Optimizing Policy for Balanced Industrial Profit and Water Pollution Control under a Complex Socioecological System Using a Multiagent-Based Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Case Study Area
2.2. Model Description and Parameterization
2.2.1. Agricultural Household Behavior Module
2.2.2. Factory Behavior Module
2.2.3. Environment Evaluation Module
2.3. Scenario Design
2.4. Policy Effects Analysis
2.5. Data Source and Processing
3. Results
3.1. Model Validation
3.2. Response Characteristics of Agricultural Household Agents and Factory Agents with Policy Change
3.3. Scenario Analysis
3.3.1. Pollutant Emissions at the Whole Watershed Scale under Different Policies
3.3.2. General Effect on the System of Different Policy Scenarios
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Harmancioglu, N.B. Overview of Water Policy Developments: Pre- and Post-2015 Development Agenda. Water Resour. Manag. 2017, 31, 3001–3021. [Google Scholar] [CrossRef]
- Wan, L.; Cai, W.; Jiang, Y.; Wang, C. Impacts on quality-induced water scarcity: Drivers of nitrogen-related water pollution transfer under globalization from 1995 to 2009. Environ. Res. Lett. 2016, 11, 074017. [Google Scholar] [CrossRef]
- Zhou, Y.; Khu, S.T.; Xi, B.; Su, J.; Hao, F.; Wu, J.; Huo, S. Status and challenges of water pollution problems in China: Learning from the European experience. Environ. Earth Sci. 2014, 72, 1243–1254. [Google Scholar] [CrossRef]
- Larsen, H. Environmental Taxes: Recent Developments in China and OECD Countries; OECD: Paris, France, 1999. [Google Scholar]
- Bongaerts, J.C.; Kraemer, A. Permits and effluent charges in the water pollution control policies of France, West Germany, and the Netherlands. Environ. Monit. Assess. 1989, 12, 127–147. [Google Scholar] [CrossRef] [PubMed]
- Baylis, K.; Peplow, S.; Rausser, G.; Simon, L. Agri-environmental policies in the EU and United States: A comparison. Ecol. Econ. 2008, 65, 753–764. [Google Scholar] [CrossRef]
- Claassen, R.; Cattaneo, A.; Johansson, R. Cost-effective design of agri-environmental payment programs: U.S. experience in theory and practice. Ecol. Econ. 2008, 65, 737–752. [Google Scholar] [CrossRef]
- Dobbs, T.L.; Pretty, J. Case study of agri-environmental payments: The United Kingdom. Ecol. Econ. 2008, 65, 765–775. [Google Scholar] [CrossRef]
- Hardner, J.; Rice, R. Rethinking green consumerism. Sci. Am. 2002, 286, 88–95. [Google Scholar] [CrossRef] [PubMed]
- Muñoz-Piña, C.; Guevara, A.; Torres, J.M.; Braña, J. Paying for the hydrological services of Mexico’s forests: Analysis, negotiations and results. Ecol. Econ. 2008, 65, 725–736. [Google Scholar] [CrossRef]
- Niesten, E.; Rice, R. Sustainable forest management and conservation incentive agreements. Int. For. Rev. 2004, 6, 56–60. [Google Scholar] [CrossRef]
- Pagiola, S. Payments for environmental services in Costa Rica. Ecol. Econ. 2008, 65, 712–724. [Google Scholar] [CrossRef] [Green Version]
- Fu, Y.; Zhang, J.; Zhang, C.; Zang, W.; Guo, W.; Qian, Z.; Liu, L.; Zhao, J.; Feng, J. Payments for Ecosystem Services for watershed water resource allocations. J. Hydrol. 2018, 556, 689–700. [Google Scholar] [CrossRef]
- Tobón Orozco, D.; Molina, C.; Vargas Cano, J.H. Pigouvian taxes and payments for environmental services in an economic model restricted by the resilience of a body of water. Water Resour. Econ. 2017, 19, 28–40. [Google Scholar] [CrossRef]
- Wunder, S.; Engel, S.; Pagiola, S. Taking stock: A comparative analysis of payments for environmental services programs in developed and developing countries. Ecol. Econ. 2008, 65, 834–852. [Google Scholar] [CrossRef]
- Engel, S.; Pagiola, S.; Wunder, S. Designing payments for environmental services in theory and practice: An overview of the issues. Ecol. Econ. 2008, 65, 663–674. [Google Scholar] [CrossRef] [Green Version]
- Pagiola, S.; Arcenas, A.; Platais, G. Can payments for environmental services help reduce poverty? An exploration of the issues and the evidence to date from Latin America. World Dev. 2005, 33, 237–253. [Google Scholar] [CrossRef]
