Can the Establishment of National Key Ecological Function Areas Enhance Vegetation Carbon Sink? A Quasi-Natural Experiment Evidence from China
Abstract
:1. Introduction
2. Literature Review and Theoretical Analysis
- (1)
- NKEFAs can optimize the pattern of territory development. The NKEFAs expand ecological space, clearly restrict large-scale and high-intensity urbanization and industrialization, and strictly control the development intensity and scope in the territory development according to the carrying capacity of regional resources and environment [24]. Urban construction and industrial development should be concentrated, and stronghold-type development in existing towns with relatively strong carrying capacity of resources and environment requires the full delineation of ecological red lines. The delineation of restricted development areas and ecological red lines promotes the optimization of territorial spatial development pattern, improves the efficiency of land spatial allocation [25], and maintains ecological function while minimizing restrictions on human land use [26].
- (2)
- NKEFAs can promote industrial structure upgrading. The negative list of industrial access in NKEFAs clarifies the list of industries restricted and prohibited from development, implements targeted industrial access and environment access policies and standards, supports the appropriate utilization of special resources, and rationally develops suitable industries. For existing industries that are not suitable for the main function positioning, it will create a crowding-out effect on polluting enterprises [27,28], promote industrial gradient transfer or elimination, and production factors will gradually transfer to the service industry. When industrial policies become stricter, local governments have more incentives to promote the upgrading of industrial structure, eliminate outdated production capacity, and guide the development of less polluting suitable industries, special industries, and service industries such as tourism and sightseeing [29], triggering the inter-industrial flow of production factors and promoting industrial structure upgrading. The upgrading of industrial structure is conducive to the reduction in pollutant emissions, and the accompanying technological upgrade also reduces the constraints of resources and the environmental impact on economic development [30].
- (3)
- NKEFAs can promote labor transfer and mobility. The limitations of large-scale urbanization development and industrial structure upgrading make it difficult for the NKEFAs to carry a larger population, and a part of the population will actively transfer to urbanized areas with more employment opportunities. Territory spatial development will also lead to an orderly transfer of population from restricted development areas to key development areas, and urbanized areas will increase the corresponding labor force to ease employment pressure and increase population density in built-up areas [31]. The population is concentrated on a large scale within the spatial unit of environmental capacity, which promotes the reallocation of factors and resources, and it facilitates the prevention of environmental pollution and the effective use of resources, thereby enhancing and improving the supply of ecological products (Figure 1).
3. Materials and Methods
3.1. Time-Varying DID Model
3.2. Parallel Trend Test and Dynamic Effect
3.3. Variable Selection
- (1)
- Explained variables: carbon sink (CS). The scale of vegetation CS, which is mainly calculated from the net primary productivity (NPP) of vegetation, can reflect the supply capacity of ecological products. Specifically, CS is a process, activity or mechanism that absorbs CO2 from the atmosphere, such as plant photosynthesis [8], while NPP refers to the residual of gross primary productivity (GPP) after deducting the value of respiration of autotrophs (RA), which can be deduced from the CO2 absorbed and the dry matter produced by plant photosynthesis [40], and the chemical equation is 6CO2 + 6H2O→C6H12O6 + 6O2. Vegetation can fix 1.63 kg CO2 per for every 1 kg of dry matter produced, and the carbon content in dry matter accounts for about 45% of the total NPP, so the CO2 that vegetation can fix per unit area is WCO2 = NPP/0.45 × 1.63, its unit is g/m2, and then, it is multiplied by the area covered by vegetation to obtain the scale of CS [41].
- (2)
- Core explanatory variable: NKEFAs
- ①
- The scope of the prefecture-level city (treat). According to the policy document, the first batch covers 436 county-level administrative regions, and the new list covers 240 county-level administrative regions. Since the study scale is prefecture-level cities, if a prefecture-level city jurisdiction covers a county in the list, it will be set as the treatment group and vice versa as the control group, and this policy is finally determined to cover 171 prefecture-level cities (the first batch of 111, the new additional of 60).
- ②
- The time node of policy implementation. According to the promulgation time of the “Main Functional Area Planning” and the time of the new list, it is determined that 2011 is the starting time of the first batch of NKEFAs, and 2016 is the starting time of the new list (approved by the Stata Council in September 2016).
