1 Introduction

Coal serves as the cornerstone of China’s energy security and plays an irreplaceable role in its economic development and national progress (Zhou et al. 2020). As both the world’s largest producer and consumer of coal, China’s energy mix in 2021 was dominated by coal, accounting for 56% of the primary energy consumption structure (Spencer 2019). To meet the substantial energy demands, China primarily employs open-pit mining for coal extraction, owing to its advantages like large-scale operations, high production output, and reduced costs (Ma et al. 2022; Guo et al. 2021). Consequently, OPCMs occupy a crucial position in China’s energy production landscape, with over 370 active mines currently operating.

Nevertheless, alongside their benefits, open-pit coal mines (OPCMs) also present significant environmental and safety challenges, as highlighted in prior research (Tian et al. 2022, 2023), with dust pollution being a prominent concern (Wang et al. 2022b). Throughout all stages of production in OPCMs, a substantial amount of dust is generated in the form of particulate matter (PM2.5, PM10, and TSP), leading to pollution in the mining area and its surrounding environment (Hosseini et al. 2023). The implications of this dust pollution are far-reaching, affecting the ecological environment (Xiang et al. 2021), the atmosphere, society, and human health (Espitia-Perez et al. 2018; Gautam et al. 2018), as well as compromising the safety of workers and equipment (Jiskani et al. 2022b). Moreover, this phenomenon exacerbates global climate change (Kok et al. 2023). Consequently, significant efforts have been made to promote green and climate-smart mining in open-pit mines (Jiskani et al. 2021, 2022a; Tian et al. 2022, 2023). Notably, particular attention has been given to addressing mine dust pollution (Wang et al. 2021; Luo et al. 2021). Regarding dust pollution in OPCMs, dust prevention and control have consistently remained a focal point of research. Studies in this field predominantly focus on several key aspects, including the physical and chemical characteristics of dust, the characteristics of dust pollution, laws governing dust diffusion, and predictive modeling for dust concentration. Investigated the intricacies of dust pollution in diverse climate and geological contexts (Wang et al. 2023; Gholami et al. 2021).

Regarding the physical and chemical characteristics of dust, Huertas et al. (2012b) conducted particle characteristics of a large OPCM in northern Colombia, revealing a logarithmic normal distribution of TSP and PM10 with carbon, oxygen, potassium, and silicon as the principal elements. The particles typically comprise clay minerals, including limestone, calcite, quartz, and potassium feldspar. Another study by Trechera et al. (2021) analyzed the dust characteristics in three different areas within an OPCM in Xinjiang, China. The findings demonstrated significant differences in the particle size and composition of dust in different areas, with moisture and ash content as critical factors affecting particle size. Additionally, significant differences were observed between the composition of respirable dust and that of the parent coal. Leshukov et al. (2022) analyzed the composition, volume, and toxicity of dust near coal mining areas in the Kemerovo region of Russia. The analysis indicated no significant trend in the overall volume and fractional composition of the dust. However, the study established a substantial association between dust pollution and PM2.5 particles, with an increase in concentration corresponding to an escalation in dust toxicity.

In the realm of dust pollution characteristics, Rojano et al. (2018) conducted a study on particulate pollution in an OPCM located in northeastern Colombia from 2012 to 2016. The results indicated a significant annual increase in PM10 concentration ranging from 6.2% to 7.7%. The rise in PM10 concentration was notably associated with northeast winds exceeding 2 m/s in selected downwind locations. Luo et al. (2021) examined the characteristics of dust concentration changes and influencing factors during a cold period at an OPCM in China. The study revealed that the order of dust pollution severity within the pit followed the December > January > February pattern. Additionally, the dust concentration showed a positive correlation with humidity and a negative correlation with wind speed. Wang et al. (2022b) analyzed the annual variation of dust concentration in the same mining area and observed that the order of dust concentration magnitude was winter > autumn > spring > summer. Ma et al. (2022) analyzed the spatial and temporal distribution characteristics of dust based on 16 measurement points established in an OPCM. The study also investigated the relationship between multiple meteorological factors and dust concentration.

