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• Published: 13 December 2023

Environmentally sustainable mining in quarries to reduce waste production and loss of resources using the developed optimization algorithm

• Mohammad Hossein Jalalian 1 ,
• Raheb Bagherpour 1 &
• Mehrbod Khoshouei 1  

Scientific Reports volume  13 , Article number:  22183 ( 2023 ) Cite this article

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• Engineering
• Environmental impact
• Environmental sciences
• Environmental social sciences
• Sustainability

The study of natural resources in the earth sciences focuses on the sustainable management of valuable materials like dimension stones. the quarrying of dimension stones is associated with environmental challenges such as significant amounts of waste production, and resource loss, mainly caused by discontinuities and fractures in the rock mass. Quarry optimization requires an optimal cutting pattern to increase the production of larger blocks while minimizing parameters that affect operational costs such as energy consumption. The algorithms used in the quarrying only focus on the number of blocks extracted, ignoring other factors such as energy consumption in the cutting of blocks. To address this issue, a new algorithm was developed in this study. The algorithm aims to optimize the quarrying process by analyzing the impact of discontinuities on waste production and cutting surfaces. It then provides an optimal cutting pattern for the quarry face based on the optimal value of these parameters. As a result, the use of this algorithm can serve as an efficient and valuable tool in dimension stone quarries. By implementing this algorithm, production costs, energy, and water consumption, cutting tools consumption, and waste production can be significantly reduced, leading to increased quarry profitability and decreased environmental problems.

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Introduction.

Dimension stones are natural stones that have standard dimensions and shapes, and are used in various construction fields such as building facades, interior parts of buildings, structures, sculptures, paving, and more 1 . Dimension stones have a distinct advantage over other building materials due to their appearance and decorative applications, which are determined by their color combination, uniform texture, and lack of discontinuity. They can also be classified based on these factors 2 . In recent years, due to the increase in construction, which is influenced by the expansion of urbanization, the dimension stones industry has become an industry with significant and increasing annual production and an industry with high economic potential. Besides, the level of profitability in this industry depends on the efficiency of the production cycle. The dimension stones production cycle consists of three main stages: exploration, quarry, and processing. After exploring the dimension stones deposit, the quarry is prepared, and large blocks are cut and extracted. Cutting the block from the quarry face requires non-destructive methods that minimize the damage to the block and increase efficiency. The most common methods for dimension stone quarrying are diamond wire cutting, chainsaw, cutting disc, flame jet, blasting methods, etc. 3 . The most common method of cutting blocks in dimension stone quarries is the diamond wire cutting method, which has been used since 1985 and is still used in 90% of dimension stone quarries today 4 , 5 . The advantages of this method include high cutting speed, more production efficiency, and increased block production 6 . The next step, cutting large blocks into smaller blocks to facilitate transportation is performed, and these blocks are transferred to the processing plant. Figure  1 shows a view of the dimension stones quarry stage.

A view of dimension stones quarry stage 7 .

The blocks that are transported to the processing plant are sorted based on their dimensions and specifications. They are then cut into final products based on their intended use, which are typically slabs or tiles. Depending on the intended market, the surfaces of these products are smoothed and polished to transform them into the desired finished product 8 . Factors affecting the efficiency of the dimension stones production cycle include the enormous amounts of waste production, resource loss, and the amount of energy and consumables. According to the data published in 2021 by Montani, from the total 318 million tons of gross quarrying from dimension stone quarries, during the quarry stage, about 163 million tons, or in other words, about 51% of total gross quarrying has become quarrying waste. The most important factors affecting the waste generated in the quarry stage are the geological conditions of the deposit, including discontinuities and fractures in the rock mass, which mainly lead to waste products such as unshaped blocks and rubbles 9 . As shown in Fig.  2 , in the continuation of the production cycle, about 49% of the remaining raw production is transferred to the dimension stones processing plant and its amount is about 155 million tons, nearly 63.5 million tons or 41% (about 20% of the total gross quarrying) is converted to the waste during the processing stage, which mainly includes waste such as crushed slabs, sludge and sawdust 10 , 11 . According to the above contents, it can be concluded that of the total gross quarrying in the dimension stone production cycle, only 91.5 million tons, or 29% was marketed as processed products, and about 71% of it was lost as waste production.

Products and wastes in different stages of the dimension stones production cycle.

While quarries are potential economic locations, further attention is needed to guarantee a cost-effective and environmentally efficient system for waste management in these places 12 . To improve the production efficiency of dimension stones, it is important to minimize the amount of waste and resource loss with optimization methods and technologies. In case it is not possible to reduce waste and loss, recycling or reuse methods should be implemented in the future 7 . Numerous studies have been conducted in recent years to enhance the production efficiency of dimension stones. These studies can be broadly categorized into two stages—quarrying and processing. The quarry stage focuses on identifying and modeling discontinuities, determining the specifications and geometry of in-situ blocks in the rock mass, and using block quarry optimization algorithms. Meanwhile, methods to improve efficiency in the processing stage involve the use of optimal devices and technologies, as well as recycling waste production. Table 1 summarizes some of the methods used in these studies.

According to Fig.  2 , the quarry stage of the dimension stones production cycle is responsible for most of the waste production and resource loss. The primary reason for waste production in this stage is the presence of discontinuities and fractures in the rock mass, which reduce the size of extracted blocks and increase waste generation. In recent years, researchers have shown interest in optimizing dimension stone quarries to increase efficiency and reduce waste production. Table 1 lists some of the methods used by these researchers, which have proven to be effective in increasing production efficiency and reducing waste. However, it is notable that these studies have not paid much attention to other parameters, such as energy consumption, that could also improve the efficiency of dimension stone quarries.

Many factors impact the economic and environmental optimization of dimension stone quarrying, including operational costs, waste production, water usage, energy consumption, and cutting tool consumption. However, the optimization methods used in dimension stone quarries have only paid attention to the amount of production of economic blocks and the amount of waste, and other important parameters have not been paid attention to. For example, in cutting blocks from the quarry face, in addition to the dimensions of the blocks, the number of surfaces that must be cut to extract the desired blocks from the quarry face is also very important. Cutting surfaces affect the amount of energy, water, and cutting tool consumption. Besides, increasing the amount of waste production and resource loss causes the energy and consumables that should be used to produce the product, used to waste production, and increases the amount of energy and consumables per product production. Increasing the amount of waste production and subsequently reducing the production of the product, along with increasing the energy consumption and consumables, increases the production cost and significantly reduces production efficiency. All these parameters affect the economic and environmental optimization of dimension stone quarries and should be seen simultaneously. In other words, paying attention simultaneously to all effective parameters in increasing quarry efficiency can show more effective results. Optimization of the dimension stones quarry stage requires that while examining the optimal cutting pattern to increase the production of blocks with maximum dimensions, consider minimizing the parameters such as cutting surfaces, energy consumption, and consumables. Accordingly, the optimization results can be more comprehensive and increase production efficiency as much as possible.

In this paper, an optimization algorithm is developed to simultaneously optimize the economic and environmental factors of dimension stone quarries. After receiving the information on discontinuities and fractures of the rock mass, as well as considering the mining limitations, this algorithm provides the optimal cutting pattern of the quarry. The main difference between the presented optimization algorithm and previous algorithms is that it considers parameters such as the cutting surfaces of the blocks, in addition to the amount of production of economic blocks and the amount of waste. Attention to this parameter has an effective impact on energy consumption, water, and consumables. The details of the developed optimization algorithm, along with its results, are presented in the next sections.

Methodology

Several quarry optimization algorithms have been developed based on block geometry modeling. However, these algorithms mainly focus on the amount of production of economic blocks and neglect other parameters such as the energy used to cut the blocks from the quarry face, which can affect production costs. Therefore, it is necessary to develop an algorithm that can simultaneously consider the main parameters affecting the economic and environmental optimization of dimension stones quarrying. Among the previous algorithms, the algorithm developed by Yarahmadi et al. 28 in 2018, was selected as the base algorithm due to its ability to model complete and incomplete discontinuities, determine the geometry of blocks, 3D modeling, and grading of blocks. The method of this algorithm is that first, the discontinuities are considered as planes and are given intersections. Edges and vertices are then identified and sorted. The block's faces are then tracked, and using these faces, the blocks are tracked, and finally, the identified blocks are graded based on their volume and shape. The larger the volume of the tracked block and the more similar its shape to a rectangular cube block with index dimensions, the higher the class of the block. The steps of this algorithm are shown in Fig.  3 .

Steps for identifying and grading blocks in the base algorithm.

Based on the given explanations, it is necessary to make changes in the direction of achieving the set goals when using the base algorithm and to update it. This implies focusing on all the parameters that affect the economic and environmental optimization of dimension stones quarrying. In the following section, the development of a new algorithm that aligns with the set goals will be explained.

Developed algorithm

Different algorithms require implementation and conversion into computer programs. Programming languages such as MATLAB, C++, and Pascal are used to prepare computer programs. Each software has its advantages and disadvantages and is used based on the user's needs. in this study, MATLAB programming language was used as it is based on matrices and has excellent graphical capabilities. A newly developed algorithm was programmed using MATLAB. The general structure of the new algorithm is shown in Fig.  4 .

General process of the developed algorithm.

Figure  4 shows how the new algorithm receives input data, which includes the discontinuity profile, model dimensions, and spacing of vertical cuts on the quarry face. The algorithm's first input is the characteristics of discontinuities, which include four main items- the type of discontinuity (complete or incomplete), the slope, the direction of slope, as well as a point of the plane of discontinuity (X, Y, and Z); that is given as input to the algorithm. The second input of the algorithm is the dimensions of the model. For example, in this study, the target model is a dimension stone quarry face, and the dimensions of the face, such as length, cutting depth, and height, are given as input to the algorithm. The third input of the algorithm is the distance of the vertical cuts in the quarry face. Vertical cuts are made to separate large blocks from the face, which are usually fixed (1.8 to 2 m) in dimension stone quarries.

