4.1. Spatial Pattern Characteristics of County Carbon Elements
Regional collaborative carbon governance is a complex dynamic system consisting of the interconnection and interaction of administrative regions, carbon reduction subjects, and carbon-reduction methods. Under the impetus of collaborative governance strategy, this study summarizes the spatial association of carbon factors in Zhejiang counties through gravity model and social network analysis and proposes a rescaled carbon control system, "Zhejiang County Carbon Control Alliance" based on administrative divisions, to further establish a collaborative carbon reduction governance mechanism.
(1) Linear connections
Through the calculation of the gravitational model, the strength of inter-county linkage was classified into three categories: low linkage (< 0.64), medium linkage (0.64–3.20), and high linkage (> 3.20) based on the natural breakpoint method, and the spatial linkage pattern of county carbon factors in Zhejiang province was obtained. As seen in Fig. 2, the low and medium linkages are reticulated structures, and the overall linkage of northern Zhejiang is higher than that of southern Zhejiang from the concentration of structural lines. The high linkage shows a linear structure, with one linkage connecting counties in Zhoushan, Ningbo, Shaoxing, and Hangzhou and another linkage connecting counties in Taizhou, Wenzhou, and Lishui. Among them, Shangcheng District and Binjiang District in Hangzhou and Dongtou District in Wenzhou have the highest connection intensity with surrounding districts and counties, becoming the polarization center of carbon element connection in Zhejiang Province.
Social network analysis is used to obtain the carbon factor affiliation degree of counties in Zhejiang Province, that is, the county with the strongest carbon factor connection is taken as the preferred place for its affiliation, and the flow direction of carbon factors among counties is determined. In Fig. 3, the green dots represent each county in Zhejiang Province, the black lines between the green dots represent the affiliation relationships of carbon elements among counties, and the arrows on the black lines symbolize the direction of affiliation. The cooperation potential among counties in Zhejiang Province shows the following characteristics: (i) geo-referential, the preferred place for carbon factor affiliation of 89 counties is their neighboring counties in the geo-referential area, which indicates that the direction of the linkage of counties in Zhejiang Province has a strong neighboring direction, and it is easy to form clusters of carbon pool cooperation and cross-domain carbon trading based on geographical space; (ii) center referential. As the "wisdom center, service center, and regulating center" of the development of prefecture-level cities, the stronger the central role of the city, the more it can drive the coordination and construction of regional carbon management. The analysis shows that districts and counties with higher connectedness show obvious central pointingness, of which 56% of the affiliated cooperation areas are the central urban areas under their administrative jurisdiction.
As point-degree centrality indicates the control of subjects over others in the linkage network, the point-out degree can be used to indicate the outward radiation ability of carbon governance in each county. From Fig. 4, the more radiant counties are, the darker they appear, and it can be seen that Hangzhou's Shangcheng, Xiacheng, Binjiang, and Xiaoshan occupy the most central position in the whole synergistic network, have the highest radiating power, and have a higher initiative in facilitating carbon factor sharing and collaboration. The main growth pole radiates to the east and north and forms a converging radiation center with the Haishu, Yinzhou, and Beilun districts of Ningbo City, as well as the Nanhu and Xiuzhou districts of Jiaxing City, which are also radiation cores. In addition, there are four sub-growth poles, Ouhai, Wenling, Jindong, and Kecheng, which have a greater radiation effect on the synergistic sharing of carbon factors in the surrounding counties.
4.2. Boundaries of the cross-county carbon governance alliance
In the context of cross-regional carbon reduction and collaborative governance, the internal microstructure was clustered and analyzed based on the grouped spatial patterns of carbon governance elements in Zhejiang Province. The carbon governance boundary of Zhejiang Province is defined by linkage, cooperation, and radiation, and the scale is shifted upward. In this way, a carbon control center is established to realize carbon responsibility determination, carbon rights allocation, and carbon trading of multiple entities within the boundary and promote internal circulation and external flow.
Taking counties as the basic unit, breaking through the existing administrative, geographical, and economic barriers at the prefecture level in Zhejiang Province; reorganizing counties with high interaction intensity, close ties, and wide radiation range as the main body of region-wide carbon control; strengthening the synergistic management of interests; establishing multi-body boundaries with the main body as the center; reconstructing the counties of Zhejiang Province into twelve geopolitical carbon governance alliances in Fig. 5; and promoting the realization of precise and differentiated cross-regional carbon governance.
