Occupational Exposure to Mineral Dust in Mining and Earthmoving Works: A Scoping Review

: Anthropogenic activity is related to several environmental imbalances, including dust. Particulate matter can also hinder humans with numerous health consequences, such as asthma, cancer, and pneumoconiosis. With a particular focus on mineral dust, this review is intended to determine in which circumstances occupational exposure occurs in the mining and earthmoving industries. Research followed the guidelines provided by the preferred reporting items for systematic review and meta-analysis protocols and its extension for scoping reviews. Of the 8993 records identiﬁed, only 24 passed both exclusion and inclusion criteria. Within the pool of results, it was possible to identify the following variables related to dust exposure: job-related (activity, job category, and site), engineering (equipment, transport system), technical (distance), and physical (season and weather) variables. Due to the signiﬁcant variance in protocol settings, it was challenging to perform a general analysis, resulting in a study-by-study approach. The most signiﬁcant conclusion of this study is not related to the setting of occupational exposure, although it derives from it. The necessity of adopting standard procedures for data collection, independent of research objective, was demonstrated within the context of occupational exposure to mineral dust.


Introduction
Air pollution related to particulate matter is a growing concern worldwide. The combination of airborne particulate matter and gaseous pollutants has the power to change the climate both locally and globally and is responsible for ozone depletion and acid rain [1]. However, this issue is not limited to the environment. It directly impacts human beings, both in relation to living conditions and health [2]. According to the World Health Organisation (https://www.who.int/news/item/02-05-2018-9-out-of-10-people-worldwidebreathe-polluted-air-but-more-countries-are-taking-action (accessed on 19 July 2021)) air pollution is a significant problem, as 9 out of 10 people breathe air containing high levels of pollutants, and around seven million people die every year from exposure to fine particles in polluted air.
The sources of air pollutants fall in one of two groups: point sources, which are easily identifiable and stationary; and fugitive sources, which are spatially distributed and cannot be linked to a specific point [3]. Specifically related to mineral dust, the Environmental Protection Agency (in the United States) categorises emissions into process dust and fugitive dust. Process dust can be captured (and mitigated). In contrast, fugitive dust is settled material transported by a the movement of machines or the wind [4]. It is known that dust emissions significantly impact air pollution and, consequently, human health [5]. Anthropogenic activities such as mining (and quarrying) and other earthworks involving pointed to as possible control strategies [29] Other technologies are also suggested in this vein, such as cutting tools with reduced dust-generation mechanisms, such as ultrasonic dust-suppression systems [30]. Timely inspection and equipment maintenance can also serve as preventive measures [29]. A simple traffic-control process is thought to decrease the dust if trucks enter the loading area at least 20 to 30 s apart [31]. Despite their practicality, these examples only mitigate the problem rather than solving it. In this sense, the main objective of this scoping review was to determine in which circumstances dust exposure occurs. By collecting data to answer the previous point, it may be possible to design tasks (and the exploitations themselves) in order to diminish this problem. This analysis is intended to guide the (re)formulation of strategies to improve occupational health and environmental settings [32].