After receiving these inputs, the developed algorithm first considers the dimensions of the model (length, depth, and height) and creates a 3D space of a rectangular cube under the title "model space". The algorithm then models the discontinuities according to their specifications in the form of planes in the "model space". According to their spacing, vertical cuts are considered vertical planes and are modeled in "model space". Finally, all the modeled planes in the 3D space are intersected and lead to the formation of in-situ blocks. The algorithm also identifies the number of cuts required to separate large blocks (rectangular cubic blocks extracted from the quarry face of dimension stone quarries) from the quarry face. It should be noted that the amount of cutting has a direct relationship with energy, water, and cutting tool consumption. After running the algorithm, it finally provides the specifications of the tracked blocks and 3D graphic modeling of the quarry face as the primary output. The algorithm also provides Block Cutting Surfaces divided by Block Value (BCSdbBV) parameter as the main output and the main optimization parameter. In BCSdbBV calculation, two main parameters are effective, including the block value and the block cutting surfaces. The calculation of the BCSdbBV parameter is explained below.

Block Cutting Surfaces (BCS)

In dimension stone quarrying, blocks are separated from the quarry face by cutting their faces. To separate a rectangular cube block from the quarry face, four faces need to be cut. These four faces include two side faces, the back face, and the bottom face of the block. In this study, the total area that needs to be cut to separate the block from the quarry face is referred to as the BCS, measured in square meters. The value of BCS can be calculated using Eq. ( 1 ).

where BCS is the area of cutting faces to separate a block from the quarry face, SF is the area of the side face, BF is the area of the back face and UF is the area of the bottom face, whose unit is m 2 .

The BCS parameter represents the operating costs of quarrying, such as energy, water, and tool consumption. The higher the BCS value, the higher the energy and water consumption during the separation of the block from the quarry face, and the consumption of cutting tools. The increase in the consumption of energy, water, and cutting tools in the extraction of dimension stones leads to an increase in operating costs and, as a result, a decrease in production efficiency. According to the description, the BCS value calculation is the first parameter that is considered in the BCSdbBV calculation. In the following, the method of calculating the second effective parameter in the calculation of BCSdbBV, that is, the block value parameter, is explained.

Block Value (BV)

The value of a block extracted from a quarry is determined by its volume and shape, which are influenced by the discontinuities of the rock mass. This study measures the block's value based on its useful volume, which is calculated by multiplying the block's volume by its shape factor 28 . A block's value increases if its volume is larger and its shape is closer to that of a block with index dimensions (the ideal block for the target market). This increase in value leads to a reduction in waste production in dimension stone quarries, thus increasing production efficiency. Calculating the BV value is the second parameter considered in the BCSdbBV calculation. The following section describes the method of calculating the BCSdbBV parameter using the developed algorithm.

Block Cutting Surfaces divided by Block Value (BCSdbBV)

According to the explanations and points expressed in the previous sections, the economic and environmental optimization of dimension stone quarrying require simultaneous attention to the following two items:

Paying attention to the parameters affecting operational costs (such as energy, water, and cutting tools consumption) can be achieved through investigation of the amount of BCS.

Paying attention to the amount of waste production (increasing the useful volume of extracted blocks) can be achieved through investigation of the amount of BV.

The parameter BCSdbBV is considered as the main goal of the developed algorithm. Equation ( 2 ) shows this parameter:

BCSdbBV indicates the amount of cutting surfaces per unit of valuable block. In other words, reducing the amount of cutting surfaces and increasing the value of the extracted block leads to a decrease in this parameter and consequently an increase in production efficiency. According to the points mentioned, the calculation of BCSdbBV has been selected as the main goal of the developed algorithm in this study.

Implementation and evaluation of the developed algorithm

To show how to implement the developed algorithm, two hypothetical models named "Model 1" and "Model 2" were considered and the algorithm was evaluated on them. The dimensions of the hypothetical models were considered 2 m in the x direction (cutting depth of the quarry face), 20 m in the y direction (quarry face length), and 4.5 m in the z direction (quarry face height). The dimensions of the models are based on the common dimensions of quarry faces in dimension stone quarries. In these hypothetical models, each one contains several discontinuities with different characteristics, which were randomly selected among the discontinuities taken in the study of Yarahmadi et al. 28 . In the following, the characteristics of the discontinuities and the results obtained from the implementation of the algorithm on each model are presented.

To evaluate the developed algorithm, a hypothetical quarry face named "Model 1" was considered. It included 7 discontinuities with different characteristics, which are shown in Table 2 .

The dimensions of the large blocks in this model are considered 2 × 2 × 4.5 m (Common dimensions of large blocks in the quarry face). The direction of the quarry in this model was considered 270 degrees, and the spacing of vertical cuts in the quarry face was assumed to be constant and is considered 2 m according to traditional quarry methods (In traditional quarrying, the spacing between vertical cuts is 1.8 m to 2 m). In the block grading step, blocks with a useful volume of more than 16 m 3 as class 1, between 10 and 16 m 3 as class 2, between 3 to 10 m 3 as class 3, and less than 3 m 3 as waste are considered. Also, the value of class 2 and class 3 blocks are considered respectively 0.25 and 0.1 of the value of class 1 blocks, and the value of the waste block is considered equal to 0. It should be noted that the assumptions such as the dimensions of the quarry face, the dimensions of the large block, grading, and the value of blocks are considered based on the case study in Yarahmadi et al. 28 . According to the specifications of "Model 1", the programmed algorithm was implemented on it, and the results are displayed below. 3D modeling of "Model 1" without considering the vertical cuts of the quarry face is shown in Fig.  5 .

Graphical 3D modeling of “Model 1” without considering vertical cuts.

For the hypothetical quarry face, the spacing of vertical cuts was set to 2 m. The algorithm was provided with vertical cuts as input to complete the modeling process, which resulted in the re-modeling of the quarry face. Figure  6 displays the graphical output of "Model 1" along with the vertical cuts and the grading of the formed blocks.

3D modeling of “Model 1” with a traditional cutting pattern.

The results related to the calculation of the main outputs of the algorithm, including cutting levels, the value of blocks, and BCSdbBV are shown in Table 3 . Also, the specifications of the blocks tracked in the model and their grading are presented in Table 4 .

According to the calculations in Table 3 , the BCSdbBV value suggests that 7.14 m 2 of cutting surfaces must be cut for each valuable block unit. Additionally, based on the number and value of the blocks, the overall efficiency of the model is estimated to be around 18%, assuming the given conditions.

To implement and evaluate the developed algorithm, another hypothetical model with different discontinuities specifications is considered "Model 2". Dimensions of the model range, block grading specifications, and optimization parameters are considered Similar to "Model 1" specifications. The discontinuities specifications of "Model 2" are shown in Table 5 .

Based on the specifications of "Model 2", the programmed algorithm was executed on it, in the following displayed the results. Figure  7 shows the 3D modeling of "Model 2" without taking into account the vertical cuts of the quarry face.

3D modeling of “Model 2” without considering vertical cuts.

The distance between vertical cuts in this model was set at 2 m. The hypothetical quarry was then re-modeled based on the characteristics of discontinuities and vertical cuts. Figure  8 shows the graphical output of "Model 2", which includes the vertical cuts and the grading of the formed blocks.

3D modeling of “Model 2” with traditional cutting pattern.

Table 6 displays the main outputs of the algorithm, and Table 7 presents the specifications and grading of tracked blocks in the model.

BCSdbBV value in Table 7 indicates that 7.98 m 2 of cutting surfaces should be cut for each unit of valuable block. Also, according to the number of blocks and their value, the overall efficiency of the model according to its assumptions is about 16%.

Cutting pattern optimization

Providing an optimal cutting pattern in the quarry face of dimension stones quarries is essential to increase production efficiency. The spacing of vertical cuts in dimension stone quarries is usually considered a fixed value regardless of the geological conditions of the quarry face. Using a fixed cutting pattern in the quarry face, regardless of the change in the geological conditions of different quarries, can increase operating costs (cost of water, energy, and cutting tools) and decrease the value of produced blocks (increase in production wastes) and finally Reduce operational efficiency. On the other hand, practical testing of all different cutting patterns in quarries is impossible. All these points make it necessary to provide an algorithm for optimizing the cutting pattern in dimension stone quarry faces. In the previous section, the implementation of the BCSdbBV calculation algorithm based on the discontinuity specifications and the spacing of the vertical cuts was fully expressed. To optimize the block cutting pattern in the quarry face, a new optimization algorithm was programmed in MATLAB based on a genetic algorithm, the main purpose of which is to provide the optimal cutting pattern based on the minimization value of BCSdbBV. The general process of the programmed optimization algorithm is shown in Fig.  9 .

General process of the programmed optimization algorithm.

As shown in Fig.  9 , the optimization algorithm receives the dimensions of the model range and the specifications of discontinuities as inputs, and after performing the optimization operation based on the desired optimization parameters, provides the optimal quarry face cutting pattern based on minimum BCSdbBV as the main output and provides some of the best cutting patterns as a secondary output if needed.

