Mine Environmental Restoration

Optimization of the Land Use Structure of Opencast Coal Mine under the Background of Low Carbon—A Case Study of Luotuoshan Mountain Mining Area in Wuhai City of Northwest China

  • LIU Jiaqi ,
  • YANG Jianying , * ,
  • ZHAO Tingning ,
  • WEI Guangkuo ,
  • LI Ruipeng ,
  • KUI Guoxian ,
  • AI Xianfeng
  • College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
*YANG Jianying, E-mail:

LIU Jiaqi, E-mail:

Received date: 2022-10-08

  Accepted date: 2023-04-30

  Online published: 2024-03-14

Supported by

The Integrated Demonstration Research on Ecological Restoration and Ecological Safety Guarantee Technology in Mining Area(2017YFC0504406)


Humans affect the global carbon cycle primarily through land use activities. In particular, the acceleration of opencast coal mining has induced serious problems such as the increase of carbon emissions in mining areas and the decline of ecosystem functions. Therefore, it has become critical to explore optimal land use structures with the best ecological benefits under low carbon emissions and provide theoretical support for the optimization and adjustment of land use structures in arid desert mining areas, especially in northwest China. Taking the Luotuoshan mining area in Wuhai City of northwest China as the research area, this study estimated carbon emissions from land use activities in the mining area and constructed a land use optimization scheme focused on low carbon emission and high ecological service value using a multi-objective programming model. The results showed that under the optimization scheme, the area of grassland and water land use types increased, while those of mining land and unused land decreased. Compared with 2021, the optimization scheme could decrease carbon emissions by 19045.93 tC and increase the ecosystem service value by 53381400 yuan. Thus, the optimization scheme of land use structure can improve the ecological benefits of land use and ensure low carbon emission in mining areas. The findings will provide scientific guidance for the optimization of the land use structure and ecological restoration in arid desert areas of northwest China.

Cite this article

LIU Jiaqi , YANG Jianying , ZHAO Tingning , WEI Guangkuo , LI Ruipeng , KUI Guoxian , AI Xianfeng . Optimization of the Land Use Structure of Opencast Coal Mine under the Background of Low Carbon—A Case Study of Luotuoshan Mountain Mining Area in Wuhai City of Northwest China[J]. Journal of Resources and Ecology, 2024 , 15(2) : 455 -463 . DOI: 10.5814/j.issn.1674-764x.2024.02.020

1 Introduction

As a large-scale coal base, the northwest arid desert area of China is the key construction area of the national “belt and road initiative”. However, it lies in an arid and windy region with an extremely fragile ecosystem (Zhao et al., 2018). With the large-scale mining of coal, the land use structure in mining areas has changed dramatically, with increased fragmentation degree, edge density and fractal dimension of land use (Huang et al., 2015), which have led to a decrease in the stability of the mining area ecosystem. In 2018, the Intergovernmental Panel on Climate Change (IPCC) put forward the goal of achieving global net zero carbon emissions by the middle of the 21st century in the Special Report on Global 1.5 ℃ Temperature Rise (Wang et al., 2022). In China’s “14th Five-Year Plan”, the goal of reducing energy consumption and carbon dioxide emissions per unit of GDP by 13.5% and 18% respectively was put forward (Fan et al., 2021). Considering that coal is the main energy source in China, under the background of peak carbon dioxide emissions and carbon neutrality, the problem of high carbon emissions in coal mining areas cannot be ignored (Li et al., 2022).
In the research of land use carbon emission, scholars mostly focus on the carbon emission mechanism of land use change (Houghton, 2002), and the impact of land use change on carbon emission (Qu et al., 2011; Li et al., 2018). However, only few studies have evaluated the combination of the low-carbon concept and ecological service value to explore the land use structure in mining areas considering the best benefits of both parties. Therefore, there is an urgent need to explore the optimal land use structure in mining areas that meets the requirements of ecological civilization construction and low-carbon theory. The optimization of the land use structure is to improve the sustainable utilization of land resources by adjusting the proportion of various land use types (Marull et al., 2010). In terms of land use structure optimization, most studies have been conducted at the provincial administrative (He et al., 2021; Li et al., 2021) and river basin scales (He et al., 2021). However, no study has explored the optimization of the land use structure in the arid desert mining areas of northwest China.
To address this shortcoming, this study investigated changes in carbon emissions and ecological service value in the Luotuoshan mining area in Wuhai City of northwest China, which was taken as an example, from 2016 to 2021, and explored the optimal structure of land use in the mining area that meets the requirement of high ecosystem service value under low carbon. The findings are expected to provide scientific guidance for realizing the virtuous cycle of high ecosystem service under low carbon control, sustainable utilization of natural resources, and sustainable development of mining area ecology in the arid desert mining areas of northwest China.

