Assessing dust concentration at the workplace of a crushing and screening plant operator for special labor conditions evaluation

Introduction

According to data from the Federal Labor and Employment Service of the Russian Federation¹, the mining industry remains the most hazardous sector of economic activity [1, 2]. This is primarily due to the specifics of production processes and the challenging climatic and geographical conditions. In 2023, crushed stone production exceeded 221 million tons, representing a 24.5% increase compared to 2017 (Fig. 1). Crushed stone is one of the primary materials used in construction and the production of building materials. A decline in extraction and production rates is not expected in the coming years due to the implementation of various large-scale federal projects. Consequently, the industry will need to expand its capacity and create more jobs [3, 4].

Fig. 1. Crushed stone production dynamics in Russia from 2017 to 2023

Crushed stone production involves a range of occupational risks and health hazards for workers [4, 5]. Various professions operate within crushing and screening plant, each with specific health risks. For example, dump truck and loader drivers are exposed to noise and vibration, which can lead to hearing loss and vibration disease. However, the most hazardous factor in crushed stone production is dust, which consists of 60% or more silicon dioxide (SiO₂). Crusher and screen operators work in high-dust environments, which can lead to silicosis and other lung diseases [6, 7].

Research in this area primarily focuses on the effects of silica dust on human health and on measuring dust concentration across the entire plant or quarry at various distances from pollution sources. This data is used for modeling and developing dust reduction methods. For instance, Kuznetsov V. S. and Sulamanidze L. F. note that during crushing and screening plant operations, dust concentration at the edge of the sanitary protection zone exceeds the permissible exposure limit (PEL) by 5–10 times [8]. Francis Ahadzi Dzifa investigated the effects of silica dust on quarry workers' health and reported their symptoms, recommending the use of personal protective equipment (PPE) for respiratory protection and eyewear [9]. In his studies, Frederick Anlimma highlights a rise in silicosis cases in several countries and questions the effectiveness of dust control methods in preventing exposure to inhalable crystalline silica [10]. Zhichao Liu proposed an optimized dust reduction method for a crushing station based on modeling results and simulated the dust diffusion pattern associated with this method [11].

Since 2014, Russia has implemented a special labor conditions assessment (SLCA), regulated by federal legislation² and aimed at identifying and evaluating hazardous and harmful production factors at individual workplaces, as well as developing measures to improve working conditions and prevent occupational diseases.

The objective of this study is to determine the dust concentration at the workplace of a crushing and screening plant operator within the framework of the SLCA.

To achieve this objective, the following tasks were set:

• conduct tests and determine the average shift dust concentration in the operator's working zone;
• identify factors affecting dust concentration at the operator's workplace;
• forecast dust concentration at the workplace based on approximated data under various wind speeds;
• evaluate the adequacy and accuracy of the obtained results;
• establish the labor conditions class (subclass) for the operator;
• develop recommendations to reduce dust concentration at the operator's workplace and improve working conditions.

The novelty of this study lies in its comprehensive approach to assessing dust concentration at the workplace of a crushing and screening plant operator, taking into account industry-specific factors and the effect of wind speed on dust concentration.

The scientific significance of the study is in the approximation of data for predicting dust concentration at the operator's workplace depending on wind speed at the production site.

The practical value of the study lies in forecasting dust concentration in the operator's workplace air based on wind speed at the production site and in developing recommendations to reduce dust concentration at the crushing and screening plant.

¹ Ministry of Labor and Social Protection of the Russian Federation. Results of Labor Conditions and Occupational Safety Monitoring in the Russian Federation, 2022. Moscow, 2022.

² Federal Law No. 426-FZ dated December 28, 2013, "On Special Labor Conditions Assessment."

Research methods

To measure dust concentration in the air at the workplace of a crushing and screening plant operator, an aspiration method was applied. This method involves passing a specified volume of air through special filters, after which the dust mass is measured and the concentration calculated¹.

The mass concentration of total dust in the air, K_d, for each individual test is determined by the formula:

were K_d is the dust concentration in the air, mg/m³; m₀ is the mass of the clean filter, mg; m_n is the mass of the filter with deposited dust particles, mg; and V₂₀ s the air volume, adjusted to standard conditions, dm³.

where V_t is the volume of air passed through the filter, dm³; P is atmospheric pressure, kPa; and T is the air temperature at the workplace, °C.

If the measurement times vary, the time-weighted average concentration is calculated by:

where t₁, t₂, … t_n is the measurement times, min.

The average shift dust concentration at the workplace is calculated by:

where K_ash1, K_ash2, … K_ashn are the time-weighted average dust concentrations for each technological operation, mg/m³; T_ash1, T_ash2, … are the durations of each technological operation, min; and ∑Т is the total duration of the work shift, min.

