Carbon Sequestration Capacity after Ecological Restoration of Open-Pit Mines: A Case Study in Yangtze River Basin, Jurong City, Jiangsu Province

Abstract

Open-pit mining seriously damages the original vegetation community and soil layer and disturbs the carbon cycle of vegetation and soil, causing instability in the mining ecosystem and decrease in the carbon sequestration capacity of the mining area. With the deepening of environmental awareness and the influence of related policies, the ecological restoration of open-pit mines has been promoted. The mining ecosystem is distinct owing to the disperse distribution of mines and small scale of single mines. However, the carbon sequestration capability of mines after ecological restoration has not been clearly evaluated. Therefore, this study evaluated the carbon sequestration capacity of restoration mines, taking the mines of the Yangtze River Basin in Jurong City, Jiangsu Province as the research objects. Firstly, the visual effects of the vegetation and soil in their current status were determined through field investigation, the methods for sampling and data collection for the vegetation and soil were selected, and the specific laboratory tests such as the vegetation carbon content and soil organic carbon were clarified. Meanwhile, the evaluation system consisting of three aspects and nine evaluation indexes was established by using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE). The process of evaluation included the following: the establishment of the judgment matrix, calculation of the index weight, determination of the membership function, and establishment of the fuzzy membership matrix. Finally, the evaluation results of the restoration mines were determined with the ‘excellent, good, normal and poor’ grade classification according to the evaluation standards for each index proposed considering the data of the field investigation and laboratory tests. The results indicated that (1) the evaluation results of the mines’ carbon sequestration capacity were of excellent and good grade at a proportion of 62.5% and 37.5%, which was in line with the field investigation results and demonstrated the carbon sequestration capacity of all the restored mines was effectively improved; and (2) the weights of the criterion layer were ranked as system stability > vegetation > soil with the largest value of 0.547, indicating the stability of the system is the main factor in the carbon sequestration capacity of the mines and the sustainability of the vegetation community and the stability of soil fixation on the slope. The proposed evaluation system effectively evaluates the short-term carbon sequestration capability of the restoration mining system according to the visual effects and the laboratory testing results, objectively reflecting the carbon sequestration capacity via qualitative assessment and quantitative analysis. The evaluation method is relatively applicable and reliable for restoration mines and can provide a reference for similar ecological restoration engineering.

1. Introduction

Open-pit mining seriously damages the ecological environment by destroying original vegetation and excavating soil mass and rock mass, leading to issues such as soil erosion, land pollution, and geological hazards [1,2,3]. Mining significantly disrupts the ‘vegetation-soil carbon pool’ in the mining area, leading to a decrease in soil organic carbon and the photosynthetic carbon fixation of vegetation [4,5]. As a result, the carbon sequestration capacity of the mining ecosystem rapidly decreases and gradually transforms into a carbon source. In recent years, the United Nations has put forward the need to restore ecosystems (including mining ecosystems) to improve the stability and sustainability of ecosystems [6]. Additionally, with the influence of the carbon peak and carbon neutrality goals and other policies in China, the ecological restoration of open-pit mines has been accelerated. Therefore, establishing an evaluation system for the carbon sequestration capacity of open-pit mines after ecological restoration is of great significance to assess the effect of the restoration of ecosystems and achieve the dual carbon goals.

The ecological restoration of mines mainly relies on measures and technologies via human intervention to gradually restore the mining ecosystem [7,8]. Measures and technologies that have been studied and developed include soil remediation and vegetation rebuilding. Soil remediation can be divided into physical remediation, chemical remediation, and biological remediation [9,10,11,12], and the effect of soil restoration is studied via factors such as the soil microbial indicators, the accumulation of soil organic carbon, and water-holding capacity [13,14,15]. The vegetation rebuilding techniques applied in instances mainly include vegetation-growing concrete, vegetative net, and vegetation bag [16,17,18], and the vegetation restoration effect is evaluated by indicators such as remote sensing data and images, soil seed bank, and vegetation diversity [19,20,21]. Therefore, the soil quality and vegetation growth state of the restoration mines have been greatly improved.

Although the ecological restoration effect of mines is verified by studies, the capacity and mechanism of carbon sequestration has not been clearly evaluated. Some studies reveal that the key approaches of the carbon sink after ecological restoration are related to vegetation and soil [5,22] and discuss the interrelationship between them in the process of carbon sequestration [23,24]. Meanwhile, a computation model, modeling, and testing are utilized to quantify or forecast the carbon sequestration of the mining site or the soil organic carbon [25,26,27,28]. Therefore, the analysis provides guidelines for evaluating the carbon sequestration capability of open-pit mines after ecological restoration.

Choosing an appropriate evaluation method can enhance the objectivity and reliability of the evaluation results. The combination of the analytic hierarchy process (AHP) and the analytic hierarchy process (FCE) can evaluate problems via qualitative and quantitative methods according to the relationship among the indexes [29,30]. An evaluation model, by using the AHP-FCE method, has been applied in assessing ecosystems. For instance, to enhance the sustainability of the distinct ecosystem called Mulberry-Dyke and Fish-Pond System, the AHP-FCE method is used to assess the provision, regulation, and cultural services from the viewpoint of ecosystem services [31]. For the restoration mines, some studies use the AHP-FCE method to establish different evaluation systems for various evaluation goals. Owing to the fact that many evaluation goals related to restoration mines have been effectively evaluated, such as the ecological restoration effects of slopes [32,33] and difficulty of limestone mine restoration [34], the AHP-FCE method can be introduced to evaluate the carbon sequestration capability of restoration mines.

