Abstract  Background: In 2012, the EPA enacted more stringent National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM2.5). Few studies have characterized the health effects of air pollution levels lower than the most recent NAAQS for long-term exposure to PM2.5 (now 12 μg/m3). Methods: We constructed a cohort of 32,119 Medicare beneficiaries residing in 5138 US ZIP codes who were interviewed as part of the Medicare Current Beneficiary Survey (MCBS) between 2002 and 2010 and had 1 year of follow-up. We considered four outcomes: all-cause hospitalizations, hospitalizations for circulatory diseases and respiratory diseases, and death. Results: We found that increasing exposure to PM2.5 from levels lower than 12 μg/m3 to levels higher than 12 μg/m3 is associated with increases in all-cause admission rates of 7% (95% CI = 3%, 10%) and in circulatory admission hazard rates of 6% (95% CI = 2%, 9%). When we restricted analysis to enrollees with exposure always lower than 12 μg/m3, we found that increasing exposure from levels lower than 8 μg/m3 to levels higher than 8 μg/m3 increased all-cause admission hazard rates by 15% (95% CI = 8%, 23%), circulatory by 18% (95% CI = 10%, 27%), and respiratory by 21% (95% CI = 9%, 34%).

Abstract  Motor vehicles are major sources of fine particulate matter (PM2.5), and the PM2.5 from mobile vehicles is associated with adverse health effects. Traditional methods for estimating source impacts that employ receptor models are limited by the availability of observational data. To better estimate temporally and spatially resolved mobile source impacts on PM2.5, we developed an approach based on a method that uses elemental carbon (EC), carbon monoxide (CO), and nitrogen oxide (NOx) measurements as an indicator of mobile source impacts. We extended the original integrated mobile source indicator (IMSI) method in three aspects. First, we generated spatially resolved indicators using 24-hr average concentrations of EC, CO, and NOx estimated at 4 km resolution by applying a method developed to fuse chemical transport model (Community Multiscale Air Quality Model [CMAQ]) simulations and observations. Second, we used spatially resolved emissions instead of county-level emissions in the IMSI formulation. Third, we spatially calibrated the unitless indicators to annually-averaged mobile source impacts estimated by the receptor model Chemical Mass Balance (CMB). Daily total mobile source impacts on PM2.5, as well as separate gasoline and diesel vehicle impacts, were estimated at 12 km resolution from 2002 to 2008 and 4 km resolution from 2008 to 2010 for Georgia. The total mobile and separate vehicle source impacts compared well with daily CMB results, with high temporal correlation (e.g., R ranges from 0.59 to 0.88 for total mobile sources with 4 km resolution at nine locations). The total mobile source impacts had higher correlation and lower error than the separate gasoline and diesel sources when compared with observation-based CMB estimates. Overall, the enhanced approach provides spatially resolved mobile source impacts that are similar to observation-based estimates and can be used to improve assessment of health effects. Implications: An approach is developed based on an integrated mobile source indicator method to estimate spatiotemporal PM2.5 mobile source impacts. The approach employs three air pollutant concentration fields that are readily simulated at 4 and 12 km resolutions, and is calibrated using PM2.5 source apportionment modeling results to generate daily mobile source impacts in the state of Georgia. The estimated source impacts can be used in investigations of traffic pollution and health.

Abstract  Background: Ambient fine particulate matter (PM2.5) is the major environmental health risk factor in Korea. Exposure to PM2.5 has been a growing public concern nationwide. With the rapid aging of the Korean population, the health effects attributable to long-term exposure to PM2.5 were expected to increase further in the future. We aimed to estimate premature deaths attributable to long-term exposure to ambient PM2.5 in Korea.Methods: A modelled estimation of long-term exposure to PM2.5 was used to calculate the nationwide exposure level. Hazard ratios of long-term exposure to PM2.5 were obtained from a large prospective cohort study in North America. Modified cause of death (CoD) data, which applied the garbage code reclassification algorithm, were used to calculate premature deaths attributable to long-term exposure to PM2.5.Results: From 1990 to 2013, the average population-weighted PM2.5 concentration in Korea was 30.2 mu g/m(3). The estimated number of premature deaths was 17,203 (95% confidence interval [CI], 11,056-22,772). The most common CoD was ischemic stroke (5,382; 3,101-7,403), followed by cancer of trachea, bronchus, and lung (4,958; 2,857-6,820), hemorrhagic stroke (3,452; 1,989-4,748), and ischemic heart disease (3,432; 1,383-5,358).Conclusion: Premature deaths due to long-term exposure to PM2.5 accounted for 6.4% of all deaths in Korea. However, individual efforts alone cannot prevent the effects of air pollution. This disease burden study can serve as a basis for the establishment of government policies and budgets and can be used to assess the effectiveness of environmental health policies.

