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Air pollution poses a grave threat to human health and everyday life. Accurate air-quality prediction plays a crucial role in effectively preventing and controlling air pollution. A multi-graph spatial-temporal attention network is proposed to predict the air quality in a given area by analyzing the interconnections between stations and the individual characteristics of each station. Firstly, this paper constructs multi-scale spatial-temporal graphs from spatial and temporal perspectives to effectively capture the interconnections between stations, thereby comprehensively understanding the spatial-temporal relationships among them. Secondly, incorporating the nonlinear temporal correlation of station data, this paper proposes a temporal multi-graph attention-fusion module to integrate information from both neighboring stations and the station itself. Finally, predictions are made using a spatial-temporal graph network. The experiments in this paper were based on air-quality data from Beijing and Tianjin, and the following experimental results were obtained. (1) The proposed model outperforms the baselines significantly in both single-step and multi-step prediction tasks. (2) The ablation study confirms that the graph constructed in this paper contributes to improving the performance of the model. (3) Comparing the performance of attention components, the proposed attention mechanism exhibits better performance than other attention mechanisms. [ABSTRACT FROM AUTHOR]

The profound impacts of severe air pollution on human health, ecological balance, and economic stability are undeniable. Precise air quality forecasting stands as a crucial necessity, enabling governmental bodies and vulnerable communities to proactively take essential measures to reduce exposure to detrimental pollutants. Previous research has primarily focused on predicting air quality using only time-series data. However, the importance of remote-sensing image data has received limited attention. This paper proposes a new multi-modal deep-learning model, Res-GCN, which integrates high spatial resolution remote-sensing images and time-series air quality data from multiple stations to forecast future air quality. Res-GCN employs two deep-learning networks, one utilizing the residual network to extract hidden visual information from remote-sensing images, and another using a dynamic spatio-temporal graph convolution network to capture spatio-temporal information from time-series data. By extracting features from two different modalities, improved predictive performance can be achieved. To demonstrate the effectiveness of the proposed model, experiments were conducted on two real-world datasets. The results show that the Res-GCN model effectively extracts multi-modal features, significantly enhancing the accuracy of multi-step predictions. Compared to the best-performing baseline model, the multi-step prediction's mean absolute error, root mean square error, and mean absolute percentage error increased by approximately 6%, 7%, and 7%, respectively. [ABSTRACT FROM AUTHOR]

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With the accelerating urbanization process in China, the extensive economic growth model with high energy consumption and high pollution aggravates atmospheric environmental pollution and restricts the sustainable development of the social economy. The Beijing–Tianjin–Hebei region has the most severe haze pollution and the most acute contradiction between resources, environment and economic development. Based on the physical coupling theory, this paper constructs a coupling coordination degree model of the economy, environment and high haze pollution industries, such as the thermal power industry. Through literature analysis and expert investigation of the economic, industrial and environmental data of the Beijing–Tianjin–Hebei region from 2006 to 2018, the coordinated development of the economy, environment and high haze pollution industries, such as the thermal power industry, in the above region, was dynamically monitored. The monitoring results show that the development level of the Beijing, Tianjin and Hebei region is significantly different, and the three subregions have not entered the stage of coordinated development. Moreover, since 2015, they have been in a bottleneck period of development and have not achieved a higher level of progress. The three subregions have different advantages and restraining factors. For example, the backward level of Hebei's economy and high haze pollution industries, such as the thermal power industry, restrict the coordinated development of the region as a whole. Only by accelerating the high-quality development of the Hebei economy can we break through the bottleneck of the development of Beijing, Tianjin and Hebei. [ABSTRACT FROM AUTHOR]

