Indoor sulfur dioxide prediction through air quality modeling and assessment of sulfur dioxide and nitrogen dioxide levels in industrial and non-industrial areas.

In this study, the levels of sulfur dioxide (SO2) and nitrogen dioxide (NO2) were measured indoors and outdoors using passive samplers in Tymar village (20 homes), an industrial area, and Haji Wsu (15 homes), a non-industrial region, in the summer and the winter seasons. In comparison to Haji Wsu village, the results showed that Tymar village had higher and more significant mean SO2 and NO2 concentrations indoors and outdoors throughout both the summer and winter seasons. The mean outdoor concentration of SO2 was the highest in summer, while the mean indoor NO2 concentration was the highest in winter in both areas. The ratio of NO2 indoors to outdoors was larger than one throughout the winter at both sites. Additionally, the performance of machine learning (ML) approaches: multiple linear regression (MLR), artificial neural network (ANN), and random forest (RF) were compared in predicting indoor SO2 concentrations in both the industrial and non-industrial areas. Factor analysis (FA) was conducted on different indoor and outdoor meteorological and air quality parameters, and the resulting factors were employed as inputs to train the models. Cross-validation was applied to ensure reliable and robust model evaluation. RF showed the best predictive ability in the prediction of indoor SO2 for the training set (RMSE = 2.108, MAE = 1.780, and R2 = 0.956) and for the unseen test set (RMSE = 4.469, MAE = 3.728, and R2 = 0.779) values compared to other studied models. As a result, it was observed that the RF model could successfully approach the nonlinear relationship between indoor SO2 and input parameters and provide valuable insights to reduce exposure to this harmful pollutant.

Modeling assessment of air pollution control measures and COVID-19 pandemic on air quality improvements over Greater Bay Area of China.

A remarkable progress has been made toward the air quality improvements over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 2017 to 2020. In this study, for the first time, the emission reductions of regional control measures together with the COVID-19 pandemic were considered simultaneously into the development of the GBA's emission inventories for the years of 2017 and 2020. Based on these collective emission inventories, the impacts of control measures, meteorological variations together with temporary COVID-19 lockdowns on the five major air quality index pollutants (SO2, NO2, PM2.5, PM10, and O3, excluding CO) were evaluated using the WRF-CMAQ and SMAT-CE model attainment assessment tool over the GBA region. Our results revealed that control measures in the Pearl River Delta (PRD) region affected significantly the GBA, resulting in pollutant reductions ranging from 48 % to 64 %. In contrast, control measures in Hong Kong and Macao contributed to pollutant reductions up to 10 %. In PRD emission sectors, stationary combustion, on-road, industrial processes and dust sectors stand out as the primary contributors to overall air quality improvements. Moreover, the COVID-19 pandemic during period I (Jan 23-Feb 23) led to a reduction of NO2 concentration by 7.4 %, resulting in a negative contribution (disbenefit) for O3 with an increase by 2.4 %. Our findings highlight the significance of PRD control measures for the air quality improvements over the GBA, emphasizing the necessity of implementing more refined and feasible manageable joint prevention and control policies.

Air pollution and upper respiratory diseases: an examination among medically insured populations in Wuhan, China.

Multiple evidence has supported that air pollution exposure has detrimental effects on the cardiovascular and respiratory systems. However, most investigations focus on the general population, with limited research conducted on medically insured populations. To address this gap, the current research was designed to examine the acute effects of inhalable particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ground-level ozone (O3), and sulfur dioxide (SO2) on the incidence of upper respiratory tract infections (URTI), utilizing medical insurance data in Wuhan, China. Data on URTI were collected from the China Medical Insurance Basic Database for Wuhan covering the period from 2014 to 2018, while air pollutant data was gathered from ten national monitoring stations situated in Wuhan city. Statistical analysis was performed using generalized additive models for quasi-Poisson distribution with a log link function. The analysis indicated that except for ozone, higher exposure to four other pollutants (NO2, SO2, PM2.5, and PM10) were significantly linked to an elevated risk of URTI, particularly during the previous 0-3 days and previous 0-4 days. Additionally, NO2 and SO2 were found to be positively linked with laryngitis. Furthermore, the effects of air pollutants on the risk of URTI were more pronounced during cold seasons than hot seasons. Notably, females and the employed population were more susceptible to infection than males and non-employed individuals. Our findings gave solid proof of the link between ambient air pollution exposure and the risk of URTI in medically insured populations.