- Yang, S.S.; Luan, S.J. Simulation on non-point pollution control from crop production based on a multi-agent model: Comparative research between fertilizer tax and payements for environmental services. Int. J. Ind. Eng. Theory 2014, 34, 777–786. (In Chinese) [Google Scholar]
- Jiao, Z.Q.; Zhang, W.G.; Wang, H.R.; Li, A.H. Somulating industrial water pollution control on a multi-agent model. J. Beijing Norm. Univ. 2017, 53, 486–494. (In Chinese) [Google Scholar]
- Terna, P. Simulation tools for social scientists: Building agent based models with swarm. J. Artif. Soc. Soc. Simul. 1998, 1, 1–12. [Google Scholar]
- Bandini, S.; Manzoni, S.; Vizzari, G. Agent Based Modeling and Simulation: An Informatics Perspective. J. Artif. Soc. Soc. Simul. 2009, 12, A51–A66. [Google Scholar]
- Berger, T.; Birner, R.; Diaz, J.; McCarthy, N.; Wittmer, H. Capturing the complexity of water uses and water users within a multi-agent framework. Water Resour. Manag. 2007, 21, 129–148. [Google Scholar] [CrossRef]
- Ng, T.L.; Eheart, J.W.; Cai, X.; Braden, J.B. An agent-based model of farmer decision-making and water quality impacts at the watershed scale under markets for carbon allowances and a second-generation biofuel crop. Water Resour. Res. 2011, 47, 113–120. [Google Scholar] [CrossRef]
- Zechman, E.M. Agent-Based Modeling to Simulate Contamination Events and Evaluate Threat Management Strategies in Water Distribution Systems. Risk Anal. 2011, 31, 758–772. [Google Scholar] [CrossRef] [PubMed]
- Yang, Y.C.E.; Zhao, J.S.; Cai, X.M. Decentralized Optimization Method for Water Allocation Management in the Yellow River Basin. J. Water Resour. Plan. Manag. 2012, 138, 313–325. [Google Scholar] [CrossRef]
- Nikolic, V.V.; Simonovic, S.P.; Milicevic, D.B. Analytical Support for Integrated Water Resources Management: A New Method for Addressing Spatial and Temporal Variability. Water Resour. Manag. 2013, 27, 401–417. [Google Scholar] [CrossRef]
- Yuan, X.C.; Wei, Y.M.; Pan, S.Y.; Jin, J.L. Urban Household Water Demand in Beijing by 2020: An Agent-Based Model. Water Resour. Manag. 2014, 28, 2967–2980. [Google Scholar] [CrossRef]
- Akhbari, M.; Grigg, N.S. Managing Water Resources Conflicts: Modelling Behavior in a Decision Tool. Water Resour. Manag. 2015, 29, 5201–5216. [Google Scholar] [CrossRef]
- Shafiee, M.E.; Berglund, E.Z.; Lindell, M.K. An agent-based modeling framework for assessing the public health protection of water advisories. Water Resour. Manag. 2018, 32, 2033–2059. [Google Scholar] [CrossRef]
- Arnold, R.T.; Troost, C.; Berger, T. Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent-based model. Water Resour. Res. 2015, 51, 648–668. [Google Scholar] [CrossRef] [Green Version]
- Mashhadi Ali, A.; Shafiee, M.E.; Berglund, E.Z. Agent-based modeling to simulate the dynamics of urban water supply: Climate, population growth, and water shortages. Sustain. Cities Soc. 2017, 28, 420–434. [Google Scholar] [CrossRef]
- Galán, J.M.; LópezParedes, A.; del Olmo, R. An agent-based model for domestic water management in valladolid metropolitan area. Water Resour. Res. 2009, 45, W05401. [Google Scholar] [CrossRef]
- Gilbert, G.N. Agent-Based Models; Sage Publications Inc.: Washington, DC, USA, 2007. [Google Scholar]
- Miller, J.H.; Page, S.E. Complex Adaptive Systems: An Introduction to Computational Models of Social Life; Princeton University Press: Princeton, NJ, USA, 2009; Volume 129, pp. 409–410. [Google Scholar]
- Wooldridge, M.; Jennings, N.R. Intelligent agents: Theory and practice. Knowl. Eng. Rev. 1995, 10, 115–152. [Google Scholar] [CrossRef]
- Bonabeau, E. Agent-based modeling: Methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. USA 2002, 99, 7280–7287. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Macal, C.M.; North, M.J. Tutorial on agent-based modelling and simulation. J. Simul. 2010, 4, 151–162. [Google Scholar] [CrossRef] [Green Version]
- Wilensky, U. NetLogo; Center for Connected Learning and Computer-Based Modeling, Northwestern University: Evanston, IL, USA, 1999; Available online: http://ccl.northwestern.edu/netlogo/2017-9-19 (accessed on 9 August 2018).