County-governance alliances have a high degree of overlap with prefecture-level administrative divisions, indicating that carbon governance alliances are based on administrative management planning to increase the flow of carbon elements, constituting a grouping environment that helps in efficient synergy and precise governance. The overall network density of Zhejiang Province is 0.64. As shown in Table 2, the network density of each alliance is greater than 0.64, indicating that the carbon elements within the alliance are more closely and frequently linked among counties, and the intensity of synergy is higher. Take Alliance 3 as an example, this alliance consists of 8 counties, namely Shangcheng District, Xihu District, Binjiang District, Xiaoshan District, Tonglu County, Lin'an District, Fuyang District, and Zhuji City, which straddles Hangzhou and Shaoxing cities in terms of administrative divisions, and its network centrality and network density are both the highest among alliances, reaching 531.63 and 12.71, respectively, indicating that Alliance 3 has the strongest carbon factor radiation capacity externally and the highest carbon factor The network activity is the highest. Alliance 7 has the largest number of counties, with 12, namely Chun'an County, Jiande City, Lanxi City, Kaihua County, Changshan County, Kecheng District, Qjiang District, Longyou County, Jiangshan City, Suichang County, Songyang County, and Liandu District. Although the network density is the lowest among all alliances, it is still higher than the overall network density of Zhejiang Province at 0.65, and its network centrality is 139.37, which proves that the radiation capacity of the 12 counties is relatively high. Table 3 shows the inter-connectedness of the 12 alliances in Zhejiang Province, which is summed by the inter-connectedness of the districts and counties contained in each alliance, symbolizing the alliance's external carbon flow capacity. From the table, we can see that the linkage between Alliance 2 and Alliance 3 is the highest at 384.73.
Table 2
Analysis of carbon governance alliances
Alliance Number
|
Number of counties
|
Network Center Degree
|
Network Density
|
1
|
5
|
84.68
|
2.28
|
2
|
11
|
517.18
|
10.12
|
3
|
8
|
531.63
|
12.71
|
4
|
6
|
169.86
|
1.76
|
5
|
10
|
170.88
|
3.28
|
6
|
4
|
50.67
|
1.81
|
7
|
12
|
139.37
|
0.65
|
8
|
10
|
164.81
|
1.01
|
9
|
6
|
102.20
|
2.63
|
10
|
5
|
133.70
|
4.60
|
11
|
6
|
107.21
|
5.13
|
12
|
6
|
58.12
|
0.94
|
Table 3. Analysis of alliance linkage degree
|
|
No.
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
1
|
|
37.80
|
14.12
|
6.38
|
14.53
|
2.87
|
2.53
|
2.93
|
1.14
|
1.04
|
0.80
|
0.54
|
2
|
37.80
|
|
384.73
|
25.10
|
20.14
|
3.96
|
21.14
|
13.10
|
3.32
|
3.16
|
2.70
|
2.02
|
3
|
14.12
|
384.73
|
|
40.99
|
24.02
|
3.25
|
30.47
|
21.51
|
3.61
|
3.47
|
3.03
|
2.43
|
4
|
6.38
|
25.10
|
40.99
|
|
35.47
|
3.55
|
8.89
|
26.82
|
8.92
|
8.39
|
3.43
|
1.92
|
5
|
14.53
|
20.14
|
24.02
|
35.47
|
|
28.28
|
6.46
|
16.29
|
10.23
|
8.98
|
4.25
|
2.24
|
6
|
2.87
|
3.96
|
3.25
|
3.55
|
28.28
|
|
1.45
|
2.39
|
1.87
|
1.53
|
0.98
|
0.55
|
7
|
2.53
|
21.14
|
30.47
|
8.89
|
6.46
|
1.45
|
|
34.72
|
4.29
|
5.28
|
9.03
|
15.10
|
8
|
2.93
|
13.10
|
21.51
|
26.82
|
16.29
|
2.39
|
34.72
|
|
14.77
|
13.22
|
11.59
|
7.47
|
9
|
1.14
|
3.32
|
3.61
|
8.92
|
10.23
|
1.87
|
4.29
|
14.77
|
|
40.31
|
10.81
|
2.94
|
10
|
1.04
|
3.16
|
3.47
|
8.39
|
8.98
|
1.53
|
5.28
|
13.22
|
40.31
|
|
43.00
|
5.32
|
11
|
0.80
|
2.70
|
3.03
|
3.43
|
4.25
|
0.98
|
9.03
|
11.59
|
10.81
|
43.00
|
|
17.59
|
12
|
0.54
|
2.02
|
2.43
|
1.92
|
2.24
|
0.55
|
15.10
|
7.47
|
2.94
|
5.32
|
17.59
|
|