- (3)
- Control variables
3.4. Data Sources
4. Results and Analysis
4.1. Baseline Regression Result
4.2. Parallel Trend Test and Policy Dynamic Effect
4.3. Robustness Test
4.3.1. Placebo Test
4.3.2. PSM-DID
4.3.3. Excluding Other Policy Interference
4.3.4. Substituting Explained Variables
4.3.5. Eliminating Special Samples
4.4. Mechanism Analysis
4.5. Heterogeneity Analysis
4.5.1. Different Ecological Function Types
4.5.2. Different Geographic Regions
4.5.3. Different Quantiles of CS
5. Expanded Analysis
5.1. Whether the Policy Effect of NEKFAs Has Ecological Spillover to the Neighboring Areas?
5.2. Whether the Ecological Objectives of NEKFAs Be Balanced with Economic Growth?
6. Conclusions
7. Policy Implications
- (1)
- Improve the sustainability of the establishment of NKEFAs. The current system of establishing NKEFAs has generally promoted the realization of enhancing ecological products supply and improving environmental quality, and the enhancement effect has become more and more significant over time. The establishment of NKEFAs has effectively stimulated local governments to act in ecological management and environmental protection. To form a long-term positive incentive and avoid the recurrence of ecological problems in NKEFAs, long-term support and supervision and guidance at the national level are necessary to improve the stability and sustainability of policy implementation.
- (2)
- Build a diversified ecological governance and supervision system for different functional area types and different ecological characteristics. For functional areas with poorer ecological endowments, such as the northwestern region, which is mainly a windbreak sand-fixing ecological functional area, the ecological vulnerability is high, and the overall deterioration of the ecological environment has not been fundamentally curbed, so the ecological management of NKEFAs should continue to be strengthened to improve the overall function of the ecosystem. The central government’s transfer funds for NKEFAs need to be tilted more toward these areas, while local governments should continue to increase investment in environmental protection, strengthen ecological environment supervision, and form a long-term operation mechanism of ecological compensation.
- (3)
- Act strictly in accordance with the requirements of the National Main Function Area Planning. On the one hand, the space for human activities should be controlled beyond the delineated ecological red line and coordinated with the environmental carrying capacity of ecological space; the expansion intensity of production space should also be reasonably controlled to improve the efficiency and sustainability of the territory use. On the other hand, actively developing ecological agriculture and service industries introduces more active population migration policies and household registration management policies, attracts labor to green industries, promotes an efficient market-oriented flow of labor, and accelerates the equalization of basic public services between the floating population and local population.
- (4)
- The existence of spatial spillover effect is hard to ignore. Neighboring ecological function areas should actively explore and build a feasible mechanism for the synergistic linkage of cross-regional cooperation in ecological environment management, industrial green development, and territory spatial utilization. Local governments should abandon the ecological management policies of separate governance and beggar-thy-neighbor, and inter-regional experience learning and joint prevention in ecological policies can effectively promote the achievement of ecological goals and the improvement of management efficiency.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