Results and discussion

At the start of the optimization algorithm evaluation process, model 1 (displayed in Fig.  6 ) was identified as the target quarry face. Extracting blocks from a quarry face involves cutting and drilling vertical and horizontal holes, which can be quite costly. Considering these costs, a spacing of less than 1.5 m between vertical cuts is not economical. Therefore, the optimization algorithm uses a minimum distance of 1.5 m between vertical cuts. Additionally, if the distance between vertical cuts is more than 3 m, the resulting blocks may be too heavy to transport due to weight limits. Hence, the optimization algorithm uses a maximum distance of 3 m between vertical cuts. This ensures that only blocks within a transportable weight range are produced.

Finally, according to operational limits, the accuracy of the spacing of vertical cuts was considered 0.5 m (the spacing of vertical cuts can be 1.5, 2, 2.5, or 3 m). also, the simulation and optimization process were time-consuming, so the initial population number was set to 100. After multiple tests and evaluations, the crossover and mutation parameters were set to 0.8 and 0.02, respectively 35 . Based on the given assumptions, the results of the optimization algorithm are presented in Table 8 , which shows the optimal cutting pattern in "model 1" based on the minimum BCSdbBV.

The graphical output of “Model 1” after implementing the optimal cutting pattern (Table 8 ) is shown in Fig.  10 .

3D modeling of “Model 1” with optimal cutting pattern.

Also, the numerical outputs of using the optimal cutting pattern for “Model 1” are shown in Tables 9 and 10 .

In Fig.  11 , "Model 1" is compared in the two modes of implementation of the traditional and optimal cutting patterns. Also, to better demonstrate the performance of the new optimization algorithm, a comparison of outputs in the two modes of implementation of the traditional cutting pattern and the optimal cutting pattern is shown in Fig.  12 .

Comparison of “Model” 1 in two modes of traditional and optimal cutting patterns.

Comparison graph of outputs of “Model 1” in two modes of traditional and optimal cutting patterns.

The best cutting patterns proposed by the programmed optimization algorithm, with calculated BCSdbBV for each pattern, are shown in Fig.  13 .

The first five cases of the best cutting patterns proposed by the optimization algorithm for "Model 1".

The optimization algorithm evaluation process continued with consideration of the "Model 2" (displayed in Fig.  7 ) and the implementation of the algorithm on it. In the following, the results of the optimization algorithm are presented. Table 11 displays the optimal cutting pattern for "Model 2" based on the minimum BCSdbBV.

The graphical output of "Model 2" after implementing the optimal cutting pattern (Table 11 ) is shown in Fig.  14 .

3D modeling of “Model 2” with optimal cutting pattern.

Also, the numerical output of the algorithm if using the optimal cutting pattern for "Model 2" is shown in Tables 12 and 13 .

In Fig.  15 , "Model 2" is compared in the two modes of implementation of the traditional and optimal cutting patterns. Also, as in "Model 1", to better demonstrate the performance of the optimization algorithm, a comparison of outputs in the two modes of implementation of the traditional cutting pattern and the optimal cutting pattern is shown in Fig.  16 .

Comparison of “Model 2” in two modes of traditional and optimal cutting patterns.

Comparison graph of outputs of “Model 2” in two modes of traditional and optimal cutting patterns.

The best cutting patterns proposed by the programmed optimization algorithm, with calculated BCSdbBV for each pattern, are shown in Fig.  17 .

The first five cases of the best cutting patterns proposed by the optimization algorithm for "Model 2".

Based on the results presented, it can be inferred that implementing the optimization algorithm can be advantageous for the economic and environmental optimization of dimension stone quarries. The hypothetical model used in this study was based on an actual quarry face. Moreover, the suggested cutting patterns are fully practicable, and all operational considerations have been considered.

In "Model 1", according to Figs.  11 and 12 , the use of optimal cutting patterns has a significant impact on the parameters affecting the optimization of dimension stone quarrying. The "BV" parameter has increased to 107.57 units from 32.08 units (a 235% increase), resulting in a higher number of valuable blocks and a lower volume of waste blocks. Additionally, the "BCS" parameter has reduced from 229 to 211 m 2 (an 8% reduction), leading to reduced operating costs of block extraction, such as water, energy, and cutting tool consumption. This reduction also saves time by decreasing the block cutting time. Finally, the "BCSdbBV" parameter has decreased from 7.14 units to 1.96 units (a 72% reduction), indicating that the cutting surfaces per valuable block unit have reached the initial value of about 27%. In case there are any limitations in implementing the optimal cutting pattern shown in Fig.  10 , the cutting patterns illustrated in Fig.  13 can also be utilized. Based on the BCSdbBV value of cutting patterns presented in Fig.  13 , implementing any of these patterns can lead to more optimal results compared to the traditional cutting pattern.

In "Model 2", as shown in Figs.  15 and 16 , the value of the "BV" parameter increased by about 186%, from 28.69 units to 82.22 units. This increase led to a rise in the number of valuable blocks and a decrease in the volume of waste blocks. Moreover, the "BCS" parameter was reduced by 8%, resulting in a reduction in operating costs and cutting time. Lastly, the "BCSdbBV" parameter also decreased from 7.98 units to 2.56 units (about 68% reduction), indicating that the cutting surfaces per valuable block unit have reached their initial value of about 32%. to achieve better results than the traditional cutting pattern in "Model 1", the cutting patterns proposed in Fig.  17 can also be used.

Although the algorithm presented in this paper has demonstrated favorable results, it can still achieve better outcomes. As mentioned earlier, due to time constraints during the optimization process, the genetic algorithm's initial population size was limited to 100, and the accuracy of the vertical cuts was set to 0.5 m. However, if more powerful computers are utilized during the optimization process and the time constraints are relaxed, it's possible to increase the initial population size and reduce the accuracy of the vertical cut spacing (for instance, 0.25 m). By doing so, we can arrive at more optimal cutting patterns.

Conclusions

The dimension stones industry has enormous economic potential, However, this industry faces several challenges such as improper operation, significant resource loss, and waste production, resulting in low efficiency and high production costs. According to data published in 2021, approximately 51% of the total gross quarrying in quarries will be converted into waste. This increase in waste production and resource loss leads to the misallocation of energy, water, and cutting tools that should be used for production, thus increasing costs, and reducing efficiency. In recent years, many studies have been conducted to optimize dimension stone quarries, which have yielded positive results. However, these studies tend to overlook other critical parameters, such as energy, water, and cutting tools consumption, that are essential for the environmental and economic optimization of dimension stone quarrying. To optimize dimension stone quarrying, producers should focus not only on producing economic blocks with large dimensions but also on parameters that affect operational costs, such as energy consumption.

In this study, an optimization algorithm was developed for dimension stone quarrying to consider all economic and environmental parameters affecting the optimization process. The algorithm takes the characteristics of the quarry (including the dimensions of the quarry face and the characteristics of the discontinuities) as input, and after performing the optimization process, provides the optimal cutting pattern of the quarry face. The goal of this algorithm is to maximize the value of the extracted blocks (decreasing the amount of waste) and minimize cutting surfaces (reducing energy, water, and cutting tools consumption), it achieves this goal by minimizing the BCSdbBV. To evaluate the developed algorithm, two hypothetical models, "Model 1" and "Model 2," were created using real data. After running the optimization algorithm on the two models, the following results were obtained:

In model 1, if the traditional cutting pattern is used, the value of BCSdbBV will be 7.14 square meters for each unit of valuable block. However, if the optimal cutting pattern recommended by the optimization algorithm is implemented, this amount will significantly reduce to 1.96 m 2 which is about 72% less.

In Model 2, when using the traditional cutting pattern, the value of BCSdbBV is 7.98 square meters per unit of valuable block. However, if you implement the optimal cutting pattern provided by the optimization algorithm, this value will decrease to 2.56 m 2 , which is a significant 67% reduction.

The optimal cutting pattern based on discontinuities specification and minimizing BCSdbBV can reduce cutting surfaces and increase valuable blocks, resulting in lower energy, water, and tool consumption, and reduced waste production.

In general, quarry optimization based on the BCSdbBV parameter can effectively optimize most of the operational parameters, reduce resource losses, and significantly increase production efficiency. The presented optimization algorithm considers all operational constraints in dimension stone quarrying. Since diamond wire machines are commonly used for dimension stone quarrying, changing the spacing of vertical cuts is operationally feasible. As a result, an optimal cutting pattern with variable spacing of vertical cuts can be used instead of the traditional pattern with fixed spacing. Implementation of this method in dimension stone quarries requires an understanding of the discontinuities conditions in the quarry face and can be achieved through a simple geological survey. Ultimately, this algorithm can serve as a means for environmentally and economically optimizing dimension stone quarries.

Data availability

All data generated or analyzed during this study are included in this published article (and its Supplementary Information files).

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Jalalian, M.H., Bagherpour, R. & Khoshouei, M. Environmentally sustainable mining in quarries to reduce waste production and loss of resources using the developed optimization algorithm. Sci Rep 13 , 22183 (2023). https://doi.org/10.1038/s41598-023-49633-w

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• Published: 11 November 2023

Environmental impact of quarrying on air quality in Ebonyi state, Nigeria

• Odera Chukwumaijem Okafor   ORCID: orcid.org/0000-0001-8089-7070 1 ,
• Chima Njoku 2 &
• Anselem Nwabuaku Akwuebu 2  

Environmental Sciences Europe volume  35 , Article number:  98 ( 2023 ) Cite this article

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The insatiable demand for rock supplies has enticed numerous building and construction enterprises to participate in stone quarrying. However, this has had an environmental impact on air quality. This paper examines the environmental impact of quarrying on air quality in Ebonyi State, Nigeria. To achieve the main aim of the study, an objective was set to detect air pollutants at the quarry sites. A total of 220 air samples were measured from six points around the quarry locations and recorded in situ for analysis. The samples were measured three times a day (morning, afternoon, and evening) for three days. Gas monitors were used to monitor air pollutants. The generated data were subjected to completely random design (CRD) sampling techniques. The separation of means and tests was performed using Fisher’s Least Significant Difference (FLSD) at a significance probability level of 5%.

