International Journal of Environmental Research and Public Health
Article A System Dynamics Model for Ecological Environmental Management in Coal Mining Areas in China
Fulei Shi , Haiqing Cao *, Chuansheng Wang * and Cuiyou Yao
School of Management and Engineering, Capital University of Economics and Business, Beijing 100070, China; [email protected] (F.S.); [email protected] (C.Y.) * Correspondence: [email protected] (H.C.); [email protected] (C.W.)
Received: 3 February 2020; Accepted: 19 March 2020; Published: 23 March 2020
Abstract: In recent years, mounting attention has been paid to ecological environmental management in coal mining areas in China. This paper conducts a system dynamics (SD) model for ecological environmental management in coal mining areas. Firstly, the whole causal loop diagram of the system is built to illustrate the general system. Secondly, five subsystems are presented according to the causal loop diagram. Then, given the stable investment for ecological environmental management in coal mining areas, our objective is to find a better allocation that can get the best ecological environmental quality in coal mining areas. Notably, we present six allocations of the investment for ecological environmental management in coal mining areas. The results show that, in allocation 4, we can get the best ecological environmental quality in coal mining areas. That is, the best improvement of mining environment can be achieved by distributing the treatment cost highly on the proportion of investment in green vegetation.
Keywords: ecological environmental management; system dynamics model; coal mining areas
1. Introduction In the past few decades, due to the fast economy development and the consequently soaring demand for coal to generate electricity, China has become the largest coal producer and consumer in the world [1]. While coal makes an important contribution to energy generation, its environmental impact has been a challenge [2]. The expansion of the coal mining industry in China has placed high pressure on the ecological environmental management in coal mining areas. As a result, a mounting amount of pollution generated. Such as air pollution, water pollution, solid waste pollution, vegetation destruction, land damage and so on. Therefore, how to effectively improve the quality of the ecological environment in coal mining areas has become an urgent problem to be solved. In recent years, researches on ecological environmental management in coal mining areas have become a very popular project for scholars to deal with. In one branch, for a review of the literature on policies of ecological environmental management in coal mining areas, see [3–7]. For example, Franks et al. [3] analyzed the cumulative impacts of coal mining on regional communities and environments in Australia. Yu [4] presented a case study in southwest China to learn the role of sustainable coal mining in enhancing environmental quality and combating global environmental change. Mikhailov et al. [5] discussed the ecological risk management in coal mining and processing. Gautam et al. [6] studied particulate matter pollution in opencast coal mining areas. Chabukdhara and Singh [7] made an overview of environmental issues and treatment approaches. Then, he proposed some management and treatment strategies to reduce environmental impacts of coals. However, these literatures only stay at the level of theoretical analysis, lacking effective methods
Int. J. Environ. Res. Public Health 2020, 17, 2115; doi:10.3390/ijerph17062115 www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2020, 17, 2115 2 of 17 and data support. In another branch, different kinds of methods are used to study the ecological environmental management in coal mining areas, such as modeling and simulation, statistical analysis method, application of GIS, AHP approach and so on, see [8–18]. For example, Kowalska [8] studied the problem of environmental and social risk management during the process of colliery liquidation. Li et al. [9] took Mentougou district of Beijing as a case, discussed the ecosystem service loss of coal mining in China. Based on the application of GIS, Liao et al. [10] evaluated ecological vulnerability in environmental impact assessment of master plan of coal mining area. Mahdevari et al. [11] presented a fuzzy TOPSIS method to study human health and safety risks management in underground coal mines. Shen et al. [13] proposed an AHP approach to explore how the “appropriate implementation approach” and “continuous improvement” are the weaker area in the case of the Indian mining sector. Yu and Gao [17] established a dynamic programming model to discuss environmental investment decision-making in coal mining. Although they used some effective methods to analysis the ecological environmental management in coal mining areas, how to allocate environmental investment in coal mining areas into many ways can get the best effect in the environmental quality has been rarely discussed. Forrester [19] established system dynamics (SD) model to study the behaviors of feedback loops which contain stocks (levels) and flows. SD provides an effective way for modeling, simulating and studying complex systems. It has been applied to many areas, such as environment, supply chains, water management, transportation and so on [20–29]. For example, Song et al. [21] proposed a system dynamics model to simulate the land green supply chain, they divided it into four subsystems to simulate the develop trend of technology, energy, environment, and economy in Shandong Province from 2003 to 2020. Chen and Wei [22] discussed the SD model in the application of water security. Golroudbary and Zahraee [23] established a SD model to evaluate the system behavior of an electrical manufacturing company. Sahin et al. [26] presented a SD model that augments the usual water utility representation of the physical linkages of water grids, by adding inter-connected feedback loops in tariff structures, demand levels and financing capacity. Thompson and Bank [28] proposed a SD model to build design and operation, and demonstrates the use of the method for the analysis of a building subjected to a bioterrorist attack. Notably, Yu and Wei [30] presented a hybrid model based on a genetic algorithm and SD for coal production environmental pollution load in China. To the best of our knowledge, there is little research discussing the topic of ecological environmental management in coal mining areas in China in a SD model. Moreover, the government will make environmental investment in coal mining areas in China, and how to allocate it into many ways can get the best effect in the environmental quality is a complex project to deal with. SD can provide an effective way on this problem. Therefore, in this paper, our contributions can be summarized as follows: (1) Given the stable investment, we propose a SD model for ecological environmental management in coal mining areas to find a better allocation that can get the best ecological environment quality in coal mining areas. (2) We discuss six cases in our study, then, some simulations are given to illustrate the results. The rest of this paper is organized as follows: In Section2, we describe in detail about the SD model. In Section3, we conduct a case study in China. Then, some simulations are proposed. In Section4, we present the results of our study. In Section5, we present the discussion to illustrate some contributions and some limitations of the study. In the last Section6, we discuss the conclusions of the study and introduced some work in the further research.
