Assessment of NO2 Purification by Urban Forests Based on the i-Tree Eco Model: Case Study in Beijing, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Site Description
2.2. Data Sources
2.3. i-Tree Eco Deposition Model
2.4. NO2 Purification Deficit
2.5. Statistical Analysis
3. Results
3.1. NO2 Absorption Trends by Urban Forests during the Period of 2014–2019
3.2. NO2 Absorption Gradient between Urban Districts and Suburban Districts
3.3. Contribution of NO2 Absorption by Urban Vegetation to N Pollution Mitigation
4. Discussion
4.1. Spatial Distribution Pattern of NO2 Absorption by Urban Forests in 16 Districts
4.2. Contribution of Urban Forests to Air Quality Improvement
4.3. Uncertainties and Limitations
4.4. Suggestions for Urban Forests Management
- There is a significant imbalance in the distribution of NO2 purification services by urban forests in Beijing. Although it is difficult to increase the area of urban forests in the central area of the city, the purification capacity of vegetation in urban forests can be improved by more natural management approaches, including reducing tree canopy pruning to increase the total leaf area of urban forests, and increasing the percentage of tree species with stronger NO2 absorption used for roadside tree planting in urban areas, such as S. japonica [54]. The forest cover should be maintained in urban areas and expanded in suburban areas to contribute to Beijing’s capacity to achieve “carbon sequestration”, as well as advancing “nitrogen sequestration” [55,56].
- Urban forests can absorb atmospheric NO2 and have a significant “nitrogen emission neutralization” effect. We found that urban forests can absorb 9.9–15.8% of total NOx emissions, and in some districts, the absorption amount of NO2 is higher than the total emissions. Plants can absorb NO2 into their nitrogen pool to reduce the chance of NO2 photolysis [8], thus reducing the potential of ozone precursor production [57], which are the emerging main air pollutants in most Chinese cities [58]. This suggests that near-ground ozone pollution can be addressed by enhancing NO2 reduction and improving the “nitrogen emission neutralization” effect of urban forests.
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Zhao, X.; Zhou, W.; Han, L. Human activities and urban air pollution in Chinese mega city: An insight of ozone weekend effect in Beijing. Phys. Chem. Earth 2019, 110, 109–116. [Google Scholar] [CrossRef]
- Gao, W.; Tie, X.; Xu, J.; Huang, R.; Mao, X.; Zhou, G.; Chang, L. Long-term trend of O-3 in a mega City (Shanghai), China: Characteristics, causes, and interactions with precursors. Sci. Total Environ. 2017, 603, 425–433. [Google Scholar] [CrossRef] [PubMed]
- Chan, C.K.; Yao, X. Air pollution in mega cities in China. Atmos. Environ. 2008, 42, 1–42. [Google Scholar] [CrossRef]
- Li, C.; Hammer, M.S.; Zheng, B.; Cohen, R.C. Accelerated reduction of air pollutants in China, 2017–2020. Sci. Total Environ. 2022, 803, 150011. [Google Scholar] [CrossRef] [PubMed]
- Wang, G.; Deng, J.; Zhang, Y.; Zhang, Q.; Duan, L.; Jiang, J.; Hao, J. Air pollutant emissions from coal-fired power plants in China over the past two decades. Sci. Total Environ. 2020, 741, 140326. [Google Scholar] [CrossRef] [PubMed]
- Xu, M.; Sbihi, H.; Pan, X.; Brauer, M. Local variation of PM2.5 and NO2 concentrations within metropolitan Beijing. Atmos. Environ. 2019, 200, 254–263. [Google Scholar] [CrossRef]
- Calfapietra, C.; Fares, S.; Manes, F.; Morani, A.; Sgrigna, G.; Loreto, F. Role of Biogenic Volatile Organic Compounds (BVOC) emitted by urban trees on ozone concentration in cities: A review. Environ. Pollut. 2013, 183, 71–80. [Google Scholar] [CrossRef]