Methodology
The study methodology was based on the protocol for scoping review [33] using the preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) [34] and the extension for scoping reviews [35].
The first step of the research was to identify the main databases/journals to search for information. In that sense, according to the availability of such databases and journals, the ones related to the engineering field or multidisciplinary sciences were selected: Web of Knowledge (Current Contents and Web of Science), Scopus, SAGE journals, Academic Search Ultimate, American Chemical Society, Directory of Open Access Journals (DOAJ), Elsevier (Science Direct), Emerald, INSPEC, IEEE Xplore, Taylor and Francis, and PubMed. Despite the focus of this scoping review on the extractive industry rather than the construction industry, in the latter, dust emission also constitutes one of the most common risks. Reported activities such as soil loading and transporting, excavation, and other road construction tasks [36] have common ground with the primary research objective of this scoping review. Therefore, this field was also considered in a first approach. The selected keywords to conduct the research were: "dust", "dusting", "particulate", "powder", and "crystalline silica", combined sequentially with "road construction", "earthworks", "open pit", "open cast", "quarry", "mining industry", and "extractive industry", resulting in 35 different combinations. Whenever possible, the keywords were searched in "Ti-tle+Abstract+Keywords"; other possibilities included: topic, title, or even abstract. Then, a set of exclusion criteria was applied to filter the best information in the first stage of research: (1) year: only papers published between 2015 and 2020 were considered; (2) type of document: research articles (articles, articles in press); (3) type of source: peer-reviewed journals; (4) language: English. In the second stage of research, all types of literature published prior to 2015 were considered, as proposed by the snowballing technique [37]. The eligibility criteria were applied on a study level. The authors were mainly interested in real operating conditions (field data) related to dust exposure/measurements in three different settings: road construction, earthworks, and open-pit mining. This research and the first screening phase were conducted by one researcher and confirmed by the second researcher. All of the extracted data were analysed by three independent researchers and confirmed by a fourth.
The primary information from each study was extracted [33]: author (and year of publication), study objective, activity, exploited material (whenever applicable), analysed substance, period (of the experiment), ethical committee, informed consent, population, sample, age, sex, control group, (used) standards, duration of the occupational exposure, source of exposure, methodology, measuring equipment, equipment calibration, sampling time, questionnaire, validation, reported symptoms, results, and limitations. However, due to the variability of information, it was impossible to cross examine the collected data. The reported measurements were classified according to the available data (study variables and experimental protocols) and gathered in form sheets. Analysis of the information was carried out at the study level.
The PRISMA guidelines include a section related to risk of bias [34]. Bias can refer to any error introduced in research that may result in misleading results. The risk of bias within studies was assessed with one of three possible classifications [38]: "high risk": the parameter has a significant effect on the results; "low risk": the parameter does not have a significant impact on the results; "unclear risk": it is not possible to characterise the effect of the parameter on the obtained results. The analysed parameters were included in tableform in two categories: methodology and other. Methodology included task definition, equipment type and standard application, measurement precision, sampling time, sample representativeness, and equipment calibration; in the other category included reporting quality and reference quality.
The first research step was carried out between July and October 2020 and updated in October 2021.

Results
From the 8993 records found in the identification phase of the PRISMA methodology [39], 4923 were excluded after applying the first exclusion criterion (article published before 2015), 896 were removed due to document type (only research articles were considered), 26 were excluded due to source type (only peer-reviewed journal articles were considered), 161 were removed due to language (only papers written in English were included), and 2776 were excluded for being off-topic (in light of the objectives proposed by this scoping review). Additionally, 160 duplicated records were removed. A total of 51 studies were assessed for eligibility, excluding 35 records that did not provide rationale nor measurements of dust levels in any of the considered settings. From the same analysis, six additional records were identified as new sources of information. During the research update in October 2021, two more papers were added to the study. A total of 24 papers were included in this study. The summary can be found in Figure 1. The PRISMA guidelines include a section related to risk of bias [34]. Bias can refer to any error introduced in research that may result in misleading results. The risk of bias within studies was assessed with one of three possible classifications [38]: "high risk": the parameter has a significant effect on the results; "low risk": the parameter does not have a significant impact on the results; "unclear risk": it is not possible to characterise the effect of the parameter on the obtained results. The analysed parameters were included in tableform in two categories: methodology and other. Methodology included task definition, equipment type and standard application, measurement precision, sampling time, sample representativeness, and equipment calibration; in the other category included reporting quality and reference quality.
The first research step was carried out between July and October 2020 and updated in October 2021.

