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Long-Term Regional Environmental Risk Assessment and Future Scenario Projection at Ningbo, China Coupling the Impact of Sea Level Rise

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  • Yongjiu Feng

    (College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
    School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia)

  • Qianqian Yang

    (College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China)

  • Xiaohua Tong

    (College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China)

  • Jiafeng Wang

    (College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China)

  • Shurui Chen

    (College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China)

  • Zhenkun Lei

    (College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China)

  • Chen Gao

    (College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China)

Abstract

Regional environmental risk (RER) denotes potential threats to the natural environment, human health and socioeconomic development caused by specific risks. It is valuable to assess long-term RER in coastal areas with the increasing effects of global change. We proposed a new approach to assess coastal RER considering spatial factors using principal component analysis (PCA) and used a future land use simulation (FLUS) model to project future RER scenarios considering the impact of sea level rise (SLR). In our study, the RER status was classified in five levels as highest, high, medium, low and lowest. We evaluated the 30 m × 30 m gridded spatial pattern of the long-term RER at Ningbo of China by assessing its 1975–2015 history and projecting this to 2020–2050. Our results show that RER at Ningbo has increased substantially over the past 40 years and will slowly increase over the next 35 years. Ningbo’s city center and district centers are exposed to medium-to-highest RER, while the suburban areas are exposed to lowest-to-medium lower RER. Storm surges will lead to strong RER increases along the Ningbo coast, with the low-lying northern coast being more affected than the mountainous southern coast. RER at Ningbo is affected principally by the combined effects of increased human activity, rapid population growth, rapid industrialization, and unprecedented urbanization. This study provides early warnings to support practical regulation for disaster mitigation and environmental protection.

Suggested Citation

  • Yongjiu Feng & Qianqian Yang & Xiaohua Tong & Jiafeng Wang & Shurui Chen & Zhenkun Lei & Chen Gao, 2019. "Long-Term Regional Environmental Risk Assessment and Future Scenario Projection at Ningbo, China Coupling the Impact of Sea Level Rise," Sustainability, MDPI, vol. 11(6), pages 1-19, March.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1560-:d:213958
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    References listed on IDEAS

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    1. Yan Liu & Yongjiu Feng, 2016. "Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China," Sustainability, MDPI, vol. 8(10), pages 1-16, October.
    2. Thomas Wahl & Shaleen Jain & Jens Bender & Steven D. Meyers & Mark E. Luther, 2015. "Increasing risk of compound flooding from storm surge and rainfall for major US cities," Nature Climate Change, Nature, vol. 5(12), pages 1093-1097, December.
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    4. Qing Huang & Xinqi Zheng & Yecui Hu, 2015. "Analysis of Land-Use Emergy Indicators Based on Urban Metabolism: A Case Study for Beijing," Sustainability, MDPI, vol. 7(6), pages 1-19, June.
    5. Qing Zheng & Xuan Yang & Ke Wang & Lingyan Huang & Amir Reza Shahtahmassebi & Muye Gan & Melanie Valerie Weston, 2017. "Delimiting Urban Growth Boundary through Combining Land Suitability Evaluation and Cellular Automata," Sustainability, MDPI, vol. 9(12), pages 1-22, November.
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    Cited by:

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    3. Xiaoxia Su & Jing Wu & Pengshuo Li & Renjie Li & Penggen Cheng, 2022. "RSEI-Based Modeling of Ecological Security and Its Spatial Impacts on Soil Quality: A Case Study of Dayu, China," Sustainability, MDPI, vol. 14(8), pages 1-17, April.

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