Analysis of Land-Use Emergy Indicators Based on Urban Metabolism: A Case Study for Beijing
Abstract
:1. Introduction
2. Methodology
2.1. Conceptual Model of an Urban Metabolic System
2.2. Emergy Accounting
2.3. Emergy-Based Evaluation System of Urban Metabolism
Indices | Formula | |
---|---|---|
Flux(F) | U | |
Structures | S1 | R/(R + N) |
S2 | N/U | |
S3 | IMP/U | |
Intensity(I) | U/population | |
Efficiency(E) | GDP/U | |
Waste Emission Ratio(W) | EW/U |
2.4. Emergy-Based Evaluation of Land Use
Indices | Formula |
---|---|
Metabolic Density(D) | Ui/Land Area |
Emergy Yield Ratio(EYR) | Total Land Emergy Output/Total Land Emergy Input |
Land Environmental Load Ratio(ELR) | (IMP + N)/R |
Land Emergy Sustainable Indices (ESI) | EYR/ELR |
2.5. Correlation Analysis of Urban Metabolism and Land Use Changes
3. Results
3.1. Emergy-Based Evaluation of the Metabolism of Beijing
Item | Solar transformity | Solar emergy (×1020 seJ) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
1996 | 1998 | 2000 | 2002 | 2004 | 2006 | 2008 | 2010 | 2012 | ||
Renewable sources | ||||||||||
1. Sunlight | 1 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 | 0.72 |
2. Wind, kinetic | 2.51 × 103 | 1.41 | 1.19 | 1.25 | 1.19 | 1.22 | 1.18 | 1.18 | 1.19 | 1.18 |
3. Rain, geopotential | 1.74 × 104 | 0.86 | 0.90 | 0.45 | 0.45 | 0.59 | 0.39 | 0.77 | 0.64 | 0.90 |
4. Rain, chemical | 3.05 × 104 | 17.33 | 18.09 | 9.18 | 9.16 | 11.95 | 7.86 | 15.49 | 12.92 | 18.13 |
5. Earth cycle | 4.70 × 104 | 8.74 | 8.74 | 8.74 | 8.74 | 8.74 | 8.74 | 8.74 | 8.74 | 8.74 |
6. Rivers, geopotential | 9.73 × 104 | 5.55 | 5.55 | 5.25 | 4.57 | 7.01 | 5.74 | 11.09 | 6.23 | 15.47 |
Non-renewable sources | ||||||||||
7. Soil losses | 1.70 × 107 | 1.12 | 1.11 | 4.58 | 5.14 | 5.75 | 2.15 | 4.33 | 1.87 | 1.91 |
Indigenous fossil fuels | ||||||||||
8. Coal | 6.69 × 104 | 198.03 | 194.11 | 135.29 | 172.54 | 209.80 | 186.27 | 113.72 | 98.04 | 96.07 |
Indigenous material input | ||||||||||
9. Limestone | 1.68 × 109 | 134.23 | 157.02 | 185.25 | 198.02 | 271.98 | 284.78 | 497.81 | 234.98 | 206.82 |
10. Steel | 3.16 × 109 | 261.96 | 253.34 | 253.88 | 258.15 | 274.37 | 258.53 | 207.55 | 250.95 | 91.51 |
11. Pig iron | 1.44 × 109 | 100.08 | 108.04 | 111.35 | 111.29 | 115.47 | 113.44 | 64.63 | 59.33 | 0.00 |
12. Electricity | 1.74 × 105 | 13.26 | 17.05 | 17.05 | 1.89 | 1.89 | 1.89 | 1.89 | 5.68 | 9.47 |
Imports and outside sources | ||||||||||
13. Agricultural production | 1.43 × 105 | 111.40 | 113.54 | 106.65 | 101.94 | 115.24 | 140.97 | 145.16 | 158.61 | 152.85 |
14. Livestock production | 9.15 × 105 | 62.22 | 107.97 | 80.52 | 93.72 | 14.55 | 12.91 | 20.79 | 11.97 | 51.74 |
