Study on Dust Hazard Levels and Dust Suppression Technologies in Cabins of Typical Mining Equipment in Large Open-Pit Coal Mines in China

Abstract

As the world’s largest open-pit coal producer, China faces severe dust pollution in mining operations. Cabins of mining equipment (electric shovels, haul trucks, drills) exhibit unique micro-environmental contamination due to dual-source pollution (external infiltration and internal secondary dust generation), posing severe health risks to miners. This study focused on electric shovel cabins at the Heidaigou open-pit coal mine to address cabin dust pollution. Through analysis of dust physicochemical properties, a pollution characteristic database was established. Field measurements and statistical methods revealed temporal–spatial variation patterns of dust concentrations, quantifying occupational exposure risks and providing theoretical foundations for dust control. A novel gradient-pressurized air purification system was developed for harsh mining conditions. Key findings include the following. (1) Both coal-shovel and rock-shovel operators were exposed to Level I (mild hazard level), with rock-shovel operators approaching Level II (moderate hazard level). (2) The system reduced respirable dust concentrations from 0.313 mg/m³ to 0.208 mg/m³ (≥33.34% improvement) in coal-shovel cabins and from 0.625 mg/m³ to 0.421 mg/m³ (≥32.64% improvement) in rock-shovel cabins. These findings offer vital guidance for optimizing cabin design, improving dust control, and developing scientific management strategies, thereby effectively protecting miners’ health and ensuring operational safety.

1. Introduction

As the world’s largest coal producer and consumer, coal has maintained a dominant position in China’s energy structure [1,2]. Open-pit mining has become a crucial coal extraction method in China due to its high resource recovery rate and large-scale production capacity [3,4]. By the end of 2023, open-pit coal mines accounted for over 25% of China’s total coal output, with this proportion demonstrating sustained growth. However, intensive operations of heavy mining equipment (e.g., electric shovels, haul trucks [5], drills) generate significant dust pollution through mechanical fragmentation [6], material transfer [7,8], and wind erosion [9]. Studies indicate that particulate matter (0–10 µm) can be inhaled into the respiratory system, posing health risks to miners. Particles smaller than 10 µm are defined as respirable dust in this study. Total dust concentrations in open-pit mines range from 50 to 200 mg/m³, with respirable dust constituting over 30% of total particulates—levels substantially exceeding China’s occupational exposure limits [10]. In the field of occupational health in open-pit mines, there is a significant research gap regarding the dust exposure mechanism and prevention and control technology in the enclosed micro-environment of mining engineering machinery cabs, despite the maturing dust control technology for the entire mining process. This phenomenon not only poses significant threats to worker health but also accelerates mechanical wear, emerging as a critical obstacle to sustainable mining practices.

Electric shovel cabins, as the primary workspaces for mining equipment operators, exhibit characteristic dual-source pollution: external high-concentration dust infiltrates through door/window gaps and ventilation systems [11], while internally, operator clothing continuously generates secondary dust contamination. This combined pollution results in PM_2.5/PM₁₀ concentrations reaching 40–60% of outdoor levels within cabins. Prolonged exposure elevates occupational disease risks, particularly pneumoconiosis and chronic obstructive pulmonary disease (COPD) [12,13,14]. More critically, reduced visibility caused by suspended dust impairs operators’ situational awareness in complex operations [15].

Current occupational dust exposure assessments for open-pit mine shovel operators remain predominantly qualitative, with two critical research gaps. (1) A quantitative characterization system for the temporal-spatial distribution of PM_2.5/PM₁₀ mass concentrations within cabins has not been established. (2) The dose–response relationship between dust particle size components and respiratory disease incidence lacks evidence-based medical support. More notably, the engineering control field has yet to develop an integrated protection system combining directional airflow and negative pressure isolation specifically for electric shovel cabins, resulting in a lack of effective technical interventions for occupational health monitoring. To address these dual challenges, urgent research is needed on cabin dust transport mechanisms and the development of gradient pressure differential dust control devices based on fluid dynamics principles. This will provide crucial theoretical support for establishing a three-tier pneumoconiosis prevention system in open-pit mines.

In recent years, research on dust pollution in confined spaces has been extended to multiple industrial scenarios, encompassing typical environments such as mining engineering machinery cabs, coal storage silos [16], tunnel excavation faces [17], and enclosed vehicle compartments [18]. Notably, Cha [19] systematically compared particulate matter exposure levels in crew cabins, driver’s cabs, and service compartments through a multi-scenario monitoring campaign conducted on trains during 2016–2017. The data revealed that the highest particulate matter exposure occurred in passenger compartments. Lexen [20] innovatively developed an exposure assessment framework for semi-volatile organic compounds (SVOCs) in vehicle cabs. Their proposed “source-pathway-receptor” tripartite analytical model provides a novel paradigm for investigating SVOC migration mechanisms, particularly emphasizing the urgent need to study SVOC bioaccumulation effects. Liu [21] established a dust distribution model based on the dispersion characteristics of blasting dust in tunnels. The tunnel was divided into heavily polluted and lightly polluted zones, while the influence of curvature radius on dust emission regions was identified. Furthermore, Wang [22] collected respirable coal mine dust samples from two coal seam roadways and conducted detailed chemical analyses. The results demonstrated a significant proportion of limestone rock dust within the respirable coal mine dust.