2. The SD Model In this section, the SD model for ecological environmental management in coal mining areas in China is established. Int. J. Environ. Res. Public Health 2020, 17, 2115 3 of 17
2.1. Causal Relationship of Ecological Environment in Coal Mining Area In this paper, we regard the coal mining areas as a whole system. As we all know, there are many subsystems in coal mining areas. To simplify the analysis, we just suppose that there are five Int. J. Environ. Res. Public Health 2020, 17, x 3 of 16 subsystems, namely: Atmospheric subsystem, solid waste subsystem, water resource subsystem, vegetation cover subsystem and land reclamation subsystem according to the introduction of problems problems in coal mining areas [2]. Then, the whole causal loop diagram of the system is shown in in coal mining areas [2]. Then, the whole causal loop diagram of the system is shown in Figure1. Figure 1.
GDP + + Environmental Investment - + + Investment in land Investment in water reclamation + pollution control Investment in solid waste management + + Investment ecological environment Vegetation in air quality in coal mining areas + treatment - investment + - - + Solid pollution Land - index reclamation Vegetation rate Water pollution greening rate + index Mining Air quality + revenue ++ - - - Cost of pollution control in mining area
Figure 1. The whole causal loop diagram of the system.
From Figure1 1,, severalseveral causalcausal feedbackfeedback loops loops see see as as follows: follows:
(1) GDPGDP →+ EnvironmentalEnvironmental Investment →++ InvestmentInvestment inin air air treatment treatment →+ +Air Air quality quality –→ Cost– Cost of → → → → ofpollution pollution control control in in mining mining area area +→Mining+ Mining revenue revenue +→GDP.+ GDP. → → → → → (2) GDPGDP + EnvironmentalEnvironmental Investment Investment + InvestmentInvestment in in solid solid waste waste management management – Solid → → → → → → pollutionpollution index index + Cost of pollution control in mining area –– MiningMining revenuerevenue ++GDP. GDP. (3) GDP →+ Environmental→ Investment →+ Investment in water→ pollution control→ →– Water (3) GDP + Environmental Investment + Investment in water pollution control – Water pollution→ index →+ Cost of pollution control→ in mining area →– Mining revenue →+→ GDP. pollution index + Cost of pollution control in mining area – Mining revenue + GDP. (4) GDP →+ Environmental→ Investment →+ Vegetation investment→ →– Vegetation →greening rate (4) GDP + Environmental Investment + Vegetation investment – Vegetation greening rate + →+ Cost→ of pollution control in mining→ area →– Mining revenue→ →+ GDP. → Cost of pollution control in mining area – Mining revenue + GDP. (5) GDP →+ Environmental Investment →+→ Investment in land →reclamation →– Land reclamation (5) GDP + Environmental Investment + Investment in land reclamation – Land reclamation rate →→+ Cost of pollution control in mining→ area →– Mining revenue →+→ GDP. rate + Cost of pollution control in mining area – Mining revenue + GDP. (6) Environmental→ Investment →+ Investment in air→ treatment →+ Air→ quality →+ ecological (6) Environmental Investment + Investment in air treatment + Air quality + ecological environment quality in coal mining→ areas →– Environmental Investment.→ → environment quality in coal mining areas – Environmental Investment. (7) Environmental Investment →+ Investment→ in solid waste management →+ Solid pollution (7) Environmental Investment + Investment in solid waste management + Solid pollution index index →– ecological environment→ quality in coal mining areas →– Environmental→ Investment. – ecological environment quality in coal mining areas – Environmental Investment. (8) Environmental→ Investment →+ Investment in water pollution→ control →– Water pollution index →– ecological environment quality in coal mining areas →– Environmental Investment. (9) Environmental Investment → + Vegetation investment → – Vegetation greening rate → – ecological environment quality in coal mining areas →– Environmental Investment. (10) Environmental Investment →+ Investment in land reclamation →– Land reclamation rate →– ecological environment quality in coal mining areas →– Environmental Investment.
Int. J. Environ. Res. Public Health 2020, 17, 2115 4 of 17
(8) Environmental Investment + Investment in water pollution control – Water pollution index → → – ecological environment quality in coal mining areas – Environmental Investment. → → (9) Environmental Investment + Vegetation investment – Vegetation greening rate – ecological → → → environment quality in coal mining areas – Environmental Investment. → (10) Environmental Investment + Investment in land reclamation – Land reclamation rate – → → → ecological environment quality in coal mining areas – Environmental Investment. → From the above loops, we just take loops (1) and (6) as two examples to make an explanation. Loops (1) is a positive feedback loop. A positive feedback loop means that an increase of the first parameter will finally lead to a higher level of the first parameter. An increase in the degree of GDP will increase the environmental investment, leading to higher investment in air treatment and higher air quality. Ultimately, this reduces the cost of pollution control in coal mining area, leading to a higher mining revenue and GDP. Loops (6) is a negative feedback loop. A negative feedback loop means that an increase of the first parameter will finally lead to a lower level of the first parameter. An increase in the degree of environmental investment will increase the investment in air pollution, leading to higher air quality and ecological environment quality in coal mining areas. Ultimately, this leading to a lower environmental investment.