Regarding dust diffusion, Kakosimos et al. (2011) simulated dust dispersion from an open-pit mine to surrounding areas using Fluent and AERMOD models. They found a similarity in the simulation results of the two models. Huertas et al. (2012a) modeled the diffusion of TSP from the mining area to the surrounding area using ISC3 and AERMOD. The results were compared with actual air quality monitoring network measurements, yielding a high correlation coefficient (> 0.73). Furthermore, researchers have explored the diffusion of dust pollution within open-pit mines. Researchers employed numerical simulation software to analyze the wind flow structure characteristics and diffusion laws of dust in deep concave OPCMs. Their findings underscore the presence of large-scale circulation that hinders dust diffusion (Tang et al. 2022; Tang and Li 2021; Wanjun and Qingxiang 2018). Wu et al. (2020) investigated the spatial and temporal distribution of dust migration on road surfaces during vehicle transportation in open-pit mines through theoretical analysis and on-site experiments, identifying the positions of maximum dust concentration in both horizontal and vertical directions. Du et al. (2022) studied the diffusion and distribution of particles during soil dumping operations in open-pit mines through numerical simulation. The results showed that the downwind diffusion distance of PM decreased with increasing PM density during the dumping process. In contrast, the dumping angle had minimal influence on the downwind PM diffusion distance. However, a larger dumping angle resulted in higher PM concentration near the dumping site.

In terms of dust control, numerous scholars have developed dust suppressants. For instance, Jin et al. (2019) developed an environmentally friendly dust suppressant using naturally biodegradable soy protein isolate, anionic surfactant sodium dodecyl sulfate, and other materials. The experiment showed that under wind level 9, a 5% dust suppressant solution exhibited a viscosity of 24.6 mPa·s, compressive strength of 0.48 MPa, and dust suppression efficiency of 93.47%. Additionally, Jin et al. (2022) used potassium persulfate (KPS) as the initiator, sodium hexametaphosphate (SHMP) as the cross-linking agent, soy protein isolate (SPI) and methacrylic acid (MAA) as materials to develop a new type of dust suppressant with a cross-linking network structure. The application of this suppressant reduced the average total suspended particles of an open-pit coal pile by 79.95%. Mingyue et al. (2020) developed an environmentally friendly composite dust suppressant called polyvinyl alcohol/sodium alginate/glycerol (PVA/SA/GLY), which possessed excellent wetting, moisturizing, and degradation properties. At the same time, Wu et al. (2020) extracted urease from soybeans based on the enzyme-induced carbonate precipitation (EICP) technology to prepare a biological dust suppressant. Yu et al. (2022) used adhesive proteins from mussels rich in phenolic hydroxyl and lysine residues to prepare a chemical dust suppressant with strong adhesion and resistance to extreme environments for reducing road dust pollution near open-pit mines.

Regarding the prediction of dust concentration, Qi et al. (2020) proposed a short-term (5 min) PM concentration prediction model based on a random forest (RF) model and mixed particle swarm optimization (PSO). The developed RF_PSO model demonstrated high accuracy in estimating PM concentration, with correlation coefficients between measured and predicted data for PM2.5, PM10, and TSP reaching 0.91, 0.84, and 0.86, respectively. Lu et al. (2021) used a gradient boosting machine (GBM) optimized by PSO for the regression and classification of dust concentration in open-pit mines. The results exhibited a correlation coefficient exceeding 0.9, and the average accuracy of PM2.5 concentration classification was 0.954. Li et al. (2021) introduced a hybrid model based on a long short-term memory network and attention mechanism and applied it to predict TSP concentration. Compared to the ARIMA and LSTM models, the LSTM Attention model displayed superior prediction performance, with an improvement in prediction accuracy of 5.6% and 3.0%, respectively. Luan et al. (2023) proposed a random forest and Markov chain (RF-MC) prediction. By incorporating MC for correction, the root mean square error (RMSE) of PM2.5, PM10, and TSP reduced from 7.40, 15.73, 18.99 to 2.56, 5.28, and 6.27 μg/m3, respectively.

