Multiscale Analysis of Green Infrastructure Impacts on PM2.5 and PM10 Pollution in Delhi, India
Abstract
Urban air pollution, particularly from fine particulate matter (PM2.5 and PM10), poses critical environmental and public health challenges in rapidly urbanizing regions. This study presents a multiscale, seasonal analysis of the relationship between Green Infrastructure (GI) landscape characteristics and PM concentrations in Delhi, India. Using high-resolution Sentinel-2 imagery (2019–2021) and air quality data from 39 Central Pollution Control Board (CPCB) monitoring stations, we quantified 15 GI characteristics across five spatial scales (0.5–2.5 km) using NDVI. Empirical Bayesian Kriging was applied for spatial interpolation of PM values, and Otsu’s thresholding was used to delineate vegetated areas. Principal Component Analysis (PCA) and regression models revealed that compositional metrics—such as Class Area (CA) and Percentage of Landscape (PLAND)—showed consistent negative correlations with PM2.5 and PM10 levels across all scales and seasons. Configuration metrics, including Largest Patch Index (LPI), Edge Density (ED), and Aggregation Index (AI), exhibited scale- and season-specific influences, with stronger effects observed at broader spatial scales during winter and autumn. The findings suggest that both the quantity and spatial arrangement of urban vegetation significantly affect local air quality. The study underscores the need for scale-aware, evidence-based GI planning as a nature-based solution, supporting India’s airshed-level approach to urban pollution management. These insights offer practical guidance for urban policymakers and planners aiming to enhance air quality through strategic green infrastructure design.
References
Agarwal, M., & Tandon, A. (2010). Modeling of the urban heat island in the form of mesoscale wind and of its effect on air pollution dispersal. Applied Mathematical Modelling, 34(9), 2520–2530. https://doi.org/10.1016/j.apm.2009.11.016
Ahern, J. (2007). Green infrastructure for cities: The spatial dimension. In Cities ofthe Future Towards Integrated Sustainable Water and Landscape Management (pp. 267–283). http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=E549A4EF0DF3B927AD82A5B40BA1C2B1?doi=10.1.1.558.8386&rep=rep1&type=pdf
AlKhaled, S., Coseo, P., Brazel, A., Cheng, C., & Sailor, D. (2020). Between aspiration and actuality: A systematic review of morphological heat mitigation strategies in hot urban deserts. Urban Climate, 31, 100570. https://doi.org/10.1016/j.uclim.2019.100570
Andersson-Sköld, Y., Klingberg, J., Gunnarsson, B., Cullinane, K., Gustafsson, I., Hedblom, M., Knez, I., Lindberg, F., Ode Sang, Å., Pleijel, H., Thorsson, P., & Thorsson, S. (2018). A framework for assessing urban greenery’s effects and valuing its ecosystem services. Journal of Environmental Management, 205, 274–285. https://doi.org/10.1016/j.jenvman.2017.09.071
Andrew, S. M., Moe, S. R., Totland, Ø., & Munishi, P. K. T. (2012). Species composition and functional structure of herbaceous vegetation in a tropical wetland system. Biodiversity and Conservation, 21(11), 2865–2885. https://doi.org/10.1007/s10531-012-0342-y
Ashok, A., Rani, H. P., & Jayakumar, K. V. (2021). Monitoring of dynamic wetland changes using NDVI and NDWI based landsat imagery. Remote Sensing Applications: Society and Environment, 23, 100547. https://doi.org/10.1016/j.rsase.2021.100547
Banerjee, T., Murari, V., Kumar, M., & Raju, M. P. (2015). Source apportionment of airborne particulates through receptor modeling: Indian scenario. Atmospheric Research, 164–165, 167–187. https://doi.org/10.1016/j.atmosres.2015.04.017
Bartesaghi-Koc, C., Osmond, P., & Peters, A. (2019). Mapping and classifying green infrastructure typologies for climate-related studies based on remote sensing data. Urban Forestry and Urban Greening, 37(July 2017), 154–167. https://doi.org/10.1016/j.ufug.2018.11.008
Bartesaghi Koc, C., Osmond, P., & Peters, A. (2018). Evaluating the cooling effects of green infrastructure: A systematic review of methods, indicators and data sources. Solar Energy, 166(April), 486–508. https://doi.org/10.1016/j.solener.2018.03.008
Barwise, E. Y. (2023). Developing a design framework for enhanced air pollution mitigation by urban green infrastructure [University of Surrey Guildford, Surrey, GU2 7XH, United Kingdom]. https://openresearch.surrey.ac.uk/esploro/outputs/doctoral/Developing-a-design-framework-for-enhanced/99890066602346
Benedict, M. A., McMahon, E., & Conservation Fund (Arlington, V. . (2006). Green infrastructure : linking landscapes and communities. Island Press.