Related studies have not only focused on the physicochemical characteristics of pollutants but scholars have also sought to advance the understanding of pollutant formation mechanisms and dispersion patterns. Tang [23] developed a 1:1 scale open-pit mining and loading simulation model using SCDM software. Through Fluent software, airflow velocity fields and dust migration patterns under varying temperature and humidity conditions were systematically investigated. To address roadway dust contamination issues, Wang [24] examined dust dispersion dynamics in underground roadways and established a predictive model for dust concentration distribution. Bai [25] constructed a continuous mining tunnel model to analyze how ventilation duct outlet positions (d) and external air curtain (EAC) outlet velocities (v_vent) influence dust dispersion patterns in mining tunnels. Ao [26] extended this research frontier by employing Fluent simulations to characterize dust dispersion patterns under various operational conditions in coal storage sheds.

Concurrently, with scholars’ fundamental research on physicochemical characteristics and formation mechanisms of dust and pollutants in confined spaces, advanced control measures have been progressively developed. Zhu [27] developed a surfactant-enhanced microbial dust suppressant by incorporating surfactants into bio-based suppressants. This compound was demonstrated to effectively agglomerate dust particles into consolidated masses, achieving significant dust concentration reduction. Chen [28] conducted a comparative investigation of multiple transfer chute configurations. Using a two-phase three-dimensional Euler–Euler model, the dust suppression performance of these configurations was predicted, with the experimental results demonstrating effectiveness in dust emission reduction. Zhou [29] performed numerical simulations of dust dispersion patterns in fully mechanized mining faces under varying dip angles using gas–solid two-phase flow theory. Field measurements validated simulation accuracy, leading to the proposal of a tracking enclosed dust suppression technology. Azam [30] subjected coal dust samples to dynamic water vapor sorption techniques, inducing particle interactions manifested as expansion, moisture adsorption, water retention, and granulometric alterations. These physicochemical modifications were found to substantially influence dust transport dynamics and sedimentation behavior. Organiscak [31] collaborated with mining equipment manufacturers to engineer a novel cabin filtration system for industrial mineral machinery, aimed at reducing the exposure of equipment operators to dust and diesel particulates in mines.

This study aims to systematically assess occupational dust exposure risks in open-pit mine electric shovel operator cabins and develop efficient engineering control technologies to improve working environments. The research protocol was implemented in three phases. First, systematic characterization of dust particle size distribution and chemical composition in operator cabins was conducted using laser diffraction analysis and X-ray fluorescence spectroscopy. These quantitative analyses provided fundamental data for subsequent engineering control development. Furthermore, field measurements combined with mathematical statistics were employed to comprehensively evaluate the temporal variation and contamination levels of dust pollution in electric shovel cabins. Finally, based on the physicochemical characteristics of cabin dust, a targeted dust suppression device was developed specifically for electric shovel cabins operating under harsh conditions in open-pit coal mines. Field validation demonstrated that this device significantly reduced dust concentrations in electric shovel cabins. The research findings have been successfully implemented at the Heidaigou open-pit coal mine, Zhungeer Energy Co., Ltd. (Ordos, China), China Energy Investment Group, providing technical support for occupational health monitoring systems in mining operations.

2. Materials and Methods

2.1. Materials and Data Collection

The Heidaigou open-pit coal mine, located in Jungar Banner, Ordos City, Inner Mongolia, is operated by China Energy Investment Corporation Zhungeer Energy Co., Ltd. With a designed capacity of 35 million tons per annum (3.5 × 10⁷ t/a), this mega-scale open-pit coal mine maintains advanced production technologies in surface mining [32]. This study selected two electric shovel models (WK-35 and WK-55) operating at the mine as research subjects, hereafter referred to as the coal shovel and rock shovel, respectively. Sampling was conducted using AKFC-92A mining dust samplers (Qingdao Juchuang Group Co., Ltd. China University of Mining and Technology; (Qingdao, China)) in the operator cabins of the No. 3 WK-35 coal shovel and the No. 3 WK-55 rock shovel. Coal dust and rock dust samples were collected over standard 8 h shifts. The sample collection and data monitoring protocol are illustrated in Figure 1.

A dual-mode dust monitoring system was developed based on high-sensitivity sensor selection principles and field operability requirements. The system integrates an SCJCY handheld dust concentration detector for real-time monitoring and a CCZG2 personal sampler (QINGDAO JINGCHENG INSTRUMENT Co., Ltd. China University of Mining and Technology; (Qingdao, China)) for collecting time-weighted average concentration data. Dust concentration variations in the cab of the No. 3 WK35 coal shovel and the No. 3 WK55 rock shovel were monitored before and after activation/deactivation of the ventilation system. The SCJCY detector (QINGDAO JINGCHENG INSTRUMENT Co., Ltd. China University of Mining and Technology; (Qingdao, China)) was deployed during daytime operations, while the CCZG2 sampler was utilized for nighttime monitoring. Further experimental details are summarized in

Table 1. Dust concentration measurement plan for electric shovel cabins.

