Efforts in reducing air pollution exposure risk in China: State versus individuals

Epidemiological trends and age-period-cohort effects on cardiovascular diseases burden attributable to ambient air pollution across BRICS

Long-term exposure to ambient air pollution raises the risk of deaths and morbidity worldwide. From 1990 to 2019, we observed the epidemiological trends and age-period-cohort effects on the cardiovascular diseases (CVD) burden attributable to ambient air pollution across Brazil, Russia, India, China, and South Africa (BRICS). The number of CVD deaths related to ambient particulate matter (PM) pollution increased nearly fivefold in China [5.0% (95% CI 4.7, 5.2)] and India [5.7% (95% CI 5.1, 6.3)] during the study period. The age-standardized CVD deaths and disability-adjusted life years (DALYs) due to ambient PM pollution significantly increased in India and China but decreased in Brazil and Russia. Due to air pollution, the relative risk (RR) of premature CVD mortality (< 70 years) was higher in Russia [RR 12.6 (95% CI 8.7, 17.30)] and India [RR 9.2 (95% CI 7.6, 11.20)]. A higher period risk (2015-2019) for CVD deaths was found in India [RR 1.4 (95% CI 1.4, 1.4)] followed by South Africa [RR 1.3 (95% CI 1.3, 1.3)]. Across the BRICS countries, the RR of CVD mortality markedly decreased from the old birth cohort to young birth cohorts. In conclusion, China and India showed an increasing trend of CVD mortality and morbidity due to ambient PM pollution and higher risk of premature CVD deaths were observed in Russia and India.

A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023

Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.

Traffic related activity pattern of Chinese adults: a nation-wide population based survey

BACKGROUND

Traffic-related air pollutants lead to increased risks of many diseases. Understanding travel patterns and influencing factors are important for mitigating traffic exposures. However, there is a lack of national large-scale research.

OBJECTIVE

This study aimed to evaluate the daily travel patterns of Chinese adults and provide basic data for traffic exposure and health risk research.

METHODS

We conducted the first nation-wide survey of travel patterns of adults (aged 18 and above) in China during 2011-2012. We conducted a cross-sectional study based on a nationally representative sample of 91, 121 adults from 31 provinces in China. We characterized typical travel patterns by cluster analysis and identified the associated factors of each pattern using multiple logistic regression and generalized linear regression models.

RESULTS

We found 115 typical daily travel patterns of Chinese adults and the top 11 accounted for 94% of the population. The interaction of age, urban and rural areas, income levels, gender, educational levels, city population and temperature affect people's choice of travel patterns. The average travel time of Chinese adults is 45 ± 40 min/day, with the longest travel time by the combination of walking and car (70 min/day). Gender has the largest effect on travel time (B = -8.94, 95% CI: -8.95, -8.93), followed by city GDP (B = -4.23, 95% CI: -4.23, -4.22), urban and rural areas (B = -3.62, 95% CI: -3.63, -3.61), age (B = -2.21, 95% CI: -2.21, -2.2), educational levels (B = -1.53, 95% CI: -1.53, -1.52), city area (B = -1.4, 95% CI: -1.4, -1.39) and temperature (B = 1.21, 95% CI: 1.2, 1.21).

SIGNIFICANCE

This study was the first nation-wide study on traffic activity patterns in China, which provides basic data for traffic exposure and health risk research and provides the basis for the state to formulate transportation-related policies.

Disease specific air quality health index (AQHI) for spatiotemporal health risk assessment of multi-air pollutants

While significant reductions in certain air pollutant concentrations did not induce obvious mitigations of health risks, a shift from air quality management to health risk prevention and control might be necessary to protect public health. This study thus constructed an Air Quality Health Index (AQHI) for respiratory (Res-AQHI), cardiovascular (Car-AQHI), and allergic (Aller-AQHI) risk groups using mixed exposure under multi-air pollutants and portrayed their distribution and variation at multiple spatiotemporal scales using spatial analysis in GIS with the medical big data and air pollution remote sensing data by taking Hunan Province in China as a case. Results showed that the AQHIs constructed for specific health-risk groups could better express their risks than common AQHI and AQI. Moreover, based on the spatiotemporal association of health and environmental information, the allergic risk group in Hunan provided the highest health risk mainly affected by O₃. The following cardiovascular and respiratory risk groups can be significantly attributed to NO₂. Moreover, the spatiotemporal heterogeneity of AQHIs within regions was also evident. On the annual scale, the population in the air health risk hotspots for respiratory and cardiovascular risk decreased, while allergic risks increased. Meanwhile, on seasonal scale, the hotspots for respiratory and cardiovascular risks expanded significantly in winter while completely disappearing for allergic risk. These findings suggest that disease specific AQHIs effectively disclose the health effects of multi-air pollutants and their subsequently varied spatiotemporal distribution patterns.

Exposure to Air Pollution and Emergency Department Visits During the First Year of Life Among Preterm and Full-term Infants

IMPORTANCE

Previous studies have focused on exposure to fine particulate matter 2.5 μm or less in diameter (PM2.5) and on birth outcome risks; however, few studies have evaluated the health consequences of PM2.5 exposure on infants during their first year of life and whether prematurity could exacerbate such risks.

