Acute effects of ambient particulate matter on mortality in Europe and North America: results from the APHENA study

Exploring the Cellular Impact of Size-Segregated Cigarette Aerosols: Insights into Indoor Particulate Matter Toxicity and Potential Therapeutic Interventions

Exposure to anthropogenic aerosols has been associated with a variety of adverse health effects, increased morbidity, and premature death. Although cigarette smoke poses one of the most significant public health threats, the cellular toxicity of particulate matter contained in cigarette smoke has not been systematically interrogated in a size-segregated manner. In this study, we employed a refined particle size classification to collect cigarette aerosols, enabling a comprehensive assessment and comparison of the impacts exerted by cigarette aerosol extract (CAE) on SH-SY5Y, HEK293T, and A549 cells. Exposure to CAE reduced cell viability in a dose-dependent manner, with organic components having a greater impact and SH-SY5Y cells displaying lower tolerance compared to HEK293T and A549 cells. Moreover, CAE was found to cause increased oxidative stress, mitochondrial dysfunction, and increased levels of apoptosis, pyroptosis, and autophagy, leading to increased cell death. Furthermore, we found that rutin, a phytocompound with antioxidant potential, could reduce intracellular reactive oxygen species and protect against CAE-triggered cell death. These findings underscore the therapeutic potential of antioxidant drugs in mitigating the adverse effects of cigarette aerosol exposure for better public health outcomes.

Modification of heat-related effects on mortality by air pollution concentration, at small-area level, in the Attica prefecture, Greece

BACKGROUND

The independent effects of short-term exposure to increased air temperature and air pollution on mortality are well-documented. There is some evidence indicating that elevated concentrations of air pollutants may lead to increased heat-related mortality, but this evidence is not consistent. Most of these effects have been documented through time-series studies using city-wide data, rather than at a finer spatial level. In our study, we examined the possible modification of the heat effects on total and cause-specific mortality by air pollution at municipality level in the Attica region, Greece, during the warm period of the years 2000 to 2016.

METHODS

A municipality-specific over-dispersed Poisson regression model during the warm season (May-September) was used to investigate the heat effects on mortality and their modification by air pollution. We used the two-day average of the daily mean temperature and daily mean PM10, NO2 and 8 hour-max ozone (O3), derived from models, in each municipality as exposures. A bivariate tensor smoother was applied for temperature and each pollutant alternatively, by municipality. Α random-effects meta-analysis was used to obtain pooled estimates of the heat effects at different pollution levels. Heterogeneity of the between-levels differences of the heat effects was evaluated with a Q-test.

RESULTS

A rise in mean temperature from the 75th to the 99th percentile of the municipality-specific temperature distribution resulted in an increase in total mortality of 12.4% (95% Confidence Interval (CI):7.76-17.24) on low PM10 days, and 21.25% (95% CI: 17.83-24.76) on high PM10 days. The increase on mortality was 10.09% (95% CI: - 5.62- 28.41) on low ozone days, and 14.95% (95% CI: 10.79-19.27) on high ozone days. For cause-specific mortality an increasing trend of the heat effects with increasing PM10 and ozone levels was also observed. An inconsistent pattern was observed for the modification of the heat effects by NO2, with higher heat effects estimated in the lower level of the pollutant.

CONCLUSIONS

Our results support the evidence of elevated heat effects on mortality at higher levels of PM10 and 8 h max O3. Under climate change, any policy targeted at lowering air pollution levels will yield significant public health benefits.

Airborne Suspended Particulate Matter and the Prevalence of Allergic Conjunctivitis in Japan

Background This study aimed to examine the association of suspended particulate matter (SPM) with outpatient attendance for allergic conjunctivitis. Methodology The information on air pollution, encompassing total hydrocarbons, non-methane hydrocarbons, methane, carbon monoxide, nitrogen oxide, nitric oxide, oxidants, and SPM alongside data concerning daily weather conditions such as temperature, wind speed, and humidity, was gathered. Subsequently, the weekly mean values for outpatient visits, air pollution, and weather parameters were computed. Results The number of outpatient visits for allergic conjunctivitis was significantly associated with SPM levels (r = 0.70, p = 0.0037), oxidant levels (r = 0.70, p = 0.0038), wind speed (r = 0.48, p = 0.0472), and humidity (r = 0.77, p = 0.0009) from January to March, as well as SPM levels (r = 0.53, p = 0.0309) and carbon monoxide (r = 0.56, p = 0.0230) from April to June. Multivariate analysis showed that SPM (odds ratio = 1.37, p = 0.0161) and wind velocity (odds ratio = 1.52, p = 0.0038) were significant predictors of the number of outpatient visits from January to December. Conclusions SPM levels were the only independent predictor of outpatient visits for allergic conjunctivitis, suggesting that SPM contributes to the pathophysiology of this condition.

Assessment of Daily Exposure to Organophosphate Esters through PM2.5 Inhalation, Dust Ingestion, and Dermal Contact

Inhalation of airborne fine particulate matter (PM2.5), dust ingestion, and dermal contact with dust are important pathways for human exposure to different contaminants, such as organophosphate esters (OPE), compounds that are widely used as flame retardants and plasticizers. There are limited studies assessing the extent of the contamination of OPE in indoor airborne PM2.5. This study offers a novel approach by examining various indoor environments, such as homes, workplaces, and means of transport, where people typically spend their daily lives. The goal is to provide a comprehensive assessment of daily exposure to these pollutants. Both PM2.5 and dust samples were collected in order to determine the concentration levels of 17 different OPEs. Fifteen OPEs in PM2.5 and 16 in dust samples were detected. Concentration levels in indoor air ranged from 4.37 to 185 ng/m3 (median 24.4 ng/m3) and from 3.02 to 36.9 μg/g for the dust samples (median 10.2 μg/g). Estimated daily intakes (EDIs) of OPEs were calculated for adults, yielding median values of 3.97 ng/(kg bw × day) for EDIInhalation, 5.89 ng/(kg bw × day) for EDIDermal, and 1.75 ng/(kg bw × day) for EDIIngestion. Such levels lie below human health threshold risk limits, although in some cases they could be only 2 times below the threshold for carcinogenic risk, with a main contribution from tris(2-chloroethyl) phosphate (TCEP). Given this threshold proximity, additional exposure to these chemicals from other pathways, such as food ingestion, gas phase exposure, and/or inhalation of coarser particles (PM10-2.5), could therefore lead to health limit exceedances.

Two-sample mendelian randomization analysis investigates ambient fine particulate matter's impact on cardiovascular disease development

PM2.5, a key component of air pollution, significantly threatens public health. Cardiovascular disease is increasingly associated with air pollution, necessitating more research. This study used a meticulous two-sample Mendelian randomization (MR) approach to investigate the potential causal link between elevated PM2.5 levels and 25 types of cardiovascular diseases. Data sourced from the UK Biobank, focusing on individuals of European ancestry, underwent primary analysis using Inverse Variance Weighting. Additional methods such as MR-Egger, weighted median, Simple mode, and Weighted mode provided support. Sensitivity analyses assessed instrument variable heterogeneity, pleiotropy, and potential weak instrument variables. The study revealed a causal link between PM2.5 exposure and higher diagnoses of Atherosclerotic heart disease (primary or secondary, OR [95% CI] 1.0307 [1.0103-1.0516], p-value = 0.003 and OR [95% CI] 1.0179 [1.0028-1.0333], p-value = 0.0202) and Angina pectoris (primary or secondary, OR [95% CI] 1.0303 [1.0160-1.0449], p-value = 3.04e-05 and OR [95% CI] 1.0339 [1.0081-1.0603], p-value = 0.0096). Additionally, PM2.5 exposure increased the likelihood of diagnoses like Other forms of chronic ischaemic heart disease (secondary, OR [95% CI] 1.0193 [1.0042-1.0346], p-value = 0.0121), Essential hypertension (secondary, OR [95% CI] 1.0567 [1.0142-1.1010], p-value = 0.0085), Palpitations (OR [95% CI] 1.0163 [1.0071-1.0257], p-value = 5e-04), and Stroke (OR [95% CI] 1.0208 [1.0020-1.0401], p-value = 0.0301). Rigorous sensitivity analyses confirmed these significant findings' robustness and validity. Our study revealed the causal effect between higher PM2.5 concentrations and increased cardiovascular disease risks. This evidence is vital for policymakers and healthcare providers, urging targeted interventions to reduce PM2.5 levels.