Early-life exposure to ambient air pollution with cardiovascular risk factors in adolescents: Findings from the "Children of 1997" Hong Kong birth cohort.

BACKGROUND: Long-term exposure to ambient air pollution is associated with cardiovascular disease (CVD) risk. Little is known about the impact of early-life exposure to air pollutants on CVD risk factors in late adolescence, which may track into adulthood. To clarify, we examined this question in a unique setting with high air pollution and a high level of economic development. METHODS: This study leveraged the "Children of 1997" Hong Kong birth cohort (N = 8327), including here 3350 participants. We estimated ambient air pollutant exposure including inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and nitrogen monoxide (NO) by growth phase (in utero, infancy, childhood) and overall based on residential address. Generalized linear regression was used to assess the associations of air pollutants exposure by growth phase and sex with CVD risk factors (fasting blood glucose, glycosylated hemoglobin, lipid profile, blood pressure, and body mass index) at 17.6 years. We also assessed whether associations varied by sex. RESULTS: Early life exposed had little association with glucose metabolism, blood pressure or body mass index, but after considering multiple comparisons early exposure to PM10 was associated with low density lipoprotein (LDL) in boys, with ß and 95 % confidence intervals (95 % CI) of 0.184 (0.069 to 0.298) mmol/l, 0.151 (0.056 to 0.248) mmol/l, and 0.157 (0.063 to 0.252) mmol/l by per interquartile range (IQR) increment of PM10 for in utero, infancy, and overall, respectively. No such associations were evident for girls, differences by sex were evident. CONCLUSIONS: Our study suggested sex-specific associations of early-life PM10 exposure with elevated LDL in adolescence, especially exposure in utero and infancy.

A novel approach to deriving the fine-scale daily NO2 dataset during 2005-2020 in China: Improving spatial resolution and temporal coverage to advance exposure assessment.

Surface NO2 pollution can result in serious health consequences such as cardiovascular disease, asthma, and premature mortality. Due to the extensive spatial variation in surface NO2, the spatial resolution of a NO2 dataset has a significant impact on the exposure and health impact assessment. There is currently no long-term, high-resolution, and publicly available NO2 dataset for China. To fill this gap, this study generated a NO2 dataset named RBE-DS-NO2 for China during 2005-2020 at 1 km and daily resolution. We employed the robust back-extrapolation via a data augmentation approach (RBE-DA) to ensure the predictive accuracy in back-extrapolation before 2013, and utilized an improved spatial downscaling technique (DS) to refine the spatial resolution from 10 km to 1 km. Back-extrapolation validation based on 2005-2012 observations from sites in Taiwan province yielded an R2 of 0.72 and RMSE of 10.7 µg/m3, while cross-validation across China during 2013-2020 showed an R2 of 0.73 and RMSE of 9.6 µg/m3. RBE-DS-NO2 better captured spatiotemporal variation of surface NO2 in China compared to the existing publicly available datasets. Exposure assessment using RBE-DS-NO2 show that the population living in non-attainment areas (NO2 ≥ 30 µg/m3) grew from 376 million in 2005 to 612 million in 2012, then declined to 404 million by 2020. Unlike this national trend, exposure levels in several major cities (e.g., Shanghai and Chengdu) continued to increase during 2012-2020, driven by population growth and urban migration. Furthermore, this study revealed that low-resolution dataset (i.e., the 10 km intermediate dataset before the downscaling) overestimated NO2 levels, due to the limited specificity of the low-resolution model in simulating the relationship between NO2 and the predictor variables. Such limited specificity likely biased previous long-term NO2 exposure and health impact studies employing low-resolution datasets. The RBE-DS-NO2 dataset enables robust long-term assessments of NO2 exposure and health impacts in China.

Urban-rural disparities in the association of nitrogen dioxide exposure with cardiovascular disease risk in China: effect size and economic burden.