- Schotter, A. Microeconomics: A Modern Approach, 2nd ed.; Addison-Wesley: Boston, MA, USA, 1997. [Google Scholar]
- Intergovernmental Panel on Climate Change. IPCC Guidelines for National Greenhouse Gas Inventories (Volume 4): Agriculture, Forestry and Other Land Use; IPCC: Geneva, Switzerland, 2006. [Google Scholar]
- Organisation for Economic Co-Operation and Development (OECD). Agricultural and Environmental Policies: Oppprtunities for Intergration; China Environemtal Science Press: Beijing, China, 1996. [Google Scholar]
- Goedkoop, M.; Spriensma, R. The Eco-indictor 99: A Damage Oriented Method for Life Cycle Impact Assessment—Methodology Annex, 3rd ed.; PRé Consultants BV: Amersfoort, The Netherlands, 2001. [Google Scholar]
- Odum, H.T. Environmental Accounting: Emergy and Environmental Decision Making; Wiley and Sons: New York, NY, USA, 1996. [Google Scholar]
- Lai, L.; Huang, X.J.; Wang, H.; Dong, Y.H.; Xiao, S.S. Estimation of environmental cost of chemical fertilizer utilization in China. Acta Pedol. Sin. 2009, 46, 64–69. (In Chinese) [Google Scholar]
- Ministry of Agriculture and Rural Affairs of the People’s Republic of China. 2012 China Agricultural Development Report. Available online: http://english.agri.gov.cn/service/ayb/201701/t20170105_246192.htm (accessed on 9 August 2018).
- CSYD. Almanac of China Paper Industry; China Light Industry Press: Beijing, China, 2009; Available online: http://tongji.cnki.net/overseas/engnavi/NaviDefault.aspx (accessed on 9 August 2018).
- Ma, B.Y.; Liu, Y.C.; Xue, J.J. Application of Chemical Fertilizer and the Loss of Nitrogen and Phosphorus in Rice and Wheat Rotation Soil in South Hebei. J. Irrig. Drain. Eng. 2007, 26, 72–74. (In Chinese) [Google Scholar]
- Xu, P.; Lin, Y.H.; Yang, S.S.; Luan, S.J. Input load to river and future projection for nitriogen and phpsphorous nutrient controlling of Pearl river basin. J. Lake Sci. 2017, 29, 1359–1371. [Google Scholar]
- Chen, C.; Huang, D.F.; Qiu, X.X.; Li, W.H. Survey and Evaluation of Agricultural Non-Point Source Pollution and Prevention-and-Cure Counter measures in Middle and Upriver of Minjiang Drainage Area. J. Agro-Environ. Sci. 2007, 26, 368–374. (In Chinese) [Google Scholar]
- National Bureau of Statistics of China. China Statistical Yearbook; China Statistics Press: Beijing, China, 2011. Available online: http://tongji.cnki.net/overseas/engnavi/HomePage.aspx?id=N2011090108&name=YINFN&floor=1 (accessed on 9 August 2018). (In Chinese)
- Mosier, A.; Kroeze, C.; Nevison, C.; Oenema, O.; Seitzinger, S.; Van Cleemput, O. Closing the global atmospheric N2O budget: Nitrous oxide emissions through the agricultural nitrogen cycle: OECD/IPCC/IEA phase II development of IPCC guidelines for national greenhouse gas inventory methodology. Nutr. Cycl. Agroecosyst. 1998, 52, 225–248. [Google Scholar] [CrossRef]
- Yang, Z.P. Estimation of Ammonia Emission from Livestock in China Based on Mass-Flow Method and Regional Comparison; Peking University: Beijing, China, 2008. (In Chinese) [Google Scholar]
- Nash, J.E.; Sutcliffe, J.V. River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol. 1970, 10, 282–290. [Google Scholar] [CrossRef]
- Rao, Q.H.; Qiu, Y.; Xu, L.Z.; Wang, C.M.; Zhang, J.S. Estimating model of economic loss for Minjiang river basin casued by wayer pllution. Water Resour. Power 2014, 32, 47–50. [Google Scholar]
- MOA (Ministry of Agriculture of China); NBS (National Bureau of Statistics of China); MEP (Ministry of Environment Protection of China) (Eds.) The First National Pollution Census Report; MEP: Beijing, China, 2010.
