The impact of winter heating on air pollution in China

Photosynthesis and stress response of coal fly ash on stem elongation in wheat

Coal is one of the primary energy sources in China and is widely used for electricity generation. Crops growing in overlapped areas of farmland and coal resources (OAFCR) suffer from coal fly ash stress, especially during stem elongation, which is a key stage that impacts wheat yield and is sensitive to environmental stress. As a primary food crop of China, wheat is essential for food security. However, the characteristics of wheat under the combined stress of fly ash and various heavy metals have not been sufficiently investigated. In this study, we explored the response of stem elongation in wheat to different levels of coal fly ash stress and determined the content of heavy metals (HMs) in wheat leaves. We found that with an increase in fly ash content, the Cu content in the shoots increased, while that in the roots decreased. Coal fly ash exposure reduced the proportions of Pb and Zn in the cytoderm, and the proportion of Cu in the soluble constituents decreased from 58.3% to 45.7%. Total chlorophyll, chlorophyll a, and chlorophyll b levels decreased significantly, whereas peroxidase (POD) and catalase (CAT) activities generally increased with increasing fly ash dose. Meanwhile, chloroplasts, mitochondria, and their internal structures were damaged, and the cell structures of leaves, such as the internal membrane structure, were damaged.

Incidence of central retinal artery occlusion peaks in winter season

Introduction

Stroke incidence exhibits seasonal trends, with the highest occurrences observed during winter. This study investigates the incidence of central retinal artery occlusion (CRAO), a stroke equivalent of the retina, and explores its monthly and seasonal variations, as well as potential associations with weather and ambient air pollutants.

Methods

A retrospective search of medical records spanning 15 years (January 2008-December 2022) was conducted at the University Eye Hospital Tübingen, Germany, focusing on diagnosed cases of CRAO. Incidences were evaluated on a monthly and seasonal basis (winter, spring, summer, fall). Weather data (temperature, precipitation, atmospheric pressure) and concentrations of ambient air pollutants [fine particulate matter (PM2.5), coarse particulate matter (PM10), nitrogen dioxide (NO2), and ozone (O3)], were analyzed for a potential association with CRAO incidence.

Results

Out of 432 patients diagnosed with CRAO between 2008 and 2022, significantly varying incidences were observed monthly (p = 0.025) and seasonally (p = 0.008). The highest rates were recorded in February and winter, with the lowest rates in June and summer. Concentrations of NO2, PM2.5 and lower ambient air temperature (average, minimum, maximum) showed significant correlations with CRAO incidence.

Discussion

This comprehensive 15-year analysis reveals a pronounced winter peak in CRAO incidence, with the lowest occurrences in summer. Potential associations between CRAO incidence and ambient air pollutants and temperature underscore the importance of considering seasonal trends and call for further investigations to elucidate contributing factors, potentially leading to targeted preventive strategies and public health interventions.

Trade-offs between cold protection and air pollution-induced mortality of China's heating policy

The winter heating policy in northern China was designed to safeguard households from the harsh subfreezing temperatures. However, it has inadvertently resulted in seasonal spikes in air pollution levels because of the reliance on coal as an energy source. While the loss of life years attributable to mortality from air pollution caused by winter heating has been estimated, the beneficial effect of protection from cold temperatures has not been assessed, primarily due to a lack of individual-level data linking these variables. Our study aims to address this research gap. We provide individual-level empirical evidence that quantifies the impact of protection from cold temperatures and air pollution on mortality, studying 5,334 older adults living around the Huai River during the period between 2000 and 2018. Our adjusted Cox-proportional hazard models show that winter heating was associated with a 22% lower mortality rate (95% CI: 16-28%). Individuals residing in areas without access to winter heating are subjected to heightened mortality risks during periods of cold temperatures. The protective effect is offset by a 27.8% rise attributed to elevated PM2.5 levels. Our results imply that the equilibrium between the effects of these two factors is achieved when PM2.5 concentration exceeds 24.3 µg/m3 (95% CI: 18.4-30.2). Our research suggests that while the existing winter heating policy significantly mitigates winter mortality by lessening the detrimental effects of cold temperatures, future air pollution reduction could provide further health benefits.

Explainable sequence-to-sequence GRU neural network for pollution forecasting

The goal of pollution forecasting models is to allow the prediction and control of the air quality. Non-linear data-driven approaches based on deep neural networks have been increasingly used in such contexts showing significant improvements w.r.t. more conventional approaches like regression models and mechanistic approaches. While such deep learning models were deemed for a long time as black boxes, recent advances in eXplainable AI (XAI) allow to look through the model's decision-making process, providing insights into decisive input features responsible for the model's prediction. One XAI technique to explain the predictions of neural networks which was proven useful in various domains is Layer-wise Relevance Propagation (LRP). In this work, we extend the LRP technique to a sequence-to-sequence neural network model with GRU layers. The explanation heatmaps provided by LRP allow us to identify important meteorological and temporal features responsible for the accumulation of four major pollutants in the air ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]), and our findings can be backed up with prior knowledge in environmental and pollution research. This illustrates the appropriateness of XAI for understanding pollution forecastings and opens up new avenues for controlling and mitigating the pollutants' load in the air.

Developing PM2.5 and PM10 prediction models on a national and regional scale using open-source remote sensing data

Clean air is the precursor to a healthy life. Air quality is an issue that has been getting under its well-deserved spotlight in the last few years. From a remote sensing point of view, the first Copernicus mission with the main purpose of monitoring the atmosphere and tracking air pollutants, the Sentinel-5P TROPOMI mission, has been widely used worldwide. Particulate matter of a diameter smaller than 2.5 and 10 μm (PM_2.5 and PM₁₀) significantly determines air quality. Still, there are no available satellite sensors that allow us to track them remotely with high accuracy, but only using ground stations. This research aims to estimate PM_2.5 and PM₁₀ using Sentinel-5P and other open-source remote sensing data available on the Google Earth Engine (GEE) platform for heating (December 2021, January, and February 2022) and non-heating seasons (June, July, and August 2021) on the territory of the Republic of Croatia. Ground stations of the National Network for Continuous Air Quality Monitoring were used as a starting point and as ground truth data. Raw hourly data were matched to remote sensing data, and seasonal models were trained at the national and regional scale using machine learning. The proposed approach uses a random forest algorithm with a percentage split of 70% and gives moderate to high accuracy regarding the temporal frame of the data. The mapping gives us visual insight between the ground and remote sensing data and shows the seasonal variations of PM_2.5 and PM₁₀. The results showed that the proposed approach and models could efficiently estimate air quality.

Air pollution and anti-social behaviour: Evidence from a randomised lab-in-the-field experiment

We conducted a pre-registered randomised lab-in-the-field online experiment in Beijing, China, to explore the relationship between acute air pollution and anti-social behaviour. Our novel experimental design exploits naturally occurring discontinuities in pollution episodes to mimic an experimental setting in which pollution exposure is exogenously manipulated, thus allowing us to identify a causal relationship. Participants were randomly assigned to be surveyed on either high pollution or low pollution days, thereby exogenously varying the degree of pollution exposure. In addition, a subset of individuals surveyed on the high-pollution days received an additional 'pollution alert' to explore whether providing air pollution warnings influences (protective) behaviour. We used a set of well-established incentivised economic games to obtain clean measures of anti-social behaviour, as well as a range of secondary outcomes which may drive the proposed pollution-behaviour relationship. Our results indicate that exposure to acute air pollution had no statistically significant effect on anti-social behaviour, but significantly reduced both psychological and physiological well-being. However, these effects do not remain statistically significant after adjusting for multiple hypothesis testing. We find no evidence that pollution affects cognitive ability, present bias, discounting, or risk aversion, four potential pathways which may explain the relationship between pollution and anti-social behaviour. Our study adds to the growing calls for purposefully designed and pre-registered experiments that strengthen experimental (as opposed to correlational or quasi-experimental) identification and thus allow causal insights into the relationship between pollution and anti-social behaviour.

