Characteristics of Particulate Matter during Haze and Fog (Pollution) Episodes over Northeast China, Autumn 2013

Yang, Li; Zhao, Huiling; Wu, Yunfei

doi:10.4209/aaqr.2014.08.0158

Cited by 31 publications

(10 citation statements)

References 41 publications

(35 reference statements)

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“…Previous studies indicated that the increase in PM 2.5 mass concentration contributed to visibility impairment significantly in China (Cao et al, 2012;Han et al, 2013;Li et al, 2015;Han et al, 2016). The relationships between visibility and PM 2.5 mass concentrations for both long-lasting haze and fog-haze mixed events are shown in Fig.…”

Section: Relationship Between Visibility and Pm 25 Mass Concentrationmentioning

confidence: 97%

Quantifying the relationship between PM<sub>2.5</sub> concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

et al. 2018

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Abstract. Air quality and visibility are strongly influenced by aerosol loading, which is driven by meteorological conditions. The quantification of their relationships is critical to understanding the physical and chemical processes and forecasting of the polluted events. We investigated and quantified the relationship between PM 2.5 (particulate matter with aerodynamic diameter is 2.5 µm and less) mass concentration, visibility and planetary boundary layer (PBL) height in this study based on the data obtained from four long-lasting haze events and seven fog-haze mixed events from January 2014 to March 2015 in Beijing. The statistical results show that there was a negative exponential function between the visibility and the PM 2.5 mass concentration for both haze and fog-haze mixed events (with the same R 2 of 0.80). However, the fog-haze events caused a more obvious decrease of visibility than that for haze events due to the formation of fog droplets that could induce higher light extinction. The PM 2.5 concentration had an inversely linear correlation with PBL height for haze events and a negative exponential correlation for fog-haze mixed events, indicating that the PM 2.5 concentration is more sensitive to PBL height in fog-haze mixed events. The visibility had positively linear correlation with the PBL height with an R 2 of 0.35 in haze events and positive exponential correlation with an R 2 of 0.56 in foghaze mixed events. We also investigated the physical mechanism responsible for these relationships between visibility, PM 2.5 concentration and PBL height through typical haze and fog-haze mixed event and found that a double inversion layer formed in both typical events and played critical roles in maintaining and enhancing the long-lasting polluted events. The variations of the double inversion layers were closely associated with the processes of long-wave radiation cooling in the nighttime and short-wave solar radiation reduction in the daytime. The upper-level stable inversion layer was formed by the persistent warm and humid southwestern airflow, while the low-level inversion layer was initially produced by the surface long-wave radiation cooling in the nighttime and maintained by the reduction of surface solar radiation in the daytime. The obvious descending process of the upper-level inversion layer induced by the radiation process could be responsible for the enhancement of the lowlevel inversion layer and the lowering PBL height, as well as high aerosol loading for these polluted events. The reduction of surface solar radiation in the daytime could be around 35 % for the haze event and 94 % for the fog-haze mixed event. Therefore, the formation and subsequent descending processes of the upper-level inversion layer should be an important factor in maintaining and strengthening the longlasting severe polluted events, which has not been revealed in previous publications. The interactions and feedbacks between PM 2.5 concentration and PBL height linked by radiation process caused a more significant an...

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Section: Relationship Between Visibility and Pm 25 Mass Concentrationmentioning

confidence: 97%

Quantifying the relationship between PM<sub>2.5</sub> concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

et al. 2018

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“…Beijing, the capital of China, a megacity with approximately 22 million inhabitants (Beijing Statistical Yearbook, 2015), has frequently suffered from extreme haze, which is characterized by high fine particle (i.e., PM 2.5 ) loading (Sun et al, 2006;Li et al, 2015). These fine particles have adverse effects on human health, can scatter and absorb the incident light and lead to atmospheric opacity, and horizontal visibility degradation (Han et al, 2015;Jing et al, 2015;Tao et al, 2015;Wu et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Variations of Chemical Composition and Source Apportionment of PM2.5 during Winter Haze Episodes in Beijing

Tao

et al. 2017

Aerosol Air Qual. Res.