Based on statistical analysis, the findings detected significantly higher concentration levels of particulate matter, nitrogen dioxide, hydrogen sulphide, carbon monoxide, sulphur dioxide, chlorine, volatile organic compounds, ammonia, and hydrogen cyanide in the quarry areas than the value detected in the control area. The findings also confirmed higher noise levels in the locations. It was also observed that the concentration levels of the parameters differed from point to point and at different times of the day. This really means the occurrence of a high rate of air pollution in the study locations.

Conclusions

Based on the above findings, it is highly recommended that, (i) if situation is not timely addressed, it will lead to a severe environmental disaster or hazard, as nobody selects the air he or she breathes; (ii) air pollution control equipment be installed in-situ at quarry sites where free air flow is available in order to reduce gaseous (pollutant) emissions, and (iii) the seasonal effects, meteorological parameters and time that were influenced by the activities of quarry should be put in check.

Introduction

Stone quarrying and crushing are a global phenomenon and have caused widespread concern throughout the world, including developed countries [ 1 ]. Quarry work is a necessity that provides many of the materials used in traditional laying, such as limestone, granite, marble, slate, sandstone, and even clay, in order to produce ceramic tiles [ 2 ].

Quarrying has become critical in several developing countries, including Nigeria. Nigeria is endowed with enormous quarry resources, which have greatly contributed to national wealth and accompanying socioeconomic benefits. Quarry resources are an essential source of income for a country, but they must first be explored, mined, and processed before they can be used [ 3 ]. Various sorts of environmental harm and risks, according to [ 4 ], unavoidably follow their three phases of mineral growth. The intricate brew of gases that compose the earth’s atmosphere has seen significantly more change recently. Due to the increase in pollutants, human activities ranging from residential energy use to large-scale industrial operations are mostly to blame for this poor state of the atmospheric elements. A significant environmental issue that affects both industrialised and developing nations worldwide is air pollution. Due to the fact that there are numerous sources, it has a wide range of impacts on human health.

According to [ 5 ], mineral discovery and growth in Nigeria date back to the Palaeolithic age. According to [ 6 ], the colonial authorities began quarrying limestone in Nigeria in 1920 at Abakaliki, and as a result of its further exploitation, the Nkalagu Cement Company (NIGERCEM) was founded. Despite the fact that limestone was only discovered in Nigeria in 1920, according to [ 7 ], quarrying at Old Ebonyi Local Government Area began around 1800.

Research has revealed that for the past 30 years, quarrying, limestone production, and the crushing of solid rock have been the main industries in Ebonyi State, Nigeria. The existing quarry industries in Ebonyi State range from stone quarrying to small and medium-sized quarries using heavy equipment, and the number of such industries is estimated to be between 100 and 150 [ 8 ]. Dust from quarries is a major source of air pollution, although the severity will depend on factors such as the local climate, the concentration of dust particles in the surrounding air, the size of the dust particles, and their chemical constituents because limestone quarries produce highly alkaline (active) dust while granite quarries produce acidic dust [ 9 ]. Dust is caused by explosions, material handling, wind blows, soil erosion, and truck movement [ 10 ]. Air pollution is not only annoying, but it has health effects, especially for those with respiratory problems.

A significant negative impact of environmental quarrying is the damage to biodiversity [ 11 ], where plants (plant cover) represent a major part of the ecosystem as they play a key role in maintaining balance in oxygen content and carbon dioxide through photosynthetic activities [ 12 ]. Such plant mutations have been a major concern for botanists and biologists in recent years, who have promoted a careful and prudent approach to activities that promote such mutations [ 13 ].

According to [ 14 ] research, of all the non-fuel mineral commodities produced globally, quarry rocks come in third in terms of size and fourth in terms of value. According to [ 15 ], the building sector uses 75% of the crushed stone that is generated in the United States and comes from rock quarries. On the slope of a hill, along or into a valley, or flat on the ground, a quarry may be found. The loss of sinkholes and underground passageways is typically the only significant geomorphological effect of quarries constructed on flat terrain.

In ref. [ 14 ] reported that quarry on valley side can extend laterally along the valley side causing large geomorphic impacts or they can work back into the valley wall, where the impact is less. Quarries on hills generally have large geomorphic impacts which indicate that crushed stone quarrying have removed an entire karsts hill. The work of [ 16 ] states that people living close to the quarries are affected by the activities that go on in that area. In quarrying areas like the village of Pali in India, the safety of human beings is not put into considerations. There is no personal protective equipment being provided to workers, helmet, safety belts, masks, safety shoes are foreign [ 16 ]. The study reported that approximately 200 people have been buried alive during the mine blasting operations in the past decade only. The work postulates that the workers and their family who are residing close to these units are more vulnerable to silica exposure. The children, women and elderly are all breathing these toxins regularly.

However, from an environmental management point of view, air pollution in the form of particles (dust) can also have significant effects on surrounding plants, such as blocking and damaging their internal structures, leaves, and cuticles, as well as chemical effects that can affect longevity [ 17 ]. Quarry activities in Ebonyi State, Nigeria, have had a devastating impact on the environment, with the explosive explosion of rocks causing air pollution, water pollution, biodiversity damage, and man-made environmental degradation that negatively impacts the environment of a specific area through unfinished or abandoned pits that leave a large open space. This not only looks like an eyesore but also endangers livestock, wildlife, and humans [ 18 ]. For example, an Ebonyi State youth leader and his entourage crashed into one of the mines in July 2021 and died on the spot. The number of quarry industries in Ebonyi State, Nigeria, is on the rise. Although it has an impact on internal revenue, there is a need to look at its impact on air quality in general. Heavy metal levels in the soil and plants of quarry locations have been studied [ 19 ] but much work remains to be done on the environmental impact of quarrying on air quality in the study area. The study therefore, intends to examine the environmental impact of quarrying on air quality in Ebonyi State, Nigeria to detect air pollutants at the quarry sites.

Materials and methods

The study area.

The study was conducted in three zones of Ebonyi districts, namely: the Ishiagu quarry site in Ebonyi South Senatorial District, the Umuoghara quarry site in Ebonyi Central Senatorial District, and the Ngbo quarry site in Ebonyi North Senatorial District. Ebonyi State is located in south-eastern Nigeria, approximately within latitudes 05 0 4ʹ and 06 0 4ʹ N at lengths 07 0 35ʹ and 08 0 25ʹ E (Figs.  1 and 2 ).

Source [ 23 ]

A Map of Ebonyi State showing the Senatorial Zones

Source: Researcher's Intern (2021)

A Map depicting the different quarry sites

Ebonyi State falls within the Asu-River Geologic Group (Lower Cretaceous), Eze-Aku Shale Formation, and Nkporo Formations (Fig.  3 ). The state is mostly made up of hydromorphic soils, which are shallow-depth reddish-brown gravelly and pale-colored clayey soils with shale parent material. The terrain is mostly flat, with a high point of 162 m and a low point of 15 m above sea level. The state lies within the Cross River Drainage Basin. It has a population of 2,176,947 and a 5,533 km 2 landmass [ 20 ]. Pseudo-bimodal (April to July and September to November) is the pattern of the rainfall in the study area. It has an annual rainfall range of 1700–2000 mm and 1800 mm as the annual mean. Ebonyi State has 27 0 C as the minimum temperature and 31 0 C as the mean maximum daily temperature. During the rainy season, the humidity of the study area is 80% high, while the dry season is 60% low. Despite the high amount of rainfall in the area, groundwater resources are relatively scarce [ 21 ]. This is because the shale, which predominantly underlies the study area, is rarely aquiferous. They are predominantly hard, massive, and impermeable [ 22 ].

Geological setting of Ebonyi State

Site selection and experimental design

The following study sites were chosen after an initial survey of the study sites was conducted in 2021 during the dry season (March) and the rainy season (July).

However, the three quarries were chosen based on the senatorial zones that make up the state to ensure proper research representation and coverage (Table 1 ).

The air quality parameters measured in the sampled air were particulate matter (PM 10 ), nitrogen dioxide (NO 2 ), carbon monoxide (CO), hydrogen sulphide (H 2 S), sulphur dioxide (SO 2 ), chlorine (Cl 2 ), volatile organic compounds (VOCs), ammonia (NH 3 ), hydrogen cyanide (HCN). Noise levels were also measured. Air quality was measured 0–50 m away from three different quarry areas (Ishiagu, Umuoghara, and Ngbo). The control was taken 3 km from each quarry area. The sampling lasted for 24 h; the reading of each parameter was taken in accordance with the hours indicated in the [ 24 ]. The air quality instruments were installed in the tripod stand position at 6 m above ground level and at stability for air quality measurement. However, in order to obtain accurate data on the effect of quarry activities on air quality in the study area, the quarry site was visited in the morning (6:00am), afternoon (12:00 noon), and evening (6:00 pm) (Table 2 ). Therefore, the measurements for each parameter were taken three times and the average reading is taken from each parameter.

Statistical analysis

The generated data was analyzed using analysis of variance (ANOVA) in a Completely Randomized Design (CRD). To statistically differentiate between datasets, Fisher's Least Significant Difference (FLSD) was used. The level of significance was accepted at a 5% probability level [ 25 , 26 ]. There were also comparative analyses between the data and World Health Organization [ 24 ] standards.