2.2. Flow Diagram of Ecological Environment Subsystem in coal Mining Area Assumption: To illustrate the results more clearly, we assume that five subsystems are interdependent and independent of each other. As we all know, in each subsystem, the environmental quality will be influenced by other subsystems in the real world. Here, to simplify the model, we assume that the environmental quality is determined only by this subsystem, not influenced by other subsystems. Based on the analysis of the causal relationship of ecological environment in coal mining area, we can establish five subsystems as follows:
2.2.1. Atmospheric Subsystem The atmospheric subsystem is an important part of the ecological environment system of coal mining areas, which plays an important role in improving the air quality of coal mining areas. The system flow diagram is presented in Figure2. Int. J. Environ. Res. Public Health 2020, 17, x 4 of 16
From the above loops, we just take loops (1) and (6) as two examples to make an explanation. Loops (1) is a positive feedback loop. A positive feedback loop means that an increase of the first parameter will finally lead to a higher level of the first parameter. An increase in the degree of GDP will increase the environmental investment, leading to higher investment in air treatment and higher air quality. Ultimately, this reduces the cost of pollution control in coal mining area, leading to a higher mining revenue and GDP. Loops (6) is a negative feedback loop. A negative feedback loop means that an increase of the first parameter will finally lead to a lower level of the first parameter. An increase in the degree of environmental investment will increase the investment in air pollution, leading to higher air quality and ecological environment quality in coal mining areas. Ultimately, this leading to a lower environmental investment.
2.2. Flow Diagram of Ecological Environment Subsystem in coal Mining Area Assumption: To illustrate the results more clearly, we assume that five subsystems are interdependent and independent of each other. As we all know, in each subsystem, the environmental quality will be influenced by other subsystems in the real world. Here, to simplify the model, we assume that the environmental quality is determined only by this subsystem, not influenced by other subsystems. Based on the analysis of the causal relationship of ecological environment in coal mining area, we can establish five subsystems as follows:
2.2.1. Atmospheric Subsystem The atmospheric subsystem is an important part of the ecological environment system of coal miningInt. J. Environ. areas, Res. which Public Healthplays2020 an ,important17, 2115 role in improving the air quality of coal mining areas. 5 The of 17 system flow diagram is presented in Figure 2.
Air pollution Air pollution Amount of air production pollution control
Air pollution Dust Waste gas index
Technical factors of Investment in air NO2 SO2 CO air pollution control treatment
Environmental Investment Proportion of investment in air pollution control
Figure 2. TheThe system system flow flow diagram of atmospheric subsystem.
In Figure 22,, airair pollutionpollution isis thethe statestate variable,variable, airair pollutionpollution productionproduction andand thethe amountamount ofof airair pollution control are the rate of the variables. Air pollution means the area of the air pollution. It is equal to air pollution production minus the amount of air pollution control. As As can can be seen from Figure 22,, airair pollutionpollution productionproduction isis consistedconsisted ofof dustdust andand wastewaste gas.gas. TheThe wastewaste gasgas isis consistedconsisted ofof
NONO22,, SOSO22 andand COCO. In. In this this model, model, to simplify to simplify the analysis, the analysis, according according to the work to the [27 work–30], the [27 equations–30], the equationsin this model in this are model shown are in shown Equations in Equations (1)–(6). As(1)– shown(6). As shown in Equations in Equations (2)–(4), (2) the–(4), amount the amount of air pollution production is equal to the amount of dust plus the amount of waste gas, and the amount of the waste gas is equal to the amount of NO2, SO2 and CO. The amount of air pollution control is meant the amount of air pollution that is treated, the value of the amount of air pollution is equal to (Air pollution producation).K (Technical f actors o f air pollution control). Technical factors of air × pollution control is depended on the investment in air pollution, the higher the value of the investment in air pollution, the higher the value of technical factors of air pollution control. Equations about the Figure2 are presented as follows:
L : (Air pollution).K = (Air pollution production).J + DT ((Air pollution production).JK × − (1) (Amount o f air pollution control).JK).
R : (Air pollution production).JK = (Dust).J + (Waste gas).J. (2)
R : (Amount o f air pollution control). JK = (Air pollution).K (Technical f actors o f air × (3) pollution control)
Waste gas = NO2 + SO2 + CO (4) Technical f actors o f air pollution control = Investment in air treatment/Environmental (5) investment
Investment in air treatment = Proportion o f investment in air pollution control × (6) Environmental investment In Equations (1)–(3), L is the equation of state, R is the equation of rate. DT is the time interval. (Air pollution).K is the amount of air pollution in the current period. (Air pollution production).J is the amount of air pollution production at the moment J. (Air pollution production).JK and Int. J. Environ. Res. Public Health 2020, 17, x 5 of 16 of air pollution production is equal to the amount of dust plus the amount of waste gas, and the amount of the waste gas is equal to the amount of NO2 , SO2 and CO . The amount of air pollution control is meant the amount of air pollution that is treated, the value of the amount of air pollution is equal to ().()Air pollution producationKTechnical factors of air pollution control . Technical factors of air pollution control is depended on the investment in air pollution, the higher the value of the investment in air pollution, the higher the value of technical factors of air pollution control. Equations about the Figure 2 are presented as follows: LAir: ().().((). pollution KAir pollution=+− production JDTA ir pollution production JK ().).Amount of air pollutioncontrol JK (1)
RAir:().().().. pollution productionJKDustJWaste=+ gasJ (2)
RAof: (mount).().( air pollution controlJKAir pollution= KTe chnical factors of air (3) pollution control)
Waste gasNOSOCO=++ 22 (4)
Technical factors of air pollution controlInv= estment in air treatmentEnvironmental/ (5) investment
Investment in air treatment= Proportion of investment in air pollution control (6) Environmental investment
In Equations (1)–(3), L is the equation of state, R is the equation of rate. DT is the time Int.interval. J. Environ. Res.().AirpollutionK Public Health 2020 ,is17 , 2115 the amount of air pollution in the current period. 6 of 17 ().Air pollution productionJ is the amount of air pollution production at the moment J . (Amount().Air pollution o f air productionJK pollution control and) .JK().Amountrespectively of air pollution represent controlJK the amount respectively of air representpollution productionthe amount andof air air pollution pollution production control in theand period air pollutionJK. control in the period JK .
