the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact of urbanization on fine particulate matter concentrations over central Europe
Abstract. The rural-to-urban transformation (RUT) is the process of turning rural or natural land-surface into urban one which brings important modifications in the surface causing well know effects like the urban heat island (UHI), reduced wind-speeds, increased boundary layer heights and so on. Moreover, with concentrated human activities RUT introduces new emission source which greatly perturbs the local and regional air-pollution. Particulate matter (PM) is one of key pollutants responsible for deterioration of urban air-quality and is still a major issue in European cities with frequent exceedances of limit values. Here we introduce a regional chemistry-climate model (regional climate model RegCM coupled offline to chemistry transport model CAMx) study which quantifies how the process of RUT modified the PM concentrations over central Europe including the underlying controlling mechanisms that contribute to the final PM pollution. Apart from the two most studied ones, i) the urban emissions and ii) the urban canopy meteorological forcing (UCMF, i.e. the impact of modified meteorological conditions on air-quality) we analyze also two less studied contributors to the RUT’s impact on air-quality: iii) the impact of modified dry-deposition velocities due to urbanized land-use and iv) the impact of modified biogenic emissions due to urbanization induced vegetation modifications and changes in meteorological conditions which affect these emissions. To calculate the magnitude of each of these RUT contributors, we perform a cascade of simulations were each contributor is added one-by-one to the reference state while focus is given on PM2.5 (particulate matter with diameter less then 2.5 µm). We also look at their primary and secondary components, namely primary elemental carbon (PEC), sulphates (PSO4), nitrates (PNO3), ammonium (PNH4) and secondary organic aerosol (SOA).
The validation using surface measurements showed a systematic negative bias for the total PM2.5 which is probably caused by underestimated organic aerosol and partly by the negative bias in sulphates and elemental carbon. For ammonium and nitrate, the underestimation is limited to the warm season while for winter, the model tends to overestimate their concentrations. However, in each case, the annual cycle is reasonably captured.
We evaluated the RUT impact on PM2.5 over an ensemble of 19 central European cities and found that the total impact of urbanization is about 2–3 and 1–1.5 µgm−3 in winter and summer, respectively. This is mainly driven by the impact of emissions alone causing a slightly higher impact (1.5–3.5 and 1.2–2 µgm−3 in winter and summer), while the effect of UCMF was a decrease at about 0.2–0.5 µgm−3 (in both seasons) which was mainly controlled by enhanced vertical eddy-diffusion while increases were modelled over rural areas. The transformation of rural land-use into urban one caused an increase of dry-deposition velocities by around 30–50 % which alone resulted in a decrease of PM2.5 by 0.1–0.25 µgm−3 in both seasons. Finally, the impact of biogenic emission modification due to modified land-use and meteorological conditions caused a decrease of summer PM2.5 of about 0.1 µgm−3 while the winter effects were negligible. The total impact of urbanization on aerosol components is modelled to be (values indicate winter and summer averages) 0.4 and 0.3 µgm−3 for PEC, 0.05 and 0.02 µgm−3 for PSO4, 0.1 and 0.08 µgm−3 for PNO3, 0.04 and 0.03 µgm−3 for PNH4 and 0 and 0.05 µgm−3 for SOA. The main contributor of each of these components was the impact of emissions which was usually larger than the total impact due to the fact that UCMF counteracted with a decrease. For each aerosol component the impact of modified DV was a clear decrease of concentration and finally, the modifications of biogenic emissions impacted predominantly SOA causing a summer decrease while a very small secondary effect of secondary inorganic aerosol was modelled too (they increased).
In summary, we showed that when analyzing the impact of urbanization on PM pollution, apart from the impact of emissions and the urban canopy meteorological forcing, one has to consider also the effect of modified land-use and its impact on dry-deposition. These were shown to be important in both seasons. For the effect of modified biogenic emissions, our calculations showed that it acts on PM2.5 predominantly trough SOA modifications which turned to be important only during summer.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-1037', Anonymous Referee #2, 09 Oct 2023
Summary: In the manuscript titled “Impact of urbanization on fine particulate matter concentrations over central Europe”, the authors examine urban contribution to particulate matter and its constituents over central Europe using a modeling approach. The study is overall written well and mostly well designed. I do have several questions about the modeling approach and uncertainties and how they might impact the results.
Major comments:
1. In general, I found the modeling approach difficult to follow. There seem to be multiple models driving each other and other models being used to derive or modify the emission inventories (for instance, MEGAN for BVOC emissions). It would really help to have a schematic of the overall modeling setup and how each component feeds into each other regarding input and output.
2. As far as I can tell, the RegCM model uses the urban representation of CLM4.5, which is a single layer canopy model with no urban vegetation and no anthropogenic heat flux from vehicles. How does this affect the BVOC estimates. Does the MEGAN algorithm actually resolved urban vegetation and biogenic emissions from them (or deposition on them?). Additionally, where did the leaf area index and plant functional type data for urban areas come from? Urban areas can have very different vegetation characteristics from their surrounding rural areas (Paschalis et al. 2021).