The diminishing effects of winter heating on air quality in northern China

Cleaner winter heating has been promoted to abate the winter air pollution in northern China. Although improvements in air quality have been observed, the effectiveness and mechanism of cleaner heating measures on air quality have not been examined on the empirical ground. In this study, we estimate the annual effects of winter heating policy on air quality from 2014 to 2017 using a regression discontinuity design (RDD) and dynamic regression model. The results show that winter heating aggravates Air Quality Index (AQI). Specifically, the AQI raised by winter heating reduce from 85.3 in 2014 to 24.1 in 2017, indicating diminishing effects of winter heating with the implementation of clean heating measures. The heterogeneous characteristics of winter heating in terms of different pollutants and city scales are further quantified. The effects of clean heating are more evident for particulate pollutants (PM_2.5 and PM₁₀) than for SO₂, NO₂, CO and O₃. The promotion of clean heating is more effective in larger cities. These findings provided insights into the diminishing air pollution change with continuous advancement in clean heating policy and the heterogeneity among cities and pollutants should be taken into account when formulating future policies in response to energy transition and climate change.

Acute and chronic maternal exposure to fine particulate matter and prelabor rupture of the fetal membranes: A nation-wide survey in China

BACKGROUND

Prelabor rupture of the fetal membranes (PROM) is a major contributor to adverse perinatal outcomes. Some epidemiologic studies explored the association between maternal PM_2.5 exposure and PROM but failed to treat the labor induction and prelabor cesarean section as censored observations.

OBJECTIVE

We aimed to evaluated whether acute and chronic maternal ambient PM_2.5 exposure may increase the risk of PROM in China.

METHODS

This study was based on the China Labor and Delivery Survey, a nationwide multicenter investigation. Included in the current analysis were 45,879 singleton spontaneous births in 96 hospitals in mainland China from 2015 to 2017. Outcomes were PROM, preterm PROM (<37 weeks' gestation) and term PROM (≥37 weeks' gestation). Daily concentration of PM_2.5 at 1 km spatial resolution was estimated by gap-filling model. Generalized linear mixed model and mixed effects Cox model were applied to assess the associations of acute (from 0 to 4 days before delivery) and chronic (average gestational and trimester-specific) ambient PM_2.5 exposure with outcomes, respectively.

RESULTS

Significant associations were found between acute PM_2.5 exposures (per interquartile range increase) and the risk of preterm PROM (OR = 1.11; 95 % CI: 1.03, 1.19 for PM_2.5 on delivery day; OR = 1.10; 95 % CI: 1.02, 1.18 for PM_2.5 1 day before delivery) but not for term PROM. An interquartile range increase in PM_2.5 during the second trimester was associated with elevated risks of PROM (HR = 1.14; 95 % CI: 1.07, 1.22), preterm PROM (HR = 1.22; 95 % CI: 1.02, 1.45) and term PROM (HR = 1.13; 95 % CI: 1.06, 1.22), respectively. Women who were less educated, obese, or gave birth in a cold season appeared to be more sensitive to ambient PM_2.5 exposure.

CONCLUSION

Our findings suggest that both acute and chronic maternal exposures to ambient PM_2.5 during pregnancy are risk factors for PROM.

Comparison of PM2.5 and CO2 Concentrations in Large Cities of China during the COVID-19 Lockdown

Estimating the impacts on PM_2.5 pollution and CO₂ emissions by human activities in different urban regions is important for developing efficient policies. In early 2020, China implemented a lockdown policy to contain the spread of COVID-19, resulting in a significant reduction of human activities. This event presents a convenient opportunity to study the impact of human activities in the transportation and industrial sectors on air pollution. Here, we investigate the variations in air quality attributed to the COVID-19 lockdown policy in the megacities of China by combining in-situ environmental and meteorological datasets, the Suomi-NPP/VIIRS and the CO₂ emissions from the Carbon Monitor project. Our study shows that PM_2.5 concentrations in the spring of 2020 decreased by 41.87% in the Yangtze River Delta (YRD) and 43.30% in the Pearl River Delta (PRD), respectively, owing to the significant shutdown of traffic and manufacturing industries. However, PM_2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region only decreased by 2.01% because the energy and steel industries were not fully paused. In addition, unfavorable weather conditions contributed to further increases in the PM_2.5 concentration. Furthermore, CO₂ concentrations were not significantly affected in China during the short-term emission reduction, despite a 19.52% reduction in CO₂ emissions compared to the same period in 2019. Our results suggest that concerted efforts from different emission sectors and effective long-term emission reduction strategies are necessary to control air pollution and CO₂ emissions.

Combining Himawari-8 AOD and deep forest model to obtain city-level distribution of PM2.5 in China

PM_2.5 (fine particulate matter with aerodynamics diameter <2.5 μm) is the most important component of air pollutants, and has a significant impact on the atmospheric environment and human health. Using satellite remote sensing aerosol optical depth (AOD) to explore the hourly ground PM_2.5 distribution is very helpful for PM_2.5 pollution control. In this study, Himawari-8 AOD, meteorological factors, geographic information, and a new deep forest model were used to construct an AOD-PM_2.5 estimation model in China. Hourly cross-validation results indicated that estimated PM_2.5 values were consistent with the site observation values, with an R² range of 0.82-0.91 and root mean square error (RMSE) of 8.79-14.72 μg/m³, among which the model performance reached the optimum value between 13:00 and 15:00 Beijing time (R² > 0.9). Analysis of the correlation coefficient between important features and PM_2.5 showed that the model performance was related to AOD and affected by meteorological factors, particularly the boundary layer height. Deep forest can detect diurnal variations in pollutant concentrations, which were higher in the morning, peaked at 10:00-11:00, and then began to decline. High-resolution PM_2.5 concentrations derived from the deep forest model revealed that some cities in China are seriously polluted, such as Xi 'an, Wuhan, and Chengdu. Our model can also capture the direction of PM_2.5, which conforms to the wind field. The results indicated that due to the combined effect of wind and mountains, some areas in China experience PM_2.5 pollution accumulation during spring and winter. We need to be vigilant because these areas with high PM_2.5 concentrations typically occur near cities.

Non-stop industries were the main source of air pollution during the 2020 coronavirus lockdown in the North China Plain

Despite large decreases of emissions of air pollution during the coronavirus disease 2019 (COVID-19) lockdown in 2020, an unexpected regional severe haze has still occurred over the North China Plain. To clarify the origin of this pollution, we studied air concentrations of fine particulate matter (PM_2.5), NO₂, O₃, PM₁₀, SO₂, and CO in Beijing, Hengshui and Baoding during the lockdown period from January 24 to 29, 2020. Variations of PM_2.5 composition in inorganic ions, elemental carbon and organic matter were also investigated. The HYSPLIT model was used to calculate backward trajectories and concentration weighted trajectories. Results of the cluster trajectory analysis and model simulations show that the severe haze was caused mainly by the emissions of northeastern non-stopping industries located in Inner Mongolia, Liaoning, Hebei, and Tianjin. In Beijing, Hengshui and Baoding, the mixing layer heights were about 30% lower and the maximum relative humidity was 83% higher than the annual averages, and the average wind speeds were lower than 1.5 m s^-1. The concentrations of NO₃ ^-, SO₄ ^2-, NH₄ ⁺, organics and K⁺ were the main components of PM_2.5 in Beijing and Hengshui, while organics, K⁺, NO₃ ^-, SO₄ ^2-, and NH₄ ⁺ were the main components of PM_2.5 in Baoding. Contrary to previous reports suggesting a southerly transport of air pollution, we found that northeast transport caused the haze formation.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10311-021-01314-8.