Results
From the 8993 records found in the identification phase of the PRISMA methodology [39], 4923 were excluded after applying the first exclusion criterion (article published before 2015), 896 were removed due to document type (only research articles were considered), 26 were excluded due to source type (only peer-reviewed journal articles were considered), 161 were removed due to language (only papers written in English were included), and 2776 were excluded for being off-topic (in light of the objectives proposed by this scoping review). Additionally, 160 duplicated records were removed. A total of 51 studies were assessed for eligibility, excluding 35 records that did not provide rationale nor measurements of dust levels in any of the considered settings. From the same analysis, six additional records were identified as new sources of information. During the research update in October 2021, two more papers were added to the study. A total of 24 papers were included in this study. The summary can be found in Figure 1. Using VOSviewer [40], it was possible to identify five clusters for the most used terms in the set of included papers and the relations between them (Figure 2). Cluster 1: assessment, particulate, PM10, range, workplace; cluster 2: concentration, distance, drilling, quarry, source; cluster 3: dust, exposure, haul truck, respirable dust, worker; cluster 4: depth, pit, time; and cluster 5: dust concentration, sample. Using VOSviewer [40], it was possible to identify five clusters for the most used terms in the set of included papers and the relations between them (Figure 2). Cluster 1: assessment, particulate, PM 10 , range, workplace; cluster 2: concentration, distance, drilling, quarry, source; cluster 3: dust, exposure, haul truck, respirable dust, worker; cluster 4: depth, pit, time; and cluster 5: dust concentration, sample. As previously, articles were classified according to their research variables, where there was significant heterogeneity, as well methodologies used for data collection. Additionally, country of origin, dust-exposure-limit value (sought for in international norms whenever (frequently) it was not provided on the paper), activity, location type, and exploited material were also considered. It is important to not that, concerning "dust exposure limit", the difference in results is due to classification. For instance, the value provided for Finland is related to occupational exposure to respirable silica dust, whereas for Taiwan, it is related to total suspended particles for a daily standard. This information is summarised in Table 1. As previously, articles were classified according to their research variables, where there was significant heterogeneity, as well methodologies used for data collection. Additionally, country of origin, dust-exposure-limit value (sought for in international norms whenever (frequently) it was not provided on the paper), activity, location type, and exploited material were also considered. It is important to not that, concerning "dust exposure limit", the difference in results is due to classification. For instance, the value provided for Finland is related to occupational exposure to respirable silica dust, whereas for Taiwan, it is related to total suspended particles for a daily standard. This information is summarised in Table 1.
Regarding "studied variables", most were inferred from the experimental protocol of each article's methodology, as each study's outcome was not solidly related to the variable itself. Therefore, each study was classified into one (or more) of the following categories: • Job-related variables: activity, job category, site; • Engineering variables: equipment, transport system; • Technical variables: distance; • Physical variables: season, weather.
Tables with the extracted data from each of the studies can be found in the Appendix A, divided into three parts: (1) paper-related data, general information, and people-related data ( Table 1); (2) occupational exposure ( Table 2); and (3) prevalence and main findings (Table 3).

Discussion
The analysis provided by VOSViewer [40] showed that the controlled terms related to the papers were grouped in five clusters that, with various links between them. All of the identified clusters were related to the research objective and selected terms, although some keywords reflected the articles' specific scope. Interestingly, two of the cluster concepts were "drilling" and "haul truck", specific situations within the research results.
However, contrary to initial expectations, it was impossible to find a common approach among the reviewed studies, considering the quality and evidence criteria placed in their selection. The difference between the variables and approaches used by the working groups made it impossible to achieve a coherent and integrative view of the research carried out in this area. However, a positive aspect is that it was possible to identify a set of relevant work that allowed for the identification of critical areas where it is essential to deepen the research in order to complement and confirm the obtained results.
Thus, our analysis will be carried out topic by topic, considering the collected data and their classification according to the variables presented in Table 1. The discussion will be oriented towards analysis, considering: job-related variables, engineering variables, technical variables, and physical variables.