Bezyk, Y., Sówka, I., Górka, M., & Blachowski, J. (2021). Gis-based approach to spatio-temporal interpolation of atmospheric co2 concentrations in limited monitoring dataset. Atmosphere, 12(3), 1–25. https://doi.org/10.3390/atmos12030384
Calfapietra, C., & Cherubini, L. (2019). Green Infrastructure: Nature-Based Solutions for sustainable and resilient cities. Urban Forestry and Urban Greening, 37, 1–2. https://doi.org/10.1016/J.UFUG.2018.09.012
Cao, W., Zhou, W., Yu, W., & Wu, T. (2024). Combined effects of urban forests on land surface temperature and PM2.5 pollution in the winter and summer. Sustainable Cities and Society, 104(February), 105309. https://doi.org/10.1016/j.scs.2024.105309
Central Pollution Control Board. (2003). Guidelines for Ambient Air Quality Monitoring. National Ambient Air Quality Monitoring, NAAQMS, 2003–2004. https://doi.org/10.1080/15265160903581718
Chatterji, A. (2020). Air Pollution in Delhi: Filling the Policy Gaps. Observer Research Foundation, December. https://www.orfonline.org/research/air-pollution-delhi-filling-policy-gaps/
Chelani, A. B., Gajghate, D. G., Tamhane, S. M., & Hasan, M. Z. (2001). Statistical modeling of ambient air pollutants in Delhi. Water, Air, and Soil Pollution, 132(3–4), 315–331. https://doi.org/10.1023/A:1013204120867
Chen, M., & Dai, F. (2022). PCA-Based Identification of Built Environment Factors Reducing PM2.5 Pollution in Neighborhoods of Five Chinese Megacities. Atmosphere, 13(1). https://doi.org/10.3390/atmos13010115
Chen, M., Dai, F., Yang, B., & Zhu, S. (2019). Effects of neighborhood green space on PM 2 . 5 mitigation : Evidence from five megacities in China. Building and Environment, 156(March), 33–45. https://doi.org/10.1016/j.buildenv.2019.03.007
Chen, M., Dai, F., & Zhu, S. (2018). Effects of spatial forms of green infrastructure in block scale on PM10 and PM2.5 removal - A case study of the main city of Wuhan. Landscape Research Record, 7.
CleanAirAsia. (2016). Guidance Framework for Better Air Quality in Asian Cities.
CPCB. (2013). News Letter CPCB. Cpcbenvis, 53(9), 1689–1699.
CPCB. (2015). CPCB Data Protocol.
Dhingra, C. (2020). Assessment of AIR Quality Index for Delhi region_ A comparison between odd-even policy 2019 and Lock Down Period_.pdf.
Dissanayake, D., Morimoto, T., & Murayama, Y. (2018). Impact of Urban Surface Characteristics and Socio-Economic Variables on the Spatial Variation of Land Surface Temperature in Lagos City, Nigeria. Sustainability, 11(25). https://doi.org/10.3390/su11010025
Elhaik, E. (2022). Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated. In Scientific Reports (Vol. 12, Issue 1). Nature Publishing Group UK. https://doi.org/10.1038/s41598-022-14395-4
Fan, C., Myint, S. W., & Zheng, B. (2015). Measuring the spatial arrangement of urban vegetation and its impacts on seasonal surface temperatures. Progress in Physical Geography, 39(2), 199–219. https://doi.org/10.1177/0309133314567583
Forman, R. T. T. (1995). Some general principles of landscape and regional ecology. 10(3), 133–142.
Franklin, S. B., Gibson, D. J., Robertson, P. A., Pohlmann, J. T., Fralish, J. S., Scott, B., David, J., Philip, A., John, T., & James, S. (1995). Parallel Analysis : a Method for Determining Significant Principal Components significant principal components. Journal of Vegetation Scienc, 6(1), 99–106.
Ganguly, T., Selvaraj, K. L., & Guttikunda, S. K. (2020). National Clean Air Programme (NCAP) for Indian cities: Review and outlook of clean air action plans. Atmospheric Environment: X, 8, 100096. https://doi.org/10.1016/j.aeaoa.2020.100096
Gašparović, M., & Dobrinić, D. (2021). Green infrastructure mapping in urban areas using sentinel-1 imagery. Croatian Journal of Forest Engineering, 42(2), 337–356. https://doi.org/10.5552/crojfe.2021.859
Ge, M., Fang, S., Gong, Y., Tao, P., Yang, G., & Gong, W. (2021). Understanding the Correlation between Landscape Pattern and Vertical Urban Volume by Time-Series Remote Sensing Data: A Case Study of Melbourne. ISPRS International Journal of Geo-Information, 10(1), 14. https://doi.org/10.3390/ijgi10010014
Ginevan, M. E., & Splistone, D. E. (2004). Statistical Tools for Environemntal Quality Measurement. In Applied Environemntal Statistics (Vol. 59).