Atmospheric deposition of inorganic nutrients to the Western North Pacific Ocean

We evaluated the potential impacts of atmospheric deposition on marine productivity and inorganic carbon chemistry in the northwestern Pacific Ocean (8-39°N, 125-157°E). The nutrient concentration in atmospheric total suspended particles decreased exponentially with increasing distance from the closest land-mass (Asia), clearly revealing anthropogenic and terrestrial contributions. The predicted mean depositional fluxes of inorganic nitrogen were approximately 34 and 15 μmol m^-2 d^-1 to the west and east of 140°E, respectively, which were at least two orders of magnitude greater than the inorganic phosphorus flux. On average, atmospheric particulate deposition would support 3-4% of the net primary production along the surveyed tracks, which is equivalent to ~2% of the dissolved carbon increment caused by the penetration of anthropogenic CO₂. Our observations generally fell within the ranges observed over the past 18 years, despite an increasing trend of atmospheric pollution in the source regions during the same period, which implies high temporal and spatial variabilities of atmospheric nutrient concentration in the study area. Continued atmospheric anthropogenic nitrogen deposition may alter the relative abundances of nitrogen and phosphorus.

Effects of Anthropogenic Emissions from Different Sectors on PM2.5 Concentrations in Chinese Cities

PM_2.5 pollution has gradually attracted people's attention due to its important negative impact on public health in recent years. The influence of anthropogenic emission factors on PM_2.5 concentrations is more complicated, but their relative individual impact on different emission sectors remains unclear. With the aid of the geographic detector model (GeoDetector), this study evaluated the impacts of anthropogenic emissions from different sectors on the PM_2.5 concentrations of major cities in China. The results indicated that the influence of anthropogenic emissions factors with different emission sectors on PM_2.5 concentrations exhibited significant changes at different spatial and temporal scales. Residential emissions were the dominant driver at the national annual scale, and the NO_X of residential emissions explained 20% (q = 0.2) of the PM_2.5 concentrations. In addition, residential emissions played the leading role at the regional annual scale and during most of the seasons in northern China, and ammonia emissions from residents were the dominant factor. Traffic emissions play a leading role in the four seasons for MUYR and EC in southern China, MYR and NC in northern China, and on a national scale. Compared with primary particulate matter, secondary anthropogenic precursors have a more important effect on PM_2.5 concentrations at the national or regional annual scale. The results can help to strengthen our understanding of PM_2.5 pollution, improve PM_2.5 forecasting models, and formulate more precise government control policy.

Evaluating the influence of land use and land cover change on fine particulate matter

Fine particulate matter (i.e. particles with diameters smaller than 2.5 microns, PM_2.5) has become a critical environmental issue in China. Land use and land cover (LULC) is recognized as one of the most important influence factors, however very fewer investigations have focused on the impact of LULC on PM_2.5. The influences of different LULC types and different land use and land cover change (LULCC) types on PM_2.5 are discussed. A geographically weighted regression model is used for the general analysis, and a spatial analysis method based on the geographic information system is used for a detailed analysis. The results show that LULCC has a stable influence on PM_2.5 concentration. For different LULC types, construction lands have the highest PM_2.5 concentration and woodlands have the lowest. The order of PM_2.5 concentration for the different LULC types is: construction lands > unused lands > water > farmlands >grasslands > woodlands. For different LULCC types, when high-grade land types are converted to low-grade types, the PM_2.5 concentration decreases; otherwise, the PM_2.5 concentration increases. The result of this study can provide a decision basis for regional environmental protection and regional ecological security agencies.

The Effects of Fireworks Discharge on Atmospheric PM2.5 Concentration in the Chinese Lunar New Year

Discharging fireworks during the Chinese Lunar New Year celebrations is a deep-rooted custom in China. In this paper, we analyze the effect of this cultural activity on PM2.5 concentration using both ground observations and satellite data. By combining remote sensing data, the problem of uneven spatial distribution of ground monitoring has been compensated, and the research time span has been expanded. The results show that the extensive firework displays on New Year's Eve lead to a remarkable increase in nationwide PM2.5 concentration, which were 159~223% of the average level, indicating the instantaneous effect far exceeds that of any other factor over the whole year. However, the averaged PM2.5 concentrations of the celebration period were 0.99~16.32 μg/m3 lower compared to the average values of the corresponding pre-celebration period and post-celebration period, indicating the sustained effect is not very significant. The implementation of firework prohibition policies can greatly reduce the instantaneous PM2.5 increase, but no obvious air quality improvement is observed over the entire celebration period. Combining these findings and the cultural significance of this activity, we recommend that this custom is actively maintained, using new technologies and scientific governance programs to minimize the negative effects.

Changes in children's respiratory morbidity and residential exposure factors over 25 years in Chongqing, China

Background

Respiratory morbidity and mortality during childhood remains a major challenge for global health. Due to the rapid economic development in Chongqing, we expect substantial temporal changes in respiratory health status and environmental risk factors in children. By leveraging a historical dataset, this study aims to assess the changes in prevalence of respiratory symptoms and diseases, residential exposure factors, and their associations in school-age children over a period of 25 years.

Methods

This study involved two cross-sectional surveys conducted in Chongqing with a 25-year interval (2017 vs. 1993). Purpose sampling was used to conduct questionnaire surveys on school-age children in both surveys. Information collected include children’s respiratory health outcomes, family residential exposures, demographic information, and parental respiratory disease history. The changes of residential exposures as well as demographics were determined by chi-square test. Odds ratios were calculated to compare the prevalence of children’s respiratory symptoms and diseases between the two periods. Associations between children’s respiratory outcomes and exposure indicators were assessed using multivariate logistic regressions.

Results

The majority of residential exposure indicators improved in 2017, including sleep in shared room, cooking with coal, poor kitchen ventilation, cooking frequency, and parental smoking. Compared to the 1993 study, the adjusted risk for children’s wheezing was lower (OR: 0.38, 95% CI: 0.29, 0.49), but the risk for bronchitis was higher (OR: 1.89, 95% CI: 1.54, 2.31) in the 2017 study. Poor kitchen ventilation and parental smoking were linked to an increased risk of children’s wheezing (OR: 1.39, 95% CI: 1.02, 1.90) and bronchitis (OR: 1.51, 95% CI: 1.02, 2.21), respectively, while heating in winter was linked to an increased risk of phlegm (OR: 1.40, 95% CI: 1.03, 1.90) and wheezing (OR: 1.47, 95% CI: 1.07, 2.01) in the 1993 study. However, these residential exposure factors were no longer associated with the children’s respiratory diseases in the 2017 study.

Conclusions

Our study found improvement of residential exposures in Chongqing, a decline of prevalence of children’s wheezing but an increase of that of bronchitis from 1993 to 2017. Poor kitchen ventilation, heating in winter, and parental smoking were significant risk factors in the 1993 survey but, with significantly reduced prevalence in 2017, were not significantly associated with children’s respiratory morbidity in the latter survey.