BACKGROUND: Together with rapid urbanization, ambient nitrogen dioxide (NO2) exposure has become a growing health threat. However, little is known about the urban-rural disparities in the health implications of short-term NO2 exposure. This study aimed to compare the association between short-term NO2 exposure and hospitalization for cardiovascular disease (CVD) among urban and rural residents in Shandong Province, China. Then, this study further explored the urban-rural disparities in the economic burden attributed to NO2 and the explanation for the disparities. METHODS: Daily hospitalization data were obtained from an electronic medical records dataset covering a population of 5 million. In total, 303,217 hospital admissions for CVD were analyzed. A three-stage time-series analytic approach was used to estimate the county-level association and the attributed economic burden. RESULTS: For every 10-µg/m3 increase in NO2 concentrations, this study observed a significant percentage increase in hospital admissions on the day of exposure of 1.42% (95% CI 0.92 to 1.92%) for CVD. The effect size was slightly higher in urban areas, while the urban-rural difference was not significant. However, a more pronounced displacement phenomenon was found in rural areas, and the economic burden attributed to NO2 was significantly higher in urban areas. At an annual average NO2 concentration of 10 µg/m3, total hospital days and expenses in urban areas were reduced by 81,801 (44,831 to 118,191) days and 60,121 (33,002 to 86,729) thousand CNY, respectively, almost twice as much as in rural areas. Due to disadvantages in socioeconomic status and medical resources, despite similar air pollution levels in the urban and rural areas of our sample sites, the rural population tended to spend less on hospitalization services. CONCLUSIONS: Short-term exposure to ambient NO2 could lead to considerable health impacts in either urban or rural areas of Shandong Province, China. Moreover, urban-rural differences in socioeconomic status and medical resources contributed to the urban-rural disparities in the economic burden attributed to NO2 exposure. The health implications of NO2 exposure are a social problem in addition to an environmental problem. Thus, this study suggests a coordinated intervention system that targets environmental and social inequality factors simultaneously.

Ethnic and socioeconomic inequalities in air pollution exposure: a cross-sectional analysis of nationwide individual-level data from the Netherlands.

BACKGROUND: Air pollution contributes to a large disease burden and some populations are disproportionately exposed. We aimed to evaluate ethnic and socioeconomic differences in exposure to air pollution in the Netherlands. METHODS: We did a nationwide, cross-sectional analysis of all residents of the Netherlands on Jan 1, 2019. Sociodemographic information was centralised by Statistics Netherlands and mainly originated from the National Population Register, the tax register, and education registers. Concentrations of NO2, PM2·5, PM10, and elemental carbon, modelled by the National Institute for Public Health and the Environment, were linked to the individual-level demographic data. We assessed differences in air pollution exposures across the 40 largest minority ethnic groups. Evaluation of how ethnicity intersected with socioeconomic position in relation to exposures was done for the ten largest ethnic groups, plus Chinese and Indian groups, in both urban and rural areas using multivariable linear regression analyses. FINDINGS: The total study population consisted of 17 251 511 individuals. Minority ethnic groups were consistently exposed to higher levels of air pollution than the ethnic Dutch population. The magnitude of inequalities varied between the minority ethnic groups, with 3-44% higher exposures to NO2 and 1-9% higher exposures to PM2·5 compared with the ethnic Dutch group. Average exposures were highest for the lowest socioeconomic group. Ethnic inequalities in exposure remained after adjustment for socioeconomic position and were of similar magnitude in urban and rural areas. INTERPRETATION: The variability in air pollution exposure across ethnic and socioeconomic subgroups in the Netherlands indicates environmental injustice at the intersection of social characteristics. The health consequences of the observed inequalities and the underlying processes driving them warrant further investigation. FUNDING: The Gravitation programme of the Dutch Ministry of Education, Culture, and Science, the Netherlands Organization for Scientific Research, the Netherlands Organisation for Health Research and Development, and Amsterdam University Medical Center.

Assessment of ambient air quality in relation to the burning of firecrackers during the festival of Diwali: A case study of Jodhpur City (India).