Prior research has predominantly focused on investigating dust generation patterns and suppression in individual processes of OPCMs. However, it is essential to recognize that OPCMs have multiple dust sources and have a vast dust generation area. Consequently, the accumulation of dust from various operational processes, as well as disturbances by wind, significantly contributes to atmospheric pollution at mining sites. Despite existing dust suppression measures, their effectiveness appears inadequate in addressing the prevailing dust pollution. Therefore, distinct from prior research, this article introduces a new approach incorporating meteorological indicators into mine design. The research commences by analyzing the production characteristics, distribution patterns, and dust emission features of large-scale OPCMs in China. Subsequently, it employs both measured data and numerical simulations to analyze the factors that impede dust dispersion at the mining site. Furthermore, the study examines atmospheric pollution characteristics in the mining area based on measured dust data. Through the integration of meteorological data from national monitoring stations with previous research findings, the study considers the escalating adverse effects of the current climatic environment on dust pollution removal and dispersion of pollutants in the mining area. Ultimately, this research proposes an optimized mine design and recommends effective dust control measures within surface mining operations. By harnessing the potential of natural conditions to facilitate dust pollution removal and diffusion, this approach aims to foster green and climate-smart mining practices.

2 Research methodology

The production data of OPCM utilized in this research was obtained from the National Bureau of Statistics. Nine on-site monitoring points were strategically set up within the Haerwusu OPCM, China, to investigate the internal circulation effects. These monitoring points were placed on the lowest coal seam bench, middle rock bench, and middle soil dumping site bench, with three points on each bench, positioned on both sides and in the middle of each bench. The monitoring frequency was set at once every five minutes, and the on-site monitoring duration spanned six days. The lowest coal seam bench was situated at an elevation of 930 m, the middle rock bench at 995 m, and the middle soil dumping site bench at 1025 m. To explore the inversion effect, two additional monitoring points were installed, one within the mining area and the other outside the mining area. The first point was positioned on the surface at 1130 m, while the second point was located on the coal bench at 930 m. Wind speed and precipitation data in Zunhe County, Ordos City, Inner Mongolia Autonomous Region, were from the monitoring station established by the National Meteorological Bureau, with a regional station number of 53553, with a longitude of 111.2167°E, and a latitude of 39.8667°N.

Haerwusu OPCM is located in a typical cold and ecologically fragile area. It is one of China’s typical large-scale OPCMs, boasting an annual output exceeding 30 million tons. The mining depth of the mine is about 200 m. The specific location and overview of the mining area are shown in Fig. 1.

Fig. 1
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Location and overview of Haerwusu Open-Pit Coal Mine, China

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The research methodology employed in this article encompasses statistical analysis of data and numerical simulation using Fluent software. For a detailed explanation of the wind flow simulation method using Fluent software, please refer to the relevant study (Wanjun and Qingxiang 2018).

3 Results and discussion

3.1 Coal production and distribution of OPCMs

3.1.1 Characteristics of coal production from OPCMs

The total coal production in China, coal production from OPCMs, and the proportion of OPCM production in China in recent years are shown in Fig. 2. The data reveals a pattern of initial growth, followed by a decline and subsequent growth. Total coal production increased from 3.52 Bt in 2011 to 4.13 Bt in 2021, representing an increase of 17.33%. Production from surface mines has consistently shown an upward trend, rising from 0.39 Bt in 2011 to 1.04 Bt in 2021, a remarkable increase of 166.67%. Simultaneously, the proportion of OPCM production in the overall coal production has steadily risen over time, climbing from 11.14% in 2011 to 25.18% in 2021. These stats highlight the rapid development of OPCM in China. Pertinent data reveals that approximately 80% of China’s coal supply in 2021 was derived from OPCM, ensuring a reliable energy supply. Considering the national energy requirements, the proportion of OPCM production is expected to continue to grow, playing a crucial role in adjusting China’s coal supply structure.

