Impact of synoptic patterns and meteorological elements on the wintertime haze in the Beijing-Tianjin-Hebei region, China from 2013 to 2017

Assessing the role of cold front passage and synoptic patterns on air pollution in the Korean Peninsula

Various numerical experiments using WRF (Weather Research & Forecasting Model) and CMAQ (Community Multiscale Air Quality Modeling System) were performed to analyze the phenomenon of rapidly high concentration PM2.5 after the passage of a cold front in an area with limited local emissions. The episode period was from January 14 to 23, 2018, and analysis was conducted by dividing it into two stages according to the characteristics of changes in PM2.5 concentrations during the period. Through the analysis of observational data during the episode period, we confirmed meteorological impacts (decrease in temperature, increase in wind speed and relative humidity) and an increase in air pollution (PM10 and PM2.5) attributed to the passage of a cold front. Using CMAQ's IPR (Integrated Process Rate) analysis, the contribution of the horizontal advection process was observed in transporting PM2.5 to Gangneung at higher altitudes, and the PM2.5 concentrations at the surface increased because the vertical advection process was influenced by the terrain. Notably, in Stage 2 (64 μg·m-3), a higher contribution of the vertical advection process compared to Stage 1 (35 μg·m-3) was observed, which is attributed to the differences in synoptic patterns following the passage of the cold front. During Stage 2, following the cold front, atmospheric stability (dominance of high-pressure system) led to air subsidence and the presence of a temperature inversion layer, creating favorable meteorological conditions for the accumulation of air pollutants. This study offers the mechanisms of air pollution over the Korean Peninsula under non-stationary meteorological conditions, particularly in relation to the passage of the cold front (low-pressure system). Notably, the influence of a cold front can vary according to the synoptic patterns that develop following its passage.

Large contributions of emission reductions and meteorological conditions to the abatement of PM2.5 in Beijing during the 24th Winter Olympic Games in 2022

To guarantee the blue skies for the 2022 Winter Olympics held in Beijing and Zhangjiakou from February 4 to 20, Beijing and its surrounding areas adopted a series of emission control measures. This provides an opportunity to determine the impacts of large-scale temporary control measures on the air quality in Beijing during this special period. Here, we applied the WRF-CMAQ model to quantify the contributions of emission reduction measures and meteorological conditions. Results show that meteorological conditions in 2022 decreased PM2.5 in Beijing by 6.9 and 11.8 µg/m3 relative to 2021 under the scenarios with and without emission reductions, respectively. Strict emission reduction measures implemented in Beijing and seven neighboring provinces resulted in an average decrease of 13.0 µg/m3 (-41.2%) in PM2.5 in Beijing. Over the entire period, local emission reductions contributed more to good air quality in Beijing than nonlocal emission reductions. Under the emission reduction scenario, local, controlled regions, other regions, and boundary conditions contributed 47.7%, 42.0%, 5.3%, and 5.0% to the PM2.5 concentrations in Beijing, respectively. The results indicate that during the cleaning period with the air masses from the northwest, the abatements of PM2.5 were mainly caused by local emission reductions. However, during the potential pollution period with the air masses from the east-northeast and west-southwest, the abatements of PM2.5 were caused by both local and nonlocal emission reductions almost equally. This implies that regional coordinated prevention and control strategies need to be arranged scientifically and rationally when heavy pollution events are forecasted.

Quantifying the scale-dependent relationships of PM2.5 and O3 on meteorological factors and their influencing factors in the Beijing-Tianjin-Hebei region and surrounding areas