Activity
Among all the eligible papers, nine collected dust samples concerning activities, which are described in Table 2 [6,25,41,43,45,46,50,52,53]. In Table 3, results are presented with their respective units [41,50,52,53]. Activities such as drilling [41,53], blasting, loading, shovelling, and transportation [53] were stressed tasks leading to high dust concentrations. However, spraying with water, which is present, for instance, in some drilling systems, also did not prove to be significantly more effective when compared to other solutions [41]. Transfer ore from belt conveyor 1 to pipe conveyor (PD2) Only one study reported dust-concentration measurements for an eight-hour period, therefore comparable with the standards [53], with every value below the permissible limit (3 mg·m −3 in India, where it took place). However, the authors note that the experimental protocol was applied right after the rainy season, affecting the measurements. Nonetheless, the influence area of the transfer point between the crusher's discharge belt and another belt (AD10) presents 75% of the permissible limit.
Overall, rock cutting/crushing operations are generally a dry process and generate large amounts of respirable dust [30,47]. In crushing operations, tertiary crushing generates twice the amount of particles as secondary crushing [24]. Focusing mainly on respirable crystalline silica, it was possible to conclude that the combination of secondary and tertiary crushing plants leads to higher concentrations of this substance [46]. On the other hand, this dust concentration can be lower during milling, as this process is usually wet [47]. Comparing crushing and drilling, the former produces more coarse particles than the latter [8].

Job Category
The relationship between worker job and dust exposure was referred to in four studies [30,32,47,50].
In one of the studies, independent of the mining sector (mining, crushing, concentrating, pelletising, shop mobile, shop stationery, and office/control room), the maintenance technician was the worker associated with higher exposure to dust [47]. This conclusion was found across the analysed mines due to the similarity in mining and processing of taconite.
However, the general results show that workers performing activities directly related to dust generation, such as (manual) drill operators [32] and the quality controllers (of the holes, in blasting) [50], were the ones showing higher exposure to dust. On the contrary, the measures taken of truck operators, excavator operators, and dozer operators, besides not being statistically different, showed that working inside cabins with air-conditioning systems decreases exposure to dust [50]. Despite the fact that this relation was not directly assessed, one of the studies reported that workers engaged in crushing activities, loading crushed material and drilling, are more vulnerable to such exposure [55].
Other authors analysed jobs in different mining operations, organising the results according to increasing particle-size exposure. Machine-operator exposure occurs with particle sizes between 2 and 3 µm; drill operator, dozer operator, and shovel operator between, 4 and 5 µm; and cable man, between 7 and 8 µm. These professions report exposure to particles with an average size below 10 µm.
Processes involving cutting rock generate many fine particles, which usually leads to higher dust-exposure values. In this study, more than 50% of the total samples above the maximum exposure limit contained particles of less than 5 µm. This issue is of particular concern since it is evidenced in the literature that sizes of this order of magnitude are potentially the leading cause of numerous lung-related chronic diseases [47].

Site
Eight selected studies analysed specific-site (location) dust concentrations [6,41,42,45,48,[54][55][56]. Drilling is one of the most hazardous activities when considering exposure to dust [41]. The face of operation was found to have measurements with higher particle concentrations. Additionally, coal-handling plants and stockyards were also referred to as critical locations. Regardless of particle type (measured respirable dust concentration or total dust concentration), extraction site and crusher section are two sites with higher dust levels in the long run. In contrast, in administration offices, the results show the most negligible dust content [42]. This is in line with the observations from other studies [48].
Particle travel time was evaluated in one of the reviewed field studies [45]. Its results showed that it takes nearly one hour for a particle to travel from a depth of 168 m to the pit surface and that this happens independent of particle size. However, when an open-pit mine is exploited at more shallow depths, the travelling time between benches (10 m apart) is only 7 min. Analysis of different scenarios (in more than one mine) led the authors to conclude that mine geometry is essential when reflecting upon occupational exposure parameters. The same study also showed that the dust concentration was higher at the source of exposure and decreased in every direction.
Additionally, and with relation to particle size, the results point out that alveoli particle matter disperses more quickly than larger particles (thoracic and inhalable). Only 9 to 30% of alveolic particles settle within a (vertical) distance of between 18 m and 20 m, compared to 19% to 37% of thoracic and 23% to 39% of inhalable particles. Another study concluded that smaller particles can travel great distances, even affecting the populations in the vicinity of mines [55].