3. I have other questions about the emission inventory. How are vehicular emissions considered in these estimates? What about impacts from asphalt-related emissions (Khare et al. 2020)?
4. Finally, as I understand it, these are offline simulations. Does that mean that there is no feedback from the land to the atmosphere? In the real world, urban heat and moisture islands (Chakraborty et al. 2022) may impact near-surface chemistry and convection; and thus overall pollutant concentrations within and sourced from urban areas. There needs to be a broader discussion about these uncertainties.
Minor comments:
1. Figs 1 and 2: Please add the y axis labels with the units.
2. Page 1: ‘We evaluated the RUT impact on PM2.5 over an ensemble of 19 central European cities’: That is not the typical usage of ensemble. 19 is just the sample size here?References:
1. Paschalis, A., Chakraborty, T. C., Fatichi, S., Meili, N., & Manoli, G. (2021). Urban forests as main regulator of the evaporative cooling effect in cities. AGU Advances, 2(2), e2020AV000303.
2. Khare, P., Machesky, J., Soto, R., He, M., Presto, A. A., & Gentner, D. R. (2020). Asphalt-related emissions are a major missing nontraditional source of secondary organic aerosol precursors. Science advances, 6(36), eabb9785.
3. Chakraborty, T., Venter, Z. S., Qian, Y., & Lee, X. (2022). Lower urban humidity moderates outdoor heat stress. Agu Advances, 3(5), e2022AV000729.Citation: https://doi.org/10.5194/egusphere-2023-1037-RC1 -
RC2: 'Comment on egusphere-2023-1037', Anonymous Referee #1, 10 Oct 2023
This manuscript discusses the effect of urbanization on PM 2.5 levels in central Europe. Four factors were considered, i.e., the urban emissions, the urban canopy meteorological forcing, the impact of modified dry deposition velocities and the impact of modified biogenic emissions. A cascade of simulations with RegCM and CAMx were performed to separate the effect of these factors. The authors found that urban emission contributes the most to increasing the PM 2.5 concentration, while urban canopy has a counter effect due to stronger vertical eddy-diffusions. The transformation of land-use also tends to decrease PM 2.5 levels by increasing the particle dry deposition velocity. Overall, the conclusions drawn from the simulations seem sound, but I believe the presentation of the results can be improved and the manuscript can become more concise by revision.
Major comments:
- Regarding the design of the simulation cascade, more explanation of the simulation sequence of is needed. If the simulations follow a different sequence, will the results change significantly?
- The authors have somewhat strictly separated results from discussions. I find this way of writing very difficult to follow. One the one hand, in the results section some paragraphs are only recounting figure contents and barely provide any explanations (e.g., sections 3.3.1-3.3.4). This makes the reading process really dry (actually, a table with numbers may actually outperform the texts in 3.3.1-3.3.4). One other hand, when I arrive at the discussion part (far away from the results), I have a hard time correlating the discussions to the corresponding results; as a result, I have difficulty in assessing the validity of some statements in the discussion section. Therefore, I recommend restructuring of the paper to some extent by combining some of the discussions with the results.
Minor comments:
- Line 175: Eqn (3) assumes that the processes are additive. This sentence seems to suggest the opposite causal relation.
- Figure 5: Please state clearly whether figure 5 shows the measured or simulated concentrations.
Technical:
There are quite a number of tiny mistakes in the manuscript. The authors need to carefully go through the manuscript for a more complete check.
For the majority of the figures: Please use larger font size for the axis tick labels. Figures 1, 2, 11, 12 also need proper labels for the axes. In Figures 11 and 12, the phrase ‘Diurnal cycle of urbanization impact’ does not need to appear above every panel.
Line 32: the abbreviation of DV has not been defined previously.
Line 65: messed up citation of Yang et al.
Line 83: this sentence needs to be revised.
Line 163: This sentence is very confusing.
Line 237: although -> despite
Line 282: the impacts of urbanization on POA.
Line 285: … and their components to observations.
Line 291: and the underestimation is stronger in winter.
Line 310: missing units
ug/m3 are sometimes italic and sometimes normal.
Line 541: we further discuss…
Line 559: know -> known
Line 561: responded -> respond
Line 623: the citation of Ortega et al. is in the wrong format
......
Citation: https://doi.org/10.5194/egusphere-2023-1037-RC2 -
AC1: 'Final authors comment on egusphere-2023-1037 to all RCs', Peter Huszar, 17 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1037/egusphere-2023-1037-AC1-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1037', Anonymous Referee #2, 09 Oct 2023
Summary: In the manuscript titled “Impact of urbanization on fine particulate matter concentrations over central Europe”, the authors examine urban contribution to particulate matter and its constituents over central Europe using a modeling approach. The study is overall written well and mostly well designed. I do have several questions about the modeling approach and uncertainties and how they might impact the results.
Major comments:
1. In general, I found the modeling approach difficult to follow. There seem to be multiple models driving each other and other models being used to derive or modify the emission inventories (for instance, MEGAN for BVOC emissions). It would really help to have a schematic of the overall modeling setup and how each component feeds into each other regarding input and output.