To investigate the variations of PM2.5 and O3 and their synergistic effects with influencing factors at different time scales, we employed Bayesian estimator of abrupt seasonal and trend change to analyze the nonlinear variation process of PM2.5 and O3. Wavelet coherence and multiple wavelet coherence were utilized to quantify the coupling oscillation relationships of PM2.5 and O3 on single/multiple meteorological factors in the time-frequency domain. Furthermore, we combined this analysis with the partial wavelet coherence to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationships. The results obtained from this comprehensive analysis are as follows: (1) The seasonal component of PM2.5 exhibited a change point, which was most likely to occur in January 2017. The trend component showed a discontinuous decline and had a change point, which was most likely to appear in February 2017. The seasonal component of O3 did not exhibit a change point, while the trend component showed a discontinuous rise with two change points, which were most likely to occur in July 2018 and May 2017. (2) The phase and coherence relationships of PM2.5 and O3 on meteorological factors varied across different time scales. Stable phase relationships were observed on both small- and large-time scales, whereas no stable phase relationship was formed on medium scales. On all-time scales, sunshine duration was the best single variable for explaining PM2.5 variations and precipitation was the best single variable explaining O3 variations. When compared to single meteorological factors, the combination of multiple meteorological factors significantly improved the ability to explain variations in PM2.5 and O3 on small-time scales. (3) Atmospheric teleconnection factors were important driving factors affecting the response relationships of PM2.5 and O3 on meteorological factors and they had greater impact on the relationship at medium-time scales compared to small- and large-time scales.

Significantly mitigating PM2.5 pollution level via reduction of NOx emission during wintertime

Despite considerable decreases in fine particulate matter (PM2.5) in Chinese megacities over the past decade, many second- and third-tier cities that distribute abundant industrial enterprises are still facing great challenges for PM2.5 further reduction under the recent policy background of eliminating heavily-polluted weather. In view of core effects of NOx on PM2.5, the deeper reductions of NOx in these cities are expected to break the plateau of PM2.5 decline, however, the link between NOx emission and PM2.5 mass loading is currently lacking. Herein, we progressively construct an evaluation system for PM2.5 productions based on daily NOx emissions in a typical industrial city (Jiyuan), considering a sequence of nested parameters involving evolutions of NO2 into nitric acid and then nitrate, and contributions of nitrate to PM2.5. The evaluation system was subsequently validated to better reproduce real increasing processes for PM2.5 pollution based on 19 pollution cases, with root mean square errors of 19.2 ± 16.4 %, suggesting the feasibility of developing NOx emission indicators linked to goals of mitigating atmospheric PM2.5. Additionally, further comparative results reveal that currently high NOx emissions in this industrial city severely hinder the achievement of atmospheric PM2.5 environmental capacity targets, especially in the scenarios of high initial PM2.5 level, low planetary boundary layer height and long pollution duration. It is anticipated that these methodologies and findings would supply guidelines for further regional PM2.5 mitigation, in which source-oriented NOx indicators could also provide some orientations for industrial cleaner production such as denitrification and low nitrogen combustion.

Substantial short- and long-term health effect due to PM2.5 and the constituents even under future emission reductions in China

Heavy pollution events of fine particulate matter (PM_2.5) frequently occur in China, seriously affecting the human health. However, how meteorological factors and anthropogenic emissions affect PM_2.5 and the major constituents, as well as the subsequent health effect, remains unclear. Here, based on regional climate and air quality models Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ), the PM_2.5 and major constituents in China at present and mid-century under the carbon neutral scenario Shared Socioeconomic Pathways (SSP)1-2.6 are simulated. Due to anthropogenic emission reduction, concentrations of PM_2.5 and the constituents decrease substantially in SSP1-2.6. The long-term exposure premature deaths at present are 2.23 million per year in mainland China, which is projected to increase by 76 % under SSP1-2.6 despite emission reduction, primarily attributable to aging which strikingly offsets the effect of air quality improvement. The number of annual premature deaths resulting from short-term exposure is 228,104 in mainland China at present, which is projected to decrease in the future. Using North China Plain as an example, we identify that among the major constituents of PM_2.5, organic carbon leads to the most short-term exposure deaths considering the largest exposure-response coefficient. Regarding the abnormally meteorological conditions, we find, relative to low relative humidity (RH) and non-stagnation, the compound events, defined as concurrence of high RH and atmospheric stagnation, exhibit an amplified role inducing larger premature deaths compared to the additive effect of the individual event of high RH and atmospheric stagnation. This nonlinear effect occurs at both present and future, but diminished in future due to emission reductions. Our study highlights the importance of considering both the long- and short-term premature deaths associated with PM_2.5 and the constituents, as well as the critical effect of extreme weather events.