2 Materials and methods

2.1 Study area

The Luotuoshan Mining Area is located in the north-central part of Zhuozishan Coalfield, Hainan District, Wuhai City, Inner Mongolia Autonomous Region, with geographical coordinates of 39°28′-39°32′N, 106°54'-106°58'E and a total area of 1435.00 ha. The original landform is dominated by low mountains and hills, belonging to an arid continental climate. The average annual precipitation is 130.67 mm, average annual evaporation is 3439.70 mm, average annual temperature is 9.0-10.3 ℃, and annual sunshine hours are 3121 h. The soil types are mainly grey desert soil, brown calcium soil, chestnut soil, aeolian sand soil, meadow soil, and saline soil. The dump is covered with aeolian sand soil. The Luotuoshan mining area comprises 8 coal mines, namely the Mengtai, Junzheng, Longchang, Xi’a, Haoyuan, New Energy, Xinyuan, and Tongzhou coal mines from south to north, and their distribution is shown in Fig. 1. All of them are opencast mines except the Haoyuan Coal Mine, in which early stripping was conducted through discharge to the west and east sides and but discontinued on the west side owing to the elevation. The later stripping is designed to be discharged to the dump on the east side, which will be filled into the mining pit after mining is completed in the middle part. According to the green mine planning of Wuhai City and the coal mine, the ecological restoration and treatment of the dump is planned.
Fig. 1 Distribution map of study area

2.2 Data source and preprocessing

Based on the remote sensing image data of Gaofen No.2 in June, 2021 over the study area, this study obtained an image with a resolution of 1 m after pretreatment comprising ENVI radiation calibration, atmospheric correction, orthorectification, and image fusion and cropping, supplemented by aerial survey images of unmanned aerial vehicles and field survey data in this area. According to the Classification of Land Use Status (GB/T 21010-2017) and the local land use situation, the following land use types in the Luotuoshan Mining Area were set: Woodland, grassland, construction land, mining land, water area, and unused land. Specifically, woodland includes small trees and bushes; grassland mainly refers to shrub grass; construction land refers to buildings in front of the factory, such as office buildings, dormitories, restaurants, coal storage yards, coal washing plants, and other auxiliary production buildings and roads; mining land mainly refers to mining pits and internal dumps; water area refers to water reservoirs and mine water; and unused land mainly includes waste dumps that have not been ecologically restored after waste disposal, and the surrounding bare land and grassland.
ENVI was used to supervise, classify, and visually interpret the mining area, and the land use data after image classification and interpretation were compared with the field survey data. The reliability of the obtained land use data was tested in terms of the Kappa index, and the value was found to be greater than 0.8, suggesting credible data. The social and economic data of Wuhai were primarily obtained from the Statistical Yearbook of Inner Mongolia 2021, Statistical Bulletin of National Economic and Social Development of Wuhai City in 2021, the 14th Five-Year Plan of National Economic and Social Development of Wuhai City and the Long-term Goals in 2035, and the General Land and Space Plan of Wuhai City (2019-2035). The basic data of carbon emission in production and life of construction land and mining land are provided by technicians from the production and operation management department of Guangna Group.