To assess data distribution, the median Me and the geometric standard deviation σ_g are determined:

                                                         Me = e^{ln Me},                                                 (5)

where

The final result is recorded as:

where K  is the arithmetic mean of the measurement results n, mg/m³, and δ is the relative error margins, %.

To assess the accuracy and reliability of the calculations, a probabilistic data processing method may also be used. In this case, the geometric standard deviation is calculated as follows:

where K₈₄ and K₁₆ are the concentration values corresponding to 84% and 16% probability levels, respectively, mg/m³.

The average shift dust concentration is then determined by:

where

ln K_ash = ln Me + 0.5(ln σ_g)².                        (11)

³ Methodology for measuring mass dust concentration by gravimetric method for special labor conditions assessment. MI APFD –18.01.2018; MUK 4.1.2468–09 Measurement of mass dust concentrations in workplace air in mining and non-metallic industry enterprises.

Research results

Dust measurements were conducted as part of the special labor conditions assessment procedure [12, 13] at a crushing and screening plant located in the Moscow region. The operator's workplace is housed in a standalone, container-type facility three meters above ground level, equipped with climate control for air conditioning.

Dust generation occurs throughout the entire production cycle at the crushing and screening plant (Fig. 2). The main factors contributing to dust generation at the site are as follows:

• movement of heavy-duty vehicles;
• loading of raw materials into the receiving hopper;
• operation of the crusher;
• operation of the vibrating screen;
• piling of crushed stone.

The most intensive dust generation at the study site occurs when sorted crushed stone is piled. As it freely falls from the conveyor belt, lighter dust particles detach from the surface of the crushed stone due to air resistance. The greater the drop height, the more kinetic energy the crushed stone acquires, which transfers to dust particles, causing them to move and collide. This results in an increase in the number of collisions and particle fragmentation, generating a larger volume of dust. Another significant factor contributing to high dust concentration at the production site is air velocity, which not only intensifies dust movement but also lifts settled particles from stockpiles and equipment surfaces, thereby increasing dust concentration in the air. Therefore, in this study, air velocity measurements were taken and analyzed for their impact on dust concentration at the operator’s workplace, in addition to the standard methodology.

Fig. 2. Schematic of the crushing and screening plant illustrating the main sources of dust generation

As a mathematical model describing dust emissions, a system of equations can be used, which includes the following [14]:

• Navier–Stokes equation:

• continuity equation:

• Mendeleev–Clapeyron equation:

• heat conduction equation:

• equation for dust concentration variation:

where x, y, z are the Cartesian coordinates; τ is the time; V is the air velocity; P is the air pressure; ρ is the material density; Т is the air temperature; M is the molar volume ; R is the universal gas constant (8.31 J/mol·K); η is the dynamic viscosity; g is the gravitational acceleration; λ(T) is the thermal conductivity coefficient of the material; С(T) is the specific heat capacity of the material; С is the concentration of dust emissions; V_c is the dust settling velocity (0.04 m/s); F_c is the power of the dust source [14].

During the testing, the production process was conditionally divided into four stages of two hours each, evenly distributed throughout the shift. The measurement time for each individual sample was 25 minutes. The total measurement time was 400 minutes, covering 83% of the work shift. Sampling was conducted using AFA filters (analytical aerosol filters) with a PU-type aspirator. During testing, the wind was blowing toward the building housing the operator's workplace. Table 1 presents the measurement results and their subsequent processing according to the standard calculation methodology.

Table 1

Air sampling results for calculating average shift dust concentrations

The results indicate a stable dust concentration in the air at the workplace, as the geometric standard deviation σ_g < 3. However, it should be noted that the average concentrations for each stage differ by a factor of 3–4, due to variations in air velocity and direction at the production site. An increase in air velocity up to 5 m/s was observed from 10:00 to 13:30, corresponding to the peak dust concentration levels at the workplace (Fig. 3).

Fig. 3. Variation in dust concentration at the workplace across different testing stages

Based on the data shown in Fig. 4, it is possible to predict the dust concentration K_dw at the workplace depending on air velocity V at the production site, with an approximation accuracy of R² = 0.95:

            K_dw = 0.2185V³ – 1.1571V² + 3.6493V + 0.4968.     (17)

Fig. 4. Dependence of dust concentration at the workplace on air velocity

Using the graph presented in Fig. 4, we determine the permissible air velocity at the study site:

V_perm = 2.6 m/s.

To establish the relationship between dust generation and various factors—such as technological equipment, vehicle movement, loading of the receiving hopper, and the height of free-falling crushed stone—we calculate the dust concentration using formula (17) with V = 0 m/s:

K_perm.0 = 0.5 mg/m³.

