Do the National Key Ecological Function Zones Promote Green Development? Evidence from the Yanshan–Taihang Mountainous Area in Hebei Province, China
Abstract
:1. Introduction
2. Model and Data
2.1. Study Area and Framework
2.2. Improved Lotka–Volterra Model
2.2.1. Model Setting
2.2.2. Indicators Selection
2.3. Difference-in-Differences Model
2.3.1. Model Setting
2.3.2. Indicators Selection
- (i)
- Explained variable: Green Development Level (GD)
- (ii)
- Explanatory variable: Establishment of ecological functional zones (EA)
- (iii)
- Control variables
2.4. Data
3. Results and Analysis
3.1. Improved Lotka–Volterra Model Results
3.1.1. The Results of the Improved L–V Model
3.1.2. The Analysis of Green Development Patterns
3.2. DID Model Results
3.2.1. Benchmark Regression Analysis
3.2.2. Parallel Trend Test and Dynamic Effect Analysis
3.2.3. The Heterogeneous Analysis of Green Development Patterns
3.2.4. Robustness Tests
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Zhang, Y.; Wang, W. How does China’s carbon emissions trading (CET) policy affect the investment of CET-covered enterprises? Energy Econ. 2021, 98, 105224. [Google Scholar] [CrossRef]
- Gao, J.; Zou, C.; Zhang, K.; Xu, M.; Wang, Y. The establishment of Chinese ecological conservation redline and insights into improving international protected areas. J. Environ. Manag. 2020, 264, 110505. [Google Scholar] [CrossRef] [PubMed]
- D’Amato, D.; Korhonen, J. Integrating the green economy, circular economy and bioeconomy in a strategic sustainability framework. Ecol. Econ. 2021, 188, 107143. [Google Scholar] [CrossRef]
- Liu, J.; Qu, J.; Zhao, K. Is China’s development conforms to the Environmental Kuznets Curve hypothesis and the pollution haven hypothesis? J. Clean. Prod. 2019, 234, 787–796. [Google Scholar] [CrossRef]
- BenDor, T.K.; Spurlock, D.; Woodruff, S.C.; Olander, L. A research agenda for ecosystem services in American environmental and land use planning. Cities 2017, 60, 260–271. [Google Scholar] [CrossRef]
- Mamat, K.; Du, P.; Ding, J. Ecological function regionalization of cultural heritage sites in Turpan, China, based on GIS. Arab. J. Geosci. 2017, 10, 90. [Google Scholar] [CrossRef]
- Du, W.; Yan, H.; Feng, Z.; Yang, Y.; Liu, F. The supply-consumption relationship of ecological resources under ecological civilization construction in China. Resour. Conserv. Recycl. 2021, 172, 105679. [Google Scholar] [CrossRef]
- Fan, J.; Sun, W.; Zhou, K.; Chen, D. Major function oriented zone: New method of spatial regulation for reshaping regional development pattern in China. Chin. Geogr. Sci. 2012, 22, 196–209. [Google Scholar] [CrossRef]
- Chen, M.; Liang, L.; Wang, Z.; Zhang, W.; Yu, J.; Liang, Y. Geographical thoughts on the relationship between ‘Beautiful China’and land spatial planning. J. Geogr. Sci. 2020, 30, 705–723. [Google Scholar] [CrossRef]
- Zhao, X.; Chen, H.; Zhao, H.; Xue, B. Farmer households’ livelihood resilience in ecological-function areas: Case of the Yellow River water source area of China. Environ. Dev. Sustain. 2021, 24, 9665–9686. [Google Scholar] [CrossRef]
- Zhao, Y.; Chi, W.; Kuang, W.; Bao, Y.; Ding, G. Ecological and environmental consequences of ecological projects in the Beijing–Tianjin sand source region. Ecol. Indic. 2020, 112, 106111. [Google Scholar] [CrossRef]
- Zhang, P. Target interactions and target aspiration level adaptation: How do government leaders tackle the “environment-economy” nexus? Public Adm. Rev. 2021, 81, 220–230. [Google Scholar] [CrossRef]