Grafius, D. R., Corstanje, R., & Harris, J. A. (2018). Linking ecosystem services, urban form and green space configuration using multivariate landscape metric analysis. Landscape Ecology, 33(4), 557–573. https://doi.org/10.1007/s10980-018-0618-z
Greenpeace. (2020). Toxiz Air: The Price of Fossil Fules (Issue February).
Grimm, N. B., Faeth, S. H., Golubiewski, N. E., Redman, C. L., Wu, J., Bai, X., & Briggs, J. M. (2008). Global Change and the Ecology of Cities. Science, 319(February).
Grover, A., & Singh, R. B. (2015). Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (NDVI): A comparative study of delhi and mumbai. Environments - MDPI, 2(2), 125–138. https://doi.org/10.3390/environments2020125
Gulia, S., Shiva Nagendra, S. M., Khare, M., & Khanna, I. (2015a). Urban air quality management-A review. Atmospheric Pollution Research, 6(2), 286–304. https://doi.org/10.5094/APR.2015.033
Gulia, S., Shiva Nagendra, S. M., Khare, M., & Khanna, I. (2015b). Urban air quality management-A review. Atmospheric Pollution Research, 6(2), 286–304. https://doi.org/10.5094/APR.2015.033
Guo, G., Wu, Z., Cao, Z., Chen, Y., & Zheng, Z. (2021). Location of greenspace matters: a new approach to investigating the effect of the greenspace spatial pattern on urban heat environment. Landscape Ecology, 0123456789. https://doi.org/10.1007/s10980-021-01230-w
Gupta, U. (2008). Valuation of urban air pollution: A case study of Kanpur City in India. In Environmental and Resource Economics (Vol. 41, Issue 3). https://doi.org/10.1007/s10640-008-9193-0
Guttikunda, S. K., & Calori, G. (2013). A GIS based emissions inventory at 1 km × 1 km spatial resolution for air pollution analysis in Delhi, India. Atmospheric Environment, 67, 101–111. https://doi.org/10.1016/j.atmosenv.2012.10.040
Guttikunda, S. K., Goel, R., & Pant, P. (2014). Nature of air pollution, emission sources, and management in the Indian cities. Atmospheric Environment, 95, 501–510. https://doi.org/10.1016/j.atmosenv.2014.07.006
Guttikunda, S. K., Nishadh, K. A., & Jawahar, P. (2019). Air pollution knowledge assessments (APnA) for 20 Indian cities. Urban Climate, 27(November 2018), 124–141. https://doi.org/10.1016/j.uclim.2018.11.005
Heo, S., Bell, M. L., Haven, N., & States, U. (2020). The Influence of Green Space on the Short-term Effects of Particulate Matter on Hospitalization in the U.S. for 2000–2013. Environment Research, 174, 61–68. https://doi.org/10.1016/j.envres.2019.04.019.The
Hirabayashi, S., Kroll, C. N., & Nowak, D. J. (2012). Development of a distributed air pollutant dry deposition modeling framework. Environmental Pollution, 171, 9–17. https://doi.org/10.1016/j.envpol.2012.07.002
Hirabayashi, S., Kroll, C. N., & Nowak, D. J. (2015). i-Tree Eco Dry Deposition Model Descriptions. http://www.itreetools.org/eco/resources/iTree_Eco_Dry_Deposition_Model_Descriptions.pdf
Hofman, J., Bartholomeus, H., Janssen, S., Calders, K., Wuyts, K., Van Wittenberghe, S., & Samson, R. (2016). Influence of tree crown characteristics on the local PM10 distribution inside an urban street canyon in Antwerp (Belgium): A model and experimental approach. Urban Forestry and Urban Greening, 20(2016), 265–276. https://doi.org/10.1016/j.ufug.2016.09.013
Im, J. (2019). Green streets to serve urban sustainability: Benefits and typology. Sustainability (Switzerland), 11(22). https://doi.org/10.3390/su11226483
Impacts, E. (n.d.). AIR.
IQAir. (2021). World Air Qualtiy Report.
Irga, P. J., Burchett, M. D., & Torpy, F. R. (2015). Does urban forestry have a quantitative effect on ambient air quality in an urban environment? Atmospheric Environment, 120, 173–181. https://doi.org/10.1016/j.atmosenv.2015.08.050
Jain, D., Bhatnagar, S., Rathi, V., Sharma, D., & Sachdeva, K. (2021). Mainstreaming Built Environment for Air Pollution Management Plan in Delhi. Economic and Political Weekly, 2019, 19–22. https://www.epw.in/journal/2021/6/commentary/mainstreaming-built-environment-air-pollution.html%0Ahttps://www.epw.in/system/files/pdf/2021_56/5/CM_LVI_06_060221_DeeptyJain_6Feb2021_Pages 19-22.pdf
Jalan, I. (2019). What is Polluting Delhi ’ s Air ? Understanding Uncertainties in Emissions Inventories (Issue March).
