Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016
Abstract
:1. Introduction
2. Index Selection and Model Construction
2.1. Index Selection and Dimensionless Method
2.2. Weight
2.3. Comprehensive Evaluation Index
2.4. Model of Coupling and Coordination
2.4.1. Contrastive Relation for Coupling and Coordination
2.4.2. Coupling, Coordination Degree, and Types
3. Result Analysis
3.1. Trend of Comprehensive Evaluation Index
3.2. Contrastive Relation for Coupling and Coordination
3.3. Coordination Degree
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Kim, M.S.; Chung, J.Y. Sustainable growth and token economy design: The case of steemit. Sustainability 2018, 11, 167. [Google Scholar] [CrossRef]
- Benatar, S.; Poland, B. Lessons for health from insights into environmental crises. Int. J. Health Serv. 2016, 46, 825–842. [Google Scholar] [CrossRef] [PubMed]
- Shahiduzzaman, M.; Alam, K. A reassessment of energy and GDP relationship: The case of Australia. Environ. Dev. Sustain. 2014, 16, 323–344. [Google Scholar] [CrossRef]
- Jing, Z. Literature Review on EKC and the Effects of FDI on the Environment. In Foreign Direct Investment, Governance, and the Environment in China; The Nottingham China Policy Institute Series; Palgrave Macmillan: London, UK, 2013. [Google Scholar]
- Zhang, X.; Davidson, E.A.; Mauzerall, D.L.; Searchinger, T.D.; Dumas, P.; Shen, Y. Managing nitrogen for sustainable development. Nature 2015, 528, 51–59. [Google Scholar] [CrossRef]
- Minihan, E.S.; Wu, Z. Economic structure and strategies for greenhouse gas mitigation. Energy Econ. 2012, 34, 350–357. [Google Scholar] [CrossRef]
- Oliveira, C.; Coelho, D.; Antunes, C.H. Coupling input-output analysis with multiobjective linear programming models for the study of economy-energy-environment-social (e3s) trade-offs: A review. Ann. Oper. Res. 2016, 247, 471–502. [Google Scholar] [CrossRef]
- Oliveira, C.; Antunes, C.H. A multi-objective multi-sectoral economy-energy-environment model: Application to Portugal. Energy 2011, 36, 2856–2866. [Google Scholar] [CrossRef]
- Zhou, Q.; Llewellyn, G.; Stancliffe, R.; Fortune, N. Working-age people with disability and labour force participation: Geographic variations in Australia. Aust. J. Soc. Issues 2019, 54, 323–340. [Google Scholar] [CrossRef]
- Stougie, L.; Giustozzi, N.; van der Kooi, H.; Stoppato, A. Environmental, economic and exergetic sustainability assessment of power generation from fossil and renewable energy sources. Int. J. Energy Res. 2018, 42, 2916–2926. [Google Scholar] [CrossRef]
- Long-de, H.E. Practical measures of australian ecological environmental protection and reference of their experience. J. Chang. Univ. Sci. Technol. 2014, 29, 48–52. [Google Scholar]
- Lydon, A.; Barry, M.; Paul, M.; Oliver, J. A new method for the fast analysis of trihalomethanes in tap and recycled waters using headspace gas chromatography with micro-electron capture detection. Int. J. Environ. Res. Public Health 2017, 14, 527. [Google Scholar]
- Sarkodie, S.A.; Strezov, V.; Weldekidan, H.; Asamoah, E.F.; Owusu, P.A.; Doyi, I.N.Y. Environmental sustainability assessment using dynamic autoregressive-distributed lag simulations—Nexus between greenhouse gas emissions, biomass energy, food and economic growth. Sci. Total Environ. 2019, 668, 318–332. [Google Scholar] [CrossRef]