Fig. 2
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China’s coal production in the last decade (2011–2021)

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3.1.2 Distribution of OPCMs

China’s coal resources are primarily concentrated in the northern region. In comparison to non-coal open-pit mines, OPCMs exhibit distinct characteristics. They are characterized by immense total stripping volumes, with individual mines reaching up to 100 million cubic meters annually. These mines demonstrate rapid advancement speeds, exemplified by the Haerwusu OPCM, which progresses at an annual rate of approximately 400 m. Moreover, OPCMs encompass vast mining areas, with individual mines exceeding 20 square kilometers.

The ecological impact range of OPCM is extensive, with a groundwater impact spanning 5–10 km, a thin soil layer, limited availability of ecological restoration soil sources, and a fragile ecological background. Table 1 and Figure 3 showcases the distribution regions and dust production characteristics of large OPCMs in China. The figure highlights that over 80% of China’s OPCMs are situated in northern high-cold and ecologically fragile areas, characterized by extremely low temperatures below − 40 °C, predominantly the average temperatures below 0℃, and an annual average rainfall of less than 400 mm, exhibiting distinct seasonality with concentration during the summer.

Table 1 Regional distribution of open-pit coal mines in China
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Fig. 3
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Regional distribution of open-pit coal mines in China and dust production characteristics under rapid mining advancement

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Open-pit coal mining represents a complex and systematic process involving multiple stages, including drilling, blasting, mining, transportation, crushing, and disposal. Throughout these processes, the mining area experiences significant dust-related challenges, such as multiple dust sources, substantial dust generation, and uncertain diffusion directions. Consequently, achieving point capture and directional control of dust proves challenging (Gautam et al. 2018). Furthermore, most OPCMs in China are in arid and semi-arid regions with low annual precipitation and over 3000 h of sunshine per year. This arid climate hampers traditional large-scale sprinkling methods to mitigate dust. It is thus apparent that the contradiction between the development of China’s coal resources with OPCMs and environmental protection is particularly prominent.

3.2 Microclimate effect of open-pit coal mines

Another significant factor contributing to severe dust pollution in OPCMs is the presence of microclimates within the pits, which are closely tied to the occurrence and production characteristics of coal seams. In China, OPCMs are predominantly horizontally stratified, featuring a sizeable annual stripping volume, rapid advancement speed, and extremely long working faces. Following surface stripping, a substantial deep concave pit is formed within a short period, leading to rapid changes in the pit’s planar and spatial morphology. The deep concave topography significantly alters the atmospheric temperature and airflow fields within the region. With the rapid dynamic evolution of the planar and spatial morphology, airflow interaction inside and outside the mining area also changes, resulting in the local microclimate in the mining area showing dynamic characteristics and forming the microclimate effect of OPCMs. There are mainly two types of microclimate effects in OPCMs, including the circulation effect and the inverse temperature effect, both unfavorable for dust diffusion (Raj 2015; Tang and Li 2021; Tang et al. 2022).