Results and discussion

Environmental impact of quarrying on pm 10 , co, h 2 s, no 2 , so 2 , cl 2 , vocs, nh 3 , hcn and noise during the dry season.

The results of PM 10 , CO, H 2 S, NO 2 , SO 2 , Cl 2 , VOC, NH 3 , HCN and Noise levels during the dry season are shown in Tables 3 , 4 , and 5 . The tables showed significant differences (p < 0.05) in PM 10 , CO, H 2 S, NO 2 , SO 2 , Cl 2 , VOCs, NH 3 , HCN, and noise levels in the study area.

According to Table 3 , the concentration levels of particulate matter (PM 10 ) in the various locations studied are lowest at 360.00 µg/m 3 , 650.07 µg/m 3 , and 800.12 µg/m 3 in the evening for Ishiagu, Umuoghara and Ngbo. They are slightly higher in the morning at 365.09 µg/m 3 , 700.13 µg/m 3 , and 830.10 µg/m 3 for Ishiagu, Umuoghara and Ngbo; while they are 380 µg/m 3 , 710.12 µg/m 3 and 860.30 µg/m 3 highest in the afternoon for Ishiagu, Umuoghara and Ngbo. However, control was 8.10 µg/m 3 , 8.97 µg/m 3 and 5.79 µg/m 3 in the morning, afternoon and evening. The diurnal pattern for all observed PM 10 concentration levels in the dry season showed a unimodal distribution pattern. The concentration level of PM 10 slowly increased at 6:00 am, significantly increased at 12:00 pm, and then decreased significantly at 6:00 pm. This significant increase and decrease can be attributed to rush-hour traffic and vehicular congestion in the afternoon and the closing of work in the evening. When the three quarry sites were compared, this observation revealed that the PM 10 concentration level was higher in the Ngbo quarry site than in the Umuoghara and Ishiagu quarry sites. They are all above the [ 24 ] recommended permissible limit of 45 µg/m 3 , except for control. High PM 10 concentrations are known to irritate mucous membranes and can lead to a number of respiratory issues, including coughing and asthma [ 27 ] Inhaling fine particles for an extended period of time and in excess can increase the risk of developing cancer and dying from respiratory diseases. Furthermore, PM 10 can harm materials by discoloring or destroying painted surfaces and corroding metals (at relative humidity levels above 75%) [ 28 ] By blocking sunlight and serving as a catalytic surface for the reaction of absorbed chemicals, it can also be unpleasant.

The concentration levels of NO 2 in the different locations and controls studied are the lowest in the evening, with concentration levels of 19.10 µg/m 3 (Ishiagu), 41.82 µg/m 3 (Umuoghara), 15.60 µg/m 3 (Ngbo), 3.18 µg/m 3 (control), and increase lightly in the morning to 23.45 µg/m 3 (Ishiagu), 45.26 µg/m 3 (Umuoghara), 18.36 µg/m 3 (Ngbo) and 4.24 µg/m 3 (control), with the highest concentration levels in the afternoon at 26.70 µg/m 3 (Ishiagu), 49.87 µg/m 3 (Umuoghara), 20.97 µg/m 3 (Ngbo), and 4.28 µg/m 3 (control). The diurnal variation of NO 2 in the dry season showed a unimodal pattern, with the first peak at 6:00 am, the highest peak at 12:00 pm, and the declination at 6:00 pm, respectively. However, the concentration of NO 2 increased significantly in the afternoon and decreased significantly in the evening. The unimodal distribution pattern of the NO 2 diurnal variation showed that the peak occurs during the afternoon due to the presence of high levels of UV radiation [ 29 ]. The NO 2 diurnal variation clearly shows that the increase in the number of motor vehicles on the roads greatly influences the air quality on the study sites during the peak hours. This study showed that a higher NO 2 concentration level was observed in the Umuoghara quarry site than in the Ishiagu or Ngbo quarry sites when the three quarry sites were compared. They are all above the [ 24 ] recommended permissible limit of 10 µg/m 3 , except control. The high concentration of NO 2 in the locations can be attributed to the usage of heavy equipment such as crushing plants, trucks, and generators, among others. The formation of nitrogen oxides often occurs during higher-temperature combustions, such as those found in industrial settings and car engines. Nitrogen is easily partially oxidized to generate NO 2 , which is typically released through the exhaust pipes of cars and other vehicles, as well as the manifolds of power generation equipment. Nitrogen can also be oxidized at high temperatures to produce NO 2 . Long-term exposure to NO 2 levels exceeding 10 µg/m 3 can increase a person's vulnerability to bacterial infections and induce lung illness.

The study also discovered that H 2 S concentrations were lowest in the evening at 60.40 µg/m 3 (Ishiagu), 75.50 µg/m 3 (Umuoghara), 90.60 µg/m 3 (Ngbo) and 5.28 µg/m 3 (Control), highest in the afternoon at 65.10 µg/m 3 (Ishiagu), 82.25 µg/m 3 (Umuoghara), 96.01 µg/m 3 (Ngbo), 6.02 µg/m 3 (Control), and moderate in the morning at 62.01 µg/m 3 (Ishiagu), 80.01 µg/m 3 (Umuoghara), 92.10 µg/m 3 (Ngbo) and 6.01 µg/m 3 (Control). The diurnal variation of H 2 S in the dry season showed a unimodal pattern, with the first peak at 6:00 am, the highest peak at 12:00 pm, and the decrease at 6:00 pm, respectively. When the three quarry sites were compared, this observation revealed that the H 2 S concentration level was higher in the Ngbo quarry site than in the Umuoghara and Ishiagu quarry sites. They are all above the [ 24 ] recommended permissible limit of 20 µg/m 3 , except control. H 2 S gas is very poisonous, pungent, and corrosive. In some areas, it can be found in natural gas, and in some quarry conditions, sulphate-reducing bacteria can release it. Therefore, sustained exposure to H 2 S gas at levels higher than 20 µg/m 3 can be fatal.

CO had the lowest concentrations of 1500 µg/m 3 (Ishiagu), 2400 µg/m 3 (Umuoghara), 3700 µg/m 3 (Ngbo) and 30 µg/m 3 (Control) in the morning, slightly higher levels in the afternoon with concentration levels of 1900 µg/m 3 (Ishiagu), 2750 µg/m 3 (Umuoghara), 3950 µg/m 3 (Ngbo), 31 µg/m 3 (Control) and moderate levels in the morning with a concentration levels of 1500 µg/m 3 (Ishiagu), 2400 µg/m 3 (Umuoghara), 3700 µg/m 3 (Ngbo) and 30 µg/m 3 (Control). The diurnal pattern for all observed CO concentration levels in the dry season showed a unimodal distribution sequence. The concentration level of CO slowly increased at 6:00 am, significantly increased at 12:00 pm, and then decreased significantly at 6:00 pm. This observation indicated that a higher CO concentration level was recorded in the Ngbo quarry site than in the Umuoghara and Ishiagu quarry sites when the three quarry sites were compared. CO is produced when fossil fuels are only partially oxidized (hydrocarbon). Large diesel-powered generating plants, processing plants, vehicular emissions, diesel and gasoline engines found in heavy-duty machinery, welding machines, trucks, and other items, among other things, are sources of CO in the study region. Long-term and excessive exposure to ambient CO concentrations of more than 1000 µg/m 3 can cause the production of carboxyhemoglobin and prevent the blood from oxygenating, which can result in asphyxia and eventual death. The most vulnerable groups to the effects of this gas exposure include children and the elderly, as well as those with cardiovascular and respiratory conditions.

According to Table 4 , the concentration levels of SO 2 in the locations are lowest in the evening at 42.80 µg/m 3 (Ishiagu), 41.60 µg/m 3 (Umuoghara), 44.00 µg/m 3 (Ngbo) and 2.90 µg/m 3 (Control), and slightly higher in the morning at 44.50 µg/m 3 (Ishiagu), 43.10 µg/m 3 (Umuoghara), 45.01 µg/m 3 (Ngbo), 3.01 µg/m 3 (Control), and in the afternoon at 53.10 µg/m 3 (Ishiagu), 51.99 µg/m 3 (Umuoghara), 58.30 µg/m 3 (Ngbo) and 5.00 µg/m 3 (Control). The diurnal variation for all observed SO 2 concentration levels in the dry season showed a unimodal distribution sequence. The concentration level of SO 2 slowly increased at 6:00 am, significantly increased at 12:00 pm, and then decreased significantly at 6:00 pm. When the three quarry sites were compared, this observation revealed that the SO 2 concentration level was higher in the Ngbo quarry site than in the Ishiagu or Umuoghara quarry sites. The different value of SO 2 in the study area can be attributed to low activities in the study area in the late hours of the day and high activities during the afternoon hour of the day. [ 30 ] contributed to the discovery that SO 2 concentrations are generally low in the morning and rise throughout the day because most of the SO 2 concentration must have settled down during the early hours of the day. However, one significant air contaminant is SO 2 . It typically develops at quarry sites from the oxidation of sulfur-containing fuels, biomass, oil combustion, and car exhaust gases. In humans, exposure to SO 2 , at concentrations exceeding 100 µg/m 3 , may increase mucus secretion, broncho-constriction (as in asthma), and eye irritation. Long-term exposure to lower concentrations may increase the prevalence of associated symptoms and cause death from cardiac and/or respiratory disorders.