- Geng, Z.; Yang, K.; Han, Y.; Gu, X. Fault detection of large-scale process control system with higher-order statistical and interpretative structural model. Chin. J. Chem. Eng. 2015, 23, 146–153. [Google Scholar] [CrossRef]
- Guo, Q.; Zhou, Z.; Huang, G.; Dou, Z. Variations of Groundwater Quality in the Multi-Layered Aquifer System near the Luanhe River, China. Sustainability 2019, 11, 994. [Google Scholar] [CrossRef]
- Pirnia, P.; Duhaime, F.; Ethier, Y.; Jean-Sébastien, D. Drag force calculations in polydisperse dem simulations with the coarse-grid method: Influence of the weighting method and improved predictions through artificial neural networks. Transp. Porous Media 2019, 129, 837–853. [Google Scholar] [CrossRef]
- Du, Y.; Yang, W.; Qi, W.; Hu, G.; Yin, Y.; Xie, P. Analysis of the coupling characteristics of multi-channel electromyography. In Proceedings of the 2017 Chinese Automation Congress (CAC), Jinan, China, 20–22 October 2017. [Google Scholar]
- Ka, Z.; Ben-Liang, Q.U.; Mei, G. Analyzing coupled regional economic development and land-water resource—A case study of liaoning province. Resour. Dev. Mark. 2015, 31, 316–320. [Google Scholar]
- Shi, H.; Al-Rubaiai, M.; Holbrook, C.M.; Miao, J.; Pinto, T.; Wang, C.; Tan, X. Screen printed soft capacitive sensors for spatial mapping of both positive and negative pressures. Adv. Funct. Mater. 2019, 29, 1809116. [Google Scholar] [CrossRef]
- Li, Y.; Wang, J.; Liu, Y.; Long, H. Problem regions and regional problems of socioeconomic development in China: A perspective from the coordinated development of industrialization, informatization, urbanization and agricultural modernization. J. Geogr. Sci. 2014, 24, 1115–1130. [Google Scholar] [CrossRef]
- Han, R.; Tong, L.; Zhu, S.; Lu, Z. The Coordinated Development of Economy and Environment Based on ARMA Model in Shenyang Economic Zone. Sci. Geogr. Sin. 2014, 34, 32–39. [Google Scholar]
- Gardner, A.; Bartlett, R.; Gray, J.; Nelson, R. Water Resources Law; LexisNexis Butterworths: Chatswood, Australia, 2017. [Google Scholar]
- Coenen, L.; Campbell, S.; Wiseman, J. Regional Innovation Systems and Transformative Dynamics: Transitions in Coal Regions in Australia and Germany. In New Avenues for Regional Innovation Systems—Theoretical Advances, Empirical Cases and Policy Lessons; Isaksen, A., Martin, R., Trippl, M., Eds.; Springer: Cham, Switzerland, 2018. [Google Scholar]
- Zander, K.K.; Moss, S.; Garnett, S.T. Climate Change—Related Heat Stress and Subjective Well-Being in Australia. Weather Clim. Soc. 2019, 11, 505–520. [Google Scholar] [CrossRef]
- Azadi, M.; Edraki, M.; Farhang, F.; Ahn, J. Opportunities for mineral carbonation in Australia’s mining industry. Sustainability 2019, 11, 1250. [Google Scholar] [CrossRef]
- Wang, B.; Liu, D.L.; Evans, J.P.; Ji, F.; Beyer, K. Modelling and evaluating the impacts of climate change on three major crops in south-eastern Australia using regional climate model simulations. Theor. Appl. Climatol. 2019, 138, 509–526. [Google Scholar] [CrossRef]
- Bo, B.C.; Lee, D.; Psaros, J. An analysis of Australian company carbon emission disclosures. Pac. Account. Rev. 2013, 25, 58–79. [Google Scholar]
- Poruschi, L.; Ambrey, C.L. Energy justice, the built environment, and solar photovoltaic (PV) energy transitions in urban Australia: A dynamic panel data analysis. Energy Res. Soc. Sci. 2019, 48, 22–32. [Google Scholar] [CrossRef]
