Long-Term Greenness Effects of Urban Forests to Reduce PM10 Concentration: Does the Impact Benefit the Population Vulnerable to Asthma?
Abstract
:1. Introduction
2. Study Area
3. Materials and Methods
3.1. PM10, PM2.5 Data
3.2. Meteorological Data
3.3. The Greenness Indies: EVI and NDVI from Landsat 5, 8
3.4. The Respiratory Diseases Statistics: Asthma
3.5. Linear Multiple Regression and Correlation Analysis
4. Results
4.1. Change in Annual PM10 Concentrations
4.2. The Main Factors Contributing to the Reduction of PM10
4.3. Association Among Urban Forest Greenness and PM10, PM2.5 Reduction, Human Health
5. Discussion
5.1. Urban Forest Management Strategy Considering the Long-Term PM10 Reduction Factors
5.2. PM Reduction Effect on the Health of Vulnerable Groups and Implications for Forest Management in Residential Areas
5.3. Limitation and Further Research
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
Appendix A
References
- Heo, S.; Bell, M.L. The Influence of Green Space on the Short-Term Effects of Particulate Matter on Hospitalization in the U.S. for 2000–2013. Environ. Res. 2019, 174, 61–68. [Google Scholar] [CrossRef] [PubMed]
- Lu, F.; Xu, D.; Cheng, Y.; Dong, S.; Guo, C.; Jiang, X.; Zheng, X. Systematic Review and Meta-Analysis of the Adverse Health Effects of Ambient PM2.5 and PM10 Pollution in the Chinese Population. Environ. Res. 2015, 136, 196–204. [Google Scholar] [CrossRef] [PubMed]
- Lelieveld, J.; Evans, J.S.; Fnais, M.; Giannadaki, D.; Pozzer, A. The Contribution of Outdoor Air Pollution Sources to Premature Mortality on a Global Scale. Nature 2015, 525, 367–371. [Google Scholar] [CrossRef] [PubMed]
- Xing, Y.-F.; Xu, Y.-H.; Shi, M.-H.; Lian, Y.-X. The Impact of PM2.5 on the Human Respiratory System. J. Thorac. Dis. 2016, 8, E69–E74. [Google Scholar] [CrossRef] [PubMed]
- Anenberg, S.C.; Henze, D.K.; Tinney, V.; Kinney, P.L.; Raich, W.; Fann, N.; Malley, C.S.; Roman, H.; Lamsal, L.; Duncan, B.; et al. Estimates of the Global Burden of Ambient PM2.5, Ozone, and NO2 on Asthma Incidence and Emergency Room Visits. Environ. Health Perspect. 2018, 126, 107004. [Google Scholar] [CrossRef] [PubMed]
- Nowak, D.J.; Crane, D.E.; Stevens, J.C. Air Pollution Removal by Urban Trees and Shrubs in the United States. Urban For. Urban Green. 2006, 4, 115–123. [Google Scholar] [CrossRef]
- Nowak, D.J.; Hirabayashi, S.; Bodine, A.; Greenfield, E. Tree and Forest Effects on Air Quality and Human Health in the United States. Environ. Pollut. 2014, 193, 119–129. [Google Scholar] [CrossRef]
- Nowak, D.J.; Hirabayashi, S.; Doyle, M.; McGovern, M.; Pasher, J. Air Pollution Removal by Urban Forests in Canada and Its Effect on Air Quality and Human Health. Urban For. Urban Green. 2018, 29, 40–48. [Google Scholar] [CrossRef]
- Zhang, J.; Yu, Z.; Zhao, B.; Sun, R.; Vejre, H. Links between Green Space and Public Health: A Bibliometric Review of Global Research Trends and Future Prospects from 1901 to 2019. Environ. Res. Lett. 2020, 15, 063001. [Google Scholar] [CrossRef]
- Choi, Y.; Ji, E.; Chon, J. Development and Verification of the Effectiveness of a Fine Dust Reduction Planting Model for Socially Vulnerable Area. Sustainability 2021, 13, 8820. [Google Scholar] [CrossRef]
