Temporal variability of the visibility, particulate matter mass concentration and aerosol optical properties over an urban site in Northeast China

Zhao, Huiling; Che, Huizheng; Ma, Yanhui; Xia, Xiangao; Wang, Yangfeng; Wang, Peng; Wu, Xianchu

doi:10.1016/j.atmosres.2015.07.003

Cited by 53 publications

(21 citation statements)

References 63 publications

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“…For the Chinese SDS sequence and supporting dataset, no information was recorded about the concentration of dust mass (ρ). However, ρ is closely correlated to the visibility of SDS events [42][43][44][45]. In this project, we replaced ρ by visibility using the equation below [46]:…”

Section: Sand and Dust Storms Index (Sdsi)mentioning

confidence: 99%

Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data

Cao

Zhang

et al. 2018

Sustainability

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Sand and dust storms (SDS) are global phenomena that significantly impact the socio-economy, human health, and the environment. The characterization of SDS intensity is a fundamental aspect of SDS issues and studies. In this study, a sand and dust storms index (SDSI) is developed to characterize SDS intensity by addressing the potential impacts of sand and dust storms on sensitive elements. Compared with other indices, SDSI includes four SDS-related components: SDS frequency, SDS visibility, SDS duration, and SDS wind speed. Using SDSI, this study characterizes the SDS intensity in the Three-North Forest Shelterbelt Program (TNFSP) region of China. The SDSI results show that high values of SDSI are mostly concentrated in southern Xinjiang, western and central Inner Mongolia, western and central Gansu, and northern Ningxia. By analyzing the SDSI components, over half of the stations experienced sand and dust storms no more than once per year on average. Most of the SDS events reduced horizontal visibility to less than 500 m, one-third of SDS events last more than two hours, and the wind speed of over half of the SDS events varied between 10-17 m/s. In comparison with SDS frequency, SDSI performs better in reflecting the spatial and temporal variation of SDS events. Therefore, instead of SDS frequency, SDSI can be applied to studies relevant to SDS intensity. Finally, five major SDS transportation routes were identified based on the surface prevailing wind direction, SDSI, and the existing literature. The SDS routes, combined with SDSI, could help governments and policy-makers cooperate on a regional level to combat SDS events more effectively.Keywords: sand and dust storms (SDS); sand and dust storms (SDS) index; sand and dust storms (SDS) intensity; sand and dust storms (SDS) routes

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Section: Sand and Dust Storms Index (Sdsi)mentioning

confidence: 99%

Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data

Cao

Zhang

et al. 2018

Sustainability

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“…Twelve years of daily monitoring data provided a effective data source for the analysis of air pollution level of major Chinese cities [9]. However, a series of studies suggested that PM2.5 in major northern Chinese cities had been an important issue, as although the air pollution index (API) under NAAQS-1996 suggested that air quality was fine, the atmospheric conditions were poor [10][11][12][13][14][15]. In February 2012, China then released new air quality standards (NAAQS-2012) by taking into account six air pollutants: PM2.5, PM10, SO2, O3, NO2 and CO [16].…”

Section: Introductionmentioning

confidence: 99%

Seasonal Variations of Atmospheric Pollution and Air Quality in Beijing

2015

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Abstract:New ambient air quality standards were released in 2012 and implemented in 2013 with real time monitoring data publication of six atmospheric pollutants: particulate matter (PM)2.5, PM10, O3, SO2, NO2 and CO. According to the new standards, Beijing began to publicize real-time monitoring data of 35 monitoring stations in 2013. In this study, real time concentrations of all six atmospheric pollutants of all 35 monitoring stations were collected from September 2014 to August 2015 to investigate the spatial and temporal pattern of the air quality and atmospheric pollutants. By comparing the annual and seasonal variations of all six pollutants' concentrations, it was found that particulate matter, especially PM2.5, is still the major contributor to the deterioration of air quality in Beijing. Although the NO2 and O3 concentrations of some stations were still high under certain circumstances, their contributions to air quality index (AQI) were not comparable to those of PM2.5 and PM10. SO2 and CO concentrations have dropped to well below the qualification standards. Winter and autumn were the most polluted seasons for all pollutants except O3, whose concentrations are higher in summer. South and southeast stations were the most polluted compared with the rest of the stations, especially for particulate matter. Wind profile analysis with heavy pollution situations indicates that low speed southwest or east wind situations have the higher possibility of heavy pollution, suggesting that it is highly possible that long-range transportation of air pollutants from south or east neighboring provinces played an important role in the worsening air conditions in Beijing. OPEN ACCESSAtmosphere 2015, 6 1754

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“…Regional air pollution events were also reported in Northeast China in recent years. Annual mean AOD at urban regions was larger than 0.4 as a result of a mixture of anthropogenic and natural aerosols Zhao et al, 2015). Events with BC concentrations > 7 μg m -3 were often observed at Tongyu in four seasons, which was suggested to be related to long-range transport of anthropogenic emissions and biomass burning aerosols Cheng et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

A Case Study of Long-Range Transport of Smoke Aerosols from Eastern Siberia to Northeast China in July 2014

Li¹,

Xia

Song

et al. 2017

Aerosol Air Qual. Res.

Self Cite

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Long-range transport of biomass burning aerosols from Eastern Siberia to Northeast China in July 2014 was studied by using ground-based ambient measurements and satellite products. Intensive active fires were revealed in Eastern Siberia during the late of July by the Moderate Resolution Imaging Spectraradiometer (MODIS) active fire products. Under the favorable synoptic pattern, the smoke layer was transported to Northeast China, which led to significant enhancement of surface PM 2.5 concentration. The peak PM 2.5 concentration exceeded 100 μg m -3 that was 3-6 times larger than the background level. High aerosol optical depth at 550 nm with daily value exceeding 1.0 was observed at a background site in Northeast China. Smoke aerosols were characterized by fine-mode dominated particles with very weak absorption. Air quality in Northeast China was revealed to be potentially impacted by the long-range transport of smoke aerosols from Eastern Siberia during the biomass burning season, which probably impacted human health, weather and climate. Therefore, futher study on this issue is urgenly required for quantitatively evaluating potential contribution of long-range transport to regional air pollution in Northeast China.

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Temporal variability of the visibility, particulate matter mass concentration and aerosol optical properties over an urban site in Northeast China

Cited by 53 publications

References 63 publications

Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data

Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data

Seasonal Variations of Atmospheric Pollution and Air Quality in Beijing

A Case Study of Long-Range Transport of Smoke Aerosols from Eastern Siberia to Northeast China in July 2014

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