2.2.2.2.2.2. SolidSolid WasteWaste SubsystemSubsystem SolidSolid wastewaste subsystemsubsystem isis alsoalso veryvery importantimportant forfor ecologicalecological environmentalenvironmental qualityquality inin coalcoal miningmining areas.areas. TheThe systemsystem flowflow diagramdiagram isis presentedpresented inin FigureFigure3 .3.
Solid waste Coal gangue Living garbage Boiler ash pollution index
Solid waste Solid waste pollution Solid waste production treatment amount
Technical factors of Investment in solid solid waste treatment waste treatment
Proportion of investment Environmental Investment in solid waste treatment
FigureFigure 3.3. TheThe systemsystem flowflow diagramdiagram ofof solidsolid wastewaste subsystem.subsystem.
In Figure3, solid waste pollution is the state variable, solid waste production and solid waste treatment amount are the rate of the variables. Here, solid waste treatment amount means the amount of solid waste that is treated. Similar to the analysis in Figure2, here, according to the work [ 27–30], the equations about the Figure3 are presented as follows:
L : (Solid waste pollution).K = (Solid waste production).J + DT ((Solid waste × (7) production).JK (Solid waste treatment amount).JK). − R : (Solid waste production).JK = (Coal gangue). J + (Living garbage). J + (Boiler ash).J. (8)
R : (Solid waste treatment amount). JK = (Solid waste production).K (Technical f actors o f × (9) Solid waste treatment)
Technical f actors o f solid waste treatment = Investment in solid waste treatment/ (10) Environmental investment
Investment in solid waste treatment = Proportion o f investment in solid waste treatment × (11) Environmental investment
2.2.3. Water Resource Subsystem Water resource subsystem is established in this section. The system flow diagram is presented in Figure4. Int. J. Environ. Res. Public Health 2020, 17, x 6 of 16
In Figure 3, solid waste pollution is the state variable, solid waste production and solid waste treatment amount are the rate of the variables. Here, solid waste treatment amount means the amount of solid waste that is treated. Similar to the analysis in Figure 2, here, according to the work [27–30], the equations about the Figure 3 are presented as follows: LSolid: ().().(( waste pollution KSolid=+ waste productio n JDTSolid waste production).().). JKSolid− wastetreatment amount JK (7)
R:( Solid waste production ).( JK= Coal gangue ).( J + Living garbage ).( J + Boiler ash ).. J (8)
R: ( Solid wastetreatment amount ). JK= ( Solid waste production ). K ( Technical factors of (9) Solid wastetreatment)
Technical factors of solid wastetreatmentInv= estment in solid wastetreatment / (10) Environmental investment
Investment in solid wastetreatmentProportio=n of investment in solid wastetreatment (11) Environmental investment
2.2.3. Water Resource Subsystem Int. J.Water Environ. resource Res. Public subsystem Health 2020, 17 is, 2115 established in this section. The system flow diagram is presented 7 of 17 in Figure 4.
Water pollution Mine water Gangue leaching Life wastewater index
Water pollution Water pollution Amount of water production pollution control
Technical factors of water Investment in water pollution treatment pollution control
Environmental Investment Proportion of investment in water pollution control
Figure 4. The system flow flow diagram of water resource subsystem.
In Figure4 4,, waterwater pollutionpollution isis thethe statestate variable,variable, waterwater pollutionpollution productionproduction andand thethe amountamount ofof water pollution control are thethe raterate ofof thethe variables.variables. Here, amount of water pollution control means the amountamount of water pollution thatthat isis treated.treated. According to the literature [[2727–3030],], the main equations concerning Figure4 4 are are presented presented as as follows: follows: L: (). Water ().(( pollution K=+ Water pollution production J DT Water pollution L : (Water pollution).K = (Water pollution production).J + DT ((Water pollution (12) production). JK− (). Amount ). of water× plooutioncontrol JK (12) production).JK (Amount o f water plooution control).JK). R: ( Water pollution production ). JK= ( Coal− gangue ). J + ( Life wastewater ). J + (13) R : (Water pollution production).JK = (CoalMine gangue water ).) J.J++ ( Gangueleaching(Li f e wastewater) )..J + . (13) (Mine water).J + (Gangue leaching).J.
R : (Amount o f water pollution control).JK = (Water pollution production).K (Technical × (14) f actors o f water pollution treatment)
Technical f actors o f water pollution treatment = Investment in water pollution control/ (15) Environmental investment
Investment in water pollution control = Proportion o f investment in water pollution control × (16) Environmental investment
2.2.4. Vegetation Cover Subsystem and Land Reclamation Subsystem To simplify, similar to the above analyses, we can get the vegetation cover subsystem and land reclamation subsystem. The system flow diagram of vegetation cover subsystem is presented in Figure5, then, the system flow diagram of land reclamation subsystem is presented in Figure6. Int. J. Environ. Res. Public Health 2020, 17, x 7 of 16
RAmount: ().().( of water pollution controlJKWater= pol lution production KTechnical (14) factors of water pollution treatment)
Technical factors of water pollution treatmentInvestment= in water pollution control / (15) Environmental investment
Investment in water pollution controlProport=ion of investment in water pollution control (16) Environmental investment
2.2.4. Vegetation Cover Subsystem and Land Reclamation Subsystem To simplify, similar to the above analyses, we can get the vegetation cover subsystem and land Int.reclamation J. Environ. Res. subsystem. Public Health The2020 , system17, 2115 flow diagram of vegetation cover subsystem is presented 8 of in 17 Figure 5, then, the system flow diagram of land reclamation subsystem is presented in Figure 6.
Construction of mining Waste rock Degree of vegetation Total vegetation industry square pile up destruction area
Vegetation destruction area Total area of destruction area Green vegetation destruction vegetation area
Technical factors of Investment in air Open-pit mining Road Technical factors of Investment in air air pollution control treatment
Environmental Investment Proportion of investment in air Environmental Investment pollution control pollution control Figure 5. The system flow flow diagram of water resource subsystem.