Abstract  Background-Prior studies have demonstrated the association of air pollution with cardiovascular deaths. Singapore experiences seasonal transboundary haze. We investigated the association between air pollution and acute myocardial infarction (AMI) incidence in Singapore.Methods and Results-We performed a time-stratified case-crossover study on all AMI cases in the Singapore Myocardial Infarction Registry (2010-2015). Exposure on days where AMI occurred (case days) were compared with the exposure on days where AMI did not occur (control days). Control days were chosen on the same day of the week earlier and later in the same month and year. We fitted conditional Poisson regression models to daily AMI incidence to include confounders such as ambient temperature, rainfall, wind-speed, and Pollutant Standards Index. We assessed relationships between AMI incidence and Pollutant Standards Index in the entire cohort and subgroups of individual-level characteristics. There were 53 948 cases. Each 30-unit increase in Pollutant Standards Index was association with AMI incidence (incidence risk ratio [IRR] 1.04, 95% CI 1.03-1.06). In the subgroup of ST-segment-elevation myocardial infarction the IRR was 1.00, 95% CI 0.98 to 1.03, while for non-ST-segment-elevation myocardial infarction, the IRR was 1.08, 95% CI 1.05 to 1.10. Subgroup analyses showed generally significant. Moderate/unhealthy Pollutant Standards Index showed association with AMI occurrence with IRR 1.08, 95% CI 1.05 to 1.11 and IRR 1.09, 95% CI 1.01 to 1.18, respectively. Excess risk remained elevated through the day of exposure and for >2 years after.Conclusions-We found an effect of short-term air pollution on AMI incidence, especially non-ST-segment-elevation myocardial infarction and inpatient AMI. These findings have public health implications for primary prevention and emergency health services during haze.

Abstract  BACKGROUND: China began to carry out fine particulate matter (PM2.5) monitoring in 2013 and the amount of related research is low, especially in areas with lighter air pollution. This study aims to explore the association between PM2.5 and cardiovascular disease (CVD), ischemic heart disease (IHD) and cerebral vascular disease (EVD) mortality in areas with lighter air pollution.

METHODS: Data on resident mortality, air pollution and meteorology in Shenzhen during 2013⁻2015 were collected and analyzed using semi-parametric generalized additive models (GAM) with Poisson distribution of time series analysis.

RESULTS: Six pollutants were measured at seven air quality monitoring sites, including PM2.5, PM10, SO₂, NO₂, CO and O₃. The PM2.5 daily average concentration was 35.0 ± 21.9 μg/m³; the daily average concentration range was from 7.1 μg/m³ to 137.1 μg/m³. PM2.5 concentration had significant effects on CVD, IHD and EVD mortality. While PM2.5 concentration of lag5 and lag02 rose by 10 μg/m³, the excess risk (ER) of CVD mortality were 1.50% (95% CI: 0.51⁻2.50%) and 2.09% (95% CI: 0.79⁻3.41%), respectively. While PM2.5 concentration of lag2 and lag02 rose by 10 μg/m³, the ER of IHD mortality were 2.87% (95% CI: 0.71⁻5.07%) and 3.86% (95% CI: 1.17⁻6.63%), respectively. While PM2.5 concentration of lag4 and lag04 rose by 10 μg/m³, the ER of EVD mortality were 2.09% (95% CI: 2.28⁻3.92%) and 3.08% (95% CI: 0.68⁻5.53%), respectively.

CONCLUSIONS: PM2.5 increased CVD mortality. The government needs to strengthen the governance of air pollution in areas with a slight pollution.

Abstract  BACKGROUND: Limited evidence is available on the health effects of particulate matter with an aerodynamic diameter of <1 μm (PM1), mainly due to the lack of its ground measurement worldwide.

OBJECTIVES: To identify and examine the mortality risks and mortality burdens associated with PM1, PM2.5, and PM10 in Zhejiang province, China.

METHODS: We collected daily data regarding all-cause (stratified by age and gender), cardiovascular, stroke, respiratory, and chronic obstructive pulmonary disease (COPD) mortality, and PM1, PM2.5, and PM10, from 11 cities in Zhejiang province, China during 2013 and 2017. We used a quasi-Poisson regression model to estimate city-specific associations between mortality and PM concentrations. Then we used a random-effect meta-analysis to pool the provincial estimates. To show the mortality burdens of PM1, PM2.5, and PM10, we calculated the mortality fractions and deaths attributable to these PMs.