- Chapman, A.J.; Tezuka, T.; McLellan, B. Renewable energy policy efficacy and sustainability: The role of equity in improving energy policy outcomes. In Sustainability through Innovation in Product Life Cycle Design; Matsumoto, M., Masui, K., Fukushige, S., Kondoh, S., Eds.; Springer: Singapore, 2017; pp. 747–763. [Google Scholar]
- Khalaj, A.H.; Scherer, T.; Halgamuge, S.K. Energy, Environmental and Economical Saving Potential of Data Centers with Various Economizers across Australia. Appl. Energy 2016, 183, 1528–1549. [Google Scholar] [CrossRef]
- Bernhardt, E.S.; Rosi, E.J.; Gessner, M.O. Synthetic chemicals as agents of global change. Front. Ecol. Environ. 2017, 15, 84–90. [Google Scholar] [CrossRef]
- Ayangbenro, A.S.; Babalola, O.O. A new strategy for heavy metal polluted environments: A review of microbial biosorbents. Int. J. Environ. Res. Public Health 2017, 14, 94. [Google Scholar] [CrossRef]
- Azad, A.K.; Rasul, M.G.; Khan, M.M.K.; Sharma, S.C.; Bhuiya, M.M.K. Study on Australian energy policy, socio-economic, and environment issues. J. Renew. Sustain. Energy 2015, 7, 063131. [Google Scholar] [CrossRef]
- Maslyuk, S.; Dharmaratna, D. Impact of Shocks on Australian Coal Mining. In Global Energy Policy and Security; Springer: London, UK, 2013. [Google Scholar]
- Dungey, M.; Matei, M.; Luciani, M.; Veredas, D. Surfing through the GFC: Systemic risk in Australia. Econ. Rec. 2017, 93, 1–19. [Google Scholar] [CrossRef]
- McNeill, J.; Meng, S.; Siriwardana, M. The environmental and economic impact of the carbon tax in Australia. Environ. Resour. Econ. 2013, 54, 313–332. [Google Scholar]
- Manalo, J.; Perera, D.; Rees, D.M. Exchange Rate Movements and the Australian Economy. Econ. Model. 2015, 47, 53–62. [Google Scholar] [CrossRef]
- Bennett, J.M.; McBratney, A.; Field, D.; Kidd, D.; Stockmann, U.; Liddicoat, C.; Grover, S. Soil Security for Australia. Sustainability 2019, 11, 3416. [Google Scholar] [CrossRef]
- Robinson, T.; Nguyen, V.H.; Wang, J. The Australian economy in 2016–2017: Looking beyond the apartment construction boom. Aust. Econ. Rev. 2017, 50, 5–20. [Google Scholar] [CrossRef]
- Leal, P.H.; Marques, A.C.; Fuinhas, J.A. How economic growth in Australia reacts to CO2 emissions, fossil fuels and renewable energy consumption. Int. J. Sect. Manag. 2018, 12, 696–713. [Google Scholar] [CrossRef]
- Dahal, S.; Nadarajah, M. Renewable energy development in Australia: Regulatory to technical challenges. In Proceedings of the 2015 IEEE PES Asia-Pacific Power Engineering Conference (APPEEC), Brisbane, Australia, 15–18 November 2015. [Google Scholar]
- Cheng, Y.; Shao, T.; Lai, H.; Shen, M.; Li, Y. Total-Factor Eco-Efficiency and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration, China. Int. J. Environ. Res. Public Health 2019, 16, 3814. [Google Scholar] [CrossRef]
- Long, Y.; Wang, J.; Wu, K.; Zhang, J. Population exposure to ambient PM2.5 at the subdistrict level in China. Int. J. Environ. Res. Public Health 2018, 15, 2683. [Google Scholar] [CrossRef] [Green Version]
System Layers | Index Layers | Unit | Index Character | Weights |
---|---|---|---|---|
Energy subsystem | Primary energy production | Quadrillion Btu | + | 0.1825 |
Primary energy consumption | Quadrillion Btu | − | 0.1349 | |