Monitoring Equipment	Monitoring Period	Methodology	Targets
SCJCY handheld dust concentration detector	4 working days (post-shovel maintenance—16:30, day shift, non-fixed intervals)	Day 1: After cleaned ventilation system activated Day 2: Comparative variables (after cleaned system deactivated) Continuous monitoring with non-periodic intervals, recording equipment status and environmental parameters	Days 1–2: Cab of No. 3 WK35 coal shovel
			Days 3–4: Cab of No. 3 WK55 rock shovel
CCZG2 personal sampler	4 working days (16:30–00:30, night shift, 8 h)	Day 1: After cleaned ventilation system activated Day 2: Control experiment (after cleaned system deactivated) Maintained operational loads with calibrated devices properly worn by operators	Days 1–2: Cab of No. 3 WK35 coal shovel
			Days 3–4: Cab of No. 3 WK55 rock shovel

.

2.2. Test Methods for Physicochemical Characteristics of Cabin Dust

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Particle size distribution analysis

Particle size characterization was performed using a Mastersizer 2000 (Shandong Naike Technology Analytical Instrument Co., Ltd China University of Mining and Technology; (Jinan, China)) laser particle analyzer. This instrument employs laser diffraction technology, where dust samples are dispersed in the optical measurement zone. The scattered light intensity from particles under laser illumination was measured to determine size distribution parameters.

(2)

Mineralogical composition analysis

X-ray diffraction (XRD) analysis was conducted for phase identification using crystal lattice diffraction phenomena.

Dust samples were analyzed with a Rigaku Ultima IV (SHANGHAI LIJING SCIENTIFIC INSTRUMENT Co., Ltd. China University of Mining and Technology; (Shanghai, China)) X-ray diffractometer. Phase matching of diffraction patterns was performed using Jade software (Jade 6.5), followed by quantitative determination of inorganic mineral percentages through adiabatic method calculations.

(3)

Elemental composition analysis

X-ray fluorescence (XRF) spectroscopy was employed for rapid, non-destructive elemental analysis. This technique utilizes X-ray excitation of inner-shell electrons, producing characteristic fluorescent X-rays that were detected and analyzed for qualitative and quantitative determination.

Dust samples were examined using an EDX-2800B (SHANGHAI JINGPU SCIENCE [T]TECHNOLOGY Co. Ltd. China University of Mining and Technology; (Shanghai, China)) energy-dispersive X-ray fluorescence spectrometer.

(4)

Proximate analysis methods

The industrial composition of coal is generally classified into four components: moisture, ash, volatile matter, and fixed carbon.

Moisture determination: The drying loss method was employed to measure coal dust moisture content.

Ash determination: Samples were placed in a muffle furnace (Hebi Metallurgical Machinery Equipment Co., Ltd. China University of Mining and Technology; (Hebi, China)) and combusted at 815 ± 10 °C for 40 min. After 5 min of air cooling, the residues were transferred to a desiccator for further cooling before weighing.

Volatile matter determination: Samples were heated in porcelain crucibles at 900 ± 10 °C, where volatile components were thermally decomposed into gaseous compounds, leaving residual organic matter as solid char.

Fixed carbon calculation: Fixed carbon content was calculated using Equation (1) after determining moisture, ash, and volatile matter contents on an air-dried basis as follows:

$$FCad(FC)=100-(Mad+Aad+Vad)$$

(1)

In Equation (1), we have the following:

Mad denotes the moisture content on an air-dried basis (%);

Aad represents the ash content on an air-dried basis (%);

Vad indicates the volatile matter on an air-dried basis (%);

FCad corresponds to the fixed carbon content on an air-dried basis (%).

(5)

Microscopic morphology analysis

To investigate the microstructural characteristics of dust samples, coal and rock dust specimens were examined using a scanning electron microscope (SEM, CIQTEK Co., Ltd. China University of Mining and Technology; (Hefei, China)) at magnifications of 1000 times and 25,000 times. An electron beam generated by the electron gun was directed onto the sample surfaces to acquire morphological and compositional information.

(6)

Free silica content determination

Given the irreversible health hazards posed by inhalation of free silica, quantification of its concentration in cabin pollutants was prioritized. The pyrophosphoric acid method was employed for free silica determination in dust samples. This method operates on the principle that free silica reacts with pyrophosphoric acid to form precipitates. The silica content was calculated through gravimetric measurement of precipitates or spectrophotometric analysis of dissolved phosphate ion concentrations. All procedures strictly followed the Chinese national standard GBZ/T192.4-2007 [33].

2.3. Method for Analyzing the Level of Hazard of Cabin Dust to the Human Body and Protection Technology

2.3.1. Method for Analyzing the Level of Hazard of Cabin Dust to the Human Body

This study applied the Chinese occupational hazard classification standard for industrial workplaces (GBZ/T 229.1-2010)[34] to assess the dust exposure risks for electric shovel operators. The hazard grading index G was calculated according to Equation (2) as follows:

$$\mathrm{G}=W_M\times W_B\times W_L$$

(2)

In Equation (2), three weighting factors are defined as follows:

$W_M$ (weighting factor for free silica content in dust);

$W_B$ (weighting factor for the occupational exposure ratio of workplace dust);

$W_L$ (weighting factor for physical labor intensity).