- Cole, K.A. A Market-Based Approach to the Protection of Instream Flow: Allowing a Charitable Contribution Deduction for the Donation of a Conservation Easement in Water Rights. Hastings W.-Nw. J. Envt’l L. Pol’y 2008, 14, 1153. [Google Scholar]
- Chen, Y.; Wang, J. Ecological security early-warning in central Yunnan Province, China, based on the gray model. Ecol. Indic. 2020, 111, 106000. [Google Scholar] [CrossRef]
- Zhai, J.; Liu, Y.; Hou, P.; Xiao, T.; Cao, G. Water conservation service assessment and its spatiotemporal features in national key ecological function zones. Adv. Meteorol. 2016, 2016, 5194091. [Google Scholar] [CrossRef]
- Xu, J.; Xiao, Y.; Xie, G.; Wang, Y.; Lei, G. Assessment of the benefit diffusion of windbreak and sand fixation service in National Key Ecological Function areas in China. Aeolian Res. 2021, 52, 100728. [Google Scholar] [CrossRef]
- Webb, N.P.; Kachergis, E.; Miller, S.W.; McCord, S.E.; Bestelmeyer, B.T.; Brown, J.R.; Chappell, A.; Edwards, B.L.; Herrick, J.E.; Karl, J.W. Indicators and benchmarks for wind erosion monitoring, assessment and management. Ecol. Indic. 2020, 110, 105881. [Google Scholar] [CrossRef]
- Caixia, Z.; Leiming, Z.; Shimei, L.; Changshun, Z. Soil conservation of national key ecological function areas. J. Resour. Ecol. 2015, 6, 397–404. [Google Scholar] [CrossRef]
- Zhang, Y.; Yang, Y.; Chen, Z.; Zhang, S. Multi-criteria assessment of the resilience of ecological function areas in China with a focus on ecological restoration. Ecol. Indic. 2020, 119, 106862. [Google Scholar] [CrossRef]
- Grieg-Gran, M. Fiscal incentives for biodiversity conservation: The ICMS Ecológico in Brazil. Int. Inst. Environ. Dev. Environ. Econ. Programme 2000. [Google Scholar] [CrossRef]
- Gong, C.; Zhang, J.; Liu, H. Do industrial pollution activities in China respond to ecological fiscal transfers? Evidence from payments to national key ecological function zones. J. Environ. Plan. Manag. 2021, 64, 1184–1203. [Google Scholar] [CrossRef]
- Liu, X.; Wang, Y. Analysis of current research on key ecological function zones in China. World For. Res. 2014, 27, 93–96. [Google Scholar]
- Ouyang, Z.; Zheng, H.; Xiao, Y.; Polasky, S.; Liu, J.; Xu, W.; Wang, Q.; Zhang, L.; Xiao, Y.; Rao, E. Improvements in ecosystem services from investments in natural capital. Science 2016, 352, 1455–1459. [Google Scholar] [CrossRef]
- Hooli, L.J. Resilience of the poorest: Coping strategies and indigenous knowledge of living with the floods in Northern Namibia. Reg. Environ. Change 2015, 16, 695–707. [Google Scholar] [CrossRef]
- Carr, E.R.; Kettle, N.P.; Hoskins, A. Evaluating poverty–environment dynamics. Int. J. Sustain. Dev. World Ecol. 2009, 16, 87–93. [Google Scholar] [CrossRef]
- Guo, L.; Qu, Y.; Tseng, M. The interaction effects of environmental regulation and technological innovation on regional green growth performance. J. Clean. Prod. 2017, 162, 894–902. [Google Scholar] [CrossRef]
- Jian, L.; Sohail, M.T.; Ullah, S.; Majeed, M.T. Examining the role of non-economic factors in energy consumption and CO2 emissions in China: Policy options for the green economy. Environ. Sci. Pollut. Res. 2021, 28, 67667–67676. [Google Scholar] [CrossRef]
- Pradhan, B.K.; Ghosh, J. A computable general equilibrium (CGE) assessment of technological progress and carbon pricing in India’s green energy transition via furthering its renewable capacity. Energy Econ. 2022, 106, 105788. [Google Scholar] [CrossRef]