15. Fisheries production | 3.36 × 106 | 6.52 | 32.26 | 31.01 | 22.85 | 17.46 | 12.50 | 7.18 | 9.83 | 8.40 |
16. Coal | 6.69 × 104 | 435.28 | 403.91 | 462.73 | 417.63 | 462.73 | 550.96 | 507.82 | 523.51 | 447.04 |
17. Coke | 1.10 × 105 | 56.37 | 37.58 | 34.45 | 31.32 | 56.37 | 40.71 | 25.05 | 25.05 | 9.40 |
18. Crude oil | 9.08 × 104 | 262.70 | 244.83 | 288.17 | 281.33 | 44.48 | 480.16 | 439.48 | 418.19 | 409.44 |
19. Gasoline | 1.05 × 105 | 27.62 | 30.79 | 31.70 | 0.00 | 0.00 | 73.81 | 74.26 | 93.73 | 112.75 |
20. Kerosene | 1.10 × 105 | 51.71 | 54.08 | 74.95 | 83.49 | 115.74 | 131.87 | 185.48 | 198.76 | 231.02 |
21. Diesel | 1.10 × 105 | 20.20 | 10.80 | 26.78 | 0.00 | 66.24 | 69.99 | 77.04 | 82.68 | 85.03 |
22. Fuel oil | 1.10 × 105 | 40.53 | 14.74 | 8.29 | 5.53 | 8.29 | 6.91 | 14.74 | 30.86 | 37.30 |
23. Liquefied petroleum gas | 1.11 × 105 | 0.00 | 0.00 | 0.00 | 0.00 | 4.46 | 6.69 | 12.83 | 7.81 | 7.81 |
24. Natural gas | 9.85 × 105 | 5.75 | 14.57 | 42.08 | 78.55 | 103.56 | 147.21 | 232.58 | 287.78 | 354.71 |
Exports | ||||||||||
25. Chemical fertilizer | 2.67 × 107 | 0.05 | 0.05 | 0.05 | 0.04 | 0.04 | 0.04 | 0.04 | 0.04 | 0.04 |
26. Plastic | 5.39 × 109 | 0.63 | 0.52 | 0.53 | 0.67 | 0.53 | 0.59 | 0.77 | 0.73 | 0.72 |
27. Pesticides | 2.49 × 1010 | 2.85 | 1.27 | 1.35 | 1.17 | 1.33 | 1.16 | 0.96 | 0.99 | 0.98 |
28. Electricity | 1.74 × 105 | 269.07 | 318.34 | 377.08 | 488.87 | 587.41 | 678.36 | 875.43 | 1072.49 | 1184.29 |
29. Goods in imports | 5.00 × 1012 | 1059.95 | 999.65 | 1871.55 | 1994.55 | 3700.30 | 6004.15 | 10,712.90 | 12,311.10 | 17,423.75 |
30. Services in imports | 5.00 × 1012 | 118.77 | 176.19 | 333.38 | 547.09 | 922.19 | 1493.96 | 2537.40 | 4298.47 | 7359.51 |
31. Foreign investment | 4.00 × 1012 | 6.88 | 8.67 | 6.74 | 7.17 | 12.34 | 18.21 | 24.33 | 25.46 | 32.17 |
32. Agricultural production | 1.43 × 105 | 7.31 | 10.83 | 6.22 | 6.10 | 4.62 | 1.73 | 1.95 | 15.85 | 10.70 |
33. Livestock production | 9.15 × 105 | 3.78 | 1.17 | 1.85 | 0.35 | 0.43 | 0.33 | 0.23 | 0.26 | 0.08 |
34. Fisheries production | 3.36 × 106 | 1.44 | 3.12 | 4.84 | 5.48 | 6.55 | 2.53 | 1.80 | 1.97 | 1.68 |
35. Coal | 6.69 × 104 | 103.92 | 84.31 | 84.31 | 101.96 | 107.84 | 137.25 | 105.88 | 98.04 | 105.88 |
36. Coke | 1.10 × 105 | 25.05 | 12.53 | 34.45 | 40.71 | 28.19 | 194.17 | 9.40 | 25.05 | 18.79 |
37. Gasoline | 1.05 × 105 | 53.43 | 48.45 | 35.32 | 38.04 | 33.51 | 38.94 | 18.11 | 40.30 | 41.20 |
38. Kerosene | 1.10 × 105 | 16.13 | 17.55 | 21.82 | 23.24 | 34.63 | 46.96 | 77.80 | 66.89 | 73.05 |
39. Diesel | 1.10 × 105 | 43.22 | 3.76 | 71.87 | 61.54 | 86.43 | 88.78 | 139.52 | 135.76 | 131.06 |
40. Fuel oil | 1.10 × 105 | 15.66 | 0.00 | 2.76 | 7.37 | 7.37 | 12.43 | 13.82 | 16.12 | 12.90 |