Cl 2 had its lowest concentration levels of 22.10 µg/m 3 (Ishiagu), 23.15 µg/m 3 (Umuoghara), 21.47 µg/m 3 (Ngbo) and 6.01 µg/m 3 (Control) in the morning and 23.01 µg/m 3 (Ishiagu), 24.33 µg/m 3 (Umuoghara), 24.20 µg/m 3 (Ngbo) and 6.01 µg/m 3 (Control) in the evening; with its highest concentration levels of 30.21 µg/m 3 (Ishiagu), 31.01 µg/m 3 (Umuoghara), 31.25 µg/m 3 (Ngbo) and 6.20 µg/m 3 (Control) being in the afternoon. During the dry season, the diurnal variation of all observed Cl 2 concentration levels revealed a unimodal distribution sequence. The concentration of Cl 2 gradually increased at 6:00 a.m., increased significantly at 12:00 p.m., and then decreased significantly at 6:00 p.m. When the three quarry sites were compared, this observation revealed that the Cl 2 concentration level was higher in the Ngbo quarry site than in the Ishiagu or Umuoghara quarry sites. The high concentration of Cl 2 in the afternoon can be attributed to explosive and drilling activities that take place around the time and unvented gas leaks from air compressors and other sources within the quarry areas.

VOCs had its lowest recorded concentration levels of 19.30 µg/m 3 (Ishiagu), 20.50 µg/m 3 (Umuoghara), 22.90 µg/m 3 (Ngbo) and 4.89 µg/m 3 (Control) in the evening and 20.20 µg/m 3 (Ishiagu), 21.21 µg/m 3 (Umuoghara), 23.42 µg/m 3 (Ngbo) and 5.90 µg/m 3 (Control) in the morning, its highest concentration levels of 27.63 µg/m 3 (Ishiagu), 30.04 µg/m 3 (Umuoghara), 33.06 µg/m 3 (Ngbo) and 6.00 µg/m 3 (Control) in the afternoon. The diurnal variation for all observed VOCs concentration levels in the dry season showed a unimodal distribution pattern. The concentration level of VOCs gradually increased at 6:00 a.m., significantly increased at 12:00 p.m., and then decreased significantly at 6:00 p.m. When the three quarry sites were compared, the VOCs concentration level was higher in the Ngbo quarry site than in the Umuoghara and Ishiagu quarry sites. The VOCs might be connected to machine and vehicle operations [ 31 ]. The sources of VOCs may be through aerosol sprays, wood preservatives, cleaners, and disinfectants.

NH 3 had its lowest concentration levels of 49.70 µg/m 3 (Ishiagu), 50.05 µg/m 3 (Umuoghara), 53.80 µg/m 3 (Ngbo) and 10.03 µg/m 3 (Control) in the morning, unlike the other parameters considered under study, and slightly higher in the evening 53.43 µg/m 3 (Ishiagu), 52.01 µg/m 3 (Umuoghara), 54.30 µg/m 3 (Ngbo), 10.45 µg/m 3 (Control) and highest in the afternoon 63.12 µg/m 3 (Ishiagu), 65.21 µg/m 3 (Umuoghara), 66.32 µg/m 3 (Ngbo) and 11.12 µg/m 3 (Control), respectively. The diurnal variation for all observed NH 3 concentration levels in the dry season showed a unimodal distribution pattern. The concentration level of NH 3 gradually increased at 6:00 am, significantly increased at 12:00 pm, and then decreased significantly at 6:00 pm. When the three quarry sites were compared, the NH 3 concentration levels were higher in the Ngbo quarry site than in the Umuoghara and Ishiagu quarry sites. The high concentration of NH 3 can be attributed to drilling activities and gas leaks from air compressors during mining activities.

Table 5 showed that HCN had its lowest concentration levels of 43.77 µg/m 3 (Ishiagu), 46.40 µg/m 3 (Umuoghara), 43.10 µg/m 3 (Ngbo) and 5.18 µg/m 3 (Control) in the morning, 45.21 µg/m 3 (Ishiagu), 47.02 µg/m 3 (Umuoghara), 44.20 µg/m 3 (Ngbo), 5.20 µg/m 3 (Control) in the evening, and 65.13 µg/m 3 (Ishiagu), 66.01 µg/m 3 (Umuoghara), 62.66 µg/m 3 (Ngbo) and 5.40 µg/m 3 (Control) in the afternoon, respectively. The diurnal variation for all observed HCN concentration levels in the dry season showed a unimodal distribution pattern. The concentration level of HCN gradually increased at 6:00 am, significantly increased at 12:00 pm, and then decreased significantly at 6:00 pm. This observation indicated that the HCN concentration level was evidently higher in the Umuoghara quarry site than in the Ishiagu and Ngbo quarry sites when comparing the three quarry sites. However, the combustion of synthetic fibres, wool, and silk produces hydrogen cyanide. Additionally, the catalytic digestion of nitrogen oxides during the burning of gasoline in automotive engines results in the production of hydrogen cyanide as well. Only in the absence of a catalyst is the level of HCN in the exhaust gases higher [ 32 ]. Cyanides are primarily gaseous in nature and can travel great distances from their source of emission before entering the atmosphere [ 33 ].

Noise dB(A) had its lowest levels of 39.89 dB(A) (Ishiagu), 40.01 dB(A) (Umuoghara), 38.99 dB(A) (Ngbo), and 09.10 dB(A) (Control) in the morning, followed by 41.01 dB(A) (Ishiagu), 42.77 dB(A) (Umuoghara), 40.33 dB(A) (Ngbo), and 09.23 dB(A) (Control) in the evening, and its highest levels of 50.57 dB(A) (Ishiagu), 52.30 dB(A) (Umuoghara), 53.60 dB(A) (Ngbo) and 10.11 dB(A) (Control) in afternoon. The diurnal variation of all observed noise dB(A) levels revealed a unimodal distribution pattern during the dry season. The level of noise dB(A) gradually increased at 6:00 a.m., significantly increased at 12:00 p.m., and then decreased significantly at 6:00 p.m. This observation revealed that the noise dB(A) level was clearly higher in the Umuoghara quarry site than in the Ishiagu and Ngbo quarry sites when the three quarry sites were compared. The primary sources of noise in the research area were rock blasting operations, crushing and processing facilities for rock, haulage lorries, diesel power plants, heavy-duty vehicles, industrial machinery, heavy traffic on the highway, traffic hooting, anthropogenic activities in the area, and so on.

The level of the parameters at different times of the day is highly influenced by the variation in the temperature of Ebonyi State, where the study area is located. The temperature at the time (March) when the field survey was carried out was between 27 and 31 °C. Low temperatures prevail in the mornings and evenings, rising sharply as noon approaches and gradually decreasing as evening approaches. As a result of this, concentration levels of all parameters are at their lowest in the morning and evening.

In a similar vein, during the dry season, the research area's wind direction is either NE or SW. This is to be expected since the NE trade winds from the Sahara desert are often the predominant wind pattern in Nigeria during the dry season. Throughout the dry season, the wind is also moderate and does not change greatly. The air pressure during the dry season also reflects this.

In ref. [ 4 ] collaborated on the findings that temperature, wind direction, and speed affect the concentration of air quality in the area. [ 34 ] also reported the finding that the concentration of gases in quarry areas is typically low in the morning and increases slightly as production activities kick off in the afternoon and evening. In ref. [ 35 ] also reported that a particle in the air does travel as there is more wind and atmospheric pressure during this period. Furthermore, most quarries increase their activities during the dry season because construction work also increases. Most construction works involving the use of quarried stones, like road construction, bridge construction, and even other operations requiring large quantities of stone, increase during the dry season. Since the companies increase their activities in the dry season, the implications for air pollution increase. This assertion is supported by [ 36 ], who reported increased activity at a quarry in Obajana, Kogi State.

Environmental impact of quarrying on PM 10 , CO, H 2 S, NO 2 , SO 2 , Cl 2 , VOCs, NH 3 , HCN and noise of air during the raining season

The Tables 6 , 7 , and 8 showed significant differences (p < 0.05) in PM 10 , CO, H 2 S, NO 2 , SO 2 , Cl 2 , VOCs, NH 3 , HCN, and noise concentration levels in the study area.

A careful examination of Table 6 revealed that the concentration levels of PM 10 were lowest in the morning at 280.10 µg/m 3 (Ishiagu), 580.70 µg/m 3 (Umuoghara), 632.00 µg/m 3 (Ngbo), 4.60 µg/m 3 (Control), highest in the afternoon at 286.00 µg/m 3 (Ishiagu), 620.07 µg/m 3 (Umuoghara), 680.22 µg/m 3 (Ngbo) and 6.79 µg/m 3 (Control), and lowest in the evening at 282.11 µg/m 3 (Ishiagu), 601.20 µg/m 3 (Umuoghara), 640.34 µg/m 3 (Ngbo) and 6.19 µg/m 3 (Control). The diurnal pattern for all observed PM 10 concentration levels in the rainy season reflects the same unimodal distribution pattern as in the dry season. It has also been said that because there is less wind and temperature during this time, airborne particles do not move. The majority of quarries also scale back their operations during this rainy season as a result of the drop in the amount of construction work, including the building of roads, bridges, and even other projects needing vast quantities of stone. Because businesses scale back during the rainy season, there is a corresponding decrease in air pollution compared to the dry season.

The concentration levels of NO 2 are observed lower in the morning 17.00 µg/m 3 (Ishiagu), 28.20 µg/m 3 (Umuoghara), 11.25 µg/m 3 (Ngbo), 3.01 µg/m 3 (Control) and increase lightly in the afternoon 21.56 µg/m 3 (Ishiagu), 33.62 µg/m 3 (Umuoghara), 12.77 µg/m 3 (Ngbo), 3.20 µg/m 3 (Control) with an increase in the evening 24.01 µg/m 3 (Ishiagu), 36.23 µg/m 3 (Umuoghara), 15.45 µg/m 3 (Ngbo) and 4.27 µg/m 3 (Control). The diurnal variation of NO 2 during the rainy season follows the same unimodal pattern as during the dry season. This observation indicated that a higher NO 2 concentration level was observed in the Umuoghara quarry site than in the Ishiagu or Ngbo quarry sites when comparing the three quarry sites as observed in the dry season. They are all above the [ 24 ] recommended permissible limit of 10 µg/m 3 , except for control.

