[Spatial-temporal Variation and Spatial Differentiation Geographic Detection of PM2.5 Concentration in the Shandong Province Based on Spatial Scale Effect].

PM2.5 remote sensing data was applied in this study, and Theil-Sen Median trend analysis and the Mann-Kendall significance test were utilized to analyze the temporal and spatial variation in PM2.5 in the Shandong Province from 2000 to 2021. The influencing power of the influencing factors on the spatial differentiation of PM2.5 concentration in the Shandong Province was detected at the provincial-city-county levels based on Geo-detector data. The results showed that:① on the temporal scale, the mean ρ(PM2.5)in the Shandong Province ranged from 38.15 to 88.63 µg·m-3 from 2000 to 2021, which was slightly higher than the secondary limit of inhalable particulate matter (35 µg·m-3) in the Ambient Air Quality Standards. On the interannual scale, 2013 was the peak year for the variation in ρ(PM2.5) with a value of 83.36 µg·m-3, according to which the trend of PM2.5 concentrations in the Shandong Province was divided into two phases:a continuous increase and a rapid decrease. On the seasonal scale, PM2.5 concentration presented the distribution characteristics of "low in summer and high in winter and moderate in spring and autumn" and the U-shaped change rule of first decreasing and then increasing. ② On the spatial scale, the PM2.5 concentration in the Shandong Province presented a spatial distribution pattern of "high in the west and low in the east." The areas with high PM2.5 concentration were distributed in the western area of the Shandong Province, whereas the areas with low PM2.5 concentration were distributed in the eastern peninsula region. The spatial variation in the changing trend of PM2.5 concentration showed significant spatial heterogeneity, and the extremely significant decrease was mainly distributed in the eastern peninsula region. ③ The results of factor detection showed that climate factor was an important factor affecting the spatial differentiation of PM2.5 concentration in the Shandong Province. Mean temperature had the highest influence on the spatial differentiation of PM2.5 concentration in the Shandong Province, with a q value of 0.512. Provincial-city-county multi-scale detection results showed that the influencing factors affecting the spatial differentiation of PM2.5 concentration and their influencing power differed at different spatial scales. At the provincial scale, mean temperature, sunshine duration, and slope were the main factors affecting the spatial differentiation of PM2.5 concentration. At the city level, precipitation, elevation, and relative humidity were the main factors affecting the spatial differentiation of PM2.5. At the county level, precipitation, mean temperature, and sunshine duration were the main factors affecting the spatial variation in PM2.5 concentration.

Association of exposure to artificial light at night during adolescence with blood pressure in early adulthood.

Artificial light at night (ALAN) is related to various diseases, such as cancer, obesity, and coronary heart disease. However, its impact on blood pressure in adolescents is not well understood. To investigate this, we conducted a cross-sectional study with a nationwide sample of college students in China, who were freshmen from four disperse universities during Sep. and Oct. 2018. Mean levels of ALAN at participants' residential addresses during 2013-2018 were estimated using time-varying satellite data. The association of the 6-y average of ALAN with blood pressure was estimated by using generalized linear mixed models. A total of 17 046 participants (18.2 ± 0.7 y of age, 46.79% female) from 2,412 counties and cities were included in the final analysis. After a full adjustment for potential confounders, ALAN was positively associated with systolic blood pressure (ß = 0.20, p = 0.032) and pulse pressure (ß = 0.28, p = 0.001), but there was no association between ALAN and diastolic blood pressure (ß = -0.08, p = 0.213). In the sensitivity analysis, the results consistent with the main analysis were observed. The blood pressure of males and those with a BMI ≤24 kg/m2 were more susceptible to ALAN exposure. Our findings highlight the importance of ALAN management for blood pressure control, particularly among male and normal-weight individuals.

Association of joint exposure to various ambient air pollutants during adolescence with blood pressure in young adulthood.