OBJECTIVE

To assess the association of PM2.5 exposure with emergency department (ED) visits during the first year of life and determine whether preterm birth status modifies the association.

DESIGN, SETTING, AND PARTICIPANTS

This individual-level cohort study used data from the Study of Outcomes in Mothers and Infants cohort, which includes all live-born, singleton deliveries in California. Data from infants' health records through their first birthday were included. Participants included 2 175 180 infants born between 2014 and 2018, and complete data were included for an analytic sample of 1 983 700 (91.2%). Analysis was conducted from October 2021 to September 2022.

EXPOSURES

Weekly PM2.5 exposure at the residential ZIP code at birth was estimated from an ensemble model combining multiple machine learning algorithms and several potentially associated variables.

MAIN OUTCOMES AND MEASURES

Main outcomes included the first all-cause ED visit and the first infection- and respiratory-related visits separately. Hypotheses were generated after data collection and prior to analysis. Pooled logistic regression models with a discrete time approach assessed PM2.5 exposure and time to ED visits during each week of the first year of life and across the entire year. Preterm birth status, sex, and payment type for delivery were assessed as effect modifiers.

RESULTS

Of the 1 983 700 infants, 979 038 (49.4%) were female, 966 349 (48.7%) were Hispanic, and 142 081 (7.2%) were preterm. Across the first year of life, the odds of an ED visit for any cause were greater among both preterm (AOR, 1.056; 95% CI, 1.048-1.064) and full-term (AOR, 1.051; 95% CI, 1.049-1.053) infants for each 5-μg/m3 increase in exposure to PM2.5. Elevated odds were also observed for infection-related ED visit (preterm: AOR, 1.035; 95% CI, 1.001-1.069; full-term: AOR, 1.053; 95% CI, 1.044-1.062) and first respiratory-related ED visit (preterm: AOR, 1.080; 95% CI, 1.067-1.093; full-term: AOR,1.065; 95% CI, 1.061-1.069). For both preterm and full-term infants, ages 18 to 23 weeks were associated with the greatest odds of all-cause ED visits (AORs ranged from 1.034; 95% CI, 0.976-1.094 to 1.077; 95% CI, 1.022-1.135).

CONCLUSIONS AND RELEVANCE

Increasing PM2.5 exposure was associated with an increased ED visit risk for both preterm and full-term infants during the first year of life, which may have implications for interventions aimed at minimizing air pollution.

The efforts of China to combat air pollution during the period of 2015-2018: A case study assessing the environmental, health and economic benefits in the Beijing-Tianjin-Hebei and surrounding "2 + 26" regions

During the period of 2015-2018, Chinese government had made great efforts to mitigate air pollutants, such as air quality monitoring, energy structure adjustment, and pollutant emission reduction from industry, transportation and household sectors. With the special investment of 152 billion Chinese Yuan (CNY) in the Beijing-Tianjin-Hebei (BTH) and surrounding "2 + 26" regions, the annual local concentrations of PM_2.5, PM₁₀, SO₂ and NO₂ decreased from 77, 132, 38 and 46 μg/m³ to 60, 109, 20 and 43 μg/m³. It was estimated that the improvement in air quality avoided 27,021 (95 % CIs 12,548-39,738) premature deaths attributed to air pollution exposure based on an exposure-response function, including 45 %, 17 % and 15 % of cardiopulmonary, lung cancer and respiratory morality cases. Air pollution reduction was also effective in reducing work time loss, which reduced the total working time loss by 3.8 × 10⁷ (95 % CIs 1.8 × 10⁷-5.6 × 10⁷) h, and the per capita working time loss by 0.28 (95 % CIs 0.13-0.41) h/capita by 2018. From the economic aspect, air pollution control actions in those regions saved 95.6 (95 % CIs 44.2-141) billion CNY economic loss by using the value of statistical life (VSL). The total benefit-cost ratio was 63.7 % (95 % CIs 29.4 %-93.7 %). The cost-effectiveness in Beijing and Tianjin were relatively low due to the regional contribution from other cities of the air pollution transmission channel. Despite the uncertainties, the results clearly show the significance of the environmental, health and economic benefits of actions in the BTH and surrounding "2 + 26" regions for combating air pollution.

Air Pollution Management: A Multivariate Analysis of Citizens' Perspectives and Their Willingness to Use Greener Forms of Transportation

The present research aims to understand how air pollution can be managed by public authorities, both central and local, starting from citizens' perspectives on the issue. Air quality is a real problem, affecting people at multiple levels. Thus, we introduced the following variables to better understand the problem and to be able to formulate theoretical and practical implications for public management: the involvement of authorities in reducing air pollution; the involvement of citizens in reducing air pollution; financial incentives for citizens and companies for adopting behaviors that reduce air pollution; green investments in the city; the impact of air pollution on the community; and the need for independent bodies to monitor air pollution. The research methodology used is partial least squares structural equation modelling (PLS-SEM) and the required data were gathered from issuing a survey to citizens from the most important cities in Romania where pollution poses important challenges for the community and for the authorities. The results are useful to public managers in local and central institutions for creating better strategies meant to reduce air pollution, increase air quality, and improve the quality of the citizens' lives.

