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Spatial Spillover Effects of Agricultural Agglomeration on Agricultural Non-Point Source Pollution in the Yangtze River Basin

Author

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  • Dayong Huang

    (Research Center for Economy of Upper Reaches of the Yangtse River, Chongqing Technology and Business University, Chongqing 400067, China)

  • Yangyang Zhu

    (Research Center for Economy of Upper Reaches of the Yangtse River, Chongqing Technology and Business University, Chongqing 400067, China)

  • Qiuyue Yu

    (Research Center for Economy of Upper Reaches of the Yangtse River, Chongqing Technology and Business University, Chongqing 400067, China)

Abstract

Agricultural non-point source pollution has become a matter of increasing public concern, and modern agriculture is gradually transforming into agglomeration, so it is important to study the influence of agricultural agglomeration on agricultural non-point source pollution to coordinate the relationship between resources, environment, and agricultural economic growth for guidance. With a focus on 89 prefecture-level cities in the main agricultural production areas of the Yangtze River basin in China, the authors analyzed the spatial and temporal evolution trends of agricultural agglomeration and agricultural non-point source pollution from 2000 to 2020 and then empirically tested the spatial spillover effects of agricultural agglomeration on agricultural non-point source pollution based on the spatial Durbin model (SDM). The results show that: (1) Between 2000 and 2020, agricultural agglomeration, in general, decreased from 0.364 to 0.342, and cities with agglomeration values in the third and fourth ranks are mainly located in the area north of the Yangtze River and have a tendency to extend southward over time. Agricultural non-point source pollution shows a general trend of increasing and then decreasing; its emissions rose from 404.319 × 10 4 tons in 2000 to 464.341 × 10 4 tons in 2015, and then fell to 373.338 × 10 4 tons in 2020, emissions in the third and fourth class of cities are mainly located in the middle and lower basin of the Yangtze River; High-value hots-pot areas of agricultural agglomeration, that is, areas with high spatial correlation, are mainly located in the upper and lower Yangtze River basin, and the areas with the higher spatial correlation of agricultural non-point source pollution are distributed in the upper, middle and lower basin of the Yangtze River. (2) The whole basin and upper basin exhibit positive and negative spatial spillover effects of agricultural non-point source pollution, Spillover effects values are 0.300 and −1.086, respectively; Agricultural agglomeration of the Whole Basin has a positive direct effect and a negative spatial spillover effect on agricultural non-point source pollution, the effect values are 0.846 and −0.520, respectively. (3) In addition to the core explanatory variable, agricultural production conditions and the share of livestock and poultry industry have a positive direct effect (the effect values are 0.109 and 0.048, respectively) and a negative spatial spillover effect (the effect values are −0.520 and −0.910, respectively) on agricultural non-point source pollution, while agricultural population size has a positive direct effect and spatial spillover effect, the effect values 0.099 and 0.452 respectively; The urbanization rate exacerbates the emission of agricultural non-point source pollution, the effect value is 0.110. while the industrial structure reduces the emission of agricultural non-point source pollution, the effect value is −0.438, but neither has a spatial spillover effect. The results imply that some effective policy measures, such as strengthening research on nutrient requirements and fertilization techniques for major crops, improving farmland infrastructure, scientifically planning and monitoring the scale of livestock farms, and strengthening inter-regional coordination and cooperation in the fight against pollution, should be taken to achieve ecological and sustainable objectives.

Suggested Citation

  • Dayong Huang & Yangyang Zhu & Qiuyue Yu, 2022. "Spatial Spillover Effects of Agricultural Agglomeration on Agricultural Non-Point Source Pollution in the Yangtze River Basin," Sustainability, MDPI, vol. 14(24), pages 1-26, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16390-:d:996634
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    References listed on IDEAS

    as
    1. Rachel Griffith & Stephen Redding & John Van Reenen, 2004. "Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 883-895, November.
    2. Chang, Chia-Lin & Oxley, Les, 2009. "Industrial agglomeration, geographic innovation and total factor productivity: The case of Taiwan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2787-2796.
    3. Haotian Zhang & Xiumei Sun & Xueyang Wang & Su Yan, 2022. "Winning the Blue Sky Defense War: Assessing Air Pollution Prevention and Control Action Based on Synthetic Control Method," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    4. Weinan Lu & Apurbo Sarkar & Mengyang Hou & Wenxin Liu & Xinyi Guo & Kai Zhao & Minjuan Zhao, 2022. "The Impacts of Urbanization to Improve Agriculture Water Use Efficiency—An Empirical Analysis Based on Spatial Perspective of Panel Data of 30 Provinces of China," Land, MDPI, vol. 11(1), pages 1-20, January.
    5. Getu Hailu & B. James Deaton, 2016. "Agglomeration Effects in Ontario’s Dairy Farming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1055-1073.
    6. Ruishi Si & Sitong Pan & Yuxin Yuan & Qian Lu & Shuxia Zhang, 2019. "Assessing the Impact of Environmental Regulation on Livestock Manure Waste Recycling: Empirical Evidence from Households in China," Sustainability, MDPI, vol. 11(20), pages 1-17, October.
    7. Guang Chen & Yue Deng & Apurbo Sarkar & Zhengbing Wang, 2022. "An Integrated Assessment of Different Types of Environment-Friendly Technological Progress and Their Spatial Spillover Effects in the Chinese Agriculture Sector," Agriculture, MDPI, vol. 12(7), pages 1-24, July.
    8. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    9. Xiangfei Xin & Fu Qin, 2011. "Decomposition of agricultural labor productivity growth and its regional disparity in China," China Agricultural Economic Review, Emerald Group Publishing, vol. 3(1), pages 92-100, January.
    10. Xiangfei Xin & Fu Qin, 2011. "Decomposition of agricultural labor productivity growth and its regional disparity in China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 3(1), pages 92-100, February.
    11. Ragnar Tveteras & George E. Battese, 2006. "Agglomeration Externalities, Productivity, And Technical Inefficiency," Journal of Regional Science, Wiley Blackwell, vol. 46(4), pages 605-625, October.
    12. Pei Xu & Zehu Jin & Huan Tang, 2022. "Influence Paths and Spillover Effects of Agricultural Agglomeration on Agricultural Green Development," Sustainability, MDPI, vol. 14(10), pages 1-16, May.
    13. Rulong Zhuang & Kena Mi & Zhangwei Feng, 2021. "Industrial Co-Agglomeration and Air Pollution Reduction: An Empirical Evidence Based on Provincial Panel Data," IJERPH, MDPI, vol. 18(22), pages 1-19, November.
    14. Zhou, Zhengyi & Zhang, Anming, 2021. "High-speed rail and industrial developments: Evidence from house prices and city-level GDP in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 98-113.
    15. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171, Elsevier.
    16. Maria Skorupka & Artur Nosalewicz, 2021. "Ammonia Volatilization from Fertilizer Urea—A New Challenge for Agriculture and Industry in View of Growing Global Demand for Food and Energy Crops," Agriculture, MDPI, vol. 11(9), pages 1-15, August.
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