RESULTS: Daily concentrations of PM1, PM2.5, and PM10 ranged between 0-199 μg/m3, 0-218 μg/m3, and 0-254 μg/m3, respectively; Mortality effects were significant in lag 0-2 days. The relative risks for all-cause mortality were 1.0064 (95% CI: 1.0034, 1.0094), 1.0061 (95% CI: 1.0034, 1.0089), and 1.0060 (95% CI: 1.0038, 1.0083) associated with a 10 μg/m3 increase in PM1, PM2.5, and PM10, respectively. Age- and gender-stratified analysis shows that elderly people (aged 65+) and females are more sensitive to PMs. The mortality fractions of all-cause mortality were estimated to be 2.39% (95% CI: 1.28, 3.48) attributable to PM1, 2.53% (95% CI: 1.42, 3.63) attributable to PM2.5, and 3.08% (95% CI: 1.95, 4.19) attributable to PM10. The ratios of attributable cause-specific deaths for PM1/PM2.5, PM1/PM10, and PM2.5/PM10 were higher than the ratios of their respective concentrations.

CONCLUSIONS: PM1, PM2.5 and PM10 are risk factors of all-cause, cardiovascular, stroke, respiratory, and COPD mortality. PM1 accounts for the vast majority of short-term PM2.5- and PM10-induced mortality. Our analyses support the notion that smaller size fractions of PM have a more toxic mortality impacts, which suggests to develop strategies to prevent and control PM1 in China, such as to foster strict regulations for automobile and industrial emissions.

Abstract  STUDY QUESTION: Is there an association between air pollution exposures and the risk of spontaneous abortion (SAB)?

SUMMARY ANSWER: Higher exposure to particulate matter (PM) air pollution above and beyond a woman's average exposure may be associated with greater risk of SAB, particularly among women experiencing at least one SAB during follow-up.

WHAT IS KNOWN ALREADY: There is sufficient biologic plausibility to suggest that air pollution adversely affects early pregnancy outcomes, particularly pregnancy loss; however, the evidence is limited.

STUDY DESIGN, SIZE, DURATION: Our prospective cohort study included 19 309 women in the Nurses' Health Study II who contributed a total of 35 025 pregnancies between 1990 and 2008. We also conducted a case-crossover analysis among 3585 women (11 212 pregnancies) with at least one SAB and one live birth during follow-up.

PARTICIPANTS/MATERIALS, SETTING, METHODS: Proximity to major roadways and exposure to PM <10 microns (PM10), 2.5-10 microns (PM2.5-10) and <2.5 microns (PM2.5) were determined for residential addresses between 1989 and 2007. Pregnancy outcomes were self-reported biannually throughout follow-up and comprehensively in 2009. Multivariable log-binomial regression models with generalized estimating equations were used to estimate the risk ratios and 95% CIs of SAB. Conditional logistic regression was used for the case-crossover analysis.

MAIN RESULTS AND THE ROLE OF CHANCE: During the 19 years of follow-up, 6599 SABs (18.8% of pregnancies) were reported. In the main analysis, living closer to a major roadway and average exposure to PM10, PM10-2.5 or PM2.5 in the 1 or 2 years prior to pregnancy were not associated with an increased risk of SAB. However, small positive associations between PM exposures and SAB were observed when restricting the analysis to women experiencing at least one SAB during follow-up. In the case-crossover analysis, an increase in PM10 (per 3.9 μg/m3), PM2.5-10 (per 2.3 μg/m3) and PM2.5 (per 2.0 μg/m3) in the year prior to pregnancy was associated with 1.12 (95% CI 1.06, 1.19), 1.09 (95% CI 1.03, 1.14) and 1.10 (95% CI 1.04, 1.17) higher odds of SAB, respectively.

LIMITATIONS, REASONS FOR CAUTION: We did not have information on the month or day of SAB, which precluded our ability to examine specific windows of susceptibility or acute exposures. We also used ambient air pollution exposures as a proxy for personal exposure, potentially leading to exposure misclassification.

WIDER IMPLICATIONS OF THE FINDINGS: In our case-crossover analysis (but not in the entire cohort) we observed positive associations between exposure to all size fractions of PM exposure and risk of SAB. This may suggest that changes in PM exposure confer greater risk of SAB or that women with a history of SAB are a particularly vulnerable subgroup.

STUDY FUNDING/COMPETING INTEREST(S): The authors are supported by the following NIH grants UM1CA176726, R00ES026648 and P30ES000002. The authors have no actual or potential competing financial interests to disclose.