The study attempts to examine the impact of firework activities during Diwali Festival on ambient air quality of Jodhpur city. Air quality parameters particulate matter of diameter 10 µm (PM10), particulate matter of diameter 2.5 µm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2) and heavy metals in PM2.5 like Pb, Ni, Ba, Al, As and Sr are monitored at two locations, for 15 days, starting from 7 days before the festival of Diwali, on the day of the festival (Diwali) and 7 days after Diwali. On the occasion of Diwali, it was discovered that the 24-h average levels of various pollutants were significantly elevated compared to regular days preceding the festival. Specifically, at the HBO site, the concentrations were notably increased, with sulfur dioxide (SO2) reaching 5.62 times higher, nitrogen dioxide (NO2) at 3 times higher, particulate matter of diameter 10 µm (PM10) at 2.35 times higher, and particulate matter of diameter 2.5 µm (PM2.5) at 1.01 times higher than the usual levels before Diwali. Similarly, at the PTMM site, there were substantial elevations in pollutant concentrations during Diwali compared to pre-festival days, with SO2 registering 2.53 times higher, NO2 at 2.37 times higher, PM2.5 at 1.9 times higher, and PM10 at 1.57 times higher levels than normal. Concentration of Al, Ba, Sr and Pb at HBO site and Al at PTMM site was highest on Diwali day. Air quality index which was in good category on normal days before Diwali, fell into poor category starting from the day before Diwali and remain in poor category on normal days after Diwali. The result indicates the worsening of ambient air quality during Diwali which can adversely impact the human health in terms of various respiratory complications.

Effects of ambient air pollution on the hospitalization risk and economic burden of mental disorders in Qingdao, China.

OBJECTIVE: The aim of this study was to examine the impacts of short-term exposure to air pollutants on hospitalizations for mental disorders (MDs) in Qingdao, a Chinese coastal city, and to assess the corresponding hospitalization risk and economic cost. METHODS: Daily data on MD hospitalizations and environmental variables were collected from January 1, 2015, to December 31, 2019. An overdispersed generalized additive model was used to estimate the association between air pollution and MD hospitalizations. The cost of illness method was applied to calculate the corresponding economic burden. RESULTS: With each 10 µg/m3 increase in the concentration of fine particulate matter (PM2.5) at lag05, inhalable particulate matter (PM10) at lag0, sulfur dioxide (SO2) at lag06 and ozone (O3) at lag0, the corresponding relative risks (RRs) and 95% confidence intervals (CIs) were 1.0182 (1.0035-1.0332), 1.0063 (1.0001-1.0126), 1.0997 (1.0200-1.1885) and 1.0099 (1.0005-1.0194), respectively. However, no significant effects of nitrogen dioxide (NO2) or carbon monoxide (CO) were found. Stratified analysis showed that males were susceptible to SO2 and O3, while females were susceptible to PM2.5. Older individuals (≥ 45 years) were more vulnerable to air pollutants (PM2.5, PM10, SO2 and O3) than younger individuals (< 45 years). Taking the Global Air Quality Guidelines 2021 as a reference, 8.71% (2,168 cases) of MD hospitalizations were attributable to air pollutant exposure, with a total economic burden of 154.36 million RMB. CONCLUSION: Short-term exposure to air pollution was associated with an increased risk of hospitalization for MDs. The economic advantages of further reducing air pollution are enormous.

Assessment of the association between ambient air pollution and stillbirth in the UK: Results from a secondary analysis of the MiNESS case-control study.

OBJECTIVE: We examined whether the risk of stillbirth was related to ambient air pollution in a UK population. DESIGN: Prospective case-control study. SETTING: Forty-one maternity units in the UK. POPULATION: Women who had a stillbirth ≥28 weeks' gestation (n = 238) and women with an ongoing pregnancy at the time of interview (n = 597). METHODS: Secondary analysis of data from the Midlands and North of England Stillbirth case-control study only including participants domiciled within 20 km of fixed air pollution monitoring stations. Pollution exposure was calculated using pollution climate modelling data for NO2 , NOx and PM2.5 . The association between air pollution exposure and stillbirth risk was assessed using multivariable logistic regression adjusting for household income, maternal body mass index (BMI), maternal smoking, Index of Multiple Deprivation quintile and household smoking and parity. MAIN OUTCOME MEASURE: Stillbirth. RESULTS: There was no association with whole pregnancy ambient air pollution exposure and stillbirth risk, but there was an association with preconceptual NO2 exposure (adjusted odds ratio [aOR] 1.06, 95% CI 1.01-1.08 per microg/m3 ). Risk of stillbirth was associated with maternal smoking (aOR 2.54, 95% CI 1.38-4.71), nulliparity (aOR 2.16, 95% CI 1.55-3.00), maternal BMI (aOR 1.05, 95% CI 1.01-1.08) and placental abnormalities (aOR 4.07, 95% CI 2.57-6.43). CONCLUSIONS: Levels of ambient air pollution exposure during pregnancy in the UK, all of were beneath recommended thresholds, are not associated with an increased risk of stillbirth. Periconceptual exposure to NO2 may be associated with increased risk but further work is required to investigate this association.

Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors.

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

The burden of disease attributable to indoor air pollutants in China from 2000 to 2017.

BACKGROUND: High-level exposure to indoor air pollutants (IAPs) and their corresponding adverse health effects have become a public concern in China in the past 10 years. However, neither national nor provincial level burden of disease attributable to multiple IAPs has been reported for China. This is the first study to estimate and rank the annual burden of disease and the financial costs attributable to targeted residential IAPs at the national and provincial level in China from 2000 to 2017. METHODS: We first did a systematic review and meta-analysis of 117 articles from 37 231 articles identified in major databases, and obtained exposure-response relationships for the candidate IAPs. The exposure levels to these IAPs were then collected by another systematic review of 1864 articles selected from 52 351 articles. After the systematic review, ten IAPs with significant and robust exposure-response relationships and sufficient exposure data were finally targeted: PM2·5, nitrogen dioxide, sulphur dioxide, ozone, carbon monoxide, radon, formaldehyde, benzene, toluene, and p-dichlorobenzene. The annual exposure levels in residences were then evaluated in all 31 provinces in mainland China continuously from 2000 to 2017, using the spatiotemporal Gaussian process regression model to analyse indoor originating IAPs, and the infiltration factor method to analyse outdoor originating IAPs. The disability-adjusted life-years (DALYs) attributable to the targeted IAPs were estimated at both national and provincial levels in China, using the population attributable fraction method. Financial costs were estimated by an adapted human capital approach. FINDINGS: From 2000 to 2017, annual DALYs attributable to the ten IAPs in mainland China decreased from 4620 (95% CI 4070-5040) to 3700 (3210-4090) per 100 000. Nevertheless, in 2017, IAPs still ranked third among all risk factors, and their DALYs and financial costs accounted for 14·1% (95% CI 12·3-15·6) of total DALYs and 3·45% (3·01-3·82) of the gross domestic product. Specifically, the rank of ten targeted IAPs in order of their contribution to DALYs in 2017 was PM2·5, carbon monoxide, radon, benzene, nitrogen dioxide, ozone, sulphur dioxide, formaldehyde, toluene, and p-dichlorobenzene. The DALYs attributable to IAPs were 9·50% higher than those attributable to outdoor air pollution in 2017. For the leading IAP, PM2·5, the DALYs attributable to indoor origins are 18·3% higher than those of outdoor origins. INTERPRETATION: DALYs attributed to IAPs in China have decreased by 20·0% over the past two decades. Even so, they are still much higher than those in the USA and European countries. This study can provide a basis for determining which IAPs to target in various indoor air quality standards and for estimating the health and economic benefits of various indoor air quality control approaches, which will help to reduce the adverse health effects of IAPs in China. FUNDING: The National Key Research and Development Program of China and the National Natural Science Foundation of China.

Assessment of health impacts and costs attributable to air pollution in urban areas using two different approaches. A case study in the Western Balkans.

In this study, two different air quality impact assessment methodologies were adopted and combined with a sensitivity analysis to estimate the unit costs. Air pollution health impact (mortality) assessment was carried out using one methodology based on log-linear concentration response functions (CRF) and another relying on the integrated exposure response curve (IER) from the Global Burden of Disease. Morbidity impacts were estimated with the CRF approach only. To assess the inequalities between low and high income countries, an area of low-medium income countries with a critical air pollution situation, was selected. The health impact and related external costs attributable to air pollution in 2019 were assessed in 30 urban areas of the Western Balkans region, one of Europe's air pollution hot spots. The evaluation was based on PM2.5, O3 and NO2 concentrations in background sites from official monitoring networks. In 2019, the cost of mortality attributable to PM2.5 in 26 urban areas was 7.8 and 9.0 billion Euro according to IER and CRF methodologies, respectively. The cost of O3 associated with all-cause mortality estimated with the CRF methodology in 17 urban areas was 1.0 billion Euro while the one attributable to NO2 pollution in 28 urban areas was 1.5 billion Euro. The study results suggest that the economic burden of air pollution in the Western Balkans is higher in terms of GDP than the one observed in EU27 in the same time window. The study concludes that CRF and IER methodologies are coherent, because the discrepancy in the results are explained by the differences in the assessed health outcomes. The two approaches are complementary because the combination of them makes it possible to obtain a wider range of outcomes. In addition, despite the different causes of death considered, the comparison between them is useful for cross-validation.

