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There is growing global concern regarding the detrimental health impacts of PM2.5 emissions from traditional stoves that utilize polluting fuels. Conventional methods for estimating daily personal PM2.5 exposure involve personal air samplers and measuring devices placed in a waist pouch, but these instruments are cumbersome and inconvenient. To address this issue, we developed a novel neck-mounted PM2.5 monitoring device (Pocket PM2.5 Logger) that is compact, lightweight, and can operate continuously for 1 week without recharging. Twelve participants who utilized charcoal, firewood, or propane gas for cooking in rural regions of Rwanda wore the Pocket PM2.5 Logger continuously for 1 week, and time-series variations in personal PM2.5 exposure were recorded at 5-min intervals. Individual daily exposure concentrations during cooking differed significantly among users of the different fuel types, and PM2.5 exposure was at least 2.6 and 3.4 times higher for charcoal and firewood users, respectively, than for propane gas users. Therefore, switching from biomass fuels to propane gas would reduce daily individual exposure by at least one-third. An analysis of cooking times showed that the median cooking time per meal was 30 min; however, half the participants cooked for 1.5 h per meal, and one-third cooked for over 4.5 h per meal. Reducing these extremely long cooking times would reduce exposure with all fuel types. The Pocket PM2.5 Logger facilitates the comprehensive assessment of personal PM2.5 exposure dynamics and is beneficial for the development of intervention strategies targeting household air pollution.

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Outdoor jogging is one of the most popular practised exercises worldwide, providing various benefits for health and wellbeing. However, PM2.5 exposure risks of jogging behaviors were rarely explored. This study aims to investigate the association between jogging behavior and PM2.5 exposure with big data. PM2.5 exposure concentration and dose inhalation of individuals were calculated by integrating hourly PM2.5 concentration data and jogging GPS trajectory recorded by a sports app during 2015 in Beijing, after which relationships between jogging behaviors and PM2.5 exposure were unpacked using statistics analysis and structural equation modelling. Experimental results on massive jogging trajectories show that: (1) the average jogging PM2.5 exposure concentration is 60.43 µg/m3, and female joggers inhaled significantly less air pollution dose (19.70 µg) than men (24.91 µg). (2) There exist significant spatiotemporal disparities in jogging exposure to PM2.5. Joggings in the city center, in the morning, on weekdays and in autumn and winter seasons were exposed to higher pollution concentrations. (3) Jogging behavior characteristics, especially distance, activity space size, duration and rotation, were systematically associated with PM2.5 exposure across space and time. (4) The role of gender directly shaped joggers' dose inhalation of PM2.5 pollution and indirectly via duration, timing choice and distance. (5) The effects of weather conditions on joggers' exposure to PM2.5 are mainly via direct effects, whereas the direct impacts of precipitation and wind speed are mitigated by indirect effects stemming from jogging behavior patterns. Our findings provide insights for personal guidance and policy intervention for the sake of promoting physical activity and reducing PM2.5 exposure.

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Particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) is a major environmental risk factor for acute asthma exacerbation, and the underlying mechanism is not completely understood. Studies have indicated that DNA methylation is a potential mechanism linking PM2.5 to its health effects. We conducted a panel study involving 24 adult patients with asthma in Beijing,China between 2017 and 2019. PM2.5 and other atmospheric pollutant exposure data were repeatedly measured. Blood samples were collected for genome-wide DNA methylation analysis. A linear mixed-effects (LME) model was conducted to identify differentially methylated probes (DMPs) associated with PM2.5 exposure. After filtering out probes that did not meet the criteria through quality control, 811,001 CpG sites were included in the LME model, and 36 DMPs were strongly associated with personal PM2.5 exposure at false discovery rate (FDR) < 0.05, of which 22 and 14 DMPs negatively and positively correlated with personal PM2.5 exposure, respectively. Functional analysis revealed that DMPs affected smooth muscle cell contraction and development, extracellular matrix synthesis and secretion, T cell activation and differentiation, and inflammatory factor production. This study provides evidence linking personal PM2.5 exposure to genome-wide DNA methylation in adult patients with asthma. Identifying enrichment pathways can provide biological insights into the acute health effects of PM2.5.

