Health-Related Quality of Life among University Students in Northern Thailand

BACKGROUND

Global awareness of ambient air pollution has heightened due to its detrimental impact on health, particularly in regions with elevated PM2.5 levels. Chiang Mai has emerged as an area experiencing the highest PM2.5 levels in Thailand.

OBJECTIVES

to examine the prevalence of respiratory allergies and assess the impact of air pollution on the health-related quality of life (QoL) among university students in Chiang Mai.

METHODS

Chiang Mai University (CMU) and Maejo University (MJU) students were recruited. The Global Asthma Network (GAN) questionnaire screened for respiratory allergies (RAs). The disease-specific QoL questionnaire (Rcq-36) was administered twice during low-PM2.5 and high-PM2.5 seasons to evaluate air pollution's impact on health-related QoL. Those showing potential RAs underwent a skin prick test (SPT) to investigate allergic sensitization.

RESULTS

Out of 406 participants, 131 (32%) reported respiratory allergies. Among those undergoing SPT, a high rate (82.54%) had positive results. Across both universities, students reported significantly lower QoL in multiple domains, particularly respiratory, eye, sleep, and emotional well-being, during the high-PM2.5 season. This aligned with their poorer self-reported health on a visual analog scale (VAS; p-value < 0.01). PM2.5 levels significantly impacted social functioning for CMU students (p-value = 0.001) and role limitations for MJU students (p-value < 0.001). Notably, participants without respiratory allergies (non-RAs) were more significantly affected by PM2.5 than RA participants in almost all parameters, despite experiencing fewer baseline symptoms.

CONCLUSIONS

Respiratory allergies, particularly allergic rhinitis, are prevalent among university students in Chiang Mai. This study underscores the substantial negative impact of ambient air pollution on QoL for both allergic and non-allergic students.

Spatiotemporally continuous PM2.5 dataset in the Mekong River Basin from 2015 to 2022 using a stacking model

With the potential to cause millions of deaths, PM2.5 pollution has become a global concern. In Southeast Asia, the Mekong River Basin (MRB) is experiencing heavy PM2.5 pollution and the existing PM2.5 studies in the MRB are limited in terms of accuracy and spatiotemporal coverage. To achieve high-accuracy and long-term PM2.5 monitoring of the MRB, fused aerosol optical depth (AOD) data and multi-source auxiliary data are fed into a stacking model to estimate PM2.5 concentrations. The proposed stacking model takes advantage of convolutional neural network (CNN) and Light Gradient Boosting Machine (LightGBM) models and can well represent the spatiotemporal heterogeneity of the PM2.5-AOD relationship. In the cross-validation (CV), comparison with CNN and LightGBM models shows that the stacking model can better suppress overfitting, with a higher coefficient of determination (R2) of 0.92, a lower root mean square error (RMSE) of 5.58 μg/m3, and a lower mean absolute error (MAE) of 3.44 μg/m3. For the first time, the high-accuracy PM2.5 dataset reveals spatially and temporally continuous PM2.5 pollution and variations in the MRB from 2015 to 2022. Moreover, the spatiotemporal variations of annual and monthly PM2.5 pollution are also investigated at the regional and national scales. The dataset will contribute to the analysis of the causes of PM2.5 pollution and the development of mitigation policies in the MRB.

Particulate Matter Induces Oxidative Stress and Ferroptosis in Human Lung Epithelial Cells

Numerous toxicological studies have highlighted the association between urban particulate matter (PM) and increased respiratory infections and lung diseases. The adverse impact on the lungs is directly linked to the complex composition of particulate matter, initiating reactive oxygen species (ROS) production and consequent lipid peroxidation. Excessive ROS, particularly within mitochondria, can destroy subcellular organelles through various pathways. In this study, we confirmed the induction of ferroptosis, an iron-dependent cell death, upon exposure to an urban PM using RT-qPCR and signaling pathway analysis. We used KRISS CRM 109-02-004, the certified reference material for the analysis of particulate matter, produced by the Korea Research Institute of Standards and Science (KRISS). To validate that ferroptosis causes lung endothelial toxicity, we assessed intracellular mitochondrial potential, ROS overproduction, lipid peroxidation, and specific ferroptosis biomarkers. Following exposure to the urban PM, a significant increase in ROS generation and a decrease in mitochondrial potential were observed. Furthermore, it induced hallmarks of ferroptosis, including the accumulation of lipid peroxidation, the loss of antioxidant defenses, and cellular iron accumulation. In addition, the occurrence of oxidative stress as a key feature of ferroptosis was confirmed by increased expression levels of specific oxidative stress markers such as NQO1, CYP1B1, FTH1, SOD2, and NRF. Finally, a significant increase in key ferroptosis markers was observed, including xCT/SLC7A11, NQO1, TRIM16, HMOX-1, FTL, FTH1, CYP1B1, CHAC1, and GPX4. This provides evidence that elevated ROS levels induce oxidative stress, which ultimately triggers ferroptosis. In conclusion, our results show that the urban PM, KRISS CRM, induces cellular and mitochondrial ROS production, leading to oxidative stress and subsequent ferroptosis. These results suggest that it may induce ferroptosis through ROS generation and may offer potential strategies for the treatment of lung diseases.