Jeanjean, A., Buccolieri, R., Eddy, J., Monks, P., & Leigh, R. (2017). Air quality affected by trees in real street canyons: The case of Marylebone neighbourhood in central London. Urban Forestry and Urban Greening, 22, 41–53. https://doi.org/10.1016/j.ufug.2017.01.009
Jeanjean, A. P. R., Monks, P. S., & Leigh, R. J. (2016). Modelling the effectiveness of urban trees and grass on PM2.5 reduction via dispersion and deposition at a city scale. Atmospheric Environment, 147, 1–10. https://doi.org/10.1016/j.atmosenv.2016.09.033
Jiang, L., & O’Neill, B. C. (2017). Global urbanization projections for the Shared Socioeconomic Pathways. Global Environmental Change, 42, 193–199. https://doi.org/10.1016/j.gloenvcha.2015.03.008
Jiang, R., Xie, C., Man, Z., Afshari, A., & Che, S. (2023). LCZ method is more effective than traditional LUCC method in interpreting the relationship between urban landscape and atmospheric particles. Science of the Total Environment, 869(October 2022), 161677. https://doi.org/10.1016/j.scitotenv.2023.161677
Jolliffe, I. T., Cadima, J., & Cadima, J. (2016). Principal component analysis : a review and recent developments Subject Areas. The Royal Society, 374.
Kenkel, N. C. (2006). On selecting an appropriate multivariate analysis. Canadian Journal of Plant Science, 86(3), 663–676. https://doi.org/10.4141/P05-164
Kotharkar, R., & Bagade, A. (2018). Evaluating urban heat island in the critical local climate zones of an Indian city. Landscape and Urban Planning, 169, 92–104. https://doi.org/10.1016/J.LANDURBPLAN.2017.08.009
Kumar, P., Abhijith, K. V., & Barwise, Y. (2019). Implementing Green Infrastructure for Air Pollution Abatement: General Recommendations for Management and Plant Species Selection. August. https://doi.org/doi.org/10.6084/m9.figshare.8198261.v1
Kumar, P., Druckman, A., Gallagher, J., Gatersleben, B., Allison, S., Eisenman, T. S., Hoang, U., Hama, S., Tiwari, A., Sharma, A., Abhijith, K. V., Adlakha, D., McNabola, A., Astell-Burt, T., Feng, X., Skeldon, A. C., de Lusignan, S., & Morawska, L. (2019). The nexus between air pollution, green infrastructure and human health. Environment International, 133(September). https://doi.org/10.1016/j.envint.2019.105181
Kushwaha, S., & Nithiyanandam, Y. (2019). The study of heat island and its relation with urbanization in Gurugram, Delhi NCR for the period of 1990 to 2018. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(5/W3), 49–56. https://doi.org/10.5194/isprs-archives-XLII-5-W3-49-2019
Lavigne, E., Yasseen, A. S., Stieb, D. M., Hystad, P., Donkelaar, A. Van, Martin, R. V, Brook, J. R., Crouse, D. L., Burnett, R. T., Chen, H., Weichenthal, S., Johnson, M., Villeneuve, P. J., & Walker, M. (2016). Ambient air pollution and adverse birth outcomes : Differences by maternal comorbidities. Environmental Research, 148, 457–466. https://doi.org/10.1016/j.envres.2016.04.026
Leão, M. L. P., Zhang, L., & da Silva Júnior, F. M. R. (2023). Effect of particulate matter (PM2.5 and PM10) on health indicators: climate change scenarios in a Brazilian metropolis. Environmental Geochemistry and Health, 45(5), 2229–2240. https://doi.org/10.1007/s10653-022-01331-8
Lei, Y., Davies, G. M., Jin, H., Tian, G., & Kim, G. (2021). Scale-dependent effects of urban greenspace on particulate matter air pollution. Urban Forestry & Urban Greening, 61(March), 127089. https://doi.org/10.1016/j.ufug.2021.127089
Lei, Y., Duan, Y., He, D., Zhang, X., Chen, L., Li, Y., Gao, Y. G., Tian, G., & Zheng, J. (2018). Effects of urban greenspace patterns on particulate matter pollution in metropolitan Zhengzhou in Henan, China. Atmosphere, 9(5), 1–15. https://doi.org/10.3390/ATMOS9050199
Li, K., Li, C., Liu, M., Hu, Y., Wang, H., & Wu, W. (2021). Multiscale analysis of the effects of urban green infrastructure landscape patterns on PM2.5 concentrations in an area of rapid urbanization. Journal of Cleaner Production, 325(October), 129324. https://doi.org/10.1016/j.jclepro.2021.129324
Li, X. (2017). Air Pollution: a global Problem Needs local Fixes. Springer Nature, 5, 9–11.