According to the literature review, it can be concluded that most of the studies related to mine ecological restoration focus on the technologies for vegetation rebuilding and soil reconstruction, while there are some studies assessing the environmental benefit and restoration effect of the ecological restoration engineering and other ecosystems using the AHP-FCE method. Although there are some studies on carbon sequestration that mainly focus on large-scale ecosystems via quantitative calculation, the evaluation of carbon sequestration on small-scale ecosystems and the establishment of the evaluation system is relatively little. Owing to the fact that the restoration mining ecosystem has the characteristics of the disperse distribution of mines and the small scale of single mines and traditional restoration measures concentrate on soil reconstruction and vegetation rebuilding, the establishment of the evaluation system for the carbon sequestration capability within the short term (3–5a) is of practical significance considering the current status of the vegetation community and soil layer. Therefore, taking specific mines in the Yangtze River Basin, Jurong City, Jiangsu Province as the research objects, the evaluation system including three aspects and nine evaluation indexes was proposed considering the visual effects and carbon content properties of the vegetation and soil by combining the content, experience, and research direction of the existing studies. The evaluation results were comprehensively obtained from the field investigation for the current status of restored mines, laboratory tests about the carbon content level of the vegetation and soil, and the evaluation system with different indexes. The research not only presents an evaluation system to evaluate the ecological restoration effect from the viewpoint of the carbon sequestration capability of restored mines by combining the qualitative assessment and quantitative analysis from the field investigation and indoor work, but also provides a reference for the similar evaluation of ecological restoration engineering and the carbon sequestration capability of other small-scale ecosystems.

2. Method

2.1. Brief Introduction of Study Area

The study area is in the northern part of Jurong City, Jiangsu Province with rich mineral resources. The open-pit mines are located within 10 km of the Yangtze River Basin, mainly concentrated near Baohua Mountain (Figure 1). The terrain of the research area mainly consists of low mountains, hills, downlands, gentle slopes, and mountain valleys. The water system in the research area is well developed, and the climate has the characteristics of abundant rainfall and ample sunshine.

During the rapid economic development period, quarrying and mining activities led to the formation of uneven rock slopes, making it difficult for ecological restoration due to a total damaged area of 246.88 hm². With the awareness of environmental protection and the enforcement of relevant protection policies, large-scale ecological restoration measures were carried out on the open-pit mining areas in the study area during the period of 2018–2020, which led to great improvement in the ecological environment.

2.2. Ecological Restoration Effect on Mines

The field investigation was conducted on mines in the study area to find out the restoration status of vegetation and soil. The mining objects in the study area are mostly building materials and stone materials (such as limestone, sandstone, dolomite, etc.), leading to the formation of rock slopes. The selection of the restoration measures is influenced by the current status and geological conditions of the slope, such as the height and angle of the slope, lithology, weathering degree, etc. The investigation results indicated that the restoration measures could be divided into slope reinforcement, soil reconstruction, and vegetation rebuilding.

1.

Slope reinforcement

The excavation process and long-term exposure lead to the decline in rock mass quality and the tendency to form geological hazards such as landslides, debris flow, etc. Therefore, to improve the slope stability and ensure the fixed carbon stored in the stable strata, the slope reinforcement measures area mainly includes slope cutting, anchor cables, protective nets, and a drainage–interception system.

2.

Soil reconstruction

The original soil is detached via excavation and transportation, resulting in a lower content and quality of soil remaining in the mining area. To ensure the soil fertility and the survival rate of vegetation, related treatments are taken to improve the organic content of soil used for reconstruction.

3.

Vegetation rebuilding

Vegetation rebuilding is a significant method to improve vegetation coverage after soil reconstruction. Although the growth state and the dominant type of vegetation are different in the study area, the shrub is the most selected type due to the growth advantage. The schemes and distribution characteristics of vegetation are shown in

Table 1. Main schemes and distribution characteristics of vegetation.

Main Combination Patterns		Distribution Characteristics
Scheme	Vegetation Types
Scheme 1	Herbs	The scheme usually occurs in mines with small areas, low slope heights, and gentle slopes. The vegetation is distributed in all areas of the mine.
Scheme 2	Shrubs
Scheme 3	Herbs + Shrubs	The scheme is the most common and occurs in small to medium-sized mines. The dominant plants are usually shrubs with good survival ability, distributing on slopes, slope platforms, and bottom of the mines, while the herbs are in a relatively small living space.
Scheme 4	Herbs + Trees	The scheme usually occurs in abandoned mines or mines with small changes on the terrain. Trees are planted at intervals of length and width at a certain distance, with herbs under the trees.
Scheme 5	Herbs + Shrubs + Trees	The scheme is relatively common while the distribution range of various vegetation is relatively fixed. The shrubs are usually located on the slopes, slope platforms, and the bottom of the mines; the trees are usually on the bottom of the mines; the herbaceous plants are under the trees and shrubs or in a specific area as the dominant species. Some mines with large-area slope platforms choose to plant trees in the platforms.

.

According to the field investigation results of the restoration mines and the data collected in the mines of the study area, 8 mines after ecological restoration were selected for vegetation and soil sampling (Figure 2). The description and the information of the 8 specific restoration mines are shown in

Table 2. The description and the information of the selected restoration mines.

No.	Location	Mining Object	Soil Type	Restoration Measures	Finish Time	Size (hm2)	Slopes Characteristics	Dominant Vegetation
M1	The southeast of the Xianglu Mountain, adjacent to Road X202	Limestone	Sandy Soil	Slope cutting, soil spray sowing, interception and drainage system, and irrigation system	2020.12	2.83	4 slopes and 3 slope pathways with the slope gradient of 25–40°	Indigofera tinctoria L.
M2	The south of the Shangmeng Village and the west of the Hongshi Village	Limestone	Sandy Soil	Slope cutting, passive prevention net, soil spray sowing, interception and drainage system, and irrigation system	2020.12	20.34	2–3 slopes and 1–2 slope pathways with the slope gradient of 35–40°	Amorpha fruticosa L.
M3	The south of the Nijia Mountain and the west of the Hanjiabian Village, adjacent to Langya Road	Limestone	Cohesive Soil	Slope cutting, soil spray sowing, interception and drainage system, and irrigation system	2020.8	3.24	3 slopes and 2 slope pathways with the slope gradient of 35–40°	Indigofera tinctoria L. and Solidago canadensis L.
M4	The southeast of the Zhujiabian Village, adjacent to Road G312	Limestone and dolomite	Cohesive Soil	Slope cutting, soil spray sowing, interception and drainage system, and irrigation system	2020.12	1.88	1–2 slopes and 1 slope pathway with the slope gradient of 30–40°	Solidago canadensis L. and Indigofera tinctoria L.
M5	The south of Huangzhixin auto shop, adjacent to Jiangcheng Road	Limestone	Sandy Soil	Slope cutting, soil spray sowing, interception and drainage system, and irrigation system	2019.12	11.25	2–6 slopes and 1–5 slope pathways with the slope gradient of 30–70°	Robinia pseudoacacia L. and Solidago canadensis L.
M6	The west side of Zhuli village, adjacent to left side of Zhouwang Road	Clay	Cohesive Soil	Land leveling and sowing	2021.1	2.16	Wastelands of the mining area, with the slope gradient of 5–10°	Solidago canadensis L.
M7	The northeast side of Sujiabian village and the Shenkeng Reservoir, adjacent to Road G312	Limestone	Gravelly Soil	Slope cutting, retaining wall, soil spray sowing, interception and drainage system, and irrigation system	2021.4	2.57	2 slopes and 1 slope pathway with the slope gradient of 25–35°	Solidago canadensis L. and Indigofera tinctoria L.
M8	The east side of Jinlong Community, adjacent to Road G312	Limestone	Cohesive Soil	Slope cutting, soil spray sowing, interception and drainage system, and irrigation system	2021.3	7.23	3 slopes and 2 slope pathways with the slope gradient of 20–35°	Solidago canadensis L. and Indigofera tinctoria L.