Health impact of the Tajogaite volcano eruption in La Palma population (ISVOLCAN study): rationale, design, and preliminary results from the first 1002 participants

BACKGROUND

The eruption of the Tajogaite volcano began on the island of La Palma on September 19, 2021, lasting for 85 days. This study aims to present the design and methodology of the ISVOLCAN (Health Impact on the Population of La Palma due to the Volcanic Eruption) cohort, as well as the preliminary findings from the first 1002 enrolled participants.

METHODS

A prospective cohort study was conducted with random selection of adult participants from the general population, with an estimated sample size of 2600 individuals. The results of the first 857 participants are presented, along with a group of 145 voluntary participants who served as interveners during the eruption. Data on epidemiology and volcano exposure were collected, and participants underwent physical examinations, including anthropometry, blood pressure measurement, spirometry, and venous blood extraction for toxicological assessment.

RESULTS

In the general population (n = 857), descriptive analysis revealed that the participants were mostly middle-aged individuals (50.8 ± 16.4), with a predominance of females. Before the eruption, the participants resided at a median distance of 6.7 km from the volcano in the Western region and 10.9 km in the Eastern region. Approximately 15.4% of the sample required evacuation, whose 34.8% returning to their homes on average after 3 months. A significant number of participants reported engaging in daily tasks involving cleaning of volcanic ash both indoors and outdoors. The most reported acute symptoms included ocular irritation, insomnia, mood disorders (anxiety-depression), and respiratory symptoms. Multivariate analysis results show that participants in the western region had a higher likelihood of lower respiratory tract symptoms (OR 1.99; 95% CI:1.33-2.99), depression and anxiety (OR 1.95; 95% CI:1.30-2.93), and insomnia (OR 2.03; 95% CI:1.33-3.09), compared to those in the eastern region.

CONCLUSION

The ongoing follow-up of the ISVOLCAN cohort will provide valuable insights into the short, medium, and long-term health impact related to the material emitted during the Tajogaite eruption, based on the level of exposure suffered by the affected population.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 μg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

Mortality burden attributable to exceptional PM2.5 air pollution events in Australian cities: A health impact assessment

Background

People living in Australian cities face increased mortality risks from exposure to extreme air pollution events due to bushfires and dust storms. However, the burden of mortality attributable to exceptional PM2.5 levels has not been well characterised. We assessed the burden of mortality due to PM2.5 pollution events in Australian capital cities between 2001 and 2020.

Methods

For this health impact assessment, we obtained data on daily counts of deaths for all non-accidental causes and ages from the Australian National Vital Statistics Register. Daily concentrations of PM2.5 were estimated at a 5 km grid cell, using a Random Forest statistical model of data from air pollution monitoring sites combined with a range of satellite and land use-related data. We calculated the exceptional PM2.5 levels for each extreme pollution exposure day using the deviation from a seasonal and trend loess decomposition model. The burden of mortality was examined using a relative risk concentration-response function suggested in the literature.

Findings

Over the 20-year study period, we estimated 1454 (95 % CI 987, 1920) deaths in the major Australian cities attributable to exceptional PM2.5 exposure levels. The mortality burden due to PM2.5 exposure on extreme pollution days was considerable. Variations were observed across Australia. Despite relatively low daily PM2.5 levels compared to global averages, all Australian cities have extreme pollution exposure days, with PM2.5 concentrations exceeding the World Health Organisation Air Quality Guideline standard for 24-h exposure. Our analysis results indicate that nearly one-third of deaths from extreme air pollution exposure can be prevented with a 5 % reduction in PM2.5 levels on days with exceptional pollution.

Interpretation

Exposure to exceptional PM2.5 events was associated with an increased mortality burden in Australia's cities. Policies and coordinated action are needed to manage the health risks of extreme air pollution events due to bushfires and dust storms under climate change.