Abstract  Passive air sampling was conducted in Toronto and the Greater Toronto Area from 2016 to 2017 for 6 periods, in order to investigate ambient levels of polycyclic aromatic compounds (PACs) associated with different source types. The selected sampling sites (n = 8) cover geographical areas with varying source emissions including background, traffic, urban, industrial and residential sites. Passive air samples were analyzed for PACs which include PAHs, alkylated PAHs (alk-PAHs), dibenzothiophene and alkylated dibenzothiophenes (DBTs) and results for PAHs were used to calculate inhalation cancer risks using different approaches. The samples were also characterized for PAH derivatives including nitrated PAHs (NPAHs) and oxygenated PAHs (OPAHs). Concentrations of Σalk-PAHs and DBTs, which are known to be enriched in fossil fuels, as well as ΣNPAHs, were highest at a traffic site (MECP) located adjacent to the 18-lane Highway 401 that runs across Toronto. Except for an industrial site (HH/BU), PAC compositions were similar across the sampling sites with Σalk-PAHs being the most abundant class of PACs suggesting traffic emission was a major contributor to PACs in the atmosphere of Toronto. The industrial site exhibited a distinct chemical composition with ΣPAHs dominating over Σalk-PAHs and with elevated levels of fluoranthene, 9-nitroanthracene, and 9,10-anthraquinone, which likely reflects emissions from nearby industrial sources. MECP and HH/BU exhibited higher lifetime excess inhalation cancer risks indicating an association with traffic and industrial sources. The importance of the traffic sector as a source of PACs to ambient air is further supported by strong correlations of the ΣPAHs, Σalk-PAHs, DBTs, and ΣOPAHs with NOx. This study highlights the importance of traffic as an emission source of PACs to urban air and the relevance of PAC classes other than just unsubstituted PAHs that are important but currently not included in air quality guidelines or for assessing inhalation cancer risks.

Abstract  Numerous experimental and epidemiological studies have demonstrated that exposure to PM2.5 may result in pathogenesis of several major cardiovascular diseases (CVDs), which can be attributed to the combined adverse effects induced by the complicated components of PM2.5. Organic materials, which are major components of PM2.5, contain thousands of chemicals, and most of them are environmental hazards. However, the contamination profile and contribution to overall toxicity of PM2.5-bound organic components (OCs) have not been thoroughly evaluated yet. Herein, we aim to provide an overview of the literature on PM2.5-bound hydrophobic OCs, with an emphasis on the chemical identity and reported impairments on the cardiovascular system, including the potential exposure routes and mechanisms. We first provide an update on the worldwide mass concentration and composition data of PM2.5, and then, review the contamination profile of PM2.5-bound hydrophobic OCs, including constitution, concentration, distribution, formation, source, and identification. In particular, the link between exposure to PM2.5-bound hydrophobic OCs and CVDs and its possible underlying mechanisms are discussed to evaluate the possible risks of PM2.5-bound hydrophobic OCs on the cardiovascular system and to provide suggestions for future studies.

Abstract  PM2.5 (particulate matter with the aerodynamic diameter Dp < 2.5 μm) was hypothesized to generate reactive oxygen species (ROS) and induce oxidative stress associated with inflammation and cardiovascular diseases. In the current study, PM2.5 concentrations, water-soluble ions and elements, carbonaceous components and ROS activity characterized by the dithiothreitol (DTT) assay were determined for the PM2.5 samples collected in Beijing, China, over a whole year. Source apportionments of PM2.5 and DTT activity were also performed. The mean ± standard deviation of PM2.5, DTTm (mass-normalized DTT activity) and DTTv (volume-normalized DTT activity) were 113.8 ± 62.7 μg·m-3, 0.13 ± 0.10 nmol·μg-1·min-1 and 12.26 ± 6.82 nmol·m-3·min-1, respectively. The seasonal averages of DTTm and DTTv exhibited peak values during the local summer. Organic carbon (OC), NO3-, SO42-, NH4+ and elemental carbon (EC) were the dominant components in the constituents tested. Higher concentrations of carbonaceous components occurred in autumn and winter compared with spring and summer. Based on the positive matrix factorization model (PMF), the simulation results of source apportionment for PM2.5 in Beijing, obtained using the annual data, identified the main categories as follows: dust, coal combustion, secondary sulfate and industrial emissions, vehicle emissions and secondary nitrates. Most detected constituents exhibited significantly positive correlations with DTTv (p < 0.01). The results corresponding to multiple linear regression (MLR) between DTTv activity and source contribution to PM2.5 manifested the sensitivity sequence of DTTv activity for the resolved sources as vehicle emissions > secondary sulfate and industrial emissions > coal combustion > dust.

CAPSULE: Based on a descending sequence of relative contribution, the diagnostic sources of DTTv activity in PM2.5 from Beijing included primarily vehicle emissions, secondary sulfates and industrial emissions, coal combustion, and dust.