Cigarette smoking and air pollution exposure and their effects on cardiovascular diseases

Cardiovascular disease (CVD) has no socioeconomic, topographical, or sex limitations as reported by the World Health Organization (WHO). The significant drivers of CVD are cardio-metabolic, behavioral, environmental, and social risk factors. However, some significant risk factors for CVD (e.g., a pitiable diet, tobacco smoking, and a lack of physical activities), have also been linked to an elevated risk of cardiovascular disease. Lifestyles and environmental factors are known key variables in cardiovascular disease. The familiarity with smoke goes along with the contact with the environment: air pollution is considered a source of toxins that contribute to the CVD burden. The incidence of myocardial infarction increases in males and females and may lead to fatal coronary artery disease, as confirmed by epidemiological studies. Lipid modification, inflammation, and vasomotor dysfunction are integral components of atherosclerosis development and advancement. These aspects are essential for the identification of atherosclerosis in clinical investigations. This article aims to show the findings on the influence of CVD on the health of individuals and human populations, as well as possible pathology and their involvement in smoking-related cardiovascular diseases. This review also explains lifestyle and environmental factors that are known to contribute to CVD, with indications suggesting an affiliation between cigarette smoking, air pollution, and CVD.

Associations between short-term exposure to fine particulate matter and acute myocardial infarction: A case-crossover study

BACKGROUND

Previous studies evaluated the impact of particle matters (PM) on the risk of acute myocardial infarction (AMI) based on local registries.

HYPOTHESIS

This study aimed to evaluate possible short term effect of air pollutants on occurrence of AMI based on a specific case report sheet that was designed for this purpose.

METHODS

AMI was documented among 982 patients who referred to the emergency departments in Tehran, Iran, between July 2017 to March 2019. For each patient, case period was defined as 24 hour period preceding the time of emergency admission and referent periods were defined as the corresponding time in 1, 2, and 3 weeks before the admission. The associations of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2 .5 ) and particulate matter with an aerodynamic diameter ≤10 μm (PM10 ) with AMI were analyzed using conditional logistic regression in a case-crossover design.

RESULT

Increase in PM2.5 and PM10 was significantly associated with the occurrence of AMI with and without adjustment for the temperature and humidity. In the adjusted model each 10 μg/m3 increase of PM10 and PM2.5 in case periods was significantly associated with increase myocardial infarction events (95% CI = 1.041-1.099, OR = 1.069 and 95% CI = 1.073-1.196, and OR = 1.133, respectively). Subgroup analysis showed that increase in PM10 did not increase AMI events in diabetic subgroup, but in all other subgroups PM10 and PM2 .5 concentration showed positive associations with increased AMI events.

CONCLUSION

Acute exposure to ambient air pollution was associated with increased risk of AMI irrespective of temperature and humidity.

Temporal and spatial heterogeneity of indoor and outdoor temperatures and their relationship with thermal sensation from a global perspective

People spend most of their time indoors. However, indoor temperature and individual thermal exposure are generally not considered in epidemiological studies of temperature and health. Based on the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) RP-884 Database, the ASHRAE Global Thermal Comfort Database II and the Chinese Thermal Comfort Database, this study first explored the relationship between outdoor temperature, indoor temperature and thermal sensation from a global perspective. Moreover, the potential influence of spatiotemporal heterogeneity on health studies was explored. A breakpoint was found at approximately 11.5 °C in the segmented regression of indoor and outdoor temperature, and the slope of the curve was greater when outdoor temperature was above the breakpoint (n = 67,896). Based on multi-group propensity score matching (PSM) and generalizedadditivemodels (GAM), spatiotemporal heterogeneity was found in the relationship between indoor and outdoor temperatures after adjusting for building type and year. Furthermore, the relationship between indoor temperature and thermal sensation was influenced by the outdoor temperature. This study highlights the importance of considering indoor temperature or individual thermal exposure in temperature-related health studies.

A longitudinal study on the effect of extreme temperature on non-accidental deaths in Hulunbuir City based on DLNM model

OBJECTIVE

To explore the frequency and effect of extreme temperature on the non-accidental death rate in Hulunbuir, a Chinese ice city.

METHODS

From 2014 to 2018, mortality data of residents residing in Hulunbuir City were collected. The lag and cumulative effects of extreme temperature conditions on non-accidental death and respiratory and circulatory diseases were analyzed by distributed lag non-linear models (DLNM).

RESULTS

The risk of death was the highest during high-temperature conditions, the RR value was 1.111 (95% CI 1.031 ~ 1.198). The effect was severe and acute. The risk of death during extreme low-temperature conditions peaked on the fifth day, (RR 1.057; 95% CI 1.012 ~ 1.112), then decreased and was maintained for 12 days. The cumulative RR value was 1.289 (95% CI 1.045 ~ 1.589). Heat significantly influenced the incidence of non-accidental death in both men (RR 1.187; 95% CI 1.059-1.331) and women (RR 1.252; 95% CI 1.085-1.445).

CONCLUSIONS

Regardless of the temperature effect, the risk of death in the elderly group (≥ 65 years) was significantly higher than that of the young group (0-64 years). High-temperature and low-temperature conditions can contribute to the increased number of deaths in Hulunbei. While high-temperature has an acute effect, low-temperature has a lagging effect. Elderly and women, as well as people with circulatory diseases, are more sensitive to extreme temperatures.

Spatiotemporal analysis and forecasting of air quality in the greater Dhaka region and assessment of a novel particulate matter filtration unit

Bangladesh is one of the most polluted nations in the world, with an average Air Quality Index (AQI) of 161 in 2021; its capital, Dhaka, has the worst air quality of any major city in the world. The present study aims to analyze the spatiotemporal distribution of air quality indicators in the greater Dhaka region, forecast weekly AQI, and assess the performance of a novel particulate matter filtration unit in removing particulate matter. Air quality indicators remained highest during the dry season with an average of 128.5 μm/m^3, while the lowest concentration was found in the monsoon season with an average of 19.096 μm/m³. Analysis revealed a statistically significant annual increasing trend of CO, which was associated with the growing number of brick kilns and usage of high-sulfur diesel. Except for the pre-monsoon AQI, concentrations of both seasonal and yearly AQI and PM_2.5 showed decreasing trend, though predominantly insignificant, demonstrating the improvement in air quality. Prevailing winds influenced the seasonal distribution of tropospheric CO & NO₂. The study also employed a seasonal autoregressive integrated moving average (ARIMA) model to forecast weekly AQI values. ARIMA (3,0,4) (3,1,3) at the 7-periodicity level performed best forecasting the AQI values among all developed models with low root mean square error (RMSE)-29.42 and mean absolute percentage error (MAPE)-13.11 values. The predicted AQI values suggested that the air quality would remain unhealthy for most weeks. The experimental simulation of the particulate matter filtration unit, designed in the shape of a road divider, generated substantial cyclonic motion while maintaining a very minimal pressure drop. In the real-world scenario, using only cyclonic separation and dry deposition, the suggested air filtration system removed 40%, 44%, and 42% of PM_2.5, PM₁₀, and TSP, respectively. Without employing filters, the device removed significant amounts of particulate matter, implying enormous potential to be used in the study area. The study could be useful for policy makers to improve urban air quality and public health in Bangladesh and in other developing countries.

Estimating future PM2.5-attributed acute myocardial infarction incident cases under climate mitigation and population change scenarios in Shandong Province, China

BACKGROUND

The effects of fine particulate matter (PM2.5) on acute myocardial infarction (AMI) have been widely recognized. However, no studies have comprehensively evaluated future PM2.5-attributed AMI burdens under different climate mitigation and population change scenarios. We aimed to quantify the PM2.5-AMI association and estimate the future change in PM2.5-attributed AMI incident cases under six integrated scenarios in 2030 and 2060 in Shandong Province, China.

METHODS

Daily AMI incident cases and air pollutant data were collected from 136 districts/counties in Shandong Province from 2017 - 2019. A two-stage analysis with a distributed lag nonlinear model was conducted to quantify the baseline PM2.5-AMI association. The future change in PM2.5-attributed AMI incident cases was estimated by combining the fitted PM2.5-AMI association with the projected daily PM2.5 concentrations under six integrated scenarios. We further analyzed the factors driving changes in PM2.5-related AMI incidence using a decomposition method.

RESULTS

Each 10 μg/m3 increase in PM2.5 exposure at lag05 was related to an excess risk of 1.3 % (95 % confidence intervals: 0.9 %, 1.7 %) for AMI incidence from 2017 - 2019 in Shandong Province. The estimated total PM2.5-attributed AMI incident cases would increase by 10.9-125.9 % and 6.4-244.6 % under Scenarios 1 - 3 in 2030 and 2060, whereas they would decrease by 0.9-5.2 % and 33.0-46.2 % under Scenarios 5 - 6 in 2030 and 2060, respectively. Furthermore, the percentage increases in PM2.5-attributed female cases (2030: -0.3 % to 135.1 %; 2060: -33.2 % to 321.5 %) and aging cases (2030: 15.2-171.8 %; 2060: -21.5 % to 394.2 %) would wholly exceed those in male cases (2030: -1.8 % to 133.2 %; 2060: -41.1 % to 264.3 %) and non-aging cases (2030: -41.0 % to 45.7 %; 2060: -89.5 % to -17.0 %) under six scenarios in 2030 and 2060. Population aging is the main driver of increased PM2.5-related AMI incidence under Scenarios 1 - 3 in 2030 and 2060, while improved air quality can offset these negative effects of population aging under the implementation of the carbon neutrality and 1.5 °C targets.