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2.3. Approaches for Carbon Sequestration of Mines after Ecological Restoration

2.3.1. Carbon Sequestration Approaches Analysis of Ecological Restoration Mines

It can be concluded that the main measures causing the obvious visual effect of ecological restoration are soil reconstruction and vegetation rebuilding, which efficiently promote a transforming role in the carbon cycle of the mining ecosystem from the carbon source to the carbon sink. The main approaches for the carbon sequestration of the restoration mines are as follows (Figure 3).

1.

Vegetation

The biomass and carbon content of vegetation in the mines are key to the carbon storage of mining vegetation. The vegetation can absorb CO₂ from the atmosphere and convert it into O₂ via photosynthesis and photosynthetic products through accumulation carbon compounds, which are released into the atmosphere and, respectively, stored in branches, stems, leaves, and roots [5]. Vegetation roots can also transport organic carbon materials to the soil, indirectly affecting soil organism activities and the soil carbon sequestration capacity. What is more, the young vegetation used for restoration with the characteristic of fast growth ensures the short-term carbon sequestration of vegetation.

2.

Soil

Soil is the largest carbon pool in terrestrial ecosystems, which can be divided into organic carbon and inorganic carbon. Owing to the low activity and difficulty of the transformation of inorganic carbon, soil carbon sequestration is mainly measured by the organic carbon content. Soil absorbs CO₂ from the atmosphere mainly through the vegetation root and soil organism [22]. The organic matter brought by dead matter or litter is the main source of nutrients in the soil, increasing the content of organic matter and soil organism activity. Soil aggregates can convert inorganic carbon and organic carbon into a steady state, enhancing the fixation capacity of carbon in soil [35]. In addition, vegetation plays a role in the maintenance of soil aggregates and soil organism activities.

3.

Soil Organisms

Soil organisms are the link between the vegetation and soil for carbon sequestration, playing an important role in facilitating carbon sequestration on a global scale [36]. The organism activities and secretions of soil organisms can participate in the carbon cycle such as the synthesis, decomposition, and fixation of carbon materials by directly fixing CO₂ with the natural pathways.

2.3.2. Selection of Carbon Pools of Ecological Restoration Mines

At present, studies on the carbon sequestration capability of terrestrial ecosystems mainly categorize or quantify from 5 carbon pools: aboveground biomass, underground biomass, dead matter, litter, and soil organic carbon [37,38]. The selection of carbon pools should follow conservative principles according to the actual situation of the mines after ecological restoration.

Based on the results of the field investigation and the analysis of the main approaches for carbon sequestration, the vegetation and soil are the important approaches. Therefore, the vegetation including the aboveground part and underground roots and soil are the non-ignorable carbon pools. The remaining carbon pools should be reasonably judged based on the restoration status. The carbon pools for the mines are shown in

Table 3. The types and selection reason of carbon pools for the mines in the study area.

Carbon Pool		Selection Result	Selection Reason
Vegetation	Aboveground biomass	Yes	The growth of vegetation coverage and the increase in vegetation biomass are the main changes in mines after ecological restoration.
	Underground biomass
Soil organic carbon		Yes	Soil reconstruction enhances the activities of soil organisms, vegetation roots, and soil respiration, as an important pathway for the carbon sequestration of the mining ecosystem.

.

2.4. Sampling, Data Collection, and Laboratory Test

The analysis indicates that vegetation and soil are the main approaches for the restoration mines. Based on the general description and information of the 8 specific mines selected for sampling and further studies, it can be concluded that most of the selection mines have the dominant vegetation of shrubs and have a certain slope gradient, which can influence the effect of ecological restoration.

To ensure the representativeness of the quadrats, 3–4 quadrats were set in each sample area for the laboratory test and data collection. The guidelines for the quadrats setting are as follows: at least one quadrat should be set in each terrain area of the mine (the bottom of the mine, slope, and slope pathway) to determine the restoration status of each terrain area; the specific quadrat location of each area should be set according to the type of dominant vegetation; and the vegetation within the quadrat can represent the average growth status of the vegetation.

2.4.1. Sampling

The location of the quadrats should be determined by on-site installation of PVC pipes and recorded by GPS. The types of quadrat were divided according to the vegetation types. The quadrat description and the sampling requirements are shown in

Table 4. The size of the vegetation quadrats and the requirements of sampling.

Vegetation Quadrats			Requirements of Sampling
Type	Size	Sampling Method
Herb	1 m × 1 m	Clear cutting method	Cut down all herbs in the quadrat and separate the aboveground and underground parts for collection.
Shrubs	2 m × 2 m		Cut down 3–5 shrubs representing the average growth status and separate the aboveground and underground parts for collection.
Trees	10 m × 10 m	Standard wooden method	Measure the diameter at breast height, height, crown width of the all the trees in the quadrat for biomass calculation.

.

The soil samples were taken within the vegetation quadrats. The soil samplings with a weight of 500–1000 g were taken from 5 points in the quadrat (Figure 4) while the ring-knife samples were collected for the density measurement. In order to test the soil properties at different depths, the soil samples should be taken at the depths of 0–10 cm and 10–20 cm.