Pulverization in Cyber-Physical Systems: Engineering the Self-Organizing Logic Separated from Deployment

Emerging cyber-physical systems, such as robot swarms, crowds of augmented people, and smart cities, require well-crafted self-organizing behavior to properly deal with dynamic environments and pervasive disturbances. However, the infrastructures providing networking and computing services to support these systems are becoming increasingly complex, layered and heterogeneous—consider the case of the edge–fog–cloud interplay. This typically hinders the application of self-organizing mechanisms and patterns, which are often designed to work on flat networks. To promote reuse of behavior and flexibility in infrastructure exploitation, we argue that self-organizing logic should be largely independent of the specific application deployment. We show that this separation of concerns can be achieved through a proposed “pulverization approach”: the global system behavior of application services gets broken into smaller computational pieces that are continuously executed across the available hosts. This model can then be instantiated in the aggregate computing framework, whereby self-organizing behavior is specified compositionally. We showcase how the proposed approach enables expressing the application logic of a self-organizing cyber-physical system in a deployment-independent fashion, and simulate its deployment on multiple heterogeneous infrastructures that include cloud, edge, and LoRaWAN network elements.

Spatiotemporal patterns of PM2.5 elemental composition over China and associated health risks

Trace metals in atmospheric particulate matter (PM) are a serious threat to public health. Although pollution from toxic metals has been investigated in many Chinese cities, the spatial and temporal patterns in PM_2.5 remain largely unknown. Long-term PM_2.5 field sampling in 11 cities, combined with a systemic literature survey covering 51 cities, provides the first comprehensive database of 21 PM_2.5-bound trace metals in China. Our results revealed that PM_2.5 elemental compositions varied greatly, with generally higher levels in North China, especially for crustal elements. Pollution with Cr, As, and Cd was most serious, with 61, 38, and 16 sites, respectively, surpassing national standards, including some in rural areas. Local emissions, particularly from metallurgical industries, were the dominant factors driving the distribution in polluted cities such as Hengyang, Yuncheng, and Baiyin, which are mainly in North and Central China. Elevated As, Cd, and Cr levels in Yunnan, Guizhou Province within Southwest China were attributed to the high metal content of local coal. Diverse temporal trends of various elements that differed among regions indicated the complexity of emission patterns across the country. The results demonstrated high non-carcinogenic risks for those exposed to trace metals, especially for children and residents of heavily cities highly polluted with As, Pb, or Mn. The estimated carcinogenic risks ranged from 6.61 × 10^-6 to 1.92 × 10^-4 throughout China, with As being the highest priority element for control, followed by Cr and Cd. Regional diversity in major toxic metals was also revealed, highlighting the need for regional mitigation policies to protect vulnerable populations.

Estimation of hourly PM1 concentration in China and its application in population exposure analysis

Particulate pollution is closely related to public health. PM1 (particles with an aerodynamic size not larger than 1 μm) is much more harmful than particles with larger sizes because it goes deeper into the body and hence arouses social concern. However, the sparse and unevenly distributed ground-based observations limit the understanding of spatio-temporal distributions of PM1 in China. In this study, hourly PM1 concentrations in central and eastern China were retrieved based on a random forest model using hourly aerosol optical depth (AOD) from Himawari-8, meteorological and geographic information as inputs. Here the spatiotemporal autocorrelation of PM1 was also considered in the model. Experimental results indicate that although the performance of the proposed model shows diurnal, seasonal and spatial variations, it is relatively better than others, with a determination coefficient (R2) of 0.83 calculated based on the 10-fold cross validation method. Geographical map implies that PM1 pollution level in Beijing-Tianjin-Hebei is much higher than in other regions, with the mean value of ∼55 μg/m3. Based on the exposure analysis, we found about 75% of the population lives in an environment with PM1 higher than 35 μg/m3 in the whole study area. The retrieval dataset in this study is of great significance for further exploring the impact of PM1 on public health.

Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China

BACKGROUND

A great number of studies have confirmed that children are a particularly vulnerable population to air pollution.

METHODS

In the present study, 332,337 outpatient visits of 15 hospitals for respiratory diseases among children (0-13 years), as well as the simultaneous meteorological and air pollution data, were obtained from 2014 to 2016 in Lanzhou, China. The generalized additive model was used to examine the effects of air pollutants on children's respiratory outpatient visits, including the stratified analysis of age, gender and season.

RESULTS

We found that PM_2.5, NO₂ and SO₂ were significantly associated with the increased total respiratory outpatient visits. The increments of total respiratory outpatient visits were the highest in lag 05 for NO₂ and SO₂, a 10 μg/m³ increase in NO₂ and SO₂ was associated with a 2.50% (95% CI: 1.54, 3.48%) and 3.50% (95% CI: 1.51, 5.53%) increase in total respiratory outpatient visits, respectively. Those associations remained stable in two-pollutant models. Through stratification analysis, all air pollutants other than PM₁₀ were significantly positive associated with the outpatients of bronchitis and upper respiratory tract infection. Besides, both NO₂ and SO₂ were positively related to the pneumonia outpatient visits. PM_2.5 and SO₂ were significantly related to the outpatient visits of other respiratory diseases, while only NO₂ was positively associated with the asthma outpatients. We found these associations were stronger in girls than in boys, particularly in younger (0-3 years) children. Interestingly, season stratification analysis indicated that these associations were stronger in the cold season than in the transition or the hot season for PM₁₀, PM_2.5 and SO₂.

CONCLUSIONS

Our results indicate that the air pollution exposure may account for the increased risk of outpatient visits for respiratory diseases among children in Lanzhou, particularly for younger children and in the cold season.

Does integrated efficiency improvement of the heating industry matter for air quality in China?

Residential and industrial heating demand is increasing sharply in China. Coal as the main fuel for the heating industry exerts heavy burdens on China's environment. This paper aims to figure out with constant technological progress, whether the improvement of the total-factor unified integrated efficiency of the heating industry helps improve the air quality in 29 provinces in China over 2003-2014. It is found that the total-factor unified integrated efficiency has no correlation with the air quality. Whether in the north or south, technological catch-up in the heating industry in China is weak. Technical progress of the heating industry in the north is limited in improving the integrated efficiency. Besides, the effects of technological progress and efficiency improvements may be greatly reduced without reasonable energy price.

Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

The air pollution crisis in China has become a global concern due to its profound effects on the global environment and human health. To significantly improve the air quality, mandatory reductions were imposed on pollution emissions and energy consumption within the framework of the 11th and 12th Five Year Plans of China. This study takes the first step to quantify the implications of recent pollution control efforts for surface solar radiation (SSR), the primary energy source for our planet. The observed bias between satellite-retrieved and surface-observed SSR time series is proposed as a useful indicator for the radiative effects of aerosol changes. This is due to the fact that the effects of temporal variations of aerosols are neglected in satellite retrievals but well captured in surface observations of SSR. The implemented pollution control measures and actions have successfully brought back SSR by an average magnitude of 3.5 W m−2 decade−1 for the whole of China from 2008 onwards. Regionally, effective pollution regulations are indicated in the East Coast regions of South and North China, including the capital Beijing, with the SSR brightening induced by aerosol reduction of 7.5 W m−2 decade−1, 5.2 W m−2 decade−1, and 5.9 W m−2 decade−1, respectively. Seasonally, the SSR recovery in China mainly occurs in the warm seasons of spring and summer, with the magnitudes induced by the aerosol radiative effects of 5.9 W m−2 decade−1 and 4.7 W m−2 decade−1, respectively.

Urban-rural comparisons in health risk factor, health status and outcomes in Tianjin, China: A cross-sectional survey (2009-2013)

OBJECTIVE

To investigate the urban-rural disparities in health risk factors, health status and outcomes in Tianjin, China and to make an international comparison with urban-rural health in Australia.

