scholarly journals Contributions of residential coal combustion to the air quality in Beijing-Tianjin-Hebei (BTH), China: A case study

2018 ◽  
Author(s):  
Xia Li ◽  
Jiarui Wu ◽  
Miriam Elser ◽  
Junji Cao ◽  
Tian Feng ◽  
...  
Keyword(s):  
Air Quality ◽  
Coal Combustion ◽  
Fine Particulate Matter ◽  
Clean Energy ◽  
Temporal Variations ◽  
Haze Formation ◽  
Surrounding Areas ◽  
Residential Coal ◽  
Good Agreement

Abstract. In the present study, the WRF-CHEM model is used to evaluate contributions of the residential coal combustion (RCC) emission to the air quality in Beijing-Tianjin-Hebei (BTH) during persistent air pollution episodes from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the air pollutants mass concentrations are in good agreement with observations at monitoring sites in BTH. The WRF-CHEM model also reasonably well reproduces the temporal variations of aerosol species compared with the AMS measurements in Beijing. The RCC emission plays an important role in the haze formation in BTH, contributing about 23.1 % of PM2.5 (fine particulate matter) and 42.6 % of SO2 during the simulation period on average. Organic aerosols dominate PM2.5 from the RCC emission, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emission in BTH and its surrounding areas is excluded in simulations, with a 30 % decrease of PM2.5 concentrations. However, when only the RCC emission in Beijing is excluded, the Beijing's PM2.5 level is decreased by 18.0 % on average. Our results suggest that implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the Beijing's air quality, but is not expected to bring back the blue sky to Beijing. Should the residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies need be conducted considering the uncertainties in the emission inventory and meteorological fields.

scholarly journals Contributions of residential coal combustion to the air quality in Beijing–Tianjin–Hebei (BTH), China: a case study

2018 ◽  
Vol 18 (14) ◽  
pp. 10675-10691 ◽  
Author(s):  
Xia Li ◽  
Jiarui Wu ◽  
Miriam Elser ◽  
Tian Feng ◽  
Junji Cao ◽  
...  
Keyword(s):  
Air Quality ◽  
Coal Combustion ◽  
Fine Particulate Matter ◽  
Clean Energy ◽  
Temporal Variations ◽  
Aerosol Mass ◽  
Haze Formation ◽  
Surrounding Areas ◽  
Residential Coal ◽  
Mass Concentrations

Abstract. In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing–Tianjin–Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1 % of PM2.5 (fine particulate matter) and 42.6 % of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30 % decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0 % on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields.

scholarly journals Contributions of Trans-boundary Transport to the Summertime Air Quality in Beijing, China

2016 ◽  
Author(s):  
Jiarui Wu ◽  
Guohui Li ◽  
Junji Cao ◽  
Naifang Bei ◽  
Yichen Wang ◽  
...  
Keyword(s):  
Air Quality ◽  
Control Strategies ◽  
Dominant Role ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Pollutant Emissions ◽  
Beijing China ◽  
Local Emissions ◽  
Factor Separation ◽  
Good Agreement

Abstract. In the present study, the WRF-CHEM model is used to evaluate the contributions of trans-boundary transport to the air quality in Beijing during a persistent air pollution episode from 5 to 14 July 2015 in Beijing-Tianjin-Hebei (BTH), China. Generally, the predicted temporal variations and spatial distributions of PM2.5 (fine particulate matter), O3 (ozone), and NO2 are in good agreement with observations in BTH. The WRF-CHEM model also reproduces reasonably well the temporal variations of aerosol species compared to measurements in Beijing. The factor separation approach is employed to evaluate the contributions of trans-boundary transport of emissions outside of Beijing to the PM2.5 and O3 levels in Beijing. On average, in the afternoon during the simulation episode, the pure local emissions contribute 22.4 % to the O3 level in Beijing, less than 36.6 % from pure emissions outside of Beijing. The O3 concentrations in Beijing are decreased by 5.1 % in the afternoon due to interactions of local emissions with those outside of Beijing. The pure emissions outside of Beijing play a dominant role in the PM2.5 level in Beijing, with a contribution of 61.5 %, much more than 13.7 % from pure Beijing local emissions. The emissions interactions enhance the PM2.5 concentrations in Beijing, with a contribution of 5.9 %. Therefore, the air quality in Beijing is primarily determined by the trans-boundary transport of emissions outside of Beijing during summertime, showing that the cooperation with neighboring provinces to mitigate pollutant emissions is a key for Beijing to improve air quality. Considering the uncertainties in the emission inventory and the meteorological field simulations, further studies need to be performed to improve the WRF-CHEM model simulations to reasonably evaluate trans-boundary transport contributions to the air quality in Beijing for supporting the design and implementation of emission control strategies.