- Kim, S.-W.; Lee, D.-K.; Bae, C.-Y. Analysis of the effect of street green structure on PM2.5 in the walk space—Using microclimate simulation -. J. Korean Soc. Environ. Restor. Technol. 2021, 24, 61–75. [Google Scholar] [CrossRef]
- Kim, P.-R.; Park, C.-R. Evaluation of Particulate Matter’s Traits and Reduction Effects in Urban Forest, Seoul. Korean J. Environ. Ecol. 2021, 35, 569–575. [Google Scholar] [CrossRef]
- Lee, A.; Jeong, S.; Joo, J.; Park, C.-R.; Kim, J.; Kim, S. Potential Role of Urban Forest in Removing PM2.5: A Case Study in Seoul by Deep Learning with Satellite Data. Urban Clim. 2021, 36, 100795. [Google Scholar] [CrossRef]
- Diener, A.; Mudu, P. How Can Vegetation Protect Us from Air Pollution? A Critical Review on Green Spaces’ Mitigation Abilities for Air-Borne Particles from a Public Health Perspective—with Implications for Urban Planning. Sci. Total Environ. 2021, 796, 148605. [Google Scholar] [CrossRef] [PubMed]
- Nguyen, T.; Yu, X.; Zhang, Z.; Liu, M.; Liu, X. Relationship between Types of Urban Forest and PM2.5 Capture at Three Growth Stages of Leaves. J. Environ. Sci. 2015, 27, 33–41. [Google Scholar] [CrossRef] [PubMed]
- Bui, H.; Odsuren, U.; Kim, S.-Y.; Park, B.-J. Particulate Matter Accumulation and Leaf Traits of Ten Woody Species Growing with Different Air Pollution Conditions in Cheongju City, South Korea. Atmosphere 2022, 13, 1351. [Google Scholar] [CrossRef]
- Yao, J.; Wu, S.; Cao, Y.; Wei, J.; Tang, X.; Hu, L.; Wu, J.; Yang, H.; Yang, J.; Ji, X. Dry Deposition Effect of Urban Green Spaces on Ambient Particulate Matter Pollution in China. Sci. Total Environ. 2023, 900, 165830. [Google Scholar] [CrossRef]
- Xu, X.; Xia, J.; Gao, Y.; Zheng, W. Additional Focus on Particulate Matter Wash-off Events from Leaves Is Required: A Review of Studies of Urban Plants Used to Reduce Airborne Particulate Matter Pollution. Urban For. Urban Green. 2020, 48, 126559. [Google Scholar] [CrossRef]
- Wolf, K.L.; Lam, S.T.; McKeen, J.K.; Richardson, G.R.A.; van den Bosch, M.; Bardekjian, A.C. Urban Trees and Human Health: A Scoping Review. Int. J. Environ. Res. Public Health 2020, 17, 4371. [Google Scholar] [CrossRef] [PubMed]
- Markevych, I.; Schoierer, J.; Hartig, T.; Chudnovsky, A.; Hystad, P.; Dzhambov, A.M.; De Vries, S.; Triguero-Mas, M.; Brauer, M.; Nieuwenhuijsen, M.J.; et al. Exploring Pathways Linking Greenspace to Health: Theoretical and Methodological Guidance. Environ. Res. 2017, 158, 301–317. [Google Scholar] [CrossRef]
- Kumar, P.; Druckman, A.; Gallagher, J.; Gatersleben, B.; Allison, S.; Eisenman, T.S.; Hoang, U.; Hama, S.; Tiwari, A.; Sharma, A.; et al. The Nexus between Air Pollution, Green Infrastructure and Human Health. Environ. Int. 2019, 133, 105181. [Google Scholar] [CrossRef] [PubMed]
- Eisenman, T.S.; Churkina, G.; Jariwala, S.P.; Kumar, P.; Lovasi, G.S.; Pataki, D.E.; Weinberger, K.R.; Whitlow, T.H. Urban Trees, Air Quality, and Asthma: An Interdisciplinary Review. Landsc. Urban Plan. 2019, 187, 47–59. [Google Scholar] [CrossRef]
- Sheng, Q.; Ji, Y.; Zhou, C.; Zhang, H.; Zhu, Z. Spatiotemporal Variation and Pattern Analysis of Air Pollution and Its Correlation with NDVI in Nanjing City, China: A Landsat-Based Study. Forests 2023, 14, 2106. [Google Scholar] [CrossRef]
- Zhai, C.; Bao, G.; Zhang, D.; Sha, Y. Urban Forest Locations and Patch Characteristics Regulate PM2.5 Mitigation Capacity. Forests 2022, 13, 1408. [Google Scholar] [CrossRef]