2.4.2. Field Investigation Data Collection

The data of the vegetation and soil can reflect the vegetation growth status and the characteristics of the soil, which should be collected within the quadrats. The requirements for data collection in the field investigation are shown in

Table 5. The main data and requirements of vegetation and soil data collection.

Object	Data Collection Requirement
Herb	Herbal type, coverage rate of unit area, average height, and number of herbaceous plants in the quadrat; connectivity of herbaceous growth in the sample area.
Shrubs	Shrub type, coverage rate of unit area, average height, tuft size, and number of shrubs in the quadrat; connectivity of shrub growth in the sample area.
Trees	Tree type, canopy density, average height, crown diameter, diameter at breast height and number of trees in the quadrat; connectivity of shrub growth in the sample area.
Soil	Soil type, average thickness, gravel content, and basic particle size of soil.

.

2.4.3. Laboratory Test

The laboratory tests were conducted to obtain the results of the carbon content of the vegetation samples, soil total nitrogen (TN), soil total phosphorus (TP), and soil organic carbon (SOC). All the specific details of each test process and quality control of the testing results should reach the requirements and guidelines of the relevant test methods and technology standards. All the vegetation and soil samples were tested after the pre-treatments of dryness, grind, sift, storage, etc. The specific analytical technique or method and the equipment (Figure 5) used for each test are illustrated.

The carbon content of the vegetation sample was measured using a carbon element analyzer (EA4000-FS125, Jena GmbH, Jena, Germany) according to the guidelines of the elemental analyzer method [39] and the component determination of agricultural biomass raw materials (NYT3498-2019 [40]). The content of the soil total nitrogen (TN) was determined by the Kjeldahl method [41] and the nitrogen determination of forest soils (LY/T 1228-2015 [42]) with the Automatic Kjeldahl Nitrogen Analyzer (K1100-FS305, Shandong Haineng Co., Ltd., Shandong, China). A spectrophotometer (UV2600-FS119, Shimadzu Co., Ltd., Suzhou, China) was used to measure the soil total phosphorus (TP) and soil organic carbon (SOC). The soil total phosphorus (TP) was determined according to the acid soluble method [43] and the phosphorus determination methods of forest soils (LY/T 1232-2015 [44]). The soil organic carbon was measured to the requirements of the potassium dichromate oxidation spectrophotometric method [45] and the soil determination of organic carbon (HJ615-2011 [46]).

2.4.4. Data Analysis

Excel 2021 was used to calculate and process the data, such as mean and standard deviation, and MATLAB 2018 was used for calculation in the process of the evaluation.

2.5. Establishment of Evaluation System for the Carbon Sequestration Capacity of Mines

The carbon sequestration capacity of restoration mines should be evaluated by scientific, systematic, hierarchical, independent indexes. The AHP model decomposes the targeted goal into the goal layer, criterion layer, and scheme layer and clusters the indexes according to the interrelationships, while the FCE method provides a quantitative and qualitative approach for evaluation based on the fuzzy transformation and maximum membership principle, solving the ambiguity and uncertainty in the judgment process [29,30,31].

Therefore, the evaluation system for the carbon sequestration capacity of mines was established by using the AHP-FCE method. The weight of each index was obtained by the judgment matrix; then, the relationship matrix of the indexes was calculated according to the membership function of fuzzy mathematics, and the final evaluation result was determined by the comprehensive. The specific steps of the evaluation are as follows.

2.5.1. Establishment of Evaluation Indexes and Evaluation Criteria

The analysis of the main approaches and carbon pools indicated that the vegetation and soil are the main indicators for the evaluation of the ecological restoration in view of the carbon sequestration. Owing to the fact that the vegetation is the driving force of the mining ecosystem and soil is important for the restoration and improvement of the ecosystem, the vegetation, soil, and slope form a common whole via the restoration measures to enhance the stability of the system.

Therefore, this study took the carbon sequestration capacity of the restored mining ecosystem as the main evaluation goal, and the criterion layer was divided into vegetation, soil, and the coherent stability of the vegetation–soil–slope system (the system stability), which contained 9 indexes selected according to the approaches of carbon sequestration, expert advice, and data collected (Figure 6).

2.5.2. Determination of Index Weight [33,47]

1.

Establishment of Judgment Matrix

Based on the structure of the evaluation system shown in Figure 6, the judgment matrix is established according to the domination relationship between the adjacent layers. The 1–9 scale method is used to compare the important values. The judgment matrix A is shown as Equation (1):

$$A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& \cdots & a_{1n}\\ a_{21}& a_{22}& \cdots & a_{2n}\\ ⋮& ⋮& \ddots & ⋮\\ a_{n1}& a_{n2}& \cdots & a_{nn}\end{array}\right]$$

(1)

where $a_{ij}$ is the comparison value of the importance of i to j ($a_{ij}>0$, $a_{ii}=1$, and $a_{ji}={\displaystyle \raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$a_{ij}$}\right.}$, and i,j = 1,2,…n).

2.

Calculation of Index Weight

The weighted vector $w_i$ is calculated as Equation (2), and the index weight is calculated after the normalization of the weighted vector shown as Equation (3):

$${\mathit{w}}_{\mathit{i}}={\left({\prod }_{j=1}^n a_{ij}\right)}^{{\displaystyle \frac{1}{n}}}$$

(2)

$$W_i={\displaystyle \frac{w_i}{{\sum }_{i=1}^n{\mathit{w}}_{\mathit{i}}}}$$

(3)

3.

Consistency Check of Judgment Matrix

The consistency check of the judgment matrix is used for verifying the objectivity of data, which can be calculated with Equations (4)–(6):

$${\lambda }_{\mathrm{m}\mathrm{a}\mathrm{x}}={\displaystyle \frac{1}{n}}\sum _{i=1}^n{\displaystyle \frac{{\left(AW\right)}_i}{w_i}}$$

(4)

$$C_{\mathrm{I}}={\displaystyle \frac{{\lambda }_{\mathrm{m}\mathrm{a}\mathrm{x}}-n}{n-1}}$$

(5)

$$C_{\mathrm{R}}={\displaystyle \frac{C_{\mathrm{I}}}{R_{\mathrm{I}}}}$$

(6)

where ${\lambda }_{\mathrm{m}\mathrm{a}\mathrm{x}}$ is the largest eigenvalue of the judgment matrix, n is the judgment matrix order, $C_{\mathrm{I}}$ is the consistency index, $C_{\mathrm{R}}$ is the consistency ratio, $R_{\mathrm{I}}$ is the average consistency index.

