Polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China: Spatiotemporal patterns and emission sources

Gao, Bo; Guo, Hai; Wang, Xinming; Zhao, Xiaofei; Ling, Zhenhao; Zhang, Zhou; Liu, Tengyu

doi:10.1016/j.jhazmat.2012.07.068

Cited by 84 publications

(30 citation statements)

References 32 publications

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“…Instead, CC became the most important source of PAHs (58±4 %), and the VE contribution was even lower than the BB contribution (31±4 %). The result was consistent with our previous study which used tracer-to-PAH ratio approach to identify sources at the six sites in Guangzhou (Gao et al 2012 (Fung et al 2010). The pollutant levels were cut down by 50-75 % due to the shift of China standards (level I) to China standard (level III).…”

Section: Source Contributions To Total Pahssupporting

confidence: 93%

“…The statistical description of the data collected and a qualitative source identification using tracer/PAH ratio method were previously described in detail by Gao et al (2012). In summary, the total PAH concentrations ranged from 2.67 to 68.9 ngm −3 , with an average value of 17.1 ngm −3 , comparable to those reported in previous studies in winter Guangzhou (Li et al 2006;Yang et al 2010).…”

Section: Resultssupporting

confidence: 68%

“…Therefore, the temporal variations of ASC for VE and CC may be largely due to the change of weather conditions. As discussed in our previous paper (Gao et al 2012), during the three high-value episodes, the weather conditions were stable, namely, high temperature and solar radiation, and low wind speed, which were favorable for the accumulation of PAHs. On the other hand, during the two low-value episodes, there were two cooling processes caused by cold front and/or rain belts, which lowered the PAH concentrations.…”

Section: Source Contributions To Total Pahsmentioning

confidence: 70%

“…The sample collection and chemical analyses used in this study were detailed by Gao et al (2012). From 28 November to 23 December 2009, 24-hPM 2.5 samples were collected consecutively at six sites in Guangzhou, including two urban sites SZ and FC, two suburban sites PY and HD, and two rural sites KD and WQS (Fig.…”

Section: Sampling and Analysismentioning

confidence: 99%

“…PAHs (including picene) and specific organic tracers levoglucosan and hopanes in PM 2.5 were determined by following the procedures such as spiking labeled surrogates on the samples, ultrasonic extraction, concentration, derivatization (for levoglucosan), and gas chromatography-mass spectrometry analysis (Gao et al 2012).…”

Section: Sampling and Analysismentioning

confidence: 99%

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Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

Gao

Guo

Wang

et al. 2012

Environ Sci Pollut Res

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From 28 November to 23 December 2009, 24-h PM 2.5 samples were collected simultaneously at six sites in Guangzhou. Concentrations of 18 polycyclic aromatic hydrocarbons (PAHs) together with certain molecular tracers for vehicular emissions (i.e., hopanes and elemental carbon), coal combustion (i.e., picene), and biomass burning (i.e., levoglucosan) were determined. Positive matrix factorization (PMF) receptor model combined with tracer data was applied to explore the source contributions to PAHs. Three sources were identified by both inspecting the dominant tracer(s) in each factor and comparing source profiles derived from PMF with determined profiles in Guangzhou or in the Pearl River Delta region. The three sources identified were vehicular emissions (VE), biomass burning (BB), and coal combustion (CC), accounting for 11±2 %, 31±4 %, and 58± 4 % of the total PAHs, respectively. CC replaced VE to become the most important source of PAHs in Guangzhou, reflecting the effective control of VE in recent years. The three sources had different contributions to PAHs with different ring sizes, with higher BB contributions (75±3 %) to four-ring PAHs such as pyrene and higher CC contributions (57±4 %) to six-ring PAHs such as benzo [ghi]perylene. Temporal variations of VE and CC contributions were probably caused by the change of weather conditions, while temporal variations of BB contributions were additionally influenced by the fluctuation of BB emissions. Source contributions also showed some spatial variations, probably due to the source emission variations near the sampling sites.

