the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Source differences in the components and cytotoxicity of PM2.5 from automobile exhaust, coal combustion, and biomass burning contributing to urban aerosol toxicity
Weijie Huang
Guofeng Shen
Yuting Pang
Mingwei Tang
Weijun Li
Zhen Zhao
Hanhan Li
Yaqian Wei
Longjiao Xie
Tariq Mehmood
Abstract. The combustions of fuels, including oil, coal, and biomass, are main anthropogenic sources of atmospheric fine particulate matters (PM2.5), however, their discrepant contributions to health toxicity risks of mixed ambient aerosol pollution dominated by respective emission intensity and chemical compositions are still unclear. In order to explore the quantitative differences of these combustion emissions, ten typical types of each source PM2.5, i.e., vehicle exhaust, coal combustion, and biomass burning, were collected by laboratory simulated combustion and dilution channel sampler. Totally thirty type combustion samples were compared with monthly urban air PM2.5 samples, which chemical characteristics and biological effects were investigated by component analysis and in vitro toxicity assays of human lung epithelial cells (A549). Heavy metals are more plentiful in PM2.5 from coal combustion and automobile exhaust, while carbonaceous fraction was plenteous in biomass burning. The overall cytotoxicity of PM2.5 was automobile exhaust > coal combustion > biomass burning, with different toxicity pathways and triggers. The toxicity of PM2.5 from gasoline/diesel and biomass combustion was relevant to the combination of carbonaceous and water-soluble components, but the toxicogenic capacity of coal combustion PM2.5 was mainly related to the high content of heavy metals. All these three emission categories of anthropogenic combustion sources were more toxic than ambient PM2.5 and should be the main independent contributors to the cytotoxicity of mixed urban air PM2.5. Associated with the source apportionment results of positive matrix factorization (PMF) model that automobile exhaust, coal and biomass combustion contributed 27.7 %, 25.2 % and 13.1 % of ambient air PM2.5, respectively, the toxicological results suggest automobile exhaust and coal combustion are priority emissions with higher toxic pollutants to be reduced preferentially for precise urban PM2.5 pollution control ensuring public health safety.
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Xiao-San Luo et al.
Status: open (until 06 Jun 2023)
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RC1: 'Comment on egusphere-2023-598', Anonymous Referee #1, 16 May 2023
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This manuscript has investigated the contribution of three common combustion pollutants to the ambient urban PM2.5 health effects. The results are interesting, which showed that particles from different combustion processes at the same concentration exert different toxic effects on the A549 cells. The English language needs to be polished to further improve the quality of this work. Other comments are as follows:
- lines 24-26: is there any difference between the two words “toxicity” and “toxicogenic” when the authors here used them for different types of samples? Generally, toxicogenic indicated the toxin production activity of bacteria or other organisms.
line 102: was the Teflon filter also baked in the muffle furnace at 500 oC?
- although the air sample information was referred to a literature, it would be better some brief information could be provided here. For example, how about the duration of the air sample?
- line 136: how about the PM2.5 concentrations for the cell stimulation experiments? If 80 mg/L, was the cellular supernatant removed before the addition of PM2.5 elution?
- cell viability test: has the authors treated the cells with other lower or higher concentrations in addition to the one concentration here (80 mg/L)?
- correlations between PM2.5 components and toxicity: has the authors measured other biological components., e.g., LPS, which is a very strong inflammation inducer and is a common component in the air?
- figure 1: it is not clear the percentage of species in what?
- figure 5: were there any statistically significant difference for each component in different types of samples?
- figure 6: similar to the last question, statistical test?
Citation: https://doi.org/10.5194/egusphere-2023-598-RC1
Xiao-San Luo et al.
Xiao-San Luo et al.
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