The association of various air pollutants exposure during adolescence with blood pressure (BP) in young adulthood is uncertain. We intended to evaluate the long-term association of individual and joint air pollutants exposure during adolescence with BP in young adulthood. This cross-sectional study of incoming students was conducted in five geographically disperse universities in China during September and October 2018. Mean concentrations of particulate matter with diameters ≤2.5 µm (PM2.5 ), ≤10 µm (PM10 ), nitrogen dioxides (NO2 ), carbon monoxide (CO), sulfur dioxide (SO2 ), and ozone (O3 ) at participants' residential addresses during 2013-2018 were collected from the Chinese Air Quality Reanalysis dataset. Generalized linear mixed models (GLM) and quantile g-computation (QgC) models were utilized to estimate the association between individual and joint air pollutants exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP). A total of 16,242 participants were included in the analysis. The GLM analyses showed that PM2.5 , PM10 , NO2 , CO, and SO2 were significantly positively associated with SBP and PP, while O3 was positively associated with DBP. The QgC analyses indicated that long-term exposure to a mixture of the six air pollutants had a significant positive joint association with SBP and PP. In conclusion, air pollutant co-exposure during adolescence may influence BP in young adulthood. The findings of this study emphasized the impacts of multiple air pollutants interactions on potential health and the need of minimizing pollution exposures in the environment.

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.

Light at night and cause-specific mortality risk in Mainland China: a nationwide observational study.

BACKGROUND: While epidemiological studies have found correlations between light at night (LAN) and health effects, none has so far investigated the impacts of LAN on population mortality yet. We aimed to estimate the relative risk for mortality from exposure to LAN in Mainland China. METHODS: This time-stratified case-crossover nationwide study used NPP-VIIRS to obtain daily LAN data of Mainland China between 2015 and 2019. The daily mortality data were obtained from the Disease Surveillance Point System in China. Conditional Poisson regression models were applied to examine the relative risk (RR) for mortality along daily LAN in each county, then meta-analysis was performed to combine the county-specific estimates at the national or regional level. RESULTS: A total of 579 counties with an average daily LAN of 4.39 (range: 1.02-35.46) were included in the main analysis. The overall RRs per 100 nW/cm2/sr increases in daily LAN were 1.08 (95%CI: 1.05-1.11) for all-cause mortality and 1.08 (95%CI: 1.05-1.11) for natural-cause mortality. A positive association between LAN and all natural cause-specific mortality was observed, of which the strongest effect was observed on mortality caused by neuron system disease (RR = 1.32, 95%CI: 1.14-1.52). The results were robust in both younger and old, as well as in males and females. The more pronounced effect of LAN was observed in median LAN-level regions. Combined with an exposure-response curve, our study suggests a non-linear association between LAN and mortality in China. CONCLUSIONS: Our study shows LAN is associated with mortality in China, particularly for neuron system disease-related mortality. These findings have important implications for public health policy establishment to minimize the health consequences of light pollution.

Long-term exposure to low levels of ambient UVB are associated with a decreased risk of moderate-to-severe acne: A retrospective cohort study in college students.

BACKGROUND: As a crucial component of solar radiation, the association between exposure to ambient ultraviolet (UV) radiation and acne remains unclear. METHODS: This was a multicenter retrospective cohort study of incoming college students in five universities of China. Previous exposure (6 years prior to enrollment) to different wavelengths of ambient UVs were obtained from public repositories by linking to individual hometown addresses. Logistic models were applied to assess the relationship between ambient UV exposure and acne. Subgroup analysis was conducted by sun protection behaviors and time of daily sun exposure. Overall effect and single effect of exposure to four different wavelengths of UVs (305, 310, 324, and 380 nm) were estimated by Bayesian kernel machine regression (BKMR). RESULTS: A total of 19,939 participants was included for analysis. Analysis in all participants showed a significant association between log-transformation levels of exposure to UV at 305 nm (log (UV 305 nm)) and acne (OR = 0.77, p = .021). The effect size was stronger in participants reporting no sun protection habit. Both UVs at 305 nm (OR = 0.51, p = .001) and 310 nm (OR = 0.50, p = .012) were associated a decreased risk of acne in participants reporting no sun protection habit. This inverse association was also observed in those exposed to low levels of UV (<1 h/day). The BKMR indicated consistent results that low levels of exposure to UVs combination and UVs at 305 and 310 nm were associated with a lower risk of acne. CONCLUSION: Long-term exposure to relatively low levels of ambient UVB are associated with a decreased risk of moderate-to-severe acne in college students.