Seasonal variations in respiratory morbidity in primary care and its correlation with the quality of air in urban Odisha, India

Poor air quality, especially in urban regions among low-and middle-income countries such as India poses a significant healthcare challenge. Amongst urban areas, metropolitan cities garner the utmost importance for air quality related policies and studies with limited studies from tier II cities which are thought to be relatively immune to air pollution. Hence, we aimed to identify the most frequent respiratory morbidities and explore its correlation with exposure to ambient PM2.5 particles in Bhubaneswar (a tier II city in coastal India), Odisha. A chart review was carried out through data extracted from the records of urban health centres. Data on PM2.5 concentrations were obtained from Odisha State Pollution Control Board. The morbidities were coded by using the International Classification of Primary Care‑2 system (ICPC-2). Descriptive statistics such as incidence of respiratory illnesses was computed across seasons. The ecological correlation between respiratory morbidity patterns and corresponding concentration of PM2.5 in air was analysed for each season. A positive correlation (r = o.94) between PM2.5 and respiratory morbidities was observed. The incidence of respiratory morbidities was 183.31 per 1000 person year. We identified 21 out of 43 respiratory diseases classified under ICPC-2. Upper Respiratory Tract Infection was the most commonly (116.8 per 1000 person year) incident condition. We observed one-fourth increase in the incidence of respiratory illnesses during winters. Respiratory morbidities are common in urban Bhubaneswar which follows a seasonal pattern and are possibly linked with the seasonal variations in levels of PM2.5 particles. Our study highlights that tier II cities are equally prone to health effects of air pollution. Future programmes and policies should take these cities into consideration too.

Effects of Particulate Matter Inhalation during Exercise on Oxidative Stress and Mitochondrial Function in Mouse Skeletal Muscle

Particulate matter (PM) has deleterious consequences not only on the respiratory system but also on essential human organs, such as the heart, blood vessels, kidneys, and liver. However, the effects of PM inhalation on skeletal muscles have yet to be sufficiently elucidated. Female C57BL/6 or mt-Keima transgenic mice were randomly assigned to one of the following four groups: control (CON), PM exposure alone (PM), treadmill exercise (EX), or PM exposure and exercise (PME). Mice in the three-treatment group were subjected to treadmill running (20 m/min, 90 min/day for 1 week) and/or exposure to PM (100 μg/m3). The PM was found to exacerbate oxidative stress and inflammation, both at rest and during exercise, as assessed by the levels of proinflammatory cytokines, manganese-superoxide dismutase activity, and the glutathione/oxidized glutathione ratio. Furthermore, we detected significant increases in the levels of in vivo mitophagy, particularly in the PM group. Compared with the EX group, a significant reduction in the level of mitochondrial DNA was recorded in the PME group. Moreover, PM resulted in a reduction in cytochrome c oxidase activity and an increase in hydrogen peroxide generation. However, exposure to PM had no significant effect on mitochondrial respiration. Collectively, our findings in this study indicate that PM has adverse effects concerning both oxidative stress and inflammatory responses in skeletal muscle and mitochondria, both at rest and during exercise.

Health risk assessment of heavy metals in exposed workers of municipal waste recycling facility in Iran

Exposure to heavy metals (HMs) present in the particulate matter from municipal solid waste during pretreatment and recycling processes may pose a serious health risk to workers. This was the first study on the exposure of municipal solid waste (MSW) recycling workers to toxic metals. The concentrations of HMs (Cd, Pb, As, Co, Cr, Ni, Cu, Fe, Mn, and Zn) during personal exposure to PM2.5 among municipal waste recycling facility workers in Kashan City, Iran, were investigated from January 15 to March 15, 2023. The research was performed in the three main stages of the waste recycling process: dismantling, sorting, and collecting. PM2.5 samples were collected using a personal environmental monitor (PEM) attached to a sampling pump. The non-carcinogenic and carcinogenic health risk values and related uncertainty for waste recyclers from HMs inhalational exposure were calculated using USEPA methodology and Monte Carlo simulations. The results showed that the dismantlers exhibited the highest exposure concentrations of PM2.5 (mean 2148 ± 1257 μg m-3), followed by sorters (mean 1864 ± 965 μg m-3), and collectors (mean 1782 ± 876 μg m-3). Health risk assessment indicated that 95th percentile contents of Ni, As, Co, and Zn were responsible for the non-carcinogenic risk (HQ) values exceeding the acceptable level of 1. The contents of As, Ni, and Cr in PM2.5 caused a non-acceptable carcinogenic risk for waste recyclers due to inhalational exposure, as the carcinogenic risk (CR) values exceeded the acceptable threshold of 1 × 10-6. Monte Carlo simulation results revealed that the mean and median CR values from inhalational exposure to carcinogenic HMs exceeded the acceptable level of 1 × 10-6 for municipal waste recyclers. As results of this study indicated the high-risk to hazardous metals for waste recyclers due to occupational exposure in the MSW recycling sites, it is suggested to consider workers' exposure as the public health concern.