The industrial dust operations are classified into four hazard levels based on the grading index G as follows:

Grade 0 (relatively harmless): G = 0;

Grade I (mild hazard): 0 < G ≤ 6;

Grade II (moderate hazard): 6 < G ≤ 16;

Grade IV (high hazard): G > 16.

The four hazard levels based on the grading index G can be seen in

Table 2. Hazard classification of industrial dust operations.

Grading Index	Hazard Levels
0	0 (Relatively Harmless)
0 < G ≤ 6	I (Mild Hazard)
6 < G ≤ 16	II (Moderate Hazard)
G > 16	IV (High Hazard)

.

The hazard assessment of dust exposure involves three weighting factors: free silica content, occupational exposure ratio, and physical labor intensity. The calculation methods for these factors can be seen in

Table 3. The weighting factor of free silica content in dust: $W_M$.

Free Silica Content M (%)	$\mathbf{Weighting} \mathbf{Factor} ({\mathbf{W}}_{\mathbf{M}}$)
M < 10	1
10 ≤ M ≤ 50	2
50 < M ≤ 80	4
M > 80	6

.

The weighting factor of free silica content in dust: $W_M$.

The weighting factor of the occupational exposure ratio: $W_B$ can be seen in

Table 4. The weighting factor of the occupational exposure ratio: $W_B$.

Exposure Ratio (B)	$\mathbf{Weighting} \mathbf{Factor} ({\mathbf{W}}_{\mathbf{B}}$)
B < 1	0
1 ≤ B ≤ 2	1
B > 2	2

.

The exposure ratio (B) is calculated using the following equation:

$$\mathrm{B}={\displaystyle \frac{C_{TWA}}{P{C}_{TWA}}}$$

(3)

In Equation (3), we have the following:

B represents the exposure ratio of industrial dust.

$C_{TWA}$ denotes the measured 8 h time-weighted average concentration (mg/m³) of airborne dust in the workplace. When multiple measurements yield inconsistent results, the maximum value is adopted for calculation.

$P{C}_{TWA}$ refers to the permissible concentration time-weighted average (see

Table 5. Permissible concentration time-weighted average $:{\mathrm{P}\mathrm{C}}_{\mathrm{T}\mathrm{W}\mathrm{A}}$.

Dust Type	Free Silica Content M (%)	${\mathbf{P}\mathbf{C}}_{\mathbf{T}\mathbf{W}\mathbf{A}}$(mg/m3)		Critical Adverse Health Effects
		Total Dust	Respirable Dust
Coal Dust	M < 10%	4	2.5	Pneumoconiosis
Rock Dust	10% ≤ M < 50%	1	0.7	Silicosis
	50% ≤ M ≤ 80%	0.7	0.3
	M > 80%	0.5	0.2

for specific values).

The weighting factor for workers’ physical labor intensity ${:\mathrm{W}}_{\mathrm{L}}$ can be seen in

Table 6. The weighting factor for workers’ physical labor intensity.

Labor Intensity Index (N)	$\mathbf{Weighting} \mathbf{Factor} ({\mathbf{W}}_{\mathbf{L}}$)
N ≤ 15	1.0
15 < N ≤ 20	1.5
20 < N ≤ 25	2.0
N > 25	2.5

Note: The calculation of the labor intensity index N in this article refers to the Chinese Standard for Classification of Physical Labor Intensity (GBZ/T 189.10-2007) [35].

.

2.3.2. Protection Technology of Cabin Dust

A new air supply pressurization system for electric shovel cabins in open-pit coal mines has been developed to address the issues of high energy consumption, short filter life, and mismatch with dynamic dust loads in traditional cabin ventilation systems. The system achieves significant energy savings by maintaining positive pressure in the cabin and using local negative pressure adsorption devices while ensuring effective air purification. Moreover, a modular composite filter structure was designed, integrating three-stage filtration technologies: cyclone pre-separation, electret nanofibers, and active catalytic oxidation materials. This design extends the filter life to 1000 h under the harsh working conditions of open-pit coal mines, thereby significantly reducing overall maintenance costs.

The new air supply system was installed on the No. 3 WK35 coal shovel and the No. 3 WK55 rock shovel at the Heidaigou open-pit coal mine. The actual dust-proof performance of the system was evaluated using relevant monitoring methods. The schematic diagram of the air supply pressurization system structure and the related installation design drawings are shown in Figure 2 below. The parameters of the electro-shovel fresh air system accessories are shown in

Table 7. Parameters of the electric shovel fresh air system accessories.

Parameter Type	Description
Dimensions (L × W × H)	479 mm × 255 mm × 261 mm
Power Supply	24 V DC
Boost Rate	3.8 m3/min ± 10%
Waterproofing of Booster	Suitable for outdoor environments but not for full immersion in water
Booster Power	144 W
Filter Element Service Life	1000 h

below.

3. Results and Discussion

3.1. Physicochemical Characterization of Dust in the Cabins of Mining Machinery in Open-Pit Coal Mines

3.1.1. Particle Size Distribution Analysis

The overall particle size distribution of dust samples in the cabin is shown in Figure 3. It is evident that coal dust particles follow a normal distribution, with a trend biased towards larger particle sizes, while rock dust particles exhibit two peaks in their distribution. With 10 μm as the dividing line, non-respirable dust particles larger than 10 μm dominate the coal dust distribution, while rock dust is particularly prominent in the respirable dust fraction of 0~10 μm, significantly exceeding that of coal dust.

