Evaluating the Impact of a Wall-Type Green Infrastructure on PM10 and NOx Concentrations in an Urban Street Environment
Abstract
:1. Introduction
2. Methodology
2.1. Green Infrastructure–CityTree Structure
2.2. Experimental Activities
2.3. Micro-SWIFT-SPRAY (PMSS)
2.4. Simulation Set-Up
- 1.
- For the year 2017, we ran PMSS to simulate vertical deposition due to the CT operating in passive mode (only deposition).
- 2.
- For the year 2018 we reproduced the air pollution abatement linked to the deposition vertical velocities when the CT operated in passive mode (as in 2017). In addition, we studied the PM10 concentration abatement produced when the CT filtration mode was activated. Here we used the passive deposition velocity, calculated from measurements analysis, able to produce the same pollutant deposition measured with the CT in filtration mode (see [16]).
2.4.1. Input Meteorological Data
2.4.2. Simulation Domain, Area and Obstacles
2.4.3. Bulk Deposition Velocities for PM10 and NOx
- Bulk Deposition Velocities with the CT in passive mode (filtration switched off)
- Bulk Deposition Velocities for PM10 with the CT in filtration mode
2.4.4. Emissions
2.4.5. Parallel Run Details CRESCO
2.4.6. NOx and PM10 Reduction Operated by the CT
2.5. Reference Air Quality and Meteorological Data
2.6. Tools for the Analyses
3. Results
3.1. NOx Modelled and Measured Data Evaluation
3.2. Green Infrastructure Abatement
3.2.1. CT in Passive Mode-Deposition
3.2.2. Vertical Profiles of Pollution Reduction in Passive Mode
- Reduction profiles for PM10 and NOx have the same characteristics. They have the maximum reduction values in the first few meters above the ground. The reduction decreases significantly at heights above the green infrastructure (above 6 m).
- For both NOx and PM10, the maximum pollutant reduction is obtained very close to the green infrastructure, at point A, with values of about 0.5%. At point D, the maximum pollutant reduction decreases to 0.1–0.2%.
- Air pollutant reduction decreases rapidly, moving away from the green infrastructure, both in the vertical and in the horizontal directions.
3.2.3. CT in Active Mode (Filtration) for PM10 Concentrations in 2018
4. Discussion
- Wind measurements taken at the urban scale (at Modena Urbana) and close to the CT (CNR measurements inside the urban canyon) are significantly “decoupled” as already well documented in the literature (e.g., [72]). It was very difficult to establish a relation between the urban and local wind datasets, likely to be due to the air circulation specific to the street.
- The agreement between modelled and measured data is significantly more evident during the days 25–31 May, characterized by urban south-easterly wind and NOx concentrations between 20–100 μg/m3. During the days 26–31 May, the Taylor diagram shows the best agreement with correlation values of about 0.85 and normalized standard deviations close to one.
5. Conclusions
- The specific urban setting centered in viale Verdi, Modena (obstacles and buildings);
- A prescribed location of the CT consistent with the experimental field CT installation;
- Meteorological data and emission features coherent with the first and the third research campaigns;
- Values of bulk deposition velocities deriving from the experimental campaigns (and in agreement with results obtained in the literature).
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix A.1. Viale Verdi Orientation and Geographical Sectors
- NE (347–77°),
- SW (167–257°);
- NW (257–347°),
- SE (77–167°).
Appendix A.2. NO2 Background Concentration
- The prevailing wind directions were easterly. However, significant contributions were also from north-west and south-west directions.
- Mean NO2 background concentrations were generally close to 20 μg/m3. These values were detected particularly with easterly winds, which were stronger (up to 6 m/s) than in the other directions where intensities were generally lower than 4 m/s (Figure A3).
Appendix A.3. Wind Distributions
Appendix A.4. NOx Concentrations—Model Evaluation
- Dataset exploration:
- Further dataset Analysis:
- Exploration with the FAIRMODE IDL-based DELTA software tool
- NOx Concentration Comparisons considering Wind Directions
- day range within the month of May 2017 (12–16; 16–21; 21–26; and 26–31);
- urban wind direction within four sectors (NE 347–77; NW 257–347; SE 77–167; SW 167–257);
- local wind direction in the same four sectors as defined in Figure A1.
Appendix B
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Parameters | 2017 | 2018 |
---|---|---|
Days Simulated | 12–31 May 2017 | 5–17 April 2018 |
Pollutant Simulated | PM10, NOx | PM10, NOx |
Horizontal Domain | 1 km × 1 km | 1 km × 1 km |
Horizontal Resolution | 2 m | 2 m |
Emissions: Vehicle Input | Flow model for 2017 + vehicle Measurements 2017 in viale Verdi | Flow model for 2017 + vehicle Measurements 2018 in viale Verdi |
Obstacle Position | Viale Verdi 21 | Viale Verdi 21 |
Meteo Input | RAMS [55] 4 km × 4 km, May 2017 | RAMS [55] 4 km × 4 km, April 2018 |
Bulk Velocity Deposition (PM10) CT passive mode: 1st quartile, median, 3rd quartile | vd ->0.0005 m/s, 0.0012 m/s, 0.003 m/s | vd -> 0.0005 m/s, 0.0012 m/s, 0.003 m/s |
Bulk Velocity Deposition (PM10) CT active mode | Not simulated | vd filtration ~ 0.024 m/s |
Bulk Velocity Deposition (NOx) CT passive mode: 1st quartile, median, 3rd quartile | vd -> 0.0004 m/s, 0.0011 m/s, 0.0025 m/s | vd -> 0.0004 m/s, 0.0011 m/s, 0.0025 m/s |
Model Versions | PSWIFT-2.1.1, PSPRAY-3.7.3, Intel16 compiler, OPENMPI library | PSWIFT-2.1.1, PSPRAY-3.7.3, Intel16 compiler, OPENMPI library |
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Villani, M.G.; Russo, F.; Adani, M.; Piersanti, A.; Vitali, L.; Tinarelli, G.; Ciancarella, L.; Zanini, G.; Donateo, A.; Rinaldi, M.; et al. Evaluating the Impact of a Wall-Type Green Infrastructure on PM10 and NOx Concentrations in an Urban Street Environment. Atmosphere 2021, 12, 839. https://doi.org/10.3390/atmos12070839
Villani MG, Russo F, Adani M, Piersanti A, Vitali L, Tinarelli G, Ciancarella L, Zanini G, Donateo A, Rinaldi M, et al. Evaluating the Impact of a Wall-Type Green Infrastructure on PM10 and NOx Concentrations in an Urban Street Environment. Atmosphere. 2021; 12(7):839. https://doi.org/10.3390/atmos12070839
Chicago/Turabian StyleVillani, Maria Gabriella, Felicita Russo, Mario Adani, Antonio Piersanti, Lina Vitali, Gianni Tinarelli, Luisella Ciancarella, Gabriele Zanini, Antonio Donateo, Matteo Rinaldi, and et al. 2021. "Evaluating the Impact of a Wall-Type Green Infrastructure on PM10 and NOx Concentrations in an Urban Street Environment" Atmosphere 12, no. 7: 839. https://doi.org/10.3390/atmos12070839
APA StyleVillani, M. G., Russo, F., Adani, M., Piersanti, A., Vitali, L., Tinarelli, G., Ciancarella, L., Zanini, G., Donateo, A., Rinaldi, M., Carbone, C., Decesari, S., & Sänger, P. (2021). Evaluating the Impact of a Wall-Type Green Infrastructure on PM10 and NOx Concentrations in an Urban Street Environment. Atmosphere, 12(7), 839. https://doi.org/10.3390/atmos12070839