Oxidative potential of ambient PM2.5 in the coastal cities of the Bohai Sea, northern China: Seasonal variation and source apportionment

Liu, Weijian; Xu, Yi; Liu, QingYang; Yu, ShuangYu; Liu, Yang; Wang, Xin; Tao, Shu

doi:10.1016/j.envpol.2018.01.116

Cited by 134 publications

(73 citation statements)

References 104 publications

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“…In MLR results, crustal source contributes significantly to DTT V , confirming the correlation observed for DTT V and Ca 2+ . Contrarily, PMF "with DTT V " showed limited crustal contributions to DTT V , in agreement with the results of a MLR study reported in literature [46] and with a previous study which highlighted as the crustal matter is characterized by a lower specific OP [30]. Another difference between PMF "with DTT V " and MLR results is for marine contribution that is negligible for the former, contrarily to MLR that showed a certain contribution to the DTT V activity.…”

Section: Mlr Analsysissupporting

confidence: 90%

“…There are some differences among the results of the two approaches, mainly in combustion sources (i.e., biomass burning, industrial, and traffic emissions); however, these differences are comparable to the differences in average source contributions to DTT activity estimated using different receptor models [34,36]. Despite these differences, both approaches give a similar trend with large contributions to DTTV due to biomass burning as found in other research works [8,34,36,43,46]. The other combustion sources, that are Figure 6 compares the contributions, in absolute and relative terms, of the different sources to DTT V obtained with PMF "with DTT V " and MLR approaches.…”

Section: Mlr Analsysissupporting

confidence: 70%

“…This finding is in agreement with other works [8,34], where ammonium sulphate source gave an insignificant contribution to DTT V . For this reason and according with what has been done in other works [34,43,46], the MLR analysis has been performed again excluding this factor and maintaining only statistically significant sources. In Figure 5 the measured and reconstructed daily DTT V values obtained with the two approaches (directly by PMF results and using MLR analysis) are compared.…”

Section: Mlr Analsysismentioning

confidence: 99%

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Source Apportionment of PM2.5 and of its Oxidative Potential in an Industrial Suburban Site in South Italy

et al. 2019

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Some studies suggested a role of the atmospheric particulate matter (PM) and of its oxidative potential (OP) in determining adverse health effects. Several works have focused on characterisation of source contributions to PM OP, mainly using three approaches: correlation between OP and chemical markers of specific sources; use of OP as input variable in source apportionment with receptor models; and multi-linear regression (MLR) between OP and source contributions to PM obtained from receptor models. Up to now, comparison of results obtained with different approaches on the same dataset is scarce. This work aims to perform a OP study of PM2.5 collected in an industrial site, located near a biogas production and combustion plant (in southern Italy), comparing different approaches to investigate the contributions of the different sources to OP. The PM2.5 samples were analysed for determining ions, metals, carbonaceous components, and OP activity with the DTT (dithiotreitol) assay. Results showed that OP normalised in volume (DTTV) is correlated with carbonaceous components and some ions (NO3−, and Ca2+) indicating that PM of combustion, secondary, and crustal origin could contribute to the OP activity. The source apportionment, done with the Environmental Protection Agency (EPA)—Positive Matrix Factorization (PMF5.0) model, identified six sources: secondary sulphate; biomass burning; industrial emissions; crustal; vehicle traffic and secondary nitrate; and sea spray. A MLR analysis between the source’s daily contributions and the daily DTTV values showed a reasonable agreement of the two approaches (PMF and MLR), identifying the biomass burning and the vehicle traffic and secondary nitrate as the main sources contributing to DTTV activity.

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Section: Mlr Analsysissupporting

confidence: 90%

Section: Mlr Analsysissupporting

confidence: 70%

Section: Mlr Analsysismentioning

confidence: 99%

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Source Apportionment of PM2.5 and of its Oxidative Potential in an Industrial Suburban Site in South Italy

et al. 2019

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“…In addition, offline measurements by DCFH predominantly depend on ozone concentrations, temperature, solar radiation, sulfate, nitrate and certain transition metals [23,44]. Finally, several studies also found a good correlation with OC for both assays [37,44,51,52].…”