Nitrogen dioxide and hospital length of stay and cost for systemic lupus erythematosus in Hunan, China.

BACKGROUND: Evidence of both epidemiological and clinical studies exploring the impact of nitrogen dioxide (NO2) on the systemic lupus erythematosus (SLE) disease activity have been contradictory. OBJECTIVES: To evaluate the association between short-term NO2 exposure and length of hospital stay (LOS) and hospital cost of SLE and estimate the burden of disease attributable to NO2 exposure. METHODS: We collected health data of SLE inpatients who were hospitalized at secondary and tertiary hospitals in Hunan province of China during 2017-2019. Daily ambient concentrations of air pollutants (O3, CO, NO2, SO2, PM2.5 and PM10) and other environmental factors were obtained from public repositories by linking to individual addresses and date of hospitalization. Mixed effect models were employed to assess the associations between LOS and hospital cost for SLE inpatients and NO2 exposures during the previous 1 to 21 days (lag1-lag21) before hospitalization. We further estimated excess LOS and hospital cost attributable to NO2 exposure according to China's and World Health Organization's air quality guideline (AQG) respectively. RESULTS: A total of 11,447 records from 221 hospitals were finally included in our study. After full adjustments, 1 µg/m3 increment of NO2 was significantly associated with 0.038 day increase in LOS (95%CI: 0.0159-0.0601, P = 0.0008) and 0.0384 thousand yuan increase in hospital cost (95%CI: 0.0017-0.0679, P = 0.0395) with a lagged effect of 7 days prior to admission. Based on the adjusted effects of lag7, controlling for short-term NO2 exposure according to AQG could avoid up to 1.47 thousand days of hospitalization and 1.35 million yuan of cost for SLE in Hunan province during 2017 to 2019. CONCLUSIONS: Excess LOS and substantial economic burden among SLE inpatients attributable to NO2 could be avoid if policies were implemented to reduce the exposure.

[Regionalization and Analysis of PM2.5 and O3 Synergetic Prevention and Control Areas Based on Remote Sensing Data].

Site-based air pollution monitoring data cannot support the regionalization of air pollution prevention and control areas. Faced with this problem, this study proposed a method of regionalizing synergetic prevention and control areas based on multi-source remote sensing data and GIS spatial statistical analysis methods and carried out quantitative analyses of PM2.5 and O3 air pollution in China from 2015 to 2020. The results showed that there was an obvious decrease in PM2.5 concentrations, and O3concentrations remained stable; PM2.5 pollution mostly occurred in autumn and winter, and O3 pollution occurred in spring and summer. A significant spatial inconsistency was shown between the change rate of PM2.5 and O3 concentrations, in which the proportions of PM2.5 decreasing and O3 increasing, PM2.5 and O3 both decreasing, PM2.5 and O3 both increasing, and PM2.5 increasing and O3 decreasing accounted for 38.34%, 35.12%, 15.24%, and 10.89%, respectively. The results also showed that the boundary of PM2.5 and O3 synergetic prevention and control areas was dynamic during 2015 and 2020, showing a trend of expanding from 2015 to 2018 and then becoming smaller after 2019. Generally, the scope of PM2.5 and O3 synergetic prevention and control areas was concentrated in "2+26" cities, Fenwei plain, north of the Yangtze River Delta, and Shandong. In contrast, the regional scopes of "PM2.5 first" and "O3 first" were relatively stable. Areas of "PM2.5 first" were mainly carried out in Liaoning-Jilin, Hubei-Hunan-Jiangxi, Chengdu-Chongqing, and Taklimakan-Hexi Corridor, whereas "O3 first" areas were mainly in specific regions of the Pearl River Delta, Yangtze River Delta, and surrounding areas of Bohai Bay. Remote sensing-based PM2.5 and O3 mapping has the advantages of full-coverage and fine spatial simulation, which can support the regionalization of synergetic prevention and control areas and implementation of policies.

