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In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei (BTH) region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ensemble Kalman filtering (EnKF) for integrating the national ground monitoring pollutant observation data and the Nested Air Quality Prediction Modeling System (NAQPMS) simulation data to inversely estimate the emission rates of SO2, NOX, CO, and primary PM2.5 over BTH region in February from 2014 to 2019. The results show that SO2, NOX, CO, and primary PM2.5 emissions in the BTH region decreased in February from 2014 to 2019 by 83%, 37%, 41%, and 42%, while decreases in Beijing during this period were 86%, 67%, 59%, and 65%, respectively. Compared with the prior emission inventory, the inversion emission inventory reduces the uncertainty of multi-pollutant simulation in the BTH region, with simulated root mean square errors of the monthly average concentrations of SO2, NOX, PM2.5, and CO reduced by 41%, 30%, 31%, and 22%, respectively. The average uncertainties of SO2, NOX, PM2.5, and CO inversion emissions in 2014–19 are ±14.03% yr−1, ±28.91% yr−1, ±126.15% yr−1, and ±43.58% yr−1. Compared with the uncertainty of MEIC emission, the uncertainties of all species changed by +2% yr−1, −2% yr−1, −26% yr−1, and −4% yr−1, respectively. The spatial distribution results illustrate that air pollutant emissions are mainly distributed over the eastern and southern BTH regions. The spatial gap between the inversion emissions and MEIC emissions was further closed in 2019 compared to 2014. The results of this paper can provide a new reference for assessing changes in air pollution emissions over the BTH region in recent years and validating a bottom-up emission inventory. [ABSTRACT FROM AUTHOR]

Vehicle emissions have become a major source of air pollution in urban areas, especially for near-road environments, where the pollution characteristics are difficult to capture by a single-scale air quality model due to the complex composition of the underlying surface. Here we developed a hybrid model CMAQ-RLINE_URBAN to quantitatively analyze the effects of vehicle emissions on urban roadside NO 2 concentrations at a high spatial resolution of 50 m × 50 m. To estimate the influence of various street canyons on the dispersion of air pollutants, a machine-learning-based street canyon flow (MLSCF) scheme was established based on computational fluid dynamics and two machine learning methods. The results indicated that compared with the Community Multi-scale Air Quality (CMAQ) model, the hybrid model improved the underestimation of NO 2 concentration at near-road sites with the mean bias (MB) changing from -10 to 6.3 µ g m -3. The MLSCF scheme obviously increased upwind concentrations within deep street canyons due to changes in the wind environment caused by the vortex. In summer, the relative contribution of vehicles to NO 2 concentrations in Beijing urban areas was 39 % on average, similar to results from the CMAQ-ISAM (Integrated Source Apportionment Method) model, but it increased significantly with the decreased distance to the road centerline, especially on urban freeways, where it reached 75 %. [ABSTRACT FROM AUTHOR]

Abstract: North China is known for its large population densities and rapid development of industry and agriculture. Air quality around Beijing improved substantially during the 2008 Summer Olympics. We measured atmospheric concentrations of various Nr compounds at three urban sites and three rural sites in North China from 2010 to 2012 and estimated N dry and wet deposition by inferential models and the rain gauge method to determine current air conditions with respect to reactive nitrogen (Nr) compounds and nitrogen (N) deposition in Beijing and the surrounding area. NH3, NO2, and HNO3 and particulate NH4 + and NO3 −, and NH4 +–N and NO3 −–N in precipitation averaged 8.2, 11.5, 1.6, 8.2 and 4.6 μg N m−3, and 2.9 and 1.9 mg N L−1, respectively, with large seasonal and spatial variability. Atmospheric Nr (especially oxidized N) concentrations were highest at urban sites. Dry deposition of Nr ranged from 35.2 to 60.0 kg N ha−1 yr−1, with wet deposition of Nr of 16.3 to 43.2 kg N ha−1 yr−1 and total deposition of 54.4–103.2 kg N ha−1 yr−1. The rates of Nr dry and wet deposition were 36.4 and 33.2% higher, respectively, at the urban sites than at the rural sites. These high levels reflect the occurrence of a wide range of Nr pollution in North China and suggest that further strict air pollution control measures are required. [Copyright &y& Elsevier]