- Sierra-Porta, D.; Solano-Correa, Y.T.; Tarazona-Alvarado, M.; de Villavicencio, L.A.N. Linking PM10 and PM2.5 Pollution Concentration through Tree Coverage in Urban Areas. Clean Soil Air Water 2023, 51, 2200222. [Google Scholar] [CrossRef]
- Hou, J.; Liu, X.; Zuo, T.; Tu, R.; Dong, X.; Li, R.; Pan, M.; Chen, R.; Yin, S.; Hu, K.; et al. Residential Greenness Attenuated Associations of Long-Term Exposure to Air Pollution with Biomarkers of Advanced Fibrosis. Env. Sci. Pollut. Res. 2022, 29, 977–988. [Google Scholar] [CrossRef] [PubMed]
- Nordeide Kuiper, I.; Svanes, C.; Markevych, I.; Accordini, S.; Bertelsen, R.J.; Bråbäck, L.; Heile Christensen, J.; Forsberg, B.; Halvorsen, T.; Heinrich, J.; et al. Lifelong Exposure to Air Pollution and Greenness in Relation to Asthma, Rhinitis and Lung Function in Adulthood. Environ. Int. 2021, 146, 106219. [Google Scholar] [CrossRef]
- Vienneau, D.; De Hoogh, K.; Faeh, D.; Kaufmann, M.; Wunderli, J.M.; Röösli, M. More than Clean Air and Tranquillity: Residential Green Is Independently Associated with Decreasing Mortality. Environ. Int. 2017, 108, 176–184. [Google Scholar] [CrossRef]
- Yoo, S.-Y.; Kim, T.; Ham, S.; Choi, S.; Park, C.-R. Importance of Urban Green at Reduction of Particulate Matters in Sihwa Industrial Complex, Korea. Sustainability 2020, 12, 7647. [Google Scholar] [CrossRef]
- Yoo, S.-Y.; Choi, S.; Koo, N.; Kim, T.; Park, C.-R.; Park, W.-H. A 10-Year Analysis on the Reduction of Particulate Matter at the Green Buffer of the Sihwa Industrial Complex. Sustainability 2021, 13, 5538. [Google Scholar] [CrossRef]
- Chen, J.; Yu, X.; Sun, F.; Lun, X.; Fu, Y.; Jia, G.; Zhang, Z.; Liu, X.; Mo, L.; Bi, H. The Concentrations and Reduction of Airborne Particulate Matter (PM10, PM2.5, PM1) at Shelterbelt Site in Beijing. Atmosphere 2015, 6, 650–676. [Google Scholar] [CrossRef]
- Choi, J.-W. A Study on Vegetation Changes for 11years and Vegetation Structure in the Green Buffer Zone of Sihwa Industrial Complex. J. Korean Soc. Environ. Restor. Technol. 2018, 21, 81–96. [Google Scholar] [CrossRef]
- Cho, S.J.; Kim, H.M. Evaluation of Green Buffer Zone Supplement Plan for Air Pollution Decrease Function; in the Case of Sihwa Industrial Complex Green Buffer Zone. J. Korea Soc. Environ. Adm. 2009, 15, 145–154. [Google Scholar]
- Huete, A.; Didan, K.; Miura, T.; Rodriguez, E.P.; Gao, X.; Ferreira, L.G. Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices. Remote Sens. Environ. 2002, 83, 195–213. [Google Scholar] [CrossRef]
- Schmid, J.N. Using Google Earth Engine for Landsat NDVI Time Series Analysis to Indicate the Present Status of Forest Stands. Bachelor’s Thesis, Leibniz Universität Hannover, Hannover, Germany, 2017. [Google Scholar]
- Liu, L.; Xiao, X.; Qin, Y.; Wang, J.; Xu, X.; Hu, Y.; Qiao, Z. Mapping Cropping Intensity in China Using Time Series Landsat and Sentinel-2 Images and Google Earth Engine. Remote Sens. Environ. 2020, 239, 111624. [Google Scholar] [CrossRef]
- Zhu, Z.; Fu, Y.; Woodcock, C.E.; Olofsson, P.; Vogelmann, J.E.; Holden, C.; Wang, M.; Dai, S.; Yu, Y. Including Land Cover Change in Analysis of Greenness Trends Using All Available Landsat 5, 7, and 8 Images: A Case Study from Guangzhou, China (2000–2014). Remote Sens. Environ. 2016, 185, 243–257. [Google Scholar] [CrossRef]
