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Environmental Science and Pollution Research

, Volume 25, Issue 24, pp 24488–24499 | Cite as

Existing agricultural ecosystem in China leads to environmental pollution: an econometric approach

  • Lei Hongdou
  • Li ShipingEmail author
  • Li Hao
Research Article

Abstract

Sustainable agriculture ensures food security and prevents starvation. However, the need to meet the increasing food demands of the growing population has led to poor and unsustainable agricultural practices, which promote environmental degradation. Given the contributions of agricultural ecosystems to environmental pollution, we investigated the impact of the agricultural ecosystem on environmental pollution in China using time series data from 1960 to 2014. We employed several methods for econometric analysis including the unit root test, Johansen test of cointegration, Granger causality test, and vector error correction model. Evidence based on the long-run elasticity indicates that a 1% increase in the emissions of carbon dioxide (CO2) equivalent to nitrous oxide from synthetic fertilizers will increase the emissions of CO2 by 1.52% in the long run. Similarly, a 1% increase in the area of harvested rice paddy, cereal production, biomass of burned crop residues, and agricultural GDP will increase the carbon dioxide emissions by 0.85, 0.63, 0.37, and 0.22%, respectively. The estimated results indicate that there are long-term equilibrium relationships among the selected variables considered for the agricultural ecosystem and carbon dioxide emissions. In particular, we identified bidirectional causal associations between CO2 emissions, biomass of burned crop residues, and cereal production.

Graphical abstract

Keywords

China agricultural ecosystem CO2 emission Environmental pollution Johansen cointegration analysis Vector error correction model 

Notes

Acknowledgments

The authors extend their sincere thanks to the editors of this journal and the two anonymous reviewers for their valuable comments and suggestions, which helped to significantly improve the manuscript.

Funding information

This survey was sponsored by a major project supported by the National Natural Social Science Foundation of China (No. 17BJY067).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Economics and ManagementNorthwest A&F UniversityYanglingChina

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