The study also observed that H 2 S had the lowest concentration levels of 38.18 µg/m 3 (Ishiagu), 52.07 µg/m 3 (Umuoghara), 61.10 µg/m 3 (Ngbo) and 3.76 µg/m 3 (Control) in the evening, the highest in the afternoon 43.70 µg/m 3 (Ishiagu), 59.52 µg/m 3 (Umuoghara), 69.24 µg/m 3 (Ngbo), 4.22 µg/m 3 (Control) and a moderately higher concentration in the morning 40.15 µg/m 3 (Ishiagu), 57.20 µg/m 3 (Umuoghara), 64.75 µg/m 3 (Ngbo) and 4.11 µg/m 3 (Control), respectively. The diurnal variation of H 2 S in the rainy season showed the same unimodal pattern as in the dry season. This observation indicated that the H 2 S concentration level was lower during the rainy season than in the dry season. This is because the majority of quarries scale back their operations during this rainy season as a result of the drop in the amount of construction work when compared with the dry season.

That of CO too is lowest in the evening 790 µg/m 3 , 1200 µg/m 3 , 2000 µg/m 3 and 21 µg/m 3 ; slightly highest in the afternoon 887 µg/m 3 (Ishiagu), 1290 µg/m 3 (Umuoghara), 2900 µg/m 3 (Ngbo), 23 µg/m 3 (Control) and moderate in the morning 843 µg/m 3 (Ishiagu), 1240 µg/m 3 (Umuoghara), 2210 µg/m 3 (Ngbo) and 22 µg/m 3 (Control). They are all above the [ 24 ] recommended permissible limit of 1000 µg/m 3 , except for control. The diurnal variation of CO in the rainy season showed the same unimodal pattern as in the dry season. This observation indicated that CO concentration levels were lower during the rainy season than during the dry season. The lower CO concentration during the rainy season compared to the dry season could be attributed to lower quarry output during the rainy season.

SO 2 concentrations (Table 7 ) are 40.00 µg/m 3 (Ishiagu), 39.21 µg/m 3 (Umuoghara), 40.13 µg/m 3 (Ngbo) and 2.60 µg/m 3 (Control) at their lowest in the morning, slightly higher at 50.23 µg/m 3 (Ishiagu), 49.12 µg/m 3 (Umuoghara), 54.00 µg/m 3 (Ngbo), 4.50 µg/m 3 (Control) in the afternoon, and decreasing at 41.19 µg/m 3 (Ishiagu), 40.30 µg/m 3 (Umuoghara), 42.40 µg/m 3 (Ngbo) and 2.99 µg/m 3 (Control) in the evening. The diurnal variation of SO 2 in the rainy season showed the same unimodal sequence as in the dry season. This observation indicated that SO 2 concentration levels were lower during the rainy season than during the dry season. The low concentration level of SO 2 in the rainy season when compared with the dry season effect may be attributed to low quarry operation output during the rainy season.

Cl 2 had the lowest concentration levels in the morning of 20.87 µg/m 3 (Ishiagu), 22.23 µg/m 3 (Umuoghara), 21.79 µg/m 3 (Ngbo) and 5.77 µg/m 3 (Control), with the highest concentration levels in the afternoon of 29.60 µg/m 3 (Ishiagu), 30.20 µg/m 3 (Umuoghara), 31.00 µg/m 3 (Ngbo) and 6.00 µg/m 3 (Control), and decreased in the evening to 22.10 µg/m 3 (Ishiagu), 23.14 µg/m 3 (Umuoghara), 24.10 µg/m 3 (Ngbo) and 5.77 µg/m 3 (Control). The diurnal variation of Cl 2 in the rainy season followed the same unimodal pattern as the dry season. This finding indicated that Cl 2 concentrations were lower during the rainy season than during the dry season. The low concentration of Cl 2 in the rainy season when compared to the dry season data may be attributed to low quarry operation output in the study areas during the rainy season.

The lowest recorded concentration levels of VOCs were 15.44 µg/m 3 (Ishiagu), 17.13 µg/m 3 (Umuoghara), 19.10 µg/m 3 (Ngbo) and 4.13 µg/m 3 (Control) in the evening, 18.53 µg/m 3 (Ishiagu), 19.00 µg/m 3 (Umuoghara), 21.20 µg/m 3 (Ngbo) and 5.10 µg/m 3 (Control) in the morning, and 23.19 µg/m 3 (Ishiagu), 26.80 µg/m 3 (Umuoghara), 29.14 µg/m 3 (Ngbo) and 5.89 µg/m 3 (Control) in the afternoon. The diurnal variation of VOCs in the rainy season showed the same unimodal flow as identified in the dry season. This showed that VOCs concentration levels were lower during the rainy season than during the dry season. The low concentration level of VOCs in the raining season when compared with dry season data may be attributed to low quarry operation output during the raining season in the study areas.

NH 3 had the lowest concentration levels in the morning at 23.54 µg/m 3 (Ishiagu), 27.80 µg/m 3 (Umuoghara), 29.29 µg/m 3 (Ngbo) and 09.45 µg/m 3 (Control), and slightly higher in the evening at 31.00 µg/m 3 (Ishiagu), 32.07 µg/m 3 (Umuoghara), 34.23 µg/m 3 (Ngbo), 09.77 µg/m 3 (Control), and highest in the afternoon at 54.11 µg/m 3 (Ishiagu), 53.32 µg/m 3 (Umuoghara), 66.32 µg/m 3 (Ngbo) and 10.00 µg/m 3 (Control). NH 3 diurnal variation in the rainy season is the same unimodal pattern as identified in dry season. During the rainy season, NH 3 concentration levels were lower than in the dry season. The low concentration level of NH 3 in the rainy season when compared with dry season data may be akin to low quarry operations during the rainy season in the study areas.

Table 8 showed that HCN had its lowest concentration levels of 42.13 µg/m 3 , 45.12 µg/m 3 , 41.52 µg/m 3 and 5.00 µg/m 3 in the morning, 44.60 µg/m 3 , 46.24 µg/m 3 , 42.09 µg/m 3 , 5.09 µg/m 3 in the evening, and 63.00 µg/m 3 , 65.11 µg/m 3 , 60.01 µg/m 3 and 5.26 µg/m 3 in the afternoon, respectively. NH 3 diurnal variation in the rainy season is the same unimodal pattern as identified in the dry season.

During the rainy season, HCN concentration levels were lower than in the dry season. The low concentration level of HCN in the rainy season when compared with dry season data may be akin to low quarry operations during the rainy season in the study areas. However, the combustion of synthetic fibres, wool, and silk produces hydrogen cyanide. Additionally, the catalytic digestion of nitrogen oxides during the burning of gasoline in automotive engines results in the production of hydrogen cyanide as well. Only in the absence of a catalyst is the level of HCN in the exhaust gases higher [ 30 ]. Cyanides are primarily gaseous in nature and can travel great distances from their source of emission before entering the atmosphere [ 31 ].

Noise dB(A) had the lowest levels in the morning of 37.01 dB(A), 38.22 dB(A), 36.01 dB(A), and 09.00 dB(A), followed by 39.56 dB(A), 40.14 dB(A), 38.67 dB(A), and 09.12 dB(A) in the evening, and 48.20 dB(A), 50.11 dB(A), 50.42 dB(A) and 10.00 dB(A) in the afternoon. Noise level is lower in the rainy season than in the dry season.

However, the temperature variation and wind speed are lower in the rainy season than in the dry season. This seasonal variation in temperature and wind speed is expected.

The results of this study confirmed that quarrying in the three zones of Ebonyi districts released air pollutants into the environment. In the quarry areas, air pollutants such as PM 10 , NO 2 , H 2 S, CO, SO 2 , Cl 2 , VOCs, NH 3 , HCN, and noise were detected. Statistical analysis confirmed that quarrying has a significant negative impact on air quality. For sustainable quarrying, it is recommended to install air pollution control equipment such as High-Efficiency Particulate Air (HEPA) Filters, Selective Non-Catalytic Reduction (SNCR), Adsorbers (Activated Carbon), Packed-Bed Scrubbers, Selective Catalytic Reduction (SCR), and Wet Gas Scrubbers in-situ in the quarry area where free air flow is available and to develop an industrial code of conduct as a means of self-regulation to reduce pollutant emissions to the atmosphere. However, proven case studies of quarry air pollution control can be seen in the Case study at Tan Uyen quarry, Ho Chi Minh megapolis, Vietnam. Additional observations showed that the effects reported were seasonal because all the parameters had higher values during the dry season than they did during the rainy season. Conclusively, if this situation is not timely addressed, it will lead to a severe environmental disaster or hazard, as nobody selects the air he or she breathes. Also, the seasonal effects, meteorological parameters and time that were influenced by the activities of quarry should be put in check.

Data availability

The datasets generated during this work are not publically available for reasons known to the authors, but they are available upon reasonable request from the corresponding author.

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Acknowledgements

Our profound appreciation goes to the almighty God for his protection, goodness, and mercy throughout the study. We also express our gratitude to the staff of the Department of Geography, Alex Ekwueme Federal University Ndufu Alike, Ebonyi State, Nigeria, and the Department of Soil Science and Environmental Management, Ebonyi State University, Nigeria who made their laboratory facilities available for the analysis of this research.

