Articles | Volume 22, issue 14
https://doi.org/10.5194/acp-22-9369-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-9369-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jul 2022
Research article |
| 20 Jul 2022
| 20 Jul 2022
Parameterizing the aerodynamic effect of trees in street canyons for the street network model MUNICH using the CFD model Code_Saturne
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, 78850 Thiverval-Grignon, France
Cédric Flageul
PPRIME Institute, Curiosity Group, Université de Poitiers, CNRS, ISAE-ENSMA, Poitiers, France
Bertrand Carissimo
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Yunyi Wang
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Andrée Tuzet
Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, 78850 Thiverval-Grignon, France
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
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The multiscale Street-in-Grid model is used to simulate black carbon (BC) concentrations in streets. To respect street-surface mass balance, particle resuspension is estimated with a new approach based on deposited mass. The contribution of resuspension is low, but non-exhaust emissions from tyre wear may largely contribute to BC concentrations. The impact of the two-way dynamic coupling between scales on BC concentrations varies depending on the street geometry and traffic emission intensity.
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Indoor air quality (IAQ) is strongly influenced by reactivity with surfaces, which is called heterogeneous reactivity. To date, this reactivity is barely integrated into numerical models due to the strong uncertainties it is subjected to. In this work, an open-source IAQ model, called the H2I model, is developed to consider both gas-phase and heterogeneous reactivity and simulate indoor concentrations of inorganic compounds.
Cited articles
Akimoto, H.: Global Air Quality and Pollution, Science, 302, 1716–1719,
https://doi.org/10.1126/science.1092666, 2003. a
Angel, S., Parent, J., Civco, D. L., Blei, A., and Potere, D.: The dimensions
of global urban expansion: Estimates and projections for all countries,
2000–2050, Prog. Plann., 75, 53–107,
https://doi.org/10.1016/j.progress.2011.04.001, 2011. a
Archambeau, F., Méchitoua, N., and Sakiz, M.: Code Saturne: A finite
volume code for the computation of turbulent incompressible flows-Industrial
applications, International Journal on Finite Volumes, 1, 1–62, https://hal.archives-ouvertes.fr/hal-01115371 (last access: 18 July 2022), 2004. a
Armson, D., Stringer, P., and Ennos, A.: The effect of street trees and
amenity grass on urban surface water runoff in Manchester, UK, Urban For.
Urban Gree., 12, 282–286, https://doi.org/10.1016/j.ufug.2013.04.001, 2013. a
Beckett, K., Freer-Smith, P., and Taylor, G.: Urban woodlands: their role in
reducing the effects of particulate pollution, Environ. Pollut., 99,
347–360, https://doi.org/10.1016/S0269-7491(98)00016-5, 1998. a
Berland, A., Shiflett, S. A., Shuster, W. D., Garmestani, A. S., Goddard,
H. C., Herrmann, D. L., and Hopton, M. E.: The role of trees in urban
stormwater management, Landscape Urban Plan., 162, 167–177,
https://doi.org/10.1016/j.landurbplan.2017.02.017, 2017. a
Bertram, C. and Rehdanz, K.: The role of urban green space for human
well-being, Ecol. Econ., 120, 139–152,
https://doi.org/10.1016/j.ecolecon.2015.10.013, 2015. a
Bowler, D. E., Buyung-Ali, L., Knight, T. M., and Pullin, A. S.: Urban
greening to cool towns and cities: A systematic review of the empirical
evidence, Landscape Urban Plan., 97, 147–155,
https://doi.org/10.1016/j.landurbplan.2010.05.006, 2010. a
Bozonnet, E., Musy, M., Calmet, I., and Rodriguez, F.: Modeling methods to
assess urban fluxes and heat island mitigation measures from street to city
scale, International Journal of Low-Carbon Technologies, 10, 62–77,
https://doi.org/10.1093/ijlct/ctt049, 2015. a
Buccolieri, R., Gromke, C., Di Sabatino, S., and Ruck, B.: Aerodynamic effects
of trees on pollutant concentration in street canyons, Sci. Total
Environ., 407, 5247–5256, https://doi.org/10.1016/j.scitotenv.2009.06.016, 2009. a, b
Buccolieri, R., Salim, M., Leo, L. S., Di Sabatino, S., Chan, A., Ielpo, P.,
de Gennaro, G., and Gromke, C.: Analysis of local scale tree–atmosphere
interaction on pollutant concentration in idealized street canyons and
application to a real urban junction, Atmos. Environ., 45, 1702–1713,
https://doi.org/10.1016/j.atmosenv.2010.12.058, 2011. a
Buccolieri, R., Santiago, J.-L., Rivas, E., and Sanchez, B.: Review on urban
tree modelling in CFD simulations: Aerodynamic, deposition and thermal
effects, Urban For. Urban Gree., 31, 212–220,
https://doi.org/10.1016/j.ufug.2018.03.003, 2018. a
Cai, X.-M., Barlow, J., and Belcher, S.: Dispersion and transfer of passive
scalars in and above street canyons – Large-eddy simulations, Atmos.
