Temporal-spatial characteristics and source apportionment of PM2.5 as well as its associated chemical species in the Beijing-Tianjin-Hebei region of China

Gao, Jiajia; Wang, Kun; Wang, Yong; Shu-Han, Liu; Zhu, Chuanyong; Hao, Jiming; Liu, Huanjia; Hua, Shenbing; Tian, Hezhong

doi:10.1016/j.envpol.2017.10.123

Cited by 282 publications

(119 citation statements)

References 46 publications

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“…Considering that the toxicity of Cr is dependent on its valence states [19] and the concentration ratio of Cr(VI) and Cr(III) is about 1 to 6 [37], the concentrations of Cr in this study were still higher. The concentration of As in both the spring and winter were lower than the corresponding standard value and the values reported in other cities [27,28,31]. The concentrations of most of heavy metals in PM2.5 in this work were lower than those in Foshan [31], but much higher than those in Beijing [27], Shanghai [28], Nanjing [19], and Taichung [29].…”

Section: Health Risk Assessmentcontrasting

confidence: 38%

“…The concentration of As in both the spring and winter were lower than the corresponding standard value and the values reported in other cities [27,28,31]. The concentrations of most of heavy metals in PM 2.5 in this work were lower than those in Foshan [31], but much higher than those in Beijing [27], Shanghai [28], Nanjing [19], and Taichung [29]. The 48-h back trajectories starting at 300 m from NUC were computed by using the HYSPLIT 4 model of the National Oceanic and Atmospheric Administration (NOAA) (https://ready.arl.noaa.gov/HYSPLIT.php).…”

Section: Health Risk Assessmentmentioning

confidence: 77%

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Sources and Health Risks of Heavy Metals in PM2.5 in a Campus in a Typical Suburb Area of Taiyuan, North China

2018

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Abstract:To evaluate air pollution and the public health burden of heavy metals in PM 2.5 in a campus with a population of approximately 40,000 in a typical suburb area of Taiyuan, North China, PM 2.5 measurements were conducted during the spring and winter of 2016. The average concentrations of PM 2.5 in spring and winter were 97.3 ± 35.2 µg m −3 and 205.9 ± 91.3 µg m −3 , respectively. The order of concentration of heavy metals in PM 2.5 was as follows: Zn > Pb > Mn > Cu > Cr > Ni > Cd > As, in both spring and winter. The concentrations of Cd and Pb in winter and the concentrations of Cr in both spring and winter in this study were significantly higher than the corresponding air quality standard values. Road/soil dust, industrial emissions/coal combustion, and vehicle emissions/oil combustion and coal combustion/industrial emissions, road/soil dust, and vehicle emissions/oil combustion were identified by principal component analysis to be the major sources of heavy metals for spring and winter, respectively. The carcinogenic risks posed by Cr via the three exposure pathways (except for inhalation exposure to children) and by Pb via ingestion exposure exceeded the acceptable level for both children and adults. The non-carcinogenic risks posed by Mn via inhalation for both children and adults, and by Cr and Pb for children via ingestion exceeded the acceptable level.

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Section: Health Risk Assessmentcontrasting

confidence: 38%

Section: Health Risk Assessmentmentioning

confidence: 77%

Sources and Health Risks of Heavy Metals in PM2.5 in a Campus in a Typical Suburb Area of Taiyuan, North China

2018

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“…Although some essential directives mitigating the effects of traffic and industrial pollutants were announced and implemented in megacities and industrial areas in the past decade [10], heavy metals pollution in PM2.5 in this work was still found to be very serious during the sampling days. As shown in Table 1, it is evident that the levels of most heavy metals in PM2.5 in the present study were consistent with those reported in Taiyuan by other researchers [51,52], but much higher than most of those reported in other cities of China [38,42,45,[53][54][55][56]. In particular, the concentrations of some carcinogenic contaminants were much higher than those reported in other cities.…”

Section: Levels Of Heavy Metals In Pm 25supporting

confidence: 81%

Characteristics and Sources of Heavy Metals in PM2.5 during a Typical Haze Episode in Rural and Urban Areas in Taiyuan, China