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Okafor, O.C., Njoku, C. & Akwuebu, A.N. Environmental impact of quarrying on air quality in Ebonyi state, Nigeria. Environ Sci Eur 35 , 98 (2023). https://doi.org/10.1186/s12302-023-00793-6

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DOI : https://doi.org/10.1186/s12302-023-00793-6

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Looking at the history of our geological and mining heritage, we can see the evolution of the role played by underground mining sites over the centuries. However, if the activity of quarrying stones is as old as the presence of humans on earth, the issue of the territorial regeneration, based on the recovery and re-functionalization of abandoned quarries, is one of the central arguments of the contemporary debate. The extractive activity that on one hand constitutes an important economic resource for numerous territories, on the other hand requires particular attention to the environmental impact it causes. The theme is that of the so-called drosscapes, soils and residual spaces, once marginal and peripheral in relation to the cities, which today occupy interstitial positions and often central locations within the urban and peri-urban tissues, covering a decisive role in the activation of processes aimed at the overall rebalancing of the affected contexts [ 1 , 2 ]. The considerable number and extent of the formerly extractive cunicular systems, underneath our urbanized grounds, makes the issue of their protection, recovery and reuse extremely urgent (together with their consolidation in the cases in which it is necessary). Today, the need for a balanced development of the territory compares with the theme of planning which involves many figures coming from different disciplines: geologists, botanists, architects, landscapers, designers and artists. The figure of the designer moves in this interconnected multidisciplinary context, describing new operational practices, in which the now stable involvement of the citizen gives rise to new inclusive and fruitful practices of participatory planning. Emphasizing the relational vocation of design, as a discipline, questions are asked about what role design can play in the dialogue with the various subjects involved. One wonders what it means for the designer to create the devices of relationship and involvement of the actors at the various scales of the landscape; to translate the desires and requests of the inhabitants into space, but also the public and private interests of the other stakeholders present, working towards the definition of a shared language; to encourage the communities to look after their daily landscape. The article, through the support of some emblematic case studies, describes some procedural lines of intervention that outline new strategies for the re-use and recovery of quarry landscapes. These, no longer perceived as “wounds” and “places of refusal”, are stabilized as territorial resources, common goods to be valued through the recognition of the underlying value and a deep comprehension of these resources. The article identifies, through the projects examined, processes constituted by minimal but significant intervention. These processes respond to the desire for simplicity, that reads (and responds to) complexity and contradictions [ 3 , 4 ] present in these landscapes, which are events rich of high anthropological, architectural, urban, historical and cultural value.

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Environmental rehabilitation linking natural and industrial heritage: a master plan for dismissed quarry areas in the emilia apennines (italy).

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Thus, if the limited compressive strength of tufi and pozzolane of some quarries (to mention the Italian ones: Orvieto, Rome and Salento) has led to the formation of hypogeal voids developed in length and of medium size, suggesting a minimum usability, based on the sole mileage, the high mechanical resistance of Vicenza stone extracted in Arcari, has generated extremely large and extremely high-quality caveale environments.

For a description of the extractive technique of “open pit quarries: in the pit, in the trench, in steps” see in [ 6 ], Le cave. Recupero e pianificazione ambientale. Manuale per la gestione sostenibile delle attività estrattive, Dario Flaccovio Editore, Palermo, 270.

Made at a mutual distance equal to the desired width for the segments; the steps were secondarily cut at a distance equal to the length of the stone that was to be made. The prisms thus delimited were then detached with the use of wedges and hoes. The cultivation works proceed by descending horizontal slices 25 cm thick. Each slice is divided into trances intersected by a double order of cuts, made with machines with vertical cuts at 50 cm intervals. The secondary cuts are performed with a horizontal single-axis machine with a vertical axis that allows the separation of a variable length depending on the intended use.

Specifically, on the subject of the stone quarry, the interventions of some contemporary artists have assumed a paradigmatic role for the conceptual and formal contents that they transmit, and for the contribution they give to the interdisciplinary contribution of the intervention approach.

The American James Turrel and the Spaniard Eduardo Chillida chose the excavation inside the rocky mountain body to react to the light and the matter of the hypogean spaces (Roden Crater, a project in the Arizona desert volcano and Tindaya Mountain in the void excavated in the island Fuerteventura of the Canary Islands).

Among the projects of Francesco Venezia particularly significant on this theme: the proposal for access to the Temple of Segesta (1980), where the passage takes place between the dark bowels of the earth dug towards the light, the “light well” of the exhibition of the exhibition “The Etruscans” inside Palazzo Grassi in Venice (2000) and the Museum of Historical Stratigraphy in Toledo (2006–2007), built at the same time as the excavation, as a “tacit alliance” between the ground, excavation and the underworld.

Mario Bellini during his participation to the conferences held in Pusiano in September 1991, in Mendini A., Mesacem. Appunti per un progetto culturale, Arti grafiche Meroni, Lissone, 1994, 36.

The concept of “weak thought”, theorized by the philosopher Gianni Vattimo in the early eighties, seems to be the interpreter and bearer of a new system of valid assumptions for a new society. The new values of fragmentation, of detachment from the closed and completed form once and for all, of the eventuality and of the basic “becoming” of all things, seem to lead to the de-legitimization of the great speculative systems of the past—in particular of the Hegelian system and of the Marxist one - embracing an interrogative, plural, uncertain and therefore “weak” dimension of being: a non-peremptory, almost never peremptory and imposing dimension, a dimension capable of accommodating amendment and variation, a “loose”, soft dimension, available from the provisional provision in which the project takes place.

The preliminary project for the whole surrounding area interested the mining area was entrusted to Enzo Mari.

The stone extracted in the south takes the local name from the municipality where it is exploited (Baux stone, Fontvieille…). Also known as “pierre du midi”, the stone of Les Baux is a limestone slightly shelled, with fine grain and white and blond colour. It derives from the aggregation of calcium carbonate on the calcareous sand. Many marine fossil remains attest to the presence of the sea.

Industrial development also involves the construction of many buildings (factories, warehouses, stations…)

The first exhibition design with the placement of 40 projectors made use of the work of Hans Walter Müller. La Salle Albert Plécy is the third space after the “Entrée Jean Cocteau” which includes the entrance, the rest area, and a majestic stage 20 m high carved into the mountain and used for film projections, and the “Salle Abel Gance” used for exhibitions.

The first exhibition is “Gauguin, Van Gogh, i pittori del colore”, produced by Culturespaces and directed by Gianfranco Iannuzzi, Renato Gatto and Massimiliano Siccardi, which is followed by many others.

The difficult balance between the two destinations of use, cultural and productive, requires the respect of a single unavoidable rule: there must be no interference between the two activities. Therefore, it is necessary to have an appropriate temporal distribution, which allows the entrance to the museum, to the area where the public leisure, play and educational activities are to be visited and performed, only on days when the quarry is inactive.

The field is divided into five levels of cultivation, which can be accessed via two large helical ramps which, from the height of the square, reach a depth of −90 m. At the −5° level, the museum area is set up with a gross area of approximately 5000 m 2 . The cultivation plan provides, in 6 years (2012–2017 authorization period), the extraction of about 400,000 m 3 of plaster, of which 80% will take place right from the 5th underground level. This means that the museum area was located right in the area most affected by the present and future mining activity, in the “beating heart” of the quarry. The choice can be attributed to three reasons: 1. Structural safety: the monitoring of the geo-structural, tensional and deformation structures have identified, in the exhausted mining chambers of the 5th level, an area of “block center”. Musealizzare here means to fit into the safest and most solid area of the quarry, minimizing intervention costs for safety; 2. Usability: the −5° level has a greater potential for use thanks to its regularity; 3. Perceptive values: entering the quarry and penetrating to the last extractive level means living and knowing the productive reality live. Mining in itinere, present at the 5th level, is an essential documentary factor.

The distribution to visitors of a brief handbook of the descent, the dressing procedure with jacket and helmet and the informed consent to be signed before accessing the hypogeum, contributed to creating an underground safety education. Subsequently, the visitors were transferred below ground level with two shuttles in small groups, to ensure the presence in the quarry of no more than 80 people at a time.

Sara Gangemi, Common Landscape. Processi di educazione, partecipazione e empowerment in paesaggi ordinari, Quodlibet, Roma, 2019.

The term choreography is used by the authors because the dance together with the music is the discipline that most contributes in Halprin to the maturation of a dynamic and procedural gaze on the landscape.

Another fundamental text is Halprin, Lawrence, The RSVP Cycles: Creative Processes in the Human Environment, New York, George Braziller, 1970. RSVP is the acronym of Resources, Score, Valuaction, Performance.

The Ephemeral Arts Connection (EAC) has worked on the value of the ephemeral, as a connecting element between contemporary arts and at the same time as a new paradigm for sustainable development. The EAC is an international workshop organized by Stardust *, a contemporary architecture and arts studio (Spain, Italy, Brazil, USA, Syria) and Elisava, International University of Design and Engineering of Barcelona (Spain). The event was supported by many international institutions of enormous prestige including: the Watermill Center in New York, founded by Bob Wilson, the AIU Arab International University of Damascus (Syria) and the Department of Architecture of the University of Palermo (Sicily).

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Serena Del Puglia

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Del Puglia, S. (2021). Re-Build Landscape: Design for the Reuse of Abandoned Quarries. In: Bianconi, F., Filippucci, M. (eds) Digital Draw Connections. Lecture Notes in Civil Engineering, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-59743-6_50

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