Electric heating is helpful in resolving air pollution, and also utilizes renewable energy power. However, the environmental benefits of electric heating are restrained by regional resources endowment and regional electrical energy structure. In the context of the active promotion of electric heating in Beijing—Tianjin–Hebei, the paper studied the development potential and limits of wind power electric heating under the constraints of environmental effects to provide reference for the orderly development of electric heating. A model to predict the capacity of the installed wind power improved by the fruit fly optimized ELM (Extreme Learning Machine) algorithm and an electric heating environment effect calculation model are constructed. The optimal value and critical value of the newly added heating area in Beijing–Tianjin–Hebei are obtained through calculation under four scenarios of wind abandonment rate. As the wind abandonment rate increases from 4–10% (with interval of 2%), the optimal value of the newly added electric heating area in Beijing—Tianjin–Hebei will be 19.15, 29.47, 36.26, and 47.90 million m2 by the year 2030. Additionally, as the utilization rate of thermal power exceeds 41.16%, electric heating will produce more carbon emissions compared to coal‐fired heating. Therefore, if we want to develop electric heating on a large scale, we need to control the proportion of thermal power in the power supply structure and increase the proportion of new energy. This study can be used as theoretical reference to the development programme of electric energy substitution in the future. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Air pollution caused by coal burning not only increases the cost of environmental pollution but also harms human health. It is urgent for China to change the practice of coal-fired central heating. Therefore, the effectiveness and sustainability of the Coal to Gas and Electricity policy have become the focus of all sectors of society. In this paper, eight cities in the Beijing–Tianjin–Hebei region were taken as the experimental groups and the other eleven cities as the control groups. Based on the PSM-DID model and the time-varying DID model, a quasi-natural experimental analysis was conducted to evaluate the effect of the policy of coal to gas and electricity to improve air quality in the Beijing–Tianjin–Hebei region from 2015 to 2020 and to test the sustainability of the policy. Three research conclusions are shown below: First, during the implementation of the policy, especially in 2019, the AQI index decreased significantly. Although there was a rebound thereafter, it was still lower than before. This shows that the Coal to Gas and Electricity policy has indeed improved the air quality in Beijing, Tianjin, and Hebei during its implementation. Second, the policy had a great impact on SO2 and PM10 but was relatively weak on PM2.5 and CO. Therefore, there is an urgent need to formulate scientific and accurate policies to control different air pollutants. Third, the time-varying DID model was used to identify the dynamic sustainability effect of the Coal to Gas and Electricity policy. The results showed that the policy had a strong impact in the initial stage, but its effect was greatly reduced at the end of the implementation or near the end, when it was far less obvious than in the initial stage of the policy. Therefore, in formulating relevant measures to reduce air pollution, it is necessary to fully consider the sustainability of the policy. [ABSTRACT FROM AUTHOR]

Air pollution in northern China is relatively serious during the winter heating period, which attracts the attention of the state and government, especially in Beijing–Tianjin–Hebei Region. To further explore the issue of air pollutant emission and energy utilization in Beijing–Tianjin–Hebei during the heating season, this paper establishes a panel data model which describes the long-term relationship between air pollutant emission, heating capacity, coal, and power consumption with the data from 2004 to 2017. Based on this, we draw the following conclusions: there is a positive relationship between winter heating capacity and air pollutant emissions, which indicates that the energy consumed by heating will produce atmospheric pollutants. However, the increase of electricity consumption does not necessarily reduce pollution, which means that replacing coal with electricity is not the best way to solve air pollution in heating season, but requires the coordination of multiple energy sources. In addition, there are obvious differences in the analysis results in Beijing, Tianjin, and Hebei. For example, the impact of coal and electricity consumption on pollutant emissions in Beijing is quite different from that in Tianjin and Hebei. The local economic development and energy conditions should be fully taken into account when formulating policies. [ABSTRACT FROM AUTHOR]

The development of industry has led to serious air pollution problems. It is very important to establish high-precision and high-performance air quality prediction models and take corresponding control measures. In this paper, based on 4 years of air quality and meteorological data from Tianjin, China, the relationships between various meteorological factors and air pollutant concentrations are analyzed. A hybrid deep learning model consisting of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) is proposed to predict pollutant concentrations. In addition, a Bayesian optimization algorithm is applied to obtain the optimal combination of hyperparameters for the proposed deep learning model, which enhances the generalization ability of the model. Furthermore, based on air quality data from multiple stations in the region, a multistation collaborative prediction method is designed, and the concept of a strongly correlated station (SCS) is defined. The predictive model is modified using the idea of SCS and is used to predict the pollutant concentration in Tianjin. The coefficient of determination R2 of PM2.5, PM10, SO2, NO2, CO, and O3 are 0.89, 0.84, 0.69, 0.83, 0.92, and 0.84, respectively. The results show that our model is capable of dealing with air pollutant prediction with satisfactory accuracy. [ABSTRACT FROM AUTHOR]