Health and Economic Benefits of Air Pollution Reductions in Vietnam During 2020-2021.

Objectives: This paper explores the potential reduction in the number of deaths and the corresponding economic benefits in Vietnam that could have arisen from the decreased in concentrations of particulate matter with a diameter of 2.5 µm or less (PM2.5) and nitrogen dioxide (NO2). Methods: Using Global Exposure Mortality Models, we estimated the potential health and economic benefits on people aged 25 and above across Vietnam's 63 provinces. The counterfactual scenario assumed reducing PM2.5 and NO2 concentrations to levels observed during the two COVID-19 epidemic waves in 2021 with national lockdowns and activity restrictions. Results: In 2019, PM2.5 concentrations ranged from 12.8 to 40.8 µg/m3 while NO2 concentrations ranged between 2.9 and 36.98 µg/m3. The reduced levels of PM2.5 and NO2 resulted in 3,807 (95% CI: 2,845-4,730) and 2,451 (95% CI: 2,845-4,730) avoided deaths of adults aged 25 and above due to non-injury-related causes, respectively. Considering that every prevented death represents potential tangible and intangible cost savings, reduced levels of PM2.5 and NO2 concentrations during COVID-19 restrictions would have resulted in economic benefits of $793.0 million (95% CI: 592.7-985.4) and $510.6 million (95% CI: 381.3-634.9), respectively. Conclusion: The COVID-19 lockdown led to decreased PM2.5 and NO2 concentrations, benefiting health and economy in Vietnam. Our findings highlight the potential advantages of implementing air quality control policies in the country.

The impact of air pollution on outpatient medical service utilization and expenditure in a clean air city.

BACKGROUND: Although there's increasing research on the health effects of air pollution in China, its direct influence on health-related expenditures, particularly during less severe pollution episodes, is still not well-understood. This study aims to quantify impact of three air pollutants (sulfur dioxide, nitrogen dioxide, and particulate matter) on individual healthcare spending in a city with relatively clean air. METHODS: Using transaction-level medical social insurance data and temperature inversion as the instrumental variable, we estimate the current and cumulative effects of air pollutants on outpatient visits and medical expenses in an eastern city in China. RESULTS: We find a significantly positive effect on outpatient visits for 15-day moving average, and a significantly positive effect on outpatient expenditure for 25-day moving average. Therefore, the cumulative effect of pollutants on medical expenditure should not be ignored. The effects on total outpatient expenditure are larger for the elderly and men. The cumulative pollution exposure increases the visits to respiratory department but also increases the expenditure on non-respiratory diseases in the long term. CONCLUSION: Our findings provide empirical evidence that even for cities with good air quality, further improvements can improve patients' quality of life and lessen the expenditure burden on medical insurance.

Long-term association of air pollution and incidence of lung cancer among older Americans: A national study in the Medicare cohort.