3.2.1 Circulation effect

The circulation effect refers to the wind flow within the mining area opposite the original wind flow. It is a typical airflow characteristic of deep concave open-pit mines (Tang and Li 2021; Tang et al. 2022). Unlike deep concave open-pit mines, the slope foot of the mining and soil dumping sites in OPCMs are small, with approximately 10° for the mining site and 23° for the soil dumping site. The slope foot of the end wall is larger, measuring around 45°. Therefore, when the end wall is the leeward slope, the circulation effect will likely occur on the side of the mining site close to the leeward slope. Due to the absence of monitoring points on the ground, the weather conditions at the ground during the monitoring period were obtained from the local meteorological bureau, as shown in Table 2. It can be observed that prevailing wind directions at the ground were mainly from the southwest, south, and southeast, accompanied by rainfall for most of the time. Figure 4 illustrates the wind speed and direction recorded at the nine monitoring points throughout the monitoring period. Points 1, 2, and 3 represent the south, middle, and north parts of the bench, respectively. Notably, prevailing wind directions at Coal bench-1 and Rock bench-1 differed significantly from the ground wind direction. The dominant wind directions at these locations were north and northeast, respectively, opposing the prevailing wind direction at the ground level. Moreover, the number of calm winds (wind speed = 0) at these two locations was high, with 1235 and 970 times, accounting for 71.5% and 56.1% of the total monitoring time during the monitoring period, respectively. These findings confirm the presence of a circulation effect within the OPCM. Additionally, diverse wind directions were observed at different locations on the same bench, primarily due to the complex topography within the mine. Furthermore, wind direction changes were complex during the monitoring period due to rainfall. The ventilation effect in the middle position of different benches was more favorable, particularly at the coal bench, where the number of calm winds was 245, accounting for 14.2% of the total monitoring times during the monitoring period. This indicates that ventilation is more effective at the bottom of the OPCM.

Table 2 Weather conditions at Haerwusu Open-Pit Coal Mine
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Fig. 4
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Wind speed at different benches

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Due to the limited monitoring period and absence of actual monitoring data for other wind directions, this study utilizes the Haerwusu OPCM as an example to establish a simplified model for simulating the distribution characteristics of wind flow under different wind directions. As depicted in Fig. 5, the simulation results reveal that when the dump bench and rock bench act as the leeward slope, no circulation phenomenon occurs within the pit. However, when the end bench functions as the leeward slope, circulation transpires on the leeward side, with lower wind speeds observed in the circulation area.

Fig. 5
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Cloud chart of internal wind speed based on numerical simulation

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3.2.2 Temperature inversion effect

Another microclimate effect prevalent in OPCMs is the inversion effect. The huge deep pits present a transformation of local terrain, generating airflow with characteristics resembling valleys and basins. During the daytime, each bench receives less solar radiation, resulting in a slower heating rate of the atmosphere inside the pit than the surrounding atmosphere on the surface. Consequently, a “warm center” phenomenon emerges in the upper part of the pit. Conversely, the surrounding benches experience rapid atmospheric cooling at night, causing cool air to descend to the pit’s bottom, giving rise to a “cold center” phenomenon. This phenomenon contributes to significant temperature inversion effects within the pit (Raj 2015). The intensity of inversion represents a crucial factor influencing dust diffusion under the influence of local airflow. Moreover, dust and water vapor within the mining area exacerbate the inversion effect (Katzwinkel et al. 2012).

For the investigation of the inversion effect within the pit, two monitoring points were established: one inside the pit and another outside the pit. The first point was located on the surface, while the second point was positioned on the coal bench. These two monitoring points were vertically separated by 200 m. The temperature variation characteristics of two measurement points on January 1, April 1, July 1, and October 1 are shown in Fig. 6. The dark blue part indicates periods without an inversion phenomenon. The results reveal that the inversion effect is most pronounced on January 1, with nearly continuous inversion occurring throughout the day in the pit. A noticeable inversion effect was observed on October 1, with no inversion between 7 and 10 a.m. Surprisingly, a significant temperature inversion effect was observed on July 1, possibly linked to rainfall. The evaporation rate of rainwater in the pit was lower than on the surface, resulting in lower temperatures inside the pit. Therefore, it can be seen that there is a significant temperature inversion effect in each season, especially in the cold season. The dust pollution caused by the temperature inversion effect is shown in Fig. 7.