2. As far as I can tell, the RegCM model uses the urban representation of CLM4.5, which is a single layer canopy model with no urban vegetation and no anthropogenic heat flux from vehicles. How does this affect the BVOC estimates. Does the MEGAN algorithm actually resolved urban vegetation and biogenic emissions from them (or deposition on them?). Additionally, where did the leaf area index and plant functional type data for urban areas come from? Urban areas can have very different vegetation characteristics from their surrounding rural areas (Paschalis et al. 2021).
3. I have other questions about the emission inventory. How are vehicular emissions considered in these estimates? What about impacts from asphalt-related emissions (Khare et al. 2020)?
4. Finally, as I understand it, these are offline simulations. Does that mean that there is no feedback from the land to the atmosphere? In the real world, urban heat and moisture islands (Chakraborty et al. 2022) may impact near-surface chemistry and convection; and thus overall pollutant concentrations within and sourced from urban areas. There needs to be a broader discussion about these uncertainties.
Minor comments:
1. Figs 1 and 2: Please add the y axis labels with the units.
2. Page 1: ‘We evaluated the RUT impact on PM2.5 over an ensemble of 19 central European cities’: That is not the typical usage of ensemble. 19 is just the sample size here?References:
1. Paschalis, A., Chakraborty, T. C., Fatichi, S., Meili, N., & Manoli, G. (2021). Urban forests as main regulator of the evaporative cooling effect in cities. AGU Advances, 2(2), e2020AV000303.
2. Khare, P., Machesky, J., Soto, R., He, M., Presto, A. A., & Gentner, D. R. (2020). Asphalt-related emissions are a major missing nontraditional source of secondary organic aerosol precursors. Science advances, 6(36), eabb9785.
3. Chakraborty, T., Venter, Z. S., Qian, Y., & Lee, X. (2022). Lower urban humidity moderates outdoor heat stress. Agu Advances, 3(5), e2022AV000729.Citation: https://doi.org/10.5194/egusphere-2023-1037-RC1 -
RC2: 'Comment on egusphere-2023-1037', Anonymous Referee #1, 10 Oct 2023
This manuscript discusses the effect of urbanization on PM 2.5 levels in central Europe. Four factors were considered, i.e., the urban emissions, the urban canopy meteorological forcing, the impact of modified dry deposition velocities and the impact of modified biogenic emissions. A cascade of simulations with RegCM and CAMx were performed to separate the effect of these factors. The authors found that urban emission contributes the most to increasing the PM 2.5 concentration, while urban canopy has a counter effect due to stronger vertical eddy-diffusions. The transformation of land-use also tends to decrease PM 2.5 levels by increasing the particle dry deposition velocity. Overall, the conclusions drawn from the simulations seem sound, but I believe the presentation of the results can be improved and the manuscript can become more concise by revision.
Major comments:
- Regarding the design of the simulation cascade, more explanation of the simulation sequence of is needed. If the simulations follow a different sequence, will the results change significantly?
- The authors have somewhat strictly separated results from discussions. I find this way of writing very difficult to follow. One the one hand, in the results section some paragraphs are only recounting figure contents and barely provide any explanations (e.g., sections 3.3.1-3.3.4). This makes the reading process really dry (actually, a table with numbers may actually outperform the texts in 3.3.1-3.3.4). One other hand, when I arrive at the discussion part (far away from the results), I have a hard time correlating the discussions to the corresponding results; as a result, I have difficulty in assessing the validity of some statements in the discussion section. Therefore, I recommend restructuring of the paper to some extent by combining some of the discussions with the results.
Minor comments:
- Line 175: Eqn (3) assumes that the processes are additive. This sentence seems to suggest the opposite causal relation.
- Figure 5: Please state clearly whether figure 5 shows the measured or simulated concentrations.
Technical:
There are quite a number of tiny mistakes in the manuscript. The authors need to carefully go through the manuscript for a more complete check.
For the majority of the figures: Please use larger font size for the axis tick labels. Figures 1, 2, 11, 12 also need proper labels for the axes. In Figures 11 and 12, the phrase ‘Diurnal cycle of urbanization impact’ does not need to appear above every panel.
Line 32: the abbreviation of DV has not been defined previously.
Line 65: messed up citation of Yang et al.
Line 83: this sentence needs to be revised.
Line 163: This sentence is very confusing.
Line 237: although -> despite
Line 282: the impacts of urbanization on POA.
Line 285: … and their components to observations.
Line 291: and the underestimation is stronger in winter.
Line 310: missing units
ug/m3 are sometimes italic and sometimes normal.
Line 541: we further discuss…
Line 559: know -> known
Line 561: responded -> respond
Line 623: the citation of Ortega et al. is in the wrong format
......
Citation: https://doi.org/10.5194/egusphere-2023-1037-RC2 -
AC1: 'Final authors comment on egusphere-2023-1037 to all RCs', Peter Huszar, 17 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1037/egusphere-2023-1037-AC1-supplement.pdf
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Alvaro Patricio Prieto Perez
Lukáš Bartík
Jan Karlický
Anahi Villalba-Pradas
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(33950 KB) - Metadata XML