The spatial spillover of air pollution in Beijing - Tianjin - Hebei region makes the territorial governance model inefficient. At the same time, it is facing the contradiction between environmental governance and economic development. So far, there is still no regional long-term mechanism for coordinated governance of air pollution. Ecological compensation theory is becoming an effective guiding theory to coordinate economic and environmental benefits. There is relatively little research on ecological compensation mechanism in the coordinated control of regional air pollution. Ecological compensation mechanism is an effective tool to promote air pollution control. At the same time, regional cooperation can realize the efficient control of air pollution. Scientifically constructing the cross regional cooperative control model of Beijing, Tianjin and Hebei is a favorable way to implement comprehensive Control of air pollution. This paper discusses the necessity of ecological compensation mechanism for regional coordinated control of air pollution. Referring to practical experience of provinces and cities that have implemented the ecological compensation mechanism for air pollution control, and the effective way to distribute the compensation amount, compensation subject and compensation standard determination method that can be implemented in Beijing - Tianjin - Hebei region are analyzed, further proposing an effective way to establish an ecological compensation mechanism for regional air pollution collaborative control according to its reality. [ABSTRACT FROM AUTHOR]

The mechanism of aerosol pollution transport remains highly elusive owing to the myriad of influential factors. In this study, ground station data, satellite data, ground-based LiDAR remote sensing data, sounding data, ERA5 reanalysis and a backward trajectory model were combined to investigate the formation process and optical properties of winter aerosol pollution in Beijing and surrounding areas. The analysis of ground station data shows that compared to 2019 and 2021, the pandemic lockdown policy resulted in a decrease in the total number of pollution days and a decrease in the average concentration of particulate matter in the Beijing area in 2020. The terrain characteristics of the Beijing-Tianjin-Hebei (BTH) made it prone to northeast and southwest winds. The highest incidence of aerosol pollution in Beijing occurs in February and March during the spring and winter seasons. Analysis of a typical heavy aerosol pollution process in the Beijing area from 28 February to 5 March 2019 shows that dust and fine particulate matter contributed to the primary pollution; surface air temperature inversion and an average wind speed of less than 3 m/s were conducive to the continuous accumulation of pollutants, which was accompanied by the oxidation reaction of NO2 and O3, forming photochemical pollution. The heavy aerosol pollution was transmitted and diffused towards the southeast, gradually eliminating the pollution. Our results provide relevant research support for the prevention and control of aerosol pollution. [ABSTRACT FROM AUTHOR]

High concentrations of air pollutants such as total suspended particulates (TSP) and sulfur dioxide (SO2) have serious impacts on nearby populations. In this paper, a survey of rural Tianjin residents' willingness-to-pay for health improvement was reported on, and the MBDC (multiple bounded discrete choice) model was adopted to study the respondents' willingness-to-pay to prevent respiratory illnesses. The results showed that the willingness-to-pay for health improvement was affected by respondents' health condition, work situation and environmental awareness, but not by personal habits, such as smoking. If person's willingness-to-pay to avoid respiratory diseases can be considered equal to the cost to personal health caused by air pollution, the total cost will reach 538 x 106 RMB Yuan ( RMB, equal to 65 million USD ) per year. [ABSTRACT FROM AUTHOR]

Copyright of Research of Environmental Sciences is the property of Research of Environmental Sciences Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Emergency measures are effective measures that can be quickly taken in response to heavy air pollution. They not only have an obvious impact on slowing down the accumulation of particulate matter but also have a significant impact on public health and socio-economic development. Therefore, to analyze the effectiveness of emergency measures, one must assess their environmental, health and economic impacts. In this paper, we use exposure-response functions and a city-level computable general equilibrium (CGE) model to do so for China's Jing-Jin-Ji region. We find that the emergency measures implemented in 2019 significantly improve the region's air quality and enhance public health by reducing risk associated with acute bronchitis. Moreover, those emergency measures notably benefit the Jing-Jin-Ji region economically by expanding labor supply, most notably in Beijing and Tianjin. It seems Beijing and Tianjin should compensate industrial cities in Hebei, which enabled the Jing-Jin-Ji region's better air quality but encountered far fewer economic benefits. Handan, Baoding, and Cangzhou are among the cities in Hebei that are expanding employment in manufacturing and service sectors. These results can provide scientific guidance and policy suggestions for government while using emergency measures to combat regional heavy air pollution considering its health and economic benefits. • Evaluating impacts of inter-regional air pollution controls at city level in China. • Overall evaluate environmental, health, and economic impacts of emergency measures. • Emergency measures improve air quality, enhancing public health by reducing risk. • Emergency measures notably benefit the region economically by expanding labor supply. [ABSTRACT FROM AUTHOR]