A probabilistic method was applied to assess the accuracy of measurements [15, 16]. This method provides a comprehensive view of all dust concentrations in the air within the workplace area using a logarithmic probability grid. To investigate the conformity of the data to a normal distribution, a frequency histogram method was employed as a graphical approach to data distribution (Fig. 5).

Fig. 5. Normal distribution graph for n = 16

The resulting histogram has a bell-shaped form, resembling a normal curve, which suggests that the data follow a normal distribution [17]. The data for probabilistic analysis are provided in Table 2, where individual dust concentration measurements have been ranked in ascending order with accumulated frequencies determined.

Table 2

Calculation of average shift dust concentration in the workplace area using the probabilistic method

The probability grid (Fig. 6) shows the concentration results with corresponding cumulative frequencies, along with an integrated line drawn through the points. From this line, the following were determined: the median Ме = 6 and concentration values for 84% and 16% (K₈₄ = 12.1 mg/m³; K₁₆ = 3.2 mg/m³).

Fig. 6. Probability coordination grid

To test the assumption of the model's conformity to a normal distribution, the Shapiro–Wilk test will be applied:

where n is the number of observations; x_i is the values of the ordered sample; and a_i are tabulated coefficients depending on the number of trials.

Table 3 presents the intermediate calculations for the Shapiro–Wilk test.

Table 3

Results of intermediate calculations for the Shapiro–Wilk Test

The calculated W statistic exceeds the tabulated value W_t = 0.887 at a significance level of α = 0.05, which confirms, providing 95% confidence that the data distribution conforms to a normal distribution.

The average shift dust concentration obtained using the probabilistic method was 7.6 mg/m³. A deviation of 0.1 mg/m³ demonstrates the accuracy and reliability of the tests, as the confidence interval, according to equation (8), is ± 1.85 mg/m³. The calculated value is therefore accepted as the final result:

K_ash = 7.7 ± 1.85 mg/m³.

The summary results for determining the labor conditions class (subclass) are presented in Table 4. Dust from crushed stone production is classified as an aerosol primarily with fibrogenic potential, which corresponds to hazard class 3. The obtained result exceeds the permissible exposure limit (PEL) by a factor of 1.28, which falls under labor conditions class 3.1 (subclass) and necessitates the establishment of a harmful exposure allowance.

Table 4

Results of labor conditions assessment for the workplace

Source: * GN 2.2.5.3532–18 Permissible Exposure Limits (PEL) for harmful substances in workplace air; ** GOST Р 54578–2011 Workplace air. Aerosols primarily with fibrogenic potential. General principles for hygienic control and impact assessment.

Conclusion

The results of the dust concentration assessment at the workplace of a crushing and screening plant operator indicate an exceedance of the permissible exposure limit (PEL) by a factor of 1.28, corresponding to labor conditions class 3.1 (subclass). The average daily dust concentration at the operator’s workplace is 7.7 mg/m³; however, it should be noted that the average concentrations across different stages vary by a factor of 3–4, influenced by the intensity and direction of air velocity at the production site.

Based on the obtained data, dust concentrations K_dw at the workplace were predicted as a function of air velocity V at the production site, with an approximation accuracy of R² = 0.95. It was determined that the maximum allowable air velocity at the site should not exceed 2.6 m/s.

When PEL values for dust concentration in workplace air are exceeded, legislation¹ requires the employer to halt production and take measures to reduce airborne dust to the lowest possible level.

To reduce dust concentration at the operator’s workplace, comprehensive dust control measures are needed at the crushing and screening plant, including [18–22]:

• washing the wheels of vehicles upon entering and exiting the production site;
• installing stationary or mobile dust suppression systems that use water spray nozzles at low and medium pressure to create a mist;
• replacing the open belt conveyor with a closed conveyor system.

Additionally, it is recommended to replace the filters in the climate control equipment with carbon filters to enhance air purification.

Using approximated data, it was forecasted that, in the absence of air movement at the production site, the dust concentration at the operator's workplace would remain at 0.5 mg/m³. Inhaling crystalline silica can lead to the formation of nodules of connective tissue in the lungs and scarring around the particles. The body's natural defense cells cannot remove this toxic dust, leading to chronic inflammation and potential lung cell damage. Some individuals may experience allergic reactions, such as skin rashes and/or itching, when in contact with the dust. To prevent the development of occupational diseases, operators are advised to use personal protective equipment (PPE) for respiratory, skin, and eye protection throughout the shift.

The presented results can be used to predict dust concentrations at the workplaces of operators at other crushing and screening plants, taking into account individual empirical data collected at each site.

¹ Labor Code of the Russian Federation, dated December 30, 2001, No. 197-FZ