Abstract  PURPOSE OF REVIEW: A number of studies over the past two decades have suggested that type 2 diabetes mellitus (T2DM) patients are at an increased risk of Alzheimer's disease (AD). Several common molecular pathways to cellular and metabolic dysfunction have been implicated in the etiology of both diseases. Here, we review the emerging evidence from observational studies that investigate the relationship between T2DM and AD, and of shared environmental risk factors, specifically air pollution and pesticides, associated with both chronic disorders.

RECENT FINDINGS: Particulate matter and traffic-related air pollution have been widely associated with T2DM, and multiple studies have associated exposures with AD or cognitive function. Organochlorine (OC) and organophosphate (OP) pesticides have been associated with T2DM in multiple independent populations. Two populations have observed increased risks for OC and OP exposures and AD. Other studies, limited in exposure assessment, have reported increased risk of AD with any pesticide exposure assessments. This may suggest shared pathogenic pathways between environmental risk factors, T2DM, and AD. Research focusing on exposures related to both T2DM and AD could provide new disease insights on shared mechanisms and help shape innovative preventative measures and policy decisions.

Abstract  Pollution caused by volatile organic compounds (VOCs) and odorous pollutants in the air can produce severe environmental problems. In recent years, the emission control of VOCs and odorous pollutants has become a crucial issue owing to the adverse effect on humans and the environment. For treating these compounds, biotrickling filter (BTF) technology acts as an environment friendly and cost-effective alternative to conventional air pollution control technologies. Besides, low concentration of VOCs and odorous pollutants can also be effectively removed using BTF systems. However, the VOCs and odorants removal performance by BTF may be limited by the hydrophobicity, toxicity, and low bioavailability of these pollutants. To solve these problems, this review summarizes the design, mechanism, and common analytical methods of recent BTF advances. In addition, the operating conditions, mass transfer, packing materials and microorganisms (which are the critical parameters in a BTF system) were evaluated and discussed in view of improving the removal performance of BTFs. Further research on these specific topics, together with the combination of BTF technology with other technologies, should improve the removal performance of BTFs.

Abstract  Indoor air pollution with toxic volatile organic compounds (VOCs) and fine particulate matter (PM2.5) is a threat to human health, causing cancer, leukemia, fetal malformation, and abortion. Therefore, the development of technologies to mitigate indoor air pollution is important to avoid adverse effects. Adsorption and photocatalytic oxidation are the current approaches for the removal of VOCs and PM2.5 with high efficiency. In this review we focus on the recent development of indoor air pollution mitigation materials based on adsorption and photocatalytic decomposition. First, we review on the primary indoor air pollutants including formaldehyde, benzene compounds, PM2.5, flame retardants, and plasticizer: Next, the recent advances in the use of adsorption materials including traditional biochar and MOF (metal-organic frameworks) as the new emerging porous materials for VOCs absorption is reviewed. We review the mechanism for mitigation of VOCs using biochar (noncarbonized organic matter partition and adsorption) and MOF together with parameters that affect indoor air pollution removal efficiency based on current mitigation approaches including the mitigation of VOCs using photocatalytic oxidation. Finally, we bring forward perspectives and directions for the development of indoor air mitigation technologies.

Abstract  The COVID-19/SARS-CoV-2 pandemic struck health, social and economic systems worldwide, and represents an open challenge for scientists -coping with the high inter-individual variability of COVID-19, and for policy makers -coping with the responsibility to understand environmental factors affecting its severity across different geographical areas. Air pollution has been warned of as a modifiable factor contributing to differential SARS-CoV-2 spread but the biological mechanisms underlying the phenomenon are still unknown. Air quality and COVID-19 epidemiological data from 110 Italian provinces were studied by correlation analysis, to evaluate the association between particulate matter (PM)2.5 concentrations and incidence, mortality rate and case fatality risk of COVID-19 in the period 20 February-31 March 2020. Bioinformatic analysis of the DNA sequence encoding the SARS-CoV-2 cell receptor angiotensin-converting enzyme 2 (ACE-2) was performed to identify consensus motifs for transcription factors mediating cellular response to pollutant insult. Positive correlations between PM2.5 levels and the incidence (r = 0.67, p < 0.0001), the mortality rate (r = 0.65, p < 0.0001) and the case fatality rate (r = 0.7, p < 0.0001) of COVID-19 were found. The bioinformatic analysis of the ACE-2 gene identified nine putative consensus motifs for the aryl hydrocarbon receptor (AHR). Our results confirm the supposed link between air pollution and the rate and outcome of SARS-CoV-2 infection and support the hypothesis that pollution-induced over-expression of ACE-2 on human airways may favor SARS-CoV-2 infectivity.