scholarly journals Contributions of trans-boundary transport to summertime air quality in Beijing, China

2017 ◽  
Vol 17 (3) ◽  
pp. 2035-2051 ◽  
Author(s):  
Jiarui Wu ◽  
Guohui Li ◽  
Junji Cao ◽  
Naifang Bei ◽  
Yichen Wang ◽  
...  
Keyword(s):  
Air Quality ◽  
Dominant Role ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Pollutant Emissions ◽  
Fine Particulate ◽  
Beijing China ◽  
Local Emissions ◽  
Factor Separation ◽  
Good Agreement

Abstract. In the present study, the WRF-CHEM model is used to evaluate the contributions of trans-boundary transport to the air quality in Beijing during a persistent air pollution episode from 5 to 14 July 2015 in Beijing–Tianjin–Hebei (BTH), China. Generally, the predicted temporal variations and spatial distributions of PM2.5 (fine particulate matter), O3 (ozone), and NO2 are in good agreement with observations in BTH. The WRF-CHEM model also reproduces reasonably well the temporal variations of aerosol species compared to measurements in Beijing. The factor separation approach is employed to evaluate the contributions of trans-boundary transport of non-Beijing emissions to the PM2.5 and O3 levels in Beijing. On average, in the afternoon during the simulation episode, the local emissions contribute 22.4 % to the O3 level in Beijing, less than 36.6 % from non-Beijing emissions. The O3 concentrations in Beijing are decreased by 5.1 % in the afternoon due to interactions between local and non-Beijing emissions. The non-Beijing emissions play a dominant role in the PM2.5 level in Beijing, with a contribution of 61.5 %, much higher than 13.7 %, from Beijing local emissions. The emission interactions between local and non-Beijing emissions enhance the PM2.5 concentrations in Beijing, with a contribution of 5.9 %. Therefore, the air quality in Beijing is generally determined by the trans-boundary transport of non-Beijing emissions during summertime, showing that the cooperation with neighboring provinces to mitigate pollutant emissions is key for Beijing to improve air quality.

scholarly journals Spatial-temporal variations in surface ozone in Northern China as observed during 2009–2010 and possible implications for future air quality control strategies

2012 ◽  
Vol 12 (5) ◽  
pp. 2757-2776 ◽  
Author(s):  
G. Tang ◽  
Y. Wang ◽  
X. Li ◽  
D. Ji ◽  
S. Hsu ◽  
...  
Keyword(s):  
Air Quality ◽  
Control Strategy ◽  
Northern China ◽  
Temporal Variations ◽  
Data Availability ◽  
Pollution Monitoring ◽  
National Standard ◽  
Integrated Analysis ◽  
Spatial Coverage ◽  
Surrounding Areas