- Tan, Z.; Lu, K.; Dong, H.; Hu, M.; Li, X.; Liu, Y.; Lu, S.; Shao, M.; Su, R.; Wang, H.; et al. Explicit diagnosis of the local ozone production rate and the ozone-NOx-VOC sensitivities. Sci. Bull. 2018, 63, 1067–1076. [Google Scholar] [CrossRef] [Green Version]
- 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]
- Xu, L.; He, N.; Yu, G. Nitrogen storage in China’s terrestrial ecosystems. Sci. Total Environ. 2020, 709, 136201. [Google Scholar] [CrossRef]
- Baró, F.; Haase, D.; Gómez-Baggethun, E.; Frantzeskaki, N. Mismatches between ecosystem services supply and demand in urban areas: A quantitative assessment in five European cities. Ecol. Indic. 2015, 55, 146–158. [Google Scholar] [CrossRef] [Green Version]
- Song, C.; Lee, W.-K.; Choi, H.-A.; Kim, J.; Jeon, S.W.; Kim, J.S. Spatial assessment of ecosystem functions and services for air purification of forests in South Korea. Environ. Sci. Policy 2016, 63, 27–34. [Google Scholar] [CrossRef]
- Manes, F.; Marando, F.; Capotorti, G.; Blasi, C.; Salvatori, E.; Fusaro, L.; Ciancarella, L.; Mircea, M.; Marchetti, M.; Chirici, G.; et al. Regulating Ecosystem Services of forests in ten Italian Metropolitan Cities: Air quality improvement by PM10 and O3 removal. Ecol. Indic. 2016, 67, 425–440. [Google Scholar] [CrossRef]
- Delaria, E.R.; Place, B.K.; Liu, A.X.; Cohen, R.C. Laboratory measurements of stomatal NO2 deposition to native California trees and the role of forests in the NOx cycle. Atmos. Chem. Phys. 2020, 20, 14023–14041. [Google Scholar] [CrossRef]
- Chen, C.; Wang, Y.; Zhang, Y.; Liu, C.; Lun, X.; Mu, Y.; Zhang, C.; Liu, J. Characteristics and influence factors of NO2 exchange flux between the atmosphere and P. nigra. J. Environ. Sci. 2019, 84, 155–165. [Google Scholar] [CrossRef]
- Escobedo, F.J.; Nowak, D.J. Spatial heterogeneity and air pollution removal by an urban forest. Landsc. Urban Plan. 2009, 90, 102–110. [Google Scholar] [CrossRef]
- Guidolotti, G.; Salviato, M.; Calfapietra, C. Comparing estimates of EMEP MSC-W and UFORE models in air pollutant reduction by urban trees. Environ. Sci. Pollut. Res. 2016, 23, 19541–19550. [Google Scholar] [CrossRef]
- Currie, B.A.; Bass, B. Estimates of air pollution mitigation with green plants and green roofs using the UFORE model. Urban Ecosyst. 2008, 11, 409–422. [Google Scholar] [CrossRef]
- 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]
- Parsa, V.A.; Salehi, E.; Yavari, A.R.; van Bodegom, P.M. Analyzing temporal changes in urban forest structure and the effect on air quality improvement. Sustain. Cities Soc. 2019, 48, 101548. [Google Scholar] [CrossRef]
- Hirabayashi, S.; Nowak, D.J. Comprehensive national database of tree effects on air quality and human health in the United States. Environ. Pollut. 2016, 215, 48–57. [Google Scholar] [CrossRef] [PubMed]
- Xian, C.; Ouyang, Z.; Lu, F.; Xiao, Y.; Li, Y. Quantitative evaluation of reactive nitrogen emissions with urbanization: A case study in Beijing megacity, China. Environ. Sci. Pollut. Res. 2016, 23, 17689–17701. [Google Scholar] [CrossRef] [PubMed]
- Yang, J.; McBride, J.; Zhou, J.; Sun, Z. The urban forest in Beijing and its role in air pollution reduction. Urban For. Urban Green. 2005, 3, 65–78. [Google Scholar] [CrossRef]
- Beijing Municipal Ecology and Environment Bureau. Annual Report of Beijing Ecological Environment Statement in 2019; China Statistics Press: Beijing, China, 2019. [Google Scholar]