Environ., 42, 5885–5895, https://doi.org/10.1016/j.atmosenv.2008.03.040, 2008. a
Calfapietra, C., Fares, S., Manes, F., Morani, A., Sgrigna, G., and Loreto, F.:
Role of Biogenic Volatile Organic Compounds (BVOC) emitted by urban trees on
ozone concentration in cities: A review, Environ. Pollut., 183, 71–80,
https://doi.org/10.1016/j.envpol.2013.03.012, 2013. a
Faiz, A.: Automotive emissions in developing countries-relative implications
for global warming, acidification and urban air quality, Transportation
Res. A-Pol., 27, 167–186,
https://doi.org/10.1016/0965-8564(93)90057-R, 1993. a
Gillner, S., Vogt, J., Tharang, A., Dettmann, S., and Roloff, A.: Role of
street trees in mitigating effects of heat and drought at highly sealed urban
sites, Landscape Urban Plan., 143, 33–42,
https://doi.org/10.1016/j.landurbplan.2015.06.005, 2015. a
Gromke, C. and Blocken, B.: Influence of avenue-trees on air quality at the
urban neighborhood scale. Part II: Traffic pollutant concentrations at
pedestrian level, Environ. Pollut., 196, 176–184,
https://doi.org/10.1016/j.envpol.2014.10.015, 2015. a, b
Gromke, C. and Ruck, B.: Influence of trees on the dispersion of pollutants in
an urban street canyon – Experimental investigation of the flow and
concentration field., Atmos. Environ., 41, 3287–3302,
https://doi.org/10.1016/j.atmosenv.2006.12.043, 2007. a
Gromke, C. and Ruck, B.: On the Impact of Trees on Dispersion Processes of
Traffic Emissions in Street Canyons, Bound.-Lay. Meteorol., 131, 19–34,
https://doi.org/10.1007/s10546-008-9301-2, 2009. a
Gromke, C. and Ruck, B.: Pollutant Concentrations in Street Canyons of
Different Aspect Ratio with Avenues of Trees for Various Wind Directions,
Bound.-Lay. Meteorol., 144, 41–64, https://doi.org/10.1007/s10546-012-9703-z, 2012. a, b
Gu, S., Guenther, A., and Faiola, C.: Effects of Anthropogenic and Biogenic
Volatile Organic Compounds on Los Angeles Air Quality, Environ. Sci.