Straw open burning in suburban areas contributes to an important proportion of air pollution threatening air quality of neighbouring highways and airports. This paper presents the characteristics of straw open burning-derived air pollution to understand its impact mechanism and take effective control measurements. In this study, PM 2.5 emissions inventory from straw open burning was established at a high spatial resolution of 0.1° × 0.1° in Tianjin using geographic information systems (GIS) for the period of 2001–2012. PM 2.5 emissions increased by 209.15% in the past nine years at an annual average rate of 23.24% from 2.95 Gg in 2002 to 6.17 Gg in 2010. WuQing District covering 13.17% of Tianjin land contributed to PM 2.5 emission of 28.21% of total PM 2.5 emissions from straw open burning. [ABSTRACT FROM AUTHOR]

China's most critically air polluted area, the Beijing-Tianjin-Hebei (BTH) region has attracted significant attention; the regional linkage of environmental indicators in BTH has been widely studied in recent years. The city-level air pollutants and economic benefits hidden in trade activities are still poorly understood. This paper examines air pollutants and economic benefits embodied in BTH's consumption based on a city-level input-output table. Our results show that transfer flows of air pollutants and value-added between different cities lead to the unequal exchange of air pollution and economic benefits in BTH. Beijing gains more value-added (38.40%) through trade compared with its atmospheric pollutant equivalents (APE, 1.75%) induced by consumption demand in BTH. Conversely, Tangshan, Shijiazhuang, and Handan emit more air pollutants compared with the benefits they gain through trade. The results provide evidence for the establishment of compensation mechanisms between cities. • Trade between cities lead to the unequal exchange of air pollution and economic benefits in BTH. • Beijing gains a higher proportion of value added compared with its air pollutants induced by trade. • Cities in Hebei province gain lower proportions of value added compared with their air pollutants induced by trade. [ABSTRACT FROM AUTHOR]

Air pollution has received more attention from many countries and scientists due to its high threat to human health. However, air pollution prediction remains a challenging task because of its nonstationarity, randomness, and nonlinearity. In this research, a novel hybrid system is successfully developed for PM2.5 concentration prediction and its application in health effects and economic loss assessment. First, an efficient data mining method is adopted to capture and extract the primary characteristic of PM2.5 dataset and alleviate the noises' adverse effects. Second, Harris hawks optimization algorithm is introduced to tune the extreme learning machine model with high prediction accuracy, then the optimized extreme learning machine can be established to obtain the forecasting values of PM2.5 series. Next, PM2.5‐related health effects and economic costs was estimated based on the predicted PM2.5 values, the related health effects, and environmental value assessment methods. Several experiments are designed using three daily PM2.5 datasets from Beijing, Tianjin, and Shijiazhuang. Lastly, the corresponding experimental results showed that this proposed system can not only provide early warning information for environmental management, assist in the formulation of effective measures to reduce air pollutant emissions, and prevent health problems but also help for further research and application in different fields, such as health issues due to PM2.5 pollutant. [ABSTRACT FROM AUTHOR]

Abstract: It is well known that nocturnal planetary boundary layer (NPBL) has important effects on urban air pollutants. However, the direct measurements of the interactions between the NPBL height and urban air pollutants are normally difficult, because such measurements require continuous vertical profiles of air pollutants and meteorological parameters. This paper provides an unique data, which temperature, NPBL, NO x and O3 concentrations are measured at a 250-m meteorological tower in the city of Tianjin, China (a much polluted city located in central-eastern China). The results are analyzed to study the trend of NPBL and the impacts of NPBL on air pollutants in the city. The results show that the measured NPBL height ranges from 100m to 150m. The measurement of 10-year trend of the NPBL height suggests that the averaged NPBL height increases by about 20% between 1995 and 2006. The results also show that the NPBL height has important effects on air pollutants. This study suggests that NO x and O3 concentrations are strongly anti-correlated inside of the NPBL height. During nighttime, NO x is directly emitted from the surface and is limited to inside of NPBL (40m), resulting in high NO x concentrations near the surface. The high NO x concentrations depress O3, producing low O3 concentrations near the surface. The measurements of vertical gradient of O3 show that about 30–50ppbv of O3 concentrations are chemically destroyed due to the surface emission of NO x during nighttime, suggesting that NPBL plays important roles in regulating the diurnal cycle of O3 at the surface. [Copyright &y& Elsevier]