- Zhou, M.; Li, D.; Liao, K.; Lu, D. Integration of Landsat Time-Series Vegetation Indices Improves Consistency of Change Detection. Int. J. Digit. Earth 2023, 16, 1276–1299. [Google Scholar] [CrossRef]
- Roy, D.P.; Kovalskyy, V.; Zhang, H.K.; Vermote, E.F.; Yan, L.; Kumar, S.S.; Egorov, A. Characterization of Landsat-7 to Landsat-8 Reflective Wavelength and Normalized Difference Vegetation Index Continuity. Remote Sens. Environ. 2016, 185, 57–70. [Google Scholar] [CrossRef]
- Orusa, T.; Viani, A.; Cammareri, D.; Borgogno Mondino, E. A Google Earth Engine Algorithm to Map Phenological Metrics in Mountain Areas Worldwide with Landsat Collection and Sentinel-2. Geomatics 2023, 3, 221–238. [Google Scholar] [CrossRef]
- Son, N.T.; Chen, C.F.; Chen, C.R.; Minh, V.Q.; Trung, N.H. A Comparative Analysis of Multitemporal MODIS EVI and NDVI Data for Large-Scale Rice Yield Estimation. Agric. For. Meteorol. 2014, 197, 52–64. [Google Scholar] [CrossRef]
- Yan, E.; Wang, G.; Lin, H.; Xia, C.; Sun, H. Phenology-Based Classification of Vegetation Cover Types in Northeast China Using MODIS NDVI and EVI Time Series. Int. J. Remote Sens. 2015, 36, 489–512. [Google Scholar] [CrossRef]
- Delgado-Moreno, D.; Gao, Y. Forest Degradation Estimation Through Trend Analysis of Annual Time Series NDVI, NDMI and NDFI (2010–2020) Using Landsat Images. In Proceedings of the Advances in Geospatial Data Science; Tapia-McClung, R., Sánchez-Siordia, O., González-Zuccolotto, K., Carlos-Martínez, H., Eds.; Springer International Publishing: Cham, Germany, 2022; pp. 149–159. [Google Scholar]
- Hwang, Y.; Ryu, Y.; Qu, S. Expanding Vegetated Areas by Human Activities and Strengthening Vegetation Growth Concurrently Explain the Greening of Seoul. Landsc. Urban Plan. 2022, 227, 104518. [Google Scholar] [CrossRef]
- Obuchowicz, C.; Poussin, C.; Giuliani, G. Change in Observed Long-Term Greening across Switzerland – Evidence from a Three Decades NDVI Time-Series and Its Relationship with Climate and Land Cover Factors. Big Earth Data 2024, 8, 1–32. [Google Scholar] [CrossRef]
- R Development Core Team. R A Language and Environment for Statistical Computing, R Foundation for Statistical; R Foundation: Vienna, Austria, 2020. [Google Scholar]
- Gautam, S.; Brema, J. Spatio-Temporal Variation in the Concentration of Atmospheric Particulate Matter: A Study in Fourth Largest Urban Agglomeration in India. Environ. Technol. Innov. 2020, 17, 100546. [Google Scholar] [CrossRef]
- Liu, Y.; Zhao, W.; Zhang, L.; Li, X.; Peng, L.; Wang, Z.; Song, Y.; Jiao, L.; Wang, H. An Assessment Framework for Mapping the Air Purification Service of Vegetation at the Regional Scale. Forests 2024, 15, 391. [Google Scholar] [CrossRef]
- Qin, H.; Hong, B.; Huang, B.; Cui, X.; Zhang, T. How Dynamic Growth of Avenue Trees Affects Particulate Matter Dispersion: CFD Simulations in Street Canyons. Sustain. Cities Soc. 2020, 61, 102331. [Google Scholar] [CrossRef]
- Zhang, T.; Gong, W.; Wang, W.; Ji, Y.; Zhu, Z.; Huang, Y. Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI). Int. J. Environ. Res. Public Health 2016, 13, 1215. [Google Scholar] [CrossRef] [PubMed]
- Gao, Z.; Qin, Y.; Yang, X.; Chen, B. PM10 and PM2.5 Dust-Retention Capacity and Leaf Morphological Characteristics of Landscape Tree Species in the Northwest of Hebei Province. Atmosphere 2022, 13, 1657. [Google Scholar] [CrossRef]