Technol., 55, 12191–12201, https://doi.org/10.1021/acs.est.1c01481, 2021. a
Gunawardena, K., Wells, M., and Kershaw, T.: Utilising green and bluespace to
mitigate urban heat island intensity, Sci. Total Environ.,
584–585, 1040–1055, https://doi.org/10.1016/j.scitotenv.2017.01.158, 2017. a
Harman, I. N., Barlow, J. F., and Belcher, S. E.: Scalar fluxes from urban
street canyons. Part II Model, Bound.-Lay. Meteorol., 113, 387–409,
https://doi.org/10.1007/s10546-004-6205-7, 2004. a, b
Hebbert, M. and Jankovic, V.: Cities and Climate Change: The Precedents and
Why They Matter, Urban Stud., 50, 1332–1347,
https://doi.org/10.1177/0042098013480970, 2013. a
Huang, Y.-D., Hou, R.-W., Liu, Z.-Y., Song, Y., Cui, P.-Y., and Kim, C.-N.:
Effects of Wind Direction on the Airflow and Pollutant Dispersion inside a
Long Street Canyon, Aerosol Air Qual. Res., 19, 1152–1171,
https://doi.org/10.4209/aaqr.2018.09.0344, 2019. a
Hwang, H.-J., Yook, S.-J., and Ahn, K.-H.: Experimental investigation of
submicron and ultrafine soot particle removal by tree leaves, Atmos.
Environ., 45, 6987–6994, https://doi.org/10.1016/j.atmosenv.2011.09.019, 2011. a
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working
Group I to the Sixth Assessment Report of the Intergovernmental Panel on
Climate Change, Report, Intergovernmental Panel on Climate Change, United
Nations, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C.,
Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K.,
Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R.,
and Zhou, B., Cambridge University Press, https://www.ipcc.ch/report/ar6/wg1/ (last access: 18 July 2022), 2021. a, b
Janhäll, S.: Review on urban vegetation and particle air pollution –
Deposition and dispersion, Atmos. Environ., 105, 130–137,
https://doi.org/10.1016/j.atmosenv.2015.01.052, 2015. a, b
Jayasooriya, V., Ng, A., Muthukumaran, S., and Perera, B.: Green
infrastructure practices for improvement of urban air quality, Urban For.
Urban Gree., 21, 34–47, https://doi.org/10.1016/j.ufug.2016.11.007, 2017. a
Jeanjean, A., Buccolierib, R., Eddy, J., Monks, P., and Leigh, R.: Air quality
affected by trees in real street canyons: The case of Marylebone
neighbourhood in central London., Urban For. Urban Gree., 22, 41–43,
https://doi.org/10.1016/j.ufug.2017.01.009, 2017. a
Katul, G. and Albertson, J.: An Investigation of Higher-Order Closure Models
for a Forested Canopy, Bound.-Lay. Meteorol., 89, 47–74,
https://doi.org/10.1023/A:1001509106381, 1998. a, b
Katul, G. G., Mahrt, L., Poggi, D., and Sanz, C.: ONE- and TWO-Equation Models
for Canopy Turbulence, Bound.-Lay. Meteorol., 113, 81–109,
https://doi.org/10.1023/B:BOUN.0000037333.48760.e5, 2004. a, b
Kent, C. W., Grimmond, S., and Gatey, D.: Aerodynamic roughness parameters in
cities: Inclusion of vegetation, J. Wind Eng. Ind.
Aerod., 169, 168–176, https://doi.org/10.1016/j.jweia.2017.07.016, 2017. a
Kim, Y., Wu, Y., Seigneur, C., and Roustan, Y.: Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1.0) by coupling MUNICH (v1.0) and Polair3D (v1.8.1), Geosci. Model Dev., 11, 611–629, https://doi.org/10.5194/gmd-11-611-2018, 2018. a
Kim, Y., Sartelet, K., Lugon, L., Roustan, Y., Sarica, T., Maison, A., Valari, M., Zhang, Y., and André, M.: The Model of Urban Network of Intersecting Canyons and Highways (MUNICH), Zenodo [code], https://doi.org/10.5281/zenodo.6167477, 2022. a