The distribution of respirable dust particle sizes in the cabin is shown in Figure 4. For coal dust, the proportions of particles with sizes of 0~2.5 μm and 2.5~10 μm are 2.76% and 6.52%, respectively, with a total inhalable particle proportion of 9.28% for particles smaller than 10 μm. For rock dust, the proportions of particles with sizes of 0~2.5 μm, 2.5~10 μm, and larger than 10 μm are 21.1%, 33.1%, and 45.8%, respectively, with a total inhalable particle proportion of 54.2% for particles smaller than 10 μm.

Data indicate that although both coal dust and rock dust pose inhalation risks to the human body, the low proportion of respirable dust in coal dust means that most of it will rapidly deposit in the nasal cavity, with only a small fraction entering the body. In contrast, the high proportion of respirable dust in rock dust suggests that it is more likely to deposit in the human body, posing a greater health risk to workers.

3.1.2. Mineralogical Composition Analysis

The XRD test results of the dust samples are shown in Figure 5. The coal dust samples are primarily composed of kaolinite (Al₂Si₂O₅(OH)₄) and amorphous substances, with typical amorphous materials, including amorphous carbon and certain metal oxides. The contents of the typical amorphous substances and kaolinite (Al₂Si₂O₅(OH)₄) are 65.9% and 20.5%, respectively, accounting for a total of 86.4%. Boehmite (γ-AlOOH) is the second most abundant component, with a proportion of 7.9%. Minor distributions of quartz (SiO₂) and calcite (CaCO₃) are also present, with proportions of 2.4% and 3.3%, respectively. Based on the high content of amorphous substances, it is inferred that coal dust contains a significant amount of carbon and metal elements. The presence of these metal elements may increase the risk of heavy metal poisoning for operators in the coal shovel cabin.

In rock dust, kaolinite (Al₂Si₂O₅(OH)₄) is the main component, accounting for 58.7%. Quartz (SiO₂) and illite–montmorillonite interlayers (I/S) are the next most abundant components, with proportions of 21% and 10.4%, respectively. The dust sample also contains a small amount of illite (It), with a proportion of 4.2%. Other minor components include sporadic distributions of potassium feldspar (KAlSi₃O₈), plagioclase ((Na,Ca)(Al,Si)₄O₈), and calcite (CaCO₃), with proportions of 3.2%, 1.6%, and 0.9%, respectively. The combined proportion of quartz (SiO₂) and kaolinite (Al₂Si₂O₅(OH)₄) reaches 79.7%, while other minerals are detected at extremely low levels. The proportion of quartz (SiO₂) in rock dust (21%) is higher than that in coal dust (2.4%), indicating that the content of free silica in rock dust is likely to be higher than that in coal dust. This suggests that workers may be exposed to a higher concentration of silica-containing environments and should pay more attention to protection.

3.1.3. Elemental Composition Analysis

As shown in Figure 6, the XRF test results of the dust samples indicate that in coal dust, the elements with the highest content are oxygen (O) and carbon (C), with proportions of 62.04% and 30.3%, respectively. Other elements, such as aluminum (Al) and silicon (Si), have proportions of less than 3.2%. The total content of heavy metals in coal dust is 1.25%, with iron (Fe) accounting for 0.81%, titanium (Ti) for 0.34%, and zirconium (Zr) for 0.1%. Although the overall proportion of heavy metals is less than 1.3%, long-term exposure to coal dust can still pose health risks.

In rock dust, silicon (Si) accounts for 26.44% and oxygen (O) for 26.33%. Other elements such as aluminum (Al), iron (Fe), potassium (K), calcium (Ca), and titanium (Ti) are also present in significant proportions, at 17.23%, 15.15%, 6.77%, 4.53%, and 2.36%, respectively. Elements such as zirconium (Zr) have lower proportions, not exceeding 0.39%. The total content of heavy metals in rock dust is 15.85%, including iron (Fe), zirconium (Zr), manganese (Mn), and zinc (Zn) with proportions of 0.38%, 0.27%, and 0.05%, respectively. Studies have shown that long-term exposure to silica-containing environments can induce a series of lung diseases, especially silicosis, which is an irreversible and serious occupational disease. Compared with coal dust, rock dust has higher contents of heavy metals and silicon (Si), and long-term contact or exposure to rock dust can pose more severe health risks [36].

3.1.4. Industrial Proximate Analysis

The industrial analysis of the collected coal samples is presented in

Table 8. The industrial analysis results.

Moisture Mad (%)	Ash Aad (%)	Volatile Vad (%)	Fixed Carbon FCad (%)
1.81	89.46	7.78	0.95

. The air-dried moisture content of the dust in the electric shovel cabin is relatively low at 2.48%, and the ash content is 17.33%, which classifies it as low–medium ash coal (referring to GB/T 15224.1-2018 [37]). The dry ash-free volatile matter content is moderately low at 26.58%, and the fixed carbon content ranges between 40% and 50%. This indicates that the coal belongs to the long-flame coal category within bituminous coal, characterized by a short coal-forming period and a low degree of coalification.