CONCLUSION

The combination of ambitious climate policies (i.e., 1.5 °C warming limits and carbon neutrality targets) with stringent clean air policies is necessary to reduce the health impacts of air pollution in Shandong Province, China, regardless of population aging.

Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements

PM₁₀-associated potential toxic elements (PTEs) can enter the respiratory system and cause health problems. In the current study, the health risk indices caused by PM₁₀ inhalation by adults, children, and infants in 158 European cities between 2013 and 2019 were studied to determine if Europeans were adversely affected by carcinogenic and non-carcinogenic factors or not. The Mann-Kendall trend test examined PM₁₀'s increasing or decreasing trend. Random Forest analysis was also used to analyse meteorological factors affecting PM₁₀ in Europe. Hazard quotient and cancer risk were estimated using PM₁₀-associated PTEs. Our results showed a decline in continental PM₁₀ concentrations. The correlation between PM₁₀ concentrations and temperature (-0.40), PBLH (-0.39), and precipitation were statistically strong (-0.21). The estimated Pearson correlation coefficients showed a statistically strong positive correlation between As & Pb, As & Cd, and Cd & Pb during 2013-2019, indicating a similar origin. PTEs with hazard quotients below one, regardless of subpopulation type, posed no noncancerous risk to Europeans. The hazard quotient values positively correlated with time, possibly due to elevated PTE levels. In our study on carcinogen pollution in Europe between 2013 and 2019, we found unacceptable levels of As, Cd, Ni, and Pb among adults, children, and infants. Carcinogenic risk rates were highest for children, followed by infants, adult women, and adult men. Therefore, besides monitoring and mitigating PM concentrations, effective control of PM sources is also needed.

PM2.5 extended-range forecast based on MJO and S2S using LightGBM

We developed an extended-range fine particulate matter (PM_2.5) prediction model in Shanghai using the light gradient-boosting machine (LightGBM) algorithm based on PM_2.5 historical data, meteorological observational data, Subseasonal-to-Seasonal Prediction Project (S2S) forecasts and Madden-Julian Oscillation (MJO) monitoring data. The analysis and prediction results demonstrated that the MJO improved the predictive skill of the extended-range PM_2.5 forecast. The MJO indexes, namely, real-time multivariate MJO series 1 (RMM1) and real-time multivariate MJO series 2 (RMM2), ranked the first, and seventh, respectively, in terms of the predictive contribution of all meteorological predictors. When the MJO was not introduced, the correlation coefficients for the forecasts on lead times of 11-40 days ranged from 0.27 to 0.55, and the root mean square errors (RMSEs) ranged from 23.4 to 31.8 μg/m³. After the MJO was introduced, the correlation coefficients for the 11-40 day forecast ranged from 0.31 to 0.56, among which those for the 16-40 day forecast substantially improved, and the RMSEs ranged from 23.2 to 28.7 μg/m³. When comparing the prediction scores, such as percent correct (PC), critical success index (CSI), and equitable threat score (ETS), the forecast model was more accurate when it introduced the MJO. A novel aspect of this study is to investigate the effects of the MJO mechanism on the meteorological conditions of air pollution in eastern China through advanced regression analysis. The MJO indexes RMM1 and RMM2 considerably impacted the geopotential height field of 28°-40° at 300-250 hPa 45 days in advance. When RMM1 increased and RMM2 decreased 45 days in advance, the 500 hPa geopotential height field weakened accordingly, and the bottom of the 500 hPa trough moved southward; thus cold air was more easily transported southward and the upstream air pollutants were transported to eastern China. With a weak ground pressure field and dry air at low altitudes, the westerly wind component increased, which led to the easier formation of a weather configuration favorable for the accumulation and transport of air pollution, thus resulting in an increase in PM_2.5 concentration in the region. These findings can guide forecasters regarding the utility of MJO and S2S for subseasonal air pollution outlooks.

Air Pollution and Aeroallergens as Possible Triggers in Preterm Birth Delivery

Preterm birth (PTB) identifies infants prematurely born <37 weeks/gestation and is one of the main causes of infant mortality. PTB has been linked to air pollution exposure, but its timing is still unclear and neglects the acute nature of delivery and its association with short-term effects. We analyzed 3 years of birth data (2015−2017) in Turin (Italy) and the relationships with proinflammatory chemicals (PM2.5, O3, and NO2) and biological (aeroallergens) pollutants on PTB vs. at-term birth, in the narrow window of a week before delivery. A tailored non-stationary Poisson model correcting for seasonality and possible confounding variables was applied. Relative risk associated with each pollutant was assessed at any time lag between 0 and 7 days prior to delivery. PTB risk was significantly associated with increased levels of both chemical (PM2.5, RR = 1.023 (1.003−1.043), O3, 1.025 (1.001−1.048)) and biological (aeroallergens, RR ~ 1.01 (1.0002−1.016)) pollutants in the week prior to delivery. None of these, except for NO2 (RR = 1.01 (1.002−1.021)), appeared to play any role on at-term delivery. Pollutant-induced acute inflammation eliciting delivery in at-risk pregnancies may represent the pathophysiological link between air pollution and PTB, as testified by the different effects played on PTB revealed. Further studies are needed to better elucidate a possible exposure threshold to prevent PTB.

Particulate Air Pollution and Primary Care Visits in Kosovo: A Time-Series Approach

This study aimed to investigate the effects of particulate air pollution (PM2.5) on cardiovascular and respiratory diseases in Pristina, Kosovo, in a time-series analysis using daily primary healthcare visits to primary care institutions from 2019 to 2022. For the observation period, 6440 cardiovascular and 15,141 respiratory visits were reported, whereas the daily mean concentrations of PM2.5 ranged between 2.41 and 120.3 µg/m³. Single-lag models indicated a bi-phasic lag structure with increasing effect estimates some days after the air pollution event. In the distributed lag model with seven lags, the effect estimates for the cardiovascular cases indicated the adverse effect of air pollution. The cumulative effect estimate (summed over lag 0 to 6) for an increase of 10 µg/m³ of PM2.5 was a relative risk of 1.010 (95% confidence interval: 1.001-1.019). For respiratory cases, a different lag model (lag 4 through 10) was additionally examined. In this model, significant increases in visits were observed on lags 7 and 8. Overall, no relevant increase in visits occurred during the seven days considered. Visits to general practitioners will often not occur immediately at disease onset because patients will wait, hoping that their health status improves spontaneously. Therefore, we expected some latency in the effects.

A Clinician's Guide to Occupational Exposures in the Military

PURPOSE OF REVIEW

Adverse occupational and environmental exposures are common causes of respiratory disease and health consequences requiring medical care. Understanding how these various exposures affect patients and how to elicit an adequate history is critical for any clinician. Military personnel are often overlooked when discussing groups at risk for environmental exposure-associated airway disease. There are close to 20 million active duty and veterans in the USA, and nearly all clinicians will at some point care for a patient that has served in the military.

RECENT FINDINGS

Exposures related to military work include burn pits, chemicals/toxins, sandstorms, and living conditions. Burn pits and military waste are increasingly recognized as potential hazards attributed to the ongoing conflicts in the Middle East. The link between these various military exposures and acute or chronic airway diseases remains difficult. Epidemiological studies are emerging to demonstrate correlations with chronic lung disease and prolonged burn pit exposure. This review provides an overview of potential occupational and environmental exposures that may affect current and/or former military service men and women.

Long-Term Exposure to Ambient Fine Particulate Matter and Incidence of Major Cardiovascular Diseases: A Prospective Study of 0.5 Million Adults in China

Few cohort studies explored the long-term effects of ambient fine particulate matter (PM_2.5) on incidence of cardiovascular diseases (CVDs), especially in countries with higher levels of air pollution. We aimed to evaluate the association between long-term exposure to PM_2.5 and incidence of CVD in China. We performed a prospective cohort study in ten regions that recruited 512,689 adults during 2004-2008, with follow-up until 2017. Annual PM_2.5 concentrations were estimated using a satellite-based model with national coverage and 1 x 1 km spatial resolution. Time-varying Cox proportional hazard regression models were used to estimate hazard ratios (HRs) for all-cause and cause-specific CVDs associated with PM_2.5, adjusting for conventional covariates. During 5.08 million person-years of follow-up, 148,030 incident cases of CVD were identified. Long-term exposure to PM_2.5 showed positive and linear association with incidence of CVD, without a threshold below any concentration. The adjusted HRs per 10 μg/m³ increase in PM_2.5 was 1.04 (95%CI: 1.02, 1.07) for total CVD. The risk estimates differed between certain population subgroups, with greater HRs in men, in household with higher income, and in people using unclean heating fuels. This prospective study of large Chinese population provided essential epidemiological evidence for CVD incident risk associated with PM_2.5.