Estimation of exposure and premature mortality from near-roadway fine particulate matter concentrations emitted by heavy-duty diesel trucks in Beijing

Traffic exhaust is a main source of fine particulate matter (PM_2.5) in cities. Heavy-duty diesel trucks (HDDTs), the primary mode of freight transport, contribute significantly to PM_2.5, posing a great threat to public health. However, existing research based on dispersion models to simulate pollutant concentrations lacks high-spatiotemporal-resolution emission inventories of HDDTs as input data, and the public health effects of such emissions in different populations have not been thoroughly assessed. To fill this gap, we focused on Beijing as the research area and developed a high-resolution PM_2.5 emission inventory for HDDTs based on Global Navigation Satellite System-equipped vehicle trajectory data. We then simulated the fine-scale spatial distribution of diesel-related PM_2.5 and assessed the population exposure by integrating the dispersion model and population distributions. Further, we quantified the mortality attributable to noncommunicable diseases (NCDs) plus lower respiratory infections (LRIs) related to PM_2.5 emissions from HDDTs. Results showed that 3.3% of Beijing people lived in areas with high PM_2.5 HDDT emissions, which were near intercity highways. Furthermore, the estimated number of NCD + LRI annual premature deaths attributed to PM_2.5 HDDT emissions in Beijing was 339 (95% CI: 276-401). The NCD + LRI mortality increased with age, and deaths were more frequent in males than females. Our results aid the identification of HDDT PM_2.5 emission exposure hotspots for the formulation of effective mitigation measures and provide important insights into the adverse health impacts of HDDT emissions.

Long-term exposure to ambient black carbon is associated with sleep disturbance in college students

BACKGROUND

Evidence suggests an association of air pollution with sleep quality. However, there is limited knowledge regarding the effect of black carbon, a key component of ambient particulate matter, on sleep.

OBJECTIVES

To investigate the association of long-term exposure to black carbon and sleep quality in a group of college students.

METHODS

A retrospective cohort study was conducted in five universities in different regions of China. The concentrations of black carbon and other environment factors were defined as the averages during the 6 years prior to the recruitment. Averagely daily dose of black carbon exposure was estimated according to the respiratory rate. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) with a cutoff >5 indicating sleep disturbance. Linear regression and logistic regression models were used to estimate the association. The sensitivity analyses were conducted to estimate the effects of 1-month, 6-month and 1-year mean levels of exposure to black carbon on sleep quality.

RESULTS

A total of 20,053 incoming college students were included. 29.3% reported impaired sleep quality, with a mean PSQI score of 4.3 ± 2.2. The logistic regression showed that the risk of impaired sleep quality was positively associated with black carbon exposure, especially in the highest quantile (OR: 1.26, 95% CI: 1.11-1.43) compared with the lowest quartile after adjusting for potential confounders. Subgroup analysis showed that the effect of black carbon on sleep quality was stronger in participants with higher BMI, lower household income, and lower parental educational level. The results of sensitivity analyses were similar with main analyses.

CONCLUSION

Long-term exposure to black carbon is associated with sleep disturbance in college students. Improvement of air quality may help improve sleep quality.

The environmental consequences of foreign aid and key economic indicators: the Sino-Africa perspective

The study differs substantially from earlier studies, by probing the environmental consequences of foreign aid and selected key economic indicators with a special focus on Sino-Africa. The study focused on China and its top foreign aid recipients in Africa in the last decade. This paper utilizes the Dynamic Augmented Mean Group Estimator (AMG), a robust and recent econometric approach to provide better statistical inferences; crucial for policy formulation and future reforms on foreign aid, trade, energy, pollutions, and economic growth of economies. The findings of the study revealed the China's Foreign aid oriented towards infrastructure has varying impacts on the economic growth and the environment of most recipient African Countries. The findings revealed the incidence of foreign aid ameliorating pollution of the countries: Nigeria and Morocco under strong domestic institutions. The study is of key relevance for policymakers and stakeholders as it explicates the key pillars, policies, and guidelines needed for foreign aid, trade, economic growth, and related internal reforms for mitigating resulting environmental pollution across a wider international context.

Restricted Anthropogenic Activities and Improved Urban Air Quality in China: Evidence from Real-Time and Remotely Sensed Datasets Using Air Quality Zonal Modeling

The study aims to examine the major atmospheric air pollutants such as NO2, CO, O3, PM2.5, PM10, and SO2 to assess the overall air quality using air quality zonal modeling of 15 major cities of China before and after the COVID-19 pandemic period. The spatio-temporal changes in NO2 and other atmospheric pollutants exhibited enormous reduction due to the imposition of a nationwide lockdown. The present study used a 10-day as well as 60-day tropospheric column time-average map of NO2 with spatial resolution 0.25 × 0.25° obtained from the Global Modeling and Assimilation Office, NASA. The air quality zonal model was employed to assess the total NO2 load and its change during the pandemic period for each specific region. Ground surface monitoring data for CO, NO2, O3, PM10, PM2.5, and SO2 including Air Quality Index (AQI) were collected from the Ministry of Environmental Protection of China (MEPC). The results from both datasets demonstrated that NO2 has drastically dropped in all the major cities across China. The concentration of CO, PM10, PM2.5, and SO2 demonstrated a decreasing trend whereas the concentration of O3 increased substantially in all cities after the lockdown effect as observed from real-time monitoring data. Because of the complete shutdown of all industrial activities and vehicular movements, the atmosphere experienced a lower concentration of major pollutants that improves the overall air quality. The regulation of anthropogenic activities due to the COVID-19 pandemic has not only contained the spread of the virus but also facilitated the improvement of the overall air quality. Guangzhou (43%), Harbin (42%), Jinan (33%), and Chengdu (32%) have experienced maximum air quality improving rates, whereas Anshan (7%), Lanzhou (17%), and Xian (25%) exhibited less improved AQI among 15 cities of China during the study period. The government needs to establish an environmental policy framework involving central, provincial, and local governments with stringent laws for environmental protection.