41. Liquefied petroleum gas | 1.11 × 105 | 2.79 | 2.79 | 4.46 | 3.35 | 4.46 | 12.27 | 3.90 | 2.23 | 1.67 |
42. Goods in exports | 1.14 × 1013 | 925.68 | 1198.48 | 1364.47 | 1438.00 | 2344.87 | 4326.76 | 6549.76 | 6320.05 | 6798.05 |
43. Services in exports | 1.14 × 1013 | 103.73 | 211.24 | 243.06 | 394.43 | 584.39 | 1076.59 | 1551.34 | 2206.67 | 2871.38 |
Waste | ||||||||||
44. Liquid waste | 9.87 × 106 | 12.96 | 13.20 | 15.20 | 16.50 | 17.30 | 18.50 | 17.80 | 20.61 | 21.20 |
45. Solid Waste | 1.80 × 106 | 0.07 | 0.07 | 0.07 | 0.06 | 0.08 | 0.08 | 0.07 | 0.08 | 0.07 |
Index | Value | ||||||||
---|---|---|---|---|---|---|---|---|---|
1996 | 1998 | 2000 | 2002 | 2004 | 2006 | 2008 | 2010 | 2012 | |
F a | 3.28 | 3.34 | 4.51 | 4.93 | 7.14 | 10.74 | 16.82 | 20.24 | 28.36 |
S1 | 4.66% | 4.59% | 3.49% | 3.22% | 3.32% | 2.83% | 4.09% | 4.47% | 10.01% |
S2 | 21.59% | 21.91% | 15.68% | 15.16% | 12.31% | 7.88% | 5.29% | 3.22% | 1.43% |
S3 | 77.35% | 77.04% | 83.75% | 84.34% | 87.27% | 91.89% | 94.48% | 96.63% | 98.41% |
I b | 2.61 | 2.68 | 3.32 | 3.46 | 4.79 | 6.79 | 9.92 | 10.32 | 13.71 |
E c | 6.56 | 8.61 | 8.47 | 10.58 | 10.20 | 9.55 | 9.51 | 10.30 | 9.99 |
W | 0.40% | 0.40% | 0.34% | 0.34% | 0.24% | 0.17% | 0.11% | 0.10% | 0.07% |
3.2. Analysis of Land Use Change
3.3. Emergy-Based Indices for Land Use Analysis
3.3.1. Emergy-Based Evaluation of the Whole Urban Area
Indices | Value | ||||||||
---|---|---|---|---|---|---|---|---|---|
1996 | 1998 | 2000 | 2002 | 2004 | 2006 | 2008 | 2010 | 2012 | |
D | 2.00 × 1013 | 2.03 × 1013 | 2.75 × 1013 | 3.00 × 1013 | 4.35 × 1013 | 6.55 × 1013 | 1.03 × 1014 | 1.23 × 1014 | 1.73 × 1014 |
EYR | 0.51 | 0.60 | 0.51 | 0.53 | 0.52 | 0.59 | 0.53 | 0.46 | 0.37 |
ELR | 93.84 | 93.81 | 175.25 | 197.42 | 235.24 | 435.16 | 441.90 | 663.98 | 627.34 |
ESI | 5.45 × 10−3 | 6.37 × 10−3 | 2.92 × 10−3 | 2.70 × 10−3 | 2.23 × 10−3 | 1.36 × 10−3 | 1.20 × 10−3 | 6.96 × 10−4 | 5.89 × 10−4 |
3.3.2. Emergy-Based Evaluation of Farm Land
Index | Value | ||||||||
---|---|---|---|---|---|---|---|---|---|
1996 | 1998 | 2000 | 2002 | 2004 | 2006 | 2008 | 2010 | 2012 | |
Industrial energy input (seJ) | 6.49 × 1020 | 5.32 × 1020 | 5.65 × 1020 | 4.99 × 1020 | 5.15 × 1020 | 4.76 × 1020 | 3.89 × 1020 | 3.60 × 1020 | 3.57 × 1020 |
Industrial energy input per unit area (seJ/m2) | 5.71 × 1010 | 4.69 × 1010 | 5.01 × 1010 | 4.46 × 1010 | 4.65 × 1010 | 4.31 × 1010 | 3.55 × 1010 | 3.29 × 1010 | 3.28 × 1010 |
D | 4.24 × 1011 | 3.74 × 1011 | 3.75 × 1011 | 3.92 × 1011 | 4.34 × 1011 | 4.18 × 1011 | 6.15 × 1011 | 6.38 × 1011 | 8.06 × 1011 |
EYR | 7.79 | 9.42 | 10.17 | 11.56 | 10.48 | 9.22 | 6.49 | 6.18 | 4.75 |
ELR | 1.40 | 1.07 | 2.02 | 2.17 | 2.06 | 2.63 | 2.76 | 3.32 | 3.46 |