Klemm, W., Heusinkveld, B. G., Lenzholzer, S., and van Hove, B.: Street
greenery and its physical and psychological impact on thermal comfort,
Landscape Urban Plan., 138, 87–98, https://doi.org/10.1016/j.landurbplan.2015.02.009,
2015. a
Krekel, C., Kolbe, J., and Wüstemann, H.: The Greener, The Happier? The
Effects of Urban Green and Abandoned Areas on Residential Well-Being, The
German Socio-Economic Panel study at DIW Berlin, 728, 65, https://doi.org/10.2139/ssrn.2554477, 2015. a
Leopold, L. B.: Hydrology for urban land planning – A guidebook on the
hydrologic effects of urban land use, US. Geological Survey, 554, 18, https://doi.org/10.3133/cir554, 1968. a
Li, X., Liu, C., Leung, D., and Lam, K.: Recent progress in CFD modelling of
wind field and pollutant transport in street canyons, Atmos. Environ., 40,
5640–5658, https://doi.org/10.1016/j.atmosenv.2006.04.055, 2006. a
Livesley, S. J., McPherson, E. G., and Calfapietra, C.: The Urban Forest and
Ecosystem Services: Impacts on Urban Water, Heat, and Pollution Cycles at the
Tree, Street, and City Scale, J. Environ. Qual., 45,
119–124, https://doi.org/10.2134/jeq2015.11.0567, 2016. a
Lobaccaro, G. and Acero, J.: Comparative analysis of green actions to improve
outdoor thermal comfort inside typical urban street canyons, Urban Climate,
14, 251–267, https://doi.org/10.1016/j.uclim.2015.10.002, 2015. a
Lugon, L., Sartelet, K., Kim, Y., Vigneron, J., and Chrétien, O.: Nonstationary modeling of NO2, NO and NOx in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach, Atmos. Chem. Phys., 20, 7717–7740, https://doi.org/10.5194/acp-20-7717-2020, 2020. a, b
Lugon, L., Sartelet, K., Kim, Y., Vigneron, J., and Chrétien, O.: Simulation
of primary and secondary particles in the streets of Paris using MUNICH,
Faraday Discuss., https://doi.org/10.1039/D0FD00092B, 2021. a
Macdonald, R., Griffiths, R., and Hall, D.: An improved method for the
estimation of surface roughness of obstacle arrays, Atmos. Environ., 32,
1857–1864, https://doi.org/10.1016/S1352-2310(97)00403-2, 1998. a
Maison, A. and Flageul, C.: Parameterizing the aerodynamic effect of trees in street canyons for the street-network model MUNICH using the CFD model Code_Saturne – Code_Saturne simulation dataset, V2, Mendeley Data [code], https://doi.org/10.17632/fzfrjsz3mv.2, 2021. a
Direction des Espaces Verts et de l'Environnement – Mairie de Paris: Les arbres – OpenDataParis,
https://opendata.paris.fr/explore/dataset/les-arbres/, last access:
17 December 2021. a
Nowak, D. J., McHale, P. J., Ibarra, M., Crane, D., Stevens, J. C., and Luley, C. J.: Modeling the Effects of Urban Vegetation on Air Pollution, in: Air Pollution Modeling and Its Application XII, edited by: Gryning, S. E. and Chaumerliac, N., NATO, Challenges of Modern Society, vol 22., Springer, Boston, MA, 1998. a
Nowak, D. J. and Crane, D. E.: Carbon storage and sequestration by urban trees
in the USA, Environ. Pollut., 116, 381–389,
https://doi.org/10.1016/S0269-7491(01)00214-7, 2002. a
Nowak, D. J., Crane, D. E., and Stevens, J. C.: Air pollution removal by urban
trees and shrubs in the United States, Urban For. Urban Gree., 4, 115–123,
https://doi.org/10.1016/j.ufug.2006.01.007, 2006. a
Oke, T.: Street design and urban canopy layer climate, Energ. Buildings,
11, 103–113, https://doi.org/10.1016/0378-7788(88)90026-6, 1988. a
Oke, T. R.: The energetic basis of the urban heat island, Q. J.