Detection of forest fires and pollutant plume dispersion using IoT air quality sensors

The widespread adoption of Internet of Things (IoT) sensors has revolutionized our understanding of the formation and mitigation of air pollution, significantly improving the accuracy of predictions related to air quality and emission sources. This study demonstrates the use of IoT air quality sensors to detect forest fire incidents by focusing on an area affected by forest fires in Tak Province, Thailand, from January to May 2021. We employed PM2.5 and carbon monoxide measurements from IoT sensors for forest fire detection and utilized the number of hotspots reported through satellite and human observations to identify forest fire incidents. Our data analysis revealed three distinct periods with forest fires and three periods without fires (non-forest fires). For model training, two forest fire and non-forest fire periods were selected and the remaining periods were set aside for validation. J48, a computer algorithm that helps make decisions by organizing information into a tree-like structure based on key characteristics, was used to construct the decision-tree model. Our model achieved an accuracy rate of 72% when classifying forest fire incidents using the training data and a solid accuracy of 69% on the validation data. In addition, we investigated the dispersion of PM2.5 plumes using a regression model. Notably, our findings highlighted the robust explanatory power of the lag time in PM2.5, for predicting PM2.5, in the next 15 min. Our analysis highlights the potential of IoT-based air quality sensors to enhance forest fire detection and predict pollution plume dispersion once fires are detected.

The Long-Term Mortality Effects Associated with Exposure to Particles and NOx in the Malmö Diet and Cancer Cohort

In this study, the long-term mortality effects associated with exposure to PM10 (particles with an aerodynamic diameter smaller than or equal to 10 µm), PM2.5 (particles with an aerodynamic diameter smaller than or equal to 2.5 µm), BC (black carbon), and NOx (nitrogen oxides) were analyzed in a cohort in southern Sweden during the period from 1991 to 2016. Participants (those residing in Malmö, Sweden, born between 1923 and 1950) were randomly recruited from 1991 to 1996. At enrollment, 30,438 participants underwent a health screening, which consisted of questionnaires about lifestyle and diet, a clinical examination, and blood sampling. Mortality data were retrieved from the Swedish National Cause of Death Register. The modeled concentrations of PM10, PM2.5, BC, and NOx at the cohort participants' home addresses were used to assess air pollution exposure. Cox proportional hazard models were used to estimate the associations between long-term exposure to PM10, PM2.5, BC, and NOx and the time until death among the participants during the period from 1991 to 2016. The hazard ratios (HRs) associated with an interquartile range (IQR) increase in each air pollutant were calculated based on the exposure lag windows of the same year (lag0), 1-5 years (lag1-5), and 6-10 years (lag6-10). Three models were used with varying adjustments for possible confounders including both single-pollutant estimates and two-pollutant estimates. With adjustments for all covariates, the HRs for PM10, PM2.5, BC, and NOx in the single-pollutant models at lag1-5 were 1.06 (95% CI: 1.02-1.11), 1.01 (95% CI: 0.95-1.08), 1.07 (95% CI: 1.04-1.11), and 1.11 (95% CI: 1.07-1.16) per IQR increase, respectively. The HRs, in most cases, decreased with the inclusion of a larger number of covariates in the models. The most robust associations were shown for NOx, with statistically significant positive HRs in all the models. An overall conclusion is that road traffic-related pollutants had a significant association with mortality in the cohort.

Modeling spatial-temporal variability of PM2.5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach

The rapid development of the Belt and Road Initiative (BRI) has led to severe air pollution dominated by PM2.5 concentrations which can cause a profound negative impact on human health and economic activity. This problem poses a critical environmental challenge to efficiently handling large-scale spatial-temporal PM2.5 data in this extended region. Functional data analysis (FDA) technique offers powerful tools that have the potential to enhance the analysis of spatial distributions and temporal dynamic changes in high-dimensional pollution data. However, modeling the spatial-temporal variability of PM2.5 concentrations by FDA remains unrevealed in the BRI region. To address this research gap, our study aimed to achieve two main objectives: first, to model the spatial-temporal dynamic variability of PM2.5 in 125 BRI nations (1998-2021), and second, to identify the underlying clusters behind the variations. We employed the recently developed functional adaptive density peak (FADP) clustering approach to solve the current problem. The proposed method is based on the joint use of functional principal components (FPCs) and functional cluster analyses. The main results are as follows: (i) The first three FPCs almost captured 99% of the total variations involving all valuable information on PM2.5 concentrations. (ii) PM2.5 pollution was highly concentrated in the developing countries (Pakistan, Bangladesh, and Nigeria) and the developed countries (Arabian Gulf countries: Qatar, United Arab Emirates, Bahrain, Saudi Arabia, Oman), and the least developed countries (Yemen and Chad). (iii) Three optimal clusters were identified and thus classified the PM2.5 into three distinct degrees of pollution: severe, moderate, and light. (iv) Cluster 1 had a severe pollution effect degree with a high rate of change, and it covered the Arabian Peninsula countries, African countries (Cameroon, Egypt, Gambia, Mali, Mauritania, Nigeria, Sudan, Senegal, Chad), Bangladesh, and Pakistan. (v) About 62 BRI countries belonged to cluster 2 showing a light pollution degree with annul average of less than 20 [Formula: see text]; this pointed out that the PM2.5 concentration remains stable in the cluster 2-related countries. The findings of this research would benefit governments and policymakers in preventing and controlling PM2.5 pollution exposure in BRI. Furthermore, this research could pay attention to sustainable development goals and the vision of the Green BRI policy.