ESI | 5.58 | 8.81 | 5.03 | 5.32 | 5.07 | 3.50 | 2.36 | 1.86 | 1.37 |
3.3.3. Emergy-Based Evaluation of Built-up Land
Index | Value | ||||||||
---|---|---|---|---|---|---|---|---|---|
1996 | 1998 | 2000 | 2002 | 2004 | 2006 | 2008 | 2010 | 2012 | |
Energy Emergy Consumption (seJ) | 9.90 × 1022 | 1.13 × 1023 | 1.26 × 1023 | 1.38 × 1023 | 1.59 × 1023 | 1.74 × 1023 | 2.14 × 1023 | 2.43 × 1023 | 2.57 × 1023 |
Unit Energy Consumption (seJ/m2) | 3.65 × 1013 | 4.09 × 1013 | 4.32 × 1013 | 4.48 × 1013 | 4.95 × 1013 | 5.31 × 1013 | 6.34 × 1013 | 6.92 × 1013 | 7.23 × 1013 |
Cement Emergy Consumption (seJ) | 1.01 × 1022 | 1.18 × 1022 | 1.39 × 1022 | 1.49 × 1022 | 2.04 × 1022 | 2.14 × 1022 | 3.73 × 1022 | 1.76 × 1022 | 1.55 × 1022 |
Unit Cement Consumption (seJ/m2) | 3.72 × 1012 | 4.26 × 1012 | 4.75 × 1012 | 4.81 × 1012 | 6.37 × 1012 | 6.53 × 1012 | 1.11 × 1013 | 5.02 × 1012 | 4.37 × 1012 |
D | 1.13 × 1014 | 1.10 × 1014 | 1.46 × 1014 | 1.52 × 1014 | 2.18 × 1014 | 3.22 × 1014 | 4.92 × 1014 | 5.70 × 1014 | 7.92 × 1014 |
EYR | 0.74 | 0.89 | 0.73 | 0.75 | 0.69 | 0.73 | 0.64 | 0.57 | 0.45 |
ELR | 638.53 | 609.53 | 1175.21 | 1227.97 | 1536.00 | 2800.02 | 3000.70 | 3862.92 | 4379.32 |
ESI | 1.16 × 10−3 | 1.46 × 10−3 | 6.24 × 10−4 | 6.08 × 10−4 | 4.50 × 10−4 | 2.60 × 10−4 | 2.13 × 10−4 | 1.47 × 10−4 | 1.03 × 10−4 |
3.4. Correlation Analysis of Urban Metabolism and Land Use Changes
Land Use Type | Correlation Coefficients | ||||
---|---|---|---|---|---|
U | D | EYR | ELR | ESI | |
Farmland | 0.8586 | 0.8566 | 0.3992 | 0.6321 | 0.8885 |
Build-up land | 0.9999 | 0.9958 | 0.9485 | 0.8151 | 0.9933 |
4. Conclusions
- (1)
- Waste emission of Beijing was reduced in recent years, and the utilization rate of resources is higher than in most of the fast-growing cities of China. However, Beijing is a typical consumer-economic urban system, which relies on the consumption of materials and energy. The production activities on built-up land depended on exploitation of local non-renewable resources and on external resource input, and the emergy sustainable indices decreased to almost zero. While there is a continued slowdown in emergy utilization and sustainability of farmland, but the farmland still has more utilization potential than in most provinces and cities of China. According to the correlation analysis, urban development in Beijing relies on production activities on built-up land, which is subjected to great environmental pressure during extraction of material resources. However, while the value of metabolic density of built-up land is between 1.46 × 1014 and 1.97 × 1014, there is a positive effect on urban environment, which provides a reliable reference for intensive and compact use of urban land.