- Qu, F.T.; Kuyvenhoven, A.; Shi, X.P.; Heerink, N. Sustainable natural resource use in rural China: Recent trends and policies. China Econ. Rev. 2011, 22, 444–460. [Google Scholar] [CrossRef]
- Jiang, Y.; Jin, L.S.; Lin, T. Higher water tariffs for less river pollution—Evidence from the Min River and Fuzhou City in China. China Econ. Rev. 2011, 22, 183–195. [Google Scholar] [CrossRef]
Parameter | Value | Source |
---|---|---|
23.91 | Fitted by the data for 1991–2010 obtained from “2012 China Agricultural Development Report” [45] | |
β1, β2, β3, β4, θ1 | 0.25, 0.075, 0.72, 0.06, 0.096 | |
0.4 | Fitted by the data for 1995–2010 obtained from Chinese paper industry yearbooks [46] | |
β5, β6, β7, θ2 | 0.13, 0.55, 0.27, 0.31 | |
TN: 15%, TP: 5% | Cited by [47,48] | |
TN: 21%, TP: 27%, COD: 15% | Cited by [18,48,49] | |
TN: 30%, TP: 27%, COD: 11% | Cited by [18,48,49] | |
34.32%, 15% | Calculated using the data from China statistic yearbooks [50] | |
25,439,809 | China statistical yearbooks [50] | |
Protein | 25.6 kg | Cited by [51] |
Pop | 598,537 | China statistical yearbooks [50] |
0.16 kg | Cited by [51] | |
1416 mg/L | Cited by [18] | |
0.206 kg/(capita × year) | Cited by [52] | |
1.1 | Cited by [51] | |
0.112 kg/(capita × year) | Cited by [52] | |
0.67 | Cited by [18] | |
1.571 kg/(capita × year) | Cited by [52] | |
25.64 | Cited by [18] |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Deng, C.; Wang, H.; Zhang, W.; Jiao, Z. Optimizing Policy for Balanced Industrial Profit and Water Pollution Control under a Complex Socioecological System Using a Multiagent-Based Model. Water 2018, 10, 1139. https://doi.org/10.3390/w10091139
Deng C, Wang H, Zhang W, Jiao Z. Optimizing Policy for Balanced Industrial Profit and Water Pollution Control under a Complex Socioecological System Using a Multiagent-Based Model. Water. 2018; 10(9):1139. https://doi.org/10.3390/w10091139
Chicago/Turabian StyleDeng, Caiyun, Hongrui Wang, Weiguang Zhang, and Zhiqian Jiao. 2018. "Optimizing Policy for Balanced Industrial Profit and Water Pollution Control under a Complex Socioecological System Using a Multiagent-Based Model" Water 10, no. 9: 1139. https://doi.org/10.3390/w10091139
APA StyleDeng, C., Wang, H., Zhang, W., & Jiao, Z. (2018). Optimizing Policy for Balanced Industrial Profit and Water Pollution Control under a Complex Socioecological System Using a Multiagent-Based Model. Water, 10(9), 1139. https://doi.org/10.3390/w10091139