Li, X., Zhou, W., & Ouyang, Z. (2013). Relationship between land surface temperature and spatial pattern of greenspace: What are the effects of spatial resolution? Landscape and Urban Planning, 114, 1–8. https://doi.org/10.1016/j.landurbplan.2013.02.005
Li, Y. (2016). A Review of Air Pollution Control Policy Development and Effectiveness in China. Intech, i(tourism), 13.
Liang, L., & Gong, P. (2020). Urban and air pollution: a multi-city study of long-term effects of urban landscape patterns on air quality trends. Scientific Reports, 10(1), 1–13. https://doi.org/10.1038/s41598-020-74524-9
Liu, H., & Shen, Y. (2014). The Impact of Green Space Changes on Air Pollution and Microclimates: A Case Study of the Taipei Metropolitan Area. 8827–8855. https://doi.org/10.3390/su6128827
Liu, Y., Wu, J., & Yu, D. (2017). Characterizing spatiotemporal patterns of air pollution in China: A multiscale landscape approach. Ecological Indicators, 76, 344–356. https://doi.org/10.1016/j.ecolind.2017.01.027
Londoño-Ciro, L. A., & Cañón-Barriga, J. E. (2015). Imputation of spatial air quality data using gis-spline and the index of agreement in sparse urban monitoring networks. In Revista Facultad de Ingenieria, 76, 73–81. https://doi.org/10.17533/udea.redin.n76a09
Łowicki, D. (2019). Landscape pattern as an indicator of urban air pollution of particulate matter in Poland. Ecological Indicators, 97(September 2018), 17–24. https://doi.org/10.1016/j.ecolind.2018.09.050
Luo, H., Han, Y., Cheng, X., Lu, C., & Wu, Y. (2020). Spatiotemporal Variations in Particulate Matter and Air Quality over China: National, Regional and Urban Scales. Atmosphere, 12(1), 43. https://doi.org/10.3390/atmos12010043
Mannucci, P. M., Harari, S., Martinelli, I., & Franchini, M. (2015). Effects on health of air pollution: a narrative review. Internal and Emergency Medicine, 10(6), 657–662. https://doi.org/10.1007/s11739-015-1276-7
Mathers, C., Vos, T., & Stevenson, C. (1999). The burden of disease and injury in Australia (pp. 216–222).
Mcdonald, A. G., Bealey, W. J., Fowler, D., Dragosits, U., Skiba, U., Smith, R. I., Donovan, R. G., Brett, H. E., Hewitt, C. N., & Nemitz, E. (2007). Quantifying the effect of urban tree planting on concentrations and depositions of PM 10 in two UK conurbations. 41, 8455–8467. https://doi.org/10.1016/j.atmosenv.2007.07.025
Mcgarigal, K. (2015). Fragstats. Fragstats, April, 1–182.
McGarigal, K. (1995). FRAGSTATS : Spatial Pattern Analysis Program for Quantifying Landscape Structure. August.
McGarigal, K., Cushman, S. A., Neel, M. C., & Ene, E. (2002). FRAGSTATS: spatial pattern analysis program for categorical maps [internet].[cited 2009 October 12]. January 2002.
Meng, F., Tang, W., Gao, J., Ma, T., Li, Y., Du, X., Liu, J., Yang, Y., & Yu, Y. (2025). A Receptor Model and CTM Integrated PM2 . 5 Source Apportionment Approach and Its Application in 2 + 26 Cities Region of China Apportionment Approach and Its Application in 2 + 26 Cities Region of China. Atmospheric Science and Meteorology, 0–15. https://doi.org/10.20944/preprints202503.2207.v1
Menon, J. S., & Sharma, R. (2021). Nature-Based Solutions for Co-mitigation of Air Pollution and Urban Heat in Indian Cities. Frontiers in Sustainable Cities, 3(October), 1–11. https://doi.org/10.3389/frsc.2021.705185
Ministry Of Environment & Forests. (1987). AIR POLLUTION CONTROL AREAS IN VARIOUS UT ( s ) (Issue February, p. 14012).