Synergistic interactions of fine particles and radiative effects in modulating urban heat islands during winter haze event in a cold megacity of Northeast China

Severe air pollution and urban heat islands (UHI) intensity (UHII) are two challenging problems that have attracted wide attention in populated cities. However, previous studies mostly focused on the relationship between fine particulate matter (PM_2.5) and UHII, but how UHII responds to the interactions between radiative effects (direct effect (DE), indirect effect (IDE) with slope and shading effects (SSE)) and PM_2.5 during heavy pollution is still unclear, especially in the cold region. Therefore, this study explores the synergistic interactions between PM_2.5 and radiative effects in influencing UHII during a heavy pollution event in the cold-megacity of Harbin-China. Hence, we designed four scenarios: non-aerosol radiative feedback (NARF), DE, IDE, and combined effects (DE + IDE + SSE) in December 2018 (clear-episode) and December 2019 (heavy-haze-episode) using numerical modeling. The results showed that the radiative effects influenced the spatial distribution of PM_2.5 concentration leading to a mean drop in 2-m air-temperature by approximately 0.67 °C (downtown) and 1.48 °C (satellite-town) between the episodes. The diurnal-temporal variations revealed that the daytime and nighttime UHIIs were strengthened in the downtown during the heavy-haze-episode, while a reverse effect was observed in the satellite-town. Interestingly, during the heavy-haze-episode, the considerable difference between excellent and heavily polluted PM_2.5 levels showed a decrease in UHIIs (1.32 °C, 1.32 °C, 1.27 °C, and 1.20 °C) due to the radiative effects (NARF, DE, IDE, and (DE + IDE + SSE)), respectively. In assessing other pollutants' interactions with the radiative effects, PM₁₀ and NOx had a considerable impact on the UHII during the heavy-haze episode while O₃ and SO₂ were discovered to be very low in both episodes. Moreover, the SSE has uniquely influenced UHII, especially during the heavy-haze-episode. Therefore, insight from this study provides an understanding of how UHII responds uniquely in the cold region, which in turn could help to formulate effective policies and co-mitigation strategies for air pollution and UHI problems.

Analysis of Factors Influencing Air Quality in Different Periods during COVID-19: A Case Study of Tangshan, China

This study aimed to analyze the main factors influencing air quality in Tangshan during COVID-19, covering three different periods: the COVID-19 period, the Level I response period, and the Spring Festival period. Comparative analysis and the difference-in-differences (DID) method were used to explore differences in air quality between different stages of the epidemic and different years. During the COVID-19 period, the air quality index (AQI) and the concentrations of six conventional air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃-8h) decreased significantly compared to 2017-2019. For the Level I response period, the reduction in AQI caused by COVID-19 control measures were 29.07%, 31.43%, and 20.04% in February, March, and April of 2020, respectively. During the Spring Festival, the concentrations of the six pollutants were significantly higher than those in 2019 and 2021, which may be related to heavy pollution events caused by unfavorable meteorological conditions and regional transport. As for the further improvement in air quality, it is necessary to take strict measures to prevent and control air pollution while paying attention to meteorological factors.

Variability of turbulence dispersion characteristics during heavy haze process: A case study in Beijing

The turbulent standard deviations and the turbulent third-order and fourth-order moments are the key turbulence dispersion parameters in Lagrangian dispersion models. However, the characteristics of these parameters under heavy haze conditions in urban areas have not been fully investigated, and the commonly used similarity relations of these parameters in models were based on observations in highly flat and sparsely populated areas. In this paper, the vertical profiles of these parameters and their local similarity relations under heavy haze conditions in the wintertime of Beijing have been analyzed by using data collected at a 325-m meteorological tower. The heavy haze process has been divided into three stages: transport stage (TS), cumulative stage (CS), and dispersion stage (DS). Results show that the turbulent dispersion parameters behave differently during three stages. In the TS and DS, the maxima appear in the profiles of the turbulent standard deviations above the urban canopy; in the CS, the turbulent standard deviation are almost constant with height. The analysis of the third and fourth order moments shows that the wind velocities above the urban canopy in the TS deviate from the Gaussian distribution more significantly than those in the CS and DS. The local similarity relations of the turbulent dispersion parameters in the TS, especially for the longitudinal wind components, are normally different from those in the CS and DS. Thus, different from the common assumptions in Lagrangian models, the turbulence dispersion in horizontal directions is anisotropic and should be parameterized by multiple similarity relations under heavy haze conditions.