BACKGROUND: Despite strong evidence of the association of fine particulate matter (PM2.5) exposure with an increased risk of lung cancer mortality, few studies had investigated associations of multiple pollutants simultaneously, or with incidence, or using causal methods. Disparities were also understudied. OBJECTIVES: We investigated long-term effects of PM2.5, nitrogen dioxide (NO2), warm-season ozone, and particle radioactivity (PR) exposures on lung cancer incidence in a nationwide cohort. METHODS: We conducted a cohort study with Medicare beneficiaries (aged ≥ 65 years) continuously enrolled in the fee-for-service program in the contiguous US from 2001 to 2016. Air pollution exposure was averaged across three years and assigned based on ZIP code of residence. We fitted Cox proportional hazards models to estimate the hazard ratio (HR) for lung cancer incidence, adjusted for individual- and neighborhood-level confounders. As a sensitivity analysis, we evaluated the causal relationships using inverse probability weights. We further assessed effect modifications by individual- and neighborhood-level covariates. RESULTS: We identified 166,860 lung cancer cases of 12,429,951 studied beneficiaries. In the multi-pollutant model, PM2.5 and NO2 exposures were statistically significantly associated with increased lung cancer incidence, while PR was marginally significantly associated. Specifically, the HR was 1.008 (95% confidence interval [CI]: 1.005, 1.011) per 1-µg/m3 increase in PM2.5, 1.013 (95% CI: 1.012, 1.013) per 1-ppb increase in NO2, and 1.005 (0.999, 1.012) per 1-mBq/m3 increase in PR. At low exposure levels, all pollutants were associated with increased lung cancer incidence. Men, older individuals, Blacks, and residents of low-income neighborhoods experienced larger effects of PM2.5 and PR. DISCUSSION: Long-term PM2.5, NO2, and PR exposures were independently associated with increased lung cancer incidence among the national elderly population. Low-exposure analysis indicated that current national standards for PM2.5 and NO2 were not restrictive enough to protect public health, underscoring the need for more stringent air quality regulations.

The impact of ambient air pollution on hospital admissions, length of stay and hospital costs for patients with diabetes mellitus and comorbid respiratory diseases in Panzhihua, Southwest China.

Background: There is limited evidence on association between air pollutants and hospital admissions, hospital cost and length of stay (LOS) among patients with diabetes mellitus (DM) and comorbid respiratory diseases (RD), especially in low- and middle-income countries (LMICs) with low levels of air pollution. Methods: Daily data on RD-DM patients were collected in Panzhihua from 2016 to 2020. A generalised additive model (GAM) was used to explore the effect of air pollutants on daily hospital admissions, LOS and hospital cost. Attributable risk was employed to estimate RD-DM's burden due to exceeding air pollution exposure, using both 0 microgrammes per cubic metre (µg/m3) and WHO's 2021 air quality guidelines as reference. Results: For each 10 ug/m3 increase of particles with an aerodynamic diameter <2.5 micron (µm) (PM2.5), particles with an aerodynamic diameter <10 µm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3), the admissions of RD-DM patients increased by 7.25% (95% CI = 4.26 to 10.33), 5.59% (95% CI = 3.79 to 7.42), 10.10% (95% CI = 7.29 to 12.98), 12.33% (95% CI = 8.82 to 15.95) and -2.99% (95% CI = -4.08 to -1.90); per 1 milligramme per cubic metre (mg/m3) increase of carbon monoxide (CO) corresponded to a 25.77% (95% CI = 17.88 to 34.19) increment for admissions of RD-DM patients. For LOS and hospital cost, the six air pollutants showed similar effect. Given 0 µg/m3 as the reference, NO2 showed the maximum attributable fraction of 32.68% (95% CI = 25.12 to 39.42%), corresponding to an avoidable burden of 5661 (95% CI = 3611 to 5860) patients with RD-DM. Conclusions: There is an association between PM2.5, PM10, SO2, NO2, and CO with increased hospital admissions, LOS and hospital cost in patients with RD-DM. Disease burden of RD-DM may be improved by formulating policies related to air pollutants exposure reduction, especially in LMICs with low levels of air pollution.

Examining the geographical distribution of air pollution disparities across different racial and ethnic groups: Incorporating workplace addresses.