In China, “green” integrated waste management methods are being implemented in response to environmental concerns. We measured the air quality at several municipal solid waste (MSW) sites to provide information for the incorporation of logistics facilities within the current integrated waste management system. We monitored ambient air quality at eight MSW collecting stations, five transfer stations, one composting plant, and five disposal sites in Beijing during April 2006. Composite air samples were collected and analyzed for levels of odor, ammonia (NH3), hydrogen sulfide (H2S), total suspended particles (TSPs), carbon monoxide (CO), sulfur dioxide (SO2), and nitrogen dioxide (NO2). The results of our atmospheric monitoring demonstrated that although CO and SO2 were within acceptable emission levels according to ambient standards, levels of H2S, TSP, and NO2 in the ambient air at most MSW logistics facilities far exceeded ambient limits established for China. The primary pollutants in the ambient air at Beijing MSW logistics facilities were H2S, TSPs, NO2, and odor. To improve current environmental conditions at MSW logistics facilities, the Chinese government encourages the separation of biogenic waste from MSW at the source. [ABSTRACT FROM AUTHOR]

While the economy and society of China are developing rapidly, various ecological and environmental problems continue to emerge. The problem of air pollution is becoming an issue of increasing concern. Since 2013, Beijing, Tianjin, and Hebei Provinces have collaborated to control air pollution and have achieved certain success. However, the air pollution problem in the capital, Beijing, remains severe. In this study, a quantitative evaluation and analysis method is established for assessing urban air quality and its influencing factors by developing a driving force model. The model combines multiple regression and principal component analysis to account for social, economic, meteorological, and regional factors. The influencing factors with the highest contributions are regional transmission, energy consumption, and industrial structure. This model is used to project the future trend of the air quality in Beijing based on the evolution of the influencing factors, aimed to provide a theoretical basis for policies improving Beijing's air quality. • A driving force model of the air quality in Beijing is established. • Factors influencing the annual air quality and their contributions are determined. • Future trends in air quality in different scenarios are explored. • Practical policy implications are proposed based on factor and trend analyses. [ABSTRACT FROM AUTHOR]

During the 2014 Asia-Pacific Economic Cooperation (APEC) conference period, Beijing's air quality was greatly improved as a result of a series of tough emission control measures being implemented in Beijing and its surrounding provinces. However, a moderate haze occurred during the period of 4–5 November. In order to evaluate the emission control measures and study the formation mechanism of the haze, a comprehensive field observation based on a supersite and a lidar network was carried out from 25 October 2014 to 20 January 2015. By investigating the variations in aerosol number concentration and mean backscattering coefficient before, during and after the APEC period, it was found that number concentration of accumulation mode and coarse mode particles experienced the most significant decrease by 47% and 68%, and mean backscattering coefficient below 1 km decreased by 34% during the APEC period. Being characterized as “rapidly accumulating and rapidly dispersing”, the moderate haze occurred during the APEC period was probably initiated by a wind direction change to south and an increase of wind speed to 4 m/s. Sulfur dioxide involved plume nucleation without growth in size as well as a burst of particles ranging between 100 and 300 nm were observed simultaneously during the haze episode. The elevation of sulfur dioxide concentration and particle number concentration was highly correlated with the southerly wind, signifying the contribution of regional transport. It was observed by the lidar network that the aerosol backscattering coefficient increased in sequence among three sites along the southwest pathway, suggesting that aerosols might be transported from the southwest to the northeast of Beijing with a speed of approximately 17 km/h, which agreed with the movement of air masses modeled by Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT). The dual-wavelength lidar (355 and 532 nm) observation suggested that transportation of fine particles from high-level atmosphere (approximately 2 km) could be the potential sources of the haze. Our result showed that regional transport would contribute to haze formation in Beijing under such meteorological conditions, thus, to maintain the “APEC blue”, significant attention should be paid to controlling regional transport through the southwest pathway. [ABSTRACT FROM AUTHOR]