In-vitro oxidative potential and inflammatory response of ambient PM2.5 in a rural region of Northwest China: Association with chemical compositions and source contribution

Overproduction of reactive oxygen species (ROS) induced by atmospheric particles and subsequent inflammatory responses are considered as one of the most important pathological mechanisms with regard to the adverse effects of air pollution exposure. In this study, fine particulate matter (PM_2.5) samples were collected at a rural site in Guanzhong Basin, Northwest China, in both summer (August 3-23, 2016) and winter (January 5-February 1, 2017). Then, human bronchial epithelial BEAS-2B cells were exposed to the PM_2.5, cultured for 24 h, and then assayed for particle-induced ROS and three inflammatory factors (tumor necrosis-α (TNF-α), interleukin-6 (IL-6), and interferon-γ (IFN-γ)) in vitro. The oxidative potential (OP) induced by winter PM_2.5 samples was higher than that induced by summertime samples, whereas inflammatory values showed contrasting seasonal variations. Both OP and inflammatory factors were significantly correlated with most chemical compounds in winter, but not in summer, which was thought to be related mainly to the higher contribution from secondary aerosols formed during the warm season. Source apportionment results showed secondary aerosols formation have significant contribution to OP of PM_2.5 in both seasons, but the dominant oxidation processes is different. Secondary nitrates-related process was the major contributors regulating the OP in winter; however, secondary sulfates formation were mainly responsible for the ROS responses in summer. For primary emission, biomass burning, rather than coal emission or vehicle exhaust, was the significant source for OP of PM_2.5 in winter. In most cases, the source contribution of each inflammatory factor was similar to that of the ROS. Our results highlighted the significant health risk of atmospheric aerosols from biomass burning in the rural regions of Guanzhong Basin, Northwest China.

The impact of perceived air pollution on labour supply: Evidence from China

Air pollution and ageing populations are two of the most important issues facing in the development of all countries around the world, and the resulting debate between air pollution and labour supply has become increasingly intense. This paper uses data from the 2017 China Migrants Dynamic Survey (CMDS data), exploring the impact of perceived air pollution on labour supply of the migrants based on the perspective of the heterogeneity of different groups' sensitivity to air pollution. After overcoming the reverse causality between perceived air pollution and labour supply using an instrumental variables approach, we find that there is a significant negative effect of perceived air pollution on labour supply. At the same time, this negative effect shows some heterogeneity in terms of the presence of susceptible persons in the family, workers' income levels and household registration. Therefore, in the current economic and social development, in addition to improving measured air quality, it is also necessary to focus on improving the perceived air quality of citizens, as well as improving the working environment of the vulnerable groups in the labour market and protecting their basic labour rights and interests, which is of positive significance for the continuation of the demographic dividend and providing impetus for high-quality and sustainable economic development.

The impacts of continuous improvements in air quality on mortality in Beijing: A longitudinal comparative study

There has been increasing concern about the health effects of air pollution in China, and many measures have been implemented to control air pollution. To investigate the impacts of air quality improvement on mortality from non-accidental causes (NAD), cardiovascular disease (CD), and respiratory disease (RD), a longitudinal comparative study was conducted in Beijing. This study investigated the effects of air pollutants on outcomes across five periods (stages 1-5). Health effect data from stage1-5 (1990-2013) were obtained through a systematic literature search of studies published before 2021. Daily atmospheric pollutant, meteorological, and cause-specific death data were collected to determine the effects in stage 5 (2015-2017). Poisson generalized additive models were used to analyze the associations between short-term exposure to air pollutants and mortality. Random-effects meta-analysis models were used to estimate the pooled effects at each stage. The effects of changes in air quality were analyzed through a difference-in-differences approach. Our results indicate that the absolute change of concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with aerodynamic diameter≤ 10 μm (PM₁₀₎ and≤ 2.5 μm (PM_2.5) decreased by up to 42%, 10%, 33%, and 15% (stage 5), respectively. The effects of SO₂ on deaths from CD and RD decreased by up to 2.76% and 1.43% (stage 3). The effects of NO₂ on mortality from NAD, CD, and RD decreased by up to 0.39%, 0.74%, and 0.37% (stage 5). The effects of PM₁₀ on death decreased by up to 0.11% (stage 3). The effects of PM_2.5 on deaths from CD and RD decreased by up to 0.33% and 0.13% (stage 5). The results indicate that continued improvements in air quality have reduced the acute impact of air pollutants on population health.