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Variable | Variable Definition | N | Mean | S.D. | Min. | Max. |
---|---|---|---|---|---|---|
Explained variables: | ||||||
CS | Vegetation carbon sink scale (million tons) | 6270 | 31.734 | 35.868 | 0.061 | 430.523 |
Core explanatory variable: | ||||||
DID | NKEFAs | 6270 | 0.198 | 0.398 | 0 | 1 |
Control variables: | ||||||
DEN | Total population/land area (people/km2) | 6270 | 402.861 | 485.234 | 0.656 | 6729.490 |
lnPGDP | Logarithm of GDP per capita (2001 as base period)/RMB yuan | 6270 | 10.010 | 0.937 | 6.898 | 12.657 |
URBAN | Urbanization rate of resident population/% | 6270 | 42.574 | 19.694 | 7.435 | 100 |
STRUC | Gross secondary industry/GDP | 6270 | 0.384 | 0.094 | 0.086 | 0.835 |
GAP | Urban per capita disposable income/rural per capita net income | 6270 | 2.685 | 0.784 | 0.917 | 7.378 |
OPEN | Total import and export trade/GDP | 6270 | 0.187 | 0.375 | 0 | 6.966 |
TRANS | Road mileage/land area (km/km2) | 6270 | 0.801 | 0.559 | 0.009 | 5.887 |
PRE | Average annual precipitation/mm | 6270 | 954.358 | 539.161 | 29.289 | 2680.360 |
TEM | Average annual temperature/°C | 6270 | 13.883 | 5.451 | −2.908 | 25.636 |
SUN | Sunshine hours/h | 6270 | 2068.952 | 511.408 | 784.640 | 3407.62 |
Variables | Explained Variable: CS | |||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
DID | 3.5388 *** (0.1333) | 2.3985 *** (0.1683) | 2.1615 *** (0.1678) | 2.1625 *** (0.1743) |
DEN | — | — | −0.0016 *** (0.0006) | −0.0011 * (0.0005) |
lnPGDP | — | — | 1.4101 *** (0.1239) | 1.2165 *** (0.2812) |
URBAN | — | — | −0.0116 * (0.0064) | −0.0110 * (0.0064) |
STRUC | — | — | 0.7183 (0.7941) | −0.4380 (0.9840) |
GAP | — | — | 0.0328 (0.1280) | −0.0780 (0.1319) |
OPEN | — | — | −0.5821 ** (0.2889) | −0.4847 * (0.2906) |
TRANS | — | — | −0.5008 ** (0.2069) | −0.4486 ** (0.2149) |
PRE | — | — | 0.0007 *** (0.0002) | 0.0006 *** (0.0002) |
TEM | — | — | −0.0327(0.0764) | −0.2245 ** (0.0871) |
SUN | — | — | −0.0004 * (0.0002) | −0.0005 * (0.0003) |
Constant | 31.6003 *** (1.7518) | 28.6806 *** (0.1896) | 19.6504 *** (2.3671) | 25.4192 *** (2.9588) |
Adj-R2 | 0.1062 | 0.1582 | 0.1424 | 0.1688 |
city FE | NO | YES | NO | YES |
year FE | NO | YES | NO | YES |
No. of cities | 330 | 330 | 330 | 330 |
Variables | PSM-DID | Excluding Other Policy Interference | Substituting Explained Variables | Eliminating Special Samples |
---|---|---|---|---|
CS | CS | NDVI | CS | |
(1) | (2) | (3) | (4) | |
DID | 2.2004 *** (0.0043) | 2.1679 *** (0.1781) | 0.0185 *** (0.0011) | 1.9909 *** (0.1895) |
Constant | 27.1356 *** (3.2617) | 25.4126 *** (2.9581) | 0.6039 *** (0.0195) | 21.2040 *** (3.1719) |
Controls | Yes | Yes | Yes | Yes |
Adj-R2 | 0.1757 | 0.1696 | 0.4931 | 0.1692 |
city FE | Yes | Yes | Yes | Yes |
year FE | Yes | Yes | Yes | Yes |
No. of cities | 330 | 330 | 330 | 292 |
Variables | TERRI | INDUS | LABOR | |||
---|---|---|---|---|---|---|
TERRI | CS | INDUS | CS | LABOR | CS | |
(1) | (2) | (3) | (4) | (5) | (6) | |
DID | 0.0025 *** (0.0003) | 2.0658 *** (0.1753) | 0.0121 * (0.0065) | 2.1437 *** (0.1737) | 0.0070 *** (0.0013) | 2.1128 *** (0.1745) |
TERRI | 38.1633 *** (8.4921) | |||||
INDUS | 1.5487 *** (0.2341) | |||||
LABOR | 7.0843 *** (1.7342) | |||||
Constant | 0.4885 *** (0.0045) | 6.7750 (5.0929) | 0.3239 ** (0.1638) | 24.9176 *** (2.9491) | 0.2968 *** (0.0222) | 23.3168 *** (2.9993) |