Abstract. The Project of Atmospheric Combined Pollution Monitoring over Beijing and its Surrounding Areas, was an intensive field campaign conducted over Northern China between June 2009 and August 2011 to provide a comprehensive record of ozone (O3) and nitrogen oxides (NOx) and contribute to an in-depth understanding of air pollution in Northern China and its driving forces. In this campaign, 25 stations in an air-quality monitoring network provided regional-scale spatial coverage. In this study, we analyzed the data on O3 and NOx levels obtained at 22 sites (out of 25 sites due to data availability) over Northern China between 1 September 2009 and 31 August 2010. Our goal was to investigate the O3 spatial-temporal variations and control strategy in this area. Significant diurnal and seasonal variations were noted, with the highest concentrations typically found at around 03:00 p.m. (local time) and in June. The lowest concentrations were generally found during early morning hours (around 06:00 a.m.) and in December. Compared with July and August, June has increased photochemical production due to decreased cloud cover coupled with reduced O3 loss due to less dry deposition, inducing an O3 peak appearing in June. The averaged O3 concentrations were lower in the plains area compared with the mountainous area due to the titration effects of high NOx emissions in urban areas. When the characteristics of O3 pollution in different regions were distinguished by factor analysis, we found high levels of O3 that exceeded China's National Standard throughout the plains, especially over Beijing and the surrounding areas. An integrated analysis with emissions data, meteorological data, and topography over Northern China found that the meteorological conditions were the main factors that dominated the spatial variations of O3, with the presence of abundant emissions of precursors in this area. The smog production algorithm and space-based HCHO/NO2 column ratio were used to show the O3-NOx-VOCs sensitivity and examine the control strategy of O3 over Northern China. The results show that summer O3 production in the plains and northern mountainous areas was sensitive to VOCs and NOx, respectively. The presented results are intended to provide guidance for redefining government strategies to control the photochemical formation of air pollutants over Northern China and are relevant for developing urban agglomerations worldwide.

scholarly journals Roadside Air Quality Forecasting in Shanghai with a Novel Sequence-to-Sequence Model

2020 ◽  
Vol 17 (24) ◽  
pp. 9471
Author(s):  
Dongsheng Wang ◽  
Hong-Wei Wang ◽  
Chao Li ◽  
Kai-Fa Lu ◽  
Zhong-Ren Peng ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Traffic Management ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Learning Ability ◽  
Observation Data ◽  
Deterministic Models ◽  
Co Concentrations ◽  
Air Quality Forecasting

The establishment of an effective roadside air quality forecasting model provides important information for proper traffic management to mitigate severe pollution, and for alerting resident’s outdoor plans to minimize exposure. Current deterministic models rely on numerical simulation and the tuning of parameters, and empirical models present powerful learning ability but have not fully considered the temporal periodicity of air pollutants. In order to take the periodicity of pollutants into empirical air quality forecasting models, this study evaluates the temporal variations of air pollutants and develops a novel sequence to sequence model with weekly periodicity to forecast air quality. Two-year observation data from Shanghai roadside air quality monitoring stations are employed to support analyzing and modeling. The results conclude that the fine particulate matter (PM2.5) and carbon monoxide (CO) concentrations show obvious daily and weekly variations, and the temporal patterns are nearly consistent with the periodicity of traffic flow in Shanghai. Compared with PM2.5, the CO concentrations are more affected by traffic variation. The proposed model outperforms the baseline model in terms of accuracy, and presents a higher linear consistency in PM2.5 prediction and lower errors in CO prediction. This study could assist environmental researchers to further improve the technologies for urban air quality forecasting, and serve as tools for supporting policymakers to implement related traffic management and emission control policies.

scholarly journals PM2.5 Pollution in Xingtai, China: Chemical Characteristics, Source Apportionment, and Emission Control Measures

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 121 ◽  
Author(s):  
Jun Hu ◽  
Han Wang ◽  
Jingqiao Zhang ◽  
Meng Zhang ◽  
Hefeng Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Urban Areas ◽  
Emission Control ◽  
Clean Energy ◽  
Ambient Air ◽  
Control Measures ◽  
Ambient Air Quality ◽  
Surrounding Areas ◽  
Emission Control Measures

Beijing-Tianjin-Hebei (BTH) and its surrounding areas are one of the most polluted regions in China. Xingtai, as a heavy industrial city of BTH and its surrounding areas, has been experiencing a severe PM2.5 pollution in recent years, characterized by extremely high concentrations of PM2.5. In 2014, PM2.5 mass concentrations monitored by online instruments in urban areas of Xingtai were 116, 77, 128, and 200 µg m−3 in spring, summer, autumn and winter, respectively, with annually average concentrations of 130 µg m−3 exhibiting 3.7 times higher than National Ambient Air Quality Standard (NAAQS) value for PM2.5 (35 µg m−3). To identify PM2.5 emission sources, ambient PM2.5 samples were collected during both cold and warm periods in 2014 in urban areas of Xingtai. Organic carbon (OC), sulfate, nitrate, ammonium and elemental carbon (EC) were the dominant components of PM2.5, accounting for 13%, 11%, 12%, 11% and 8% in the cold period, respectively, and 11%, 12%, 9%, 6%, and 5% in the warm period, respectively. Source apportionment results indicated that coal combustion (24.4%) was the largest PM2.5 emission source, followed by secondary sulfate (22.2%), secondary nitrate (18.4%), vehicle exhaust dust (12.4%), fugitive dust (9.7%), construction dust (5.5%), soil dust (3.4%) and metallurgy dust (1.6%). Based on PM2.5 source apportionment results, some emission control measures, such as replacing bulk coal with clean energy sources, controlling coal consumption by coal-fired boiler upgrades, halting operations of unlicensed small polluters, and controlling fugitive and VOCs emission, were proposed to be implemented in order to improve Xingtai’s ambient air quality.