Energy intensity index | MJ per dollar of GDP | − | 0.2360 | |
Net energy imports (as a percentage of energy consumption) | % | − | 0.1754 | |
Ores and metals exports (% of merchandise exports) | % | − | 0.1648 | |
Carbon dioxide emissions from energy consumption | Million Metric Tons | − | 0.1064 | |
Economic subsystem | Per capita GDP | USD | + | 0.1394 |
government final consumption expenditure | USD | − | 0.1352 | |
Imports (Inflow of goods and services) | USD | + | 0.1998 | |
exports (inflow of goods and services) | USD | − | 0.1196 | |
Agriculture, forestry, and fishing, value added (% of GDP) | % | + | 0.3105 | |
Industry (including construction), value added (% of GDP) | % | + | 0.0955 | |
Ecological environment subsystem | water resources use | KL per capita | − | 0.1101 |
forest area (% of land area) | % | + | 0.1497 | |
Australian mean temperature anomaly (based on 2011) | °C | − | 0.1494 | |
Australian annual mean rainfall | MM | + | 0.2368 | |
PM2.5 air pollution, mean annual exposure | Micrograms Per Cubic Meter | − | 0.1331 | |
particulate emission damage (% of GNI) | % | − | 0.2209 |
L Level | Classifying Criterion | Types |
---|---|---|
I | 0.00–0.59 | Extreme damage |
II | 0.60–0.79 | Serious damage |
III | 0.80–0.99 | Shortage |
IV | 1.00–1.49 | More adequate |
V | 1.50 and over | Sufficient |
Coordination Level | Classifying Criterion | Types |
---|---|---|
I | 0.00–0.19 | Severely maladjusted |
II | 0.20–0.39 | Moderately maladjusted, |
III | 0.40–0.49 | Slightly maladjusted |
IV | 0.50–0.59 | Barely coordinated |
V | 0.60–0.69 | Moderately coordinated |
VI | 0.70–0.79 | Good coordinated |
VII | 0.80–1.00 | Pre-eminently coordinated |
Year | Energy f(x) | Economy f(x) | Ecological Environment f(x) | C | T | D | Types |
---|---|---|---|---|---|---|---|
2007 | 0.3563 | 0.3232 | 0.5265 | 0.8129 | 0.4020 | 0.5716 | Barely coordinated |
2008 | 0.4059 | 0.5727 | 0.5584 | 0.8992 | 0.5123 | 0.6787 | Moderately coordinated |
2009 | 0.3308 | 0.3216 | 0.5634 | 0.7301 | 0.4053 | 0.5440 | Barely coordinated |
2010 | 0.4345 | 0.3043 | 0.6094 | 0.6996 | 0.4494 | 0.5607 | Barely coordinated |
2011 | 0.2366 | 0.3438 | 0.5610 | 0.5689 | 0.3805 | 0.4652 | slightly maladjusted |
2012 | 0.5736 | 0.5536 | 0.2776 | 0.6328 | 0.4683 | 0.5444 | Barely coordinated |
2013 | 0.6290 | 0.3286 | 0.2142 | 0.4100 | 0.3906 | 0.4002 | slightly maladjusted |
2014 | 0.7435 | 0.4567 | 0.3290 | 0.6001 | 0.5098 | 0.5531 | Barely coordinated |
2015 | 0.7476 | 0.2446 | 0.3483 | 0.3639 | 0.4468 | 0.4033 | slightly maladjusted |
2016 | 0.6725 | 0.5567 | 0.5359 | 0.9558 | 0.5884 | 0.7499 | Good coordinated |
© 2019 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
Yan, X.; Chen, M.; Chen, M.-Y. Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016. Sustainability 2019, 11, 6568. https://doi.org/10.3390/su11236568
Yan X, Chen M, Chen M-Y. Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016. Sustainability. 2019; 11(23):6568. https://doi.org/10.3390/su11236568
Chicago/Turabian StyleYan, Xin, Min Chen, and Mu-Yen Chen. 2019. "Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016" Sustainability 11, no. 23: 6568. https://doi.org/10.3390/su11236568
APA StyleYan, X., Chen, M., & Chen, M. -Y. (2019). Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016. Sustainability, 11(23), 6568. https://doi.org/10.3390/su11236568