Spatiotemporal variations of PM2.5 pollution and its dynamic relationships with meteorological conditions in Beijing-Tianjin-Hebei region

Identifying the effects of meteorological conditions on PM_2.5 pollution is of great significance to explore methods to reduce atmospheric pollution. This study attempts to analyze the spatiotemporal variations of PM_2.5 pollution and its dynamic nexus with meteorological factors in the Beijing-Tianjin-Hebei (BTH) region from 2015 to 2020 using standard deviation ellipse (SDE) and panel vector autoregressive (PVAR) model. The results indicate that: (1) In 2015-2020, PM_2.5 pollution decreased significantly, indicating air pollution control policies in China have taken effect; Also, it showed a cumulative effect, or there was the path dependence of air pollution. (2) PM_2.5 pollution presented a distribution pattern from northeast to southwest, while the directionality of air pollution has weakened. Based on SDE, PM_2.5 pollution in Cangzhou can reflect the average level in the BTH; (3) Meteorological conditions exhibited a lagged and sustained effect on PM_2.5 pollution. Specifically, the effects of meteorological factors on PM_2.5 presented disequilibrium over time. In the long run, precipitation and temperature mainly showed negative impacts on PM_2.5 pollution, while wind speed, relative humidity and sunshine duration aggravated PM_2.5 pollution in the BTH. This study contributes to extending the study on the spatiotemporal evolution of PM_2.5 pollution and its links with meteorological conditions.

The Heavy Particulate Matter Pollution During the COVID-19 Lockdown Period in the Guanzhong Basin, China

Nationwide restrictions on human activities (lockdown) in China since 23 January 2020, to control the 2019 novel coronavirus disease pandemic (COVID-19), has provided an opportunity to evaluate the effect of emission mitigation on particulate matter (PM) pollution. The WRF-Chem simulations of persistent heavy PM pollution episodes from 20 January to 14 February 2020, in the Guanzhong Basin (GZB), northwest China, reveal that large-scale emission reduction of primary pollutants has not substantially improved the air quality during the COVID-19 lockdown period. Simultaneous reduction of primary precursors during the lockdown period only decreases the near-surface PM_2.5 mass concentration by 11.6% (12.6 μg m^-3), but increases ozone (O₃) concentration by 9.2% (5.5 μg m^-3) in the GZB. The primary organic aerosol and nitrate are the major contributor to the decreased PM_2.5 in the GZB, with the reduction of 28.0% and 21.8%, respectively, followed by EC (10.1%) and ammonium (7.2%). The increased atmospheric oxidizing capacity by the O₃ enhancement facilitates the secondary aerosol (SA) formation in the GZB, increasing secondary organic aerosol and sulphate by 6.5% and 3.3%, respectively. Furthermore, sensitivity experiments suggest that combined emission reduction of NO_X and VOCs following the ratio of 1:1 is conducive to lowering the wintertime SA and O₃ concentration and further alleviating the PM pollution in the GZB.

Causes of PM2.5 pollution in an air pollution transport channel city of northern China