2.3 Mining area carbon emission accounting

The calculation of carbon emissions requires the determination of carbon emission sources. According to the analysis of carbon source composition in the mining area, this study divided carbon emission sources into two categories: direct carbon emissions and indirect carbon emissions. As the study area has no cultivated land, carbon emission from agricultural means of production was not considered. According to the on-site investigation, the electric shovel and electric drill were all replaced by diesel machinery. Therefore, power consumption was not considered in this study, and the carbon emission composition of land use in mining area is shown in Fig. 2.
Fig. 2 Composition of carbon emission from land use in mining area

2.3.1 Direct carbon emissions from land use

For a period of time, the change rate of carbon emission and carbon absorption per unit area of woodland, grassland, water area, and other unused land was small (Meng et al., 2019). Therefore, the direct carbon emission coefficient method was used to calculate the carbon emission of each land use type. The carbon emission coefficient for various land use types was referred from previous research on carbon emission in the Inner Mongolia Autonomous Region: -0.487 tC ha-1 yr-1 for woodland (Fang et al., 2007; Lai, 2010), -0.191 tC ha-1 yr-1 for grassland (Fang et al., 2007); -0.410 tC ha-1 yr-1 for water (Duan et al., 2008), and -0.005 tC ha-1yr-1 for unused land (Shi et al., 2012).

2.3.2 Indirect carbon emissions from land use

As ammonium nitrate explosives are often used for deep-hole blasting in mining areas, coal transportation vehicles mainly consume diesel oil, and both production and life activities in mining areas consume a large amount of fossil fuels, if the construction land area is directly used for conversion, the carbon emission level attributable to human activities cannot be accurately reflected. Therefore, the indirect carbon emission calculation model was adopted. According to the carbon emission sources of mining land, the carbon emission model of mining land type was constructed as follows:

CI = CI1+CI2+CI3

CI is the total carbon emissions of mining land; CI1 is the carbon emission from gas emission, mainly CH4 gas emission from coal mining; CI2 is the carbon emission from diesel combustion, mainly through the operation of large machinery during coal mining and transportation; CI3 is the carbon emission from explosive blasting, mainly from coal seam blasting with ammonium nitrate explosives. The calculation formula is shown in Table 1.
The carbon emission model of construction land is:

CL = CL1+CL2+CL3

where CL is the total carbon emissions of construction land, CL1 is the carbon emissions from human respiration, CL2 is the carbon emissions from landfill, and CL3 is the carbon emissions from domestic energy consumption. The calculation formula is shown in Table 2 below.
Table 1 Calculation of carbon emissions from mining land
Carbon emission type Formula Symbolic meaning
Gas escape (CI1) CI1=a×G×ρ×(EFa+EFb) (3) CI1 is CH4 emission, t yr-1; a is the global warming potential of CH4, taking 24.5; G is the coal mining amount, t yr-1; ρ is the density of CH4 under standard conditions, taking 0.714 kg m-3; EFa is the CH4 emission factor during mining, which is 1.2 m3 t-1 (referring to the 2006 IPCC Guidelines for National Gas Inventory); EFb is the CH4 emission factor after mining, which is 0.1 m3 t-1
Diesel combustion (CI2) CI2= E × P (4)
P = F × R × O × 10-6 (5)
CI2 is the carbon emission from diesel consumption, tC; E is the consumption of diesel oil, t; F is the average low calorific value of diesel oil, which is 42652 kJ kg-1 (referring to the General Rules for Calculation of Comprehensive Energy Consumption GB/T 2589-2008); R is the carbon content per unit calorific value of diesel oil, taking 20.2 tC tJ-1; O is the carbon oxidation rate of diesel oil, taking 0.98 (referring to the Guide for Compilation of Provincial Greenhouse Gas Inventory)
Explosive consumption (CI3) CI3= GE× p (6) CI3 is the carbon emission of ammonium nitrate explosive, tC; GE is the amount of ammonium nitrate explosive, t; p is the carbon emission factor of ammonium nitrate explosive, taking 0.2629 tC t-1 (Zhang, 2013)
Table 2 Calculation of carbon emissions of construction land
Carbon emission type Computing formula Symbolic meaning
Human respiration (CL1) CL1 = Nh×fh (7) CL1 is the carbon emission from human and animal respiration; Nh is the total population of the study area; fh is a parameter of annual respiratory volume per capita of human body, with a value of 0.079 (Fang et al., 2007; Kuang et al., 2010)
Landfill (CL2) CL2=M×0.167×(1‒71.5%) (8) CL2 is the total carbon emission from landfills of domestic garbage, and M is the amount of domestic garbage landfill in the study area within one year. Referring to the default value in the 2006 IPCC Guidelines for National Greenhouse Gas Inventory, the emission factor of methane in landfill was set as 0.167, and the moisture content of garbage was set as 71.5% (Guo, 2009)
Domestic energy consumption (CL3) CL3= ∑(Bi× bi× ci) (9) CL3 is the total carbon emissions of domestic energy consumption; Bi is the consumption of type i energy; bi is the conversion coefficient of the i energy source into standard coal; ci is the carbon emission coefficient of the i energy source (IPCC Guidelines for National Greenhouse Gas Inventory, Zhao et al., 2011)