- Khan, F.I.; Abbasi, S.A. Effective Design of Greenbelts Using Mathematical Models. J. Hazard. Mater. 2001, 81, 33–65. [Google Scholar] [CrossRef] [PubMed]
- Janhäll, S. Review on Urban Vegetation and Particle Air Pollution – Deposition and Dispersion. Atmos. Environ. 2015, 105, 130–137. [Google Scholar] [CrossRef]
- Zhang, B.; Jiao, L.; Xu, G.; Zhao, S.; Tang, X.; Zhou, Y.; Gong, C. Influences of Wind and Precipitation on Different-Sized Particulate Matter Concentrations (PM2.5, PM10, PM2.5–10). Meteorol. Atmos. Phys. 2018, 130, 383–392. [Google Scholar] [CrossRef]
- Xie, C.; Kan, L.; Guo, J.; Jin, S.; Li, Z.; Chen, D.; Li, X.; Che, S. A Dynamic Processes Study of PM Retention by Trees under Different Wind Conditions. Environ. Pollut. 2018, 233, 315–322. [Google Scholar] [CrossRef] [PubMed]
- Elliott, C.T.; Henderson, S.B.; Wan, V. Time Series Analysis of Fine Particulate Matter and Asthma Reliever Dispensations in Populations Affected by Forest Fires. Environ. Health 2013, 12, 11. [Google Scholar] [CrossRef] [PubMed]
- Rao, M.; George, L.A.; Rosenstiel, T.N.; Shandas, V.; Dinno, A. Assessing the Relationship among Urban Trees, Nitrogen Dioxide, and Respiratory Health. Environ. Pollut. 2014, 194, 96–104. [Google Scholar] [CrossRef]
- Cong, L.; Zhang, H.; Zhai, J.; Yan, G.; Wu, Y.; Wang, Y.; Ma, W.; Zhang, Z.; Chen, P. The Blocking Effect of Atmospheric Particles by Forest and Wetland at Different Air Quality Grades in Beijing China. Environ. Technol. 2020, 41, 2266–2276. [Google Scholar] [CrossRef]
- Keet, C.A.; Keller, J.P.; Peng, R.D. Long-Term Coarse Particulate Matter Exposure Is Associated with Asthma among Children in Medicaid. Am. J. Respir. Crit. Care Med. 2018, 197, 737–746. [Google Scholar] [CrossRef]
- Wu, J.; Zhong, T.; Zhu, Y.; Ge, D.; Lin, X.; Li, Q. Effects of Particulate Matter (PM) on Childhood Asthma Exacerbation and Control in Xiamen, China. BMC Pediatr. 2019, 19, 194. [Google Scholar] [CrossRef] [PubMed]
- Lavigne, É.; Talarico, R.; van Donkelaar, A.; Martin, R.V.; Stieb, D.M.; Crighton, E.; Weichenthal, S.; Smith-Doiron, M.; Burnett, R.T.; Chen, H. Fine Particulate Matter Concentration and Composition and the Incidence of Childhood Asthma. Environ. Int. 2021, 152, 106486. [Google Scholar] [CrossRef] [PubMed]
- Šulc, L.; Gregor, P.; Kalina, J.; Mikeš, O.; Janoš, T.; Čupr, P. City-Scale Assessment of Long-Term Air Quality Impacts on the Respiratory and Cardiovascular Health. Front. Public Health 2022, 10, 1006536. [Google Scholar] [CrossRef] [PubMed]
- Khreis, H.; Kelly, C.; Tate, J.; Parslow, R.; Lucas, K.; Nieuwenhuijsen, M. Exposure to Traffic-Related Air Pollution and Risk of Development of Childhood Asthma: A Systematic Review and Meta-Analysis. Environ. Int. 2017, 100, 1–31. [Google Scholar] [CrossRef] [PubMed]
- Abhijith, K.V.; Kumar, P.; Gallagher, J.; McNabola, A.; Baldauf, R.; Pilla, F.; Broderick, B.; Di Sabatino, S.; Pulvirenti, B. Air Pollution Abatement Performances of Green Infrastructure in Open Road and Built-up Street Canyon Environments—A Review. Atmos. Environ. 2017, 162, 71–86. [Google Scholar] [CrossRef]
- Zhang, B.; Xie, Z.; She, X.; Gao, J. Quantifying the Potential Contribution of Urban Forest to PM2.5 Removal in the City of Shanghai, China. Atmosphere 2021, 12, 1171. [Google Scholar] [CrossRef]