DESIGN

A descriptive analytical cross-sectional survey.

SETTING

Mobile research teams conducted door-to-door field surveys of each house or department. The teams included local administrative staff and Tianjin Center for Disease Control and Prevention's epidemiologists, clinicians and laboratory technicians.

PARTICIPANTS

A total of 25 288 residents were interviewed and clinically observed, including 8583 urban residents and 16 705 rural residents.

MAIN OUTCOME MEASURE

Health risk factors, health status and outcomes.

RESULTS

The age structure in urban areas of Tianjin was growing older. Rural residents received less high school education and university education than did urban residents. Urban residents had higher medical insurance coverage and paid more out-of-pocket medical expenditures than did rural residents. The prevalence of smoking and the crude alcohol consumption rate were higher in rural areas than in urban areas. Rural residents had feelings of higher self-satisfaction concerning their health status than did urban residents. The prevalence of hypertensive disease, type 2 diabetes and heart, stroke and vascular diseases were significantly lower in rural areas than in urban areas. The incidence rate of serious injuries resulting from traffic accidents was significantly higher in rural areas than in urban areas.

CONCLUSION

Contrary to Australian urban-rural survey outcomes, the health status and outcomes of residents in rural areas of Tianjin seemed to be better than those of their counterparts in urban areas. The underlying determinants of these outcomes need to be explored with further study.

Contribution of Meteorological Conditions to the Variation in Winter PM2.5 Concentrations from 2013 to 2019 in Middle-Eastern China

Severe air pollution events accompanied by high PM2.5 concentrations have been repeatedly observed in Middle-Eastern China since 2013 and decreased in recent years. The reason for this caused widespread attention. The month of January was selected to represent the winter season annual changes in the winter PM2.5 and meteorological conditions—including the upper-air meridional circulation index (MCI), winds at 700 and 850 hPa levels and surface meteorology—from 2013 to 2019. These conditions were analyzed to study the contribution of meteorology changing to the annual PM2.5 changing on the regional scale. Results show that, based on values of upper-level MCI, the years 2014, 2015, 2017, and 2019 were defined as meteorology-haze years and the years 2016 and 2018 were defined as meteorology-clean years. A change in meteorological conditions may lead to a 26% change in PM2.5 concentration between 2014 and 2013 (two meteorology-haze years) and 16–20% changes in PM2.5 concentration between meteorology-haze years and meteorology-clean years. Changes in pollutant emissions may cause 21–47% changes in PM2.5 concentration between each two meteorology-haze years. A comparison of two meteorology-clean years and pollutant emissions in 2018 may be reduced by 40% compared with 2016. Overall, changes in emissions had a greater influence on changes in PM2.5 compared with meteorological conditions.

An Evolutionary Game Study of Clean Heating Promotion Mechanisms under the Policy Regulation in China

Recently, various Chinese provinces have greatly reduced their coal consumption due to new environmental protection policies. Because of these policies, the orderly development of the clean energy heating mode has been effectively promoted. As the problem of air pollution in the northern part of China is particularly prominent, adopting clean heating in winter is an important solution to control air pollution for those regions. However, there is a tricky balance to be struck between the government and the heating companies when it comes to using clean heating during winter. Therefore, it is crucial for the government and heating enterprises to research new strategies. Consequently, this paper carries out a comprehensive study on the multiple factors influencing the game relationship between the government and heating enterprises, and tries to set up a more general model for the theoretical analysis of mechanisms of clean heating promotion, as well as their numerical simulation. The research results show: (1) The initial possibilities available to government and heating enterprises have a significant impact on the final strategy choice for the heating system; (2) due to advantages such as increases in social benefits, subsidies, fines, and clean heating profits, as well as the lessening of traditional heating costs, and regardless of the decrease in traditional heating profits, it is possible for the government to adopt the promotion strategy; and (3) there are more opportunities for heating companies to pursue in order to implement clean heating strategies. In conclusion, this paper proposes valuable suggestions for the government and heating companies concerning clean heating in China.

Evidence on the Impact of Winter Heating Policy on Air Pollution and Its Dynamic Changes in North China

Environmental pollution, especially air pollution, is an alarming issue for the public, which is extensively debated among academic scholars. During the winter heating season, “smog” has become somewhat a normal phenomenon to local residents’ livelihood in northern China. Based on the daily air pollution data of regional cities in China from 2014 to 2016, and using a regression discontinuity design (RDD), the study finds that winter heating makes the air quality worse in the northern part of China. With the start of the winter heating, it increases the Air Quality Index (AQI) by 10.4%, particulate matter smaller than 10 μm (PM10) by 9.77%, particulate matter smaller than 2.5 μm (PM2.5) by 17.25%, CO by 9.84%, NO2 by 5.23%, and SO2 by 17.1%. Furthermore, dynamic changes demonstrate that air quality has gradually improved due to a series of heating policy changes implemented by the central government in recent years. Specifically, from 2014 to 2016, major indicators measuring the air pollution decrease dramatically, such as AQI by 92.36%, PM10 by 91.24%, PM2.5 by 84.06%, CO by 70.97%, NO2 by 52.76%, and SO2 by 17.15%.

Spatial distribution differences in PM2.5 concentration between heating and non-heating seasons in Beijing, China

Suffered from serious air pollution, Beijing, the capital of China, has implemented multiple measures to reduce the discharge of PM_2.5 (particulate matter with aerodynamic diameters of less than 2.5 μm). The average annual PM_2.5 concentration of Beijing has shown a continued decline in recent years. However, the improvement was not obvious during the heating season, which had heavier pollution than the non-heating season. Analyzing the spatial distribution of PM_2.5 concentrations during heating and non-heating seasons, as well as their spatial differences, is believed to benefit the study of spatial-temporal variation of air pollution and provide scientific reference for the control of air pollution in Beijing. In this study, land use regression (LUR) model was employed to simulate the spatial distribution of PM_2.5 concentrations in Beijing during heating and non-heating seasons in 2015. The spatial distribution of the concentration difference between heating and non-heating seasons was analyzed, and the influencing factors were also examined. The results showed that: (1) PM_2.5 concentrations during heating and non-heating seasons, as well as their differences, were clearly at a maximum in the south and east of Beijing and at a minimum in the north and west; (2) the area with the biggest concentration difference was situated in a suburban area to the south and east, as well as in outer suburbs to the southeast and northwest; and (3) wind speed, area of transport land and industrial-mining-warehouse land were the main influence factors for the PM_2.5 concentration difference in the central, eastern and southern area. Heating activity was not the only cause for the increased PM_2.5 concentration during the heating season, vehicle emission, industrial discharge and regional transport of pollutants also played varied roles in PM_2.5 pollution in different area.

Mitigation pathways of air pollution from residential emissions in the Beijing-Tianjin-Hebei region in China

Air pollution is one of the most harmful consequences of China's rapid economic development and urbanization. Particularly in the Beijing-Tianjin-Hebei (BTH) regions, particulate matter concentrations have consistently exceeded the national air quality standards. Over the last years, China implemented ambitious measures to reduce emissions from the power, industry and transportation sectors, with notable success during the 11th and 12th Five Year Plan (FYP) periods. However, such strategies appear to be insufficient to reduce the ambient PM_2.5 concentration below the National Air Quality Standard of 35 μg m^-3 across the BTH region within the next 15 years. We find that a comprehensive mitigation strategy for the residential sector in the BTH region would deliver substantial air quality benefits. Beyond the already planned expansion of district heating and natural gas distribution in urban centers and the foreseen curtailment of coal use for households, such a strategy would redirect some natural gas from power generation units towards the residential sector. Rural households would replace biomass for cooking by liquid petroleum gas (LPG) and electricity, and substitute coal for heating by briquettes. Jointly, these measures could reduce the primary PM_2.5 and SO₂ emissions by 28% and 11%, respectively, and the population-weighted PM_2.5 concentrations by 13%, i.e., from 68 μg m^-3 to 59 μg m^-3. We estimate that such a strategy would reduce premature deaths attributable to ambient and indoor air pollution by almost one third.