Short-Term Effects of PM10, NO2, SO2 and O3 on Cardio-Respiratory Mortality in Cape Town, South Africa, 2006–2015

Background: The health effect of air pollution is rarely quantified in Africa, and this is evident in global systematic reviews and multi-city studies which only includes South Africa. Methods: A time-series analysis was conducted on daily mortality (cardiovascular (CVD) and respiratory diseases (RD)) and air pollution from 2006–2015 for the city of Cape Town. We fitted single- and multi-pollutant models to test the independent effects of particulate matter (PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ozone (O3) from co-pollutants. Results: daily average concentrations per interquartile range (IQR) increase of 16.4 µg/m3 PM10, 10.7 µg/m3 NO2, 6 µg/m3 SO2 and 15.6 µg/m3 O3 lag 0–1 were positively associated with CVD, with an increased risk of 2.4% (95% CI: 0.9–3.9%), 2.2 (95% CI: 0.4–4.1%), 1.4% (95% CI: 0–2.8%) and 2.5% (95% CI: 0.2–4.8%), respectively. For RD, only NO2 showed a significant positive association with a 4.5% (95% CI: 1.4–7.6%) increase per IQR. In multi-pollutant models, associations of NO2 with RD remained unchanged when adjusted for PM10 and SO2 but was weakened for O3. In CVD, O3 estimates were insensitive to other pollutants showing an increased risk. Interestingly, CVD and RD lag structures of PM10, showed significant acute effect with evidence of mortality displacement. Conclusion: The findings suggest that air pollution is associated with mortality, and exposure to PM10 advances the death of frail population.

The impact of local fugitive particulate matter and emission inventories on air quality and health in dry and arid areas

The arid and semi-arid regions are facing a huge brunt of fugitive Particulate Matter (fPM) pollution, usually ascribed to the natural dust generated at the regional level (>100 km). In this study, the contribution of locally generated fPM to air pollution and it's environmental risk were assessed at a typical dry-arid area in the Middle East (i.e., State of Qatar, 200 × 200 km² domain) with the use of different emission and dispersion models. Four modelling scenarios were constructed to reflect standard practices (e.g., regional emission models and the World Health Organization's (WHO) Environmental Burden of Disease (EBD) method) and higher resolution calculations with emission models that were developed in past field campaigns. Emphasis was given to the effect on the WHO methodology beyond the typical emission estimates and ambient concentration levels. Eventually, the use of higher spatial resolution population and concentration data revealed fPM hot spots yielding up to 11.0 times higher short-term excess mortalities (an average increase of 1.8 times) compared to the baseline WHO methodology, where the whole population was exposed to a single average concentration. A difference that could be attributed to the improvement of the emission estimations for barren lands and traffic. For example, the estimated PM₁₀ emission fluxes from barren lands, within the main metropolitan area, using the improved emissions model ranged from 0.05 to 42.0 μg m^-2 s^-1, which is considerably higher than the emissions predicted using just the literature models (0.03 to 2.0 μg m^-2 s^-1). Overall, the barren lands emissions accounted for more than 90% of the fPM emissions during the study period. Consequently, this study is one of the first to quantify the significance of locally induced fPM and highlight the need for dedicated field studies and improved emissions estimation tools.

Comparison of metropolitan cities for mortality rates attributed to ambient air pollution using the AirQ model

In the present study, the air pollution dynamics of the metropolitan cities of Balıkesir, Bursa, Istanbul, Kocaeli, Sakarya and Tekirdağ in the Marmara Region, which is the geographical region with the highest urban and industrial activity in Turkey, were examined for the time period between 2016 and 2019. Annual changes in the cities in terms of air pollution, which was examined with a focus on the PM_2.5 parameter as indicated by United Nations (UN) Sustainable Development Goals (SDGs); differences in the cities by years; and the seasonal changes in air pollution in the cities were investigated. Additionally, mortality rates attributed to air pollution were calculated with the AirQ + software based on integrated exposure-response function recommended by the World Health Organization (WHO) and the UN using city-scale statistics of fatal disease cases that can be attributed to air pollution. It was determined that all cities in the Marmara Region study area exceeded the limit PM_2.5 values specified by the European Union (EU) in the years 2016, 2017 and 2018 while only Kocaeli and Tekirdağ were below the limit values in 2019. The limit values specified by the WHO were exceeded in all cities in each year. A total of 46,920 premature deaths attributed to the exceedance of WHO limit values were calculated for the years 2016, 2017, 2018 and 2019 with 11,895, 13,853, 11,748 and 9,429, respectively. Determining national limit values for the PM_2.5 parameter, which is among the most important factors of air pollution, and monitoring it in a sustainable manner using a sufficient number of well-equipped stations is of great importance. This way, national, regional and urban action plans regarding the impact of air pollution on human health, as indicated by UN SDGs, can be prepared.

Fine-Grained Urban Air Quality Mapping from Sparse Mobile Air Pollution Measurements and Dense Traffic Density

Urban air quality mapping has been widely applied in urban planning, air pollution control and personal air pollution exposure assessment. Urban air quality maps are traditionally derived using measurements from fixed monitoring stations. Due to high cost, these stations are generally sparsely deployed in a few representative locations, leading to a highly generalized air quality map. In addition, urban air quality varies rapidly over short distances (<1 km) and is influenced by meteorological conditions, road network and traffic flow. These variations are not well represented in coarse-grained air quality maps generated by conventional fixed-site monitoring methods but have important implications for characterizing heterogeneous personal air pollution exposures and identifying localized air pollution hotspots. Therefore, fine-grained urban air quality mapping is indispensable. In this context, supplementary low-cost mobile sensors make mobile air quality monitoring a promising alternative. Using sparse air quality measurements collected by mobile sensors and various contextual factors, especially traffic flow, we propose a context-aware locally adapted deep forest (CLADF) model to infer the distribution of NO2 by 100 m and 1 h resolution for fine-grained air quality mapping. The CLADF model exploits deep forest to construct a local model for each cluster consisting of nearest neighbor measurements in contextual feature space, and considers traffic flow as an important contextual feature. Extensive validation experiments were conducted using mobile NO2 measurements collected by 17 postal vans equipped with low-cost sensors operating in Antwerp, Belgium. The experimental results demonstrate that the CLADF model achieves the lowest RMSE as well as advances in accuracy and correlation, compared with various benchmark models, including random forest, deep forest, extreme gradient boosting and support vector regression.

Long-Term Exposures to Air Pollutants and Risk of Peripheral Arterial Occlusive Disease: A Nationwide Cohort Study in Taiwan

Air pollution is one of the most alarming environmental issues which causes multiple health hazards. An association between air pollution and cardiovascular diseases has been established through many prior studies. In this study, we aimed to evaluate the risk of long-term exposure to air pollution (PM_2.5, CO, and NO₂) and its association with the risk of developing peripheral arterial occlusive disease (PAOD). PAOD is a condition involving impairment of perfusion of blood in the distal parts of the aorta due to narrowing of the arteries (arterial stenosis) and has been reported as a risk factor for developing cardiovascular diseases. Furthermore, the risk of PAOD increases with age, and hence is a serious public health issue and a cause for concern, especially for an aging society such as Taiwan. Two national-scale databases from Taiwan, the national health insurance database (NHIRD) and the Taiwan air quality-monitoring database (TAQMD), were linked to conduct this cohort study between 2003 and 2013. Cox proportional hazards regression with time-dependent modeling was used to evaluate the hazard ratio (HR) for PAOD with respect to daily exposure to air pollutants. The concentrations of each of the pollutants of interest (PM_2.5, NO₂, and CO) were categorized into four categories according to the daily average concentration of air pollutants for every quarter of the year, Q1 to Q4 (Q4 = highest). The cumulative incidence of PAOD was examined by Kaplan–Meier analysis with two-tailed log-rank test. A total of 1,598 PAOD cases were identified during the 10-year follow-up period, along with 98,540 non-PAOD controls. In the multivariate analysis, after adjusting for age, gender, urbanization level, residential area, baseline comorbidities, and medications, the adjusted HRs were PM_2.5 = 1.14 (95% CI 1.13–1.16), NO₂ = 1.03 (95% CI 1.02–1.04), and CO = 2.35 (95% CI 1.95–2.84). Kaplan–Meier analysis showed that CO (P < 0.0001) and PM_2.5 (P < 0.0001) concentrations were strongly and positively associated with the cumulative incidence of PAOD during the follow-up period. Findings from this study established that prolonged exposure to air pollutants CO and PM_2.5 are significant factors that, among other well-known causes, may also play a potential role in PAOD pathogenesis.