Synergistic Effects between Ambient Air Pollution and Second-Hand Smoke on Inflammatory Skin Diseases in Chinese Adolescents.

Atopic dermatitis (AD), chronic hand eczema (CHE), and urticaria are common inflammatory skin diseases among adolescents and associated with air quality. However, the synergistic effects of ambient air pollution and second-hand smoke (SHS) have been unclear. We conducted a cross-sectional study including 20,138 Chinese college students where dermatological examinations and a questionnaire survey were carried out. A generalized linear mixed model was applied for the association between individualized exposure of O3, CO, NO2, SO2, PM2.5, and PM10 and the prevalence of inflammatory skin diseases. Interactions between air pollutants and SHS were analyzed. As a result, CO, NO2, SO2, PM2.5, and PM10 were positively correlated with the prevalence of AD, CHE, and urticaria. Higher frequency of SHS exposure contributed to increased probabilities of AD (p = 0.042), CHE (p < 0.001), and urticaria (p = 0.002). Of note, CO (OR: 2.57 (1.16−5.69) in third quartile) and NO2 (OR: 2.38 (1.07−5.27) in third quartile) had positive interactions with SHS for AD, and PM2.5 synergized with SHS for CHE (OR: 2.25 (1.22−4.15) for second quartile). Subgroup analyses agreed with the synergistic results. In conclusion, SHS and ambient air pollution are both associated with inflammatory skin diseases, and they have a synergistic effect on the prevalence of AD and CHE.

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.

Association of Long-term Ambient Fine Particulate Matter (PM2.5) and Incident CKD: A Prospective Cohort Study in China.

RATIONALE & OBJECTIVE: Increasing evidence has linked ambient fine particulate matter (ie, particulate matter no larger than 2.5 µm [PM2.5]) to chronic kidney disease (CKD), but their association has not been fully elucidated, especially in regions with high levels of PM2.5 pollution. This study aimed to investigate the long-term association of high PM2.5 exposure with incident CKD in mainland China. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 72,425 participants (age ≥18 years) without CKD were recruited from 121 counties in Hunan Province, China. EXPOSURE: Annual mean PM2.5 concentration at the residence of each participant derived from a long-term, full-coverage, high-resolution (1 × 1 km2), high-quality dataset of ground-level air pollutants in China. OUTCOMES: Incident CKD during the interval between the baseline examination of each participant (2005-2017) and the end of follow-up through 2018. ANALYTICAL APPROACH: Cox proportional hazards models were used to estimate the independent association of PM2.5 with incident CKD and the joint association of PM2.5 with temperature or humidity on the development of PM2.5-related CKD. Restricted cubic splines were used to model exposure-response relationships. RESULTS: Over a median follow-up of 3.79 (IQR, 2.03-5.48) years, a total of 2,188 participants with incident CKD were identified. PM2.5 exposure was associated with incident CKD with an adjusted hazard ratio of 1.71 (95% CI, 1.58-1.85) per 10-µg/m3 greater long-term exposure. Multiplicative interactions between PM2.5 and humidity or temperature on incident CKD were detected (all P < 0.001 for interaction), whereas an additive interaction was detected only for humidity (relative risk due to interaction, 3.59 [95% CI, 0.97-6.21]). LIMITATIONS: Lack of information on participants' activity patterns such as time spent outdoors. CONCLUSIONS: Greater long-term ambient PM2.5 pollution is associated with incident CKD in environments with high PM2.5 exposure. Ambient humidity has a potentially synergetic effect on the association of PM2.5 with the development of CKD. PLAIN-LANGUAGE SUMMARY: Exposure to a form of air pollution known as fine particulate matter (ie, particulate matter ≤2.5 µm [PM2.5]) has been linked to an increased risk of chronic kidney disease (CKD), but little is known about how PM2.5 affects CKD in regions with extremely high levels of PM2.5 pollution. This longitudinal cohort study in China investigates the effect of PM2.5 on the incidence of CKD and whether temperature or humidity interact with PM2.5. Our findings suggest that long-term exposure to high levels of ambient PM2.5 significantly increased the risk of CKD in mainland China, especially in terms of cumulative average PM2.5. The associations of PM2.5 and incident CKD were greater in high-humidity environments. These findings support the recommendation that reducing PM2.5 pollution should be a priority to decrease the burden of associated health risks, including CKD.