2.4 Construction of land use structure optimization model

2.4.1 Model establishment and solution

In this study, in order to explore the optimal land use structure with ecological benefits under the condition of low carbon, the objective function needs to comprehensively consider carbon emissions and ecological benefits. Moreover, it is difficult to solve conflicts among multiple objective functions using simple linear programming. Therefore, a multi-objective linear programming model was constructed, and its general form can be expressed as:

max(or min)f(x) = (f1(x), f2(x),…fp(x))T

s.t           g i x b i               i = 1 , 2 , , m x 0
Formula (10) refers to finding the maximum or minimum value of the objective function. In the formula, fi(x)=Cix, i=1,2,…, p; x is the required variable vector, C is the coefficient matrix of the objective function, x=(x1, x2,…, xn)T, Ci=(c1, c2,…, cm), and m is the number of variables, gi(x) is the constraint condition, bi is constraint constants.
The linear weighting method was used to solve the multi-objective programming problem in multi-objective decision-making, the coefficients of multiple objective functions were normalized, and the analytic hierarchy process (AHP) was used to assign weight coefficients wi to fp(x), such that the multi-objective programming problem is transformed into single-objective programming, expressed by F(x). The objective function formula is as follows:

max(or min)F(x)=wi f(x)

2.4.2 Setting of decision variables

According to the existing land use situation in the mining area, the land characteristics and recent development and changes were comprehensively considered. Moreover, the requirements of the overall land use planning and the Classification Regulations of Land Use Status were satisfied, and the actual situation of the study area was reflected as much as possible. In this manner, the following five land use types were taken as variables: woodland (x1), grassland (x2), construction land (x3), mining land (x4), water area (x5), and unused land (x6).

2.4.3 Construction of objective function

The objective functions of the multi-objective linear programming model comprised two objective functions based
on minimizing carbon emissions and maximizing the ecosystem service value, as shown below.
(1) Land use carbon emission target
According to the calculated carbon emission coefficients of the six land use types in 2.3, the objective function of carbon emission minimization was constructed:

min f1 (x) = −0.487 x1−0.191 x2 + 63.443 x3 + 56.276 x4 − 0.410 x5 − 0.005 x6

(2) Land use ecological benefit target
The evaluation of the ecological service value of land use was adopted to construct the land use ecological benefit function. For woodland, grassland, water area, and unused land, the market value evaluation method was adopted by referring to Xie et al. (2003, 2008). The ecological service value equivalent scale was developed by referring to relevant studies (Ran et al., 2006; Yuerigul et al., 2019). Considering the actual situation of Wuhai City, the actual value of grain yield per unit area of farmland was revised. According to the Wuhai Statistics Bureau, the sown area of grain in 2018 was 4333.33 ha the grain yield was 36200 t, and the average grain yield was 8353.85 kg ha-1. According to the Wuhai Agriculture and Animal Husbandry Bureau and Wuhai Development and Reform Commission, grain crops such as wheat, corn, and soybean are mainly planted in Wuhai. In the same year, the average purchase price of the three types of grain was 2.588 yuan kg-1. The economic value of a unit farmland ecosystem in Wuhai providing food production services was estimated to be 3088.54 yuan ha-1 yr-1. Accordingly, the ecosystem service value coefficient of woodland, grassland, water area, and unused land in the study area were revised.
The cost estimation method is used to calculate the ecosystem service value of construction land and mining land, mainly calculating the consumption of water conservation and waste treatment service functions. According to the waste water, water resources consumed, tailings and domestic garbage discharged from mining and living activities and their treatment prices, the loss equivalent of ecological service function value under the two land use types is calculated (Table 3).
Table 3 Loss equivalent of ecosystem service function value of industrial and mining land
Land use type Ecosystem service function Basic data Land use type area (ha) Service value equivalent (ha)
Data type Quantity (t) Cost (yuan t-1)
Mining land Water conservation Water resources supply 318780 2.5 793.46 1165.10
Sewage treatment fee 0.3
Water resource fee 0.1
Waste disposal Tailings discharge 90000 15 1701.41
Construction land Water conservation Water resources supply 43560 1.3 100.92 690.61
Sewage treatment fee 0.2
Water resource fee 0.1
Waste disposal household garbage 528.84 20.43 107.06
The ecosystem service value coefficient of each land use type in the mining area is shown in Table 4. According to the ecosystem service value coefficient of each land use type, the objective function of maximizing the ecosystem service value was constructed, as shown below.
Table 4 Ecosystem service value coefficient of land use types
Ecosystem service function Land use type
First-class type Secondary type Plough Woodland Grassland Construction land Mining lease Water area Unused land
Adjustment service Gas regulation 2069.3218 4354.841 6084.424 0.00 0.00 2378.176 339.7394
Climate regulation 1111.8744 13064.52 16091.29 0.00 0.00 7072.757 308.854
Water conservation 833.9058 10346.61 11798.22 -690.61 -1165.1 315772.3 648.5934
Waste disposal 308.854 3953.331 5312.289 -107.06 -1701.41 17141.4 957.4474
Supply service Food supply 2625.259 586.8226 1173.645 0.00 0.00 2470.832 30.8854
Support services Soil conservation 3181.1962 5312.289 7412.496 0.00 0.00 2872.342 401.5102
Biodiversity 401.5102 4849.008 6733.017 0.00 0.00 5837.341 370.6248
Amount 10531.9214 42467.4216 54605.38 -797.67 -2866.51 353545.1 3057.655

max f2(x) = 42467.42 x1+54605.38 x2‒797.67 x3‒2866.51 x4+353545.15 x5+3057.65 x6

2.4.4 Setting of constraints

Based on the Land and Space Planning of Wuhai City (2019-2035), the 14th Five-Year Plan of Green Mine Construction and Mine Geological Environment Governance in Wuhai and its Surrounding Areas (2021-2025), and the main objective constraints of green mine construction planning of coal mines in Luotuoshan, the following seven constraints are proposed.
(1) Total land area constraints
Overall, the study area remains unchanged. The sum of the land use areas in the mining area is 1435.27 ha, and the land use areas are non-negative. The constraint conditions are as follows:
i = 1 6   x i =1435.27 (xi≥0)
(2) Woodland area constraints
The “Wuhai Land and Space Planning (2019-2035)” requires that woodland areas should be appropriately increased and the forest coverage rate should be improved. As the mining area features intense resource development, the plan is focused on building windbreaks on both sides of roads in the mining area, aiming at road greening construction. The woodland area should be set as the lower limit in 2021, and the areas on both sides of roads should be set as the upper limit. The constraint conditions for the woodland area are as follows:

76.46 ≤x1≤145.46

(3) Grassland area constraints
The 14th Five-Year Plan for Green Mine Construction and Mine Geological Environment Governance in Wuhai and Surrounding Areas (2021-2025) requires that the slope greening rate of the contiguous dump in Luotuoshan should reach more than 80%. Accordingly, the lower limit of the planned grassland area should be 80% slope greening. The constraint conditions for grassland area are as follows:


(4) Construction land constraints
The internal construction land in the mining area mainly comprises buildings such as office buildings, factory buildings, and staff quarters in coal washing plants and industrial sites. As some coal mines in the Luotuoshan mining area are still expected to last approximately 10 years, some construction land needs to be reserved. However, under the national low-carbon control policy and time sequence local coal mining, the increase of construction land in 2025 should not exceed the increase of 24.63 ha in the last five years. Therefore, the area of construction land will be larger than that of 2021 and but its increase will be smaller than the sum of the increase in 2021 and the last five years, namely:
100.92   x 3   125.55
(5) Mining land area constraints
As the stopes of all coal mines in the mining area have reached the final boundary, the upper limit of the mining land area is the mining land area in 2021. As some coal mines still need to be mined in 2025, the mining pit and the inner dump area in the mining coal mines are set as the lower limit. The constraints of the mining land area are as follows:


(6) Water resources constraints
The study area is an arid mining area, with scarce water resources. Based on land use data spanning four periods from 2004 to 2021, it appears that the water area has remained relatively stable over the past 18 years. However, with the acceleration of coal mining in the area, water accumulation areas may form during the rainstorm season. To address this issue, plans have been made for the construction of sedimentation tanks and clarifiers across various coal mines, totaling approximately 48.55 ha, in order to treat water accumulation and enable comprehensive utilization. As a result, the lower limit of water area in the mining area has been set at 2021 levels, while the upper limit is set at 48.55 ha, representing the total area of reservoirs.