- D’Amato, A.; Mazzanti, M.; Nicolli, F. Green technologies and environmental policies for sustainable development: Testing direct and indirect impacts. J. Clean. Prod. 2021, 309, 127060. [Google Scholar] [CrossRef]
- Khan, S.A.R.; Qianli, D. Does national scale economic and environmental indicators spur logistics performance? Evidence from UK. Environ. Sci. Pollut. Res. 2017, 24, 26692–26705. [Google Scholar] [CrossRef]
- Bhatia, M.S.; Gangwani, K.K. Green supply chain management: Scientometric review and analysis of empirical research. J. Clean. Prod. 2021, 284, 124722. [Google Scholar] [CrossRef]
- Zhang, D.; Zheng, M.; Feng, G.; Chang, C. Does an environmental policy bring to green innovation in renewable energy? Renew. Energy 2022, 195, 1113–1124. [Google Scholar] [CrossRef]
- Yumei, H.; Iqbal, W.; Irfan, M.; Fatima, A. The dynamics of public spending on sustainable green economy: Role of technological innovation and industrial structure effects. Environ. Sci. Pollut. Res. 2022, 29, 22970–22988. [Google Scholar] [CrossRef] [PubMed]
- Khan, S.A.R.; Quddoos, M.U.; Akhtar, M.H.; Rafique, A.; Hayat, M.; Gulzar, S.; Yu, Z. Re-investigating the nexuses of renewable energy, natural resources and transport services: A roadmap towards sustainable development. Environ. Sci. Pollut. Res. 2022, 29, 13564–13579. [Google Scholar] [CrossRef] [PubMed]
- Khan, S.A.R.; Yu, Z.; Umar, M.; Zia Ul Haq, H.M.; Tanveer, M.; Janjua, L.R. Renewable energy and advanced logistical infrastructure: Carbon-free economic development. Sustain. Dev. 2021, 30, 693–702. [Google Scholar] [CrossRef]
- Feng, Z.; Chen, W. Environmental regulation, green innovation, and industrial green development: An empirical analysis based on the Spatial Durbin model. Sustainability 2018, 10, 223. [Google Scholar] [CrossRef]
- Song, Y.; Yang, L.; Sindakis, S.; Aggarwal, S.; Chen, C. Analyzing the Role of High-Tech Industrial Agglomeration in Green Transformation and Upgrading of Manufacturing Industry: The Case of China. J. Knowl. Econ. 2022, 20, 1–31. [Google Scholar] [CrossRef]
- Cui, L.; Weng, S.; Nadeem, A.M.; Rafique, M.Z.; Shahzad, U. Exploring the role of renewable energy, urbanization and structural change for environmental sustainability: Comparative analysis for practical implications. Renew. Energy 2022, 184, 215–224. [Google Scholar] [CrossRef]
- Khan, S.A.R.; Ponce, P.; Yu, Z.; Golpîra, H.; Mathew, M. Environmental technology and wastewater treatment: Strategies to achieve environmental sustainability. Chemosphere 2022, 286, 131532. [Google Scholar] [CrossRef]
- Zou, H.; Zhang, Y. Does environmental regulatory system drive the green development of China’s pollution-intensive industries? J. Clean. Prod. 2022, 330, 129832. [Google Scholar] [CrossRef]
- Sun, H.; Chen, F. The impact of green finance on China’s regional energy consumption structure based on system GMM. Resour. Policy 2022, 76, 102588. [Google Scholar] [CrossRef]
- Chen, D.; Pan, Y.; Jin, X.; Du, H.; Li, M.; Jiang, P. The delineation of ecological redline area for catchment sustainable management from the perspective of ecosystem services and social needs: A case study of the Xiangjiang watershed, China. Ecol. Indic. 2021, 121, 107130. [Google Scholar] [CrossRef]
- Zhang, M.; Bao, Y.; Xu, J.; Han, A.; Liu, X.; Zhang, J.; Tong, Z. Ecological security evaluation and ecological regulation approach of East-Liao River basin based on ecological function area. Ecol. Indic. 2021, 132, 108255. [Google Scholar] [CrossRef]