Roy. Meteor. Soc., 108, 1–24,
https://doi.org/10.1002/qj.49710845502, 1982. a
Ozdemir, H.: Mitigation impact of roadside trees on fine particle pollution,
Sci. Total Environ., 659, 1176–1185,
https://doi.org/10.1016/j.scitotenv.2018.12.262, 2019. a
Pascal, M., Corso, M., Chanel, O., Declercq, C., Badaloni, C., Cesaroni, G.,
Henschel, S., Meister, K., Haluza, D., Martin-Olmedo, P., and Medina, S.:
Assessing the public health impacts of urban air pollution in 25 European
cities: Results of the Aphekom project, Sci. Total Environ.,
449, 390–400, https://doi.org/10.1016/j.scitotenv.2013.01.077, 2013. a
Pigeon, G., Legain, D., Durand, P., and Masson, V.: Anthropogenic heat release
in an old European agglomeration (Toulouse, France), Int. J. Climatol.,
27, 1969–1981, https://doi.org/10.1002/joc.1530, 2007. a
Préndez, M., Araya, M., Criollo, C., Egas, C., Farías, I., Fuentealba, R.,
and González, E.: Urban Trees and Their Relationship with Air Pollution by
Particulate Matter and Ozone in Santiago, Chile, in: Urban Climates in Latin
America, edited by: Henríquez, C. and Romero, H., Springer
International Publishing, pp. 167–206, https://doi.org/10.1007/978-3-319-97013-4_8, 2019. a
Revelli, R. and Porporato, A.: Ecohydrological model for the quantification of
ecosystem services provided by urban street trees, Urban Ecosyst., 21,
489–504, https://doi.org/10.1007/s11252-018-0741-2, 2018. a
Robine, J., Cheung, S., and Roy, S. L.: Report on excess mortality in Europe
during summer 2003, Tech. Rep., EU Community Action Programme for Public
Health, http://ec.europa.eu/health/ph_projects/2005/action1/docs/action1_2005_a2_15_en.pdf (last access: 18 July 2022), 2007. a
Santiago, J.-L., Rivas, E., Sanchez, B., Buccolieri, R., and Martin, F.: The
Impact of Planting Trees on NOx Concentrations: The Case of the Plaza de la
Cruz Neighborhood in Pamplona (Spain), Atmosphere, 8, 131,
https://doi.org/10.3390/atmos8070131, 2017. a
Sartelet, K., Zhu, S., Moukhtar, S., André, M., André, J., Gros, V.,
Favez, O., Brasseur, A., and Redaelli, M.: Emission of intermediate, semi
and low volatile organic compounds from traffic and their impact on secondary
organic aerosol concentrations over Greater Paris, Atmos. Environ., 180,
126–137, 2018. a
Selmi, W., Weber, C., Rivière, E., Blond, N., Mehdi, L., and Nowak, D.: Air
pollution removal by trees in public green spaces in Strasbourg city,
France, Urban For. Urban Gree., 17, 192–201,
https://doi.org/10.1016/j.ufug.2016.04.010, 2016. a
Soulhac, L., Salizzoni, P., Cierco, F.-X., and Perkins, R.: The model SIRANE
for atmospheric urban pollutant dispersion; part I, presentation of the
model, Atmos. Environ., 45, 7379–7395,
https://doi.org/10.1016/j.atmosenv.2011.07.008, 2011. a, b
Speziale, C., Sarkar, S., and Gatski, T.: Modelling the pressure-strain
correlation of turbulence – An invariant dynamical systems approach, J. Fluid
Mech., 227, 245–272, https://doi.org/10.1017/S0022112091000101, 1991. a
Stewart, I.: A systematic review and scientific critique of methodology in
modern urban heat island literature, Int. J. Climatol., 31, 200–217,
https://doi.org/10.1002/joc.2141, 2011. a
Svirejeva-Hopkins, A., Schellnhuber, H., and Pomaz, V.: Urbanised territories
as a specific component of the Global Carbon Cycle, Ecol. Model.,
173, 295–312, https://doi.org/10.1016/j.ecolmodel.2003.09.022, 2004. a
Taha, H., Akbari, H., and Rosenfeld, A.: Heat island and oasis effects of
vegetative canopies: Micro-meteorological field-measurements, Theor. Appl.