Land area Land damage Land area reclamation area
Land Land Land Land to dig reclamation rate subsidence Land to dig Technical factors of Investment in land land reclamation reclamation
Proportion of investment in Environmental Investment land reclamation
Figure 6. The system flow flow diagram of water resource subsystem.
2.3. General System Flow Diagram of Ecological Environment in Coal Mining Area Based on the above analyses, the general system flow diagram of ecological environment in coal mining area is established in Figure7. As can be seen from Figure7, the five subsystems are combined with the variable “Environmental investment”. Here, to simplify the analysis, as can be seen from Equation (A11), to find a better allocation that can get the best ecological environmental quality in coal mining areas, we use the variable “Environmental quality assessment” to show the ecological environmental quality in coal mining areas. We assume that the value of it is the average quality of the five sub-systems. The higher the value of environmental quality assessment, the higher the environmental quality in coal mining areas. All Equations left in the general system are shown in AppendixA. Int. J. Environ. Res. Public Health 2020, 17, x 8 of 16
2.3. General System Flow Diagram of Ecological Environment in Coal Mining Area Based on the above analyses, the general system flow diagram of ecological environment in coal mining area is established in Figure 7. As can be seen from Figure 7, the five subsystems are combined with the variable “Environmental investment”. Here, to simplify the analysis, as can be seen from Equation (A11), to find a better allocation that can get the best ecological environmental quality in coal mining areas, we use the variable “Environmental quality assessment” to show the ecological environmental quality in coal mining areas. We assume that the value of it is the average quality of the five sub-systems. The higher the value of environmental quality assessment, the higher the environmentalInt. J. Environ. Res. quality Public Health in 2020coal, 17mining, 2115 areas. All Equations left in the general system are shown 9 of in 17 Appendix A.
Vegetation destruction area Open-pit Total area of mining vegetation Green vegetation area
Land area Water pollution Land damage Land Amount of water Water pollution area reclamation area pollution control production Investment in water Investment in land pollution control Technical factors of reclamation Technical factors of land reclamation Life wastewater water pollution Land treatment subsidence Proportion of
3. A A case case Study in China In the model, we setset thethe initialinitial valuevalue asas INITIAL-TIMEINITIAL-TIME == 0, FINAL-TIMEFINAL-TIME = 24, TIME TIME-STEP-STEP = 1.1. Units for Time: Month. Integration Integration Type: Euler. Then, Then, a a case study in China is presented.
3.1. Data 3.1. Data In this section, a case study of coal mining area in Shanxi Province is presented. The data is In this section, a case study of coal mining area in Shanxi Province is presented. The data is referenced by Ministry of Natural Resources of the People’s Republic of China and Shanxi provincial referenced by Ministry of Natural Resources of the People’s Republic of China and Shanxi provincial environmental protection department. The parameters of this model include state variable, rate of environmental protection department. The parameters of this model include state variable, rate of the variable, instrumental variable and the constant. Then, the specific initial variables are presented the variable, instrumental variable and the constant. Then, the specific initial variables are presented in Table1. in Table 1.
Table 1. The main parameters in the model.
Variable Types The Variable Name The Initial Value Unit Construction of mining industry 30,000 m2 square Constant Waste rock pile up 9833 m2 Open-pit mining 1500 m2 Road 80 m2
Int. J. Environ. Res. Public Health 2020, 17, 2115 10 of 17
Table 1. The main parameters in the model.
Variable Types The Variable Name The Initial Value Unit Construction of mining industry 30,000 m2 square Waste rock pile up 9833 m2 Open-pit mining 1500 m2 Road 80 m2 Ten thousand Environmental Investment 50 yuan Constant Total vegetation area 2645.2 10,000 m2 Dust 3310 m2 Waste gas 1514 m2 Land subsidence 4400 m2 Land to dig 8800 m2 Coal gangue 8750 m2 Boiler ash 298 m2 Life waste water 980 m2 Mine water 5392 m2 Gangue leaching 73 m2 Vegetation destruction area 275 10,000 m2 Air pollution 300 m2 State variables Land area 450 10,000 m2 Solid waste pollution 25.6 m2 Water pollution 35 m2
3.2. Simulations In this section, we select five indexes, namely, proportion of investment in green vegetation, proportion of investment in air pollution control, proportion of investment in land reclamation, proportion of investment in water pollution control and proportion of investment in solid waste treatment, as the control parameters for simulation control. Then, the following five regulatory schemes are presented in Table2.
Table 2. The five regulatory schemes.
Regulatory Schemes Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Proportion of investment in air 0.4 0.15 0.15 0.15 0.15 0.2 pollution control Proportion of investment in 0.15 0.4 0.15 0.15 0.15 0.2 solid waste treatment Proportion of investment in 0.15 0.15 0.4 0.15 0.15 0.2 water pollution control Proportion of investment in 0.15 0.15 0.15 0.4 0.15 0.2 green vegetation Proportion of investment in 0.15 0.15 0.15 0.15 0.4 0.2 land reclamation
To illustrate the results, we analyze the environmental pollution control of coal mining areas from six aspects: Total vegetation destruction area, solid waste pollution, water pollution, land area, air pollution and environmental quality assessment. Then, the simulation results are presented in Figures8–13. Int. J. Environ. Res. Public Health 2020, 17, x 9 of 16
Environmental Investment 50 Ten thousand yuan Total vegetation area 2645.2 10,000 m2 Dust 3310 m2 Waste gas 1514 m2 Land subsidence 4400 m2 Land to dig 8800 m2 Coal gangue 8750 m2 Boiler ash 298 m2 Life waste water 980 m2 Mine water 5392 m2 Gangue leaching 73 m2 Vegetation destruction area 275 10,000 m2 Air pollution 300 m2 State variables Land area 450 10,000 m2 Solid waste pollution 25.6 m2 Water pollution 35 m2
3.2. Simulations In this section, we select five indexes, namely, proportion of investment in green vegetation, proportion of investment in air pollution control, proportion of investment in land reclamation, proportion of investment in water pollution control and proportion of investment in solid waste treatment, as the control parameters for simulation control. Then, the following five regulatory schemes are presented in Table 2.