PM2.5 Concentration Exposure over the Belt and Road Region from 2000 to 2020.

Ambient fine particulate matter (PM2.5) can cause respiratory and heart diseases, which have a great negative impact on human health. While, as a fast-developing region, the Belt and Road (B&R) has suffered serious air pollution, more detailed information has not been revealed. This study aims to investigate the evolutionary relationships between PM2.5 air pollution and its population-weighted exposure level (PWEL) over the B&R based on satellite-derived PM2.5 concentration and to identify the key regions for exposure control in the future. For this, the study focused on the B&R region, covering 51 countries, ranging from developed to least developed levels, extensively evaluated the different development levels of PM2.5 concentrations during 2000-2020 by spatial-temporal trend analysis and bivariate spatial correlation, then identified the key regions with high risk under different levels of Air Quality Guidelines (AQG). Results show that the overall PM2.5 and PWEL of PM2.5 concentration remained stable. Developing countries presented with the heaviest PM2.5 pollution and highest value of PWEL of PM2.5 concentration, while least developed countries presented with the fastest increase of both PM2.5 and PWEL of PM2.5 concentration. Areas with a high level and rapid increase PWEL of PM2.5 concentration were mainly located in the developing countries of India, Bangladesh, Nepal, and Pakistan, the developed country of Saudi Arabia, and least developed countries of Yemen and Myanmar. The key regions at high risk were mainly on the Indian Peninsula, Arabian Peninsula, coastal area of the Persian Gulf, northwestern China, and North China Plain. The findings of this research would be beneficial to identify the spatial distributions of PM2.5 concentration exposure and offer suggestions for formulating policies for the prevention and control PM2.5 air pollution at regional scale by the governments.

Association of exposure to artificial light at night with atopic diseases: A cross-sectional study in college students.

The impact of artificial light at night (ALAN) exposure on health has become increasingly prominent. However, little is known about the effect of ALAN exposure on atopic diseases. In this study, a cross-sectional analysis of incoming students was conducted in 5 geographically disperse universities which locate in Changsha (south), Wuhan (central), Xiamen (east), Urumchi (west), and Hohhot (north), respectively. All incoming students who consented to participate were recruited, followed by a health examination and a questionnaire survey. Prevalent atopic diseases were diagnosed by clinicians. Mean ALAN (nanoWatts/cm2/sr) during their adolescence was obtained from the remote sensing observed nighttime light data matching with their residence information, which was obtained from survey. Mixed generalized linear models (log-binomial) were used to estimate the associations, in terms of prevalence ratio (PR) with 95% confidence interval (CI). A total of 20106 participants were included in the analysis. Based on previous work, we chose factors including socioeconomic status, behavioural factors, major air pollutants, and air climatic parameters for adjustment. After full adjustment, the PR for atopic diseases was 1.35 (95% CI: 1.27-1.42; P < 0.001). The effect size of ALAN was the largest for asthma (PR = 1.80; 95% CI: 1.48-2.19; P < 0.001), followed by atopic rhinitis (PR = 1.42; 95% CI: 1.33-1.51; P < 0.001), and atopic dermatitis (PR = 1.20; 95% CI: 1.06-1.35; P = 0.003). Subgroup analyses by covariates showed consistent results. This study revealed that exposure to ALAN during adolescence may contribute to a higher risk of atopic diseases in young adulthood.

Exposure to black carbon is associated with symptoms of depression: A retrospective cohort study in college students.