Equipment
Only three studies referred to a link between dust concentration and equipment [43,46,54]. Few pieces of equipment were mentioned in the studies, but some conclusions could be drawn from analysis of the available data. Trucks travelling along unpaved roads are related to high dust concentrations [43]. The same study remarked that rollers generate mostly coarse particles as a dust source.
The crusher is also one of the most frequently mentioned pieces of equipment when analysing dust concentrations, especially in plants that combined secondary and tertiary crushing (usually using hydrocone cyclone crushers) [46]. Table 4 shows the results of excavators and front-end loader activities, expressed in mg·m −3 [54]. Operating conditions also impact exposure values, and these differences are verifiable for both inhalable and respirable dust.

Transport System
Only one study analysed the possible relationship between transport system and dust concentration [28]. It was developed considering two types of transporting system: vertical wall and conventional (steps) in a limestone quarry. The main results showed that the vertical wall, a closed system, prevented most fine particles from spreading. On the contrary, in the conventional method, the dust concentration was higher (see Table 5, expressed in µm·m −3 ). It is essential to state that these results may not be time-weighted averages, as there was no information available concerning time frame. Table 5. Relation between transport system and dust concentration [28].

Technical Variables Distance
In general, there is a relationship between distance and total dust concentration [28]. As expected, the results showed that the overall dust concentration decreased with increasing distance from the source. According to two studies, this is also particularly true in relation to activities such as crushing [8,44]. Some authors reported that with increased distance from the exposure source, dust concentration decreased by about 89% [44]. In particular, dust concentration from drilling activities spreads up to 80-100 m from the source, where the heavier fractions of dust settle [44]. For this reason, some authors suggest that the proportion of fine dust tends to increase with increasing distance from the source [49], as PM 10 can travel up to 100 km (or more) and stay in the atmosphere for days, whereas PM 2.5 can travel as far as thousands of kilometres, staying in the air for weeks. Coarse particulates usually deposit quickly and within short distances of the source [3].

Season
Only two studies made reference to season when assessing dust exposure [6,28], with interesting conclusions.
In one of the studies, it is reported that in the hotter seasons (spring and summer), particles are shorter due to low air humidity, as opposed to during the colder seasons (autumn and winter). This happens because the increased moisture causes suspended matter to forming larger particles. The maximum dust concentration was achieved during summer (hourly concentrations of 1100 µg·m −3 ) [28], falling outside of the average concentration range of 600-820 µm·m −3 . Conversely, other studies observed that both PM 2.5 and PM 10 concentrations were higher during winter [6]. However, this was attributable, according to the authors, to the prevalence of anticyclonic conditions.
The influence of season is, for obvious reasons, related to weather conditions, which will be discussed in the following section.

Weather
Dust concentration related to weather was referred to in two studies [28,44]. Dust concentration has an almost linear relation with wind speed at a measurement point at 300 m from the extraction outline [28]. Additionally, it was verified that the aerosol concentration increased with increasing wind speed, despite decreasing with increased humidity. This latter fact occurs due increasing particle size (as a result of combination with water), leading to easier deposition. The other study mentioned that dust concentrates the downwind, and upwind of the source, there is no significant dust concentration [44]. Interestingly, it was reported that particles moving in the downward direction (within the pit) take longer to escape from the zone, which increases the duration exposure to dust, meaning that attention should be paid to the behaviour of particles [45]. It is also stated that villages in downwind locations can suffer from traveling particles [55].