Controls | Yes | Yes | Yes | Yes | Yes | Yes |
Adj-R2 | 0.3338 | 0.1716 | 0.6547 | 0.3345 | 0.3305 | 0.1711 |
city FE | Yes | Yes | Yes | Yes | Yes | Yes |
year FE | Yes | Yes | Yes | Yes | Yes | Yes |
No. of cities | 330 | 330 | 330 | 330 | 330 | 330 |
Variables | Water Conservation | Soil Conservation | Windbreak Sand-Fixation | Biodiversity Maintenance |
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
DID | 1.1967 *** (0.2137) | 2.0411 *** (0.2815) | 7.7708 *** (0.3853) | 0.6964 *** (0.2543) |
Constant | 22.4709 *** (2.9962) | 26.7325 *** (3.0078) | 25.1438 *** (2.8970) | 24.2242 *** (2.9958) |
Controls | Yes | Yes | Yes | Yes |
Adj-R2 | 0.1516 | 0.1546 | 0.2020 | 0.1482 |
city FE | Yes | Yes | Yes | Yes |
year FE | Yes | Yes | Yes | Yes |
No. of NKEFAs | 95 | 40 | 18 | 52 |
No. of cities | 330 | 330 | 330 | 330 |
Variables | NEC | NC | NWC | SWC | MLY | SEC | West side | East side |
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
DID | 2.4679 *** (0.4665) | 2.0233 *** (0.2149) | 3.7120 *** (0.7461) | 0.7847 * (0.4041) | 0.5737 *** (0.1501) | 0.6091 *** (0.2186) | 3.0197 *** (0.9017) | 1.7315 *** (0.1332) |
Constant | 41.7258 *** (9.8409) | 26.0882 *** (4.9821) | 16.5328 *** (10.7054) | 53.7831 *** (8.1748) | 28.3889 *** (3.5909) | 38.7921 *** (4.5361) | 13.9183 *** (11.7277) | 29.7897 *** (2.3952) |
Controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Adj-R2 | 0.3559 | 0.5711 | 0.2611 | 0.3891 | 0.3576 | 0.2888 | 0.1944 | 0.2338 |
city FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
year FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
No. of cities | 36 | 59 | 63 | 47 | 67 | 58 | 57 | 273 |
Quantile | DID | Controls | City FE | Year FE | No. of Cities | |
---|---|---|---|---|---|---|
(1) | 0.05 | 4.2911 *** (0.1783) | Yes | Yes | Yes | 330 |
(2) | 0.25 | 6.0542 *** (0.1052) | Yes | Yes | Yes | 330 |
(3) | 0.50 | 17.4855 *** (0.2128) | Yes | Yes | Yes | 330 |
(4) | 0.75 | 35.0966 *** (0.2275) | Yes | Yes | Yes | 330 |
(5) | 0.95 | 16.5249 *** (1.1962) | Yes | Yes | Yes | 330 |
Variables | Ecological Spillover Effect | Economic Growth | ||
---|---|---|---|---|
CS | CS | lnGDP | lnPGDP | |
(1) | (2) | (3) | (4) | |
DID | 2.6682 *** (0.4691) | 2.4188 *** (0.4395) | 0.0299 *** (0.0082) | 0.0491 *** (0.0084) |
Spillover effect | 0.5395 *** (0.1644) | 0.4858 *** (0.1656) | ||
Constant | 28.6401 *** (0.3257) | 22.7182 *** (5.2892) | 5.7650 *** (0.0704) | 9.5025 *** (0.0712) |
Controls | No | Yes | Yes | Yes |
Adj-R2 | 0.1606 | 0.1700 | 0.0299 | 0.9498 |
city FE | Yes | Yes | Yes | Yes |
year FE | Yes | Yes | Yes | Yes |
No. of cities | 330 | 330 | 330 | 330 |
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Zhang, T.; Hou, M.; Chu, L.; Wang, L. Can the Establishment of National Key Ecological Function Areas Enhance Vegetation Carbon Sink? A Quasi-Natural Experiment Evidence from China. Int. J. Environ. Res. Public Health 2022, 19, 12215. https://doi.org/10.3390/ijerph191912215
Zhang T, Hou M, Chu L, Wang L. Can the Establishment of National Key Ecological Function Areas Enhance Vegetation Carbon Sink? A Quasi-Natural Experiment Evidence from China. International Journal of Environmental Research and Public Health. 2022; 19(19):12215. https://doi.org/10.3390/ijerph191912215
Chicago/Turabian StyleZhang, Tongyue, Mengyang Hou, Liqi Chu, and Lili Wang. 2022. "Can the Establishment of National Key Ecological Function Areas Enhance Vegetation Carbon Sink? A Quasi-Natural Experiment Evidence from China" International Journal of Environmental Research and Public Health 19, no. 19: 12215. https://doi.org/10.3390/ijerph191912215