BACKGROUND: Previous studies have revealed a significant association of fine particulate matter (PM2.5) with emotional disorders. However, as a crucial component of PM2.5, little is known about the potential effect of exposure to black carbon (BC) on the symptoms of depression and anxiety. OBJECTIVES: To explore the associations of long-term exposure to BC during the past six years with the current symptoms of depression and anxiety in a group of incoming college students. METHODS: This was a retrospective cohort study of incoming students in five universities of China. Symptoms of depression and anxiety during the past two weeks were measured by the Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder Scale-2 (GAD-2), respectively. Levels of BC and other environmental factors during 2013 âˆ¼ 2018 (six years prior to the recruitment) was obtained from public repositories and linked to individual data by home addresses. Averagely daily dose of BC exposure was estimated according to the respiratory rate. Demographic and behavioral variables were collected through a questionnaire. The associations of BC with symptoms of depression and anxiety were estimated by mixed linear models adjusting for socioeconomic and behavioral characteristics, and the principal components of multiple environmental exposures. Subgroup analysis was conducted to assess the effect modification by covariates. Overall effect of environmental mixture was evaluated by weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR). RESULTS: A total of 20,079 participants was included in the current study. After adjustment for covariates, long-term BC exposure was significantly associated with symptoms of depression (ß = 0.17, P < 0.001) but not anxiety (ß = 0.07, P = 0.125). Effect modification by sex and parental educational level: BC was correlated with depressive symptoms in women (ß = 0.23, P < 0.001) but not in men (ß = 0.04, P = 0.581), and higher educational level was associated with decreased effect sizes of BC. Sensitivity analysis showed that the acute and short-term effects of BC on depression was consistent with its long-term exposure (ß varied from 0.18 to 0.20). WQS identified BC as the primary pollutant in association with symptoms of depression but not anxiety. BKMR identified no significant interaction between BC and other exposures. CONCLUSION: Exposure to BC is associated with symptoms of depression but not anxiety in college students, and the relationship is modified by sex and education.

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 (PM2.5, 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 PM2.5 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 PM2.5 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.

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

China has made great efforts towards air pollutant concentration control during the past five years, which has led to positive outcomes. However, air pollutant concentration focused efforts were considered separately from human exposure risk. And this might result in a misunderstanding that reducing exposure risk can only rely on the national level measures of air pollutant control. This study integrates the first Chinese survey of human activity patterns and the spatially continuous high-resolution PM2.5 concentration maps to reveal the spatial and temporal variations of China's air pollution exposure risk from 2013 to 2017. More importantly, the effects on risk reduction from multi-scale and multi-object perspectives (reductions of ambient PM2.5 concentrations by national or provincial measures and changes of individual behavior patterns by personal efforts) are deeply investigated. Results show that the reductions of PM2.5 concentration and associated reductions of exposure risk from 2013 to 2017 were 40% and 35.7%, respectively. They also showed that both the reduction of PM2.5 concentrations and change of personal behavior patterns were effective for risk reduction when China's total PM2.5 exposure risk was higher than 1.58. However, only individual behavior changes contributed to risk reduction for scenarios with state-level risk value below 1.58. For regional strategies, threshold values for PM2.5 exposure risk control differentiating national measures or personal efforts were spatially and temporally dependent. The role of personal behavior changes on PM2.5 exposure risk reduction was growing in these five years with concentration rapidly decreasing regions. The findings suggest that people-centered air pollution exposure risk prevention not only depends on government management for air pollution control, but also on individual changes of activity patterns. Efforts from the state and individuals are both essential for reducing air pollution exposure risk in China, especially growing individual efforts are needed in regions with the decreasing air pollutant concentrations in the coming future. Moreover, this study mainly discussed the PM2.5 exposure risk from the macroscopic perspective, the research at the microcosmic perspective is also needed in the further study.

Time series modeling of PM2.5 concentrations with residual variance constraint in eastern mainland China during 2013-2017.