When the $C_{\mathrm{R}}$ is less than 10, it indicates that the consistency of the judgment matrix is very good. Therefore, the weight set can be obtained, which is shown as Equation (7):

$$W=(W_1,W_2,\dots ,W_n)$$

(7)

4.

Determination of Membership Function

The membership function is designed based on the distribution characteristics of the evaluation index, combined with the features of the trapezoidal distribution function, shown as Equations (8)–(11):

$$Y_{\nu 1}=\left\{\begin{array}{ll}1& (x_i⩽e_1)\\ {\displaystyle \frac{e_2-x_i}{e_2-e_1}}& (e_1<x_i⩽e_2)\\ 0& (x_i>e_2)\end{array}\right.$$

(8)

$$Y_{\nu 2}=\left\{\begin{array}{ll}0& (x_i⩽e_1,x_i⩾e_3)\\ {\displaystyle \frac{x_i-e_1}{e_2-e_1}}& (e_1<x_i⩽e_2)\\ {\displaystyle \frac{e_3-x_i}{e_3-e_2}}& (e_2<x_i⩽e_3)\end{array}\right.$$

(9)

$$Y_{\nu 3}=\left\{\begin{array}{ll}0& (x_i⩽e_2,x_i⩾e_4)\\ {\displaystyle \frac{x_i-e_2}{e_3-e_2}}& (e_2<x_i⩽e_3)\\ {\displaystyle \frac{e_4-x_i}{e_4-e_3}}& (e_3<x_i⩽e_4)\end{array}\right.$$

(10)

$$Y_{\nu 4}=\left\{\begin{array}{ll}0& (x_i⩽e_3)\\ {\displaystyle \frac{x_i-e_3}{e_4-e_3}}& (e_3<x_i⩽e_4)\\ 1& (x_i>e_4)\end{array}\right.$$

(11)

where $x_i$ is the actual value of each index, $x_i$ is the upper and lower limit of the evaluation value.

2.5.3. Fuzzy Comprehensive Evaluation [33,47]

1.

Establishment of Fuzzy Set of Evaluation

According to the evaluation structure, the fuzzy sets of evaluation U are established with the evaluation index, shown as Equation (12):

$$U=\left(B_1,B_2,B_3\right)=\left(C_1,C_2,C_3,\dots ,\dots ,C_9\right)$$

(12)

2.

Establishment of Comments Set of Evaluation

According to the classification of the evaluation level in the relevant studies, the evaluation levels of the carbon sequestration capacity for the mines were divided into excellent capacity, good capacity, normal capacity, and poor capacity, as shown in

Table 6. Comments set of evaluation.

V	V1	V2	V3	V4
Comment	Level 1	Level 2	Level 3	Level 4
Capacity level	Excellent	Good	Normal	Poor

. Each evaluation level reflects the carbon sequestration capability of restoration mines via the vegetation, soil properties, and the system stability. The evaluation levels stand for different restoration statuses of mines with practical significance, for instance, excellent capacity demonstrates the vegetation with almost full coverage in the mining area and higher carbon content, the soil properties close to the primitive soil around the mining area, and the coherent system with little deformation on the vegetation community, soil layer, and slope. The evaluation level standards for each index are shown in

Table 7. The evaluation level standards for each index.

Evaluation Index	V1	V2	V3	V4
Carbon Content (C1)/%	40–55	30–40	20–30	5–20
Connectivity Rate (C2)/%	>85	70–90	70–50	<50
Coverage of Unit Area (C3)/%	>85	70–85	70–45	<45
Biomass (C4)/g	>250	180–250	90–180	<90
Soil Organic Carbon (C5)/(g·kg−1)	>25	16–25	9–16	<9
Soil Total Nitrogen (C6) /(g·kg−1)	>2	1.4–2	0.8–1.4	<0.8
Soil Total Phosphorus (C7)/(g·kg−1)	>2	1.4–2	0.8–1.4	<0.8
Proportion of Soil Rainfall Erosion Area on Slope (C8)/%	No Soil Rainfall Erosion Area	Soil Rainfall Erosion Area < 12%	Soil Rainfall Erosion Area < 15%	Soil Rainfall Erosion Area ≥ 15%
Proportion of Slope Local Instability Area (C9)/%	No Slope Instability Area	Slope Instability Area < 12%	Slope Instability Area < 15%	Slope Instability Area ≥ 15%

.

3.

Establishment of Fuzzy Membership Matrix

The establishment of the fuzzy membership matrix R is based on the classification criteria of each evaluation index level, shown as Equation (13):

$$R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& \cdots & r_{1k}\\ r_{21}& r_{22}& \cdots & r_{2\mathrm{k}}\\ ⋮& ⋮& \ddots & ⋮\\ r_{n1}& r_{n2}& \cdots & r_{nk}\end{array}\right]$$

(13)

where $r_{ij}$ is the grade of membership of the i evaluation index in the j evaluation level (i = 1, 2, …, n; j = 1, 2, …, k).

4.

Establishment of Fuzzy Comprehensive Evaluation Matrix

The fuzzy comprehensive evaluation matrix S is calculated by synthesizing the weighted vector w and membership matrix R, shown as Equation (14):

$$\mathrm{S}=w_i\times R_i=\left\{b_1,b_2,\dots ,b_n\right\}$$

(14)

where $b_i$ is the grade of membership of the evaluated goal to the fuzzy subset.

According to the maximum membership principle, it is known that the evaluation result is the evaluation level of the carbon sequestration capacity of the mines after ecological restoration corresponding to the maximum value.

3. Results of Case Study

The limestone quarry (M₁) is taken as the specific case to demonstrate the process of calculation and evaluation using the evaluation system for the evaluation of the carbon sequestration capacity.

3.1. Analysis of the Landscape Changes in the Case Study

The general description and information of the limestone quarry (M₁, Figure 7) are displayed in Table 1, including the location, size, mining object, soil type, restoration measures, etc. Based on the growth status of the vegetation (Figure 7c,d), the data that are obtained from the field investigation and laboratory test and used for comprehensive evaluation are shown in

Table 8. The evaluation index data for each case study.