et al. 2017

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PM 2.5 samples were collected in the rural and urban areas of Taiyuan, China during a typical haze episode and the heavy metals (Cr, Mn, Ni, Cu, Zn, As, Cd and Pb) in PM 2.5 were analyzed. The haze was characterized by start-up stage with a daily mean PM 2.5 of 149.34 ± 52.33 and 146.73 ± 18.96 µg m −3 in the rural and urban sites, respectively, a peak stage (288.20 ± 12.43 and 323.44 ± 5.23 µg m −3 ), and a weakening stage (226.59 ± 12.43 and 195.60 ± 2.93 µg m −3 ). The concentrations of PM 2.5 in the rural and urban sites in the peak stage were 5.9 and 5.5 times higher than those in the normal stage, respectively. The order of concentrations of heavy metals in PM 2.5 at the rural and urban sites were the same and are listed as follows: Zn > Pb > Mn > Cr > Cu > Ni > Cd > As. Pb at the rural site, As at the urban site, and Cd at the both sites failed to meet the air quality standard. The concentrations of Pb and Zn were higher at the rural site than those at the urban site. Principal component analysis indicated that the main sources of heavy metals for the rural area were raw coal combustion and soil/road dust, and for the urban area were coal combustion/industrial emissions, road/soil dust, and vehicle emissions/oil combustion.

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“…The concentration differences of K, Cr, Mn, Fe, Cu, and Pb during HP days and MP days were statistically significant ( p < 0.05) based on the Mann‐Whitney U test, while the differences of Ni, As, Se, and Zn during these two periods were not statistically significant. It is known that the local emissions of industrial activities, coal combustion, and biomass burning are lower in urban Beijing than in the areas outside Beijing in the BTH (Gao et al, ; Liu et al, ; Zhu et al, ); this is because a series of the strictest air pollution control measures were taken in the Beijing Municipality, including phasing out and/or relocation of highly polluting industries, reduction in coal consumption, and usage of clean energy. Consequently, during the highest polluted days, there was some decline in the concentrations of K, Cr, Mn, Fe, Ni, Zn, and Pb, which are closely associated with industrial emission and coal combustion.…”

Section: Resultsmentioning

confidence: 99%

“…As shown in Figure , significant correlations were recorded between TEs, sulfate, and the sulfur oxidation ratio ( SOR ) which is defined as n SO 4 2− /( n SO 4 2− + n SO 2 ) (where n is the molar concentration) in autumn and winter when severe particulate air pollution frequently occurred (Gao et al, ). The aim of looking for an association of TEs with the formation of sulfate is to obtain some preliminary insights into the issue for scientists and the public because sulfate formation is a matter of serious concern in China (He et al, ; Huang et al, ; Wang et al, ; Zheng et al, ).…”

Section: Resultsmentioning

confidence: 99%

Characteristics and Sources of Hourly Trace Elements in Airborne Fine Particles in Urban Beijing, China

Cui

Chen

et al. 2019

JGR Atmospheres

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To better investigate the characteristics and sources of trace elements (TEs) in PM2.5 in urban Beijing, a 1‐year hourly observation was continuously made using an online multi‐element analyzer from 1 June 2016 to 31 May 2017. The average concentrations of 14 individual TEs ranged from 1.1 (V) to 900 ng/m3 (K). The occurrence levels of most TEs of interest in Beijing were lower than those in most domestic cities, but higher than those in most foreign countries. The formation of sulfate increased with the concentrations of all studied TEs during autumn and winter. Dust, industry, biomass burning and waste incineration, vehicle emissions, coal combustion, and oil combustion were identified by the positive matrix factorization (PMF) model, which accounted for 36.3%, 10.7%, 27.1%, 13.7%, 7.6%, and 4.6%, respectively, of the total elements. All factors exhibited higher concentrations on weekends than on weekdays. Local vehicular emissions and industry contributed to the loading of TEs, but dust, biomass burning and waste incineration, coal combustion, and oil combustion from neighboring areas appeared to be dominant sources of TEs. Except for dust and industry, the four other sources of TEs were mainly located in the south and southeast areas of the sampling site. The analysis by conditional probability function and potential source contribution function showed that the distribution of the PMF sources of TEs roughly agreed with the location of the main point sources. Overall, this work provides more detailed information on the characteristics of the TEs for the scientific community and modelling work.

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Temporal-spatial characteristics and source apportionment of PM2.5 as well as its associated chemical species in the Beijing-Tianjin-Hebei region of China

Cited by 282 publications

References 46 publications

Sources and Health Risks of Heavy Metals in PM2.5 in a Campus in a Typical Suburb Area of Taiyuan, North China

Sources and Health Risks of Heavy Metals in PM2.5 in a Campus in a Typical Suburb Area of Taiyuan, North China

Characteristics and Sources of Heavy Metals in PM2.5 during a Typical Haze Episode in Rural and Urban Areas in Taiyuan, China

Characteristics and Sources of Hourly Trace Elements in Airborne Fine Particles in Urban Beijing, China

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