Abstract  Background: Fine particulate matter (PM2.5) has been widely associated with airway inflammation represented by increased fractional concentration of exhaled nitric oxide (FeNO). However, it remains unclear whether various PM2.5 constituents have different impacts on FeNO and its production process from the arginase (ARG)-nitric oxide synthase (NOS) pathway.Objectives: To investigate the acute effects of PM2.5 constituents on FeNO and DNA methylation of genes involved.Methods: We conducted a longitudinal panel study among 43 young adults in Shanghai, China from May to October in 2016. We monitored the concentrations of 25 constituents of PM2.5. We applied the linear mixe-deffect model to evaluate the associations of PM2.5 constituents with FeNO and DNA methylation of the ARG2 and NOS2A genes.Results: Following PM2.5 exposure, NOS2A methylation decreased and ARG2 methylation increased only on the concurrent day, whereas FeNO increased most prominently on the second day. Nine constituents (OC, EC, K, Fe, Zn, Ba, Cr, Se, and Pb) showed consistent associations with elevated FeNO and decreased NOS2A methylation or increased ARG2 methylation in single-constituent models and models adjusting for PM2.5 total mass and collinearity. An interquartile range increase of these constituents was associated with respective decrements of 0.27-1.20 in NOS2A methylation (%5mC); increments of 0.48-1.56 in ARG2 methylation (%5mC); and increments of 7.12%-17.54% in FeNO.Conclusions: Our results suggested that OC, EC, and some metallic elements may be mainly responsible for the development and epigenetic regulation of airway inflammatory response induced by short-term PM2.5 exposure.

Abstract  Global burden of disease estimates reveal that people in Nigeria are living shorter lifespan than the regional or global average life expectancy. Ambient air pollution is a top risk factor responsible for the reduced longevity. But, the magnitude of the loss or the gains in longevity accruing from the pollution reductions, which are capable of driving mitigation interventions in Nigeria, remain unknown. Thus, we estimate the loss, and the gains in longevity resulting from ambient PM2.5 pollution reductions at the local sub-national level using life table approach. Surface average PM2.5 concentration datasets covering Nigeria with spatial resolution of ∼1 km were obtained from the global gridded concentration fields, and combined with ∼1 km gridded population of the world (GPWv4), and global administrative unit layers (GAUL) for territorial boundaries classification. We estimate the loss or gains in longevity using population-weighted average pollution level and baseline mortality data for cardiopulmonary disease and lung cancer in adults ≥25 years and for respiratory infection in children under 5. As at 2015, there are six "highly polluted", thirty "polluted" and one "moderately polluted" States in Nigeria. People residing in these States lose ∼3.8-4.0, 3.0-3.6 and 2.7 years of life expectancy, respectively, due to the pollution exposure. But, assuming interventions achieve global air quality guideline of 10 μg/m3, longevity would increase by 2.6-2.9, 1.9-2.5 and 1.6 years for people in the State-categories, respectively. The longevity gains are indeed high, but to achieve them, mitigation interventions should target emission sources having the highest population exposures.

Abstract  Exposure to fine particulate matter (PM2.5) could induce lung impairment aggravation. Moreover, endogenous substances are known to play a significant role in lung impairment. Therefore, the research objectives was to investigate the influence of PM2.5-induced lung impairment on the levels of the eight endogenous substances, γ-aminobutyric acid (GABA), acetylcholine (ACh), glutamate (Glu), serotonin (5-HT), 5-hydroxyindole-3-acetic acid (5-HIAA), noradrenaline (NE), dopamine (DA), and 3, 4-dihydroxyphenylacetic acid (DOPAC). A sensitive UPLC-MS/MS method for the simultaneous determination of these endogenous substances in rat plasma and lung tissues was developed. The validated method was successfully applied for comparing profiles of analytes in rat plasma and lung tissues. The results indicated that five endogenous substances, namely, GABA, Ach, Glu, DA, and DOPAC, had a significant change in the rats with PM2.5-induced lung impairment.

Abstract  In biological fluids, micro- or nano-size particles are prone to adsorb proteins and form a layer. The ambient air fine particulate matter (PM2.5) is inhaled via the lung, penetrates biological barriers and eventually reaches systemic blood circulation. However, there are very few data available regarding the adsorption of proteins on PM2.5. Here, we compared protein corona formed in plasma after bronchoalveolar lavage fluid (BALF) exposure with those formed in plasma alone. Using purified coronal proteins, we explored their adsorption behaviors on PM2.5 and their influence on biological reactivity of PM2.5. Liquid-chromatography tandem mass-spectrometry (LC-MS/MS) analysis revealed that exposure to BALF significantly changed the blood protein profile on PM2.5. Regardless of the presence of BALF, the protein corona on PM2.5 contained an abundance of serum albumin, hemoglobin (Hb) and fibrinogen (Fg) proteins. Using Fg as a corona surrogate, we found that van der Waals interactions, hydrophobic interactions, π-π stacking and electrostatic attractions contributed to the Fg adsorption and led to the conformational changes of Fg. In addition, Fg decoration decreased cellular internalization of PM2.5 and corresponding subsequent oxidative stress responses in a murine RAW264.7 macrophage. These results support the view that the formation of PM2.5 corona should be considered for toxicity assessment of PM2.5.