- Mandal, M.; Popek, R.; Przybysz, A.; Roy, A.; Das, S.; Sarkar, A. Breathing Fresh Air in the City: Implementing Avenue Trees as a Sustainable Solution to Reduce Particulate Pollution in Urban Agglomerations. Plants 2023, 12, 1545. [Google Scholar] [CrossRef] [PubMed]
- Li, S.; He, C.; Zhang, Y.; Wang, L.; Zhang, Y.; Wei, C.; Zhang, L. Effects of Different External Factors on Urban Roadside Plants for the Reduction of Airborne Fine Particulate Matters. Int. J. Phytoremediation 2023, 25, 1901–1912. [Google Scholar] [CrossRef] [PubMed]
- Wang, C.; Guo, M.; Jin, J.; Yang, Y.; Ren, Y.; Wang, Y.; Cao, J. Does the Spatial Pattern of Plants and Green Space Affect Air Pollutant Concentrations? Evidence from 37 Garden Cities in China. Plants 2022, 11, 2847. [Google Scholar] [CrossRef]
- Zhang, R.; Chen, G.; Yin, Z.; Zhang, Y.; Ma, K. Urban Greening Based on the Supply and Demand of Atmospheric PM2.5 Removal. Ecol. Indic. 2021, 126, 107696. [Google Scholar] [CrossRef]
Parameter | Estimate | Standard Error | p-Value | Significance |
---|---|---|---|---|
(a) ALL period | ||||
JJA_EVI | −81.4039 | 21.5256 | 0.0008 | *** |
ALL_P | −0.0109 | 0.0053 | 0.0498 | * |
DJF_W.S | −28.7971 | 12.3529 | 0.0275 | * |
JJA_W.S | −48.7253 | 11.9996 | 0.0004 | *** |
MAM_T | 5.7150 | 2.2229 | 0.0160 | * |
MAM_W.S | 19.1562 | 10.5761 | 0.0812 | + |
SON_T | 4.9698 | 1.9673 | 0.0177 | * |
SON_W.S | 37.7498 | 18.9809 | 0.0569 | + |
Age Group | Asthma Care Visits | Percentage (%) |
---|---|---|
0–5 | 164,107 | 34.21 |
6–11 | 81,691 | 17.03 |
12–17 | 21,932 | 4.57 |
18–44 | 84,795 | 17.68 |
45–64 | 75,801 | 15.80 |
65+ | 51,404 | 10.72 |
Correlation Coefficient | NDVI | EVI | PM10 (Residential Area) | |
---|---|---|---|---|
Asthma care visits | All age groups | −0.586 * | −0.410 | 0.782 *** |
For vulnerable populations (ages 0–5 and 65+) | −0.593 * | −0.420 | 0.781 *** | |
For vulnerable populations (ages 0–11 and 65+) | −0.597 * | −0.416 | 0.803 *** |
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Jeong, J.; Kim, C.; Choi, S.; Sou, H.-D.; Park, C.-R. Long-Term Greenness Effects of Urban Forests to Reduce PM10 Concentration: Does the Impact Benefit the Population Vulnerable to Asthma? Int. J. Environ. Res. Public Health 2025, 22, 167. https://doi.org/10.3390/ijerph22020167
Jeong J, Kim C, Choi S, Sou H-D, Park C-R. Long-Term Greenness Effects of Urban Forests to Reduce PM10 Concentration: Does the Impact Benefit the Population Vulnerable to Asthma? International Journal of Environmental Research and Public Health. 2025; 22(2):167. https://doi.org/10.3390/ijerph22020167
Chicago/Turabian StyleJeong, Jinsuk, Chaewan Kim, Sumin Choi, Hong-Duck Sou, and Chan-Ryul Park. 2025. "Long-Term Greenness Effects of Urban Forests to Reduce PM10 Concentration: Does the Impact Benefit the Population Vulnerable to Asthma?" International Journal of Environmental Research and Public Health 22, no. 2: 167. https://doi.org/10.3390/ijerph22020167
APA StyleJeong, J., Kim, C., Choi, S., Sou, H.-D., & Park, C.-R. (2025). Long-Term Greenness Effects of Urban Forests to Reduce PM10 Concentration: Does the Impact Benefit the Population Vulnerable to Asthma? International Journal of Environmental Research and Public Health, 22(2), 167. https://doi.org/10.3390/ijerph22020167