Extraction and determination of organic/inorganic pollutants in the ambient air of two cities located in metropolis of Tehran

In the present study, PM_2.5, volatile organic compounds (VOC), heavy metals, and polycyclic aromatic hydrocarbons (PAHs)-bonded PM_2.5 as well as asbestos fibers were investigated in two cities in the east of Tehran, Iran. To this end, 72 samples were collected from six stations located in the cities of Varamin and Pakdasht from March 2018 to March 2019. The concentration of BTEX compounds, PAHs, and heavy metals were measured using gas chromatography-flame ionization detector (GC-FID), gas chromatography-mass spectrometry (GC-Mas), and inductively coupled plasma atomic emission spectroscopy (ICP-OES), respectively. In addition, phase contrast microscopy (PCM) method was used to identify the properties of asbestos fibers. The results obtained from the present showed that the mean concentrations of PM_2.5, heavy metals, PAHs, BTEX, and asbestos fibers were 52.05 µg/m³, 319.08 ng/m³, 3.97 ng/m³, 40.58 µg/m³, and 2.84 f/L, respectively. In addition, the results obtained from PCA and heavy metals sources showed that transport fleets were the natural source of most of these pollutants. In case of PAH sources, transport and incineration of coal had the highest contribution in the emission. Furthermore, the risk assessment showed that most of the compounds have a higher risk value than the guideline value spatial distribution and also showed that stations close to airports, city terminals, and highways were more polluted than other parts of the city. Therefore, in order to have healthy air and with the least pollution, it seems necessary to formulate the necessary strategies in the cities of Varamin and Pakdasht.

Associations between prenatal multiple metal exposure and preterm birth: Comparison of four statistical models

BACKGROUND

Exposure to some heavy metals has been demonstrated to be related to the risk of preterm birth (PTB). However, the effects of multi-metal mixture are seldom assessed. Thus, we aimed to investigate the associations of maternal exposure to metal mixture with PTB, and to identify the main contributors to PTB from the mixture.

METHODS

The population in the nested case-control study was from a prospective cohort enrolled in Wuhan, China between 2012 and 2014. Eighteen metals were measured in maternal urine collected before delivery. Logistic regression, elastic net regularization (ENET), weighted quantile sum regression (WQSR), and Bayesian kernel machine regression (BKMR) were used to estimate the overall effect and identify important mixture components that drive the associations with PTB.

RESULTS

Logistic regression found naturally log-transformed concentrations of 13 metals were positively associated with PTB after adjusting for the covariates, and only V, Zn, and Cr remained the significantly positive associations when additionally adjusting for the 13 metals together. ENET identified 11 important metals for PTB, and V (β = 0.23) had the strongest association. WQSR determined the positive combined effect of metal mixture on PTB (OR: 1.44, 95%CI: 1.32, 1.57), and selected Cr and V (weighted 0.41 and 0.32, respectively) as the most weighted metals. BKMR analysis confirmed the overall mixture was positively associated with PTB, and the independent effect of V was the most significant. Besides, BKMR showed the non-linear relationships of V and Cu with PTB, and the potential interaction between Zn and Cu.

CONCLUSION

Applying different statistical models, the study found that exposure to the metal mixture was associated with a higher risk of PTB, and V was identified as the most important risk factor among co-exposed metals for PTB.

PM2.5-associated risk for cardiovascular hospital admission and related economic burdens in Beijing, China

BACKGROUND

The study of ambient air particulate matter (PM_2.5)-associated health and economic burdens of cardiovascular disease are crucial for air pollution control and disease prevention strategies. Quantified evidence remains inadequate.

OBJECTIVES

This study aimed to estimate the PM_2.5 associated risk in cardiovascular hospital admission as well as attributable health burdens and economic costs.

METHODS

A total of 2,202,244 hospital admission records of cardiovascular disease and six common clinical subtypes in Beijing were included. A time-stratified case-crossover design was applied to estimate the associations and the concentration-response curve. Then, the annual average additional hospital admissions, days of hospital stay, and hospital expenditures were evaluated from 2013 to 2017 and compared between 2017 and 2013.

RESULTS

The results showed that each 10 μg/m³ increase in previous-day PM_2.5 concentration was associated with a risk increase of 0.44% (95%CI: 0.40%, 0.47%) for cardiovascular disease, 0.66% (95%CI: 0.58%, 0.73%) for angina pectoris, 0.53% (95%CI: 0.39%, 0.66%) for chronic ischemic heart disease, 0.48% (95%CI: 0.34%, 0.63%) for myocardial infarction, 0.44% (95%CI: 0.29%, 0.60%) for hypertensive heart disease and 0.40% (95%CI: 0.27%, 0.52%) for ischemic stroke. There were 1938 PM_2.5 attributed additional hospital admissions, resulting in 21,668 additional days in hospital, along with 5527.12 and 1947.04 ten-thousand of additional total hospital cost and self-afforded cost, respectively. Compared with 2013, the above-mentioned four burdens decreased by 18.17%, 28.80%, 18.90% and 13.72% in 2017, respectively.