Fig. 6
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Temperature variation characteristics

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Fig. 7
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Dust pollution during cold periods

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3.3 Characteristics of dust pollution

3.3.1 Dust pollution in different areas

Figure 8 illustrates the dust pollution characteristics at different locations of the Harwusu OPCM on July 9, 2020, and July 14, 2020. The designations C, R, and D correspond to coal seam benches, working slope rock benches, and waste dump benches, respectively. Additionally, the numerical labels 1, 2, and 3 pertain to the southern, central, and northern segments of these respective benches. According to the findings, the southern parts of the coal seam benches, and waste dump benches exhibited significantly higher dust pollution levels compared to other areas of the corresponding benches. Notably, the southern part of the waste dump bench experienced the most severe pollution, with respective TSP, PM10, and PM2.5 values of 84.23 μg/m3, 69.95 μg/m3, and 43.44 μg/m3. Similarly, the dust pollution in the coal benches was relatively severe, with corresponding TSP, PM10, and PM2.5 values of 72.16 μg/m3, 59.92 μg/m3, and 39.35 μg/m3, respectively. In contrast, the dust concentration in the southern part of the working rock bench did not exhibit the same pattern. This difference might be attributed to the impact of land acquisition at the time, resulting in significantly lower mining intensity in the southern part compared to the northern part. Nonetheless, even with these factors considered, the dust pollution in the southern part of the coal bench still exceeded that in the northern part, further affirming the exacerbating effect of the circulation phenomenon on dust pollution. Additionally, the southern part of the benches receives less direct sunlight than the central and northern parts. It is more susceptible to temperature inversion effects, which could be another contributing factor to the severe dust pollution in that area. Furthermore, it can be observed that the middle parts of the benches generally experience less dust pollution than the sides.

Fig. 8
figure 8

Dust pollution at coal bench, rock bench, and dump bench

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3.3.2 Dust pollution during different seasons

The pollution characteristics of dust within the mining site were studied for different seasons, including spring (March to May), summer (June to August), autumn (September to November), and winter (December to February). Figure 9 shows the pollution characteristics of dust inside the mining site under different seasons. Monitoring points inside the Harwusu OPCM near the operating area were used to determine these pollution patterns. Taking TSP as an example, as shown in Fig. 9, we can observe that the highest average TSP concentration occurs during the winter season, reaching 86 μg/m3. It is followed by the autumn and spring seasons, with concentrations of 77 μg/m3 and 67 μg/m3, respectively. The summer season exhibits the lowest TSP concentration, at 46 μg/m3. The results indicate that the order of dust pollution in different seasons is winter > autumn > spring > summer, which aligns with findings by Ma et al. (2022) and others based on multiple dust monitoring points in the pit, Ma et al. (2022) established 12 monitoring points at the Anjialing open-pit coal mine. They found that in winter, the average values of PM2.5, PM10, and TSP were 97.04 μg/m3, 125.90 μg/m3, and 345.52 μg/m3, respectively. In summer, the corresponding average values were 67.28 μg/m3, 88.89 μg/m3, and 272.57 μg/m3. The observed seasonal pollution patterns appear to correlate well with the changes in the temperature inversion phenomenon discussed above, implying that temperature inversion significantly impacts dust pollution. Wanjun and Qingxiang (2017) have also noted that temperature inversion is a crucial factor influencing changes in dust pollution. Nevertheless, other meteorological factors, such as wind speed and humidity, can also affect dust pollution (Ma et al. 2022; Huertas et al. 2014).