Association between long-term exposure to low level air pollutants and incident end-stage kidney disease in the UK Biobank: A prospective cohort

BACKGROUND

Previous studies suggest that air pollution can increase the risk of incident chronic kidney disease (CKD). However, the association between end-stage kidney disease (ESKD) and co-exposure to relatively low-level air pollutants remains unclear.

METHODS

A prospective cohort was designed based on UK Biobank. From 1 January 2010 to 12 November 2021, 453,347 participants were followed up over a median of 11.87 years. Principal component analysis was used to identify major patterns of five air pollutants, including PM2.5, PM2.5-10, PM10, NO2, and NOx. Sub-distribution hazards models were used to estimate the associations between air pollution, individually or jointly, and incident ESKD, CKD, and all-cause death, respectively.

RESULTS

Principal component analysis identified two principal components, namely RC1 (PM2.5, NO2, and NOx) and RC2 (PM2.5-10 and PM10). An elevated risk of incident ESKD was associated with an interquartile range (IQR) increase in PM2.5 (hazard ratio: 1.11, 95% confidence interval: 1.02-1.22), NO2 (1.16, 1.04-1.30), NOx (1.08, 1.00-1.17), and RC1 (1.12, 1.02-1.23). An elevated risk of incident CKD was associated with an IQR increase in PM2.5 (1.05, 1.03-1.07), NO2 (1.04, 1.02-1.06), NOx (1.03, 1.02-1.05), and RC1 (1.04, 1.02-1.06). An increased risk of all-cause mortality was associated with an IQR increase in PM2.5 (1.02, 1.00-1.04). Restricted cubic spline analyses indicated a monotonic elevating association of PM2.5, NO2, NOx, and RC1 with ESKD incidence.

CONCLUSIONS

Long-term exposure to PM2.5, NO2, NOx, and their complex was associated with elevated ESKD incidence, even at relatively lower levels of air pollution.

Incident risk and burden of cardiovascular diseases attributable to long-term NO2 exposure in Chinese adults

BACKGROUND

A number of studies suggested a nexus between long-term exposure to nitrogen dioxide (NO2) and the incidence of cardiovascular disease (CVD), while population-based cohort evidence in low- and middle-income countries was extensively sparse.

METHODS

We carried out an 8-year longitudinal study (2010-2018) in a nationwide dynamic cohort of 36,948 Chinese adult participants, who were free of CVD at baseline. Annual average estimates of NO2 exposure were predicted using a well-validated spatiotemporal model and assigned to study participants based on their residential counties. Considering death as a competing risk event, Fine-Gray competing risk models with time-varying exposures at an annual scale were used to quantify incident risks of overall CVD, hypertension, and stroke associated with a 10-μg/m3 rise in NO2 exposure. Using the meta-analysis approach, we performed a pooled analysis of hazard ratio (HR) drawn from this and prior multinational cohort studies for the assessment of attributable burden. NO2-attributable overall CVD incidents in China were evaluated by city and province for years 2010 and 2018, referring to a counterfactual exposure level of 10 μg/m3 (2021 World Health Organization [WHO] air quality guidelines). A decomposition method was used to decompose net change in NO2-attributable CVD incidents during 2010 and 2018 into 3 primary contributions of driving factors (i.e., changes in NO2 exposure, population size, and incidence rate).

RESULTS

A total of 4428 overall CVD events (hypertension 2448, stroke 1044) occurred during a median follow-up period of 6.1 years. Annual mean NO2 concentration from 2010 to 2018 was 20.0 μg/m3 (range: 6.9-57.4 μg/m3). An increase of 10-µg/m3 in NO2 was associated with an HR of 1.558 (95% confidence interval [CI]: 1.477, 1.642) for overall CVD, 1.521 (95% CI: 1.419, 1.631) for hypertension, and 1.664 (95% CI: 1.485, 1.865) for stroke. Longitudinal associations of NO2 exposure with incident CVD were nearly linear over the exposure range, suggesting no discernible thresholds. Subgroup analyses indicated significantly higher NO2-associated risks of incident CVD among urban residents and overweight/obese individuals. According to pooled HR of NO2-CVD association (1.108, 95% CI: [1.007, 1.219]) from 10 multinational cohort studies, we estimated totally 1.44 million incident CVD cases attributable to NO2 exposure in 2018, representing a substantial decrease of 0.41 million compared to the estimate in 2010 (1.85 million) in mainland of China. Nationally, from 2010 to 2018, the attributable incident cases greatly dropped by 22.4%, which was dominantly driven by declined NO2 concentration (-47.1%) that had offset far from the rise of CVD incidence rate (+19.6%) and population growth (+5.1%).