Satellite-based mapping has been proven to be an effective method to reveal the spatiotemporal variations of PM2.5 distributions. However, most satellite AOD (aerosol optical depth) statistical models suffer from unstable accuracy over long time spans. This study thus aims to propose an accurate and stable method for PM2.5 concentration estimations in time series. Specifically, a three-step residual variance constraint method (RVCM) is developed to simulate PM2.5 concentrations from January 2013 to December 2017 with the aid of AODs and other auxiliary data. Results show that the five-year fitting R2 and cross-validation R2 of RVCMs improved from 0.77 to 0.88 and 0.71 to 0.84, respectively, compared to those models without residual variance constraint (WO-RVCM). Additionally, RVCM demonstrated more stable performance on time series simulation of PM2.5 concentrations than WO-RVCM, with the yearly fitting R2 of 0.89, 0.88, 0.85, 0.87 and 0.88, and corresponding cross validation R2 of 0.85, 0.84, 0.80, 0.82 and 0.83, respectively. Furthermore, accuracy verification of removed outliers in residual variance constraint modeling confirmed the credibility of RVCM in outliers' simulation compared to WO-RVCM models. Finally, RVCM-aided estimations of time series PM2.5 concentrations and associated premature deaths in the study area (east and southeast mainland China) revealed their total decrease rates were 35.21% and 21.57%, and excellent air quality days increased from 7% to 35%. These findings suggest that residual variance constraint is effective and could be a reliable solution to providing time series AOD-PM2.5 modeling with stable accuracy over long time spans.

Air pollution intervention and life-saving effect in China.

As a critical air pollutant, PM2.5 is proved to be associated with numerous adverse health impacts and pose serious challenges to human life. This situation is especially important for China as the most populous and one of the heaviest PM2.5 polluted country in the world. However, health burden estimations reported for China in previous studies may be biased due to the usage of PM2.5 concentrations at a coarsely spatial resolution, as well as the ignorance of the spatial discrepancies of parameters (e.g. respiratory rate) employed in the exposure-response function. This study therefore utilized a hybrid remote sensing-geostatistical approach to refine PM2.5 concentrations at 1 km resolution across mainland China from 2013 to 2017. Meanwhile, nationwide exposure parameters were for the first time introduced to weight the integrated exposure response (IER) function to calculate and spatially reallocate the corresponding PM2.5-attributable premature deaths at 1 km resolution. Results showed that annually averaged PM2.5 concentrations in mainland China decreased by 39.5%, from 59.1 µg/m3 in 2013 to 35.8 µg/m3 in 2017. Subsequently, PM2.5 attributable premature deaths reduced 12.6%, from 1.20 million (95% CI: 0.57; 1.71) in 2013 to 1.05 million (95% CI: 0.44; 1.44) in 2017. This declining trend was found in most parts of China except some areas in Xinjiang, Jilin, and Heilongjiang provinces. As a result, 214,821 (95% CI: 96,675; 302,897) life were saved with an estimated monetary value of US$ 210.14 billion (2011 values). However, it has to be acknowledged that, the central and northern China within priority areas of air pollution control were still experiencing high numbers of premature deaths due to the severe PM2.5 pollution and high-density population. But more worrying than these priority areas are those Harbin-Changchun Metropolitan Region, City Belt in Central Henan and Yangtze-Huaihe City Belt in non-priority areas, which also have been seriously suffering PM2.5 attributable premature deaths over 28, 000 cases per year. In conclusion, despite the huge gain in life-saving effects in China over the past five years with the help of air pollution intervention policy, future work on cleaner air and better human health is still strongly needed, especially in non-priority areas of air pollution control.

Degradation of diphenylamine by persulfate: Performance optimization, kinetics and mechanism.

The degradation of diphenylamine (DPA) in aqueous solution by persulfate is investigated. Effects of pH, persulfate concentration, ionic strength, temperature and catalytic ions Fe(3+) and Ag(+) on the degradation efficiency of DPA by persulfate are examined in batch experiments. The degradation of DPA by persulfate is found to follow the pseudo-first-order kinetic model. Increasing the reaction temperature or persulfate concentration may significantly accelerate the DPA degradation. Fe(3+) and Ag(+) ions can enhance the degradation of DPA, and Ag(+) ion is more efficient than Fe(3+) ion. However, the increase of either the pH value or ionic strength will decrease the rate of DPA degradation. N-Phenyl-4-quinoneimine, N-carboxyl-4-quinoneimine, 4-quinoneimine and oxalic acid are identified as the major intermediates of DPA degradation, and a primary pathway for the degradation of DPA is proposed. The degradation of DPA in surface water, groundwater and seawater is also tested by persulfate, and more than 90% of DPA can be degraded at room temperature in 45min at an initial concentration of 20mgL(-1).