Abstract  INTRODUCTION: Air pollution is increasingly becoming a serious global public health concern. Prior studies examining the effect of air pollution on health have ignored the role of households' hygienic practices and socioeconomic condition, which are key determinants of the health status of a country like India. This study examines the effects of air pollution, measured in levels of particulate matters of size below 10 µg/m3 (PM10), on child-health outcomes after adjusting for hygiene practices.

METHODS: Health data from the National Family Health Survey-4 (NFHS-4) and PM10 levels provided by the Central Pollution Control Board were matched for 184 Indian towns/cities. Child health outcomes included neonatal mortality, post-neonatal mortality, premature births, children with symptoms of acute respiratory infections (ARI) and low birth weight. Multilevel mixed-effects models were used to estimate the risk associated with exposure to PM10.

RESULT: Analyses based on 23 954 births found that every 10-unit increase in PM10 level, increased the risk of neonatal mortality by 6% (adjusted RR (95% CI): 1.02 (1.02 to 1.09)), and the odds of symptoms of ARI among children by 7% (adjusted OR (95% CI): 1.07 (1.03 to 1.12)), and premature births by 8% (adjusted OR (95% CI): 1.08 (1.03 to 1.12)). There was no statistically significant difference in the effect of PM10 on child health regardless of household's hygienic practices. Effects of PM10 on child health outcomes remained similar for cities whether or not they were part of the National Clean Air Program (NCAP).

CONCLUSION: Exposure to PM10, regardless of hygienic practices, increases the risk of adverse child health outcomes. Study findings suggest that the focus of mitigating the effects of air pollution should be beyond the towns/cities identified under NCAP. Given the increasing industrialisation and urbanisation, a systemic, coherent approach is required to address the issue of air pollution in India.

Abstract  As power production from renewable energy and natural gas grows, closures of some coal-fired power plants in Texas become increasingly likely. In this study, the potential effects of such closures on air quality and human health were analyzed by linking a regional photochemical model with a health impacts assessment tool. The impacts varied significantly across 13 of the state's largest coal-fired power plants, sometimes by more than an order of magnitude, even after normalizing by generation. While some power plants had negligible impacts on concentrations at important monitors, average impacts up to 0.5 parts per billion (ppb) and 0.2 µg/m3 and maximum impacts up to 3.3 ppb and 0.9 µg/m3 were seen for ozone and fine particulate matter (PM2.5), respectively. Individual power plants impacted average visibility by up to 0.25 deciviews in Class I Areas. Health impacts arose mostly from PM2.5 and were an order of magnitude higher for plants that lack scrubbers for SO2. Rankings of health impacts were largely consistent across the base model results and two reduced form models. Carbon dioxide emissions were relatively uniform, ranging from 1.00 to 1.26 short tons/MWh, and can be monetized based on a social cost of carbon. Despite all of these unpaid externalities, estimated direct costs of each power plant exceeded wholesale power prices in 2016. Implications: While their CO2 emission rates are fairly similar, sharply different NOx and SO2 emission rates and spatial factors cause coal-fired power plants to vary by an order of magnitude in their impacts on ozone, particulate matter, and associated health and visibility outcomes. On a monetized basis, the air pollution health impacts often exceed the value of the electricity generated and are of similar magnitude to climate impacts. This suggests that both air pollution and climate should be considered if externalities are used to inform decision making about power-plant dispatch and retirement.

Abstract  American Indian women are more likely to die from cardiovascular disease (CVD) than White or African American women. Inflammatory processes may underlie CVD disparities by gender and race and may be critical to understanding population-specific drivers and potential buffers. Exposure to environmental air pollutants, especially particulate matter (PM), is known to be an important catalyst in CVD-associated inflammation. Positive psychological states, associated with low levels of inflammatory gene expression, could serve to moderate the inflammatory response to environmental air pollutants and ultimately lead to better cardiovascular health outcomes. The aim of the ongoing community-engaged and NIH-funded study described in this study protocol is to address the racial and gender gaps in CVD mortality by investigating the contextually relevant and culturally important determinants of health among American Indian women. In this paper we describe the procedures used to examine the relationship between environmental air pollutant exposures (PM10-2.5 and PM 2.5 ), psychological factors (e.g., depressive symptoms, posttraumatic stress symptoms, eudemonic well-being, and positive emotions), and cardiovascular-associated inflammation (hs-CRP, IL-6, Amyloid A, CBCs with differentials) in a sample of 150 women 18-50 years of age from the Lumbee Tribe in southeastern North Carolina. We describe lessons learned and strategies used in developing a community-engaged approach to enhance recruitment of American Indian women in biomedical research. The empirical data and community infrastructure resulting from this study will be foundational in designing and testing future interventions to reduce CVD-associated morbidity and mortality in American Indian women.