CONCLUSIONS

This study provided nationwide cohort evidence for elevated risks of CVD incidence associated with long-term ambient NO2 exposure among Chinese adults, particularly in urban areas and among overweight/obese individuals. Our findings highlighted that reducing NO2 exposure below 2021 WHO guideline could help prevent a substantial portion of incident CVD cases in China.

Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China

Background

Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk.

Methods

We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants.

Findings

During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 μg/m3), PM2.5 (mean [baseline]: 70.2 μg/m3), SO2 (mean [baseline]: 113.0 μg/m3) and NO2 (mean [baseline]: 39.2 μg/m3) were adversely and consistently associated with all mortality outcomes. A 10 μg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10.

Interpretation

There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study.

Funding

National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.

Potential causal links between long-term ambient particulate matter exposure and cerebrovascular mortality: Insights from a large cohort in southern China

Cohort studies conducted in North America and Europe have linked cerebrovascular mortality to long-term exposure to particulate matter (PM). However, limited evidence from large cohorts in high-exposure areas and the traditional approach of association assessment may cause residual confounding issues. In this study, we aimed to investigate the causal links between cerebrovascular mortality and long-term exposure to PM_2.5, PM₁₀, and PM_2.5-10 in an ongoing cohort study with 580,757 participants in southern China. Using satellite-based estimates of PM concentration at a 1-km² spatial resolution, we assigned exposure levels to each participant and used the marginal structural Cox model to assess the association between PM exposure and cerebrovascular mortality while accounting for time-varying covariates. We also explored the potential modification effects of sociodemographic and behavioral factors on the PM-health associations. Adjusted hazard ratios (HR) for overall cerebrovascular mortality were 1.041 (95% confidence interval (CI): 1.034-1.049) and 1.032 (95% CI: 1.026-1.038) for each 1 μg/m³ increase in PM_2.5, and PM₁₀, respectively. Similar trends were observed in the mortality risk from stroke and ischemic stroke, with HRs ranging from 1.040 to 1.069 and 1.025 to 1.052, respectively, across 2 p.m. exposures. The impact of PM exposure was generally more apparent among women, participants with primary school diplomas and below, and the subgroup under low-exposure. Multiple sensitivity analyses confirmed the robustness of the results. In conclusion, this sizable prospective cohort study hypothesizes causal links between long-term PM exposure and cerebrovascular mortality, particularly among vulnerable participants, supporting the rationale for reducing PM concentration in China to reduce cerebrovascular mortality.

Substantial short- and long-term health effect due to PM2.5 and the constituents even under future emission reductions in China

Heavy pollution events of fine particulate matter (PM_2.5) frequently occur in China, seriously affecting the human health. However, how meteorological factors and anthropogenic emissions affect PM_2.5 and the major constituents, as well as the subsequent health effect, remains unclear. Here, based on regional climate and air quality models Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ), the PM_2.5 and major constituents in China at present and mid-century under the carbon neutral scenario Shared Socioeconomic Pathways (SSP)1-2.6 are simulated. Due to anthropogenic emission reduction, concentrations of PM_2.5 and the constituents decrease substantially in SSP1-2.6. The long-term exposure premature deaths at present are 2.23 million per year in mainland China, which is projected to increase by 76 % under SSP1-2.6 despite emission reduction, primarily attributable to aging which strikingly offsets the effect of air quality improvement. The number of annual premature deaths resulting from short-term exposure is 228,104 in mainland China at present, which is projected to decrease in the future. Using North China Plain as an example, we identify that among the major constituents of PM_2.5, organic carbon leads to the most short-term exposure deaths considering the largest exposure-response coefficient. Regarding the abnormally meteorological conditions, we find, relative to low relative humidity (RH) and non-stagnation, the compound events, defined as concurrence of high RH and atmospheric stagnation, exhibit an amplified role inducing larger premature deaths compared to the additive effect of the individual event of high RH and atmospheric stagnation. This nonlinear effect occurs at both present and future, but diminished in future due to emission reductions. Our study highlights the importance of considering both the long- and short-term premature deaths associated with PM_2.5 and the constituents, as well as the critical effect of extreme weather events.

Greenness modifies the association between ambient air pollution and cognitive function in Australian adolescents, but not in mid-life adults

Exposure to ambient air pollution has been associated with reduced cognitive function in childhood and later life, with too few mid-life studies to draw conclusions. In contrast, residential greenness has been associated with enhanced cognitive function throughout the lifecourse. Here we examine the extent to which (1) ambient air pollution and residential greenness predict later cognitive function in adolescence and mid-life, and (2) greenness modifies air pollution-cognitive function associations.