To develop effective mitigation policies, a comprehensive understanding of the evolution of the chemical composition, formation mechanisms, and the contribution of sources at different pollution levels is required. PM_2.5 samples were collected for 1 year from August 2016 to August 2017 at an urban site in Zibo, then chemical compositions were analyzed. Secondary inorganic aerosols (SNA), anthropogenic minerals (MIN), and organic matter (OM) were the most abundant components of PM_2.5, but only the mass fraction of SNA increased as the pollution evolved, implying that PM_2.5 pollution was caused by the formation of secondary aerosols, especially nitrate. A more intense secondary transformation was found in the heating season (from November 15, 2016, to March 14, 2017), and a faster secondary conversion of nitrate than sulfate was discovered as the pollution level increased. The formation of sulfate was dominated by heterogeneous reactions. High relative humidity (RH) in polluted periods accelerated the formation of sulfate, and high temperature in the non-heating season also promoted the formation of sulfate. Zibo city was under ammonium-rich conditions during polluted periods in both seasons; therefore, nitrate was mainly formed through homogeneous reactions. The liquid water content increased significantly as the pollution levels increased when the RH was above 80%, indicating that the hygroscopic growth of aerosol aggravated the PM_2.5 pollution. Source apportionment showed that PM_2.5 was mainly from secondary aerosol formation, road dust, coal combustion, and vehicle emissions, contributing 36.6%, 16.5%, 14.7%, and 13.1% of PM_2.5 mass, respectively. The contribution of secondary aerosol formation increased remarkably with the deterioration of air quality, especially in the heating season.

Mechanism of haze pollution in summer and its difference with winter in the North China Plain

Heavy haze pollution usually occurs in winter. However, according to the enhanced atmospheric boundary layer (ABL) field experiments conducted in the North China Plain (NCP) from 17 June to 6 July 2019, heavy haze pollution may also occur in summer, although with a lower probability. Winter haze pollution is significantly affected by adverse boundary layer meteorological conditions, whereas our study shows different mechanisms of summer haze pollution from that of winter. In summer, PM_2.5 is distributed uniformly as a thick layer at a lighter pollution level; however, the PM_2.5 column content in summer exceeds that in winter, suggesting that the better air quality in summer is mainly due to improved diffusion conditions. In summer, even under haze conditions, the ABL can develop over 1000 m and has a large ventilation similar to clean periods, which indicates both favourable vertical diffusion conditions and advection capability of the summer ABL. Unlike in winter, the heavy haze pollution in summer is often caused by regional transport which is related to local circulation. To explore the influence of different scale systems on summer haze pollution, we applied the spectral analysis method to surface PM_2.5 concentrations. Strong periodicity of PM_2.5 concentrations is found in 4-9 d and 1 d, corresponding to the impacts of large-scale synoptic system changes and the ABL evolution, respectively. The influence of weather change is much stronger than that of the ABL evolution on PM_2.5 concentrations in summer. The resulting changes in PM_2.5 concentrations are approximately 45 μg/m³ and 15 μg/m³, respectively. There has been a consensus on the importance of emission control in winter. And this study shows that heavy haze pollution can also occur in summer and regional joint emission control should also be emphasized in summer.

The deep blue day is decreasing in China

The deep blue sky is an indicator of a lower concentration of aerosols and a cloudless sky. With increasing human emissions, a trend towards days with fewer deep blue skies might indicate a decline in a good living environment for humans. This study investigates the long-term changes of the deep blue sky in China from 1980 to 2018. Due to a lack of direct measurements, we use atmospheric visibility and low cloud cover to classify blue sky days into three grades: light blue day, medium blue day, and deep blue day. Climatologically, annual deep blue days increase from southeast China to northwest China, with the maximum number in Xinjiang and eastern Inner Mongolia and the minimum number in western Qinghai and southern Hebei. From 1980 to 2018, annual deep blue days show a prominent decreasing trend in most of China, with area-mean annual deep blue days decreasing by -0.48 days per year (d/y) in China, and the variation becomes more obvious after 2013. The maximum decreasing trend is observed in eastern China. The most prominent decreases of deep blue days are seen in winter. Both air pollution and the change in meteorological conditions contribute to the decrease of wintertime deep blue days in China. Specifically, the decrease in surface wind speed hinders the cleaning of air by winds, the increase in surface air temperature, and decrease in relative humidity is favorable for low cloud increase, and the increasing emission of pollution reduces atmospheric visibility.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00704-021-03898-1.