3.1.5. Microscopic Morphology Analysis

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Analysis of sem results for coal dust samples

As shown in Figure 7, under a magnification of 1000 times, the coal dust samples clearly exhibit a large number of coarse particles, which is consistent with the particle size distribution results. Additionally, some particles can be observed to have flaky smooth structures on their surfaces. When the magnification is increased to 25,000 times, the presence of pores and mineral components can be further observed. It can be seen that the crystals are tightly packed to form aggregates with few pores, and there is an obvious lack of well-developed pore structures.

(2)

Analysis of sem results for rock dust samples

As shown in Figure 8, under a magnification of 1000 times, the rock dust samples exhibit a large number of fine particles, with only a few larger particles present. This indicates that the particle size of the rock dust samples is significantly smaller than that of the coal dust samples. However, the particle distribution of the rock dust samples is more compact, and some particles have a honeycomb-like pore structure attached to them. Under a magnification of 25,000 times, a large number of flaky or laminar structures were found to exist. Kaolinite (Al₂Si₂O₅(OH)₄) is clearly visible in flaky form and sometimes forms aggregates similar to microspheres.

3.1.6. Free Silica Content Determination Analysis

The detection results of free silica are shown in

Table 9. Free silica test results.

Sample Parameters	Dust Samples
	Coal Dust	Rock Dust
Collection Site	No. 3 WK35 cabin	No. 3 WK55 cabin
Results	0.74%	24.6%

. The mass fraction of free silica in rock dust is 24.6%, which is significantly higher than that in coal dust samples (0.74%). This detection result shows a significant positive correlation with the proportion of Si-O elements in the XRF elemental composition analysis. Epidemiological studies have confirmed that when the content of free silica in the working environment exceeds 10%, the risk of silicosis significantly increases. Moreover, if the exposure to free silica increases by 1%, the progression of pulmonary fibrosis speeds up. Workers in rock dust cabin environments should pay attention to protection.

3.2. Analysis of Pollutants in the Cabins of Mining Machinery in Open-Pit Coal Mines

3.2.1. Analysis of Pollutants

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Analysis of pollutants in the cabin of the no. 3 WK35 coal shovel

The variation graph of dust concentration in the cabin of the No. 3 WK35 coal shovel was made based on the measurement data recorded, as shown in Figure 9. By analyzing Figure 9, the image intuitively shows the concentration variation process of PM_2.5 and PM₁₀ in the cabin of the No. 3 WK35 coal shovel under the start–stop state of the fresh air pressurization system.

When the system was not enabled, the dust concentration in the cabin showed significant fluctuation characteristics. The real-time curves of PM_2.5 (0.040–0.050 mg/m³) and PM₁₀ (0.050–0.057 mg/m³) continuously stayed at the high position of the vertical axis, indicating that the dust generated by the operation of mechanical equipment, the combustion emissions, and the pollutants infiltrating from the external environment continuously accumulated in the enclosed space. During the monitoring process, two sharp drops in concentration occurred at 103 min and 146 min, which may be attributed to the following. ① The electric shovel was intermittently interrupted due to the full load of the mine truck. ② The brief opening of the cabin doors and windows caused instantaneous airflow disturbance, accelerating the diffusion of dust. ③ The sensor was triggered to automatically clean due to the signal shift caused by the accumulation of dust.

After the system was started, the overall distribution range of PM_2.5 concentration dropped to the range of 0.022–0.028 mg/m³, and the overall distribution range of PM₁₀ concentration dropped to the range of 0.028–0.038 mg/m³, with the concentration difference between the two stabilizing at 0.006–0.010 mg/m³. The comprehensive analysis shows that after the operation of the fresh air pressurization system, the overall dust concentration band shifted downward, and the overall concentrations of PM_2.5 and PM₁₀ showed the characteristics of small variation amplitude and relatively concentrated distribution, with the variation curves of PM_2.5 and PM₁₀ dust concentrations showing high similarity. These data confirm that the fresh air pressurization system effectively reduces the dust concentration in the cabin through continuous air exchange, significantly improving the quality of the working environment for open-pit mining equipment.

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Analysis of pollutants in the cabin of the no. 3 wk55 rock shovel

The variation graph of dust concentration in the cabin of the No. 3 WK35 coal shovel was made based on the measurement data recorded, as shown in Figure 10. By analyzing Figure 10, the image intuitively compares the dynamic variation process of PM_2.5 and PM₁₀ concentrations in the cabin of the No. 3 WK55 rock shovel before and after the fresh air pressurization system was activated.

