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Influence of Road Patterns on PM 2.5 Concentrations and the Available Solutions: The Case of Beijing City, China

Author

Listed:
  • Fang Wang

    (Sino-German Joint Laboratory on Urbanization and Locality Research (UAL), College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

  • Yaoyao Peng

    (Sino-German Joint Laboratory on Urbanization and Locality Research (UAL), College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

  • Chunyan Jiang

    (Sino-German Joint Laboratory on Urbanization and Locality Research (UAL), College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

Abstract

With the increase in urbanization and energy consumption, PM 2.5 has become a major pollutant. This paper investigates the impact of road patterns on PM 2.5 pollution in Beijing, focusing on two questions: Do road patterns significantly affect PM 2.5 concentrations? How do road patterns affect PM 2.5 concentrations? A land-use regression model (LUR model) is used to quantify the associations between PM 2.5 concentrations, and road patterns, land-use patterns, and population density. Then, in the condition of excluding other factors closely correlated to PM 2.5 concentrations, based on the results of the regression model, further research is conducted to explore the relationship between PM 2.5 concentrations and the types, densities, and layouts of road networks, through the controlling variables method. The results are as follows: (1) the regression coefficient of road patterns is significantly higher than the water area, population density, and transport facilities, indicating that road patterns have an obvious influence on PM 2.5 concentrations; (2) under the same traffic carrying capacity, the layout of “a tight network of streets and small blocks” is superior to that of “a sparse network of streets and big blocks”; (3) the grade proportion of urban roads impacts the road patterns’ rationality, and a high percentage of branch roads and secondary roads could decrease PM 2.5 concentrations. These findings could provide a reference for the improvement of the traffic structure and air quality of Beijing.

Suggested Citation

  • Fang Wang & Yaoyao Peng & Chunyan Jiang, 2017. "Influence of Road Patterns on PM 2.5 Concentrations and the Available Solutions: The Case of Beijing City, China," Sustainability, MDPI, vol. 9(2), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:217-:d:89504
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    References listed on IDEAS

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    1. Lisa Schweitzer & Jiangping Zhou, 2010. "Neighborhood Air Quality, Respiratory Health, and Vulnerable Populations in Compact and Sprawled Regions," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 363-371.
    2. Int Panis, L. & Beckx, C. & Broekx, S. & De Vlieger, I. & Schrooten, L. & Degraeuwe, B. & Pelkmans, L., 2011. "PM, NOx and CO2 emission reductions from speed management policies in Europe," Transport Policy, Elsevier, vol. 18(1), pages 32-37, January.
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    Cited by:

    1. Xinghan Xu & Weijie Ren, 2019. "Application of a Hybrid Model Based on Echo State Network and Improved Particle Swarm Optimization in PM 2.5 Concentration Forecasting: A Case Study of Beijing, China," Sustainability, MDPI, vol. 11(11), pages 1-19, May.
    2. Bumseok Chun & Kwangyul Choi & Qisheng Pan, 2022. "Key determinants of particulate matter 2.5 concentrations in urban environments with scenario analysis," Environment and Planning B, , vol. 49(7), pages 1980-1994, September.
    3. Grazia Ghermandi & Sara Fabbi & Giorgio Veratti & Alessandro Bigi & Sergio Teggi, 2020. "Estimate of Secondary NO 2 Levels at Two Urban Traffic Sites Using Observations and Modelling," Sustainability, MDPI, vol. 12(19), pages 1-13, September.
    4. Yifei Wang & Xin Zhang & Hideki Nakamura, 2024. "Left-Turn Lane Capacity Estimation based on the Vehicle Yielding Maneuver Model to Pedestrians at Signalized Intersections," Sustainability, MDPI, vol. 16(6), pages 1-13, March.
    5. Hongyou Lu & Yunchan Zhu & Yu Qi & Jinliang Yu, 2018. "Do Urban Subway Openings Reduce PM 2.5 Concentrations? Evidence from China," Sustainability, MDPI, vol. 10(11), pages 1-24, November.

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