Polyethylene mesh knitted fabrics mulching the soil to mitigate China's haze: A potential source of PBDEs

The fate of polybrominated diphenyl ethers (PBDEs) from polyethylene mesh knitted fabrics (PMKFs) to mulched soil and nearby plants was studied. PBDEs in the soil sample collected from Tianjin University of Commerce in April 2019 increased significantly after 6 months of PMKF mulching owing to PMKFs as the main input source. The compositional profiles/congener patterns of the PBDEs in the soil and PMKFs became similar after 6 months. High correlations were found between ΣPBDEs in the soil and PMKFs in October 2019, with no significant correlation in April. Plants could take up, accumulate and biotransform PBDEs in contaminated soil. The uptake of BDE-209 by plants was the highest compared with other lesser brominated PBDE congeners, due to its higher log Kow value and molecular weight or size. BDE-47 taken up in the plant was biotransformed via hydroxylation. These results prove that the government's PMKF solution to haze is causing environmental problems in bare soil, i.e., PBDE pollution in both soil and nearby plants. The present study provides important pieces of evidence for government and policymakers, and it is recommended that one environmental problem is not solved by creating another.

Assessment of the effects of straw burning bans in China: Emissions, air quality, and health impacts

Open biomass burning (OBB) plays an important role in air pollution and climate change by releasing short-term but intensive amounts of particulate matter and gaseous air pollutants. During past years, policies with respect to prohibition on open straw burning have been issued in China in order to mitigate the air pollution problems and the effectiveness of these straw burning bans in different regions remains to be evaluated. In this study, open crop straw burning (OCSB) emissions during 2010-2018 were analyzed based on a commonly used emission inventory with high spatial and temporal resolution. High emissions concentrated over Northeast China (31.8% of national total PM_2.5 emissions in 2018), East China (24.0%), and North China (16.6%). Simulations based on an integrated meteorology-air quality modeling system and an exposure-response function show that OCSB emissions could increase monthly PM_2.5 concentration by as much as 10 μg/m³ during burning seasons in Northeast China and were associated with 4741 premature deaths in 2018. Spatial heterogeneities were observed with respect to the trends of OCSB emissions during 2010-2018. In East China, North China, and Central China, OCSB emissions showed a general declining trend since 2013 while an opposing increasing trend was observed in Northeast China with peak emissions in 2017. Comparing 2013 (before intensive implementation of straw burning bans) and 2018 (after), national total PM_2.5 emissions from OCSB activities decreased by 46.9%, ranging from -14.1% to +70% depending on the specific regions. Northeast China is the only region that showed higher OCSB emissions in 2018 compared to 2013, probably associated with the relatively delayed implementation of the straw burning bans. Avoided number of premature deaths due to reduced OCSB emissions was estimated to be 4256 on a national scale, with most health benefits gained in East and Central China. Results from this study demonstrate the importance of OCSB contribution to PM_2.5 concentrations and spatial heterogeneities exist in terms of the effectiveness of the straw burning bans in reducing OCSB emissions and gained health benefits.

Characteristics of chemical profile, sources and PAH toxicity of PM2.5 in beijing in autumn-winter transit season with regard to domestic heating, pollution control measures and meteorology

Several air pollution episodes occurred in Beijing before and after the 2014 Asia-Pacific Economic Cooperation (APEC) summit, during which air-pollution control measures were implemented. Within this autumn-winter transit season, domestic heating started. Such interesting period merits comprehensive chemical characterization, particularly the organic species, to look into the influence of additional heating sources and the control measures on air pollution. Therefore, this study performed daily and 6h time resolved PM_2.5 sampling from the 24th October to 7th December, 2014, followed by comprehensive chemical analyses including water-soluble ions, elements and organic source-markers. Apparent alterations of chemical profiles were observed with the initiation of domestic heating. Through positive matrix factorization (PMF) source apportionment modeling, six PM_2.5 sources including secondary inorganic aerosol (SIA), traffic emission, coal combustion, industry emission, biomass burning and dust were separated and identified. Coal combustion was successfully distinguished from traffic emission by hopane diagnostic ratio. The result of this study reveals a gradual shift of dominating sources for PM pollution episodes from SIA to primary sources after starting heating. BaP_eq toxicity from coal combustion increased on average by several to dozens of times in the heating period, causing both long-term and short-term health risk. Air mass trajectory analysis highlights the regional influence of the industry emissions from the area south to Beijing. Control measures taken during APEC were found to be effective for reducing industry source, but less effective in reducing the overall PM_2.5 level. These results provide implications for policy making regarding appropriate air pollution control measures.