Spatiotemporal Pattern of Fine Particulate Matter and Impact of Urban Socioeconomic Factors in China

Frequent hazy weather has been one of the most obvious air problems accompanying China's rapid urbanization. As one of the main components of haze pollution, fine particulate matter (PM2.5), which severely affects environmental quality and people's health, has attracted wide attention. This study investigated the PM2.5 distribution, changing trends and impact of urban factors based on remote-sensing PM2.5 concentration data from 2000 to 2015, combining land-use data and socioeconomic data, and using the least-squares method and structural equation model (SEM). The results showed that the high concentration of PM2.5 in China was mainly concentrated in the eastern part of China and Sichuan Province. The trends of the PM2.5 concentration in eastern part and Northeast China, Sichuan, and Guangxi Provinces were positive. Meanwhile, the ratios of increasing trends were strongest in built-up land and agricultural land, and the decreasing trends were strongest in forest and grassland, but the overall trends were still growing. The SEM results indicated that economic factors contributed most to PM2.5 pollution, followed by demographic factors and spatial factors. Among all observed variables, the secondary industrial GDP had the highest impact on PM2.5 pollution. Based on the above results, PM2.5 pollution remains an important environmental issue in China at present and even in the future. It is necessary for decision-makers to make actions and policies from macroscopic and microscopic, long-term and short-term aspects to reduce pollution.

Spatiotemporal patterns of aerosol optical depth throughout China from 2003 to 2016

With China's rapid economic growth, particle pollution, especially fine particulate matter (PM_2.5), which is known to have adverse health impacts, has become an increasingly serious issue. Satellite aerosol optical depth (AOD), an important physical property of aerosol particles, can serve as a proxy for investigating particle pollution because it can provide observations with comprehensive spatial and temporal coverage compared with ground-level measurements. This study used an improved 14-year high-resolution AOD dataset to examine the spatial characteristics and temporal dynamics of the dominant pollutants in China from 2003 to 2016 using advanced statistical methods. The improved AOD dataset combines the Moderate Resolution Imaging Spectroradiometer (MODIS) 3-km dark target AOD and 10-km deep blue AOD datasets, which enables a comparison of aerosol loading between eastern and western China. Pixel-based analysis indicates a significant difference between eastern and western China: high AOD values were generally observed in the east with a notable decrease, while low aerosol loadings were found in western China with no distinct change. The most particle polluted areas were the North China Plain, Hubei-Hunan region, Sichuan Basin, and Guangxi-Guangdong region in eastern China and western Qinghai and Tarim Basin in western China, with changes in the national AOD average center shifting to the northwest from 2013 to 2016. The impact factor analysis based on geographically weighted regression indicates that the effect of topography on the spatial characteristics of AOD is negative and more important in eastern China, which has low elevations. Built-up areas significantly exacerbate air pollution in the areas between eastern and western China, and there is no apparent AOD-vegetation relation dominates the country. This study thus provides a comprehensive understanding of the spatiotemporal variations of particle concentrations and can facilitate environmental management, policies to alleviate particle pollution, and health risk assessment studies.

Nonlabor Income and Age at Marriage: Evidence From China's Heating Policy

We exploit China’s heating policy to investigate how nonlabor income affects marriage. From the mid-1950s, the policy gave substantial subsidies to urban residents north of the Huai River. Applying geographic regression discontinuity, we find that with the policy, urban men in the north married 15 months earlier than men in the south. The difference is substantial given that the average age at first marriage is 24.9 years for urban men in the south. The effect is larger for later birth cohorts, which is consistent with the progressive implementation of the policy. The effect is smaller among women, consistent with women having less power in the household than men. There is no effect among rural residents, who did not benefit from the heating policy.

Stochastic Modelling of Air Pollution Impacts on Respiratory Infection Risk

The impact of air pollution on people's health and daily activities in China has recently aroused much attention. By using stochastic differential equations, variation in a 6 year long time series of air quality index (AQI) data, gathered from air quality monitoring sites in Xi'an from 15 November 2010 to 14 November 2016 was studied. Every year the extent of air pollution shifts from being serious to not so serious due to alterations in heat production systems. The distribution of such changes can be predicted by a Bayesian approach and the Gibbs sampler algorithm. The intervals between changes in a sequence indicate when the air pollution becomes increasingly serious. Also, the inflow rate of pollutants during the main pollution periods each year has an increasing trend. This study used a stochastic SEIS model associated with the AQI to explore the impact of air pollution on respiratory infections. Good fits to both the AQI data and the numbers of influenza-like illness cases were obtained by stochastic numerical simulation of the model. Based on the model's dynamics, the AQI time series and the daily number of respiratory infection cases under various government intervention measures and human protection strategies were forecasted. The AQI data in the last 15 months verified that government interventions on vehicles are effective in controlling air pollution, thus providing numerical support for policy formulation to address the haze crisis.

Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China's Megacities

Urban form is increasingly being identified as an important determinant of air pollution in developed countries. However, the effect of urban form on air pollution in developing countries has not been adequately addressed in the literature to date, which points to an evident omission in current literature. In order to fill this gap, this study was designed to estimate the impacts of urban form on air pollution for a panel made up of China's five most rapidly developing megacities (Beijing, Tianjin, Shanghai, Chongqing, and Guangzhou) using time series data from 2000 to 2012. Using the official Air Pollution Index (API) data, this study developed three quantitative indicators: mean air pollution index (MAPI), air pollution ratio (APR), and continuous air pollution ratio (CAPR), to evaluate air pollution levels. Moreover, seven landscape metrics were calculated for the assessment of urban form based on three aspects (urban size, urban shape irregularity, and urban fragmentation) using remote sensing data. Panel data models were subsequently employed to quantify the links between urban form and air pollution. The empirical results demonstrate that urban expansion surprisingly helps to reduce air pollution. The substitution of clean energy for dirty energy that results from urbanization in China offers a possible explanation for this finding. Furthermore, urban shape irregularity positively correlated with the number of days with polluted air conditions, a result could be explained in terms of the influence of urban geometry on traffic congestion in Chinese cities. In addition, a negative association was identified between urban fragmentation and the number of continuous days of air pollution, indicating that polycentric urban forms should be adopted in order to shorten continuous pollution processes. If serious about achieving the meaningful alleviation of air pollution, decision makers and urban planners should take urban form into account when developing sustainable cities in developing countries like China.

Health Effects of Air Pollution in China

Background Rapid economic and social development in China has resulted in severe air pollution and consequent adverse impacts on society. The health effects of air pollution have been widely studied. Methods Using information from the China Health and Retirement Longitudinal Study (CHARLS) database, we established a hierarchical linear model combining pollution and socioeconomic and psychosocial variables to examine the effects of air pollution on public health in China. Local air pollution was characterized in multiple dimensions. Results The relationship of health to its determinants greatly differed between Eastern and Central/Western China. Higher education, higher income level, better life satisfaction, and long-term marriage were significantly associated with better health status among Chinese. In addition, regional healthcare resources were positively associated with the health of residents. As indicated by the hierarchical model with health as dependent variable, in Central/Western China, longest duration of good air quality in spring/summer was positively associated with health (estimated coefficient = 0.067, standard error = 0.026), while the mean Air Quality Index (AQI) in autumn/winter was inversely associated with health (estimated coefficient = −0.082, standard error = 0.031). Good air quality in the current study is defined as daily average AQI less than 35. Conclusions Duration (in days) of acceptable air quality was particularly important for improving public health. Future policies should target increased duration of good air quality while managing air pollution by controlling or decreasing severe air pollution.

