the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Decadal trends (2013–2023) in PM10 sources and oxidative potential at a European urban supersite (Alpine Valley, Grenoble, France)
Abstract. The identification of particulate matter (PM) sources and the quantification of their contribution to the urban environment is a necessary input for policymakers to reduce the air pollution impacts. The association between the PM sources and the oxidative potential (OP) is also a key indicator for evaluating the ability of PM sources to induce in-vivo oxidative stress and lead to adverse health effects, which becomes an emerging metric in the Directive on ambient air quality (22024/2881/EU). Most studies in Europe have focused on PM and OP sources in the short term, for only 1 or 2 years. However, the efficiency of reduction policies, trends, and epidemiological impacts cannot be properly evaluated with such short-term studies due to a lack of statistical robustness. Here, long-term PM10 filter sampling at the Grenoble (France) urban background supersite and detailed chemical analyses were used to investigate decadal trends of the main PM sources and related OP metrics. Positive matrix factorization (PMF) analyses were conducted on the corresponding 11-year dataset (Jan 2013 to May 2023, n = 1570), enlightening the contributions of 10 PM sources: mineral dust, sulfate-rich, primary traffic, biomass burning, primary biogenic, nitrate-rich, MSA-rich, aged sea salt, industrial and chloride-rich. The stability of the chemical profile of these sources was validated by comparison with the profiles retrieved from shorter-term (3 years) successive PMF analyses. A Seasonal-Trend using LOESS decomposition was then applied to evaluate the trends of these PM10 sources, which revealed a substantial decrease in PM10 (-0.73 µg m-3 yr-1) as well as that of many of the PM10 sources. Specifically, negative trends for primary traffic and biomass burning sources are detected, with a reduction of 0.30 and 0.11 µg m-3 yr-1, respectively. The OP PM10 source apportionment in 11 years confirmed the high redox activity of the anthropogenic sources, including biomass burning, industrial, and primary traffic. Eventually, downward trends were also observed for OPAA and OPDTT, mainly driven by the reduction of residential heating and transport emissions, respectively.
- Preprint
(1552 KB) - Metadata XML
-
Supplement
(1939 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2025-2933', Xiao-San Luo, 26 Jul 2025
This manuscript investigated the decadal trends in PM10 sources and oxidative potential (OP) at an urban background supersite in France by 11 years of long-term observations by the method of positive matrix factorization (PMF) analyses, and found the downward trends of OP and the high redox activity of the anthropogenic sources. Such findings are valuable for air quality managements to protect public health. But there are still some defects, and comments are suggested for considering:
Title should be limited as “urban background supersite”.
Introduction
Line 64-67: The limitations of short-term studies should be explained more and in depth.
Methods and Materials
Line 85: What’s the representativeness and environmental implications of the urban background supersite?
Line 108-113: Any rainy days for the sampling? The weather is important factor.
Lines 129-131: Since the analysis method of HPLC-PAD was changed to another one followed CEN standards from 2017, how to ensure the comparability of the measured data from different methods?
Lines 133-134: Two models of ICP-MS (ELAN 6100 DRC II and NEXION) were used, so please tell all the quality control and assurance for data comparable.
Lines 153-154: Details about the external references should be told.
Line 161: Vertical temperature and humidity were measured only during November 2017 to May 2023, so how to use the data for the 11 years of period?
Lines 163-165: Can the meteorological station represent the PM10 sampling site?
Results and Discussion
Line 297: Why are the concentrations of OM and EC are highest in winter?
Lines 317-318: What is the scientific basis for selecting the three time periods of 2013-2016, 2017-2021, 2022-2023? The reasons for the division must be clearly stated.
Lines 356-358: What are the differences in the respective periods of these studies? What are the key differences between the current study and those of Borlaza et al. (2021) and Srivastava et al. (2018)?
Lines 395-398: Because the results of this urban site of current study are compared with the rural sites of EMEP (Colette et al., 2021) and Aas et al. (2024), it is suggested to search the literature of similar urban sites for reasonable comparison. If not, please also discuss the differences between rural and urban sites. Moreover, using the rate of change for comparison would be better for explanation.
Lines 429-420: In conjunction with Section 2.2.3, as mentioned above in the Methods, the meteorological analysis only cover 2017-2023, and there is a time mismatch with the PMF source analysis covering 2013-2023, so can the conclusions drawn based on 2017-2023 about the impact of inversion on PM10 and its sources be applicable to the entire 2013-2023 period?
Lines 523-526: Consistent with problems in lines 395-398, please compare with similar urban sites by percentages.
Besides local sources, any long-range transport considered?
Figure 2: The air quality guideline could be used for comparison. Some statistics should also be conducted for overall trends.
Figure 4: In fact, the seasonal variation is also valuable.
Table 1: Is it linear relationship?
Citation: https://doi.org/10.5194/egusphere-2025-2933-RC1 -
RC2: 'Comment on egusphere-2025-2933', Anonymous Referee #2, 05 Aug 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2933/egusphere-2025-2933-RC2-supplement.pdf
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
305 | 34 | 13 | 352 | 27 | 10 | 9 |
- HTML: 305
- PDF: 34
- XML: 13
- Total: 352
- Supplement: 27
- BibTeX: 10
- EndNote: 9
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1