Particle-bound polycyclic aromatic hydrocarbons in typical urban of Yunnan-Guizhou Plateau: Characterization, sources and risk assessment

doi:10.1007/s11783-022-1535-6

Front. Environ. Sci. Eng.

2022, Vol. 16

Issue (9) : 114 https://doi.org/10.1007/s11783-022-1535-6

RESEARCH ARTICLE

Particle-bound polycyclic aromatic hydrocarbons in typical urban of Yunnan-Guizhou Plateau: Characterization, sources and risk assessment

Yaoqian Zhong¹, Bingxin Xia¹, Jianwu Shi¹(

), Ping Ning¹(

), Chaoneng Zhang¹, Xinyu Han¹, Jiming Hao^1,²

¹. Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China
². State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China

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Abstract

• The sampling was conducted in city on the Yunnan-Guizhou Plateau for one year.

• The groups of PAHs revealed their different environmental fates and migration paths.

• Seasonal biomass burning could affect the concentration by long-distance transport.

• Industrial sources and traffic emissions were the main contributor of PAHs.

• Living in industrial areas or winter had higher health risk by exposure PAHs in PM_2.5.

Monthly particle-phase ambient samples collected at six sampling locations in Yuxi, a high-altitude city on the edge of Southeast Asia, were measured for particle-associated PAHs. As trace substances, polycyclic aromatic hydrocarbons (PAHs) are susceptible to the influences of meteorological conditions, emissions, and gas-particulate partitioning and it is challenging job to precise quantify the source and define the transmission path. The daily concentrations of total PM_2.5-bound PAHs ranged from 0.65 to 80.76 ng/m³, with an annual mean of 11.94 ng/m³. Here, we found that the concentration of PM_2.5-bound PAHs in winter was significantly higher than that in summer, which was mainly due to source and meteorology influence. The increase of fossil combustion and biomass burning in cold season became the main contributors of PAHs, while precipitation and low temperature exacerbated this difference. According to the concentration variation trend of PM_2.5-bound PAHs and their relationship with meteorological conditions, a new grouping of PAHs is applied, which suggested that PAHs have different environmental fates and migration paths. A combination of source analysis and trajectory model supported local sources from combustion of fossil fuel and vehicle exhaust contributed to the major portion on PAHs in particle, but on the Indochina Peninsula the large number of pollutants emitted by biomass burning during the fire season would affect the composition of PAHs through long-range transporting. Risk assessment in spatial and temporal variability suggested that citizens living in industrial areas were higher health risk caused by exposure the PM_2.5-bound PAHs than that in other regions, and the risk in winter was three times than in summer.

Keywords Particle-associated PAHs Fine particle Source appointment Group analysis Risk assessment Biomass burning

Corresponding Author(s): Jianwu Shi,Ping Ning

About author:

Tongcan Cui and Yizhe Hou contributed equally to this work.

Issue Date: 24 January 2022

Cite this article:

Yaoqian Zhong,Bingxin Xia,Jianwu Shi, et al. Particle-bound polycyclic aromatic hydrocarbons in typical urban of Yunnan-Guizhou Plateau: Characterization, sources and risk assessment[J]. Front. Environ. Sci. Eng., 2022, 16(9): 114.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-022-1535-6
https://academic.hep.com.cn/fese/EN/Y2022/V16/I9/114

Tab.1 Sample sites

Tab.2 PAHs (their abbreviations and molecular weight) and toxic equivalent factors (TEFs)

Fig.1 PM_2.5-bound PAHs profiles at each station and city average PAHs and other studies: Tianjin (Shi et al 2010), Taiyuan (Li et al 2014), Kunming (Bi et al 2015), Madrid (Barrado et al 2012), Italy (Martellini et al 2012), Malaysia (Khan et al 2015). Diamond shape represents the total PM_2.5-bound PAHs concentrations.

Fig.2 Heat map of PAH compounds in PM_2.5 with meteorology, pollutants, correlation coefficient calculated from daily PAH concentrations. Each correlation coefficient was calculated using 120 sample pairs. Temp: average daily ambient temperature, Pressure: average daily ambient pressure, MMD: maximum mixed layer height of the day, PM_2.5: average daily concentration of PM_2.5, PM₁₀: average daily concentration of PM₁₀.

Fig.3 Relationships between Groups of PAHs in PM_2.5 and ambient temperature at each group, fitting data with standard deviation. Group A: AC, AN, FA, BaA, CHR, BbFA, BkFA, BaP, DBahA, BghiP, IP. Group B: PHE, PY. Group C: NA, FL, ACL.

Fig.4 Daily concentration of PM_2.5-bound PAHs with standard deviation and monthly mass ratio of groups. Daily ambient pressure and temperature during sample period.

Tab.3 PCA seasonal analysis of PM_2.5-bound BaP_eq

Fig.5 120-h backward trajectory cluster analysis from January to April. Overlay of the PM_2.5 grid emission inventory on the Indochina Peninsula by spatial resolution (0.05º × 0.05º).

Fig.6 Temporal variation in the concentration and composition of PM_2.5-bound BaP_eq.

Fig.7 Toxic equivalent concentrations of PM_2.5-bound BaP_eq, calculated from the daily concentrations of compounds for stations and seasons.

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