the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jul 2025
Persistent high PM pollution in the Eastern Mediterranean and Middle East: Insights from long-term observations and source apportionment in Cyprus
Abstract. Long-term daily PM2.5 and PM10 chemical speciation data was collected continuously from 2015 to 2023 at an urban traffic and regional background site in Cyprus, offering a unique opportunity to quantify the influence and trends of i) local emissions on urban PM concentration levels and sources, and ii) regional PM emissions over the Eastern Mediterranean basin. Despite a statistically significant drop in PM2.5 and PM10 at both sites over the last 19 years (2005–2023), concentration levels remain high with no further significant improvements observed over the last 9 years; making PM concentration levels well above the new EU annual limits. To refine this analysis, long-term trends (2015–2023) were explored for individual PM chemical species and sources derived by PMF source apportionment. A decreasing trend in traffic-related PM10 of 35 % was observed at the traffic site, suggesting the effectiveness of the gradual shift of the vehicle fleet towards the latest EURO-standard vehicles. On the other hand, this reduction in tailpipe traffic emissions was completely offset by an increase of uncontrolled urban emissions, such as road dust re-suspension and biomass burning from domestic heating, calling for the rapid implementation of abatement measures.
Based on cluster analysis of air mass origins, the Middle East region was identified as a major hotspot of PM10 over the Eastern Mediterranean; with both high concentration levels of dust from the Arabian desert and substantial anthropogenic pollution with continuously increasing trends in biomass burning and sulfate-rich emissions from fossil fuel combustion over the past decade.
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RC1: 'Comment on egusphere-2025-3234', Anonymous Referee #1, 05 Aug 2025
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General Comments
This paper focuses on long-term daily measurements of chemical speciation data at 2 coarser size cuts at both an urban site with traffic and a more regional background site in Cyprus in order to distinguish between local and regional emissions and sources. A key finding is a statistically significant drop in particulate matter concentrations which still exceed EU regulations. This paper also focuses on long term trends of individual sources using PMF and found a decrease in traffic-related emissions due to a shift towards EURO-standard vehicles that was largely negated by increases in road dust and biomass burning. They conclude that this region remains a pollutant hotspot due to contributions of desert dust and anthropogenic pollution as well as increases in biomass burning.
The introduction focuses on the effects of PM on human health, glances over climate, and establishes the importance of researching it for public policy. They identify gaps in the literature by describing how scarce long-term data is in these regions and how focus has typically instead been on Greece. For example, the authors describe how the most comprehensive long-term PM trend study in Cyprus lacks chemical data to distinguish factors driving downward trends in local urban and regional PM. The annual trends observed are consistent with the literature and the PMF factors resolved at both sites are well supported by tracer analysis and volume of data. The meat of this study is in the trends of identified PMF sources. Overall, I believe that this body of work is good quality, comprehensive, and novel.
Specific Comments:
The agreement in section 2.2 is very high between the gravimetric PM mass determination and TEOM-FDMS and does not raise concern, but can you please be more specific on the number of samples substituted this way?
In section 2.3, is it known what causes the differences in site-specific conversion factors?
This paper would benefit from a map used to describe the geographic origin of the different source regions as well as a pie chart of their percent frequency. This paper would also benefit from a short discussion of the differences in de-seasonalized monthly means and monthly means in section 3.1. I understand it is explained in a previous paper, but it seems odd then to present both results in this paper. This paper’s flow would benefit with a short description on what drives the decrease in regional dust emissions at AMX earlier in section 3.1.
It would be important to describe the methodology for how the optimal number of PMF factors was chosen for both sites. Has separate work been done on temporal correlation of the factors to tracers and of factor concentration to each other? There is often debate about if PMF is distinguishing individual sources or the same source at multiple stages of aging. As an example, an anti-correlation of fresh to aged sea salt could help distinguish these. What method do you use to describe “significant” differences in chemical composition of your factors, specifically in line 285? Given that PMF factor profiles are fixed I wasn’t sure how this was determined.
It confuses me that there is both a decrease in traffic emissions and decrease in heavy oil combustion, but an increase in regional fossil fuel combustion. How well or poorly temporally correlated are the factors to each other? PMF does not provide perfect separation so I worry this conclusion may be driven by regional fossil fuel combustion correlating with dust as it would seem difficult to me to temporally separate local road dust emissions and vehicle emissions. My other concern is that PMF uses a fixed source profile and if there are changes in European car emissions, could other factors be increasing in contribution to compensate? How does the traffic emission factor change in say the first half and second half of the research campaign?
Technical Corrections:
This paper overall reads smoothly with minimal typos. I’ve added some comments suggesting ways sentences can be restructured to improve readability and clarity.
Line 85
“Following rigorously” to “rigorously following”
Line 87
“Then, they were” to “They were then”
Line 147
“Allows building” to “builds”
Line 147
Remove “herewith”
Line 162
“details “ to “detail”
Line 340
“offsetting completely” to “completely offsetting”
Line 417
“minimal variations (statistically insignificant)” to “minimal and statistically significant variations”
Line 424
“As illustrated in Figure 5b, besides having the highest sulfate levels, the West Turkey sector also shows an increasing trend” to “As illustrated in Figure 5b, the West Turkey sector has the highest sulfate levels and also shows an increasing trend”
Line 429
“Surprising” to “Surprisingly”
Line 440
“Such approach” to “This approach”
Line 447
“being common” to “were common”
Line 448
“at AMX” to “only at AMX”
Line 461
“(nearly double that of North Africa) to “that is nearly double that of North Africa)”
Line 466
“uncontrolled emissions from local sources (road dust resuspension and biomass burning),” to “uncontrolled emissions, road dust resuspension and biomass burning, from local sources,"
Citation: https://doi.org/10.5194/egusphere-2025-3234-RC1 -
RC2: 'Comment on egusphere-2025-3234', Anonymous Referee #2, 15 Sep 2025
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General comment
The paper reports a long-term study of PM concentration and composition at two sites of eastern mediterranean area. The trends of the contributions of the different sources are investigated by means of source apportionment. The topic is interesting and suitable for the Journal. The paper is clear and generally well written. I just have some minor suggestions detailed in my specific comments.
Specific comments
Lines 30-35. I would suggest to mention the recent works on trends of composition and sources in a southern Italy background site that could be representative of a central or centra-east mediterranean area such as Merico et al (Atmospheric Pollution Research, 102668, 2025) and Giannossa et al (Journal of Environmental Management 319, 115752, 2022).
Section 2.4. All years have been used as a single input dataset?
Lines 191-194. Here it seems that there is a decreasing trend on dust coming out from chemical mass closure; however, source apportionment results indicate an increasing trend of this source. Could this aspect be discussed in more detail?
Lines 303-308. Regional fossil fuel combustion. I would suggest naming this component just as combustion sources because it is likely a mixed source including both traffic and biomass burning. This will justify the large OC/EC ratio and the aspect that biomass burning is surprisingly identified at traffic site but not a background. This kind of mixing could be due to the lack of a specific tracer for biomass burning such as levoglucosan and has been observed also in other sites.
The profile named LRT is usually called sulphate or secondary sulphate in PMF-based source apportionment. I would suggest to consider this flag.
Citation: https://doi.org/10.5194/egusphere-2025-3234-RC2 -
RC3: 'Comment on egusphere-2025-3234', Anonymous Referee #3, 15 Sep 2025
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3234/egusphere-2025-3234-RC3-supplement.pdf
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