The development of wind power plays an essential role in achieving China's carbon neutrality goals and air quality standards. A large number of studies have addressed the benefits of substituting fossil fuels with wind power on climate and air quality (defined as indirect impact) by macro-scale methodology. In recent years, more and more researchers have discussed its impacts on the general atmospheric circulation and air pollution dispersion (defined as direct impact) by parameterizing wind energy extraction in meso-micro scale models. However, the comprehensive investigation (considering both direct and indirect impacts) of the utilization of wind power on atmosphere environmental impacts remains vacant. Our study first evaluated both the direct and indirect impacts of wind power on air quality through an integrated methodological framework by using WRF-CMAQ system. The present analysis took wind farms located in Zhangjiakou to explore their impacts on air quality in winter, particularly over the downwind Beijing municipal area in the North China Plain. Results indicated that the deployment of wind power leads to spatially mixed direct impacts on PM 2.5 concentrations in Beijing with a monthly net increase of 0.067 μg/m3 (0.08%) relative to the regional average. Contrarily, the substitution of coal-burning with wind power in rural household heating would result in notable indirect benefits to monthly PM 2.5 concentrations in Beijing, specifically, reducing emissions of CO 2 and conventional air pollutants by 64% in rural heating sector. The combined impacts of wind power displayed regional differences: in the wintertime (January), Zhangjiakou PM 2.5 concentrations increased (+0.147 μg/m3) whereas, decreases are achieved (−5.642 μg/m3) in Beijing. Therefore, to support the large-scale deployment of wind power, future energy policies should take comprehensive account of the diverse environmental impacts, including both the indirect benefits of fossil energy substitution and the potential direct atmospheric effects on regional air quality. [Display omitted] • Direct and indirect wind power deployment effects on air quality were evaluated. • Integrated frame treating wind extracting and emission substituting is established. • Direct impacts are generally negligible but occasionally worsen in polluted days. • Indirect impacts by substituting rural heating significantly improved air quality. • Compressive evaluation should be taken into account to support energy policies. [ABSTRACT FROM AUTHOR]

Abstract: To investigate the lag effects and seasonal differences of urban air quality change on human health, we carried out a time-series analysis of daily general practitioner consultations for allergic rhinitis (AR) in Beijing, China. In earlier publications we had assessed the relative risks of air pollutants on AR in Beijing during the period 2009–2010. This article analyzes for the same time period the lag effects of air pollutants and the seasonal effects on daily number of outpatient with allergic rhinitis; differences among age groups and gender groups were also taken into consideration. The results show that, the largest effect RRs of PM10 were at lag01, lag0, lag01, lag01, and lag01 for the total population, male, female, young/middle aged people (20–60years age group), and old people (more than 60years age group), respectively. The largest associations of SO2 were observed at lag3, lag1, lag3, lag0 and lag0 for the total population, male, female, young people/middle aged people (20–60years age group), and old people (more than 60years age group), respectively. The strongest effects of NO2 were found at lag03 for the total population, female and the young/middle aged people; at lag0 for male and lag03 for elder people. RRs of the three pollutants for AR have shown a decreasing relevance from NO2 to PM10 to SO2. The seasonal effect models show that PM10, SO2, and NO2 had higher risk for AR in the warm season than in the cold season. [Copyright &y& Elsevier]

Large areas of mainland China have been suffering frequently from heavy haze pollution during the past years, which feature high concentrations of fine particulate matter (PM 2.5 , particulate matters with aerodynamic diameters less than 2.5 μm) and low visibility. Moreover, these areas manifested strong regional complex pollution characteristics, particularly in North China including Beijing and the five surrounding provinces (BSFP). In this study, by using the localized comprehensive emission inventory of BSFP region in 2012 as an input, the Comprehensive Air Quality Model with Extensions-Particulate Matter Source Apportionment Technology (CAMx/PSAT) was used to assess the seasonal variations and source apportionment of PM 2.5 in the highly polluted BSFP region, with a specific focus on the sectoral and sub-regional contributions to PM 2.5 in Beijing during winter and summer. Results showed that the PM 2.5 concentrations of BSFP region was higher in winter than that in summer. And the heavily polluted area in BSFP region shrinked noticeably in summer, compared with winter. As for source apportionment of PM 2.5 , residential and remaining industrial sectors constituted the top two sources of PM 2.5 mass concentrations in Beijing. In addition, agricultural source represented a major contributor to ammonium, whereas transportation and power sectors constituted major sources to nitrates. In terms of contributions from sub-regions, the local sources ranked as the dominant contributors to PM 2.5 in Beijing, while the main external contributions originated from the surrounding areas, such as Hebei and Shandong. Results of daily source apportionment to PM 2.5 in Beijing showed that sub-regional long-distance transport became stronger when haze pollution was severe, in which contribution from remaining industrial sector would be higher than that of other periods. The results will allow for an improved understanding of the causes and origins of heavy regional PM 2.5 pollution, and thus will benefit the development of effective joint control policies and identification of key polluting emission categories in North China and ultimately serve as references for other highly polluted megacities in the world. Image 1 • Local sources represented the dominant contributors to ambient PM 2.5. • Residential and industrial sectors were main contributors to PM 2.5 in Beijing. • Lowering emission intensity from industrial sources should be prioritized. • Contributions from iron & steel and cement plants to PM 2.5 should be highlighted. • Contribution of regional transport became stronger during severe haze days compared to normal days. [ABSTRACT FROM AUTHOR]