Source apportionment of atmospheric pollutants based on the online data by using PMF and ME2 models at a megacity, China

Liu, Baoshuang; Yang, Jialin; Yuan, Jing; Wang, Jiao; Dai, Qili; Li, Tingkun; Bi, Xinhui; Feng, Yinchang; Xiao, Zhimei; Zhang, Yufen; Xu, Hong

doi:10.1016/j.atmosres.2016.10.023

Cited by 74 publications

(26 citation statements)

References 74 publications

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“…Compared to the reported fine aerosol pH values in other cities (see Table S5), pH in Hohhot was much higher, which might have been caused by the characteristics of arid regions. Annual crustal dust contributions were about 25% which was much higher than contributions in other cities (such as Beijing and Tianjin (China) and Atlanta and Birmingham (United States)) (Lang et al, 2017;Liu et al, 2017;Verma et al, 2014;Baumann et al, 2008). On the other hand, annual secondary sulfate in Hohhot was only 13%.…”

Section: Aerosol Phmentioning

confidence: 77%

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Wang

Ding

et al. 2019

Science of The Total Environment

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Section: Aerosol Phmentioning

confidence: 77%

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Wang

Ding

et al. 2019

Science of The Total Environment

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“…Factor 3 was identified as coal combustion, as it is characterized by high Cl -, OC and EC loadings. The high Clloading associated with coal combustion in winter is a distinctive feature in Beijing and inland China (Liu et al, 2017b;Zhang et al, 2013). The contribution of coal combustion to the PM 2.5 was 21%.…”

Section: Source Apportionment Of Pm 25 For the Three Selected Episodesmentioning

confidence: 96%

“…Seven, six and six factors were found to be reasonable for E1, E2 and E3, respectively. , NH 4 + , OC and EC (Liu et al, 2017b;Singh et al, 2016;Zong et al, 2016). It is well known that vehicular emissions provide a substantial contribution to the OC and EC levels and that NH 4 + is emitted by vehicles that are equipped with three-way catalytic converters (Chang et al, 2015).…”

Section: Source Apportionment Of Pm 25 For the Three Selected Episodesmentioning

confidence: 99%

Characterization and source identification of fine particulate matter in urban Beijing during the 2015 Spring Festival

Cui

et al. 2018

Science of The Total Environment

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The Spring Festival (SF) is the most important holiday in China for family reunion and tourism. During the 2015 SF an intensive observation campaign of air quality was conducted to study the impact of the anthropogenic activities and the dynamic characteristics of the sources. During the study period, pollution episodes frequently occurred with 12days exceeding the Chinese Ambient Air Quality Standards for 24-h average PM (75μg/m), even 8days with exceeding 150μg/m. The daily maximum PM concentration reached 350μg/m while the hourly minimum visibility was <0.8km. Three pollution episodes were selected for detailed analysis including chemical characterization and diurnal variation of the PM and its chemical composition, and sources were identified using the Positive Matrix Factorization model. The first episode occurring before the SF was characterized by more formation of SO and NO and high crustal enrichment factors for Ag, As, Cd, Cu, Hg, Pb, Se and Zn and seven categories of pollution sources were identified, whereby vehicle emission contributed 38% to the PM. The second episode occurring during the SF was affected heavily by large-scale firework emissions, which led to a significant increase in SO, Cl, OC, K and Ba; these emissions were the largest contributor to the PM accounting for 36%. During the third episode occurring after the SF, SO, NO, NH and OC were the major constituents of the PM and the secondary source was the dominant source with a contribution of 46%. The results provide a detailed understanding on the variation in occurrence, chemical composition and sources of the PM as well as of the gaseous pollutants affected by the change in anthropogenic activities in Beijing throughout the SF. They highlight the need for limiting the firework emissions during China's most important traditional festival.

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“…Source apportionment studies based on online aerosol molecular/elemental composition data in China are relatively scarce. Only a few studies are found in the literature, with most of them are conducted in Jing‐Jin‐Ji region (Gao et al, ; Li, Chang, et al, ; Li, Ma, et al, ; Liu et al, ; Peng et al, ; Tian et al, ), among which only Peng et al () and Gao et al () incorporated inorganic ions, OC, EC, and elements. For the Yangtze River Delta (YRD) region, only one study was found (Wang et al, ), in which principle component analysis of major inorganic ions alone were used for source apportionment.…”

Section: Introductionmentioning

confidence: 99%

Source Apportionment of PM_2.5 Using Hourly Measurements of Elemental Tracers and Major Constituents in an Urban Environment: Investigation of Time‐Resolution Influence

et al. 2018

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We demonstrate with field data the benefit of using high‐time‐resolution chemical speciation data in achieving more robust source apportionment of fine particulate matter (PM2.5) using positive matrix factorization (PMF). Hourly composition data were collected over a month in Shanghai, including four inorganic ions, 13 elements, organic, and elemental carbon. PMF analysis of the hourly data set (PMF1h) resolves eight factors: secondary nitrate/sulfate, vehicular/industrial emissions, coal combustion, secondary sulfate, tire wear, Cr and Ni point source, residual oil combustion, and dust, with the first three being the major ones and each contributing to >20% of PM2.5 mass. To characterize the benefit gained from time resolution, we carried out separate PMF analyses of 4‐ and 6‐hr averaged data of the same data set (PMF6h and PMF4h). PMF6h and PMF4h produce an eight‐factor solution sharing similar factors to those by PMF1h but show less stability and more mixing in source profiles. Profile mixing was especially noticeable for tire wear, coal combustion, and Cr and Ni point source in PMF6h, as the 6‐hr averaging significantly decreased between‐sample variability and increased rotational ambiguity. While the three sets of PMF solutions were similar in contributions for factors with major species as source markers (e.g., secondary nitrate/sulfate), larger variations existed for factors with trace species as markers due to mixing of major species in the profiles and higher rotational uncertainties in PMF4h and PMF6h. Our results indicate that hourly time series of elements and major components could achieve more robust source apportionment through better capturing of diurnal‐scale dynamics in source activities.

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Source apportionment of atmospheric pollutants based on the online data by using PMF and ME2 models at a megacity, China

Cited by 74 publications

References 74 publications

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Characterization and source identification of fine particulate matter in urban Beijing during the 2015 Spring Festival

Source Apportionment of PM_2.5 Using Hourly Measurements of Elemental Tracers and Major Constituents in an Urban Environment: Investigation of Time‐Resolution Influence

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Source apportionment of atmospheric pollutants based on the online data by using PMF and ME2 models at a megacity, China

Cited by 74 publications

References 74 publications

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Characterization and source identification of fine particulate matter in urban Beijing during the 2015 Spring Festival

Source Apportionment of PM2.5 Using Hourly Measurements of Elemental Tracers and Major Constituents in an Urban Environment: Investigation of Time‐Resolution Influence

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Source Apportionment of PM_2.5 Using Hourly Measurements of Elemental Tracers and Major Constituents in an Urban Environment: Investigation of Time‐Resolution Influence