Study on characteristics of organic components in condensable particulate matter before and after wet flue gas desulfurization system of coal-fired power plants

Wet flue gas desulfurization (WFGD) in coal-fired power plants has a great impact on the emission of particulate matter, including filterable particulate matter (FPM) and condensable particulate matter (CPM). In this paper, CPM and FPM in flue gas before and after WFGD in coal-fired power plants were sampled in parallel. FPM was tested according to ISO standard 23210-2009, and CPM was tested according to U.S. EPA Method 202. A method for quantitatively analyzing fatty acid methyl esters in CPM was established, and the removal capacity of fatty acid methyl esters and phthalate esters by WFGD in a typical coal-fired unit was compared. Results show that WFGD has a significant effect on particle size distribution, concentration, and chemical composition. WFGD has a high removal efficiency of inorganic components in CPM, up to 54.74%. CPM contains a variety of organic compounds, including hydrocarbons, esters, siloxanes, halogenated hydrocarbons, and so on. In particular, esters are an important component in CPM, whose concentration tends to decrease after WFGD. Furthermore, a total of 11 fatty acid methyl esters and 5 phthalate esters were detected in CPM before and after WFGD. Noted that fatty acid methyl esters account for 13.38% of CPM, which make a higher contribution to the concentration of particulate matter than phthalate esters, while WFGD has a stronger control effect on the removal of phthalates.

Exposure of e-waste dismantlers from a formal recycling facility in Spain to inhalable organophosphate and halogenated flame retardants

Concentration levels of 16 organophosphate esters (OPEs) and 18 halogenated flame retardants (HFRs) were measured in airborne fine particulate matter (PM_2.5) from an e-waste dismantling facility in Catalonia (Spain) to assess their occurrence, profiles and potential health risks. Three different areas from the facility were studied, including an area for cathodic ray-tube (CRT) TV dismantling, a grinding area, and the outdoor background. OPEs and HFRs were detected in all samples, with concentrations between 10.4 and 110 ng/m³ for OPEs and from 0.72 to 2213 ng/m³ for HFRs. The compounds with highest concentrations in both working areas were triphenyl phosphate (TPHP) and tris(2-chloroisopropyl) phosphate (TCIPP) for OPEs and decabromodiphenyl ether (BDE-209) for HFRs. Higher concentration levels were found in the CRT area compared to the grinding one, probably due to the lower ventilation and different types of e-waste being processed. OPEs were also detected in the solid e-waste from the facility, highlighting the need to evaluate pollutant levels in e-waste before proceeding to its re-use. Estimated daily intakes via inhalation during workday were calculated, as well as carcinogenic and non-carcinogenic health risks, these being 25 and 50 times lower than threshold risk values in the worst cases, respectively. However, this calculated risk only considers the workday exposure via inhalation, while other routes of exposure (e.g., ingestion, dermal) could bring these values closer to threshold values.

Effect of airflow pattern and distance on removal of particulate matters and volatile organic compounds from cigarette smoke using Sansevieria trifasciata botanical biofilter

Botanical biofilters can effectively remove indoor air pollution. However, to apply botanical biofilters in situ, the distance of botanical biofilter to the pollutants and airflow pattern can be important factors impacting efficiency. This study examined the removal efficiency of particulate matters (PMs) and volatile organic compounds (VOCs) from cigarette smoke, such as formaldehyde and acetone, at various distances (100 cm, 175 cm, 240 cm, and 315 cm) using a Sansevieria trifasciata botanical biofilter. The botanical biofilter was placed inside a testing room (24 m³) and exposed to cigarette smoke. The pollutants removal efficiency was evaluated for six cycles (24 h/cycle) and one cycle as a recovery period where botanical biofilter was placed under normal conditions for 30 days. Results showed that the botanical biofilter could remove 140-250 μg m^-3, 147-257 μg m^-3, 212-455 μg m^-3 for PM₁, PM_2.5, and PM₁₀, respectively, at 8 h. Total VOCs, formaldehyde, and acetone removal were 40%-65%, 46%-69%, and 31%-61% at 24 h. PMs and VOCs removal efficiency can be affected by both distance and pattern of airflow in the testing room. The highest PM₁ and PM_2.5 elimination appeared at 240 cm and 315 cm, while VOCs removal was high at 100 cm. Botanical biofilter creates airflow vortices around 100 cm, indicating low removal of PMs. This is the first study that demonstrated the effect of airflow patterns on different pollutants removal efficiency.

Socio-Environmental Determinants and Human Health Exposures in Arid and Semi-Arid Zones of Iran-Narrative Review

Lifestyle is different in arid and semi-arid zones. However, where people are born and live have a lasting influence on their social and environmental exposure. This review focuses on the, various dimensions of environmental health imbalance inequality especially in significant environmental sources such as (ie, air, water, soil) among provinces that creates a big health gap in the center, East and the Southeast of Iran. Thus, the population of the arid and semi-arid zones of Iran is facing respiratory, cardiovascular, cancer and infection diseases linked to environmental problems such as chemical and microbial pollution due to air pollution and unsafe water sources, respectively. The prevalence of certain types of cancer such as skin, stomach, bladder, prostate and colorectal cancer together with some respiratory and cardiovascular diseases in arid and semiarid zones such as Kerman, Yazd, etc., has been reported in comparison with other provinces frequently. These impacts have effects on multiple levels of health security in those zones. Based on these concerns, we propose key questions that should guide research in the context of the socio environmental science to support science-based management actions in Iran and other similar semi-arid areas worldwide.

Exposure to particulate matter: a brief review with a focus on cardiovascular effects, children, and research conducted in Turkey

Exposure to environmental particulate matter (PM), outdoor air pollution in particular, has long been associated with adverse health effects. Today, PM has widely been accepted as a systemic toxicant showing adverse effects beyond the lungs. There are numerous studies, from those in vitro to epidemiological ones, suggesting various direct and indirect PM toxicity mechanisms associated with cardiovascular risks, including inflammatory responses, oxidative stress, changes in blood pressure, autonomic regulation of heart rate, suppression of endothelium-dependent vasodilation, thrombogenesis, myocardial infarction, and fibrinolysis. In addition to these and other health risks, considerations about air quality standards should include individual differences, lifestyle, and vulnerable populations such as children. Urban air pollution has been a major environmental issue for Turkey, and this review will also address current situation, research, and measures taken in our country.

Robust prediction of hourly PM2.5 from meteorological data using LightGBM

Retrieving historical fine particulate matter (PM2.5) data is key for evaluating the long-term impacts of PM2.5 on the environment, human health and climate change. Satellite-based aerosol optical depth has been used to estimate PM2.5, but estimations have largely been undermined by massive missing values, low sampling frequency and weak predictive capability. Here, using a novel feature engineering approach to incorporate spatial effects from meteorological data, we developed a robust LightGBM model that predicts PM2.5 at an unprecedented predictive capacity on hourly (R2 = 0.75), daily (R2 = 0.84), monthly (R2 = 0.88) and annual (R2 = 0.87) timescales. By taking advantage of spatial features, our model can also construct hourly gridded networks of PM2.5. This capability would be further enhanced if meteorological observations from regional stations were incorporated. Our results show that this model has great potential in reconstructing historical PM2.5 datasets and real-time gridded networks at high spatial-temporal resolutions. The resulting datasets can be assimilated into models to produce long-term re-analysis that incorporates interactions between aerosols and physical processes.

Real-Time Low-Cost Personal Monitoring for Exposure to PM2.5 among Asthmatic Children: Opportunities and Challenges

This study aims to evaluate the accuracy and effectiveness of real-time personal monitoring of exposure to PM concentrations using low-cost sensors, in comparison to conventional data collection method based on fixed stations. PM2.5 data were measured every 5 min using a low-cost sensor attached to a bag carried by 47 asthmatic children living in the Seoul Metropolitan area between November 2019 and March 2020, along with the real-time GPS location, temperature, and humidity. The mobile sensor data were then matched with station-based hourly PM2.5 data using the time and location. Despite some uncertainty and inaccuracy of the sensor data, similar temporal patterns were found between the two sources of PM2.5 data on an aggregate level. However, average PM2.5 concentrations via personal monitoring tended to be lower than those from the fixed stations, particularly when the subjects were indoors, during nighttime, and located farther from the fixed station. On an individual level, a substantial discrepancy is observed between the two PM2.5 data sources while staying indoors. This study provides guidance to policymakers and researchers on improving the feasibility of personal monitoring via low-cost mobile sensors as an alternative or supplement to the conventional station-based monitoring.

Three month inhalation exposure to low-level PM2.5 induced brain toxicity in an Alzheimer's disease mouse model

Although numerous epidemiological studies revealed an association between ambient fine particulate matter (PM2.5) exposure and Alzheimer's disease (AD), the PM2.5-induced neuron toxicity and associated mechanisms were not fully elucidated. The present study assessed brain toxicity in 6-month-old female triple-transgenic AD (3xTg-AD) mice following subchronic exposure to PM2.5 via an inhalation system. The treated mice were whole-bodily and continuously exposed to real-world PM2.5 for 3 months, while the control mice inhaled filtered air. Changes in cognitive and motor functions were evaluated using the Morris Water Maze and rotarod tests. Magnetic resonance imaging analysis was used to record gross brain volume alterations, and tissue staining with hematoxylin and eosin, Nissl, and immunohistochemistry methods were used to monitor pathological changes in microstructures after PM2.5 exposure. The levels of AD-related hallmarks and the oxidative stress biomarker malondialdehyde (MDA) were assessed using Western blot analysis and liquid chromatography-mass spectrometry, respectively. Our results showed that subchronic exposure to environmental levels of PM2.5 induced obvious neuronal loss in the cortex of exposed mice, but without significant impairment of cognitive and motor function. Increased levels of phosphorylated-tau and MDA were also observed in olfactory bulb or hippocampus after PM2.5 exposure, but no amyloid pathology was detected, as reported in previous studies. These results revealed that a relatively lower level of PM2.5 subchronic exposure from the environmental atmosphere still induced certain neurodegenerative changes in the brains of AD mice, especially in the olfactory bulb, entorhinal cortex and hippocampus, which is consistent with the nasal entry and spreading route for PM exposure. Systemic factors may also contribute to the neuronal toxicity. The effects of PM2.5 after a more prolonged exposure period are needed to establish a more comprehensive picture of the PM2.5-mediated development of AD.

Effect of indoor and outdoor sources on indoor particle concentrations in South Korean residential buildings

The rising indoor air pollution from particles is a cause for concern especially in houses where children and the elderly reside. In South Korea, assessment of exposure to particle number (PN) in residential apartments, which account for 76% of all houses, is limited. In our study, the indoor and outdoor PN (sizes 0.3-10.0 µm) concentrations were measured in ten typical apartments for 24 h each. In addition, the occupants' schedules were examined by conducting a survey. Results showed that the average outdoor PN concentrations were 0.30-4.37 × 10⁹/m³ with very large deviations. Indoor peak events were mainly caused by cooking, and total emitted particles were 0.01-81.3 × 10¹³ particles. Indoor PN concentrations were sustained for a long time because of inefficient ventilation that led to lowered attenuation. Indoor particles are generated during various indoor activities. The daily-integrated particle exposures were 21.4% and 78.6% for indoor and outdoor sources, respectively. Thus, outdoor sources were the predominant sources of particle exposure compared with indoor sources. In conclusion, penetration from outdoor sources needs to be reduced by adding air filtration to improve the airtightness of buildings when introducing outdoor air to lower the indoor PN concentration.

Coastal meteorology on the dispersion of air particles at the Bachok GAW Station

Meteorology over coastal region is a driving factor to the concentration of air particles and reactive gases. This study aims to conduct a research to determine the level of year-round air particles and the interaction of the meteorological driving factors with the particle number and mass in 2018, which is moderately influenced by Southeast Asian haze. We obtained the measurement data for particle number count (PNC), mass, reactive gases, and meteorological factors from a Global Atmospheric Watch (GAW) station located at Bachok Marine Research Center, Bachok, Kelantan, Malaysia. For various timeseries and correlation analyses, a 60-second resolution of the data has been averaged hourly and daily and visualized further. Our results showed the slight difference in particle behavior that is either measured by unit mass or number count at the study area. Diurnal variations showed that particles were generally high during morning and night periods. Spike was observed in August for PM_2.5/PNC_2.5 and PM₁₀/PNC₁₀ and in November for PM_Coarse/PNC_Coarse. From a polar plot, the particles came from two distinct sources (e.g., seaside and roadside) at the local scale. Regional wind vector shows two distinct wind-blown directions from northeast and southwest. The air mases were transported from northeast (e.g., Philippines, mainland China, and Taiwan) or southwest (e.g., Sumatra) region. Correlation analysis shows that relative humidity, wind direction, and pressure influence the increase in particles, whereas negative correlation with temperature is observed, and wind speed may have a potential role on the decline of particle concentration. The particles at the study area was highly influenced by the changes in regional wind direction and speed.

Combining machine learning models through multiple data division methods for PM2.5 forecasting in Northern Xinjiang, China

In this study, daily average PM_2.5 forecasting models were developed and applied in the Northern Xinjiang, China, through combining the back propagation artificial neural network (BPANN) and multiple linear regression (MLR) with another BPANN model. The meteorological (daily average precipitation, pressure, relative humidity, temperature, and wind speed, daily maximum wind speed and sunshine hours on the same day) and air pollutant data (daily PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃ concentrations on the previous day) in January and August of each year from 2015 to 2019 were used as candidate inputs. The optimal member and combining models were evaluated through the leave-one-out cross-validation (LOOCV), fivefold cross-validation, and hold-out methods. Twelve member models with optimal or sub-optimal performance were further used to develop the combining models. The performances of the BPANN and MLR member models were different using three data division methods. The models were evaluated more comprehensively through the LOOCV. The performances of the combining models were generally better than the member models. For both member and combining models, the PM_2.5 forecasting model performance in August was generally better than in January. The correlation coefficient (R) for the validation set of the optimal combination model was about 0.87 in January and 0.946 in August. These results showed that combining linear and nonlinear models through multiple data division methods would be an effective tool to forecast PM_2.5 concentrations.

Factors influencing protective behaviours during haze episodes in Singapore: A population-based study

INTRODUCTION

Haze is a recurrent problem in Southeast Asia. Exposure to haze is linked to ophthalmic, respiratory and cardiovascular diseases, and mortality. In this study, we investigated the role of demographic factors, knowledge and perceived risk in influencing protective behaviours during the 2013 haze in Singapore.

METHODS

We evaluated 696 adults in a cross-sectional study. Participants were sampled via a 2-stage simple random sampling without replacement from a large residential district in Singapore in 2015. The questionnaire measured the participant's knowledge, perceived risk and behaviours during the Southeast Asian haze crisis in 2013. Reliability and validity of the questionnaire were assessed using comparative fit index (≥0.96) and root mean square error of approximation (≤0.05). We performed structural equation modelling to examine the relationship between the hypothesised factors and protective behaviours.

RESULTS

More than 95% of the individuals engaged in at least 1 form of protective behaviour. Knowledge was strongly associated with protective behaviours via direct effect (β=0.45, 95% CI 0.19-0.69, P<0.001) and indirect effect through perceived risk (β=0.18, 95% CI 0.07-0.31, P=0.002). Perceived risk was associated with protective behaviours (β=0.28, 95% CI:0.11-0.44, P=0.002). A lower household income and ethnic minority were associated with protective behaviours. A lower education level and smokers were associated with lower knowledge of haze. A higher education and ethnic minority were associated with a lower perceived risk. Wearing of N95 masks was associated with other haze-related protective behaviours (β=0.24, 95% CI 0.08-0.37, P=0.001).

CONCLUSION

Knowledge was associated with protective behaviours, suggesting the importance of public education. Efforts should target those of lower education level and smokers. The wearing of N95 masks correlates with uptake of other protective behaviours.

A Novel Rabbit Dry Eye Model Induced by a Controlled Drying System

Purpose

To establish an environment-induced dry eye model in rabbits using a controlled drying system (CDS).

Methods

Rabbits were randomly divided into two groups. The rabbits in the dry group were housed in the CDS, in which the relative humidity, airflow, and temperature were controlled at 22% ± 4%, 3 to 4 m/s, and 23°C to 25°C for 14 days. The rabbits in the control group were housed in a normal environment at the same time. A Schirmer test, fluorescein staining, and lissamine green staining were performed. On day 14, the eyeballs and lacrimal glands were processed for evaluating the corneal epithelial thickness, inflammatory cell infiltration index, goblet cell density, and expression of the MUC5AC protein and caspase-3 protein. The mRNA expression of the involved inflammatory genes was analyzed.

Results

The CDS was able to maintain a dry environment, in which the tear production decreased, and the ocular surface staining increased over time in the rabbits. In the dry group, the corneal epithelium became thinner, inflammatory cells were noted, goblet cells and MUC5AC proteins decreased, and the increased levels of caspase-3 proteins and inflammatory cytokines were observed in the ocular surface tissues and lacrimal glands.

Conclusions

This CDS could create a dry environment, in which the rabbits exhibited a pathological change in dry eye similar to that in humans.

Translational Relevance

This model would be helpful in offering a platform to identify and test candidate therapies for environment-induced dry eye and to explore its underlying mechanisms.

Confounding by Socioeconomic Status in Epidemiological Studies of Air Pollution and Health: Challenges and Opportunities

BACKGROUND

Despite a vast air pollution epidemiology literature to date and the recognition that lower-socioeconomic status (SES) populations are often disproportionately exposed to pollution, there is little research identifying optimal means of adjusting for confounding by SES in air pollution epidemiology, nor is there a strong understanding of biases that may result from improper adjustment.