- Lee, S.; Kim, M.; Park, Y. ICT Co-evolution and Korean ICT strategy—An analysis based on patent data. Telecommun. Policy 2009, 33, 253–271. [Google Scholar] [CrossRef]
- Du, Y.; Song, B.; Duan, H.; Tsvetanov, T.G.; Wu, Y. Multi-renewable management: Interactions between wind and solar within uncertain technology ecological system. Energy Convers. Manag. 2019, 187, 232–247. [Google Scholar] [CrossRef]
- Chakrabarti, A.S. Stochastic Lotka–Volterra equations: A model of lagged diffusion of technology in an interconnected world. Phys. A Stat. Mech. Its Appl. 2016, 442, 214–223. [Google Scholar] [CrossRef]
- Capello, R.; Faggian, A. An economic-ecological model of urban growth and urban externalities: Empirical evidence from Italy. Ecol. Econ. 2002, 40, 181–198. [Google Scholar] [CrossRef]
- Rodriguez-Gonzalez, P.T.; Rico-Martinez, R.; Rico-Ramirez, V. Effect of feedback loops on the sustainability and resilience of human-ecosystems. Ecol. Model. 2020, 426, 109018. [Google Scholar] [CrossRef]
- Van Donkelaar, A.; Martin, R.V.; Brauer, M.; Hsu, N.C.; Kahn, R.A.; Levy, R.C.; Lyapustin, A.; Sayer, A.M.; Winker, D.M. Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors. Environ. Sci. Technol. 2016, 50, 3762–3772. [Google Scholar] [CrossRef]
- Yanhua, G.; Lianjun, T.; Lin, M. The level of green development and obstacle factors in the limited development ecological zone of Jilin Province. Acta Ecol. Sin. 2020, 40, 2463–2472. [Google Scholar]
- Jia, R.; Shao, S.; Yang, L. High-speed rail and CO2 emissions in urban China: A spatial difference-in-differences approach. Energy Econ. 2021, 99, 105271. [Google Scholar] [CrossRef]
- Pan, D.; Tang, J. The effects of heterogeneous environmental regulations on water pollution control: Quasi-natural experimental evidence from China. Sci. Total Environ. 2021, 751, 141550. [Google Scholar] [CrossRef] [PubMed]
- Cao, H.; Qi, Y.; Chen, J.; Shao, S.; Lin, S. Incentive and coordination: Ecological fiscal transfers’ effects on eco-environmental quality. Environ. Impact Assess. Rev. 2020, 87, 106518. [Google Scholar] [CrossRef]
- Du, J.; Fang, S.; Sheng, Z.; Wu, J.; Quan, Z.; Fu, Q. Variations in vegetation dynamics and its cause in national key ecological function zones in China. Environ. Sci. Pollut. Res. 2020, 27, 30145–30161. [Google Scholar] [CrossRef]
- Jiang, W. Can Environmental Protection in Ecological Functional Zones Break Free from the Constraints of Focusing Just on Economic Benefits?—A Case Study of the Plateau Ecological Zone’s Tiamitcheen. Chin. J. Urban Environ. Stud. 2018, 6, 1850018. [Google Scholar] [CrossRef]
- Sun, M.; Yang, R.; Li, X.; Zhang, L.; Liu, Q. Designing a path for the sustainable development of key ecological function zones: A case study of southwest China. Glob. Ecol. Conserv. 2021, 31, e01840. [Google Scholar] [CrossRef]
- Li, G.; Li, L.; Li, X.; Chen, Y. Can the establishment of National Key Ecological Functional Zones improve air quality? An empirical study from China. PLoS ONE 2021, 16, e246257. [Google Scholar] [CrossRef]
First Level Indicators | Second Level Indicators | Unit of Measurement | Indicator Weighting | Positive/Negative |
---|---|---|---|---|
Environmental Governance | Harmless disposal rate of domestic waste | % | 0.0988 | Positive |
Centralized sewage treatment rate | % | 0.1004 | Positive | |
Quality of growth | GDP | million yuan | 0.1054 | Positive |