Characterizing isotopic compositions of TC-C, NO3--N, and NH4+-N in PM2.5 in South Korea: Impact of China's winter heating

The origin of PM_2.5 has long been the subject of debate and stable isotopic tools have been applied to decipher. In this study, weekly PM_2.5 samples were simultaneously collected at an urban (Seoul) and rural (Baengnyeong Island) site in Korea from January 2014 through February 2016. The seasonal variation of isotopic species showed significant seasonal differences with sinusoidal variation. The isotopic results implied that isotope species from Baengnyeong were mostly originated from coal combustion during China's winter heating seasons, whereas in summer, the isotopic patterns observed that were more likely to be from marine. In Seoul, coal combustion related isotopic patterns increased during China's winter heating period while vehicle related isotopic patterns were dominated whole seasons by default. Therefore, aerosol formation was originated from long-range transported coal combustion-related NO_x by vehicle-related NH₃ in Seoul. δN-NH₄⁺ in Seoul showed highly enriched ¹⁵N compositions in all seasons, indicating that NH₃ from vehicle emission is the important source of NH₄⁺ in PM_2.5 in Seoul. In addition, Baengnyeong should be consistently considered as a key region for observing the changes of isotopic features depend on the contribution of individual emissions to the atmospheric as a result of the reduction of coal consumption in China.

The contribution of socioeconomic factors to PM2.5 pollution in urban China

PM_2.5 pollution poses severe health risks to urban residents in low and middle-income countries. Existing studies have shown that the problem is affected by multiple socioeconomic factors. However, the relative contribution of these factors is not well understood, which sometimes leads to controversial controlling measures. In this study, we quantified the relative contribution of different socioeconomic factors, including the city size, industrial activities, and residents' activities, to PM_2.5 pollution in urban China between 2014 and 2015 by using structural equation model (SEM). Our results showed that industrial activities contributed more to PM_2.5 pollution than other factors. The city size and residents' activities also had significant impacts on PM_2.5 pollution. The combined influence of all socioeconomic factors could explain between 44% and 48% of variation in PM_2.5 pollution, which indicated the existence of influences from other factors such as weather conditions and outside sources of pollutants. Findings from our study can contribute to a more comprehensive understanding of the socioeconomic causes of PM_2.5 pollution.

Spatiotemporal Variations and Driving Factors of Air Pollution in China

In recent years, severe and persistent air pollution episodes in China have drawn wide public concern. Based on ground monitoring air quality data collected in 2015 in Chinese cities above the prefectural level, this study identifies the spatiotemporal variations of air pollution and its associated driving factors in China using descriptive statistics and geographical detector methods. The results show that the average air pollution ratio and continuous air pollution ratio across Chinese cities in 2015 were 23.1 ± 16.9% and 16.2 ± 14.8%. The highest levels of air pollution ratio and continuous air pollution ratio were observed in northern China, especially in the Bohai Rim region and Xinjiang province, and the lowest levels were found in southern China. The average and maximum levels of continuous air pollution show distinct spatial variations when compared with those of the continuous air pollution ratio. Monthly changes in both air pollution ratio and continuous air pollution ratio have a U-shaped variation, indicating that the highest levels of air pollution occurred in winter and the lowest levels happened in summer. The results of the geographical detector model further reveal that the effect intensity of natural factors on the spatial disparity of the air pollution ratio is greater than that of human-related factors. Specifically, among natural factors, the annual average temperature, land relief, and relative humidity have the greatest and most significant negative effects on the air pollution ratio, whereas human factors such as population density, the number of vehicles, and Gross Domestic Product (GDP) witness the strongest and most significant positive effects on air pollution ratio.

Assessment of PM2.5 concentrations and exposure throughout China using ground observations

Exposure to PM2.5 results in negative effects on human health. However, PM2.5 exposure at the national scale is poorly known for China owing to limited spatial and temporal PM2.5 concentration data. In this study, we present analyses of PM2.5 exposure throughout China using high-resolution temporal and spatial ground-level PM2.5 data from 2015. Our results indicated that the annual mean PM2.5 concentration was 52.81μg/m³, and that the highest annual mean PM2.5 concentrations primarily appeared in the North China Plain. We also found the lowest and highest monthly mean PM2.5 concentrations appeared in August and January, respectively, while the lowest and highest diurnal mean PM2.5 concentrations occurred at 16:00 and 10:00, respectively. Moreover, comparisons to data from 2013 indicated that the annual mean PM2.5 concentrations decreased by 12.31% from 2013 to 2015, which was likely due to the implementation of environmental protection laws in early 2015. Our findings provide new insights, for not only studies of PM2.5 exposure and human health, but also to inform the implementation of national and regional air pollution reduction policies.

Visibility-Based PM2.5 Concentrations in China: 1957-1964 and 1973-2014

China established ground PM_2.5 monitoring network in late 2012 and hence the long-term and large-scale PM_2.5 data were lacking before 2013. In this work, we developed a national-scale spatiotemporal linear mixed effects model to estimate the long-term PM_2.5 concentrations in China from 1957 to 1964 and from 1973 to 2014 using ground visibility monitoring data as the primary predictor. The overall model-fitting and cross-validation R² is 0.72 and 0.71, suggesting that the model is not overfitted. Validation beyond the model year (2014) indicated that the model could accurately estimate historical PM_2.5 concentrations at the monthly (R² = 0.71) level. The historical PM_2.5 estimates suggest that air pollution is not a new environmental issue that occurs in the recent decades but a problem existing in a longer time before 1980. The PM_2.5 concentrations have reached 60-80 μg/m³ in the north part of North China Plain during 1950s-1960s and increased to generally higher than 90 μg/m³ during 1970s. The results also show that the entire China experienced an overall increasing trend (0.19 μg/m³/yr, P < 0.001) in PM_2.5 concentrations from 1957 to 2014 with fluctuations among different periods. This paper demonstrated visibility data allow us to understand the spatiotemporal characteristics of PM_2.5 pollution in China in a long-term.

Differential pulmonary effects of wintertime California and China particulate matter in healthy young mice

Airborne particulate matter (PM) is associated with adverse cardiorespiratory effects. To better understand source-orientated PM toxicity, a comparative study of the biological effects of fine PM (diameter≤2.5μm, PM_2.5) collected during the winter season from Shanxi Province, China, and the Central Valley, California, United States, was conducted. The overarching hypothesis for this study was to test whether the chemical composition of PM on an equal mass basis from two urban areas, one in China and one in California, can lead to significantly different effects of acute toxicity and inflammation in the lungs of healthy young mice. Male, 8-week old BALB/C mice received a single 50μg dose of vehicle, Taiyuan PM or Sacramento PM by oropharyngeal aspiration and were sacrificed 24h later. Bronchoalveolar lavage, ELISA and histopathology were performed along with chemical analysis of PM composition. Sacramento PM had a greater proportion of oxidized organic material, significantly increased neutrophil numbers and elevated CXCL-1 and TNF-α protein levels compared to the Taiyuan PM. The findings suggest that Sacramento PM_2.5 was associated with a greater inflammatory response compared to that of Taiyuan PM_2.5 that may be due to a higher oxidice. Male, 8-week old BALB/C mice received a single 50μg dose of vehicle, Taiyuan PM or Sacramento PM by oropharyngeal aspiration and were sacrificed 24h later. Bronchoalveolar lavage, ELISA and histopathology were performed along with chemical analysis of PM composition. Sacramento PM had a greater proportion of oxidized organic material, significantly increased neutrophil numbers and elevated CXCL-1 and TNF-α protein levels compared to the Taiyuan PM. The findings suggest that Sacramento PM_2.5 was associated with a greater inflammatory response compared to that of Taiyuan PM_2.5 that may be due to a higher oxidized state of organic carbon and copper content.