- (2)
- The research on urban metabolism and land use based on emergy analysis magnifies every link of land use and metabolism, thus revealing the details of urban development. This makes it possible to conduct specific research on different problems, and to bridge the gap in correlation research, between urban metabolism and land use. The measuring units of materials, energy, and capital are always different, thus it is difficult to compare or combine them in one system, while analysis of the dynamics of emergy indices of different kinds of land, can solve the problems of conflicting measurement units, and avoid the disadvantages of subjective assignment. Each kind of industrial and agricultural product produced by different modes and at different levels has different resource input and output, so its solar transformity is different also, but we used a single transformity value for some resources, thus leading to the inaccuracy of material, energy, and capital emergy in the emergy-analysis method. However, the error is acceptable in the research of urban systems [72].
- (3)
- To realize sustainable development of urban social economy and land use, we suggest that it is necessary to reduce the input of external feedback emergy, reuse materials, recycle products, and control wastes [73], to commit to development of a circular economy. Regarding land administration, the concept of urban land use should be changed to traffic accessible, land-use efficient, and ecological “Smart Growth” [74], to reduce energy consumption and environmental cost. Moreover, developing the potential of farmland appropriately, and popularizing metropolitan modern circulating agriculture of plant-production/animal-transformation/microbial-loop/process model, etc. [75] is necessary to reduce the urban load pressure.
- (4)
- To achieve efficient use of land resources and sustainable urban development, we need further research. First, we need more study about the mechanism of effects between land use and urban metabolism. If we find the key point of land use change, and material, energy, and capital flow change, we might then construct a better land use pattern that is less consumption oriented, has high metabolic efficiency, and is more eco-friendly. Second, we need to apply methods and models to more cases, combined with spatial information sciences, and to compare the research results of these different cases on temporal and spatial scales. Then we might give reliable suggestions on land use and urban sustainable development. Third, we need to explore more methods by which to analyze land use and urban metabolism on different scales, and to evaluate the effect of methodological pluralism. In this way, we might provide new ideas for land administration and urban planning, and also provide a basis for solving urban ecological problems.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Huang, Q.; Zheng, X.; Hu, Y. Analysis of Land-Use Emergy Indicators Based on Urban Metabolism: A Case Study for Beijing. Sustainability 2015, 7, 7473-7491. https://doi.org/10.3390/su7067473
Huang Q, Zheng X, Hu Y. Analysis of Land-Use Emergy Indicators Based on Urban Metabolism: A Case Study for Beijing. Sustainability. 2015; 7(6):7473-7491. https://doi.org/10.3390/su7067473
Chicago/Turabian StyleHuang, Qing, Xinqi Zheng, and Yecui Hu. 2015. "Analysis of Land-Use Emergy Indicators Based on Urban Metabolism: A Case Study for Beijing" Sustainability 7, no. 6: 7473-7491. https://doi.org/10.3390/su7067473