C1	C2	C3	C4	C5	C6	C7	C8	C9
%	%	%	g	g·kg−1	g·kg−1	g·kg−1	%	%
36.36	80	90	1002.24	6.10	0.68	0.62	14	0

.

3.2. Comprehensive Evalution of the Carbon Sequestration Capacity of the Case Study

3.2.1. Calculation of Index Weight of the Case Study

According to the assignment of relative importance values of each of the evaluation indicators in different layers, the judgment matrix and consistency check of the case study are shown in

Table 9. The judgment matrix and consistency check of the case study.

Adjacent Layers	Judgment Matrix					Index Weight	Consistency Check
A–B	Bi	B1	B2	B3		$W_i$	${\lambda }_{max}$ = 3.054 $C_{\mathrm{I}}$ = 0.027 $C_{\mathrm{R}}$ = 0.047 < 0.100
	B1	1	4	1/2		0.345
	B2	1/4	1	1/4		0.108
	B3	2	4	1		0.547
B1–C	B1Cj	C1	C2	C3	C4	$W_{1j}$	${\lambda }_{max}$ = 4.249 $C_{\mathrm{I}}$ = 0.083 $C_{\mathrm{R}}$ = 0.092 < 0.100
	C1	1	2	6	7	0.540
	C2	1/2	1	3	4	0.279
	C3	1/6	1/3	1	5	0.129
	C4	1/7	1/4	1/5	1	0.052
B2–C	B2Cj	C5	C6	C7		$W_{2j}$	${\lambda }_{max}$ = 3.108 $C_{\mathrm{I}}$ = 0.054 $C_{\mathrm{R}}$ = 0.093 < 0.100
	C5	1	2	3		0.517
	C6	1/2	1	4		0.359
	C7	1/3	1/4	1		0.124
B3–C	B3Cj	C8	C9			$W_{3j}$	${\lambda }_{max}$ = 2.000 $C_{\mathrm{I}}$ = 0 $C_{\mathrm{R}}$ = 0.000 < 0.100
	C8	1	3			0.800
	C9	1/3	1			0.200

.

Therefore, the weight set of the criterion layer is

$$W_{A-\mathrm{B}}=\mathrm{W}\left\{B_1,B_2,B_3\right\}=\mathrm{W}\left\{0.345,0.108,0.547\right\}$$

and the weight sets of the scheme layer are

$$W_{{\mathrm{B}}_1-\mathrm{C}}=\left\{C_1,C_2,C_3,C_4\right\}={\mathrm{W}}_1\left\{0.540,0.279,0.129,0.052\right\}$$

$$W_{{\mathrm{B}}_2-\mathrm{C}}=\left\{C_5,C_6,C_7\right\}={\mathrm{W}}_1\left\{0.517,0.3594,0.124\right\}$$

$$W_{{\mathrm{B}}_3-\mathrm{C}}=\left\{C_7,C_8\right\}={\mathrm{W}}_1\left\{0.800,0.200\right\}$$

3.2.2. Determination of Fuzzy Membership Matrix of the Case Study

The fuzzy membership matrixes were established via the grade of the evaluation indexes, evaluation level standards, and the specific evaluation index data in Table 7. The fuzzy membership matrixes of the indexes in the criterion layer the case study are

$$\left.R_1=\left[\begin{array}{cccc}0& 0.6& 0.4& 0\\ 0& 0.5& 0.5& 0\\ 0.5& 0.5& 0& 0\\ 1& 0& 0& 0\end{array}\right.\right]$$

$$\left.R_2=\left[\begin{array}{ccc}0.5& 0.5& 0\\ 0& 0.3& 0.7\\ 0& 0.8& 0.2\end{array} \begin{array}{c}0\\ 0\\ 0\end{array}\right.\right]$$

$$\left.R_3=\left[\begin{array}{ccc}0& 0.7& 0.3\\ 0.8& 0.2& 0\end{array}\right. \begin{array}{c}0\\ 0\end{array}\right]$$

3.2.3. Multi-Level Fuzzy Comprehensive Evaluation of the Case Study

Based on the weight sets and fuzzy membership matrixes of the scheme layers, the fuzzy comprehensive evaluation matrix of the criterion layer was calculated and the evaluation results of each aspect of the criterion layer were obtained according to the maximum membership principle. The fuzzy membership matrixes of the goal layer are calculated via the same method and the results of the case study are shown in

Table 10. The calculation results and evaluation results of index in different layers.

Layer	Index	Calculation Process	Excellent	Good	Normal	Poor	Evaluation Result
Criterion Layer	B1	$S_{{\mathrm{B}}_1-\mathrm{C}}=W_{{\mathrm{B}}_1-\mathrm{C}}\times R_1$	0.117	0.528	0.356	0	Good
	B2	$S_{{\mathrm{B}}_2-\mathrm{C}}=W_{{\mathrm{B}}_2-\mathrm{C}}\times R_2$	0.259	0.391	0.351	0	Good
	B3	$S_{{\mathrm{B}}_3-\mathrm{C}}=W_{{\mathrm{B}}_3-\mathrm{C}}\times R_3$	0.160	0.600	0.240	0	Good
Goal Layer	A	$S_{A-\mathrm{B}}=W_{A-\mathrm{B}}\times R_1$	0.156	0.553	0.292	0	Good

.

3.2.4. Analysis of Evaluation Results

According to the calculation results of the index weight of the criterion layer, it can be seen that the weight value of the system stability had the highest proportion of 0.547; next was the vegetation community with the proportion of 0.345. Therefore, the stability of the system is the main factor contributing to the carbon sequestration capacity of mines. Owing to the fact that mining excavation causes changes in the stress state of the mining slope and loosens the soil and rock mass, the primary goal of ecological restoration is the stability of the mining ecosystem including the improvement in the slope stability and the reduction in soil erosion. Therefore, the coherent system represents the sustainability of the vegetation community, and the stability of the soil fixed on the slope. Secondly, by combing the weight sets of the scheme layer, it can be known that the vegetation community is the key factor in the carbon sequestration effect. Not only does the vegetation reduce the soil erosion by intercepting rainfall and improve the environmental and physicochemical properties of the soil but quick carbon storage in the vegetation can be achieved in the short term due to the fact that the vegetation seedlings used for planting have a strong growth ability at their young stage.