PARTICIPANTS

6220 adolescents (51% male) and 2623 mid-life adults (96% mothers) from the Longitudinal Study of Australian Children.

MEASURES

Exposures: Annual average particulate matter <2.5 μm (PM_2.5), nitrogen dioxide (NO₂) and greenness (Normalised Difference Vegetation Index) for residential addresses from validated land-use regression models over a 10-13-year period.

OUTCOMES

Cognitive function from CogState tests of attention, working memory and executive function, dichotomised into poorer (worst quartile) versus not poor.

ANALYSES

Adjusted mixed-effects generalised linear models with residential greenness assessed as an effect modifier (high vs. low divided at median). The annual mean for PM_2.5 and NO₂ across exposure windows was 6.3-6.8 μg/m³, and 5.5-7.1 ppb, respectively. For adolescents, an IQR increment of NO₂ was associated with 19-24% increased odds of having poorer executive function across all time windows, while associations weren't observed between air pollution and other outcomes. For adults, high NO₂ predicted poorer cognitive function across all outcomes, while high PM_2.5 predicted poorer attention only. There was little evidence of associations between greenness and cognitive function in adjusted models for both generations. Interactions were found between residential greenness, air pollutants and cognitive function in adolescents, but not adults. The magnitude of effects was similar across generations and exposure windows. Findings highlight the potential benefits of cognitive health associated with the regulation of air pollution and urban planning strategies for increasing green spaces and vegetation.

Effect of particulate matter (PM2.5 and PM10) on health indicators: climate change scenarios in a Brazilian metropolis

Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM₁₀ and PM_2.5 considering the new limits recommended by the WHO: 15 µg/m³ (PM₁₀) and 5 µg/m³ (PM_2.5) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM_2.5 and PM₁₀ were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM_2.5 and PM₁₀, with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.

Association between exposure to ambient PM2.5 and the health status in the mobile population from 338 cities in China

There are limited studies investigating the relationship between exposure to PM_2.5 and the health status among the mobile population. A cross-sectional analysis was performed in a nationally representative sample (2017 China Migrants Dynamic Survey data) consisting of 169,469 mobile population. The ordered logistic regression model was used to examine the association between PM_2.5 and the health status in mobile population. Stratified analyses were performed to identify whether the association varied across gender, age group, and regions in China. Overall, every 10 μg/m³ increment in annual average PM_2.5 was associated with increased risk of poor self-reported health (OR = 1.021, 95% CI: 1.012-1.030). Mobile population aged 31-49 years and living in the central region suffers the highest PM_2.5-associated health risk (OR = 1.030, 95% CI: 1.019-1.042; OR = 1.095, 95% CI: 1.075-1.116). Our study suggests that PM_2.5 exposure was associated with an increased risk of poor self-reported health in mobile population, particularly among the population aged 31-49 years and people living in the central region of China. Policymakers should pay more attention to the vulnerable mobile population to tackle the health burden of ambient air pollution.

Potential causal links between long-term ambient particulate matter exposure and cardiovascular mortality: New evidence from a large community-based cohort in South China

BACKGROUND

Cardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited.

AIMS

We examined the potential causal links between PM exposure and the CVD mortality in South China.

METHODS

580,757 participants were recruited during 2009-2015 and followed up through 2020. Satellite-based annual concentrations of PM_2.5, PM₁₀, and PM_coarse (i.e., PM₁₀ - PM_2.5) at 1 km² spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality.

RESULTS

For overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 μg/m³ increase in the annual average concentration of PM_2.5, PM₁₀, and PM_coarse were 1.033 (1.028-1.037), 1.028 (1.024-1.032), and 1.022 (1.012-1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM_2.5 and PM₁₀. Significant association between PM_coarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM₁₀ concentrations below 70 μg/m³ were more vulnerable to PM_2.5-, PM₁₀- and PM_coarse-CVD mortality risks.

CONCLUSION

This large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.

Health and economic benefits of meeting WHO air quality guidelines, Western Pacific Region

Objective

To quantify the number of avoidable annual deaths and associated economic benefits from meeting the World Health Organization (WHO) air quality guidelines for ambient concentrations for fine particulate matter (PM_2.5) for Member States of the WHO Western Pacific Region.

Methods

Using the AirQ+ software, we performed a quantitative health impact assessment comparing country-level PM_2.5 concentrations with the 2005 and 2021 air quality guidelines recommended maximum concentrations of 10 and 5 μg/m³, respectively. We obtained PM_2.5 data from the WHO Global Health Observatory (latest available year 2016), and population and mortality estimates from the United Nations World Population Prospects database for the latest 5-year period available (2015-2019), which we averaged to 1-year estimates. A risk estimate for all-cause mortality, based on a meta-analysis, was embedded within AirQ+ software. Our economic assessment used World Bank value of a statistical life adjusted to country-specific gross domestic product (latest available year 2014).