(7) Unused land area constraints
The unused land in the mining area mainly comprise bare land of untreated slopes and platforms in the dump. In the 14th Five-Year Plan for Green Mine Construction and Mine Geological Environment Treatment in Wuhai and Surrounding Areas (2021-2025), greening work is required on the slopes of the dump, and greening work on bare land in industrial sites is also mentioned in the green mine plans of various coal mines. Therefore, the upper limit of the unused land area is the unused land area in 2021, namely:


3 Results

3.1 Model results

In this study, taking into account carbon emissions and ecological benefits, the coefficients of carbon emissions and ecological benefits functions were normalized inversely and positively, respectively, and the weights of two objective functions, w1 and w2 were set to 0.5. The multi-objective function was transformed into a single objective function, and its constraints with decision variables were rewritten into a programming language. The objective functions established were tested iteratively using LINGO 18.0 software, and the optimal land use structure optimization scheme with the best ecological benefits under low-carbon mining was obtained. The results are shown in Table 5.
Table 5 Optimization results of land use structure in Luotuoshan Mining Area
Variable Area in 2016 (ha) Area in 2021 (ha) Optimized area (ha)
x1 38.44 76.46 76.46
x2 72.72 81.11 750.05
x3 76.29 100.92 100.92
x4 458.19 793.49 457.64
x5 3.27 0.29 48.55
x6 786.37 383.00 0

3.2 Results of land use structure optimization

Comparing the optimized results with the land use area in 2016 and 2021, Fig. 3 and Table 6 show that the grassland, mining land, and unused land in the optimized land use structure change greatly, with the grassland area increasing by 677.33 ha compared with that in 2016 and by 668.94 ha compared with that in 2021. With reference to 2016 and 2021, the area of mining land decreased by 0.55 ha and 335.85 ha, respectively, and the area of unused land decreased by 786.37 ha and 383 ha, respectively.
Fig. 3 Proportion of land use types before and after optimization
Table 6 Carbon emissions of land use before and after optimization (Unit: tC)
Carbon emissions x1 x2 x3 x4 x5 x6
2016 -18.72 -13.89 4844.72 25785.10 -1.34 -3.93
2021 -37.24 -15.49 6408.82 44654.44 -0.12 -1.92
After optimization -37.24 -143.26 6408.82 25754.15 -19.91 0.00
Figure 3 shows that the proportion of optimized woodland and grassland in the total land area increased significantly from that in 2016, with the proportion of woodland increasing by 2.65%. With reference to 2016 and 2021, the proportion of grassland increased by 47.25% and 46.67%, respectively, indicating that the process of low-carbon optimization could well promote the carbon sink effect and ecological benefits of woodland and grassland. In the optimized structure, the proportion of unused land decreased by 54.79% and 26.68% compared with those in 2016 and 2021, respectively. With the acceleration of ecological restoration, the area of unused land gradually decreased. Therefore, we should continue to strengthen the greening of unused land such as bare land and grassland, so as to enhance the carbon sink of the mining area. Compared with 2021, the proportion of mining land decreased by 23.37%. In order to achieve the double-carbon goal and enhance the ecosystem service value, it is necessary to control and reduce the mining land area. At present, all mining pits in the mining area have reached the boundary of the final pit, and some coal mines are already in the stage of land reclamation and ecological restoration. This optimization result agrees with the timing arrangement of coal mining and reclamation.
As shown in Table 6, woodland and grassland are the main carbon sinks in the mining area, and after their optimization, carbon emissions are reduced by 18.52 tC and 129.37 tC, respectively, compared with the corresponding emissions in 2016. Furthermore, the optimization of grassland could reduce carbon emissions by 127.77 tC, with reference to 2021. Construction land and mining land are the main carbon sources. With the acceleration of mining from 2016 to 2021, the carbon emissions from these two land use types increased by 1564.10 tC and 18869.34 tC, respectively, in the five years. Therefore, it is urgent to adjust the land use structure to reduce their carbon emissions. As construction land in the mining area requires continued use, the mining land can be primarily optimized. After optimization, the carbon emissions from mining land decreased by 30.95 tC compared with that in 2016.
As shown in Table 7, carbon emissions from land use reached 51008.50 tC in 2021. Nevertheless, it could be reduced to 31962.57 tC through the optimization, amounting to a reduction of 19045.93 tC. On the whole, the area of mining land as the main carbon source will decrease, and the area of carbon sinks such as grassland and water will increase. At the same time, the value of ecosystem services will increase from 6594700 yuan to 59976100 yuan, an increase of 53381400 yuan. This can be attributed to the large increase in the area of grassland and water area, which will enhance the supply capacity of ecosystem regulation services. Mining land will gradually be transformed into grassland through land reclamation and ecological restoration, which will reduce the loss of the ecosystem service value.
Table 7 Changes of carbon emissions and ecological benefits before and after optimization
Index Before the optimization After the optimization Change value
Carbon emissions (tC) 51008.50 31962.57 -19045.93
Ecosystem service value (104 yuan) 659.47 5997.61 5338.14
In summary, the optimization and adjustment of the land use structure in mining areas based on low carbon emission and ecological benefits actively responded to the national call for “peak carbon dioxide emissions, and carbon neutrality” and the construction of green mines in Inner Mongolia. While complying with the production sequence and industrial transformation of coal mines in mining areas, it effectively achieved carbon emission reduction, taking into account the improvement of the ecological benefits of land use in mining areas. Essentially, the optimization scheme could meet the requirements of the optimal comprehensive benefits of land use in the Luotuoshan mining area.