Based on the evaluation results of the limestone quarry (M₁) as the case study, by using the multi-level fuzzy comprehensive evaluation, it is indicated that the status of the vegetation community and soil is good while the stability of the coherent system is excellent. The evaluation results are consistent with the visual effect and conclusions of the field investigation (Figure 7c,d).

4. Discussion

4.1. Analysis of Carbon Sequestration Capacity of the Mines after Ecological Restoration in the Study Area

Although the restoration mines in the study area are of great number, the ecological restoration has also been well and orderly carried out. The types of mines and the dominant vegetation in the research area are relatively uniform, but the slope conditions vary greatly. Therefore, using the evaluation system to assess the carbon sequestration capacity of the restoration mining ecosystem can provide a reference for engineering experience for ecological restoration. The above calculation and evaluation processes were extended to the eight selected sample areas. To verify the effectiveness of the evaluation results, the comparison of the situation before and after the restoration of each mine is shown in Figure 8. The test results of the vegetation and soil samples of each selected mine (including M₁) are shown in

Table 11. The laboratory testing results of sampling areas.

Sample Areas	Quadrat Number	Carbon Content of Vegetation (%)	Soil Organic Carbon (g·kg−1)		Soil Total Nitrogen (g·kg−1)		Soil Total Phosphorus (g·kg−1)
			0–10 cm	10–20 cm	0–10 cm	10–20 cm	0–10 cm	10–20 cm
M1	Q1–1	36.26	6.80	5.90	0.613	0.657	0.634	0.608
	Q1–2	36.03	6.50	6.00	0.634	0.772	0.653	0.592
	Q1–3	36.78	5.90	5.50	0.698	0.714	0.623	0.601
M2	Q2–1	35.71	7.10	5.80	0.561	0.545	0.423	0.439
	Q2–2	33.94	6.80	7.20	0.548	0.539	0.366	0.358
	Q2–3	34.38	7.80	7.20	0.684	0.742	0.408	0.460
M3	Q3–1	37.76	4.80	4.30	0.578	0.651	0.477	0.486
	Q3–2	37.39	6.30	5.60	0.645	0.606	0.430	0.426
	Q3–3	39.08	5.40	5.80	0.612	0.551	0.392	0.429
M4	Q4–1	38.71	4.50	4.70	0.412	0.453	0.374	0.371
	Q4–2	37.46	4.30	5.20	0.444	0.366	0.534	0.525
	Q4–3	38.82	4.50	5.30	0.472	0.398	0.444	0.461
M5	Q5–1	44.91	5.20	5.60	0.458	0.582	0.589	0.638
	Q5–2	44.79	5.10	5.40	0.382	0.477	0.616	0.622
	Q5–3	44.84	4.70	4.20	0.550	0.473	0.606	0.586
M6	Q6–1	42.94	4.80	4.30	0.753	0.681	0.830	0.795
	Q6–2	43.67	5.60	4.20	0.795	0.612	0.737	0.766
	Q6–3	42.49	6.30	5.70	0.863	0.781	0.791	0.819
M7	Q7–1	44.36	6.10	5.00	0.578	0..453	0.252	0.251
	Q7–2	44.63	6.50	5.50	0.598	0.462	0.265	0.263
	Q7–3	44.27	5.50	4.90	0.529	0.486	0.237	0.250
M8	Q8–1	42.18	5.10	6.20	0.469	0.433	0.550	0.543
	Q8–2	43.97	5.00	5.80	0.510	0.483	0.578	0.523
	Q8–3	44.51	6.20	7.40	0.535	0.479	0.567	0.555

and the results are shown in

Table 12. The results of selected sample areas.

Sample Areas	Criterion Layer		Goal Layer
	Calculation Result	Evaluation Result	Calculation Result	Evaluation Result
M2	{0.272, 0.728, 0.000, 0.000}	Good	{0.384, 0.573, 0.041, 0.000}	Good
	{0.259, 0.355, 0.386, 0.000}	Normal
	{0.480, 0.520, 0.000, 0.000}	Good
M3	{0.075, 0.761, 0.164, 0.000}	Good	{0.288, 0.558, 0.138, 0.015}	Good
	{0.000, 0.103, 0.757, 0.139}	Normal
	{0.480, 0.520, 0.000, 0.000}	Good
M4	{0.542, 0.416, 0.042, 0.000}	Excellent	{0.668, 0.209, 0.081, 0.041}	Excellent
	{0.000, 0.000, 0.617, 0.383}	Normal
	{0.880, 0.120, 0.000, 0.000}	Excellent
M5	{0.558, 0.416, 0.026, 0.000}	Excellent	{0.674, 0.212, 0.067, 0.047}	Excellent
	{0.000, 0.025, 0.537, 0.438}	Normal
	{0.880, 0.120, 0.000, 0.000}	Excellent
M6	{0.373, 0.498, 0.000, 0.129}	Good	{0.621, 0.320, 0.014, 0.045}	Excellent
	{0.103, 0.763, 0.134, 0.000}	Good
	{0.880, 0.120, 0.000, 0.000}	Excellent
M7	{0.302, 0.624, 0.075, 0.000}	Good	{0.323, 0.566, 0.094, 0.018}	Good
	{0.000, 0.207, 0.629, 0.164}	Normal
	{0.400, 0.600, 0.000, 0.000}	Good
M8	{0.300, 0.700, 0.000, 0.000}	Good	{0.278, 0.637, 0.065, 0.019}	Good
	{0.000, 0.217, 0.603, 0.180}	Normal
	{0.320, 0.680, 0.000, 0.000}	Good

.

The evaluation results of the eight selected mines for sampling showed that the proportion at the excellent level of the carbon sequestration capacity of the mines is 62.5% and the proportion at the good level is 37.5% while there are none at the normal level and poor level. By combing through the changes in the vegetation coverage and the soil layer in Figure 8 and the evaluation results, it can be concluded that the stability of the coherent system is key to improving the restoration mining ecosystem, which stands for the sustainability of the vegetation community development and the adaptability of the soil layer fixed in the slope as a matrix. For example, the mines M_4–6, with results at the excellent level, have the advantage of a low slope gradient, which can encounter less difficulty in soil construction to provide nutrients for vegetation and more areas for the improvement in the soil quality. The results indicated that all the abandoned open-pit mines that have undergone ecological restoration can meet the requirements for the carbon sequestration capacity.