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The increasing frequency and severity of wildfires due to climate change pose health risks to migrant farm workers laboring in wildfire-prone regions. This study focuses on Sonoma County, California, investigating the effectiveness of air monitoring and safety protections for farmworkers. The analysis employs AirNow and PurpleAir PM2.5 data acquired during the 2020 wildfire season, comparing spatial variability in air pollution. Results show significant differences between the single Sonoma County AirNow station data and the PurpleAir data in the regions directly impacted by wildfire smoke. Three distinct wildfire pollution episodes with elevated PM2.5 levels are identified to examine the regional variations. This study also examines the system used to exempt farmworkers from wildfire mandatory evacuation orders, finding incomplete information, ad hoc decision-making, and scant enforcement. In response, we make policy recommendations that include stricter requirements for employers, real-time air quality monitoring, post-exposure health screenings, and hazard pay. Our findings underscore the need for significant consideration of localized air quality readings and the importance of equitable disaster policies for protecting the health of farmworkers (particularly those who are undocumented migrants) in the face of escalating wildfire risks.

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As a global problem, fine particulate matter (PM2.5) really needs local fixes. Considering the increasing epidemiological relevance to anxiety and depression but inconsistent toxicological results, the most important question is to clarify whether and how PM2.5 causally contributes to these mental disorders and which components are the most dangerous for crucial mitigation in a particular place. In the present study, we chronically subjected male mice to a real-world PM2.5 exposure system throughout the winter heating period in a coal combustion area and revealed that PM2.5 caused anxiety and depression-like behaviors in adults such as restricted activity, diminished exploratory interest, enhanced repetitive stereotypy, and elevated acquired immobility, through behavioral tests including open field, elevated plus maze, marble-burying, and forced swimming tests. Importantly, we found that dopamine signaling was perturbed using mRNA transcriptional profile and bioinformatics analysis, with Drd1 as a potential target. Subsequently, we developed the Drd1 expression-directed multifraction isolating and nontarget identifying framework and identified a total of 209 compounds in PM2.5 organic extracts capable of reducing Drd1 expression. Furthermore, by applying hierarchical characteristic fragment analysis and molecular docking and dynamics simulation, we clarified that phenyl-containing compounds competitively bound to DRD1 and interfered with dopamine signaling, thereby contributing to mental disorders. Taken together, this work provides experimental evidence for researchers and clinicians to identify hazardous factors in PM2.5 and prevent adverse health outcomes and for local governments and municipalities to control source emissions for diminishing specific disease burdens.

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BACKGROUND: Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability. METHODS: This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers' exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers' activities. RESULTS: The taxi drivers' weekday and weekend 24-h PM2.5 exposure was 83.60 µg/m3 and 55.62 µg/m3 respectively, 3.4 and 2.2 times than the WHO's recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the "Inner Ring Road", while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the "Third Ring Road". CONCLUSION: These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.

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While numerous studies have associated maternal exposure to PM2.5 with adverse birth outcomes, findings remain inconsistent and difficult to generalize. We aimed to investigate the causal relationship and window of sensitivity between gestational exposure to PM2.5 and birth outcomes. We leveraged high-resolution satellite data to quantify gestational PM2.5 exposure at the individual level, along with a combined model to determine daily relative risks (RRs) of birth outcomes in COVID-19 prelockdown and lockdown groups. RRs between the two groups were further compared using a longitudinal pre-post non-experimental design to identify sensitivity windows of adverse birth outcomes. A total of 73,781 pregnant women from the COVID-19 prelockdown group and 6267 pregnant women from the lockdown group were included for analysis. The daily mean PM2.5 concentrations in the lockdown group decreased by 21.7% compared to the prelockdown group. During the first trimester, every 10 µg/m3 increase in PM2.5 significantly increased the risk of congenital abnormalities of major organs such as the cardiovascular system, gastrointestinal tract, nervous system, urinary system, and respiratory system. Moreover, gestational exposure to PM2.5 during the first trimester was associated with higher risks of premature delivery and term low birth weight. While PM2.5 exposure during the second trimester was positively correlated with macrosomia. Gestational exposure to PM2.5 is associated with increased risks of various adverse birth outcomes with specific sensitive windows. We demonstrated that gestational exposure to PM2.5 increased risks of various adverse birth outcomes with specific window of sensitivity through the natural experiment design. Our findings underscore the urgent need for policies and initiatives targeting PM2.5 reduction, especially during critical periods of pregnancy.