Climatol., 44, 123–138, https://doi.org/10.1007/BF00867999, 1991. a
van Dillen, S. M. E., de Vries, S., Groenewegen, P. P., and Spreeuwenberg, P.:
Greenspace in urban neighbourhoods and residents' health: adding quality to
quantity, J. Epidemiol. Commun. H., 66, e8,
https://doi.org/10.1136/jech.2009.104695, 2012. a
Vardoulakis, S., Fisher, B. E., Pericleous, K., and Gonzalez-Flesca, N.:
Modelling air quality in street canyons: a review, Atmos. Environ., 37,
155–182, https://doi.org/10.1016/S1352-2310(02)00857-9, 2003. a
Vos, P. E., Maiheu, B., Vankerkom, J., and Janssen, S.: Improving local air
quality in cities: To tree or not to tree?, Environ. Pollut., 183, 113–122,
https://doi.org/10.1016/j.envpol.2012.10.021, 2013.
a, b, c, d
Wang, W.: An Analytical Model for Mean Wind Profiles in Sparse Canopies,
Bound.-Lay. Meteorol., 142, 383–399, https://doi.org/10.1007/s10546-011-9687-0, 2012. a, b, c, d
Wania, A., Bruse, M., Blond, N., and Weber, C.: Analysing the influence of
different street vegetation on traffic-induced particle dispersion using
microscale simulations., J. Env. Manag., 94, 91–101,
https://doi.org/10.1016/j.jenvman.2011.06.036, 2012. a, b, c
Wei, X., Dupont, E., Gilbert, E., Musson-Genon, L., and Carissimo, B.:
Experimental and Numerical Study of Wind and Turbulence in a Near-Field
Dispersion Campaign at an Inhomogeneous Site, Bound.-Lay. Meteorol., 160,
475–499, https://doi.org/10.1007/s10546-016-0148-7, 2016. a
West, J. J., Cohen, A., Dentener, F., Brunekreef, B., Zhu, T., Armstrong, B.,
Bell, M. L., Brauer, M., Carmichael, G., Costa, D. L., Dockery, D. W.,
Kleeman, M., Krzyzanowski, M., Künzli, N., Liousse, C., Lung, S.-C. C.,
Martin, R. V., Pöschl, U., Pope, C. A., Roberts, J. M., Russell, A. G., and
Wiedinmyer, C.: What We Breathe Impacts Our Health: Improving Understanding
of the Link between Air Pollution and Health, Environ. Sci. Technol., 50,
4895–4904, https://doi.org/10.1021/acs.est.5b03827, 2016. a
Xue, F. and Li, X.: The impact of roadside trees on traffic released PM10 in
urban street canyon: Aerodynamic and deposition effects, Sustain. Cities
Soc., 30, 195–204, https://doi.org/10.1016/j.scs.2017.02.001, 2017. a
Yuan, C., Ng, E., and Norford, L. K.: Improving air quality in high-density
cities by understanding the relationship between air pollutant dispersion and
urban morphologies, Build. Environ., 71, 245–258,
https://doi.org/10.1016/j.buildenv.2013.10.008, 2014. a
Zaïdi, H., Dupont, E., Milliez, M., Musson-Genon, L., and Carissimo, B.:
Numerical Simulations of the Microscale Heterogeneities of Turbulence
Observed on a Complex Site, Bound.-Lay. Meteorol., 147, 237–259,
https://doi.org/10.1007/s10546-012-9783-9, 2013. a, b, c, d
Zhang, Y., Gu, Z., and Yu, C. W.: Impact Factors on Airflow and Pollutant
Dispersion in Urban Street Canyons and Comprehensive Simulations: a Review,
Current Pollution Report, 6, 425–439, https://doi.org/10.1007/s40726-020-00166-0,
2020. a
Short summary
This paper presents a parameterization of the tree crown effect on air flow and pollutant dispersion in a street network model used to simulate air quality at the street level. The new parameterization is built using a finer-scale model (computational fluid dynamics). The tree effect increases with the leaf area index and the crown volume fraction of the trees; the street horizontal velocity is reduced by up to 68 % and the vertical transfer into or out of the street by up to 23 %.
This paper presents a parameterization of the tree crown effect on air flow and pollutant...
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