Molina, M. J., Molina, L. T., Molina, M. J., & Molina, L. T. (2012). Megacities and Atmospheric Pollution Megacities and Atmospheric Pollution. 2247(2004). https://doi.org/10.1080/10473289.2004.10470936
Morelli, X., Rieux, C., Cyrys, J., Forsberg, B., & Slama, R. (2016). Air pollution , health and social deprivation : A fine-scale risk assessment. 147, 59–70. https://doi.org/10.1016/j.envres.2016.01.030
Myint, S. W., Zheng, B., Talen, E., Fan, C., Kaplan, S., Middel, A., Smith, M., Huang, H. ping, & Brazel, A. (2015). Does the spatial arrangement of urban landscape matter? examples of urban warming and cooling in phoenix and las vegas. Ecosystem Health and Sustainability, 1(4), 1–15. https://doi.org/10.1890/EHS14-0028.1
Nations, U., Programme, E., This, R., United, T., Environment, N., Nations, U., Programme, E., The, D., Nations, U., Programme, E., Nations, U., Programme, E., Nations, U., Programme, E., Nations, U., Programme, E., Pollution, A., This, S. S., Pacific, A., … Coalition, C. A. (2018). Air Pollution in Asia and the Pacific: Science-based solutions. In United Nations Environment Programme. http://www.ccacoalition.org/en/resources/air-pollution-asia-and-pacific-science-based-solutions
Nautiyal, S. N., Joshi, V., Gautam, A. S., Kumar, R., Kumar, S., Singh, K., & Gautam, S. (2025). Characterization and source apportionment of PM2.5 and PM10 in a Mountain Valley: seasonal variations, morphology, and elemental composition. Journal of Atmospheric Chemistry, 82(1). https://doi.org/10.1007/s10874-025-09469-2
Nowak, D. J., Crane, D. E., & Stevens, J. C. (2006). Air pollution removal by urban trees and shrubs in the United States. Urban Forestry and Urban Greening, 4(3–4), 115–123. https://doi.org/10.1016/j.ufug.2006.01.007
NWGITT. (2008). Green Infrastructure Guide.
Ou, Y., Rousseau, A. N., Wang, L., & Yan, B. (2017). Spatio-temporal patterns of soil organic carbon and pH in relation to environmental factors—A case study of the Black Soil Region of Northeastern China. Agriculture, Ecosystems and Environment, 245(May), 22–31. https://doi.org/10.1016/j.agee.2017.05.003
Ouyang, W., Morakinyo, T. E., Ren, C., Liu, S., & Ng, E. (2021). Thermal-irradiant performance of green infrastructure typologies: Field measurement study in a subtropical climate city. Science of the Total Environment, 764, 144635. https://doi.org/10.1016/j.scitotenv.2020.144635
Peters, A. (2011). Ambient Particulate Matter and the Risk for Cardiovascular Disease. Progress in Cardiovascular Diseases, 53, 327–333. https://doi.org/10.1016/j.pcad.2011.02.002
Power, A. L., Tennant, R. K., Stewart, A. G., Gosden, C., Worsley, A. T., Jones, R., & Love, J. (2023). The evolution of atmospheric particulate matter in an urban landscape since the Industrial Revolution. Scientific Reports, 13(1), 1–15. https://doi.org/10.1038/s41598-023-35679-3
Ramadan, B. S., Budihardjo, M. A., Syafrudin, Huboyo, H. S., & Sari, S. A. (2025). Analysis of particulate matter (PM10 and PM2.5) emissions from Jatibarang landfill: implications for air quality and health. IOP Conference Series: Earth and Environmental Science, 1477(1). https://doi.org/10.1088/1755-1315/1477/1/012033
Ramaiah, M., & Avtar, R. (2019). Urban Green Spaces and Their Need in Cities of Rapidly Urbanizing India: A Review. Urban Science, 3(3), 94. https://doi.org/10.3390/urbansci3030094
Ramani, P., Shah, C., Parikh, D., & Dadhaniya, B. (2019). AIR POLLUTION EFFECT ON URBAN AREAS. Pramana Research Journal, 9(9), 1–12.
Ramyar, R., & Zarghami, E. (2017). Green infrastructure contribution for climate change adaptation in urban landscape context. Applied Ecology and Environmental Research, 15(3), 1193–1209. https://doi.org/10.15666/aeer/1503_11931209
Rezaei, N., & Millard-Ball, A. (2023). Urban form and its impacts on air pollution and access to green space: A global analysis of 462 cities. PLoS ONE, 18(1 January), 1–26. https://doi.org/10.1371/journal.pone.0278265
Rohde, R. A., & Muller, R. A. (2015). Air Pollution in China : Mapping of Concentrations and Sources. PLoS ONE, 2, 1–14. https://doi.org/10.1371/journal.pone.0135749
Role, T. (2021). Integrating Clean Air , Climate , and Health Policies in the COVID-19 Era. March.
Sangkham, S., Phairuang, W., Sherchan, S. P., Pansakun, N., Munkong, N., Sarndhong, K., Islam, M. A., & Sakunkoo, P. (2024). An update on adverse health effects from exposure to PM2.5. Environmental Advances, 18(September), 100603. https://doi.org/10.1016/j.envadv.2024.100603
Saraswat, I., Mishra, R. K., & Kumar, A. (2017). Estimation of PM10 concentration from Landsat 8 OLI satellite imagery over Delhi, India. Remote Sensing Applications: Society and Environment, 8(April), 251–257. https://doi.org/10.1016/j.rsase.2017.10.006
Sathyakumar, V., Ramsankaran, R. A. A. J., & Bardhan, R. (2020). Geospatial approach for assessing spatiotemporal dynamics of urban green space distribution among neighbourhoods: A demonstration in Mumbai. Urban Forestry and Urban Greening, 48(December 2019), 126585. https://doi.org/10.1016/j.ufug.2020.126585
Schneekloth, L. H. (2000). Urban green infrastructure. In Time-Saver Standards for Urban Design (Issue 1987).