• A mathematic model is built to evaluate the air pollution of heating consumption. • The coal substitution policy can reduce the PM2.5 concentrations by about 20 μg/m3. • Effect of renewable energy and its development to air quality is considered. • PM2.5 concentration in 2030 will drop by about 27% in Northern China compared to 2016. The Air Pollution Prevention and Control Action Plan proposed in 2013 has contributed to the fossil fuel reduction in central heating, but the consumption of scattered coal in rural areas should not be overlooked as it accounts for nearly 50% pollutant emissions during the heating season. Air Pollution Prevention and Control Action Plan for Beijing-Tianjin-Hebei and Surrounding Areas was issued to solve the problem of scattered coal consumption and improve the heating energy structure in 2017. In this paper, an air quality-heating model is established to evaluate the air quality improvement potential and far-reaching influence of scattered coal consumption reduction in rural areas. Distinct from other air quality evaluation models, the proposed model is to evaluate the regional air quality related to the heating factors. The results indicate that the coal substitution policy can reduce PM2.5 concentrations in the heating season by about 20 μg/m3 in Beijing-Tianjin-Hebei and surrounding areas. Furthermore, predictions about the variation of PM2.5 concentration in the heating season are conducted, which indicate that the PM2.5 concentration of Beijing, Tianjin, Hebei and surrounding areas in 2030 will drop by 48%, 35%, 29% and 23% respectively compared to that in 2016. The reduction could be further enhanced to be 55%, 40%, 32% and 27% with the consideration of clean power development. This study is conducive to evaluate the clean heating technologies role in improving the environment and air quality. [ABSTRACT FROM AUTHOR]

Air quality in China has gradually been improving in recent years; however, the Beijing-Tianjin-Hebei (BTH) region continues to be the most polluted area in China, with the worst air quality index. BTH and its surrounding areas experience high agglomeration of heavy-polluting manufacturers that generate electric power, process petroleum and coal, and carry out smelting and pressing of ferrous metals, raw chemical materials, chemical products, and non-metallic mineral products. This study presents evidence of the air pollution impacts of industrial agglomeration using the Ellison–Glaeser index, Herfindahl–Hirschman index, and spatial autocorrelation analysis. This was based on data from 73,353 enterprises in "2+26" atmospheric pollution transmission channel cities in BTH and its surrounding areas (herein referred to as BTH "2+26" cities). The results showed that Beijing, Yangquan, Puyang, Kaifeng, Taiyuan, and Jinan had the highest Ellison–Glaeser index among the BTH "2+26" cities; this represents the highest enterprise agglomeration. Beijing, Langfang, Tianjin, Baoding, and Tangshan also showed a low Herfindahl–Hirschman index of pollutant emissions, which have a relatively high degree of industrial agglomeration in BTH "2+26" cities. There was an inverted U-shaped relationship between enterprise agglomeration and air quality in the BTH "2+26" cities. This means that air quality improved with increased industrial agglomeration up to a certain level; beyond this point, the air quality begins to deteriorate with a decrease in industrial agglomeration. [ABSTRACT FROM AUTHOR]

The haze climate has seriously affected people's lives in China, and one of the important causes is particular matter (PM). For further, PM also has a negative impact on human health, especially respiratory health. A modified two-stage EBM (Epsilon-based Measure)data envelopment analysis (DEA) model considering undesirable outputs was used in this study to explore the energy utilization, PM and respiratory efficiency evaluation in China. It is concluded that the total efficiency value of Beijing, Inner Mongolia, Shandong and Tianjin is high, while that of China's other provinces is low. The overall efficiency of most provinces in the first stage is better than that in the second stage, and the efficiency difference between provinces in the second stage is more significant. There is a significant difference in PM efficiency between provinces, which needs to be managed by governments of different regions. Except for Beijing, Jiangsu, Inner Mongolia, Shandong and Tianjin, the efficiency of respiratory diseases in most provinces still needs to be improved. Therefore, it is suggested to optimize the industrial structure, accelerate the adjustment of energy structure, strengthen the treatment of air pollution and increase public expenditure on medical care, so as to improve residents' respiratory health. [ABSTRACT FROM AUTHOR]

Joint prevention and control of air pollution (JPCAP) is an inevitable choice for controlling air pollution in the future. The existing air pollution prevention and control methods pay less attention to environmental justice, which results in poor treatment effects; hence, a more reasonable method is imperative. The innovation of this work is to construct a new method for dividing the scope and priorities of JPCAP by introducing environmental justice. First, we analyze the distribution and injustice of air pollution, and then divide JPCAP regions based on environmental justice using a clustering method. Finally, by selecting indicators from the characteristics of air pollution, natural conditions, and trade, the Entropy-TOPSIS method is employed to define the priorities of the JPCAP regions. Accordingly, we divided Beijing, Tianjin, Hebei, and its surrounding areas in China into four JPCAP regions. We also discovered key regions of air pollution control by determining the priorities of the four regions. The new method provides a practical guidance and a theoretical basis for regional joint control of air pollution. [ABSTRACT FROM AUTHOR]