OBJECTIVE

We aim to provide a conceptualization of SES and a review of approaches to its measurement in the U.S. context and discuss pathways by which SES may influence health and confound effects of air pollution. We explore bias related to measurement and operationalization and identify statistical approaches to reduce bias and confounding.

DISCUSSION

Drawing on the social epidemiology, health geography, and economic literatures, we describe how SES, a multifaceted construct operating through myriad pathways, may be conceptualized and operationalized in air pollution epidemiology studies. SES varies across individuals within the contexts of place, time, and culture. Although no single variable or index can fully capture SES, many studies rely on only a single measure. We recommend examining multiple facets of SES appropriate to the study design. Furthermore, investigators should carefully consider the multiple mechanisms by which SES might be operating to identify those SES indicators that may be most appropriate for a given context or study design and assess the impact of improper adjustment on air pollution effect estimates. Last, exploring model contraction and expansion methods may enrich adjustment, whereas statistical approaches, such as quantitative bias analysis, may be used to evaluate residual confounding. https://doi.org/10.1289/EHP7980.

Characteristics and sources of hourly elements in PM10 and PM2.5 during wintertime in Beijing

Characteristics and sources of ambient particle elements in urban Beijing were studied by hourly observations in two size fractions (PM₁₀ and PM_2.5) during November and December 2017 using an online multi-element analyzer. The reconstructed oxide concentrations of 24 elements (from Al to Pb) comprise an appreciable fraction of PM₁₀ and PM_2.5, accounting for 37% and 17%, respectively on average. We demonstrate the benefit of using high-time-resolution chemical speciation data in achieving robust source apportionment of the total elemental PM₁₀ (PM_10el) and elemental PM_2.5 (PM_2.5el) mass using positive matrix factorization (PMF). Biomass burning, coal combustion, secondary sulfate, industry, non-exhaust traffic and dust were identified in both size fractions (with varying relative concentrations), which accounted on average for 4%, 12%, 5%, 2%, 14%, and 63%, respectively to the total PM_10el, and 14%, 35%, 21%, 6%, 12% and 12%, respectively to the total PM_2.5el. Biomass burning and coal combustion exhibited higher concentrations during haze episodes of the heating season. In contrast, secondary sulfate and industry contributed more to haze episodes during the non-heating season. The fractional contribution of dust was mostly high during clean days, while the fractional non-exhaust traffic emission contribution was similar throughout the measurement period. The non-exhaust traffic emissions contributed locally, while the remaining sources were dominated by neighboring areas. Furthermore, trajectory analysis showed that the origin of the industrial sources roughly agreed with the locations of the main point sources. Overall, this work provides detailed information on the characteristics of the elements during different haze events during heating and non-heating seasons.

Effect of PM2.5 pollution on perinatal mortality in China

Using ArcGIS to analyze satellite derived PM_2.5 estimates, this paper obtains the average concentration and maximum concentration of fine particulate matter (PM_2.5) in China's 31 provinces from 2002 to 2015. We adopt fixed effects model and spatial Durbin model to investigate the association between PM_2.5 and perinatal mortality rates. The results indicate that PM_2.5 has a significantly positive association with perinatal mortality rates. A 1% increase of log-transformed average concentration and maximum concentrations of PM_2.5 is associated with 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM_2.5 has significant spatial autocorrelation characteristics. The concentrations of log-transformed average and maximum PM_2.5 increase 1% is associated with a 2.49% increase in a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. The potential mechanism is that air pollution has an impact on infant weight to impact perinatal mortality rates.

Ambient Air Pollution and Mortality among Older Patients Initiating Maintenance Dialysis

BACKGROUND

Fine particulate matter (particulate matter with diameter <2.5 µm [PM2.5]) is associated with CKD progression and may impact the health of patients living with kidney failure. While older (aged ≥65 years) adults are most vulnerable to the impact of PM2.5, it is unclear whether older patients on dialysis are at elevated risk of mortality when exposed to fine particulate matter.

METHODS

Older adults initiating dialysis (2010-2016) were identified from US Renal Data System (USRDS). PM2.5 concentrations were obtained from NASA's Socioeconomic Data and Application Center (SEDAC) Global Annual PM2.5 Grids. We investigated the association between PM2.5 and all-cause mortality using Cox proportional hazard models with linear splines [knot at the current Environmental Protection Agency (EPA) National Ambient Air Quality Standard for PM2.5 of 12 μg/m3] and robust variance.

RESULTS

For older dialysis patients who resided in areas with high PM2.5, a 10 μg/m3 increase in PM2.5 was associated with 1.16-fold (95% CI: 1.08-1.25) increased risk of mortality; furthermore, those who were female (aHR = 1.26, 95% CI: 1.13-1.42), Black (aHR = 1.31, 95% CI: 1.09-1.59), or had diabetes as a primary cause of kidney failure (aHR = 1.25, 95% CI: 1.13-1.38) were most vulnerable to high PM2.5. While the mortality risk associated with PM2.5 was stronger at higher levels (aHR = 1.19, 95% CI: 1.08-1.32), at lower levels (≤12 μg/m3), PM2.5 was significantly associated with mortality risk (aHR = 1.04, 95% CI: 1.00-1.07) among patients aged ≥75 years (Pslope difference = 0.006).

CONCLUSIONS

Older adults initiating dialysis who resided in ZIP codes with PM2.5 levels >12 μg/m3 are at increased risk of mortality. Those aged >75 were at elevated risk even at levels below the EPA Standard for PM2.5.

Did the COVID-19 lockdown in Delhi and Kolkata improve the ambient air quality of the two cities?

To control the spread of COVID-19, the government of India imposed a nationwide lockdown on all nonessential activities from 22 Mar. to 3 May 2020. Daily ambient particulate matter ≤10 μm in diameter (PM₁₀ ), particulate matter ≤2.5 μm in diameter (PM_2.5 ), NO, NO₂ , and O₃ concentrations in Delhi and Kolkata from 1 March to 3 May in both 2019 and 2020 were collected from different monitoring stations along with meteorological data to study the impact of the COVID-19 lockdown on ambient pollutant concentrations. In 2020, average ambient concentrations of PM₁₀ and PM_2.5 were significantly decreased (Delhi: 59 and 43%, respectively; Kolkata: 49 and 50%, respectively) during the lockdown period compared with the same period during 2019 in both cities. Average ambient O₃ concentration in Delhi was significantly lower in 2020 (38.5 μg m^-3 ) compared with 2019 (44.7 μg m^-3 ) during the study period. However, average ambient O₃ concentration was significantly higher during 2020 (46.9 μg m^-3 ) compared with 2019 (31.4 μg m^-3 ) in Kolkata. Effect size analysis of different predictive variables reveals that the lockdown period explains maximum variation in ambient concentrations of PM₁₀ and PM_2.5 during 2020 in both cities. However, maximum variation in ambient O₃ concentrations in both cities was explained primarily by spatial variation rather than by the lockdown period. This study suggests that major policy implementation related to the transport and industrial sectors that aims to address the ambient air pollution problem in India may reduce the ambient particulate matter concentrations, although it may not have a significant effect on other ambient air pollutants such as O₃ in major Indian cities.

[Air pollution and cardiovascular diseases]

Air pollution in the environment and in households is responsible worldwide for almost 9 million preventable premature deaths per year and almost 800,000 such deaths within Europe. Air pollution therefore shortens life expectancy worldwide by almost 3 years. Smoking, a proven cardiovascular risk factor, shortens the mean life expectancy by 2.2 years. Epidemiological studies have shown that air pollution from fine and coarse particulate matter is associated with increased cardiovascular morbidity and mortality. Responsible for this are mainly cardiovascular diseases, such as coronary heart disease, heart attack, heart failure, stroke, hypertension and also diabetes, which are mainly caused or aggravated by fine particulate matter. After inhalation fine particulate matter can reach the brain directly and also reach the bloodstream via a transition process. There, the particles are absorbed by the blood vessels where they stimulate the formation of reactive oxygen species (ROS) in the vascular wall. They therefore promote the formation of atherosclerotic changes and in this way increase the cardiovascular risks, especially an increase in chronic ischemic heart disease and stroke. Recent studies also reported that in coronavirus disease 2019 (COVID-19) patients a high degree of air pollution is correlated with severe disease courses with cardiovascular complications and pulmonary diseases. This necessitates preventive measures, such as lowering of the upper limits for air pollutants. Individual measures to mitigate the health consequences of fine particulate matter are also discussed.