Selmi, W., Weber, C., Rivière, E., Blond, N., Mehdi, L., & Nowak, D. (2016). Air pollution removal by trees in public green spaces in Strasbourg city, France. Urban Forestry and Urban Greening, 17(2), 192–201. https://doi.org/10.1016/j.ufug.2016.04.010
Shareef, M. M., Husain, T., & Alharbi, B. (2016). Optimization of Air Quality Monitoring Network Using GIS Based Interpolation Techniques. Journal of Environmental Protection, 7(6), 895–911. https://doi.org/10.4236/jep.2016.76080
Sharma, S. K., Mandal, T. K., Saxena, M., Rashmi, Rohtash, Sharma, A., & Gautam, R. (2014). Source apportionment of PM10 by using positive matrix factorization at an urban site of Delhi, India. Urban Climate, 10, 656–670. https://doi.org/10.1016/j.uclim.2013.11.002
Singh, N., Singh, S., & Mall, R. K. (2020). Urban ecology and human health: implications of urban heat island, air pollution and climate change nexus. In Urban Ecology. Elsevier Inc. https://doi.org/10.1016/b978-0-12-820730-7.00017-3
Singh, P., & Tyagi, A. (2013a). Applying Kriging Approach on Pollution Data Using GIS Software. International Journal of Environmental Engineering and Management, 4(3), 185–190. http://www.ripublication.com/ijeem.htm
Singh, V., Guizani, N., Al-Alawi, A., Claereboudt, M., & Rahman, M. S. (2013b). Instrumental texture profile analysis (TPA) of date fruits as a function of its physico-chemical properties. Industrial Crops and Products, 50, 866–873. https://doi.org/10.1016/j.indcrop.2013.08.039
Sinnett, D., Smith, N., & Burgess, S. (2015). Handbook on green infrastructure: Planning, design and implementation. Handbook on Green Infrastructure: Planning, Design and Implementation, 1–474. https://doi.org/10.4337/9781783474004
Song, Z., Li, R., Qiu, R., Liu, S., Tan, C., Li, Q., Ge, W., Han, X., Tang, X., Shi, W., Song, L., Yu, W., Yang, H., & Ma, M. (2018). Global land surface temperature influenced by vegetation cover and PM 2.5 from 2001 to 2016. Remote Sensing, 10(12), 1–18. https://doi.org/10.3390/rs10122034
Soni, P. (2021). Effects of COVID-19 lockdown phases in India: an atmospheric perspective. Environment, Development and Sustainability, 0123456789. https://doi.org/10.1007/s10668-020-01156-4
Soydan, O. (2020). Effects of landscape composition and patterns on land surface temperature: Urban heat island case study for Nigde, Turkey. Urban Climate, 34(December 2019), 100688. https://doi.org/10.1016/j.uclim.2020.100688
Srbinovska, M., Andova, V., Mateska, A. K., & Krstevska, M. C. (2021). The effect of small green walls on reduction of particulate matter concentration in open areas. Journal of Cleaner Production, 279, 123306. https://doi.org/10.1016/j.jclepro.2020.123306
Tallis, M. J., Amorim, J. H., Calfapietra, C., & Smith, P. F. (2015). The impacts of green infrastructure on air quality and temperature. In Handbook on Green Infrastructure: Planning, design and implementation (Issue January 2016). https://doi.org/10.4337/9781783474004.00008
Thiis, T. K., Gaitani, N., Burud, I., & Engan, J. A. (2018). Classification of urban blue green structures with aerial measurements. International Journal of Sustainable Development and Planning, 13(4), 506–515. https://doi.org/10.2495/SDP-V13-N4-506-515
Tiwari, A., & Kumar, P. (2020). Integrated dispersion-deposition modelling for air pollutant reduction via green infrastructure at an urban scale. Science of the Total Environment, 723, 138078. https://doi.org/10.1016/j.scitotenv.2020.138078
Tomson, N., Michael, R. N., & Agranovski, I. E. (2025). Classic Theory of Aerosol Filtration for Application to Urban Green Infrastructure. Water, Air, and Soil Pollution, 236(3), 1–9. https://doi.org/10.1007/s11270-025-07829-y
UNDESA. (2019). World population prospects 2019. In Department of Economic and Social Affairs. World Population Prospects 2019. (Issue 141).
Urban Climate Lab. (2016). The benefits of green infrastructure for heat mitigation and emissions reductions in cities. June.
US EPA, OW, O. (2010). What is Green Infrastructure?