Fig. 9
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Dust pollution during different seasons

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3.4 Characteristics of major climate change

3.4.1 Trends in wind speed and rainfall changes

The source of dust mainly comes from various operations, and the removal and diffusion of dust mainly rely on meteorological conditions. Of course, mining dust reduction operations can also remove some dust. The primary origin of dust emissions stems from diverse mining operations, while its dispersion and mitigation primarily rely on meteorological factors. Naturally, mine dust reduction measures can also effectively reduce dust levels to a certain extent. Natural factors, such as wind flow and rainfall, play vital roles in dust removal and diffusion, complementing dust reduction efforts in mining operations. Figure 10 depicts the variation characteristics of wind speed and rainfall in different seasons in Zhungeer Banner from 2000 to 2021. The green columns represent wind speed, the blue columns represent rainfall, and the red dashed line indicates the average values.

Fig. 10
figure 10

Characteristics of wind speed and rainfall changes during different seasons from 2000 to 2021

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In spring, wind speed remained higher than the average from 2005 to 2011, but since 2011, it has generally been lower than the average. Meanwhile, the rainfall has consistently been below the average since 2011, with a significant decrease to 13.7 mm in 2020. In summer, the characteristics of wind speed changes are similar to those in spring, with generally lower wind speeds observed after 2011. Furthermore, the summer rainfall showed a pronounced downward trend from 2018, plummeting from 305.3 mm in 2018 to 184.5 mm in 2021. During autumn, the wind speed has remained chiefly lower or close to the average since 2011, exhibiting a slow decreasing trend since 2018. In contrast, rainfall was relatively high from 2014 to 2017 but has been consistently below average since 2017, displaying a declining trend. In winter, the wind speed has mostly been below or close to the average since 2011, with a similar downward trend since 2017. Moreover, rainfall has been significantly lower than the average from 2017 to 2021 (except for 2019). Overall, the self-cleaning capacity of the climate in Zhungeer Banner has shown a decreasing trend in recent years, posing greater challenges for dust prevention and control in OPCMs.

3.4.2 Trends in air stagnation day/air stagnation event

Air stagnation days, where air remains still, often lead to severe pollution. As already proposed (Liao et al. 2018; Wang et al. 2018), air stagnation days are primarily determined by the boundary layer height (BLH) and wind speed at a 10 m height near the ground. According to a prior study (Wang et al. 2022a), as shown in Fig. 11, air stagnation inside OPCMs corresponds to severe dust pollution, particularly during low temperatures. Such days accounted for 46.7% of the study period. If an air stagnation persists for three or more days, it is defined as an air stagnation event. Research indicates a gradual increase in the occurrence of air stagnation days/events, signifying greater challenges for air pollution prevention and control in mining areas in the future.

Fig. 11
figure 11

a Relationship between wind speed and boundary layer height under the standardized PM10 b Grid sample distribution c Winter air stagnation days/event frequency changes in 2009–2018

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3.5 Recommendation for dust prevention and control

The analyses conducted on the distribution characteristics of OPCMs, the microclimate effects within OPCMs, the characteristics of dust pollution under these effects, and the impact of climate change all underscore the urgency and necessity of dust prevention and control in OPCMs for green and climate-smart mining. The current primary method employed for dust reduction in OPCMs is watering (Wang et al. 2021). However, this approach encounters limitations, particularly during winter. Given that most OPCMs are situated in arid and semi-arid regions, large-scale watering becomes challenging. Additionally, there are currently no measures for reducing dust already suspended in the air, which can significantly impair visibility (Baddock et al. 2014; Camino et al. 2015). For instance, in our investigation, dust pollution led to low visibility in the mining area, resulting in multiple equipment shutdowns for over 100 h. Therefore, the key to improving such pollution in mining areas and their surroundings lies in efficiently removing and diffusing dust through appropriate meteorological conditions.