Table 2. The five regulatory schemes.
Regulatory Schemes Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Proportion of investment in air pollution control 0.4 0.15 0.15 0.15 0.15 0.2 Proportion of investment in solid waste treatment 0.15 0.4 0.15 0.15 0.15 0.2 Proportion of investment in water pollution control 0.15 0.15 0.4 0.15 0.15 0.2 Proportion of investment in green vegetation 0.15 0.15 0.15 0.4 0.15 0.2 Proportion of investment in land reclamation 0.15 0.15 0.15 0.15 0.4 0.2
To illustrate the results, we analyze the environmental pollution control of coal mining areas from six aspects: Total vegetation destruction area, solid waste pollution, water pollution, land area,
Int.air J.pollution Environ. Res. and Public environmental Health 2020, 17, 2115 quality assessment. Then, the simulation results are presented 11 of 17in Figures 8–13.
10
7.5
5
Air Air pollution (10000m^2) 2.5
0 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Air pollution : case 1 Air pollution : case 4 Air pollution : case 2 Air pollution : case 5 Air pollution : case 3 Air pollution : case 6 Int. J. Environ. Res. Public Health 2020, 17, x 10 of 16 Int. J. Environ. Res. Public Health 2020, 17, x 10 of 16 FigureFigure 8. 8.The The simulationsimulation resultresult ofof airair pollutionpollutioncontrol. control. 20 20
10 10
Solid pollutionwaste (10000m^2) 0 Solid pollutionwaste (10000m^2) 0 0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 Time10 (Month)12 14 16 18 20 22 24 Solid waste pollution : case 1 Time (Month) SolidSolid waste waste pollution pollution : :case case 2 1 SolidSolid waste waste pollution pollution : :case case 3 2 SolidSolid waste waste pollution pollution : :case case 4 3 SolidSolid waste waste pollution pollution : :case case 5 4 SolidSolid waste waste pollution pollution : :case case 6 5 Solid waste pollution : case 6 Figure 9. The simulation result of solid waste pollution. FigureFigure 9. 9.The The simulation simulation result result of of solid solid waste waste pollution. pollution.
20 20 15 15 10 10 5
Water pollution Water (10000m^2) 5 Water pollution Water (10000m^2) 0 0 0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 Time10 (Month)12 14 16 18 20 22 24 Water pollution : case 1 Time (Month)Water pollution : case 4 WaterWater pollution pollution : :case case 2 1 WaterWater pollution pollution : :case case 5 4 Water pollution : case 3 Water pollution : case 6 Water pollution : case 2 Water pollution : case 5 Water pollution : case 3 Water pollution : case 6
FigureFigure 10.10. TheThe simulationsimulation resultresult ofof waterwater pollution.pollution. Figure 10. The simulation result of water pollution.
400 400
300 300
Vegetation destruction area (10000m^2) area destruction Vegetation 200
Vegetation destruction area (10000m^2) area destruction Vegetation 200 0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 Time10 (Month)12 14 16 18 20 22 24 Vegetation destruction area : case 1 Time (Month) VegetationVegetation destruction destruction area area : :case case 2 1 VegetationVegetation destruction destruction area area : :case case 3 2 VegetationVegetation destruction destruction area area : :case case 4 3 VegetationVegetation destruction destruction area area : :case case 5 4 VegetationVegetation destruction destruction area area : :case case 6 5 Vegetation destruction area : case 6
Figure 11. The simulation result of total vegetation destruction area. Figure 11. The simulation result of total vegetation destruction area.
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Solid pollutionwaste (10000m^2) 0 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Solid waste pollution : case 1 Solid waste pollution : case 2 Solid waste pollution : case 3 Solid waste pollution : case 4 Solid waste pollution : case 5 Solid waste pollution : case 6 Figure 9. The simulation result of solid waste pollution.
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5 Water pollution Water (10000m^2)
0 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Water pollution : case 1 Water pollution : case 4 Water pollution : case 2 Water pollution : case 5 Water pollution : case 3 Water pollution : case 6
Int. J. Environ. Res. Public Health 2020, 17, 2115 12 of 17 Figure 10. The simulation result of water pollution.
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Vegetation destruction area (10000m^2) area destruction Vegetation 200 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Vegetation destruction area : case 1 Vegetation destruction area : case 2 Vegetation destruction area : case 3 Vegetation destruction area : case 4 Vegetation destruction area : case 5 Vegetation destruction area : case 6 Int. J. Environ. Res. Public Health 2020, 17, x 11 of 16 FigureFigure 11. 11.The The simulation simulation result result of of total total vegetation vegetation destruction destruction area. area.
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425 Land damage area (10000m^2) area damage Land
400 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Land area : case 1 Land area : case 4 Land area : case 2 Land area : case 5 Land area : case 3 Land area : case 6
FigureFigure 12. 12.The The simulation simulation result result of of land land damage damage area. area.
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Environmental Environmental quality assessment 65 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Environmental quality assessment : case 1 Environmental quality assessment : case 2 Environmental quality assessment : case 3 Environmental quality assessment : case 4 Environmental quality assessment : case 5 Environmental quality assessment : case 6
Figure 13. The simulation result of environmental quality assessment.