CONCLUSION

PM_2.5 exposure was significantly associated with substantial burdens of cardiovascular hospital admission and economic expenditures. The results highlight the necessity of continuous PM_2.5 control from the perspective of healthy and sustainable city development in urban China.

Prediction of PM2.5 concentrations at unsampled points using multiscale geographically and temporally weighted regression

Numerous statistical models have established the relationship between ambient fine particulate matter (PM_2.5, with an aerodynamic diameter of less than 2.5 μm) and satellite aerosol optical depth (AOD) along with other meteorological/land-related covariates. However, all the models assumed that all covariates affect the PM_2.5 concentration at the same scale, and none could provide a posterior uncertainty analysis at each regression point. Therefore, a multiscale geographically and temporally weighted regression (MGTWR) model was proposed by specifying a unique bandwidth for each covariate. However, the lack of a method for predicting values at unsampled points in the MGTWR model greatly restricts its corresponding application. Thus, this study developed a method for inferring unsampled points and used the posterior uncertainty assessment value to improve the model accuracy. With the aid of the high-resolution satellite multi-angle implementation of atmospheric correction (MAIAC) AOD product, daily PM_2.5 concentrations with a 1 km × 1 km resolution were generated over the Beijing-Tianjin-Hebei region between 2013 and 2019. The coefficient of determination (R²) and root mean square error (RMSE) of the fitted MGTWR results vary from 0.90 to 0.94 and from 10.66 to 25.11 μg/m³, respectively. The sample-based and site-based cross-validation R² and RMSE vary from 0.81 to 0.89 and from 14.40 to 34.43 μg/m³ respectively, demonstrating the effectiveness of the proposed inference method at unsampled points. With the uncertainty constraint, the sample-based and site-based validated MGTWR R² results for all years are further improved by approximately 0.02-0.04, demonstrating the effectiveness of the posterior uncertainty assessment constraint method. These results suggest that the inference method proposed in this study is promising to overcome the defects of the MGTWR model in inferring the prediction values at unsampled points and could consequently enhance the wide applications of MGTWR modeling.

Health Impact Attributable to Improvement of PM2.5 Pollution from 2014–2018 and Its Potential Benefits by 2030 in China

With the advancement of urbanization and industrialization, air pollution has become one of the biggest challenges for sustainable development. In recent years, ambient PM2.5 concentrations in China have declined substantially due to the combined effect of PM2.5 control and meteorological conditions. To this end, it is critical to assess the health impact attributable to PM2.5 pollution improvement and to explore the potential benefits which may be obtained through the achievement of future PM2.5 control targets. Based on PM2.5 and population data with a 1 km resolution, premature mortality caused by exposure to PM2.5 in China from 2014 to 2018 was estimated using the Global Exposure Mortality Model (GEMM). Then, the potential benefits of achieving PM2.5 control targets were estimated for 2030. The results show that premature mortality caused by PM2.5 pollution decreased by 22.41%, from 2,361,880 in 2014 to 1,832,470 in 2018. Moreover, the reduction of premature mortality in six major regions of China accounted for 52.82% of the national total reduction. If the PM2.5 control target can be achieved by 2030, PM2.5-related premature deaths will further decrease by 403,050, accounting for 21.99% of those in 2018. Among them, 87.02% of cities exhibited decreases in premature deaths. According to the potential benefits in 2030, all cities were divided into three types, of which type III cities should set stricter PM2.5 control targets and further strengthen the associated monitoring and governance. The results of this study provide a reference for the formulation of air pollution control policies based on regional differences.

Global PM2.5-attributable health burden from 1990 to 2017: Estimates from the Global Burden of disease study 2017

BACKGROUND

Long-term exposure to ambient and household particulate matter (PM2.5) causes death and health loss, and both are the leading risk factor to global disease burden. We assessed spatiotemporal trends of ambient and household PM2.5 attributable burdens across various diseases at the global, regional, and national levels from 1990 to 2017.

METHODS

Data on PM2.5-attributable disease burdens were extracted from the Global Burden of Disease (GBD) study 2017. Numbers and age-standardized rates (ASRs) of deaths, disability-adjusted life years (DALYs) and corresponding estimated annual percentage change (EAPC) were estimated by disease, age, sex, Socio-demographic Index (SDI), locations.

RESULTS

Exposure to PM2.5 contributed to 4.58 million deaths and 142.52 million DALYs globally in 2017, among which ambient PM2.5 contributed to 64.2% deaths and 58.3% DALYs. ASRs of deaths and DALYs in 2017 decreased to 59.62/10⁵ persons with an EAPC of -2.15 (95% CI: 2.21 to -2.09) and 1856.61/10⁵ persons with an EAPC of -2.58 (95% CI: 2.64 to -2.51), respectively compared to those in 1990. Ambient PM2.5-attributable Non-communicable diseases (NCDs) have dominated major concern in middle and low SDI countries especially in South Asia and East Asia, while household PM2.5-attributable lower respiratory infections (LRIs) still caused the largest burden in low SDI countries in Africa and Asia. Those under 5 and over 70 years old had the largest burdens in PM2.5 attributable LRI and NCDs, respectively.