scholarly journals Impacts of Meteorological Uncertainties on the Haze Formation in Beijing-Tianjin-Hebei (BTH) during Wintertime: A case study

2017 ◽  
Author(s):  
Naifang Bei ◽  
Jiarui Wu ◽  
Tian Feng ◽  
Junji Cao ◽  
Rujin Huang ◽  
...  
Keyword(s):  
Fine Particles ◽  
Initial Conditions ◽  
Control Strategies ◽  
Temporal Variations ◽  
Ensemble Mean ◽  
Haze Episode ◽  
Haze Formation ◽  
Region Scale ◽  
The Impact

Abstract. In the present study, a persistent heavy haze episode from 13 to 20 January 2014 in Beijing-Tianjin-Hebei (BTH) is simulated using the WRF-CHEM model through ensemble simulations to investigate impacts of meteorological initial uncertainties on the haze formation. Model results have shown that uncertainties in meteorological initial conditions substantially influence the aerosol constituent simulations at an observation site in Beijing, and the ratio of the ensemble spread to ensemble mean (RESM) exceeds 50 %. The ensemble mean generally preforms well in reproducing the fine particles (PM2.5) temporal variations and spatial distributions against measurements in BTH. The initial meteorological uncertainties do not alter the PM2.5 distribution pattern in BTH principally or dominate the haze formation and development, but remarkably affect the simulated PM2.5 level, and the RESM of PM2.5 concentrations can be up to 30 % at the region scale. In addition, the rather large RESM in PM2.5 simulations at the city scale also causes difficulties in implementation of the control strategies. Therefore, our results suggest that the ensemble simulation is imperative to avoid the impact of the initial meteorological uncertainties on the haze prediction.

scholarly journals Impacts of meteorological uncertainties on the haze formation in Beijing–Tianjin–Hebei (BTH) during wintertime: a case study

2017 ◽  
Vol 17 (23) ◽  
pp. 14579-14591 ◽  
Author(s):  
Naifang Bei ◽  
Jiarui Wu ◽  
Miriam Elser ◽  
Tian Feng ◽  
Junji Cao ◽  
...  
Keyword(s):  
Fine Particles ◽  
Control Strategies ◽  
Regional Scale ◽  
Temporal Variations ◽  
Ensemble Mean ◽  
Haze Episode ◽  
Haze Formation ◽  
The Impact ◽  
The City

Abstract. In the present study, a persistent heavy haze episode from 13 to 20 January 2014 in Beijing–Tianjin–Hebei (BTH) is simulated using the WRF-CHEM model through ensemble simulations to investigate impacts of meteorological uncertainties on the haze formation. Model results show that uncertainties in meteorological conditions substantially influence the aerosol constituent simulations at an observation site in Beijing, and the ratio of the ensemble spread to the ensemble mean (RESM) exceeds 50 %. The ensemble mean generally preforms well in reproducing the fine particles' (PM2.5) temporal variations and spatial distributions against measurements in BTH. The meteorological uncertainties do not alter the PM2.5 distribution pattern in BTH principally or dominate the haze formation and development, but remarkably affect the simulated PM2.5 level, and the RESM for the simulated PM2.5 concentrations can be up to 30 % at the regional scale. In addition, the rather large RESM in PM2.5 simulations at the city scale also causes difficulties in evaluation of the control strategies. Therefore, our results suggest that the ensemble simulation is imperative to take into account the impact of the meteorological uncertainties on the haze prediction.

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