IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i2p311-d1044131.html
   My bibliography  Save this article

Effect of Agricultural Structure Adjustment on Spatio-Temporal Patterns of Net Anthropogenic Nitrogen Inputs in the Pearl River Basin from 1990 to 2019

Author

Listed:
  • Kai Xu

    (School of Chemical Engineering, Northeast Electric Power University, Jilin 132012, China
    Jiangsu Provincial Engineering Research Center for Intelligent Monitoring and Ecological Management of Pond and Reservoir Water Environment, Huaiyin Normal University, Huaian 223300, China)

  • Jiaogen Zhou

    (Jiangsu Provincial Engineering Research Center for Intelligent Monitoring and Ecological Management of Pond and Reservoir Water Environment, Huaiyin Normal University, Huaian 223300, China
    Current address: No.111 West Changjiang Road, Huai’an 223300, China)

  • Qiuliang Lei

    (Key Laboratory of Nonpoint Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Wenbiao Wu

    (Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Guangxiong Mao

    (Jiangsu Provincial Engineering Research Center for Intelligent Monitoring and Ecological Management of Pond and Reservoir Water Environment, Huaiyin Normal University, Huaian 223300, China)

Abstract

Worldwide urbanization has brought dramatic changes in agricultural structures, as well as serious agricultural non-point source pollutions of nitrogen and phosphorus. However, understanding the effect of agricultural structure adjustment on net anthropogenic nitrogen inputs (NANI) has been still limited. In this paper, statistical data from the agricultural statistical Yearbook, the National Economic and Social Development Statistical Bulletin were collected from 1990 to 2019 in the Pearl River Basin, China, and used to analyze the spatial and temporal patterns of NANI and its influencing factors. The results indicated that the agricultural structure adjustment has significantly influenced the spatial and temporal patterns of NANI in the last 30 years in the Pearl River Basin. The NANI decreased from 1990 to 2019, and had a spatial pattern of higher values in the upstream areas and lower in the downstream areas. In terms of the nitrogen input sources of NANI, in the economically developed regions downstream, nitrogen inputs are dominated by food/feed nitrogen, which accounted for an average of 49.6% of total nitrogen inputs. In upstream areas with relatively low economic development, fertilizer nitrogen accounted for an average of 54.9% of total nitrogen inputs. A novel nitrogen input source index of NANI, namely the ratio of agricultural nitrogen inputs to non-agricultural nitrogen inputs of NANI(ASNA), was also proposed to characterize the impact of the agricultural industry restructuring on NANI changes over time. Similar to the characteristics of NANI from 1990 to 2019, the ASNA showed a decreasing trend in the study area. Moreover, agricultural variables (agricultural land area, nitrogen fertilizer consumption and livestock farming density) tended to contribute less to the explained ASNA variances, while the contributions of the non-agricultural factors (population density and non-agricultural GDP) increased from 1990 to 2019. This indicated that the contribution of nitrogen inputs from agricultural sources to the NANI decreased while the contribution of nitrogen inputs from non-agricultural sources increased, with the shifts of agricultural sectors to the secondary and tertiary sectors in the Pearl River Basin. Our findings also suggest that differently regional targeting should be considered for the nitrogen pollution management in the Pearl River Basin, which focuses on the nitrogen pollution management of non-agricultural sources in the downstream areas, and but highlights agricultural nitrogen pollution management in the upstream areas.