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Section: Source Contributions To Total Pahssupporting

confidence: 93%

Section: Resultssupporting

confidence: 68%

Section: Source Contributions To Total Pahsmentioning

confidence: 70%

Section: Sampling and Analysismentioning

confidence: 99%

Section: Sampling and Analysismentioning

confidence: 99%

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Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

Gao

Guo

Wang

et al. 2012

Environ Sci Pollut Res

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Nonpolar organic compounds as PM_2.5 source tracers: Investigation of their sources and degradation in the Pearl River Delta, China

et al. 2016

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A group of nonpolar organic compounds (NPOCs) in five compound classes including alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and 1,3,5‐triphenylbenzene were quantified in samples of particulate matter of aerodynamic diameter less than 2.5 μm collected at four sites in the Pearl River Delta (PRD) region, China, over a 2 year period from 2011 to 2012. The four sites include industrial (Nanhai), urban (Guangzhou), urban outskirt (Dongguan), and suburban (Nansha) locations. Some NPOCs are uniquely emitted from particular combustion sources and thereby serving as markers in source apportionment. Based on this multiyear and multisite NPOC data set, spatial and seasonal variations, correlation analysis, and ratio‐ratio plots were used to investigate the source information and degradation of NPOC tracers. In summer, NPOCs showed distinct local emission characteristics, with urban sites having much higher concentrations than suburban sites. In winter, regional transport was an important influence on NPOC levels, driving up concentrations at all sampling sites and diminishing an urban‐suburban spatial gradient. The lighter NPOCs exhibited more prominent seasonal variations. Such spatiotemporal features suggest that their particle‐phase abundance is more influenced by temperature, which is a critical factor in controlling the extent of semivolatile organics partitioned into the aerosol phase. The heavier NPOCs, especially PAHs, showed negligible correlation among the four sites, suggesting more influence from local emissions. Ratio‐ratio plots indicate photodegradation and mixing of various sources for the NPOCs in the PRD. A positive matrix factorization (PMF) analysis of this large NPOC data set suggests that heavier NPOCs are more suitable source indicators than lighter NPOCs. Incorporating particle‐phase light NPOC concentrations in PMF produces a separate factor, which primarily contains those light NPOCs and likely is not a source factor. Total NPOC concentrations predicted using Pankow partitioning theory were explored as PMF inputs; however, the PMF solution is not able to fully explain the input total concentrations or to give reasonable source profiles, suggesting the need for reliable gas‐phase NPOC data before their use in source apportionment studies. In addition, degradation of NPOCs needs to be considered to avoid misinterpretation of PMF source apportionment results.

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The toxic effects of indoor atmospheric fine particulate matter collected from allergic and non‐allergic families in Wuhan on mouse peritoneal macrophages

Yan

Guo

et al. 2015

J of Applied Toxicology

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Recent studies have shown that fine particulate matter (PM2.5) is associated with multiple adverse health outcomes and PM2.5-induced oxidative stress is now commonly known as a proposed mechanism of PM2.5-mediated toxicity. However, the association between allergic symptoms in children and exposure to PM2.5 has not been fully elucidated, particularly the role of PM2.5 on the indoor environment involved in allergy or non-allergy is unknown. The aim of the present study was to explore whether indoor PM2.5 from the homes of children with allergic symptoms had more increased risks of allergy than that of healthy ones and then compare the toxicity and inflammatory response of them. In this study, indoor PM2.5 was collected from the homes of schoolchildren with allergic symptoms and those of healthy ones respectively, and components of PM2.5 were analyzed. PM2.5-mediated oxidative damage and inflammatory response were further evaluated in mouse peritoneal macrophages based on its effects on the levels of reactive oxygen species accumulation, lipid peroxidation, DNA damage or cytokine production. It seems that oxidative stress may contribute to PM2.5-induced toxicity, and PM2.5 from the allergic indoor environment produced more serious toxic effects and an inflammatory response on mouse peritoneal macrophages than that from a non-allergic indoor environment.

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Polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China: Spatiotemporal patterns and emission sources

Cited by 84 publications

References 32 publications

Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

Nonpolar organic compounds as PM_2.5 source tracers: Investigation of their sources and degradation in the Pearl River Delta, China

The toxic effects of indoor atmospheric fine particulate matter collected from allergic and non‐allergic families in Wuhan on mouse peritoneal macrophages

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Polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China: Spatiotemporal patterns and emission sources

Cited by 84 publications

References 32 publications

Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

Nonpolar organic compounds as PM2.5 source tracers: Investigation of their sources and degradation in the Pearl River Delta, China

The toxic effects of indoor atmospheric fine particulate matter collected from allergic and non‐allergic families in Wuhan on mouse peritoneal macrophages

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Nonpolar organic compounds as PM_2.5 source tracers: Investigation of their sources and degradation in the Pearl River Delta, China