- Beijing Municipal Bureau Statistics. Beijing Statistical Yearbook; China Statistics Press: Beijing, China, 2020. [Google Scholar]
- National Bureau of Statistics of China. China Statistical Yearbook; China Statistics Press: Beijing, China, 2020. [Google Scholar]
- Zhang, Z.; Guan, H.; Xiao, H.; Liang, Y.; Zheng, N.; Luo, L.; Liu, C.; Fang, X.; Xiao, H. Oxidation and sources of atmospheric NOx during winter in Beijing based on δ18O-δ15N space of particulate nitrate. Environ. Pollut. 2021, 276, 116708. [Google Scholar] [CrossRef]
- Su, Y.; Gong, C.; Cui, B.; Guo, P.; Ouyang, Z.; Wang, X. Spatial Heterogeneity of Plant Diversity within and between Neighborhoods and Its Implications for a Plant Diversity Survey in Urban Areas. Forests 2021, 12, 416. [Google Scholar] [CrossRef]
- Su, Y.; Cui, B.; Luo, Y.; Wang, J.; Wang, X.; Ouyang, Z.; Wang, X. Leaf Functional Traits Vary in Urban Environments: Influences of Leaf Age, Land-Use Type, and Urban–Rural Gradient. Front. Ecol. Evol. 2021, 892, 681959. [Google Scholar] [CrossRef]
- Morani, A.; Nowak, D.; Hirabayashi, S.; Guidolotti, G.; Medori, M.; Muzzini, V.; Fares, S.; Mugnozza, G.S.; Calfapietra, C. Comparing i-Tree modeled ozone deposition with field measurements in a periurban Mediterranean forest. Environ. Pollut. 2014, 195, 202–209. [Google Scholar] [CrossRef]
- Emmerichs, T.; Kerkweg, A.; Ouwersloot, H.; Fares, S.; Mammarella, I.; Taraborrelli, D. A revised dry deposition scheme for land-atmosphere exchange of trace gases in ECHAM/MESSy v2.54. Geosci. Model Dev. 2021, 14, 495–519. [Google Scholar] [CrossRef]
- Zhang, L.; Brook, J.R.; Vet, R. A revised parameterization for gaseous dry deposition in air-quality models. Atmos. Chem. Phys. 2003, 3, 2067–2082. [Google Scholar] [CrossRef] [Green Version]
- De Jalon, S.G.; Burgess, P.J.; Yuste, J.C.; Moreno, G.; Graves, A.; Palma, J.H.N.; Crous-Duran, J.; Kay, S.; Chiabai, A. Dry deposition of air pollutants on trees at regional scale: A case study in the Basque Country. Agric. For. Meteorol. 2019, 278, 107648. [Google Scholar] [CrossRef]
- Zhang, L.M.; Moran, M.D.; Makar, P.A.; Brook, J.R.; Gong, S.L. Modelling gaseous dry deposition in AURAMS: A unified regional air-quality modelling system. Atmos. Environ. 2002, 36, 537–560. [Google Scholar] [CrossRef]
- Wu, J.; Wang, Y.; Qiu, S.; Peng, J. Using the modified i-Tree Eco model to quantify air pollution removal by urban vegetation. Sci. Total Environ. 2019, 688, 673–683. [Google Scholar] [CrossRef] [PubMed]
- Fang, K. Footprint family: Concept, classification, theoretical framework and integrated pattern. Acta Ecol. Sin. 2015, 35, 1647–1659. [Google Scholar]
- Feng, D.; Zhao, G. Footprint assessments on organic farming to improve ecological safety in the water source areas of the South-to-North Water Diversion project. J. Clean. Prod. 2020, 254, 120130. [Google Scholar] [CrossRef]
- Garcia-Palacios, P.; Gross, N.; Gaitan, J.; Maestre, F.T. Climate mediates the biodiversity-ecosystem stability relationship globally. Proc. Natl. Acad. Sci. USA 2018, 115, 8400–8405. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2020. [Google Scholar]
- Bartoń, K. MuMIn: Multi-Model Inference, R Package Version 1.10.5. 2014. Available online: https://r-forge.r-project.org/projects/mumin/ (accessed on 18 January 2022).
- Oksanen, J.; Blanchet, F.G.; Friendly, M.; Kindt, R.; Legendre, P.; McGlinn, D.; Minchin, P.R.; O’Hara, R.B.; Simpson, G.L.; Solymos, P.; et al. Vegan: Community Ecology Package. 2020. Available online: https://cran.ism.ac.jp/web/packages/vegan/vegan.pdf (accessed on 18 January 2022).