Section: Op Dtt and Op Dcfh Measurements And Their Correlation With Pmentioning

confidence: 88%

Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays

Jovanović

Savić

Salimi

et al. 2019

IJERPH

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To estimate the oxidative potential (OP) of particulate matter (PM), two commonly used cell-free, molecular probes were applied: dithiothreitol (DTT) and dichloro-dihydro-fluorescein diacetate (DCFH-DA), and their performance was compared with 9,10-bis (phenylethynyl) anthracene-nitroxide (BPEAnit). To the best of our knowledge, this is the first study in which the performance of the DTT and DCFH has been compared with the BPEAnit probe. The average concentrations of PM, organic carbon (OC) and elemental carbon (EC) for fine (PM2.5) and coarse (PM10) particles were determined. The results were 44.8 ± 13.7, 9.8 ± 5.1 and 9.3 ± 4.8 µg·m−3 for PM2.5 and 75.5 ± 25.1, 16.3 ± 8.7 and 11.8 ± 5.3 µg·m−3 for PM10, respectively, for PM, OC and EC. The water-soluble organic carbon (WSOC) fraction accounted for 42 ± 14% and 28 ± 9% of organic carbon in PM2.5 and PM10, respectively. The average volume normalized OP values for the three assays depended on both the sampling periods and the PM fractions. The OPBPEAnit had its peak at 2 p.m.; in the afternoon, it was three times higher compared to the morning and late afternoon values. The DCFH and BPEAnit results were correlated (r = 0.64), while there was no good agreement between the BPEAnit and the DTT (r = 0.14). The total organic content of PM does not necessarily represent oxidative capacity and it shows varying correlation with the OP. With respect to the two PM fractions studied, the OP was mostly associated with smaller particles.

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“…Fine inhalable particulate matter with an aerodynamic diameter <2.5 μm (PM 2.5 ) is characterized by small particle size, large surface area, and strong absorption of air pollutants (Wang et al 2015; Liu et al 2018). The economy has developed very rapidly, making air pollution a serious environmental health problem in China.…”

Section: Introductionmentioning

confidence: 99%

Metal Element Detection and Carcinogenicity Risk Assessment of PM_2.5 Samples

Qin

Wang

et al. 2020

Enviro Toxic and Chemistry

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The objective of the present study was to conduct metal element analysis and carcinogenicity risk assessment of particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) from Shenzhen and Taiyuan. Samples of PM2.5 were collected in Shenzhen and Taiyuan during the yeas 2017 and 2018. Ten heavy metal elements were detected by inductively coupled plasma mass spectrometry. Health risk was assessed using the recommended US Environmental Protection Agency model. Metal elements found in PM2.5 samples from Shenzhen included (in decreasing order of concentration) Al, Pb, Mn, Cr, Cu, V, As, Ni, Cd, and Co. Metal elements found in Taiyuan included (in decreasing order of concentration) Al, Mn, Pb, Cr, Cu, As, Ni, V, Cd, and Co. There were significant differences in Pb, Mn, Al, As, and Ni levels between Shenzhen and Taiyuan (p < 0.05); but the remaining element levels did not show significant differences between the 2 cities. Risk‐assessment data showed higher total risk from 5 carcinogenic metal elements in Taiyuan (3.79 × 10−4) compared to Shenzhen (2.44 × 10−4): Cr had the highest carcinogenicity risk (>10−4), followed by As, Ni, and Cd (10−6 ~ 10−4), and Pb had the lowest risk (<10−6). The results indicated that some of the metal elements in PM2.5 samples from Shenzhen and Taiyuan pose a carcinogenicity risk; further research and measures for prevention and control should be considered. Environ Toxicol Chem 2020;39:1273–1276. © 2020 SETAC

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Oxidative potential of ambient PM2.5 in the coastal cities of the Bohai Sea, northern China: Seasonal variation and source apportionment

Cited by 134 publications

References 104 publications

Source Apportionment of PM2.5 and of its Oxidative Potential in an Industrial Suburban Site in South Italy

Source Apportionment of PM2.5 and of its Oxidative Potential in an Industrial Suburban Site in South Italy

Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays

Metal Element Detection and Carcinogenicity Risk Assessment of PM_2.5 Samples

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Oxidative potential of ambient PM2.5 in the coastal cities of the Bohai Sea, northern China: Seasonal variation and source apportionment

Cited by 134 publications

References 104 publications

Source Apportionment of PM2.5 and of its Oxidative Potential in an Industrial Suburban Site in South Italy

Source Apportionment of PM2.5 and of its Oxidative Potential in an Industrial Suburban Site in South Italy

Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays

Metal Element Detection and Carcinogenicity Risk Assessment of PM2.5 Samples

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Metal Element Detection and Carcinogenicity Risk Assessment of PM_2.5 Samples