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An Approach to Evaluating Light Pollution in Residential Zones: A Case Study of Beijing

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  • Xueting Jin

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China
    School of Geography, Beijing Normal University, Beijing 100875, China
    School of Geographic Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA)

  • Yu Li

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China
    School of Geography, Beijing Normal University, Beijing 100875, China)

  • Jinzhou Zhang

    (School of Geographic Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA)

  • Ji Zheng

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China)

  • Huiping Liu

    (School of Geographic Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA)

Abstract

Outdoor lighting is becoming increasingly widespread, and residents are suffering from serious light pollution as a result. Residents’ awareness of their rights to protection has gradually increased. However, due to the sometimes-inaccessible nature of residential vertical light incidence intensity data and the high cost of obtaining specific measurements, there is no appropriate hierarchic compensation for residents suffering from different degrees of light pollution. It is therefore important to measure light pollution levels and their damage at the neighborhood scale to provide residents with basic materials for proper protection and to create more politically-suitable solutions. This article presents a light pollution assessment method that is easy to perform, is low-cost and has a short data-processing cycle. This method can be used to monitor residential zone light pollution in other cities. We chose three open areas to test the spatial variation pattern of light intensity. The results are in accordance with spatial interpolation patterns and can be fit, with high precision, using the inverse distance weighted interpolation (IDW) method. This approach can also be used in three dimensions to quantitatively evaluate the distribution of light intensity. We use a mixed-use zone in Beijing known as The Place as our case study area. The vertical illumination at the windows of residential buildings ranges from 2 lux to 23 lux; the illumination in some areas is far higher than the value recommended by CIE. Such severe light pollution can seriously interfere with people's daily lives and has a serious influence on their rest and health. The results of this survey will serve as an important database to assess whether the planning of night-time lighting is scientific, and it will help protect the rights of residents and establish distinguished compensation mechanisms for light pollution.

Suggested Citation

  • Xueting Jin & Yu Li & Jinzhou Zhang & Ji Zheng & Huiping Liu, 2017. "An Approach to Evaluating Light Pollution in Residential Zones: A Case Study of Beijing," Sustainability, MDPI, vol. 9(4), pages 1-12, April.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:652-:d:96214
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    References listed on IDEAS

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    1. Gallaway, Terrel & Olsen, Reed N. & Mitchell, David M., 2010. "The economics of global light pollution," Ecological Economics, Elsevier, vol. 69(3), pages 658-665, January.
    2. Terrel Gallaway, 2010. "On Light Pollution, Passive Pleasures, and the Instrumental Value of Beauty," Journal of Economic Issues, Taylor & Francis Journals, vol. 44(1), pages 71-88.
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    Cited by:

    1. Mintai Kim & SangHyun Cheon & Youngeun Kang, 2019. "Use of Electroencephalography (EEG) for the Analysis of Emotional Perception and Fear to Nightscapes," Sustainability, MDPI, vol. 11(1), pages 1-15, January.
    2. Jiayi Li & Yongming Xu & Weiping Cui & Meng Ji & Boyang Su & Yuyang Wu & Jing Wang, 2020. "Investigation of Nighttime Light Pollution in Nanjing, China by Mapping Illuminance from Field Observations and Luojia 1-01 Imagery," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    3. Ping-Huan Kuo & Hsin-Chuan Chen & Chiou-Jye Huang, 2018. "Solar Radiation Estimation Algorithm and Field Verification in Taiwan," Energies, MDPI, vol. 11(6), pages 1-12, May.

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