CONCLUSION

In conclusion, ambient PM2.5-attributable NCDs have threatened public health in middle and low SDI countries, while household PM2.5-attributable LRI still caused the largest burden in low SDI countries. More positive strategies should be tailored to reduce PM2.5-attributable burdens considering specific settings globally.

The potential co-benefits for health, economy and climate by substituting raw coal with waste cooking oil as a winter heating fuel in rural households of northern China

The toxic emissions from coal combustion associated with domestic winter heating requirements are an important public health issue. Waste cooking oil (WCO) holds promise as a means of reducing pollutant emissions thereby improving human health with the co-benefit of decreasing climate-forcing gas emissions by avoiding the combustion of mineral coal. With an annual production of ~2.17 Mt of WCO in Northern China, it could be used to meet the winter heating demand of ~3.25 million rural households, offsetting ~9.83 Mt of raw coal consumption. Through the adoption of coal-to-WCO shift in rural regions of 15 provinces, approximately 15.0%, 15.6%, 15.9% and 13.7%, respectively of CO, PM_2.5, SO₂ and NO_X emissions would be eliminated. It is estimated that such a change would remove the respective contributions of these pollutants to the premature deaths of respectively, 63,400, 29,300, 173,00 and 31,300 rural residents. Such a positive health impact on the labor cohort would reduce the loss of labor supply and work time, as well as producing billions of RMB in economic benefits. WCO-based heating technology has the same effect on the reduction of GWC₁₀₀ value as other modern energy carriers while also being cheaper and sustainable, long term. Reducing household emissions by substituting raw coal with green energy is a vital strategy to support pathways for sustainable environment design. The results of this work for the coal-to-WCO shift can reinforce the support for coal phase-out in China.

Cleaner production practices at company level enhance the desire of employees to have a significant positive impact on society through work

Implementation of cleaner production practices (CPP), service quality (SQ) and corporate social responsibility (CSR) is often studied at organizational level. A number of studies on trio have reported it's significant impact on overall organizational performance and profitability across the globe. However, not much is studied about the individual level micro influence of these constructs on employee engagement (EE), organizational pride (OP), organizational identification (OI) and "desire to have a significant impact through work" (DSIW). Therefore, this study presents a comprehensive framework for assessing the impact of the implementation of CPP, SQ and CSR on EE, OP, OI and DSIW. Data collected from 320 non-managerial staff members employed at a garments manufacturing company in Pakistan was analyzed using partial least square (PLS) approach. Findings revealed that the implementation of CPP, SQ and CSR plays an important role in shaping EE, OP, OI and DSIW in the garments manufacturing industry. Further, it is found that the implementation of CPP has a non-significant impact on SQ. Additionally, results of the importance-performance map analysis (IPMA) have also confirmed that the implementation of CPP at company level has shown a highest importance and performance amongst all the latent constructs proposed as predictors of DSIW in the garments manufacturing industry. These findings are a step forward and unique contribution of this study in the domain of CPP, SQ, CSR, EE, OP, OI and DSIW.

Long-term exposure to PM2.5 and Children's lung function: a dose-based association analysis

Background

The current literature is still not consist regarding the effect of long-term exposure to PM2.5 and children’s lung function, partly due to inadequate or inaccurate exposure assessment. In this study, we aim to investigate the associations between long-term exposure to PM2.5, estimated as average daily dose (ADD), and lung function in school-age children.

Methods

We recruited 684 participants of 7–12 years old from the city of Lanzhou located in northwestern China. Participants underwent spirometric tests for lung function and responded to a questionnaire survey. Detailed information about individual air exposure and personal information were collected, including length of school hours, home address, age, gender, etc. Combining the spatial distribution of PM2.5 concentrations in the past 5 years and individual time-activity data, we estimated annual ADD for 5 years preceding the lung function tests and 5-year average ADD, respectively. We used multiple linear regression models to examine the associations between ADD values and lung function, controlling for a range of individual-level covariates.

Results

The 5-year average ADD among all the participants was 50.5 µg/kg-d, with higher values estimated for children living in the urban area than the suburban area, for boys than girls, and for children whose parents received a lower education attainment. We found that a 1 μg/kg-d increment in ADD of PM2.5 was associated with a 10.49 mL (95% CI: −20.47, −0.50) decrease in forced vital capacity (FVC) and a 7.68 mL (95% CI: −15.80, −0.44) decrease in forced exploratory volume in 1 second (FEV₁). Among the annual ADDs estimated for the preceding 5 years, the immediate past year prior to lung function measurement had the greatest effect on lung function. The effect was greater in girls than in boys. We found no associations between annual exposure of PM2.5 (instead of ADD) and lung function when defined concentration was used as an exposure variable.

Conclusions

Long-term PM2.5 exposure, when estimated as exposure dose averaged over a year or longer, was associated with statistically significant reductions in FVC and FEV1 in children of elementary-school age. Future studies may consider the use of individual-level dose estimates (as opposed to exposure concentrations) to improve the dose-response assessment.