4.2. Analysis of Ecological Restoration Effect for the Open-Pit Mines

Although the effect of the ecological restoration and the carbon sequestration capability of the open-pit mines are presented and obviously improved through the qualitative evaluation via the visual effects and quantitative analysis of the evaluation results, more analysis is needed as a guideline for similar ecological restoration mines.

4.2.1. Effect of Ecological Restoration Measures on the Mining Ecosystem

Ecological restoration measures have improved the ecological environment of open-pit mines. The landscape of the mine gradually becomes compatible with the undamaged landscape of the surrounding area as a whole. According to the coverage from Figure 8 and the evaluation results, the vegetation mainly maintains in the range of 80–95% under the impact of the slope gradient. The capability of vegetation growth should be considered for the vegetation combination scheme, which can influence the distribution of different vegetation and further affect the total vegetation growth status in the mines. For instance, among the selected mines, the slopes of M_2–4 are steep, but the shrub is selected for restoration in the lower part of the slope while the whole slope of M₃ and the upper slope of M₄ are planted with herbs, with a larger area exposed and a weaker fixation of the soil layer. Therefore, the selection of the appropriate scheme for the vegetation combination of vegetation rebuilding on the slope plays a significant role in reducing soil erosion and geological disasters and ensuring the stability of the soil layer on the slope and the sustainability of the vegetation community’s survival.

Therefore, the evaluation and investigation results provide experience for the selection of mine treatment measures, thereby enhancing the potential for the self-restoration of mining ecosystems and the sustainability of carbon sequestration.

4.2.2. Effect of Ecological Restoration on Approaches of Carbon Sequestration of Mines

The vegetation and soil are the main carbon pools in the restoration mining ecosystem and are related to the sustainability of carbon sequestration, which forms the whole interaction with the medium between the vegetation and soil. Owing to the fact that the ecosystem converts CO₂ from a free into a steady state through a process such as vegetation photosynthesis and the soil organism, a greater proportion of vegetation and soil coverage can offer a larger area for the absorption, transformation, and storage of CO₂.

So, the restoration status can be monitored via the data from the laboratory testing results, and also be effectively evaluated via the changes obtained from the visual effect to determine if there are additional areas for more carbon sequestration. So, it broadens the mind regarding the selection of the quantitative evaluation data for the establishment of the evaluation system for the carbon sequestration capacity.

4.2.3. Evaluation of Effect on the Carbon Sequestration of Mining Ecosystem

Based on the changes in the landscape and the approaches for the carbon sequestration of mines, the evaluation system quantitatively evaluates the carbon sequestration capability considering three aspects and nine evaluation indexes.

The results of the calculation and evaluation not only assess the effect of the stability of the soil layer, the sustainability of the vegetation community’s survival, and the stability of the system, but also determine the contribution of each index to the carbon sequestration effect according to the weight value. The fact that the evaluation results are consistent with the reality via the qualitative analysis, which also compared the restoration effects, provides theoretical data and experience reference for restoration measures.

4.3. Limitations and Future Work of the Study

In the research, the carbon sequestration capacity of the restoration mines was studied based on a field investigation, laboratory tests, and an evaluation system. Although the ecological restoration effects were studied from the view of carbon sequestration via the evaluation system regarding the influencing factors, there are some existing limitations.

In the evaluation system, the aspects of the criterion layer and evaluation indexes are relatively few. For instance, the restoration measures influence the carbon sequestration capacity and other soil physical and chemical properties may reflect the restoration effect. So, the aspects and indexes of the evaluation system can be enriched and deepened with more collected materials and laboratory tests.

Also, the data collection heavily relies on the field investigation and laboratory tests. However, the number of sampling areas and samples in a single mine are not enough, and all the mines are from a single region. In a subsequent study, more sampling areas and sampling quadrats should be set, and other regions will be taken into consideration to improve the accuracy and reliability.

Moreover, although the evaluation system can analyze the targeted goals, it relies on the investigation of the restoration state and the AHP-FCE method heavily, which is not suitable for long-term evaluation. Therefore, other data collection methods such as remote sensing and suppled investigation and other evaluation methods will be introduced for mutual verification in the future research. The development of software tools can also facilitate the data processing and evaluation process much easier and faster.

5. Conclusions

The assessment of restoration mines is to evaluate the influence and effect of ecological restoration on the mining ecosystem. However, there are few studies on the evaluation of the carbon sequestration capability of open-pit mines after ecological restoration. In the process, we concluded that the vegetation and soil in restoration mines are the main media for fixing and storing CO₂. Therefore, the evaluation system with nine indexes was proposed from the aspects of the vegetation, soil, and coherent stability of the vegetation–soil–slope system based on the AHP-FCE method. The evaluation was performed via the data obtained from the field investigation and laboratory tests.

The calculation results of the weights showed that the system stability was the most important influencing factor with the largest value of 0.547, followed by vegetation and soil; the weight values of the vegetation carbon content (C₁), soil organic carbon (C₅), and proportion of soil erosion area on the slope (C₈) were relatively higher. Therefore, the system stability and the restoration state of the vegetation and soil were closely related to the carbon sequestration capability, ensuring fixed CO₂ was stored in the stable system. Additionally, the evaluation results of the mines in the study area and all aspects of the evaluation system are at the excellent and good levels, which are consistent with the qualitative evaluation results of the field investigation. It revealed the improvement in the mining ecosystem and the carbon sequestration capability due to the ecological restoration.

Therefore, according to the results of the weight calculation and evaluation, it can be concluded that the evaluation system has strong applicability and effectiveness, which can provide a reference for the evaluation of the carbon sequestration capability of mines or other similar small-scale projects after ecological restoration. In the subsequent evaluation work, the evaluation indexes can be further refined and improved according to the secondary data sources such as remote sensing and complement field investigations. In summary, the research and findings offer a new approach for the sustainable development of the mining ecosystem and the relevant guidelines for the evaluation of the ecological restoration effect.