Based on the Weather Research and Forecasting model and the Models-3 community multi-scale air quality model (WRF-CMAQ), this study analyzes the impacts of meteorological conditions and changes in air pollutant emissions on the heavy air pollution episode occurred over North China around the 2020 Spring Festival (January to Februray 2020). Regional reductions in air pollutant emissions required to eliminate the PM2.5 heavy pollution episode are also quantified. Our results found that meteorological conditions for the Beijing-Tianjin-Hebei and surrounding "2+26" cities are the worst during the heavy pollution episode around the 2020 Spring Festival as compared with two other typical heavy pollution episodes that occurred after 2015. However, because of the substantial reductions in air pollutant emissions in the "2+26" cities in recent years, and the 32% extra reduction in emissions during January to February 2020 compared with the baseline emission levels of the autumn and winter of 2019 to 2020, the maximum PM2.5 level during this heavy pollution episode around the 2020 Spring Festival was much lower than that in the other two typical episodes. Yet, these emission reductions are still not enough to eliminate regional heavy pollution episodes. Compared with the actual emission levels during January to February 2020, a 20% extra reduction in air pollutant emissions in the "2+26" cities (or a 45% extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020) could help to generally eliminate regionwide severe pollution episodes, and avoid heavy pollution episodes that last three or more consecutive days in Beijing; a 40% extra reduction in emissions (or a 60% extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020) could help to generally eliminate regionwide and continuous heavy pollution episodes. Our analysis finds that during the clean period after the heavy pollution episode around the 2020 Spring Festival, the regionwide heavy pollution episode would only occur with at least a 10-fold increase in air pollutant emissions. [ABSTRACT FROM AUTHOR]

A comprehensive field experiment measuring aerosol chemical and physical properties at a suburban site in Beijing around the 2019 Spring Festival was carried out to investigate the impact of reduced anthropogenic emissions on aerosol formation. Sharply reduced sulfur dioxide (SO2) and nitrogen dioxide (NO2) concentrations during the festival holiday resulted in an unexpected increase in the surface ozone (O3) concentration caused by the strong O3 -titration phenomenon. Simultaneously, the reduced anthropogenic emissions resulted in massive decreases in particle number concentration at all sizes and the mass concentrations of organics and black carbon. However, the mass concentrations of inorganics (especially sulfate) decreased weakly. Detailed analyses of the sulfur oxidation ratio and the nitrogen oxidation ratio suggest that sulfate formation during the holiday could be promoted by enhanced nocturnal aqueous-phase chemical reactions between SO2 and O3 under moderate relative humidity (RH) conditions (40 % < RH < 80 %). Daytime photochemical reactions in winter in Beijing mainly controlled nitrate formation, which was enhanced a little during the holiday. A regional analysis of air pollution patterns shows that the enhanced formation of secondary aerosols occurred throughout the entire Beijing–Tianjin–Hebei (BTH) region during the holiday, partly offsetting the decrease in particle matter with an aerodynamic diameter less than 2.5 µ m. Our results highlight the necessary control of O3 formation to reduce secondary pollution in winter under current emission conditions. [ABSTRACT FROM AUTHOR]

Seven Chinese cities have enacted One-Weekday Limit (OWL) driving restrictions following Beijing's implementation shortly after the Olympics in 2008. Existing literature examines the short-run effect of the OWL or the long-run effect of the Olympic-year policy package on air pollution in Beijing. Using two difference-in-differences (DD) approaches, this study compares the long-run effect of the Olympic-year policy package with the effect of the OWL. Using the city of Tianjin as a control, this study finds a significant drop in pollution due to the Olympic-year policy package. Using weekends as a control, this study finds a much smaller and less significant drop due to the OWL. These new findings suggest that compared to the OWL, other policies enforced in the Olympic year account for a greater portion of the drop. [ABSTRACT FROM AUTHOR]