4. Results
4.1. Sensitivity Analysis In Figure 8, when the value of ‘proportion of investment in air pollution control’ is 0.4, curve 1 shows the lowest value compared with other curves, which indicates that high investment in air pollution control will get a high effect in air pollution control. Similar to the analysis of Figure 8, we can obtain the same result on other pollution control. However, compared with the above figures, these results reveal that the effect of the high proportion of investment in green vegetation is obvious.
4.2. Results Analysis From the above analyses, we can see that the five subsystems are combined with the variable “Environmental investment”. Therefore, the proportion of environmental investment in each subsystem under different cases will determine the overall environmental quality.
Int. J. Environ. Res. Public Health 2020, 17, x 11 of 16
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425 Land damage area (10000m^2) area damage Land
400 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Land area : case 1 Land area : case 4 Land area : case 2 Land area : case 5 Land area : case 3 Land area : case 6
Int. J. Environ. Res. Public Health 2020Figure, 17, 211512. The simulation result of land damage area. 13 of 17
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Environmental Environmental quality assessment 65 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Month) Environmental quality assessment : case 1 Environmental quality assessment : case 2 Environmental quality assessment : case 3 Environmental quality assessment : case 4 Environmental quality assessment : case 5 Environmental quality assessment : case 6
FigureFigure 13. 13.The The simulationsimulation resultresult of of environmental environmental quality quality assessment. assessment. 4. Results 4. Results 4.1. Sensitivity Analysis 4.1. Sensitivity Analysis In Figure8, when the value of ‘proportion of investment in air pollution control’ is 0.4, curve 1 showsIn Figure the lowest 8, when value the compared value of ‘proportion with other curves,of investment which in indicates air pollution that high control’ investment is 0.4, curve in air 1 pollutionshows the control lowest will value get compared a high eff ectwith in other air pollution curves, control.which indicates Similar tothat the high analysis investment of Figure in 8air, wepollution can obtain control the samewill get result a high on othereffect pollutionin air pollution control. control. However, Similar compared to the analysis with the of above Figure figures, 8, we thesecan obtain results the reveal same that result the eonffect other of the pollution high proportion control. However, of investment compared in green with vegetation the above is obvious. figures, these results reveal that the effect of the high proportion of investment in green vegetation is obvious. 4.2. Results Analysis 4.2. Results Analysis From the above analyses, we can see that the five subsystems are combined with the variable “EnvironmentalFrom the above investment”. analyses, Therefore, we can thesee proportionthat the five of environmentalsubsystems are investment combined in with each the subsystem variable under“Environmental different cases investment”. will determine Therefore, the overall the environmental proportion of quality. environmental investment in each subsystemIn case under 1, we different assume that cases the will proportion determine of the investment overall environmental in air pollution quality. control is higher than the other cases, the result is shown in Figure8. From Figure8, we can see that on the same time line, the lower the value of air pollution, the better effect in dealing with the problem of air pollution.
Thus, we can see that case 1 is the best allocation in dealing with the problem of air pollution. That is to say, if we put a higher proportion of investment in air pollution, we can get a better effect in dealing with the problem of air pollution. In case 2, we know that the proportion of investment in solid waste treatment is higher than the other cases, the result is shown in Figure9. From Figure9, we can obtain that on the same timeline, the lower the value of solid waste pollution, the better effect in handling the problem of solid waste pollution. Therefore, we can see that case 2 is the best allocation in dealing with the problem of solid waste pollution. In other words, if we put a higher proportion of investment in solid waste pollution, we can get a better effect in dealing with the problem of solid waste pollution. Similar to this method of the above analyses, we can also get the following conclusions. In case 3, the result is shown in Figure 10. The results show that, if we put a higher proportion of investment in water pollution, we can get a better effect in dealing with the problem of water pollution control. In case 4, the result is shown in Figure 11. The lower the value of vegetation destruction area comes with the better effect in handling the problem of vegetation destruction. In case 5, the result is shown in Figure 12. From Figure 12, we can see that on the same timeline, the lower the value of land damage area, the better effect in dealing with the problem of land damage. Thus, if we put a higher proportion of investment in land reclamation, we can get a better effect in solving the problem of land damage. Int. J. Environ. Res. Public Health 2020, 17, 2115 14 of 17
In case 6, we know that the proportion of investment in every subsystem is equal. However, it can’t get the best environmental quality in coal mining areas. As can be seen from Figure 13, on the same timeline, the higher the value of environmental quality assessment, the higher the environmental quality in coal mining areas. As such, case 4 can get the highest environmental quality. Case 6 have the second environmental quality. Case 1, 2, 3, 5 will get the lowest environmental quality compared with the other two cases. Combined with the above figures, some conclusions are drawn as follows: If we want to get a better effect in dealing with some single pollution, we often need to input a huge increase in the proportion of investment in some subsystems. From all the six cases, case 4 is the optimal solution in the whole environmental quality. That is, the best improvement of mining environment can be achieved by distributing the treatment cost highly on the proportion of investment in green vegetation. Therefore, to get a better environmental quality in coal mining areas, we should focus on strengthening the restoration of vegetation damage. As such, combining the common sense, we can say that green vegetation is a sample and straight way to improve the environmental quality.