Other Variables
Interestingly, one study reported and analysed workers' respiratory symptoms, and 49.1% of total workers were found suffered from phlegm, 42.9% from breathlessness, and 37.5% from a cough. Despite the fact that exposure to dust remained below the maximum exposure value, these workers showed a high prevalence of respiratory symptoms [50].
The relationship between dust exposure and other variables, such as air humidity or wind velocity, is complex and cannot be summarised in this analysis, our analysis was carried out case by case, and the relationship itself is not entirely clear. Despite gathering data regarding weather parameters, could be proposed. However, the risk of exposure depends on, among other factors, the characteristics of the dust, activity, duration of exposure, characteristics of workers, and use of personal protective equipment [46,54]. Notwithstanding the results, particular attention should be continuously paid to this issue because exposure, in the long term, may impair the health of workers [53].

Bias
Risk of bias [38] (Table 6) was assessed at the study level. Papers were analysed according to methodology (task definition, equipment type, standard application, measurement precision, sampling time, sample representativeness, and equipment calibration), and other factors (reporting quality and reference quality). The possibility of each parameter having impacted on the outcome, therefore representing some type of bias, was determined using one of the classifications [38]: "high risk", "low risk", and "unclear risk". Notwithstanding that the experimental protocols were well-defined, primarily regarding task definition, no information about equipment calibration or measurement precision was provided. It is important to note that this assessment is subjective and depends on the information reported in each study. Whenever the required piece of information is clearly stated in the text, the classification is more or less direct, according to the suitability of its methods (for instance, if the used equipment was appropriate for the study's needs). In cases of no information, it is not possible to infer a relationship. When the methodology is not appropriate or the results (obtained by the studies) do not align with the methodology, risk of bias is elevated. With the exception of equipment type, every other variable in the Methodology section demonstrates the necessity of improving reporting quality concerning the applied experimental protocols.

Study Limitations
One of the main limitations of this study is that the collected data could not be compared due to a lack of specificity of the studies concerning aims, applied protocol, and presentation of results. This led to a paper-by-paper analysis that does not provide a general view on the topic, making it difficult to standardise design solutions. The idea of using a common standardised protocol is stressed in the literature [57]. Additionally, it was not possible to infer whether the culture of each country influenced practices. For instance, it is mentioned in one of the studies that although remaining below the national standard, the dust exposure was way above international standards [41]. Uncertainties related to exposure assessment may influence risk-management practices, which may, in turn, negatively impact the health of workers [58]. Overall, it was impossible to determine the extent to which the results of the reviewed studies truly represent real-life working conditions. Therefore, this scoping review mainly supports the need to apply or develop standardised protocols concerning information, such as that reflected in Table 6.

Conclusions
Air pollution is a growing issue worldwide, and dust emission from anthropogenic activities affects not only directly exposed workers but also surrounding communities [1]. Dust is produced in almost every mining activity and similar tasks, such as road construction and earthmoving tasks [16]. Common dust-control strategies include spraying water, although other mechanisms are starting to be developed, such as ultrasonic suppression systems [30]. Despite significant downward trends in exposure to respirable quartz and respirable silica, according to a recent assessment [59], deaths associated with this issue still occur, with a special focus on pneumoconiosis [60]. Some authors suggest that highrisk workers need training in use of personal protective equipment and that dust-control mechanisms are still far from what they need to be [30]. The aim of this scoping review was to determine the specific circumstances under which exposure to dust occurs within the context of open-pit mining and quarrying, including research from other fields with similar tasks, such as road construction and earthworks and identifying measures to mitigate or even eliminate dust production. Within the reviewed studies, it was possible to identify the following variables related to dust exposure: job-related (activity, job category, and site), engineering (equipment, transport system), technical (distance), and physical (season and weather) variables. However, the significant variance in protocol settings made it difficult to perform any general analysis, resulting in a study-by-study approach. Despite this, data were grouped by assessed variable (whenever possible). Results showed that drilling was often pointed to as a task leading to higher levels of dust exposure [41,53], although every activity related to rock processing (blasting and loading, for instance) also had a positive association with high dust levels [53]. Workers performing their job inside climatised vehicles experienced less exposure to dust [50] than workers whose work leads directly to dust generation [32].
Notwithstanding the task, it was reported in one study that the size of the particles was below 10 µm [30]. The face of operation where most work occurs was naturally the site where the highest dust levels were measured. One study addressed particle travel time and concluded that mine geometry is an important factor reflecting occupational exposure [45]. Few types of equipment were mentioned related to dust exposure: drill, crusher, truck, excavator, and loader. Concerning this variable, the focus was on the setting; for example, trucks travelling on unpaved roads were associated with high dust levels [43]. Other specific assumptions were described but not in a way constituting data. Transport system was analysed in just one of the studies and only compared two methodologies [28]. Therefore, no general conventions can be drawn. According to the same author, dust concentration decreased with increased distance from the source, and this was also verified in other contexts [44,49]. Season as a variable was acknowledged with relation to moisture or rain, which depend on weather and specific factors, such as wind direction and humidity. Concerning mitigating measures, none of the studies analysed potential mechanisms for solving this problem.