Mitigating NOX emissions does not help alleviate wintertime particulate pollution in Beijing-Tianjin-Hebei, China

Stringent mitigation measures have reduced wintertime fine particulate matter (PM_2.5) concentrations by 42.2% from 2013 to 2018 in the Beijing-Tianjin-Hebei (BTH) region, but severe PM pollution still frequently engulfs the region. The observed nitrate aerosols have not exhibited a significant decreasing trend and constituted a major fraction (about 20%) of the total PM_2.5, although the surface-measured NO₂ concentration has decreased by over 20%. The contributions of nitrogen oxides (NO_X) emissions mitigation to the nitrate and PM_2.5 concentrations and how to alleviate nitrate aerosols efficiently under the current situation still remains elusive. The WRF-Chem model simulations of a persistent and heavy PM pollution episode in January 2019 in the BTH reveal that NO_X emissions mitigation does not help lower wintertime nitrate and PM_2.5 concentrations under current conditions in the BTH. A 50% reduction in NO_X emissions only decreases nitrate mass by 10.3% but increases PM_2.5 concentrations by 3.2%, because the substantial O₃ increase induced by NO_X mitigation offsets the HNO₃ loss and enhances sulfate and secondary organic aerosols formation. Our results are further consolidated by the occurrence of severe PM pollution in the BTH during the COVID-19 outbreak, with a significant reduction in NO₂ concentration. Mitigation of NH₃ emissions constitutes the priority measure to effectively lower the nitrate and PM_2.5 concentrations in the BTH under current conditions, with 35.5% and 12.7% decrease, respectively, when NH₃ emissions are reduced by 50%.

City-level air quality improvement in the Beijing-Tianjin-Hebei region from 2016/17 to 2017/18 heating seasons: Attributions and process analysis

With the implementation of clean air strategies, PM_2.5 pollution abatement has been observed in the "2 + 26" cities in the Beijing-Tianjin-Hebei (BTH) region (referred to as the BTH2+26) and their surrounding areas. To identify the drivers for PM_2.5 concentration decreases in the BTH2+26 cites from the 2016/17 heating season (HS1617) to the 2017/18 heating season (HS1718), we investigated the contributions of meteorological conditions and emission-reduction measures by Community Multi-Scale Air Quality (CMAQ) model simulations. The source apportionments of five sector sources (i.e., agriculture, industry, power plants, traffic and residential), and regional sources (i.e., local, within-BTH: other cities within the BTH2+26 cities, outside-BTH, and boundary conditions (BCON)) to the PM_2.5 decreases in the BTH2+26 cities were estimated with the Integrated Source Apportionment Method (ISAM). Mean PM_2.5 concentrations in the BTH2+26 cities substantially decreased from 77.4 to 152.5 μg m^-3 in HS1617 to 52.9-101.9 μg m^-3 in HS1718, with the numbers of heavy haze (daily PM_2.5 ≥150 μg m^-3) days decreasing from 17-77 to 5-30 days. The model simulation results indicated that the PM_2.5 concentration decreases in most of the BTH2+26 cities were attributed to emission reductions (0.4-55.0 μg m^-3, 2.3-81.6% of total), but the favorable meteorological conditions also played important roles (1.9-25.4 μg m^-3, 18.4-97.7%). Residential sources dominated the PM_2.5 reductions, leading to decreases in average PM_2.5 concentrations by more than 30 μg m^-3 in severely polluted cities (i.e., Shijiazhuang, Baoding, Xingtai, and Beijing). Regional source analyses showed that both local and within-BTH sources were significant contributors to PM_2.5 concentrations for most cities. Emission controls in local and within-BTH sources in HS1718 decreased the average PM_2.5 concentrations by 0.1-47.2 μg m^-3 and 0.3-22.1 μg m^-3, respectively, relative to those in HS1617. Here we demonstrate that a combination of favorable meteorological conditions and anthropogenic emission reductions contributed to the improvement of air quality from HS1617 to HS1718 in the BTH2+26 cities.