5. Discussion In this paper, we presented a SD model for ecological environmental management in coal mining areas. we discussed the problem on “Given the stable investment for ecological environmental management in coal mining areas, how to find a better allocation that can get the best ecological environment quality in coal mining areas”. The result shows that, to get a better environmental quality in coal mining areas, we should focus on strengthening the restoration of vegetation damage. Compared with other related studies, the findings of this paper have some important contributions among the perspective of the research, methods and results. These specific contributions of this research are shown as follows: Firstly, in terms of the perspective of the research, the development of the environmental quality in coal mining areas has received much attention of a lot of scholars and governments [1–7]. The objective of these studies mainly introduced the development of the environmental quality or the existed environmental problems in coal mining areas. They also introduced some policies on how to treat these environmental problems. However, they didn’t give some measures on how to solve these problems can get the more effective results. For example, Zhengfu et al. [2] introduced several environmental problems of subsystems in the coal mining areas, they just listed these problems without any critical advices on how to solve these problems can get the best effect in the coal mining areas. Obviously, these studies can be more meaningful if the scholars can solve some problems in detail, instead of talking about protecting the environment in general. Therefore, in this study, our objective is to solve a specific problem on how to find a better allocation that can get the best ecological environment quality in coal mining areas when the stable investment for ecological environmental management in coal mining areas is given. This is a more meaningful and more special problem to be solved. Secondly, in terms of methods, SD is a method of modeling to ignore the details of a system and produce a general representation of a complex system. It has been widely used in strategic and policy-making modeling and simulation, such as such as environment, supply chains, water management, transportation and so on [20–29]. As Zhengfu et al. [2] proposed, the coal mining areas is a general system combined with many subsystems. Therefore, according to our research problem, it is very appropriate to build a general model with the method of SD. This study is our first try to conduct a SD model to deal with this problem. Combined with the results of other related studies, the findings in this paper have more theoretical significance and practical value in reality. Thirdly, in terms of results, other scholars mainly based on the qualitative and theoretical analysis, lacking effective methods and data support. This study is based on the SD model, then, we present a real case in China to make the result more convincing. There are also some weaknesses in this paper. Some limitations are listed as follows: Int. J. Environ. Res. Public Health 2020, 17, 2115 15 of 17
The simulation results are based on predefined scenarios in this paper. We don’t consider all the possible scenarios. For the convenience of comparisons, we simply choose six cases. We will refine all cases and examine their effects on this problem in the future work. The system dynamics model is built based on assumptions and simplifications of the real systems. It can be applied to ecological environmental management in coal mining areas for many different countries. However, the conclusions are drawn from the simulations only in six cases. Therefore, they have not been validated to the best case. We plan to validate our models with more cases and find the best case to deal with ecological environmental management in coal mining areas. This will make the model more promising. Moreover, in the future work, we can simplify consider the following cases: We can control two or more variables unchanged, and study the change of the overall environmental quality when the variables left increase or decrease, this is a more complicated situation.
6. Conclusions This paper presents a SD model for ecological environmental management in coal mining areas. First, we regard the coal mining areas as a whole system. Then, we divide it into five subsystems, namely: Atmospheric subsystem, solid waste subsystem, water resource subsystem, vegetation cover subsystem and land reclamation subsystem. Given the stable investment for ecological environmental management in coal mining areas, our objective is to find a better allocation that can get the best ecological environment in coal mining areas. Then, we present six allocations of the investment for ecological environmental management in coal mining areas. The results show that, in allocation 1, we can get the best ecological environment in coal mining areas. That is, the best improvement of mining environment can be achieved by distributing the treatment cost highly on the proportion of investment in green vegetation. From the above results, some recommendations are presented to the policy of the government. Each subsystem is very important to the environmental quality of the coal mining area. However, to get a better environmental quality in coal mining areas, they should focus on strengthening the restoration of vegetation damage. The government should take measures to handle this problem, besides, they cannot ignore the importance of other subsystems to the environment. Moreover, enterprises should shoulder the important responsibility of protecting the environment in coal mining during the process of production. This paper studies a SD model for ecological environmental management in coal mining areas under five cases. However, the real situation in the real world is more complicated. So the further research we can present more cases to examine the results. Moreover, in the future work, we should also focus on simultaneous changes in all the variables to determine the global sensitivity of the model.
Author Contributions: Data curation, H.C. and C.W.; Formal analysis, F.S.; Funding acquisition, C.Y. and C.W.; Methodology, F.S. and C.W.; Supervision, H.C. and C.W.; Writing—original draft, F.S.; Writing—review & editing, F.S., H.C., C.W., C.Y. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by Natural Science Foundation of Beijing, China (Grant No.9192005), Natural Science Foundation of Beijing, China (Grant No.9182002) and Philosophy and Social Science Planning Project of Beijing, China (Grant No. 17GLA084). Acknowledgments: Authors would like to thank the Editor and the anonymous reviewers for their valuable comments and detailed suggestions that have improved the presentation of this paper. Conflicts of Interest: The authors declare no conflict of interest.
Appendix A All Equations Lest in the General System
L : (Vegetation destruction area).K = (Total area o f vegetation destruction area).J+ (A1) DT ((Total area o f vegetation destruction area).JK (Green vegetation area).JK). × − Int. J. Environ. Res. Public Health 2020, 17, 2115 16 of 17
R : (Total area o f vegetation destruction).JK = (Open pit mining).J + (Road). J+ − (A2) (Construction o f mining industry square).J + (Waste rock pile up).J.
R : (Green vegetation area).JK = (Total area o f vegetation destruction).K (Technical × (A3) f actors o f air pollution control)
Technical f actors o f green vegetation = Investment in green vegetation/Environmental (A4) investment
Investment in green vegetation = Proportion o f investment in green vegetation × (A5) Environmental investment
L : (Land area).K = (Land damage area).J + DT ((Land damage area).JK × − (A6) (Land reclamation area).JK).
R : (Land damage area).JK = (Land subsidence).J + (Land to dig). J. (A7)
R : (Land reclamation area). JK = (Land damage area).K (Technical × (A8) f actors o f land reclamation)
Technical f actors o f land reclamation = Investment in land reclamation/Environmental (A9) investment
Investment in land reclamation = Proportion o f investment in land reclamation × (A10) Environmental investment
Environmental quality assessment = (Solid waste pollution index + Land reclamation rate (A11) +Air pollution index + Degree o f vegetation destruction + Water pollution index)/5
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