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PM 2.5 samples were collected in Beijing between February 24 and March 12 of 2014, and analyzed to examine chemical compositions and origins of the PM 2.5 at pollution levels of clean (PM 2.5 < 75 µg m -3 ), light-medium (75-150 µg m -3 ), heavy (150-250 µg m -3 ) and severe (> 250 µg m -3 ). The mean PM 2.5 concentration was 137.7 ± 124.8 µg m -3 during the observation period, accounting for 66% of PM 10. As all aerosol species concentrations increased with the pollution level, the contributions of secondary inorganic aerosols (SIA) to PM 2.5 continuously increased while the contributions of OC and EC decreased, indicating a substantial contribution from secondary formation to the elevation of PM 2.5 pollution. The acidity of PM 2.5 , the ratio of anion microequivalent concentration to cation, increased from 0.96 to 1.08 as pollution levels increased. Using a PMF model, secondary inorganic aerosols, industrial emissions, soil dust, traffic emissions, and coal combustion and biomass burning were identified as contributors to the PM 2.5 , and on average accounted 46%, 20%, 10%, 6% and 18% of the PM 2.5 , respectively, in the observation period. Industrial emissions were the dominant PM 2.5 source during the clean period (60%). Except for traffic emission, sources of PM 2.5 at the light-medium level were consistent, accounting for 17%-29%. Secondary inorganic aerosols were the largest origin of PM 2.5 at heavy and severe pollution levels, accounting for 40% and 78%, respectively. In addition, the 48 h transport distances of air masses decreased from 2000 km (clean) to 300 km (severe level) and the proportion of air masses from south pollution areas in the total air masses at each pollution level increased from 0% to 97%, indicating that the stability of near surface air and the northerly transport of pollutants from the south at local and regional scales played a the key role in the PM 2.5 elevation.

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“…In China, air pollution in megacities is mainly caused by the drastic economic growth, together with the rapid industrialization and the wide urbanization (e.g., Wang et al, 2014a, b;Li et al, 2015;Lang et al, 2017). China has been suffering from serious air quality problems, mostly related to fine particulate matter (Jiang et al, 2015;Lv et al, 2015;San Martini et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Characteristics and Source Analysis of Trace Elements in PM2.5 in the Urban Atmosphere of Wuhan in Spring

Acciai

Zhang

Wang

et al. 2017

Aerosol Air Qual. Res.

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The concentrations of PM 2.5 and trace elements with hourly resolution were measured during May 2014 in urban residential area of Wuhan, the biggest city in central China. During the period of measurement, the average temperature was approximate 25°C without domestic heating and cooling. The average concentration of PM 2.5 was 95.53 µg m -3 , which was higher than the limit of Ambient Air Quality Standard of China GB3095-2012 (75 µg m -3 , Level 2). A sand storm original from Northwestern China was also recorded. Concentrations of major trace elements (K, Ca, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, As, Se, Pd, Ag, Cd, Au, Hg, Pb, Co, Sn, Sb, Tl) were comparable to previous studies, except for Ba and Ca with more than doubled concentrations (103 ng m -3 , 1,792.49 ng m -3 ) due to the storm. Enrichment Factor (EF) and Positive Matrix Factorization (PMF) were employed to characterize the emission sources. The computation of EF showed that Zincs was highly enriched. Four sources, biomass burning (63.2%) might mainly related to power plants using biowaste burning and bio-related cooking activities, metallurgical and steel industries (14%), dust crustal (12.5%) and dust associated with vehicular traffic (10.4%), were identified in decreasing order of average percentage contribution to the PM 2.5 mass with the aid of trace elements. The orientations of emission sources were also addressed.

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Characteristics of Particulate Matter during Haze and Fog (Pollution) Episodes over Northeast China, Autumn 2013

Cited by 31 publications

References 41 publications

Quantifying the relationship between PM<sub>2.5</sub> concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

Quantifying the relationship between PM<sub>2.5</sub> concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

Variations of Chemical Composition and Source Apportionment of PM2.5 during Winter Haze Episodes in Beijing

Characteristics and Source Analysis of Trace Elements in PM2.5 in the Urban Atmosphere of Wuhan in Spring

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Characteristics of Particulate Matter during Haze and Fog (Pollution) Episodes over Northeast China, Autumn 2013

Cited by 31 publications

References 41 publications

Quantifying the relationship between PM&lt;sub&gt;2.5&lt;/sub&gt; concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

Quantifying the relationship between PM&lt;sub&gt;2.5&lt;/sub&gt; concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

Variations of Chemical Composition and Source Apportionment of PM2.5 during Winter Haze Episodes in Beijing

Characteristics and Source Analysis of Trace Elements in PM2.5 in the Urban Atmosphere of Wuhan in Spring

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Quantifying the relationship between PM<sub>2.5</sub> concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

Quantifying the relationship between PM<sub>2.5</sub> concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing