IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i3p662-d1094727.html
   My bibliography  Save this article

The Extension of Vegetable Production to High Altitudes Increases the Environmental Cost and Decreases Economic Benefits in Subtropical Regions

Author

Listed:
  • Tao Liang

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Weilin Tao

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Yan Wang

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Na Zhou

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Wei Hu

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Tao Zhang

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Dunxiu Liao

    (Chongqing Academy of Agricultural Sciences, Chongqing 401329, China)

  • Xinping Chen

    (College of Resources and Environment, Southwest University, Chongqing 400716, China)

  • Xiaozhong Wang

    (College of Resources and Environment, Southwest University, Chongqing 400716, China)

Abstract

Global warming has driven the expansion of cultivated land to high-altitude areas. Intensive vegetable production, which is generally considered to be a high economic value and high environmental risk system, has expanded greatly in high-altitude mountainous areas of China. However, the environmental cost of vegetable production in these areas is poorly understood. In this study, pepper production at low (traditional pepper production area) and high (newly expanded area) altitudes were investigated in Shizhu, a typical pepper crop area. The output and environmental cost at the two altitudes were identified. the influence of resource inputs, climate, and soil properties on pepper production was evaluated. There were obvious differences in output and environmental cost between the two altitudes. High-altitude pepper production achieved a 16.2% lower yield, and had a higher fertilizer input, resulting in a 22.3% lower net ecosystem economic benefit (NEEB), 23.0% higher nitrogen (N) footprint and 24.0% higher carbon (C) footprint compared to low-altitude farming. There is potential for environmental mitigation with both high- and low-altitude pepper production; Compared to average farmers, high-yield farmers groups reduced their N and C footprints by 16.9–24.8% and 18.3–25.2%, respectively, with 30.6–34.1% higher yield. A large increase in yield could also be achieved by increasing the top-dress fertilizer rate and decreasing the plant density. Importantly, high-altitude pepper production was achieved despite less advanced technology and inferior conditions (e.g., a poor road system and uneven fields). It provides a reference for the study of the environmental cost of other high-altitude regions or other crop systems at high-altitude areas.