Evaluating the Effect of Ambient Concentrations, Route Choices, and Environmental (in)Justice on Students' Dose of Ambient NO2 While Walking to School at Population Scales

The commuting microenvironment accounts for a large part of students' diurnal exposure to air pollution, especially in cities in developed countries where air pollution is caused predominantly by vehicle traffic. Accurate quantification of students' exposure and pollution dose during their commute from home to school requires their home addresses and details of the schools they attend. Such details are usually inaccessible or difficult to obtain at population scales due to privacy issues. Therefore, estimates of students' exposure to, and dose of, air pollution at population scales have to rely on simulated origins and destinations, which may bias the results. This contribution overcomes this limitation by quantifying students' terrain-based dosage of ambient nitrogen dioxide (NO₂) during their commute from home to school while walking along (a) the shortest-distance routes and (b) an alternative lowest-dose route. This is determined at population scales for students in Auckland, New Zealand using a rich dataset of observed home addresses and schools attended for 14,091 walking students. This study also determines the bias introduced when using simulated addresses (as opposed to observed data) to calculate the same result. Finally, we examine exposure inequalities among students of different socioeconomic backgrounds at school, at home, and during walking commutes. Results show that only 17.48% of students in the whole of Auckland can find alternative lowest-dose routes. The portion is higher (26%) in central Auckland because of its better road network connectivity. The trade-off analysis identifies that for only about 30% of students, a 1% increase in route length is associated with a >1% reduction in dosage if using the alternative lowest-dose route. Greater benefits were observed in suburban Auckland (a less-polluted area) than in central Auckland, which highlights the importance of taking an alternative lowest-dose route, especially for students whose shortest-distance routes overlap with or run parallel to an arterial road. The use of simulated addresses resulted in underestimates of both the length and reduced dosage of the alternative routes by up to a quarter in comparison with the results derived from the observed data. Limited evidence of exposure inequality based on commuter exposure was found, but patterns in the central city were opposite to those in the suburbs.

Spatiotemporal variability in long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across the Yangtze River Delta (YRD) region over 2010-2016: A multistage approach

The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM_2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM_2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM_2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM_2.5 and lung cancer mortality attributable to PM_2.5 across YRD during 2010-2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R² and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9-8 times higher than the other major cities (7-year average: 192,000 μg·people/m³·km²). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%-33% higher than in low-risk areas. There were 12,574-14,504 total lung cancer deaths attributable to PM_2.5, and lung cancer deaths in each square kilometer of urban areas were 7-13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment.

Assessing schoolchildren's exposure to air pollution during the daily commute - A systematic review

Air pollution is mostly caused by emissions from human activities, and exposure to air pollution is linked with numerous adverse human health outcomes. Recent studies have identified that although people only spend a small proportion of time on their daily commutes, the commuter microenvironment is a significant contributor to their total daily air pollution exposure. Schoolchildren are a particularly vulnerable cohort of the population, and their exposure to air pollution at home or school has been documented in a number of case studies. A few studies have identified that schoolchildren's exposure during commutes is linked with adverse cognitive outcomes and severe wheeze in asthmatic children. However, the determinants of total exposure, such as route choice and commute mode, and their subsequent health impacts on schoolchildren are still not well-understood. The aim of this paper is to review and synthesize recent studies on assessing schoolchildren's exposure to various air pollutants during the daily commute. Through reviewing 31 relevant studies published between 2004 and 2020, we tried to identify consistent patterns, trends, and underlying causal factors in the results. These studies were carried out across 10 commute modes and 12 different air pollutants. Air pollution in cities is highly heterogeneous in time and space, and commuting schoolchildren move through the urban area in complex ways. Measurements from fixed monitoring stations (FMSs), personal monitoring, and air quality modeling are the three most common approaches to determining exposure to ambient air pollutant concentrations. The time-activity diary (TAD), GPS tracker, online route collection app, and GIS-based route simulation are four widely used methods to determine schoolchildren's daily commuting routes. We found that route choices exerted a determining impact on schoolchildren's exposure. It is challenging to rank commute modes in order of exposure, as each scenario has numerous uncontrollable determinants, and there are notable research gaps. We suggest that future studies should concentrate on examining exposure patterns of schoolchildren in developing countries, exposure in the subway and trains, investigating the reliability of current simulation methods, exploring the environmental justice issue, and identifying the health impacts during commuting. It is recommended that three promising tools of smartphones, data fusion, and GIS should be widely used to overcome the challenges encountered in scaling up commuter exposure studies to population scales.

Stronger policy required to substantially reduce deaths from PM2.5 pollution in China

Air pollution kills nearly 1 million people per year in China. In response, the Chinese government implemented the Air Pollution Prevention and Control Action Plan (APPCAP) from 2013 to 2017 which had a significant impact on reducing PM_2.5 concentration. However, the health benefits of the APPCAP are not well understood. Here we examine the spatiotemporal dynamics of annual deaths attributable to PM_2.5 pollution (DAPP) in China and the contribution from the APPCAP using decomposition analysis. Despite a 36.1% increase in DAPP from 2000 to 2017, The APPCAP-induced improvement in air quality achieved substantial health benefits, with the DAPP in 2017 reduced by 64 thousand (6.8%) compared to 2013. However, the policy is unlikely to result in further major reductions in DAPP and more ambitious policies are required to reduce the health impacts of air pollution by 2030 and meet the United Nation's Sustainable Development Goal 3.