3.5.1 Incorporating meteorological indicators into mining design

Presently, mining design in OPCMs in China neglects meteorological elements, contributing to severe dust pollution. Our previous study (Wang et al. 2022a) revealed that existing mining designs often involve inadequate mining intensity during weather conditions conducive to dust diffusion and, conversely, high mining intensity during conditions unfavorable for dust diffusion. Dealing with this issue necessitates the integration of meteorological indicators in mine design. This includes incorporating weather forecasts to optimize and adjust mining design and leveraging natural conditions for effective dust removal and diffusion. Mining intensity should be adjusted at the leeward slope and back sunny slope based on meteorological elements. For instance, in OPCMs advancing from east to west, special attention should be given to dust prevention and control at the southern slope. In circumstances where the wind direction is oriented towards the south or exhibits a minor southerly component, it is advisable to curtail the operational intensity on the corresponding side of the southern slope.

3.5.2 Modeling dust predictions with meteorological indicators and production intensity

Currently, only a few OPCMs in China have established meteorological dust monitoring platforms, enabling real-time monitoring, and issuing alarms when the concentration exceeds. Although several dust prediction models have been developed (Qi et al. 2020; Lu et al. 2021; Li et al. 2021; Luan et al. 2023), they lack consideration for the intensity of mining operations, limiting their practical application of accurate prediction for guiding production practices. In order to overcome this limitation, establishing a dust concentration prediction model for OPCMs is imperative. This model must encompass essential factors such as dust concentration data, meteorological data, and production intensity data, as depicted in Fig. 12. By incorporating these elements, the model will enable accurate predictions of dust concentration variations during specific timeframes. Subsequently, this will allow for the optimization of production operations’ intensity and the efficient utilization of natural meteorological conditions to enhance dust removal and diffusion processes.

Fig. 12
figure 12

Schematic diagram of the dust prediction model

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4 Conclusions

A green and climate-smart mining approach is an inevitable trajectory for the future development of open-pit mines to assure the harmonious coexistence of resource development and environment protection. This research article comprehensively presents the production and distribution characteristics of OPCMs in China, provides evidence for the presence of circulation and inversion effects in OPCMs, analyzes the dust pollution situation in different regions and seasons of OPCMs, examines the trends of key meteorological indicators impacting dust concentration over the past two decades, and puts forward practical suggestions for future dust prevention and control in OPCMs. The main conclusions drawn from this study are as follows:

  1. (1)

    Rapid Development of OPCMs: China’s OPCMs have experienced significant growth, with production escalating from 0.39 Bt in 2011 to 1.04 Bt in 2021, marking a notable increase of 166.67%. However, over 80% of OPCMs are situated in arid and semi-arid regions, leading to a prominent conflict between resource development and environmental protection.

  2. (2)

    Microclimate Effects in OPCMs: Data from the studied mine indicates the existence of microclimate effects, encompassing circulation effects and inversion effects. Circulation effects occur when the end bench functions as a leeward slope, predominantly affecting one side of the leeward slope. Inversion effects are observed throughout the seasons, with winter exhibiting the most severe effects, followed by autumn. Both circulation and inversion effects exacerbate dust pollution.

  3. (3)

    Regional and seasonal dust pollution patterns: The actual dust monitoring data reveals distinct dust pollution patterns in different regions, with the southern region experiencing the highest pollution levels, followed by the northern and central regions. Similarly, the order of dust pollution in different seasons follows the pattern of winter > autumn > spring > summer. Circulation and inversion effects further contribute to the increased dust pollution.

  4. (4)

    Decreasing atmospheric self-cleaning capacity: Over the past 20 years, there has been a declining trend in the atmospheric self-cleaning capacity, raising concerns about dust pollution in OPCMs. Furthermore, from 2009 to 2018, there has been an increasing trend in the number of air stagnation days/events during the winter in the mining area, further emphasizing the challenges that lie ahead for dust prevention and control in OPCMs.

  5. (5)

    Mine design considerations: To enhance dust removal and diffusion, the design of open-pit mines should carefully consider meteorological elements. Optimizing mining operations in accordance with weather forecasts can maximize the utilization of natural conditions for effective dust prevention and control.

By incorporating these findings and implementing the proposed suggestions, the mining industry can take meaningful steps toward sustainable and environmentally responsible practices in open-pit mining.