Suggested Citation

  • Kai Xu & Jiaogen Zhou & Qiuliang Lei & Wenbiao Wu & Guangxiong Mao, 2023. "Effect of Agricultural Structure Adjustment on Spatio-Temporal Patterns of Net Anthropogenic Nitrogen Inputs in the Pearl River Basin from 1990 to 2019," Land, MDPI, vol. 12(2), pages 1-18, January.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:2:p:311-:d:1044131
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/2/311/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/2/311/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xin Zhou & Chunqing Chen & Fajin Chen & Zhiguang Song, 2021. "Changes in net anthropogenic nitrogen input in the watershed region of Zhanjiang Bay in south China from 1978 to 2018," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 17201-17219, December.
    2. Muhammad, Sulaman & Pan, Yanchun & Agha, Mujtaba Hassan & Umar, Muhammad & Chen, Siyuan, 2022. "Industrial structure, energy intensity and environmental efficiency across developed and developing economies: The intermediary role of primary, secondary and tertiary industry," Energy, Elsevier, vol. 247(C).
    3. Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad & Sahrbacher, Christoph, 2008. "Does structure matter? The impact of switching the agricultural policy regime on farm structures," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 431-444, August.
    4. Yongsheng Wang & Yan Chen & Zhengjia Liu, 2020. "Agricultural Structure Adjustment and Rural Poverty Alleviation in the Agro-Pastoral Transition Zone of Northern China: A Case Study of Yulin City," Sustainability, MDPI, vol. 12(10), pages 1-13, May.
    5. Xiaobin Dong & Yufang Zhang & Weijia Cui & Bin Xun & Baohua Yu & Sergio Ulgiati & Xinshi Zhang, 2011. "Emergy-Based Adjustment of the Agricultural Structure in a Low-Carbon Economy in Manas County of China," Energies, MDPI, vol. 4(9), pages 1-15, September.
    6. Li, Wenchao & Guo, Shufang & Liu, Hongbin & Zhai, Limei & Wang, Hongyuan & Lei, Qiuliang, 2018. "Comprehensive environmental impacts of fertilizer application vary among different crops: Implications for the adjustment of agricultural structure aimed to reduce fertilizer use," Agricultural Water Management, Elsevier, vol. 210(C), pages 1-10.
    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. Li, Tianyu & Yue, Xiao-Guang & Waheed, Humayun & Yıldırım, Bilal, 2023. "Can energy efficiency and natural resources foster economic growth? Evidence from BRICS countries," Resources Policy, Elsevier, vol. 83(C).
    2. Salman, Muhammad & Long, Xingle & Wang, Guimei & Zha, Donglan, 2022. "Paris climate agreement and global environmental efficiency: New evidence from fuzzy regression discontinuity design," Energy Policy, Elsevier, vol. 168(C).
    3. Fang, Shuya & Fang, Wei, 2023. "How fiscal decentralization and trade diversification influence sustainable development: Moderating role of resources dependency," Resources Policy, Elsevier, vol. 84(C).
    4. Andrius Kazukauskas & Carol Newman & Johannes Sauer, 2014. "The impact of decoupled subsidies on productivity in agriculture: a cross-country analysis using microdata," Agricultural Economics, International Association of Agricultural Economists, vol. 45(3), pages 327-336, May.
    5. Editors: & Jones, J. & O’Hara, J. K., 2023. "Marginal Abatement Cost Curves for Greenhouse Gas Mitigation on U.S. Farms and Ranches (Updated)," USDA Miscellaneous 349144, United States Department of Agriculture.
    6. Lili Yang & Ning Ma, 2022. "Empirical Study on the Influence of Urban Environmental Industrial Structure Optimization on Ecological Landscape Greening Construction," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    7. Robert Huber & Christian Häberli, 2010. "A ‘beyond WTO’ scenario for Swiss agriculture: Consequences for income generation and the provision of public goods," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 3(1), pages 361-400.
    8. Jordan Hristov & Yann Clough & Ullrika Sahlin & Henrik G. Smith & Martin Stjernman & Ola Olsson & Amanda Sahrbacher & Mark V. Brady, 2020. "Impacts of the EU's Common Agricultural Policy “Greening” Reform on Agricultural Development, Biodiversity, and Ecosystem Services," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(4), pages 716-738, December.
    9. Bert, Federico E. & Rovere, Santiago L. & Macal, Charles M. & North, Michael J. & Podestá, Guillermo P., 2014. "Lessons from a comprehensive validation of an agent based-model: The experience of the Pampas Model of Argentinean agricultural systems," Ecological Modelling, Elsevier, vol. 273(C), pages 284-298.
    10. Won Sil Choi & Sang Hyeon Lee, 2023. "Market Structure Analysis Using Changes in the Number of Farms and Farm Income: In the Case of Korea," Agriculture, MDPI, vol. 13(7), pages 1-20, July.
    11. Möhring, A. & Zimmermann, A. & Mack, G. & Mann, S. & Ferjani, A. & Gennaio, M.-P., 2010. "Multidisziplinäre Agentendefinitionen für Optimierungsmodelle," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 45, March.
    12. Happe, Kathrin & Kellermann, Konrad, 2007. "DIESE MODELLE SIND ZU KOMPLEX!-ODER DOCH NICHT?: EXPERIMENTELLES DESIGN UND METAMODELLIERUNG ALS MOGLICHER WEG, DAS KOMMUNIKATIONSPROBLEM AGENTENBASIERTER MODELLE IN DER POLITIKANALYSE ZU LOSEN (Germa," 47th Annual Conference, Weihenstephan, Germany, September 26-28, 2007 7613, German Association of Agricultural Economists (GEWISOLA).
    13. Rui Wang & Shilong Li, 2024. "Research on the influence mechanism of fiscal and tax policy on green economic transition: from the perspective of industrial structure conduction effect," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(6), pages 16129-16148, June.
    14. Marius Eisele & Christian Troost & Thomas Berger, 2021. "How Bayesian Are Farmers When Making Climate Adaptation Decisions? A Computer Laboratory Experiment for Parameterising Models of Expectation Formation," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 805-828, September.
    15. Qian Li & Jianping Wang & Guohong Gao & Yingying Lv & Zhiyu Li & Guanglan Chen, 2023. "Spatial Analysis of Tertiary Industry Evolution Based on Gravity Model: A Case of Central Plains Economic Region in China," Sustainability, MDPI, vol. 15(10), pages 1-22, May.
    16. Hugo Storm & Klaus Mittenzwei & Thomas Heckelei, 2015. "Direct Payments, Spatial Competition, and Farm Survival in Norway," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(4), pages 1192-1205.
    17. Wang, Zihan & Chen, Xi & Ullah, Sami & Abbas, Shujaat, 2023. "Resource curse or blessing? Evaluating the role of natural resource, social globalization, and environmental sustainability in China," Resources Policy, Elsevier, vol. 85(PA).
    18. Zhao, Jun & Dong, Kangyin & Dong, Xiucheng, 2024. "How does energy poverty eradication affect global carbon neutrality?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    19. Du, Yuqiu & Wang, Wendi, 2023. "The role of green financing, agriculture development, geopolitical risk, and natural resource on environmental pollution in China," Resources Policy, Elsevier, vol. 82(C).
    20. Ping Han & Ziyu Zhou, 2023. "The Harmonious Relationship between Energy Utilization Efficiency and Industrial Structure Development under Carbon Emission Constraints: Measurement, Quantification, and Identification," Sustainability, MDPI, vol. 15(14), pages 1-21, July.

    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:2:p:311-:d:1044131. 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.