Practical Implications
This scoping review highlights the necessity of adopting standard procedures for data collection, independent of research objective. It is mentioned in the literature that this process is quite demanding, as it is conditioned by each specific setting, which, as a standalone condition, already makes it difficult to properly apply in the protocol [8].
Nonetheless, with the collected data, one study suggests the following steps [58]: (1) A comprehensive description of the occupational setting; (2) Analysis of the mineralogical characteristics of the hazardous agent; (3) Measurement of the exposure to respirable dust, according to international standards, in the workers' breathing zone during a full shift.
Although these steps seem achievable, they are not applied often. The same author also states that it is important to preserve historical data so that a database can be organised that can help determine more strategic actions concerning the health and safety of both workers and operations.    The study was conducted in two sites measuring approximately 30 m: a surface-stone quarry (Virginia) and a coal-preparation plant (Pennsylvania). The first had a slight grade and was the main access to the pit. The second was flat and was the main access to the waste dump. Seven monitoring stations were placed for data collection. However, only two were considered for respirable dust: one adjacent to the road and one on the opposite side of the road. All measurements were performed between 20 and 60 m downwind of the sites. Measurements were taken at a height of 4 m. Overall meteorological data were also collected, as well as trace gases (NOx, CO, SO 2 , O 3 , and CO 2 ). Total particulate polycyclic aromatic hydrocarbon (p-PAH) mass concentration was recorded. Particle size distributions were analysed by a fast-mobility particle-sizer spectrometer (FMPSS) and an optical particle counter (OPC).      The highest respirable dust concentration was measured in the extraction section (10.6 mg·m −3 ), and the lowest concentration was measured in the administration section (4.02 mg·m −3 ). The highest total dust concentration was measured in the crusher section (94.3 mg·m −3 ), and the lowest concentration was measured in the administration section (16.6 mg·m −3 ).
NM [43] NA NA NA NA Emission factors for PM 10 were related to earthworks and plate-compactor under dry weather conditions. Comparing emissions under dry and wet weather conditions before and after wetting the ground showed that dust can be reduced to a significant degree.
NM [44] NA NA NA NA Measured dust concentrations were between 693 ug·m −3 and 126 ug·m −3 . It was confirmed that dust spread up to 80-100 m from the source.
NM [45] NA NA NA NA No relation was found between PM concentration and wind speed. The inhalable fraction of PM varied in the range of 37-52%. The fraction of thoracic PM was between 31-36%, and alveoli PM was between 17-29%. The results showed that the average PM concentrations in mining sites were 1.2-2 times the concentrations at residential sites. PM peak concentrations were observed during peak production time. Results show that there are considerable differences in particle size and composition between locations. In the working fronts, there are chemical elements, such as Nb, Th, Cr, Sr, Li, As, Pb, Cu, Zr and Ni, mostly attributed to mining machinery, tyre and brake-wear emissions, and deposition of dust emitted from gangue working zones. NM NM: not Mentioned; NA: not applicable.