4 Conclusions

This study constructed a multi-objective programming model, with low carbon emission and high ecosystem service value as the objective functions. Furthermore, model constraints were set according to the development plan of a mining area. LINGO.18 software was used to solve the model, and an optimization scheme of the land use structure in a mining area was obtained.
(1) Compared with 2016 and 2021, Grassland area increased by 677.33 ha and 668.94 ha respectively; The mining land area decreased by 0.55 ha and 335.85 ha; The water area increased by 45.28 ha and 48.26 ha; The unused land area decreased by 786.37 ha and 383.00 ha. Compared with 2016, the area of woodland after land use structure optimization increased by 668.94 ha; The construction land area increased by 24.63 ha.
(2) Compared with 2016 and 2021, the carbon emissions of woodland after land use structure optimization decreased by 18.52 tC and 0.00 tC; Grassland carbon emissions decreased by 129.37 tC and 127.77 tC; Carbon emissions from construction land increased by 1564.10 tC and 0.00 tC; Carbon emissions from mining land decreased by 30.9 tC and 18900.29 tC; Carbon emissions in the water area decreased by 18.56 tC and 19.79 tC;Unused carbon emissions increased by 3.93 tC and 1.92 tC.
(3) Compared with 2021, the total carbon emissions could be decreased by 19045.93 tC and the total value of ecosystem services increased by 53381400 yuan using the optimization scheme. This scheme meets the needs of carbon emission reduction, green mine construction, and industrial transformation in mining areas. The multi-objective linear programming model can be used to optimize the allocation of land resources in mining areas, provide guidance for land reclamation and ecological restoration in mining areas in the future, and propose directions for green mine construction and sustainable development of land resources in mining areas under the “double carbon” goal.
Duan X N, Wang X K, Fei F, et al. 2008. Carbon sequestration and its potential by wetland ecosystems in China. Acta Ecologica Sinica, 28(2): 463-469. (in Chinese)


Fan D L, Li F B, Wang Z L, et al. 2021. Development status and prospects of China’s energy minerals under the target of carbon peak and carbon neutral. China Mining Magazine, 30(6): 1-8. (in Chinese)

Fang J Y, Guo Z D, Park S L, et al. 2007. Estimation of carbon sink of China’s land vegetation from 1981 to 2000. Scientia Sinica (Terrae), 37(6): 804-812. (in Chinese)

Guo Y G. 2009. The analysis on calculation and characteristics of greenhouse gas emission in Mega-cities—A case study of Shanghai. Diss., Shanghai, China: East China Normal University. (in Chinese)

He Y, Tang X L, Dai J F. 2021. Land-use structure optimization for the Lijiang River Basin ecosystem service value maximization. Acta Ecologica Sinica, 41(13): 5214-5222. (in Chinese)

Houghton R A. 2002. Magnitude, distribution and causes of terrestrial carbon sinks and some implications for policy. Climate Policy, 2(1): 71-88.