Effects of PM10 and Weather on Respiratory and Cardiovascular Diseases in the Ciuc Basin (Romanian Carpathians)

This study presents the PM10 concentration, respiratory and cardiovascular disease hospital admissions evolution in the Ciuc basin for a period of 9 years (2008–2016), taking into consideration different meteorological conditions: boundary layer, lifting condensation level, temperature-humidity index, and wind chill equivalent chart index. The PM10 and hospital admissions evolution showed a very fluctuated hourly, weekly, monthly, yearly tendency. The PM10 concentration in winter (34.72 μg/m3) was 82% higher than the multiannual average (19.00 μg/m3), and almost three times higher than in summer (11.71 μg/m3). During the winter, PM10 concentration increased by an average of 9.36 μg/m3 due to the increased household heating. Climatological parameters have a demonstrable effect on the PM10 concentration variation. Children, the elderly and men are more sensitive to air pollution, the calculated relative risk for men was (RR = 1.45), and for women (RR = 1.37), respectively. A moderate correlation (0.51) was found between PM10 and pneumonia (P), while a relatively weak correlation (0.39) was demonstrated in the case of PM10 and upper respiratory tract infections (URTI). Furthermore, except thermal humidity index (THI), strong negative correlations were observed between the multiannual monthly mean PM10 and the meteorological data. The PM10 followed a moderate negative correlation with the boundary layer (−0.61). In the case of URTI and P, the highest number of hospital admissions occurred with a 5 to 7-day lag, while the 10 μg/m3 PM10 increase resulted in a 2.04% and 8.28% morbidity increase. For lung cancer (LC) and cardiovascular diseases (AMI, IHD, CCP), a maximum delay of 5–6 months was found. Three-month delay and an average growth of 1.51% was observed in the case of chronic obstructive pulmonary disease (COPD). Overall, these findings revealed that PM10 was and it is responsible for one-third of the diseases.

Quantitative analysis of air pollution and mortality in Portugal: Current trends and links following proposed biological pathways

A wealth of studies focusing on the relationships between negative health outcomes and short-term and long-term exposures to environmental risk factors have produced estimates of the burden of disease attributable to air pollution, which have led to the implementation of air pollution control strategies. However, the call to expand those studies, in terms of geographical units of analysis to produce more accurate estimates of the burden of disease in the different countries has been made. Studies of the specific environment-health relationship concerning air pollution in Portugal are scarce and rather descriptive. Therefore, this work assesses the trends both in atmospheric levels of pollutants including particulate matter (PM₁₀), ozone (O₃), nitrogen dioxide (NO₂) and sulphur dioxide (SO₂), and in mortality rates for diabetes, malignant neoplasms and diseases of the respiratory, digestive and circulatory systems, and explores the links between exposure to air pollutants and mortality, following proposed biological pathways and using inferential statistics methods, for the period 2010 to 2017 in Portugal. The following major conclusions were drawn: (i) despite a somewhat initial downward trend in PM₁₀ and a peak in O₃ levels, fairly constant air pollution levels were mostly observed; (ii) concomitantly, increases in age-adjusted mortality rates were significant for all diseases except diabetes; (iii) lower atmospheric levels of pollutants were observed in rural areas, when compared to urban areas, except for ozone; (iv) age-adjusted mortality rates were higher in rural regions, for diabetes, and in urban regions, for malignant neoplasms; (v) for a 10 μg/m³ increase in atmospheric levels of PM₁₀, regression analysis estimated an increase of 0.30% in the mortality rate for diseases of the respiratory, digestive and circulatory systems, and malignant neoplasms combined.

A review of current air quality indexes and improvements under the multi-contaminant air pollution exposure

The air quality is one of the major concerns in the urban environment due to the rapid changes in pollutant emissions driven by complex and intensive human activities. Therefore, quantification of the urban air quality has become an essential need for both urban residents and authorities to quickly assess air quality conditions. To reach this aim, the air quality index (AQI) is the primary way to better understand the urban air quality. However, the varied AQIs in different countries are difficult to directly compare due to the varied calculation methods. Thus, this research presents an updated review of the major AQIs worldwide by dividing them into two categories: single- and multi-contaminant-oriented AQIs. Single-contaminant-oriented AQIs are based on the maximum value of individual pollutants and are applied in most countries with location-dependent standards, such as the United States, China, the United Kingdom and New South Wales, Australia. However, these may greatly underestimate the impact of multiple contaminants, be difficult to dynamically update or to be compared internationally. Moreover, multi-contaminant-oriented AQIs are available in the literature, which consider the combined effects of exposure to multiple contaminants. Among these AQIs, arithmetic pollutant aggregation simply integrates pollutants in a linear or nonlinear way, and weighted pollutant aggregation further assigns varied weights from different perspectives. Combining the advantages and disadvantages of the existing AQIs, the general air quality health index (GAQHI) is proposed as a pollutant-aggregated, local health-based AQI paradigm suitable for the present complex multi-contaminant situation. It provides a direction for the construction of a more accurate, consistent and comparable AQI system and can help both researchers and governments improve human well-being and achieve sustainable development.

Source Apportionment and Assessment of Air Quality Index of PM2.5–10 and PM2.5 in at Two Different Sites in Urban Background Area in Senegal

Identifying the particulate matter (PM) sources is an essential step to assess PM effects on human health and understand PM’s behavior in a specific environment. Information about the composition of the organic or/and inorganic fraction of PM is usually used for source apportionment studies. In this study that took place in Dakar, Senegal, the identification of the sources of two PM fractions was performed by utilizing data on the elemental composition and elemental carbon content. Four PM sources were identified using positive matrix factorization (PMF): Industrial emissions, mineral dust, traffic emissions, and sea salt/secondary sulfates. To assess the effect of PM on human health the air quality index (AQI) was estimated. The highest values of AQI are approximately 497 and 488, in Yoff and Hlm, respectively. The spatial location of the sources was investigated using potential source contribution function (PSCF). PSCF plots revealed the high effect of transported dust from the desert regions to PM concentration in the sampling site. To the best of our knowledge, this is the first source apportionment study on PM fractions published for Dakar, Senegal.

Liaison between exposure to sub-micrometric particulate matter and allergic response in children from a petrochemical industry city

The study examines the association between exposure to sub-micrometric Particulate Matter (PM₁) and allergic response in a group of sensitive young children (age: 2-10 years) from Ploiesti city, Romania. The city is the only urban agglomeration in Europe surrounded by four oil refineries. A panel study was conducted by collecting medical information from children with respiratory illnesses and atopy (n = 135). Hot Spot Analysis revealed the areas of the city that are susceptible to high levels of PM₁. We found a close interaction between exposure to PM₁ outdoor concentrations and various physiological changes and clinical symptoms in children including triggering of allergic reactions, rhinitis, alteration of lung function, upper and lower respiratory tract symptoms, and bronchial asthma. During the 2-year study period, the incidence of hospitalizations was 40.7%. Strong correlations (p < 0.001) were observed between the PM₁ exposure and hospitalizations, and exposure and Immunoglobulin E (IgE). PM₁ exposure was also correlated with eosinophils (p < 0.05). Another positive correlation was observed between hospitalizations and IgE levels (p < 0.05). The mean results of tested indicators were as follows: wheezing (5.3, 95% CI (1.4-1.8); Coeff. of var. (CV) = 30%), IgE (382, 95% CI (349-445); CV = 102%), and EO% (5.3, 95% CI (3.3-4.2); CV = 69.5%). We can conclude that exposure to PM₁ influenced the frequency of wheezing episodes, increased hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers. CAPSULE: Exposure to sub-micrometric particles (PM₁) influences the frequency of wheezing episodes, hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers.

Short-term PM2.5 exposure and circulating von Willebrand factor level: a meta-analysis

BACKGROUND

Ambient fine particulate matter (PM_2.5) is a major threat to cardiovascular health. Endothelial dysfunction is the initiating event associated with the PM_2.5-induced cardiovascular disease (CVD). A sensitive marker of endothelial function-circulating von Willebrand factor (vWF), is an independent predictor of adverse clinical outcome in CVD patients. PM_2.5 exposure may cause CVD, but the reports of relationship between short-term PM_2.5 exposure and circulating vWF are inconsistent.

OBJECTIVE

To explore the influence of short-term PM_2.5 exposure on circulating vWF.

METHODS

By using a combination of computer and manual retrieval, a systematic literature retrieval was conducted on PubMed, Cochrane Library, Web of Science, Embase and Scopus databases up to October 2019. The heterogeneity among studies was tested by Stata 12.0, and the pooled %-change (percentage change per 10 μg/m³ increase in PM_2.5) and its 95% confidence interval (95%CI) were calculated by using random effect model. Sensitivity analysis and publication bias detection were also carried out.

RESULTS

12 articles were included in this meta-analysis. Short-term PM_2.5 exposure (per 10 μg/m³ increase) was associated with the increased vWF (%-change = 0.41, 95%CI: 0.11-0.71). The pooled effect estimates of subgroup with PM_2.5 exposure level < 25 μg/m³ was higher (%-change = 8.26; 95%CI: 1.99-14.53) than that with PM_2.5 exposure level ≥ 25 μg/m³ (%-change = 0.36; 95%CI: 0.09-0.63).

CONCLUSION

Short-term PM_2.5 exposure is associated with the increased circulating vWF. It suggests that short-term PM_2.5 exposure causes endothelial dysfunction.