Mining has contributed a significant role in improving societies to the modern civilization by providing the necessary raw minerals. The mining industry influences economic growth at the national and regional levels. This industry has also played a substantial role in improving the quality of human life by creating jobs, increasing life expectancy, skills and knowledge, contributing to the proper distribution of income, and improving infrastructure, public health services, and education. However, mining’s various negative environmental and social consequences, such as land disturbance, water, soil, air pollution, and socio-cultural aspects, made mining a challenge to sustainable development. These impacts attracted the attention of the environmental defenders and legislators to investigate the impact of mining activity on the three indices of sustainable development; environment, Social, and economy. In most previous studies, only the negative impacts were considered in determining the level of sustainability or unsustainability, which may mislead the managers and policymakers to wrong and unreal decisions and strategies. In this study, for the first time, both positive and negative factors of the mining operation are incorporated simultaneously in the framework of a hybrid semi-quantitative model combined with a multi-criteria decision-making approach to evaluate the sustainability of the mining activities. The proposed holistic model identified 43 influential factors, including 22 positive and 21 negative factors, and their impacts on the proposed 13 sub-criteria of sustainable development were evaluated. The model is able to calculate the sustainability score for both negative and positive factors individually and in combination. The proposed model was verified in Sungun Copper Mine as large-scale open-pit mining. Analyses showed that “Social Relationship, Economic Growth and Productivity” and “Flora and Fauna, Landscape and Social Infrastructure Developments” are the two sets of three top sustainable development sub-criteria which contributed the most positive and negative impacts on the sustainability of mining activity, respectively. Results indicated that the mining operations in total are slightly sustainable, with a total score of 4.20, and have slightly enhanced the economic and social conditions while having posed unsustainability in the environmental index. Finally, as the proposed holistic model considers both negative and positive impacting factors, it will provide a realistic value for the individual and total sustainability score of mining activities. This model can also be used by other industries adopting their corresponding conditions, impacting factors, regulations, and laws in the sustainability evaluation process.
Introduction
Historically, mining and mineral resources are among the primary activities of societies. Especially metal mines, have played an essential role in developing civilization, economy, human welfare, and providing the necessary needs of human beings. The world’s population is currently 7.8 billion, and it is predicted that with a growth rate of 2%, this population will reach 9.7 billion by 2050. Mineral consumption and mining will increase even at a rate higher than the world’s population growth rate to provide goods and services to the world’s growing population. On the other hand, with the increase in mineral prices and depletion of the near-surface resources, ore extraction will be done in greater depths and with a lower grade. Hence, mining will produce more waste and tailings in the mineral processing plants (Osanloo, 2012). In comparison, surface mining methods vs. underground mining methods have advantages such as high production rate, the possibility of the extraction of low-grade minerals, and low mineral losses, which are more consistent in achieving the production increment. More than 95% of non-metallic minerals, more than 90% of metallic minerals, more than 60% of coal in the world, and 97% of mines in Iran are extracted by surface mining methods (Moradi and Osanloo, 2015; Ramani, 2012). However, studies in Iran have shown that for about 393 million tons of open-pit mining of metallic and non-metallic ores, more than 900 ha of land have been affected in the form of a pit waste dump and tailing dams (Moradi and Osanloo, 2015). Large-scale land degradation is one of the most damaging impacts of mining on the environment, caused mainly by surface mining.
Developed countries, at the beginning of their development, achieved effective growth by relying on the exploitation of natural and mineral resources. However, an increase in mining activities and neglecting environmental considerations led to the destruction of natural ecosystems and the adverse impacts on the environment of these countries. Simultaneously, a series of social problems in developed countries during economic development, such as poverty, injustice, destruction of natural resources, and the creation of a class gap, resulted in the development of the sustainable development (SD) concept in 1992. SD was defined as; “SD is a development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” at the UN earth summit in Brazil (Asr et al., 2019; Hustrulid et al., 2013).