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Short-term exposure to fine particulate matter (PM2.5) is associated with the activation of adverse inflammatory responses, increasing the risk of developing acute respiratory diseases, such as those caused by pathogen infections. However, the functional mechanisms underlying this evidence remain unclear. In the present study, we generated a zebrafish model of short-term exposure to a specific PM2.5, collected in the northern metropolitan area of Milan, Italy. First, we assessed the immunomodulatory effects of short-term PM2.5 exposure and observed that it elicited pro-inflammatory effects by inducing the expression of cytokines and triggering hyper-activation of both neutrophil and macrophage cell populations. Moreover, we examined the impact of a secondary infectious pro-inflammatory stimulus induced through the injection of Pseudomonas aeruginosa lipopolysaccharide (Pa-LPS) molecules after exposure to short-term PM2.5. In this model, we demonstrated that the innate immune response was less responsive to a second pro-inflammatory infectious stimulus. Indeed, larvae exhibited dampened leukocyte activation and impaired production of reactive oxygen species. The obtained results indicate that short-term PM2.5 exposure alters the immune microenvironment and affects the inflammatory processes, thus potentially weakening the resistance to pathogen infections.

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Secular trends of mortality and disability-adjusted life years (DALY) in type 2 diabetes mellitus (T2DM) attributable to PM2.5 exposure in China remain unclear. This study applied the joinpoint regression analysis and age-period-cohort model to assess the secular trends. There was a slight alternation in age-standardized rate of mortality and DALY in the total population, while the changes were increased in males and decreased in females from 1990 to 2019. Meanwhile, the changes attributable to ambient particular matter pollution exposure (APE) increased significantly and reduced household air pollution from solid fuels exposure (HPE). Longitudinal age curves showed that T2DM mortality and DALY increased with age. Period rate ratios (RR) attributable to APE increased but fell to HPE. Similar trends were observed in the cohort RR. PM2.5 exposure is more harmful to males and older people. The type of air pollution responsible for T2DM has changed from HPE to APE.

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Fine particulate matter (PM2.5), a detrimental urban air pollutant primarily emitted by traffic and biomass burning, poses disproportionately significant health risks at relatively limited exposure during commuting. Previous studies have mainly focused on fixed locations when assessing PM2.5 exposure, while neglecting pedestrians and cyclists, who often experience higher pollution levels. In response, this research aimed to independently validate the effectiveness of bicycle-mounted low-cost sensors (LCS) adopted by citizens, evaluate temporal and spatial PM2.5 exposure, and assess associated health risks in Ljubljana, Slovenia. The LCS quality assurance results, verified by co-location field tests by air quality monitoring stations (AQMS), showed comparable outcomes with an average percentage difference of 21.29 %, attributed to humidity-induced nucleation effects. The colder months exhibited the highest air pollution levels (µ = 32.31 µg/m3) due to frequent thermal inversions and weak wind circulation, hindering vertical air mixing and the adequate dispersion of pollutants. Additionally, PM2.5 levels in all sampling periods were lowest in the afternoon (µ = 12.09 µg/m3) and highest during the night (µ = 61.00 µg/m3) when the planetary boundary layer thins, leading to the trapping of pollutants near the surface, thus significantly affecting diurnal and seasonal patterns. Analysis of exposure factors revealed that cyclists were approximately three times more exposed than pedestrians. However, the toxicological risk assessment indicated a minimal potential risk of PM2.5 exposure. The collaborative integration of data from official AQMS and LCS can enhance evidence-based policy-making processes and facilitates the realignment of effective regulatory frameworks to reduce urban air pollution.