Abstract  Recent technological advances in both air sensing technology and Internet of Things (IoT) connectivity have enabled the development and deployment of remote monitoring networks of air quality sensors. The compact size and low power requirements of both sensors and IoT data loggers allow for the development of remote sensing nodes with power and connectivity versatility. With these technological advancements, sensor networks can be developed and deployed for various ambient air monitoring applications. This paper describes the development and deployment of a monitoring network of accurate ozone (O3) sensor nodes to provide parallel monitoring in an air monitoring site relocation study. The reference O3 analyzer at the station along with a network of three O3 sensing nodes was used to evaluate the spatial and temporal variability of O3 across four Southern California communities in the San Bernardino Mountains which are currently represented by a single reference station in Crestline, CA. The motivation for developing and deploying the sensor network in the region was that the single reference station potentially needed to be relocated due to uncertainty that the lease agreement would be renewed. With the implication of siting a new reference station that is also a high O3 site, the project required the development of an accurate and precise sensing node for establishing a parallel monitoring network at potential relocation sites. The deployment methodology included a pre-deployment co-location calibration to the reference analyzer at the air monitoring station with post-deployment co-location results indicating a mean absolute error (MAE) < 2 ppb for 1-h mean O3 concentrations. Ordinary least squares regression statistics between reference and sensor nodes during post-deployment co-location testing indicate that the nodes are accurate and highly correlated to reference instrumentation with R2 values > 0.98, slope offsets < 0.02, and intercept offsets < 0.6 for hourly O3 concentrations with a mean concentration value of 39.7 ± 16.5 ppb and a maximum 1-h value of 94 ppb. Spatial variability for diurnal O3 trends was found between locations within 5 km of each other with spatial variability between sites more pronounced during nighttime hours. The parallel monitoring was successful in providing the data to develop a relocation strategy with only one relocation site providing a 95% confidence that concentrations would be higher there than at the current site.

Abstract  Road traffic pollution is one of the key factors affecting urban air quality. There is a consensus in the community that the efficient use of public transport is the most effective solution. In that sense, much effort has been made in the data mining discipline to come up with solutions able to anticipate taxi demands in a city. This helps to optimize the trips made by such an important urban means of transport. However, most of the existing solutions in the literature define the taxi demand prediction as a regression problem based on historical taxi records. This causes serious limitations with respect to the required data to operate and the interpretability of the prediction outcome. In this paper, we introduce QUADRIVEN (QUalitative tAxi Demand pRediction based on tIme-Variant onlinE social Network data analysis), a novel approach to deal with the taxi demand prediction problem based on human-generated data widely available on online social networks. The result of the prediction is defined on the basis of categorical labels that allow obtaining a semantically-enriched output. Finally, this proposal was tested with different models in a large urban area, showing quite promising results with an F1 score above 0.8.

Abstract  BACKGROUND: The association between long-term exposure to ambient fine particulate matter with aerodynamic diameter () and lung function in young people remains uncertain, particularly in Asia, where air pollution is generally a serious problem.

OBJECTIVES: This study investigated the association between long-term exposure to ambient and lung function in Taiwanese children, adolescents, and young adults.

METHODS: This study comprised 24,544 participants 6-24 years of age, with 33,506 medical observations made between 2000 and 2014. We used a spatiotemporal model to estimate concentrations at participants' addresses. Spirometry parameters, i.e., forced vital capacity (FVC), forced expiratory volume in 1 s (), and maximum midexpiratory flow (MMEF), were determined. A generalized linear mixed model was used to examine the associations between long-term exposure to ambient and lung function. The odds ratios (ORs) of poor lung function were also calculated after adjusting for a range of covariates.

RESULTS: Every increase in the 2-y average concentration was associated with decreases of 2.22% [95% confidence interval (CI): , ], 2.94 (95% CI: , ), and 2.79% (95% CI: , ) in the FVC, , and MMEF, respectively. Furthermore, it was associated with a 20% increase in the prevalence of poor lung function (OR: 1.20; 95% CI: 1.12, 1.29).

CONCLUSIONS: Two-year ambient concentrations were inversely associated with lung function and positively associated with the prevalence of poor lung function in children, adolescents, and young adults in Taiwan. https://doi.org/10.1289/EHP5220.