BACKGROUND: Most previous studies on air pollution exposure disparities among racial and ethnic groups in the US have been limited to residence-based exposure and have given little consideration to population mobility and spatial patterns of residences, workplaces, and air pollution. This study aimed to examine air pollution exposure disparities by racial and ethnic groups while explicitly accounting for both the work-related activity of the population and localized spatial patterns of residential segregation, clustering of workplaces, and variability of air pollutant concentration. METHOD: In the present study, we assessed population-level exposure to air pollution using tabulated residence and workplace addresses of formally employed workers from LEHD Origin-Destination Employment Statistics (LODES) data at the census tract level across eight Metropolitan Statistical Areas (MSAs). Combined with annual-averaged predictions for three air pollutants (PM2.5, NO2, O3), we investigated racial and ethnic disparities in air pollution exposures at home and workplaces using pooled (i.e., across eight MSAs) and regional (i.e., with each MSA) data. RESULTS: We found that non-White groups consistently had the highest levels of exposure to all three air pollutants, at both their residential and workplace locations. Narrower exposure disparities were found at workplaces than residences across all three air pollutants in the pooled estimates, due to substantially lower workplace segregation than residential segregation. We also observed that racial disparities in air pollution exposure and the effect of considering work-related activity in the exposure assessment varied by region, due to both the levels and patterns of segregation in the environments where people spend their time and the local heterogeneity of air pollutants. CONCLUSIONS: The results indicated that accounting for workplace activity illuminates important variation between home- and workplace-based air pollution exposure among racial and ethnic groups, especially in the case of NO2. Our findings suggest that consideration of both activity patterns and place-based exposure is important to improve our understanding of population-level air pollution exposure disparities, and consequently to health disparities that are closely linked to air pollution exposure.

Environmental Burden of Disease due to Emissions of Hard Coal- and Lignite-Fired Power Plants in Germany.

Objectives: The study estimated the environmental burden of disease (EBD) attributable to a long-term exposure of the population to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions from hard coal- and lignite-fired power plants in Germany for the year 2015. Methods: The contribution of coal-fired power plants to the total air pollutant concentration was modelled using a chemical transport model and then combined with population data to assess the corresponding population exposure. We calculated years of life lost (YLL), years of life with disability, or disability-adjusted life years for different health outcomes with a strong evidence for an association with the exposure. Results: The burden of disease from PM2.5 emissions from lignite is 1.2 times higher than that from hard coal emissions (7,866 YLL compared to 6,412 YLL). NO2 emissions from lignite, cause a burden of disease 2.3 times higher than hard coal NO2-emission (13,537 YLL compared to 5,906 YLL). The EBD for both pollutants is dominated by diseases of the cardiovascular system. Conclusion: Abandoning energy generation by coal-fired power plants would lower the burden of disease in Germany.

Assessment of forest fire emissions in Uttarakhand State, India, using Open Geospatial data and Google Earth Engine.

In the recent past, forest fires have increased due to the changing climate pattern. It is necessary to analyse and quantify various gaseous emissions so as to mitigate their harmful effects on air pollution. Satellite remote sensing data provides an opportunity to study the greenhouse gases in the atmosphere. The multispectral sensor of the Tropospheric Monitoring Instrument (Sentinel-5) is capable of recording the reflectance of wavelengths vital for measuring the atmospheric concentrations of methane, formaldehyde, aerosol, carbon monoxide, etc., at a spatial resolution of 0.01°. The present study utilized the Google Earth Engine (GEE) platform to study the emissions caused by forest fires in four districts of Uttarakhand State of India, which witnessed unprecedented fires in April-May 2021. All the datasets were ingested in GEE, which has the capability to analyse large datasets without the need to download them. The pre-fire period chosen was September 2020; the fire period was February-May 2021, and the post-fire period was June 2021. The variables chosen were aerosol absorbing index (AAI), carbon monoxide (CO) and nitrogen dioxide (NO2). The climate parameter temperature (Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) and precipitation (from Climate Hazards Group InfraRed Precipitation (CHIRPS) Pentad) were also studied for the period mentioned. The results indicate a different trend for emissions in each district. For AAI, maximum emissions were noted in district Nainital followed by Almora, Tehri Garhwal and Garhwal. For CO emissions, the most affected district was Almora followed by Nainital, Garhwal and Tehri Garhwal. For NO2 emissions, the most affected district was Garhwal, followed by Nainital, Tehri Garhwal and Almora. Delta Normalized Burn Ratio was computed from Sentinel data (difference of pre-fire and post-fire images) to assess the burnt area severity. The Delta Normalized Burn Ratio values observed that the district with the most burnt area is Garhwal, followed by Nainital, Almora and Tehri Garhwal. The elevated temperatures and scanty rainfall patterns regulated the intensity and duration of forest fire. Monitoring the gaseous emissions as a consequence of forest fire in the GEE platform is much easier and more convenient at a regional level. Such data is much needed for mitigation measures to be implemented in time.