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Determining the most feasible and cost-effective approaches to improving PM2.5 exposure assessment with low-cost monitors (LCMs) can considerably enhance the quality of its epidemiological inferences. We investigated features of fixed-site LCM designs that most impact PM2.5 exposure estimates to be used in long-term epidemiological inference for the Adult Changes in Thought Air Pollution (ACT-AP) study. We used ACT-AP collected and calibrated LCM PM2.5 measurements at the two-week level from April 2017 to September 2020 (N of monitors [measurements] = 82 [502]). We also acquired reference-grade PM2.5 measurements from January 2010 to September 2020 (N = 78 [6186]). We used a spatiotemporal modeling approach to predict PM2.5 exposures with either all LCM measurements or varying subsets with reduced temporal or spatial coverage. We evaluated the models based on a combination of cross-validation and external validation at locations of LCMs included in the models (N = 82), and also based on an independent external validation with a set of LCMs not used for the modeling (N = 30). We found that the model's performance declined substantially when LCM measurements were entirely excluded (spatiotemporal validation R2 [RMSE] = 0.69 [1.2 µg/m3]) compared to the model with all LCM measurements (0.84 [0.9 µg/m3]). Temporally, using the farthest apart measurements (i.e., the first and last) from each LCM resulted in the closest model's performance (0.79 [1.0 µg/m3]) to the model with all LCM data. The models with only the first or last measurement had decreased performance (0.77 [1.1 µg/m3]). Spatially, the model's performance decreased linearly to 0.74 (1.1 µg/m3) when only 10% of LCMs were included. Our analysis also showed that LCMs located in densely populated, road-proximate areas improved the model more than those placed in moderately populated, road-distant areas.

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Air pollution perception biases hinder the public's awareness of actual air quality. Past studies that examined the association and mismatch between actual and perceived air quality neglected individuals' dynamic exposure and their activity, travel, spatial, temporal, and social contexts. Using data collected with real-time air pollutant sensors and ecological momentary assessment (EMA), this study investigated the association and mismatch between momentary air pollution exposure and perceived air quality. It also examined how activity type, travel mode, spatial and temporal contexts, and social factors contribute to this disparity. The results show that exposure to air pollution is significantly higher in residential areas (1.777 µg/m3) and transportation land-use areas (2.863 µg/m3) compared to commercial areas. Exposure in the evening is 1.308 µg/m3 higher than in the afternoon. Working or studying activities are associated with 2.863 µg/m3 lower exposure, and individuals perceive air quality as good when working or studying and in residential areas. Conversely, individuals assess air quality as poor in railway travel contexts and being accompanied by friends. This study also reveals the nonstationary association between air pollution exposure and perceived air quality. The odds of underestimating air pollution are 1.8-2.7 times as high as that in residential areas and 2.1 to 2.6 times that in transportation land-use areas when compared to commercial areas. Implementing targeted mitigation measures in these contexts can enhance public awareness of air pollution.

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Background Air pollution has been recognized as an untraditional risk factor for myocardial infarction (MI). However, the MI risk attributable to long-term exposure to fine particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) is unclear, especially in younger populations, and few studies have represented the general population or had power to examine comorbidities. Methods and Results We applied the difference-in-differences approach to estimate the relationship between annual PM2.5 exposure and hospitalizations for MI among US residents and further identified potential susceptible subpopulations. All hospital admissions for MI in 10 US states over the period 2002 to 2016 were obtained from the Healthcare Cost and Utilization Project State Inpatient Database. In total, 1 914 684 MI hospital admissions from 8106 zip codes were included in this study. We observed a 1.35% (95% CI, 1.11-1.59) increase in MI hospitalization rate for 1-µg/m3 increase in annual PM2.5 exposure. The estimate was robust to adjustment for surface pressure, relative humidity, and copollutants. In the population exposed to ≤12 µg/m3, there was a larger increment of 2.17% (95% CI, 1.79-2.56) in hospitalization rate associated with 1-µg/m3 increase in PM2.5. Young people (0-34 years of age) and elderly people (≥75 years of age) were the 2 most susceptible age groups. Residents living in more densely populated or poorer areas and individuals with comorbidities were observed to be at a greater risk. Conclusions This study indicates long-term residential exposure to PM2.5 could increase risk of MI among the general US population, people with comorbidities, and poorer individuals. The association persists below current standards.

