A Transportation Network Optimization Model for Livestock Manure under Different Terrains Considering Economic and Environmental Benefits
Abstract
:1. Introduction
- (1)
- Taking, for example, Xinzhou District of Wuhan City, Hubei Province in China, some important information, including the spatial distribution of livestock and poultry farms, the crop demand of livestock manure, and the special terrains such as water areas and woodlands that hinder the transport of manure, were mined and extracted using statistical methods and the Voronoi diagram method.
- (2)
- Considering the influence of the surrounding environment on the livestock and poultry manure returned, such as special terrains and farmland area, a transportation optimization model is comprehensively proposed, considering the economic and environmental benefits.
2. Literature Review
3. Materials and Methods
3.1. Research Area
3.2. Data Collection and Preprocessing
3.3. Hierarchical Clustering of Farmland in Xinzhou District
3.4. Region Division and Classification Based on Voronoi Diagram
3.5. Optimization Model of Manure Transportation
3.5.1. Manure Amount Required to Replace Chemical Fertilizer (in Terms of Nitrogen)
3.5.2. Analysis of Economic Benefits of Manure Returning to Field
3.5.3. Manure Transportation Model Combining Economic and Environmental Benefits
3.5.4. Obstacle Coefficient
3.5.5. Solving by Genetic Algorithm
4. Results
4.1. Data Collection, Clustering and Region Division
4.2. Analysis of Regional Manure Distribution Scheme
4.2.1. Farm-Intensive Type
4.2.2. Water-Intensive Type (Obstruction Coefficient Is Equal to 1)
4.2.3. Water-Intensive Type (Obstruction Coefficient Is Equal to 2)
4.2.4. Influence of Terrain Obstacles on the Optimization Scheme of Manure Transportation
4.3. Global Optimal Solution Analysis
5. Discussion
6. Conclusions
- (1)
- Hierarchical clustering and regional division applying the Voronoi diagram were used to evaluate the density of breeding and the situation of special terrains in Xinzhou District. It can be divided into one farm-intensive region and three water-intensive or woodland-intensive regions.
- (2)
- An optimization model of manure transportation considering economic and environmental benefits under terrain obstruction was established. With the global solution of our method, the utilization rate of manure is improved to 90.64%, which is far higher than the requirement of the General Office of the State Council.
- (3)
- Under different optimization preferences, i.e., four benefit coefficient combinations, the impact ranges of topographic obstacles on the return benefit of manure were quantified. Through our model for optimization and evaluation, some suggestions are given for improving the benefit of the livestock and poultry breeding industries.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Symbols | Illustrations (Unit) |
---|---|
The fertilizer amount required by the farmer (t) | |
The manure amount required by the farmer (t) | |
Nitrogen content in nitrogen fertilizer (g/kg) | |
Nitrogen content in manure (g/kg) | |
Price of manure transportation and pretreatment (Yuan/t·km) | |
Distance of manure transportation (km) | |
Unit price of fertilizer (Yuan) | |
The amount of manure from the farm to the farmland (t) | |
Economic benefit of from the farm to thefarmland (Yuan) | |
Benefits from manure substitute fertilizer (Yuan) | |
Manure transportation cost (Yuan) | |
Total economic benefits (Yuan) | |
Transport distance from the farm to thefarmland (km) | |
The maximum load vector of manure | |
The yield vector of manure in the farm | |
Obstacle coefficient of terrain | |
Gains from thefarmland (Yuan) | |
Weight of economic benefits | |
Weight of environmental benefits |
Parameters | Values (Unit) |
---|---|
Nitrogen content of chemical fertilizer | 46% |
Nitrogen content of nitrogen fertilizer | 0.83% |
Manure transport price | 16 (Yuan/t·km) |
Fertilizer unit price | 1723 (Yuan/t) |
Rice yield per mu | 700 (kg) |
Required nitrogen content of 100 kg rice | 2.2 (kg) |
Nitrogen content of 1 kg pig manure | 2.28 (mg) |
Variables | Farm Intensive | Water Intensive | Water Intensive | |||
---|---|---|---|---|---|---|
Period | Before | After | Before | After | Before | After |
Obstruction coefficient | \ | 1 | 2 | |||
Coefficient combinations (environmental coefficient—economic coefficient) | 0.995–0.005 | 0.999–0.001 | 0.999–0.001 | |||
Utilization amount (t) | 2902 | 3337 | 1024 | 1194 | 1024 | 891 |
Utilization rate | 81.5% | 93.7% | 85.8% | 100% | 85.8% | 74.6% |
Economic benefits (Yuan/ha) | 1057.64 | 1637.8 | 75.81 | 265.92 | 49.05 | 181.05 |
Total benefits | 14,627 | 20,067 | 1079 | 1404 | 929 | 1034 |
Groups | Group 1 | Group 2 | Group 3 | Group 4 |
---|---|---|---|---|
Economic coefficient | 0.001 | 0.002 | 0.005 | 0.010 |
Environmental coefficient | 0.999 | 0.998 | 0.995 | 0.990 |
Increased manure discharge rate | 3.82% | 1.42% | 2.92% | 3.01% |
Increased manure discharge amount (t) | 45.6 | 17.0 | 34.7 | 35.9 |
Decreased average economic benefit (Yuan) | −2976.5 | −691.9 | 1134.6 | 2760.2 |
Index | Minimum | Lower Quantile | Upper Quantile | Maximum |
---|---|---|---|---|
Discharge rate before optimization | 0.0500 | 0.1400 | 0.2000 | 0.8790 |
Discharge rate after optimization | 0.0000 | 0.0001 | 0.0020 | 0.5000 |
Economic benefits before optimization | −17,003,654 | 6844 | 395,618 | 9,660,998 |
Economic benefits after optimization | −6,018,232 | 116,885 | 1,114,178 | 10,910,522 |
Index | Standard Deviation | Coefficient of Variation | Skewness | Average |
Discharge rate before optimization | 0.0621 | 0.3600 | 3.0286 | 0.1725 |
Discharge rate after optimization | 0.1318 | 2.4019 | 2.4258 | 0.0549 |
Economic benefits before optimization | 2,236,826 | 6.3071 | −1.6516 | 354,654 |
Economic benefits after optimization | 2,253,632 | 2.0083 | 2.1669 | 1,122,134 |
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Deng, B.; Chen, T.; Pu, Z.; Peng, X.; Qin, X.; Zhan, X.; Wen, J. A Transportation Network Optimization Model for Livestock Manure under Different Terrains Considering Economic and Environmental Benefits. Sustainability 2022, 14, 7721. https://doi.org/10.3390/su14137721
Deng B, Chen T, Pu Z, Peng X, Qin X, Zhan X, Wen J. A Transportation Network Optimization Model for Livestock Manure under Different Terrains Considering Economic and Environmental Benefits. Sustainability. 2022; 14(13):7721. https://doi.org/10.3390/su14137721
Chicago/Turabian StyleDeng, Bing, Taoyu Chen, Zhenyu Pu, Xia Peng, Xiner Qin, Xiaomei Zhan, and Jianghui Wen. 2022. "A Transportation Network Optimization Model for Livestock Manure under Different Terrains Considering Economic and Environmental Benefits" Sustainability 14, no. 13: 7721. https://doi.org/10.3390/su14137721
APA StyleDeng, B., Chen, T., Pu, Z., Peng, X., Qin, X., Zhan, X., & Wen, J. (2022). A Transportation Network Optimization Model for Livestock Manure under Different Terrains Considering Economic and Environmental Benefits. Sustainability, 14(13), 7721. https://doi.org/10.3390/su14137721