Vieira, J., Matos, P., Mexia, T., Silva, P., Lopes, N., Freitas, C., Correia, O., Santos-Reis, M., Branquinho, C., & Pinho, P. (2018). Green spaces are not all the same for the provision of air purification and climate regulation services: The case of urban parks. Environmental Research, 160(October 2017), 306–313. https://doi.org/10.1016/j.envres.2017.10.006
Vieira, L., Polisel, R., Ivanauskas, N., Shepherd, G., Waechter, J., Yamamoto, K., & Martins, F. (2015). Geographical patterns of terrestrial herbs : a new component in planning the conservation of the Brazilian. Biodivers Conserv, 24, 2181–2198. https://doi.org/10.1007/s10531-015-0967-8
WHO. (2018). World Health Organization releases new global air pollution data | Climate & Clean Air Coalition. 1–11. https://www.ccacoalition.org/en/news/world-health-organization-releases-new-global-air-pollution-data
Wu, H., Yang, C., Chen, J., Yang, S., Lu, T., & Lin, X. (2018). Effects of Green space landscape patterns on particulate matter in Zhejiang Province, China. Atmospheric Pollution Research, 9(5), 923–933. https://doi.org/10.1016/j.apr.2018.03.004
Wu, J., Xie, W., Li, W., & Li, J. (2015). Effects of urban landscape pattern on PM2.5 Pollution-A Beijing Case Study. PLoS ONE, 10(11), 1–20. https://doi.org/10.1371/journal.pone.0142449
Wu, X., Chen, Y., Guo, J., Wang, G., & Gong, Y. (2017). Spatial concentration, impact factors and prevention-control measures of PM2.5 pollution in China. Natural Hazards, 86(1), 393–410. https://doi.org/10.1007/s11069-016-2697-y
Yale and Columbia Universities. (2022). Environmental Performance Index (Vol. 1, Issue June).
Yang, H., Wu, M., Liu, W., Zhang, Z., Zhang, N., & Wan, S. (2011). Community structure and composition in response to climate change in a temperate steppe. Global Change Biology, 17(1), 452–465. https://doi.org/10.1111/j.1365-2486.2010.02253.x
Yao, M., Smith, M., & Peng, C. (2025). Modelling the effects of vegetation and urban form on air quality in real urban environments: A systematic review of measurements, methods, and predictions. In Urban Forestry and Urban Greening (Vol. 105). https://doi.org/10.1016/j.ufug.2025.128693
Yu, X., & Jingyi L, Y. H. (2019). A Review of the Relationship Between Urban Green Morphology and Urban Climate. Urban Morphology Theory, 23(10), 835–846.
Yu, Z., Wang, Y., Deng, J., Shen, Z., Wang, K., Zhu, J., & Gan, M. (2017). Dynamics of hierarchical urban green space patches and implications for management policy. Sensors (Switzerland), 17(6). https://doi.org/10.3390/s17061304
Zhang, R., Chen, G., Yin, Z., Zhang, Y., & Ma, K. (2021a). Urban greening based on the supply and demand of atmospheric. Ecological Indicators, 126, 107696. https://doi.org/10.1016/j.ecolind.2021.107696
Zhang, R., Chen, G., Yin, Z., Zhang, Y., & Ma, K. (2021b). Urban greening based on the supply and demand of atmospheric PM2.5 removal. Ecological Indicators, 126, 107696. https://doi.org/10.1016/j.ecolind.2021.107696
Zhang, S., Ban, Y., Xu, Z., Cheng, J., & Li, M. (2016). Comparative evaluation of influencing factors on aquaculture wastewater treatment by various constructed wetlands. Ecological Engineering, 93, 221–225. https://doi.org/10.1016/j.ecoleng.2016.05.029
Zhang, X., Xi, Z., Li, X., Wang, C., Qiu, L., & Gao, T. (2024). Urban green space influencing air particulate matter concentration at different spatial scales base on land use regression model Urban green space influencing air particulate matter concentration at different 2 spatial scales base on land use regression m. Sustainability, 3. https://ssrn.com/abstract=4684225
Zheng, D., Zhang, G., Shan, H., Tu, Q., Wu, H., & Li, S. (2020). Spatio-temporal evolution of urban morphology in the Yangtze River Middle Reaches Megalopolis, China. Sustainability (Switzerland), 12(5), 1–15. https://doi.org/10.3390/su12051738
Zhou, W., Huang, G., & Cadenasso, M. L. (2011). Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes. Landscape and Urban Planning, 102(1), 54–63. https://doi.org/10.1016/j.landurbplan.2011.03.009
Zhou, W., Shen, X., Cao, F., Sun, Y., & Ph, D. (2019). Effects of Area and Shape of Greenspace on Urban Cooling in Nanjing , China. 145(4), 1–9. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000520.
Zhou, Y., Liu, H., Zhou, J., & Xia, M. (2019). GIS-based urban afforestation spatial patterns and a strategy for PM2.5 removal. Forests, 10(10), 1–17. https://doi.org/10.3390/f10100875