- Wickham, H. Ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2016. [Google Scholar]
- Tennekes, M. Tmap: Thematic Maps in R. J. Stat. Softw. 2018, 84, 1–39. [Google Scholar] [CrossRef] [Green Version]
- Cabaraban, M.T.I.; Kroll, C.N.; Hirabayashi, S.; Nowak, D.J. Modeling of air pollutant removal by dry deposition to urban trees using a WRF/CMAQ/i-Tree Eco coupled system. Environ. Pollut. 2013, 176, 123–133. [Google Scholar] [CrossRef]
- Qian, Y.G.; Zhou, W.Q.; Nytch, C.J.; Han, L.J.; Li, Z.Q. A new index to differentiate tree and grass based on high resolution image and object-based methods. Urban For. Urban Green. 2020, 53, 126661. [Google Scholar] [CrossRef]
- Li, F.; Zheng, W.; Wang, Y.; Liang, J.; Xie, S.; Guo, S.; Li, X.; Yu, C. Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective. Forests 2019, 10, 333. [Google Scholar] [CrossRef] [Green Version]
- Tang, H.; Liu, W.; Yun, W. Spatiotemporal Dynamics of Green Spaces in the Beijing-Tianjin-Hebei Region in the Past 20 Years. Sustainability 2018, 10, 2949. [Google Scholar] [CrossRef] [Green Version]
- Shi, Y.; Yang, G.; Feng, H.; Li, W.; Wang, R. Remote sensing of seasonal variability monitoring of forest LAI over mountain areas in Beijing. Trans. Chin. Soc. Agric. Eng. 2012, 28, 133–139. [Google Scholar]
- Bottalico, F.; Travaglini, D.; Chirici, G.; Garfì, V.; Giannetti, F.; De Marco, A.; Fares, S.; Marchetti, M.; Nocentini, S.; Paoletti, E.; et al. A spatially-explicit method to assess the dry deposition of air pollution by urban forests in the city of Florence, Italy. Urban For. Urban Green. 2017, 27, 221–234. [Google Scholar] [CrossRef]
- Gong, C.; Xian, C.; Cui, B.; He, G.; Wei, M.; Zhang, Z.; Ouyang, Z. Estimating NOx removal capacity of urban trees using stable isotope method: A case study of Beijing, China. Environ. Pollut. 2021, 290, 118004. [Google Scholar] [CrossRef] [PubMed]
- Xian, C.; Zhang, X.; Zhang, J.; Fan, Y.; Zheng, H.; Salzman, J.; Ouyang, Z. Recent patterns of anthropogenic reactive nitrogen emissions with urbanization in China: Dynamics, major problems, and potential solutions. Sci. Total Environ. 2019, 656, 1071–1081. [Google Scholar] [CrossRef]
- Wesely, M.L.; Hicks, B.B. A review of the current status of knowledge on dry deposition. Atmos. Environ. 2000, 34, 2261–2282. [Google Scholar] [CrossRef]
- Lin, J.; Kroll, C.N.; Nowak, D.J.; Greenfield, E.J. A review of urban forest modeling: Implications for management and future research. Urban For. Urban Green. 2019, 43, 126366. [Google Scholar] [CrossRef]
- Gong, C.; Xian, C.; Su, Y.; Ouyang, Z. Estimating the nitrogen source apportionment of Sophora japonica in roadside green spaces using stable isotope. Sci. Total Environ. 2019, 689, 1348–1357. [Google Scholar] [CrossRef]
- Liao, L.; Zhao, C.; Li, X.; Qin, J. Towards low carbon development: The role of forest city constructions in China. Ecol. Indic. 2021, 131, 108199. [Google Scholar] [CrossRef]
- Speak, A.; Escobedo, F.J.; Russo, A.; Zerbe, S. Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach. J. Clean. Prod. 2020, 256, 120420. [Google Scholar] [CrossRef]
- Prendez, M.; Carvajal, V.; Corada, K.; Morales, J.; Alarcon, F.; Peralta, H. Biogenic volatile organic compounds from the urban forest of the Metropolitan Region, Chile. Environ. Pollut. 2013, 183, 143–150. [Google Scholar] [CrossRef]
- Lu, X.; Zhang, L.; Chen, Y.; Zhou, M.; Zheng, B.; Li, K.; Liu, Y.; Lin, J.; Fu, T.-M.; Zhang, Q. Exploring 2016–2017 surface ozone pollution over China: Source contributions and meteorological influences. Atmos. Chem. Phys. 2019, 19, 8339–8361. [Google Scholar] [CrossRef] [Green Version]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gong, C.; Xian, C.; Ouyang, Z. Assessment of NO2 Purification by Urban Forests Based on the i-Tree Eco Model: Case Study in Beijing, China. Forests 2022, 13, 369. https://doi.org/10.3390/f13030369
Gong C, Xian C, Ouyang Z. Assessment of NO2 Purification by Urban Forests Based on the i-Tree Eco Model: Case Study in Beijing, China. Forests. 2022; 13(3):369. https://doi.org/10.3390/f13030369
Chicago/Turabian StyleGong, Cheng, Chaofan Xian, and Zhiyun Ouyang. 2022. "Assessment of NO2 Purification by Urban Forests Based on the i-Tree Eco Model: Case Study in Beijing, China" Forests 13, no. 3: 369. https://doi.org/10.3390/f13030369
APA StyleGong, C., Xian, C., & Ouyang, Z. (2022). Assessment of NO2 Purification by Urban Forests Based on the i-Tree Eco Model: Case Study in Beijing, China. Forests, 13(3), 369. https://doi.org/10.3390/f13030369