Findings

Data were complete for 21 of 27 Member States. If these countries achieved the 2021 guidelines for PM_2.5, an estimated 3.1 million deaths would be avoided annually, which are 0.4 million more deaths avoided than meeting the 2005 guidelines. China would avoid the most deaths per 100 000 population (303 deaths) and Brunei Darussalam the least (5 deaths). The annual economic benefit per capita ranged from 5781 United States dollars (US$) in Singapore to US$ 143 in Solomon Islands.

Conclusion

Implementing effective measures to reduce PM_2.5 emissions would save a substantial number of lives and money across the Region.

Dietary Intervention with Quercetin Attenuates Diesel Exhaust Particle-Instilled Pulmonary Inflammation and Behavioral Abnormalities in Mice

Exposure to diesel exhaust particles (DEPs) is inevitable and closely linked with increased health hazards, causing pulmonary abnormalities by increasing inflammation, hypoxia, and so on. Moreover, long-term exposure to DEPs may trigger whole-body toxicity with behavioral alterations. Therefore, nutritional intervention with natural components may be desirable to prevent and/or ameliorate DEP-inducible pathophysiology in mammals. Quercetin has been demonstrated to reduce metabolic complications by possessing antioxidative, anti-inflammatory, and antimutagenic effects. In this study, we investigated the effects of quercetin on pulmonary inflammation and behavioral alteration in male C57BL/6 mice against DEP instillation. The experimental mice were separated into four treatment groups (n = 8 per group), which include: vehicle control, DEP instillation, dietary intervention with a low dose of quercetin (20 mg/kg) for 14 days with DEP instillation for 7 days, or dietary intervention with a high dose of quercetin (100 mg/kg) for 14 days with DEP instillation for 7 days. Compared with the DEP-instilled group, dietary intervention with quercetin significantly attenuated eosinophils in the bronchoalveolar lavage fluid analysis, pulmonary cytokine, and hypoxic mRNA expressions regardless of quercetin concentrations. DEP instillation triggered hyperactivities in the experimental mice, while quercetin pretreatment successfully normalized DEP-inducible abnormalities regardless of the dosage. Therefore, dietary intervention with quercetin may be an applicable means to prevent DEP-triggered pulmonary and behavioral abnormalities.

Water-based air purifier with ventilation fan system: a novel approach for cleaning indoor/outdoor transitional air during the pandemic

Abstract

This article presents the design and fabrication of an air purifier that uses a water-based technique to clean indoor/outdoor transitional air to provide a low-tech air purifier against the annual smog crisis and the ongoing COVID-19 pandemic. The air purifier was designed and built. All tests were conducted in a closed room as well as a semi-outdoor area. Particle sizes of PM0.3, 0.5, 1.0, 3.0, 5.0, and 10 μm (particle/m³) were measured at an air inlet, air outlet, 2 m from an air inlet, and 4 m from an air outlet after 0, 5, 10, 15, and 20 min of air treatment, respectively, as well as CO₂ levels and relative humidity (RH). The average airflow rate was also measured. When compare to 0 min, all parameters, except semi-outdoor PM0.3 and CO₂ levels, tend to decrease in both indoor and semi-outdoor conditions. When measure by total airflow specification of a dual ventilation fan, the average airflow rate at an air outlet is reduced by 20 times.

Article Highlights

Design and fabrication of a water-based air purifier.

A low-tech air purifier helping to protect against the annual smog crisis and the ongoing COVID-19 pandemic.

The novel water-based air purifier effectively traps air particles ranging in size from 0.5 to 10 µm.

The cytotoxicity of PM2.5 and its effect on the secretome of normal human bronchial epithelial cells

Exposure to airborne fine particulate matter (PM_2.5) induced various adverse health effects, such as metabolic syndrome, systemic inflammation, and respiratory disease. Many works have studied the effects of PM_2.5 exposure on cells through intracellular proteomics analyses. However, changes of the extracellular proteome under PM_2.5 exposure and its correlation with PM_2.5-induced cytotoxicity still remain unclear. Herein, the cytotoxicity of PM_2.5 on normal human bronchial epithelia cells (BEAS-2B cells) was evaluated, and the secretome profile of BEAS-2B cells before and after PM_2.5 exposure was investigated. A total of 83 proteins (58 upregulated and 25 downregulated) were differentially expressed in extracellular space after PM_2.5 treatment. Notably, we found that PM_2.5 promoted the release of several pro-apoptotic factors and induced dysregulated secretion of extracellular matrix (ECM) constituents, showing that the abnormal extracellular environment attributed to PM_2.5-induced cell damage. This study provided a secretome data for the deep understanding of the molecular mechanism underlying PM_2.5-caused human bronchial epithelia cell damage.