Despite frequent foehns in the Beijing–Tianjin–Hebei (BTH) region, there are only a few studies of their effects on air pollution in this region, or elsewhere. Here, we discuss a foehn-induced haze front (HF) event using observational data to document its structure and evolution. Using a dense network of comprehensive measurements in the BTH region, our analyses indicate that the foehn played an important role in the formation of the HF with significant impacts on air pollution. Northerly warm–dry foehn winds, with low particulate concentration in the northern area, collided with a cold–wet polluted air mass to the south and formed an HF in the urban area. The HF, which is associated with a surface wind convergence line and distinct contrasts of temperature, humidity and pollutant concentrations, resulted in an explosive growth of particulate concentration. As the plain–mountain wind circulation was overpowered by the foehn, a weak pressure gradient due to the different air densities between air masses was the main factor forcing advances of the polluted air mass into the clean air mass, resulting in severe air pollution over the main urban areas. Our results show that the foehn can affect air pollution through two effects: direct wind transport of air pollutants, and altering the air mass properties to inhibit boundary layer growth and thus indirectly aggravating air pollution. This study highlights the need to further investigate the foehn and its impacts on air pollution in the BTH region. [ABSTRACT FROM AUTHOR]

Dust aerosols from the desert areas of China can be lifted to the upper troposphere and transported eastward by the westerly, affecting regional and local air pollution process. In this paper, we analyzed the long-range transport of dust and its impact on the haze-fog process that occurred in Tianjin from 23 November to 5 December 2018. Satellite and ERA5 reanalysis data revealed that dust from northwestern China was transported to eastern China by the westerly flow behind the troughs, which subsequently enhanced the air pollution in Tianjin area. On 26 November and 2 December, the visibility was less than 2 km with a relative humidity (RH) over 90%, indicating there was fog weather in Tianjin. The dust influx from the northwest direction mixed with ground pollutants, increased the PM 2.5 and PM 10 mass concentrations and enhanced the air pollution with the cumulative peak value of the PM 2.5 mass concentration reaching over 300 μg/m3 on 26 November. On 27 November and 3 December, the wind speed increased and large dust particles were transported to Tianjin, the PM 10 mass concentration exceeded a much higher value of 550 μg/m3 whereas the PM 2.5 mass concentration decreased to its lowest value, indicating dust weather followed the typical haze-fog pollution period in Tianjin. The ground lidar observations indicated that a large amount of non-spherical dust aerosols transmitted to Tianjin at 1.5~2.5 km height and settled down near the ground, which substantially affected the aerosol optical characteristics and air quality over the area. The influx of dust successive after the haze-fog weather, aggravated the air pollution process in Tianjin area, make it lasting for 153 h. • Long-range transport of dust and its effects on air pollution in Tianjin were studied. • The process of air pollution includes haze, fog and dust weather. • Dust alternates with haze-fog, make the duration of pollution lasting for 153 h. [ABSTRACT FROM AUTHOR]

This study is aimed at defining the relationship between a set of environmental factors and childhood HFMD and then at estimating the related effect. The 16 environmental factors included meteorological, air pollution, and sunspot. A traditional TSR modified by using susceptible-infectious-recovery models and distribution lag nonlinear model was applied to estimate the short-term effects of daily environmental factors on children HFMD occurrence in 2014–2018 with adjustment of potential confounding factors. A total of 70,027 children aged 0–15 years with HFMD were enrolled. No significant effect was observed for daily sunspot numbers and average visibility. We found positive effects of the ambient average temperature, with an approximately m-shaped curve of the overall cumulative relationship, peaking at 25.6 °C with a relative risk (RR) of 1.45 (95% confidence intervals 1.21–1.73). The largest RR value of hot effect was achieved on the current day and then decreased by 2 days (total group, male group, and scatter group) or 1 day (female group and nursery group), and the effect lasted about 6 to 8 days from the lag 4 or lag 6 day. A greater association of temperature with HFMD for the female group and the scattered group was observed. This study suggests that ambient average temperature might be a risk factor for children HFMD in Tianjin. Further studies are warranted to confirm these findings. [ABSTRACT FROM AUTHOR]

In addition to many recent actions taken to reduce emissions from energy production, industry, and transportation, a new campaign substituting residential solid fuels with electricity or natural gas has been launched in Beijing, Tianjin, and 26 other municipalities in northern China, aiming at solving severe ambient air pollution in the region. Quantitative analysis shows that the campaign can accelerate residential energy transition significantly, and if the planned target can be achieved, more than 60% of households are projected to remove solid fuels by 2021, compared with fewer than 20% without the campaign. Emissions of major air pollutants will be reduced substantially. With 60% substitution realized, emission of primary PM2.5 and contribution to ambient PM2.5 concentration in 2021 are projected to be 30% and 41% of those without the campaign. With 60% substitution, average indoor PM2.5 concentrations in living rooms in winter are projected to be reduced from 209 (190 to 230) μg/m³ to 125 (99 to 150) μg/m³. The population-weighted PM2.5 concentrations can be reduced from 140 μg/m³ in 2014 to 78 μg/m³ or 61 μg/m³ in 2021 given that 60% or 100% substitution can be accomplished. Although the original focus of the campaign was to address ambient air quality, exposure reduction comes more from improved indoor air quality because ∼90% of daily exposure of the rural population is attributable to indoor air pollution. Women benefit more than men. [ABSTRACT FROM AUTHOR]