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Children are disproportionately represented among those who suffer asthma, which is a kind of chronic airway inflammation. Asthma symptoms might worsen when exposed to the air pollutant particulate matter 2.5 (PM2.5). However, it is becoming more prevalent among older adults, with more asthma-related deaths occurring in this pollution than in any other age group, and symptoms caused by asthma can reduce the quality of life of the elderly, whose asthma is underdiagnosed due to physiological factors. Therefore, in an effort to discover a therapy for older asthma during exposure to air pollution, we sought to ascertain the effects of pre-exposure (PA) and persistent exposure (PAP) to PM2.5 in aged asthma rats. In this study, we exposed aged rats to PM2.5 at different times (PA and PAP) and established an ovalbumin-mediated allergic asthma model. The basic process of elderly asthma caused by PM2.5 exposure was investigated by lung function detection, enzyme-linked immunosorbent assay (ELISA), histopathology, cytology, cytokine microarray, untargeted metabolomics, and gut microbiota analysis. Our findings demonstrated that in the PA and PAP groups, exposure to PM2.5 reduced lung function and exacerbated lung tissue damage, with varying degrees of effect on immunoglobulin levels, the findings of a cytological analysis, cytokines, and chemokines. The PA and PAP rats had higher amounts of polycyclic aromatic hydrocarbons (PAHs), such as naphthalene, 2-methylNaphthalene, 1-methylNaphthalene and flourene. Moreover, exposure to PM2.5 at different times showed different effects on plasma metabolism and gut microbiota. Bioinformatics analysis showed a strong correlation between PAHs, cytokines, and gut microbiota, and PAHs may cause metabolic disorders through the gut microbiota. These findings point to a possible mechanism for the development of asthma in older people exposure to PM2.5 that may be related to past interactions between PAHs, cytokines, gut microbiota, and plasma metabolites.

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Numerous epidemiological studies have shown that PM2.5 exposure in early life can influence brain development and increase the risk of neurodevelopmental disorders in boys, but the underlying molecular mechanisms remain unclear. In the current study, pregnant C57BL/6 J mice were oropharyngeally administered with PM2.5 suspension (3mg/kg/2 days) until the birth of offspring. Based on mRNA expression profiles, two-way analysis of variance (two-way ANOVA) and weighted gene co-expression network analysis (WGCNA) were conducted to explore the most impacted neurodevelopmental processes in male offspring and the most significantly associated gene modules. Gene Ontology (GO) enrichment and Encyclopedia of Genes and Genomes (KEGG) pathway analyses suggested that prenatal PM2.5 exposure significantly altered several biological processes (such as substrate adhesion-dependent cell spreading, myelination, and ensheathment of neurons) and KEGG pathways (such as tight junction and axon guidance). We further found that PM2.5 exposure significantly changed the expression of myelination-related genes in male offspring during postnatal development and impaired myelin ultrastructure on PNDs 14 and 21, as demonstrated by the decreased thickness of myelin sheaths in the optic nerves, and mild loss of myelin in the corpus callosum. Importantly, lncRNA NONMMUT058932.2 and NONMMUT029203.2 played key roles in abnormal myelination by regulating the expression of several myelination-related genes (Fa2h, Mal, Sh3tc2, Trf and Tppp) through the binding to transcription factor Ctcf. Our work provides genomic evidence for prenatal PM2.5 exposure-induced neurodevelopmental disorders in male offspring.

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Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

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High blood pressure associated with PM2.5 exposure is of great concern, especially for rural residents exposed to high PM2.5 levels. However, the impact of short-term exposure to high PM2.5 on blood pressure (BP) has not been well elucidated. Thus, this study aims to focus on the association between short-term PM2.5 exposure with BP of rural residents and its variation between summer and winter. Our results showed that the summertime PM2.5 exposure concentration was 49.3 ± 20.6 µg/m3, among which, mosquito coil users had 1.5-folds higher PM2.5 exposure than non-mosquito coil users (63.6 ± 21.7 vs 43.0 ± 16.7 µg/m3, p < 0.05). The mean systolic and diastolic BP (SBP and DBP, respectively) of rural participants were 122 ± 18.2 and 76.2 ± 11.2 mmHg in summer, respectively. The PM2.5 exposure, SBP, and DBP in summer were 70.7 µg/m3, 9.0 mmHg, and 2.8 mmHg lower than that in winter, respectively. Furthermore, the correlation between PM2.5 exposure and SBP was stronger in winter than that in summer, possibly due to higher PM2.5 exposure levels in winter. The transition of household energy from solid fuels in winter to clean fuels in summer would be benefit to the decline of PM2.5 exposure as well as BP. Results from this study suggested that the reduction of PM2.5 exposure would have positive effect on human health.