Cancer risk from polycyclic aromatic compounds in fine particulate matter generated from household coal combustion in Xuanwei, China

Polycyclic aromatic hydrocarbons (PAHs) and their polar derivatives (oxygenated PAHs: OPAHs and azaarenes: AZAs) were characterized in fine particulates (PM_2.5) emitted from indoor coal combustion. Samples were collected in Xuanwei (Yunnan Province), a region in China with a high rate of lung cancer. A sample from the community with the highest mortality contained the highest total concentration of PAHs, OPAHs and AZAs and posed the highest excess cancer risk from a lifetime of inhaling fine particulates. Positive correlations between total carbonyl-OPAHs, total AZAs and total PAHs implied that the emissions were dependent on similar factors, regardless of sample location and type. The calculated cancer risk ranged from 5.23-10.7 × 10^-3, which is higher than the national average. The risk in each sample was ∼1-2 orders of magnitude higher than that deemed high risk, suggesting that the safety of these households is in jeopardy. The lack of potency equivalency factors for the PAH derivatives could possibly have underestimated the overall cancer risk.

The Regional Impacts of Cooking and Heating Emissions on Ambient Air Quality and Disease Burden in China

Exposure to air pollution is a major risk factor globally and particularly in Asia. A large portion of air pollutants result from residential combustion of solid biomass and coal fuel for cooking and heating. This study presents a regional modeling sensitivity analysis to estimate the impact of residential emissions from cooking and heating activities on the burden of disease at a provincial level in China. Model surface PM2.5 fields are shown to compare well when evaluated against surface air quality measurements. Scenarios run without residential sector and residential heating emissions are used in conjunction with the Global Burden of Disease 2013 framework to calculate the proportion of deaths and disability adjusted life years attributable to PM2.5 exposure from residential emissions. Overall, we estimate that 341 000 (306 000-370 000; 95% confidence interval) premature deaths in China are attributable to residential combustion emissions, approximately a third of the deaths attributable to all ambient PM2.5 pollution, with 159 000 (142 000-172 000) and 182 000 (163 000-197 000) premature deaths from heating and cooking emissions, respectively. Our findings emphasize the need to mitigate emissions from both residential heating and cooking sources to reduce the health impacts of ambient air pollution in China.

Spatial Variability of AERONET Aerosol Optical Properties and Satellite Data in South Korea during NASA DRAGON-Asia Campaign

We investigated spatial variability in aerosol optical properties, including aerosol optical depth (AOD), fine-mode fraction (FMF), and single scattering albedo (SSA), observed at 21 Aerosol Robotic Network (AERONET) sites and satellite remote sensing data in South Korea during the spring of 2012. These dense AERONET networks established in a National Aeronautics and Space Administration (NASA) field campaign enabled us to examine the spatially detailed aerosol size distribution and composition as well as aerosol levels. The springtime particle air quality was characterized by high background aerosol levels and high contributions of coarse-mode aerosols to total aerosols. We found that between-site correlations and coefficient of divergence for AOD and FMF strongly relied on the distance between sites, particularly in the south-north direction. Higher AOD was related to higher population density and lower distance from highways, and the aerosol size distribution and composition reflected source-specific characteristics. The ratios of satellite NO2 to AOD, which indicate the relative contributions of local combustion sources to aerosol levels, represented higher local contributions in metropolitan Seoul and Pusan. Our study demonstrates that the aerosol levels were determined by both local and regional pollution and that the relative contributions of these pollutions to aerosols generated spatial heterogeneity in the particle air quality.

Annual and diurnal variations of gaseous and particulate pollutants in 31 provincial capital cities based on in situ air quality monitoring data from China National Environmental Monitoring Center

Long-term air quality data with high temporal and spatial resolutions are needed to understand some important processes affecting the air quality and corresponding environmental and health effects. The annual and diurnal variations of each criteria pollutant including PM2.5 and PM10 (particulate matter with aerodynamic diameter less than 2.5 μm and 10 μm, respectively), CO (carbon monoxide), NO2 (nitrogen dioxide), SO2 (sulfur dioxide) and O3 (ozone) in 31 provincial capital cities between April 2014 and March 2015 were investigated by cluster analysis to evaluate current air pollution situations in China, and the cities were classified as severely, moderately, and slightly polluted cities according to the variations. The concentrations of air pollutants in winter months were significantly higher than those in other months with the exception of O3, and the cities with the highest CO and SO2 concentrations were located in northern China. The annual variation of PM2.5 concentrations in northern cities was bimodal with comparable peaks in October 2014 and January 2015, while that in southern China was unobvious with slightly high PM2.5 concentrations in winter months. The concentrations of particulate matter and trace gases from primary emissions (SO2 and CO) and NO2 were low in the afternoon (~16:00), while diurnal variation of O3 concentrations was opposite to that of other pollutants with the highest values in the afternoon. The most polluted cities were mainly located in North China Plain, while slightly polluted cities mostly focus on southern China and the cities with high altitude such as Lasa. This study provides a basis for the formulation of future urban air pollution control measures in China.

An Investigation on Formaldehyde Emission Characteristics of Wood Building Materials in Chinese Standard Tests: Product Emission Levels, Measurement Uncertainties, and Data Correlations between Various Tests

As a large producer and consumer of wood building materials, China suffers product formaldehyde emissions (PFE) but lacks systematic investigations and basic data on Chinese standard emission tests (CST), so this paper presented a first effort on this issue. The PFE of fiberboards, particleboards, blockboards, floorings, and parquets manufactured in Beijing region were characterized by the perforator extraction method (PE), 9–11 L and 40 L desiccator methods (D9, D40), and environmental chamber method (EC) of the Chinese national standard GB 18580; based on statistics of PFE data, measurement uncertainties in CST were evaluated by the Monte Carlo method; moreover, PFE data correlations between tests were established. Results showed: (1) Different tests may give slightly different evaluations on product quality. In PE and D9 tests, blockboards and parquets reached E1 grade for PFE, which can be directly used in indoor environment; but in D40 and EC tests, floorings and parquets achieved E1. (2) In multiple tests, PFE data characterized by PE, D9, and D40 complied with Gaussian distributions, while those characterized by EC followed log-normal distributions. Uncertainties in CST were overall low, with uncertainties for 20 material-method combinations all below 7.5%, and the average uncertainty for each method under 3.5%, thus being acceptable in engineering application. A more complicated material structure and a larger test scale caused higher uncertainties. (3) Conventional linear models applied to correlating PFE values between PE, D9, and EC, with R² all over 0.840, while novel logarithmic (exponential) models can work better for correlations involving D40, with R² all beyond 0.901. This research preliminarily demonstrated the effectiveness of CST, where results for D40 presented greater similarities to EC—the currently most reliable test for PFE, thus highlighting the potential of Chinese D40 as a more practical approach in production control and risk assessment.

PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.