Does public concern over haze pollution matter? Evidence from Beijing-Tianjin-Hebei region, China

Chinese residents are becoming more and more concerned about the living environment especially under the situation of environmental degradation caused by the unbalanced and inadequate economic development. The widespread of internet use provide a new way for public to express the dissatisfaction on environmental pollution. Although the public is the main body of society, the public concern over environmental issues are rarely studied. In this paper, the impact of public concern over haze on haze pollution is quantitatively examined by the utilization of econometric model. Specifically, the Baidu search index (BSI) is utilized as indicators for public concern. Using the panel data consisting of 13 cities in Beijing-Tianjin-Hebei region from the period from January 2014 to December 2019, estimation results showed a significant improvement effect of public concern on haze pollution. In general, the public concern can improve the air quality in a short turn. However, this improvement effect varies with different economic development levels. These findings can help policy makers to better understand the role of public in social governance and improve the air quality in China with the inclusion of public participation.

Construction of Meteorological Simulation Knowledge Graph Based on Deep Learning Method

With the maturity of meteorological simulation technology, the research literature in this field is undergoing a rapid increase. The published literature can provide useful guidance for current research to get scientific results; however, it tends to be rather time consuming to obtain exact knowledge from massive literature, and it is necessary to transform the literature into structured knowledge to meet the efficient management, sharing, and reuse of meteorological simulation knowledge. In this paper, methods of meteorological simulation knowledge extraction and knowledge graph construction are proposed. A deep learning model based on bilateral long short-term memory-conditional random field (BiLSTM-CRF) is used to extract the meteorological simulation knowledge from the massive literature. Then, the Neo4j graph database is used to construct the meteorological simulation knowledge graph. Based on the meteorological simulation knowledge graph, it can realize the structured storage and integration of meteorological simulation knowledge, which can bridge the gap in the transformation of massive literature to sharable and reusable knowledge. Furthermore, the meteorological simulation knowledge graph can be used as an expert resource and contribute to sustainable guidance and optimization for meteorological simulation research.

Fine-Grained Spatiotemporal Analysis of the Impact of Restricting Factories, Motor Vehicles, and Fireworks on Air Pollution

Aiming at improving the air quality and protecting public health, policies such as restricting factories, motor vehicles, and fireworks have been widely implemented. However, fine-grained spatiotemporal analysis of these policies' effectiveness is lacking. This paper collected the hourly meteorological and PM2.5 data for three typical emission scenarios in Hubei, Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD). Then, this study simulated the PM2.5 concentration under the same meteorological conditions and different emission scenarios based on a reliable hourly spatiotemporal random forest model (R2 exceeded 0.84). Finally, we investigated the fine-grained spatiotemporal impact of restricting factories, vehicles, and fireworks on PM2.5 concentrations from the perspective of hours, days, regions, and land uses, excluding meteorological interference. On average, restricting factories and vehicles reduced the PM2.5 concentration at 02:00, 08:00, 14:00, and 20:00 by 18.57, 16.22, 25.00, and 19.07 μg/m3, respectively. Spatially, it had the highest and quickest impact on Hubei, with a 27.05 μg/m3 decrease of PM2.5 concentration and 17 day lag to begin to show significant decline. This was followed by YRD, which experienced a 23.52 μg/m3 decrease on average and a 23 day lag. BTH was the least susceptible; the PM2.5 concentration decreased by only 8.2 μg/m3. In addition, influenced by intensive human activities, the cultivated, urban, and rural lands experienced a larger decrease in PM2.5 concentration. These empirical results revealed that restricting factories, vehicles, and fireworks is effective in alleviating air pollution and the effect showed significant spatiotemporal heterogeneity. The policymakers should further investigate influential factors of hourly PM2.5 concentrations, combining with local geographical and social environment, and implement more effective and targeted policies to improve local air quality, especially for BTH and the air quality at morning and night.