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Maternal PM2.5 exposure has been identified as a potential risk factor for preterm birth, yet the inconsistent findings on the susceptible exposure windows may be partially due to the influence of gaseous pollutants. This study aims to examine the association between PM2.5 exposure and preterm birth during different susceptible exposure windows after adjusting for exposure to gaseous pollutants. We collected 2,294,188 records of singleton live births from 30 provinces of China from 2013 to 2019, and the gridded daily concentrations of air pollutants (including PM2.5, O3, NO2, SO2, and CO) were derived by using machine learning models for assessing individual exposure. We employed logistic regression to develop single-pollutant models (including PM2.5 only) and co-pollutant models (including PM2.5 and a gaseous pollutant) to estimate the odds ratio for preterm birth and its subtypes, with adjustment for maternal age, neonatal sex, parity, meteorological conditions, and other potential confounders. In the single-pollutant models, PM2.5 exposure in each trimester was significantly associated with preterm birth, and the third trimester exposure showed a stronger association with very preterm birth than that with moderate to late preterm birth. The co-pollutant models revealed that preterm birth might be significantly associated only with maternal exposure to PM2.5 in the third trimester, and not with exposure in the first or second trimester. The observed significant associations between preterm birth and maternal PM2.5 exposure in the first and second trimesters in single-pollutant models might primarily be influenced by exposure to gaseous pollutants. Our study provides evidence that the third trimester may be the susceptible window for maternal PM2.5 exposure and preterm birth. The association between PM2.5 exposure and preterm birth could be influenced by gaseous pollutants, which should be taken into consideration when evaluating the impact of PM2.5 exposure on maternal and fetal health.

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In recent years, complex air pollution with the characteristic pollutant of PM2.5 has remained serious in China. Long term exposure to PM2.5 might harm residential health and can increase premature death from specific diseases. The annual average concentration of PM2.5 in Zhengzhou was much higher than the national secondary standard, which has an extremely negative impact on the health of residents. Based on the high spatial resolution grids of population density established through web-crawling and outdoor monitoring concentrations and urban residential emissions used to evaluate PM2.5 exposure concentration, the exposure concentration of PM2.5 for urban residents of Zhengzhou was assessed, considering both indoor and outdoor exposures. Relevant health risks were quantified with the integrated exposure-response model. Finally, the contributions of various reducing measures and different standards of air quality to the decreases in PM2.5 exposure concentration were analyzed. The results showed that in 2017 and 2019, the time weighted exposure concentrations of PM2.5 for Zhengzhou's urban residents were 74.06 µg·m-3 and 60.64 µg·m-3, respectively, which was decreased by 18.12%. In addition, the mass fractions of the indoor exposure concentrations in the time weighted exposure concentrations were 83.58% and 83.01%, and its contribution to the drop of the time weighted exposure concentrations was 84.06%. In 2017 and 2019, the numbers of premature deaths attributed to PM2.5 exposures for urban residents of Zhengzhou over the age of 25 were 13285 and 10323, respectively, showing a 22.30% decrease. By using these comprehensive measures, PM2.5 exposure concentration for Zhengzhou's urban residents could be reduced by 86.23% at most, and 8902 premature deaths could be avoided.

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Using air purifiers is an intervention to reduce exposure to fine particulate matter (PM2.5) for health benefits. We performed a comprehensive simulation in urban China to estimate the cost-effectiveness of long-term use of air purifiers to remove indoor PM2.5 from indoor and ambient air pollution in five intervention scenarios (S1-S5), where the indoor PM2.5 targets were 35, 25, 15, 10, and 5 µg/m3, respectively. In scenarios S1 to S5, 5221 (95% uncertainty interval: 3886-6091), 6178 (4554-7242), 8599 (6255-10,109), 11,006 (7962-13,013), and 14,990 (10,888-17,610) thousand disability-adjusted-life-years (DALYs) can be avoided at the cost of 201 (199-204), 240 (238-243), 364 (360-369), 522 (515-530), and 921 (905-939) billion Chinese Yuan (CNY), respectively. A high disparity in per capita health benefits and costs was observed by city, which expanded with the decrease of the indoor PM2.5 target. The net benefits of using purifiers in cities varied across scenarios. Cities with a lower ratio of annual average outdoor PM2.5 concentration to gross domestic product (GDP) per capita tended to achieve higher net benefits in the scenario with a lower indoor PM2.5 target. Controlling ambient PM2.5 pollution and developing the economy can reduce the inequality in air purifier use across China.

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