Suggested Citation

  • Tao Liang & Weilin Tao & Yan Wang & Na Zhou & Wei Hu & Tao Zhang & Dunxiu Liao & Xinping Chen & Xiaozhong Wang, 2023. "The Extension of Vegetable Production to High Altitudes Increases the Environmental Cost and Decreases Economic Benefits in Subtropical Regions," Land, MDPI, vol. 12(3), pages 1-15, March.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:662-:d:1094727
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/3/662/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/3/662/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lihua Xie & Lingling Li & Junhong Xie & Jinbin Wang & Sumera Anwar & Changliang Du & Yongjie Zhou, 2022. "Substituting Inorganic Fertilizers with Organic Amendment Reduced Nitrous Oxide Emissions by Affecting Nitrifiers’ Microbial Community," Land, MDPI, vol. 11(10), pages 1-14, September.
    2. Małgorzata Holka & Jolanta Kowalska & Magdalena Jakubowska, 2022. "Reducing Carbon Footprint of Agriculture—Can Organic Farming Help to Mitigate Climate Change?," Agriculture, MDPI, vol. 12(9), pages 1-21, September.
    3. Qing Xiang & Huan Yu & Xiaoyu Xu & Hong Huang, 2022. "Temporal and Spatial Differentiation of Cultivated Land and Its Response to Climatic Factors in Complex Geomorphic Areas—A Case Study of Sichuan Province of China," Land, MDPI, vol. 11(2), pages 1-18, February.
    4. Shan, Linan & He, Yunfeng & Chen, Jie & Huang, Qian & Lian, Xu & Wang, Hongcai & Liu, Yili, 2015. "Nitrogen surface runoff losses from a Chinese cabbage field under different nitrogen treatments in the Taihu Lake Basin, China," Agricultural Water Management, Elsevier, vol. 159(C), pages 255-263.
    5. Pishgar-Komleh, Seyyed Hassan & Omid, Mahmoud & Heidari, Mohammad Davoud, 2013. "On the study of energy use and GHG (greenhouse gas) emissions in greenhouse cucumber production in Yazd province," Energy, Elsevier, vol. 59(C), pages 63-71.
    6. Pahlavan, Reza & Omid, Mahmoud & Akram, Asadollah, 2012. "Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production," Energy, Elsevier, vol. 37(1), pages 171-176.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Xiaozhong & Liu, Bin & Wu, Gang & Sun, Yixiang & Guo, Xisheng & Jin, Zhenghui & Xu, Weining & Zhao, Yongzhi & Zhang, Fusuo & Zou, Chunqin & Chen, Xinping, 2018. "Environmental costs and mitigation potential in plastic-greenhouse pepper production system in China: A life cycle assessment," Agricultural Systems, Elsevier, vol. 167(C), pages 186-194.
    2. Stanisław Bielski & Renata Marks-Bielska & Paweł Wiśniewski, 2022. "Investigation of Energy and Economic Balance and GHG Emissions in the Production of Different Cultivars of Buckwheat ( Fagopyrum esculentum Moench): A Case Study in Northeastern Poland," Energies, MDPI, vol. 16(1), pages 1-24, December.
    3. Šarauskis, Egidijus & Masilionytė, Laura & Juknevičius, Darius & Buragienė, Sidona & Kriaučiūnienė, Zita, 2019. "Energy use efficiency, GHG emissions, and cost-effectiveness of organic and sustainable fertilisation," Energy, Elsevier, vol. 172(C), pages 1151-1160.
    4. Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
    5. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    6. Han, Huanhao & Gao, Rong & Cui, Yuanlai & Gu, Shixiang, 2022. "A semi-empirical semi-process model of ammonia volatilization from paddy fields under different irrigation modes and urea application regimes," Agricultural Water Management, Elsevier, vol. 272(C).
    7. Sara Ilahi & Yongchang Wu & Muhammad Ahsan Ali Raza & Wenshan Wei & Muhammad Imran & Lyankhua Bayasgalankhuu, 2019. "Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    8. Yongqiang Zhang & Hao Sun & Maosheng Ge & Hang Zhao & Yifan Hu & Changyue Cui & Zhibin Wu, 2023. "Difference in Energy Input and Output in Agricultural Production under Surface Irrigation and Water-Saving Irrigation: A Case Study of Kiwi Fruit in Shaanxi," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    9. Shaikh, Mohammad A. & Kucukvar, Murat & Onat, Nuri Cihat & Kirkil, Gokhan, 2017. "A framework for water and carbon footprint analysis of national electricity production scenarios," Energy, Elsevier, vol. 139(C), pages 406-421.
    10. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Yousefi, Marziye & Movahedi, Mehran, 2013. "Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks," Energy, Elsevier, vol. 52(C), pages 333-338.
    11. Thongsouk Sompouviset & Yanting Ma & Eakkarin Sukkaew & Zhaoxia Zheng & Ai Zhang & Wei Zheng & Ziyan Li & Bingnian Zhai, 2023. "The Effects of Plastic Mulching Combined with Different Fertilizer Applications on Greenhouse Gas Emissions and Intensity, and Apple Yield in Northwestern China," Agriculture, MDPI, vol. 13(6), pages 1-23, June.
    12. Shulong Li & Zhizhang Wang, 2023. "The Effects of Agricultural Technology Progress on Agricultural Carbon Emission and Carbon Sink in China," Agriculture, MDPI, vol. 13(4), pages 1-21, March.
    13. Xiaobo Xue Romeiko & Zhijian Guo & Yulei Pang & Eun Kyung Lee & Xuesong Zhang, 2020. "Comparing Machine Learning Approaches for Predicting Spatially Explicit Life Cycle Global Warming and Eutrophication Impacts from Corn Production," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    14. Soltanali, Hamzeh & Nikkhah, Amin & Rohani, Abbas, 2017. "Energy audit of Iranian kiwifruit production using intelligent systems," Energy, Elsevier, vol. 139(C), pages 646-654.
    15. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein & Rajaeifar, Mohammad Ali, 2014. "Application of artificial neural networks for prediction of output energy and GHG emissions in potato production in Iran," Agricultural Systems, Elsevier, vol. 123(C), pages 120-127.
    16. Asgharipour, Mohammad Reza & Amiri, Zahra & Campbell, Daniel E., 2020. "Evaluation of the sustainability of four greenhouse vegetable production ecosystems based on an analysis of emergy and social characteristics”," Ecological Modelling, Elsevier, vol. 424(C).
    17. Jolanta Kowalska & Kinga Matysiak, 2023. "Advances in Crop Protection in Organic Farming System," Agriculture, MDPI, vol. 13(10), pages 1-5, October.
    18. Elsoragaby, Suha & Yahya, Azmi & Mahadi, Muhammad Razif & Nawi, Nazmi Mat & Mairghany, Modather, 2019. "Energy utilization in major crop cultivation," Energy, Elsevier, vol. 173(C), pages 1285-1303.
    19. Shaowen Xie & Fen Yang & Hanxiao Feng & Zhenzhen Yu & Xinghu Wei & Chengshuai Liu & Chaoyang Wei, 2022. "Potential to Reduce Chemical Fertilizer Application in Tea Plantations at Various Spatial Scales," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    20. Andrés Villarruel-Jaramillo & Josué F. Rosales-Pérez & Manuel Pérez-García & José M. Cardemil & Rodrigo Escobar, 2023. "Modeling and Performance Evaluation of Hybrid Solar Cooling Systems Driven by Photovoltaic and Solar Thermal Collectors—Case Study: Greenhouses of Andalusia," Energies, MDPI, vol. 16(13), pages 1-28, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:662-:d:1094727. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.