Formation process of the widespread extreme haze pollution over northern China in January 2013: Implications for regional air quality and climate

Tao, Minghui; Chen, Liangfu; Xiong, Xiaozhen; Zhang, Meigen; Ma, Pengfei; Tao, Jianhua; Wang, Zifeng

doi:10.1016/j.atmosenv.2014.09.026

Cited by 185 publications

(90 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Frequently occurring severe haze is characterized by long duration, extensive coverage, and sharply increasing particulate concentration (Tao et al, 2014;Jiang and Xia, 2017). It has been suggested that severe haze pollution increases the risk of respiratory and cardiovascular diseases (Chen et al, 2013;Pan et al, 2014; Z. L. Gao et al, 2015;Zhou et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

et al. 2018

View full text Add to dashboard Cite

Abstract. To evaluate the environmental effectiveness of the control measures for atmospheric pollution in Shijiazhuang, China, a large-scale controlling experiment for emission sources of atmospheric pollutants (i.e. a temporary emission control action, TECA) was designed and implemented during 1 November 2016 to 9 January 2017. Compared to the no-control action and heating period (NCAHP), under unfavourable meteorological conditions, the mean concentrations of PM 2.5 , PM 10 , SO 2 , NO 2 , and chemical species (Si, Al, Ca 2+ , Mg 2+ ) in PM 2.5 during the control action and heating period (CAHP) still decreased by 8, 8, 5, 19, 30.3, 4.5, 47.0, and 45.2 %, respectively, indicating that the control measures for atmospheric pollution were effective. The effects of control measures in suburbs were better than those in urban area, especially for the control effects of particulate matter sources. The control effects for emission sources of carbon monoxide (CO) were not apparent during the TECA period, especially in suburbs, likely due to the increasing usage of domestic coal in suburbs along with the temperature decreasing.The results of positive matrix factorization (PMF) analysis showed that crustal dust, secondary sources, vehicle emissions, coal combustion and industrial emissions were main PM 2.5 sources. Compared to the whole year (WY) and the no-control action and no-heating period (NCANHP), the contribution concentrations and proportions of coal combustion to PM 2.5 increased significantly during other stages of the TECA period. The contribution concentrations and proportions of crustal dust and vehicle emissions to PM 2.5 decreased noticeably during the CAHP compared to other stages of the TECA period. The contribution concentrations and proportions of industrial emissions to PM 2.5 during the CAHP decreased noticeably compared to the NCAHP. The pollutants' emission sources during the CAHP were in effective control, especially for crustal dust and vehicles. However, the necessary coal heating for the cold winter and the unfavourable meteorological conditions had an offset effect on the control measures for emission sources to some degree. The results also illustrated that the discharge of pollutants might still be enormous even under such strict control measures.

show abstract

Section: Introductionmentioning

confidence: 99%

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Developing countries usually experience severely high concentrations of air pollutants due to fast growth of population, industrialization, transportation, and urbanization without prompt emission controls. As one of such countries, China started to publish real-time concentration data of six criteria pollutants from the ambient air quality monitoring networks after multiple severe pollution events across the country (Sun et al, 2014;M. Tao et al, 2014;Zheng et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

et al. 2016

View full text Add to dashboard Cite

Abstract. China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O 3 ), total PM 2.5 , and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O 3 and PM 2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O 3 generally occurs at low concentration range while underprediction of PM 2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM 2.5 exist and wind speed and direction play important roles in high PM 2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO 2− 4 ), nitrate (NO − 3 ), ammonium (NH + 4 ), and primary organic aerosol (POA) are the most important PM 2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

show abstract

“…One implication is that in the 1980s and part of the 1990s, synoptic conditions might have been playing a major role in modulating aerosol variability. For example, several extremely heavy pollution events are believed to be linked to stagnant weather (Tao et al, 2014;Zheng et al, 2015). After the mid-1990s, emission might have become more dominate, which tends to increase both the extreme and the mean.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Different trends in extreme and median surface aerosol extinction coefficients over China inferred from quality-controlled visibility data

Zhao

2018

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. Although the temporal changes in aerosol properties have been widely investigated, the majority of studies has focused on average conditions without much emphasis on the extremes. However, the latter can be more important in terms of human health and climate change. This study uses a previously validated, quality-controlled visibility dataset to investigate the long-term trends (expressed in terms of relative changes) in extreme surface aerosol extinction coefficient (AEC) over China and compares them with the median trends. Two methods are used to independently evaluate the trends, which arrive at consistent results.

show abstract

Formation process of the widespread extreme haze pollution over northern China in January 2013: Implications for regional air quality and climate

Cited by 185 publications

References 20 publications

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

Different trends in extreme and median surface aerosol extinction coefficients over China inferred from quality-controlled visibility data

Contact Info

Product

Resources

About