When the fresh air pressurization system was not enabled, the dust pollution in the cabin was severe. During the monitoring period from 0 to 32 min, the concentration curves of PM_2.5 (0.110–0.138 mg/m³) and PM₁₀ (0.150–0.177 mg/m³) showed violent fluctuations; after 36 min, PM_2.5 concentration dropped from 0.141 mg/m³ to 0.081 mg/m³, with a decrease of 0.060 mg/m³, and PM₁₀ concentration dropped from 0.188 mg/m³ to 0.112 mg/m³, with a decrease of 0.076 mg/m³. It was also found that sharp drops in concentration occurred at the monitoring nodes of 36 min and 76 min. The first sharp drop was due to the planned blasting operation in the area near the monitoring equipment, which caused the measurement personnel to temporarily leave the rock shovel and interrupt the monitoring. When the measurement resumed, the initial concentration increased to 0.141 mg/m³ (PM_2.5) and 0.188 mg/m³ (PM₁₀) due to external dust. The second sharp drop was directly related to the material handling during the rock shovel loading operation, where a large amount of material slid from the rock pile or fell from the bucket, causing instantaneous dust, and the dust concentration in the cabin increased to 0.121 mg/m³ (PM_2.5) and 0.163 mg/m³ (PM₁₀).

After the system was activated, the dust concentration significantly decreased and showed a stable layered distribution. The overall distribution range of PM_2.5 concentration was 0.070–0.080 mg/m³, and the overall distribution range of PM₁₀ concentration was 0.105–0.113 mg/m³, indicating that the system has the ability to continuously purify.

The comprehensive analysis shows that after the fresh air pressurization system was activated, the overall dust concentration band shifted downward, indicating that the system has the ability to continuously purify and improve the air quality around the operators. At the same time, the stable low-concentration environment also helps to improve the visibility of the dashboard and the comfort of operation.

3.2.2. Analysis of the Degree of Hazard of Dust to the Human Body

The degree of dust hazard to workers is related to the weight numbers of factors such as the content of free silica in dust, the occupational exposure ratio of dust in the workplace air, and the physical labor intensity of the work. Therefore, the degree of dust hazard to workers can be determined by obtaining the weights of each factor.

(1)

Degree of dust hazard to coal shovel operators

The No. 3 WK35 electric shovel excavates coal seams, so by selecting the relevant data measured by the No. 3 WK35 electric shovel, the degree of dust hazard to coal shovel operators can be determined. According to the “Table 8 Free Silica Test Results”, the free silica content M of coal dust collected in the cabin of the No. 3 WK35 coal shovel is 0.74%, so the weight number ${\mathrm{W}}_{\mathrm{M}}$ is assigned a value of 1. According to the Section 3.2.1, the maximum measured value of the 8 h time-weighted average concentration of productive dust in the air of the No. 3 WK35 coal shovel is 4.479 mg/m³, and the corresponding time-weighted average permissible concentration of dust in the workplace air, ${\mathrm{P}\mathrm{C}}_{\mathrm{T}\mathrm{W}\mathrm{A}}$, is 2.5 mg/m³. The exposure ratio B is calculated to be 1.7916, so the weight number ${\mathrm{W}}_{\mathrm{B}}$ is assigned a value of 1. Referring to the Chinese standard for grading physical labor intensity (GBZ/T 189.10-2007 [35]), the labor intensity index N of the operators of the No. 3 WK35 electric shovel is statistically calculated as 27, so the weight number ${\mathrm{W}}_{\mathrm{L}}$ is assigned a value of 2.5. The hazard degree grading index G can be calculated as 2.5 using Equation (1), so it is finally determined that the dust hazard degree of coal shovel operators in the Heidaigou open-pit coal mine is at Level I (mild hazard level).

(2)

Degree of dust hazard to rock shovel operators

The No. 3 WK55 electric shovel excavates rock strata, so by selecting the relevant data measured by the No. 3 WK55 rock shovel, the degree of dust hazard to rock shovel operators can be determined. According to the “Table 8 Free Silica Test Results”, the free silica content M of rock dust collected in the cabin of the No. 3 WK55 rock shovel is 24.6%, so the weight number ${\mathrm{W}}_{\mathrm{M}}$ is assigned a value of 2. According to the Section 3.2.1, the maximum measured value of the 8 h time-weighted average concentration of productive dust in the air of the No. 3 WK55 rock shovel is 0.833 mg/m³, and the corresponding time-weighted average permissible concentration of dust in the workplace air, $C_{TWA}$, is 0.7 mg/m³. The exposure ratio B is calculated to be 1.19, so the weight number ${\mathrm{W}}_{\mathrm{B}}$ is assigned a value of 1. Referring to the Chinese standard for grading physical labor intensity (GBZ/T 189.10-2007 [35]), the labor intensity index N of the operators of the No. 3 WK55 rock shovel is statistically calculated as 29, so the weight number ${\mathrm{W}}_{\mathrm{L}}$ is assigned a value of 2.5. The hazard degree grading index G can be calculated as 5 using Equation (1), so it is finally determined that the dust hazard degree of rock shovel operators in the Heidaigou open-pit coal mine is at Level I (mild hazard level) and is about to reach Level II (moderate hazard level).

According to the aforementioned analysis, both coal shovel and rock shovel operators at the Heidaigou open-pit coal mine are currently classified under Class I (mild hazard level). However, the hazard exposure for rock shovel operators approaches the threshold of Class II (moderate hazard level). Under current working conditions, the following interventions should be implemented: (1) the improvement of the working environment in electric shovel cabins to reduce operators’ actual dust exposure levels; (2) the installation of standardized hazard warning signs with protective guidelines; (3) the implementation of occupational health training programs targeting dust-related risks; and (4) the establishment of regular workplace monitoring and occupational health surveillance protocols.