Huang Y F, Zhang S W, Zhang L P, et al. 2015. Research progress on conservation and restoration of biodiversity in land reclamation of opencast coal mines. Transactions of the Chinese Society for Agricultural Machinery, 46(8): 72-82. (in Chinese)

Kuang Y Q, Ouyang T P, Zou Yi, et al. 2010. Present situation of carbon source and sink and potential for increase of carbon sink in Guangdong Province. China Population Resources and Environment, 20(12): 56-61. (in Chinese)

Lai L. 2010. Study on carbon emission effect of land use in China. Diss., Nanjing, China: Nanjing University. (in Chinese)

Li H Q, Li W Q, Zheng F. 2021. Optimal land use structure for sustainable agricultural development—A case study in Changsha County, south central China. Journal of Resources and Ecology, 12(2): 203-213.


Li S Z, Li X L, Yin D W. 2022. Several basic issues of ecological restoration of coal mines under background of carbon neutrality. Coal Science and Technology, 50(1): 286-292. (in Chinese)

Li X K, Wang X M, Hua H. 2018. Research on influences of land use structure change on carbon emissions. Ecological Economy, 34(1): 14-19. (in Chinese)

Marull J, Pino J, Tello E, et al. 2010. Social metabolism, landscape change and land-use planning in the Barcelona Metropolitan Region. Land Use Policy, 27(2): 497-510.


Meng M, Cui X Y, Wang Z Q. 2019. Study on land ues structure optimization in Urumqi City at background of low-carbon. Jiangsu Agricultural Science, 47(19): 261-265. (in Chinese)

Qu F T, Lu N, Feng S Y. 2011. Effects of land ues change on carbon emissions. China Population, Resources and Environment, 21(10): 76-83. (in Chinese)

Ran S H, Lu C H, Jia K J, et al. 2006. National environmental impact assessment of land use change based on ecological service value. Environmental Science, 27(10): 2139-2144. (in Chinese)

Shi H X, Mu X M, Zhang Y L, et al. 2012. Effects of different land ues patterns on carbon emission in Guangyuan City of Sichuan Province. Bulletin of Soil and Water Conservation, 32(3): 101-106. (in Chinese)

Wang G S, Liu H L, Wu Q, et al. 2022. Resource development and utilization of positive environmental impacts of abandoned mines under carbon neutrality. Coal Science and Technology, 50(6): 321-328. (in Chinese)

Xie G D, Lu C X, Leng Y F, et al. 2003. Evaluation of ecological assets in Qinghai-Tibet Plateau. Journal of Natural Resources, 18(2): 189-196. (in Chinese)

Xie G D, Zhen L, Lu C X, et al. 2008. A valuation method of ecosystem services based on expert knowledge. Journal of Natural Resources, 23(5): 911-919. (in Chinese)

Yuerigul K S M, Yang S T, Zibibla S M Y. 2019. Impact of land use change on ecosystem service value in Ebinur Lake Basin, Xinjiang. Journal of Agricultural Engineering, 35(2): 260-269. (in Chinese)

Zhang Z F. 2013. Research on carbon emission accounting and carbon emission reduction ways in opencast coal mines. Diss., Beijing, China: China University of Mining and Technology. (in Chinese)

Zhao R Q, Huang X J, Zhong T Y, et al. 2011. Carbon footprint of different industrial spaces based on energy consumption in China. Journal of Geographic Sciences, 21(2): 285-300.


Zhao T N, Zhang Y X, Cao B, et al. 2018. Eco-security technology for coal mining bases in the northwest arid desert regions in China. Journal of Soil and Water Conservation, 32(1): 1-5. (in Chinese)