To comprehensively evaluate the effects of the recent " 2+26 " regional strategy for air quality improvement, we compared the variations in PM 2.5 concentrations in Beijing during four pollution episodes with different emission-reduction strategies. The 2+26 strategy implemented in March 2018 led to a mean PM 2.5 concentration 16.43 % lower than that during the pollution episode in March 2013, when no specific emission-reduction measures were in place. The same 2+26 strategy implemented in November 2017 led to a mean PM 2.5 concentration 32.70 % lower than that during the pollution episode in November 2016, when local emission-reduction measures were implemented. The results suggested that the effects of the 2+26 regional emission-reduction measures on PM 2.5 reductions were influenced by a diversity of factors and could differ significantly during specific pollution episodes. Furthermore, we found the proportions of sulfate ions decreased significantly, and nitrate ions were the dominant PM 2.5 components during the two 2+26 orange alert periods. Meanwhile, the relative contribution of coal combustion to PM 2.5 concentrations in Beijing during the pollution episodes in March 2013, November 2016, November 2017 and March 2018 was 40 %, 34 %, 28 % and 11 %, respectively, indicating that the recent "Coal to Gas" project and the contingent 2+26 strategy led to a dramatic decrease in coal combustion in the Beijing–Tianjin–Hebei region. On the other hand, the relative contribution of vehicle exhaust during the 2+26 orange alert periods in November 2017 and March 2018 reached 40 % and 54 %, respectively. The relative contribution of local emissions to PM 2.5 concentrations in Beijing also varied significantly and ranged from 49.46 % to 89.35 % during the four pollution episodes. These results suggested that the 2+26page6880 regional emission-reduction strategy should be implemented with red air pollution alerts during heavy pollution episodes to intentionally reduce the dominant contribution of vehicle exhausts to PM 2.5 concentrations in Beijing, while specific emission-reduction measures should be implemented accordingly for different cities within the 2+26 framework. [ABSTRACT FROM AUTHOR]

Currently, Haze is one of the greatest environmental problems with serious impacts on human health in China, especially in capital region (Beijing-Tianjin-Hebei region). To alleviate this problem, the Chinese government introduced a National Air Pollution Control Action Plan (NAPCAP) with air pollutants reduction targets by 2017. However, there is doubt whether these targets can be achieved once the plan is implemented. In this work, the effectiveness of NAPCAP is analyzed by developing models of the statistical relationship between PM2.5 concentrations and air pollutant emissions (SO2, NOx, smoke and dust), while taking into account wind and neighboring transfer impacts. The model can also identify ways of calculating the intended emission levels in the Beijing–Tianjin–Hebei area. The results indicate that haze concentration control targets will not be attained by following the NAPCAP, and that the amount of progress needed to meet the targets is unrealistic. A more appropriate approach to reducing air emissions is proposed, which addresses joint regional efforts. [ABSTRACT FROM AUTHOR]

A campaign was conducted to assess and compare the personal exposure in L3 of Tianjin subway, focusing on PM levels, chemical compositions, morphology analysis, as well as the health risk of heavy metal in PM. The results indicated that the average concentration of the PM was 151.43 μg/m inside the train of the subway during rush hours. PM concentrations inside car under the ground are higher than those on the ground, and PM concentrations on the platform are higher than those inside car. Regarding metal concentrations, the highest element in PM samples was Fe; the level of which is 17.55 μg/m. OC is a major component of PM in Tianjin subway. Secondary organic carbon is the formation of gaseous organic pollutants in subway. SEM-EDX and TEM-EDX exhibit the presence of individual particle with a large metal content in the subway samples. For small Fe metal particles, iron oxide can be formed easily. With regard to their sources, Fe-containing particles are generated mainly from mechanical wear and friction processes at the rail-wheel-brake interfaces. The non-carcinogenic risk to metals Cr, Ni, Cu, Zn and Pb, and carcinogenic hazard of Cr and Ni were all below the acceptable level in L3 of Tianjin subway. [ABSTRACT FROM AUTHOR]