There are many studies by scholars investigating the impacts of the mining operation on SD indices, namely, the environment, societies, and economy (Alves et al., 2018; Amirshenava and Osanloo, 2019; Azapagic, 2004; Phillips, 2013; Syahrir et al., 2020). Laurence (2011) investigation of the main reasons for the temporary closure of 1000 mines over the 30 years revealed that a mine operation would be sustainable if the safety, environmental protection, and engagement of the local and national communities were covered in the mine plans. Leopold (1971) performed one of the first studies on mining Environmental Impact Assessment (EIA) by developing a two-dimensional (2D) assessment matrix known as the “Leopold matrix”. The dependency of the scores on people’s opinions and the difficulty of interpreting the results are the disadvantages of the Leopold matrix. Pastakia and Jensen (1998) developed the Rapid Impact Assessment Method (RIAM) to compare and select the different alternatives in a mining project based on their environmental impacts. Despite its high ability to assess environmental issues, the economic and social indicators weren’t considered in RIAM. Folchi (2003) introduced the most widely used 2D matrix-based environmental assessment method for quantifying environmental impacts concerning mining activities. Considering small ranges for the influencing factors and the lack of appropriate scenarios for scoring are the disadvantages of this method. Azapagic (2004) developed a framework for the sustainable development of suitable for large-scale mining. Azapagic adapted and raised the indicators compatible with the 2000 version of the global reporting initiative guidelines. Azapagic stressed the need to identify relevant stakeholders and understand their interests in developing a meaningful set of sustainability indicators. A total of 24 economic, 63 environmental, and 45 social indicators were proposed for the mining industry stakeholders. Some integrated indicators that address two dimensions of sustainability were also furnished as examples. Azapagic generic framework is contributing to further standardization of sustainability reporting, but he did not develop a SD evaluation method corresponding to the developed indicators. Mirmohammadi et al. (2009) modified the Folchi method and used it to study the impacts of extraction and processing units on the environmental index of SD by focusing on the negative impacts. Phillips (2013) evaluated sustainability in two open-pit iron ore mines in Iran through a combination of the Folchi methodology for impact assessment and a mathematical model for sustainable development evaluation. The results revealed that the mentioned mines were deemed unsustainable and the obligation of the sustainability approach to certify the progress of a co-evolutionary relationship between the environment and humans. His model considers the mining’s negative impacts on the environment and also positive socio-economic benefits. Mobtaker and Osanloo (2014) studied the positive impacts of mining on SD, emphasizing the environmental index employing the Folchi method. Their results showed that mining operations could positively affect the environment. Moradi and Osanloo (2015) presented a multi-criteria decision-making (MCDM) method for quantifying SD criteria and influencing SD indicators in mine design. Rahmanpour and Osanloo (2017) proposed a decision support system consisting of a 2D impact assessment matrix in combination with fuzzy logic for selecting the most sustainable Ultimate Pit Limit (UPL) in an open-pit copper mine. Farahani and Bayazidi (2018) investigate the impacts of sand mining on local communities’ socio-economic and environmental issues through a field study in the form of a questionnaire and confirmatory and exploratory factor analysis. The study revealed the negative impacts of sand mining on the environment, but the socio-economic impacts of sand mining were positive. In total, the positive and negative impact of sand mining on the studied site was found 65.25% and %34.75 respectively. Alves et al. (2018) examined the situation of SD in Brazilian mining companies using semi-quantitative methods. They concluded that the lack of attention to the negative impact of mining on the environment and society is the biggest challenge of sustainable mining in this country. Amirshenava and Osanloo (2019) studied the mining activities negative impact on SD indices in Gol-Gohar and Sangan Iron mines by developing a semi-quantitative 2D matrix in combination with MCDMs. The results revealed the moderate negative impacts of both mines on SD. They did not consider the positive impacts of mining operations in their analysis. Syahrir et al. (2020) examined and evaluated the socio-economic impacts of a tin mine in Indonesia after the closure of the mine and concluded that attention to economic indicators at the regional level is as important as at the national level. Worlanyo and Jiangfeng (2020) provided valuable guidance and suggestions for mining and post-mined rehabilitation form SD perspectives. Considering the pressure posed on mining companies by the government and the local communities, Antwi et al. (2022) examined which environmentally accepted supply chain management practices can ensure that mining firms’ performance is economically, socially, and environmentally acceptable from SD’s point of view. They used an explanatory study and PLS-SEM data analysis method to model the relationship between green supply chain practices and sustainable performance. They found that when mining companies engage in eco-innovative practices such as using environmentally friendly inputs, carrying out internal recycling of inputs, and are efficient with the amounts of input used, it is liable to record considerable increases in social, economic, and environmental performance. In this study no exact model is given to assess the current mining sustainability level. In order to realize the goals of SD in the Chinese mining industry, green mining has been advocated and supported by the government and society. Hence Chen et al. (2022) developed a mixed grey decision-making model based on grey analysis that employs subjective and objective data to carefully evaluate the level of green mine construction based on an evaluation index system. The evaluation index system included 24 indices, divided into four groups, and constructed according to the conditions of a green coal mine. The summary of previous studies’ advantages and disadvantages are shown in Table 1.
Despite having negative impacts on the environment, mining operations have significant positive impacts on the economic and social dimensions of SD that cannot be ignored. Both positive and negative impacts are even more pronounced in large mining activities. Determining the sustainability of mines based on one of the negative or positive impacting factors of mining activities does not reveal the actual value of sustainability, and both positive and negative impacts should be evaluated simultaneously. As the investigation of the previous studies shows (Table 1), most of the studies have focused on the negative impacts of mining operations and ignored the positive impacts of mining in sustainability studies. In this study, for the first time, a holistic hybrid semi-quantitative 2D assessment matrix and MCDM techniques are developed to evaluate the impacts of both positive and negative impacts of mining activities individually as well as simultaneously on the three principles of SD. Avoiding pessimistic or optimistic judgment, the results of this model will help to have a realistic perspective on mining operation SD conditions and help the managers and policymakers to make or review mine plans to recognize the priorities, vulnerable and resilient parts of SD indices and emphasize them for corrective and supportive measures. The developed model is verified in a large open-pit copper mine in Iran.
Conclusion
This study proposed a holistic hybrid semi-quantitative approach consisting of MCDM techniques and the 2D SD assessment matrix to assess the impacts of mining activities on SD indices. The superiority of the proposed hybrid method over the previous studies is its comprehensive attitude towards calculating a more accurate level of sustainability mining projects by considering concurrent incorporation of both negative and positive impacts of the mining operations on SD. In most previous studies,