The proportion of tertiary industry output value | % | 0.1039 | Positive | |
Disposable income of urban residents | yuan/person | 0.0905 | Positive | |
Financial revenue | million yuan | 0.1052 | Positive | |
Financial Expenditure | million yuan | 0.0944 | Positive | |
Ecological Protection | Ecological Environment Index | % | 0.1212 | Positive |
The annual average value of PM2.5 concentration | μg/m3 | 0.0913 | Negative | |
Sulfur dioxide emission | million tons | 0.0890 | Negative |
Variable | Variable Description | Number of Samples | Mean | Standard Deviation | Min | Max |
---|---|---|---|---|---|---|
GD | Green Development Level | 384 | 0.4992 | 0.1077 | 0.2619 | 0.8711 |
EA | With or without NKEFZs | 384 | 0.3594 | 0.4804 | 0 | 1 |
IN | Industrial development level | 384 | 0.4390 | 0.1427 | 0.0534 | 0.7696 |
AR | Agricultural development level | 384 | 0.1590 | 0.1073 | 0.0020 | 0.4677 |
EC | Agro-ecological quality | 384 | 0.8928 | 0.8568 | −2.8538 | 3.3605 |
VE | Greening level | 384 | 0.7317 | 0.0756 | 0.4517 | 0.8644 |
Pattern | Classification Basis | Performances |
---|---|---|
Low-High | α↑; β↓; R↑ | Ecologically weaker, economically stronger |
High-Low | α↓; β↑; R↓ | Ecologically stronger, economically weaker |
High-High | α↑; β↑; R- | Ecologically stronger, economically stronger |
Low-Low | α↓; β↓; R- | Ecologically weaker, economically weaker |
Variables | (1) | (2) | (3) |
---|---|---|---|
EA | −0.0411 ** (0.0133) | −0.0232 (0.0143) | −0.0309 *** (0.0103) |
IN | −0.0703 (0.0444) | −0.2081 *** (0.0538) | |
AR | −0.2460 *** (0.0619) | −0.0095 (0.1119) | |
EC | −0.0035 ** (0.0015) | −0.0006 (0.0010) | |
VE | 0.1487 ** (0.0778) | 0.3458 *** (0.1314) | |
Time fixed | NO | NO | YES |
City fixed | NO | NO | YES |
N | 384 | 384 | 384 |
R2 | 0.8360 | 0.1163 | 0.8501 |
Variables | (1) Low-High | (2) High-Low | (3) Low-Low |
---|---|---|---|
EA | −0.0433 ** (0.0211) | −0.0469 *** (0.0161) | 0.0081 (0.0151) |
IN | 0.0624 (0.1355) | −0.1734 (0.1132) | −0.1737 *** (0.0673) |
AR | 1.0922 *** (0.3487) | −0.0647 (0.1803) | −0.1991 (0.2131) |
EC | 0.0037 (0.0044) | 0.0015 (0.0017) | −0.0011 (0.0014) |
VE | −0.3204 (0.2068) | 0.4524 ** (0.2016) | 0.7051 *** (0.2188) |
Time fixed | YES | YES | YES |
City fixed | YES | YES | YES |
N | 54 | 102 | 148 |
R2 | 0.9826 | 0.7929 | 0.7863 |
Variables | (1) | (2) | (3) |
---|---|---|---|
Random Grouping | PSM-DID | Changing the Sample Range | |
EA | −0.0069 (0.0102) | −0.0302 * (0.0172) | −0.0298 *** (0.0107) |
Variable control | YES | YES | YES |
Time fixed | YES | YES | YES |
City fixed | YES | YES | YES |
R2 | 0.8503 | 0.8211 | 0.8256 |
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Liu, M.; Zhang, G.; Yang, D. Do the National Key Ecological Function Zones Promote Green Development? Evidence from the Yanshan–Taihang Mountainous Area in Hebei Province, China. Sustainability 2022, 14, 10364. https://doi.org/10.3390/su141610364
Liu M, Zhang G, Yang D. Do the National Key Ecological Function Zones Promote Green Development? Evidence from the Yanshan–Taihang Mountainous Area in Hebei Province, China. Sustainability. 2022; 14(16):10364. https://doi.org/10.3390/su141610364
Chicago/Turabian StyleLiu, Meiyu, Guofeng Zhang, and Du Yang. 2022. "Do the National Key Ecological Function Zones Promote Green Development? Evidence from the Yanshan–Taihang Mountainous Area in Hebei Province, China" Sustainability 14, no. 16: 10364. https://doi.org/10.3390/su141610364