3.3. Assessment of the Dust Purification Effect of the Cabin Fresh Air System

3.3.1. Effectiveness Assessment of the Monitoring System Based on a Handheld Dust Concentration Detector

Based on the data of dust concentration variation before and after the activation of the fresh air pressurization system for the No. 3 WK35 coal shovel and the No. 3 WK55 rock shovel obtained from Section 2.1, the average values were taken to create an effectiveness evaluation graph of the fresh air system for open-pit mining equipment using a handheld dust concentration detector, as shown in Figure 11. By analyzing Figure 11, it can be seen that the operation of the fresh air system significantly improves the working environment of the electric shovel. The average PM_2.5 concentration of the No. 3 WK35 coal shovel decreases from 0.042 mg/m³ to 0.025 mg/m³, achieving a purification efficiency of 40.48%, and PM₁₀ concentration decreases from 0.054 mg/m³ to 0.032 mg/m³, with a reduction of 40.74%. In comparison, the average PM_2.5 concentration of the No. 3 WK55 rock shovel decreases from 0.123 mg/m³ to 0.078 mg/m³ (a reduction of 36.59%), and PM₁₀ concentration decreases from 0.165 mg/m³ to 0.109 mg/m³ (a reduction of 33.94%). These data indicate that the system performs better in dust reduction in coal shovel operation scenarios than in rock shovel scenarios, suggesting that equipment type and working intensity have a significant impact on system performance. The data also confirm that the fresh air pressurization system has a universal effect on intercepting dust particles of different sizes. Through a continuous purification mechanism, it significantly suppresses dust accumulation, achieving the dual protection goals of engineering control and the prevention and control of occupational diseases.

3.3.2. Effectiveness Assessment of the Monitoring System Based on a Personal Sampler

Based on the respirable dust data before and after the activation of the fresh air pressurization system for the No. 3 WK35 coal shovel and the No. 3 WK55 rock shovel obtained from Section 2.1, an effectiveness evaluation graph of the fresh air system for open-pit mining equipment based on personal protection devices was created, as shown in Figure 12. By analyzing Figure 12, after the fresh air pressurization system was activated, the average concentration of respirable dust for the No. 3 WK35 coal shovel decreased from 0.313 mg/m³ to 0.208 mg/m³ (a reduction of 33.34%), and for the No. 3 WK55 rock shovel, it decreased from 0.625 mg/m³ to 0.421 mg/m³ (a reduction of 32.64%). The dust concentration reduction for both equipment is over 30%, indicating that the system has a stable purification capability for different working scenarios of the electric shovel. It was also found that regardless of whether the fresh air system was activated, the respirable dust concentration of the No. 3 WK55 rock shovel was higher than that of the No. 3 WK35 coal shovel. This may be attributed to systematic differences in working characteristics and equipment conditions. Due to the difference in material crushing characteristics, rock dust is more likely to accumulate in the air than coal dust; the mechanical interaction between the rock shovel and the material during operation is more intense, leading to a significant increase in dust generation. The airtightness of the rock shovel cabin may be better than that of the coal shovel.

4. Conclusions

This study takes the electric shovel cab as the object, systematically analyzes the physicochemical properties and health hazards of dust in the cab of an open-pit coal mine electric shovel, and develops a gradient pressurized dust-proof fresh air system. It breaks through the limitations of traditional dust-proof technology’s insufficient understanding of the dynamic coupling mechanism of the micro-environment and has achieved the following innovative results:

(1)

The total proportion of inhalable particles with a diameter of less than 10 μm in coal dust and rock dust is 9.82% and 45.8%, respectively, indicating that rock dust is more likely to be inhaled into the lungs. The heavy metal content in coal dust and rock dust is 1.25% and 15.85%, respectively, indicating that rock dust has a greater toxic hazard. The free silica content in coal dust and rock dust is 0.74% and 24.6%, respectively, indicating that rock shovel operators are more likely to cause silicosis.

(2)

Operators of coal shovels and rock shovels in the Heidaigou open-pit coal mine are exposed to a dusty environment for a long time, and both are at Level I (mild hazard level) hazard level, but the hazard level for rock shovel operators is about to reach Level II (moderate hazard level).

(3)

The dust prevention effect of the fresh air system in the electric shovel cab is good. After the fresh air system is activated, the concentration of respirable dust in the coal shovel cab is reduced from 0.313 mg/m³ to 0.208 mg/m³, and the protection effect is at least increased by 33.34%. The concentration of respirable dust in the rock shovel cab is reduced from 0.625 mg/m³ to 0.421 mg/m³, and the protection effect is at least increased by 32.64%. Given the outstanding performance of the fresh air system in the electric shovel cab, we will investigate the dust prevention performance of the fresh air system in the cabins of other mining equipment and study the possibility of its large-scale promotion.

This study provides a theoretical basis for the prevention and control of dust pollution in the cab of electric shovels in open-pit coal mines and verifies the engineering applicability of the fresh air system under the harsh working conditions of open-pit coal mines. It also provides data support and practical experience for the optimization and promotion of dust prevention technologies in the future. This achievement is of milestone significance for the primary prevention of occupational pneumoconiosis and provides key technical support for promoting the transformation of the mining industry towards inherent safety and clean production.