There are two sources of PM emission in mines, viz. Primary and Secondary. The primary sources include: 1) drilling and blasting, where air blast and blast intensity are the main mechanisms of emission; 2) crushing sites and associated processes, where impacts, dropping of materials from a specified altitude, and abrasion are the major mechanisms of emission [28][29]. The secondary sources include: 1) conveying sites, where dropping of materials from a specified altitude is the mechanism of emission [30][31]; 2) haulage roads, where raise, exhaust, tyres, and cooling fans of dumpers are the main mechanisms of emission [30][32][33]; and 3) stock piles, where the mechanisms of emission are caused by wind speed and wind blow.

In an attempt to assess the environmental impact of iron ore mining, two different iron ore mining regions were selected. The first one is the Barsua-Tensa Area (BTA), and the second is Koira Township, both of which are situated in the Keonjhar and Sundergarh Districts of Odisha, India.

The study area contains 73 mines in total. Of these, 23 were active during the study period mining iron and manganese ores on a large scale. Iron ore being mined in the regions serves as a major source of raw materials for steel plants within and outside of Odisha State. Some of these steel plants include Rourkela Steel Plant (RSP), Tata Steel Ltd (TSL), Jindal Steel and Power Ltd (JSPL), etc. The study zone can be found within the space of latitude 21˚52'48'' and 21˚53'58''N and longitude 85˚08'37'' and 85˚17'22''E. The map of the study area is presented in Figure 1.

To increase reproducibility and openness, the sampling framework has been made clearer. Due to low moisture levels, particulate emissions from mining and haul-road operations are usually at their highest during the dry season (pre-monsoon period), when ambient air monitoring was carried out. Each of the ten monitoring stations was sampled several times throughout the course of a continuous 15-day period. Using established procedures, paired PM₁₀ and PM_2.5 samples were obtained concurrently at each site for eight hours during each sampling event. As a result, each site had several observations, which increased the dataset’s dependability and made it possible to evaluate short-term variability.

Figure 1. Map of the study area showing all sampling stations (D1 - D10).

The ten sampling locations were chosen and dispersed geographically according to the mining corridor’s population exposure, land-use features, and emission intensity. Due to its high density of operating mines, processing facilities, and significant haul-road junctions, Tensa represents the operational center of the mining activity and was given five sampling locations. Because Koira is a major residential and transportation hub with substantial vehicle traffic and human exposure, it was given four sites. In order to depict background and transitional conditions, one site was used to represent Barsua, which has comparatively less mining activity within the township boundaries and functions more as a peripheral zone. Thus, a gradient of mining intensity and exposure risk along the corridor is reflected in the combined distribution of 1 (Barsua), 5 (Tensa), and 4 (Koira), guaranteeing that the sampling strategy appropriately represents both source-dominated and receptor-sensitive situations. Along the mining corridor, this distribution as a whole offers a fair depiction of upstream, midstream, and downstream impacts.

Air Quality Monitoring (AQM) was carried out in the mining townships of Barsua, Tensa, and Koira, inhabited by miners and locals. From the studies, PM₁₀ and PM_2.5 were sampled at ten different locations, one set (PM₁₀ & PM_2.5) from Barsua, five sets from Tensa, and four sets from Koira townships with the help of Respirable Dust Samplers, Model: Envirotech APM 460 NL, and Fine Particulate Samplers (Model: Envirotech APM 550). At each sampling station, PM₁₀ and PM_2.5 were gathered simultaneously, sampling 2 locations at a time using 4 samplers to optimize the sampling process (two PM₁₀ and two PM_2.5 samplers). Respirable Dust Samplers (Model: Envirotech APM 460 NL) were used to collect PM₁₀ samples, while Fine Particulate Samplers (Model: Envirotech APM 550) were used to collect PM_2.5 samples. PM_2.5 samplers were manually operated (non-programmable), while the PM₁₀ samplers were operated by means of programming on an 8-hourly basis. The maximum sampling time for both samplers (PM₁₀ and PM_2.5), as per manufacturer prescription, is 24 hours, while the minimum sampling time is 8 hrs. Whatman GFA 8" × 10" filter paper was used for gathering PM₁₀ while the Teflon filter papers were used to gather PM_2.5 samples.

The National Ambient Air Quality Standards (NAAQS) particulate matter limitations were directly compared to the 8-hour average PM concentrations recorded at each location. Rather than offering a complete compliance judgment, these comparisons are clearly given as screening-level assessments meant to show whether detected concentrations approach or surpass regulatory criteria.

The U.S. EPA’s AirNow calculator was utilized to convert measured values into Air Quality Index (AQI) categories. Because it offers a clear, well-known conversion framework and enables uniform interpretation of pollutant concentrations in terms of public health importance, this tool was chosen. The AirNow/US EPA calculator uses a standardized breakpoint approach that is generally equivalent to other AQI frameworks, which justifies its use as a screening tool even though the study region is in India. One AQI framework (AirNow/US EPA) has been used consistently throughout the article to prevent confusion, and this justification is now made clear.

PM₁₀ filters were used in the field to collect all suspended particles for particulate sampling. A size-selective extraction procedure was then used in the lab to separate the fine fraction (PM_2.5) from these filters. In order to ensure that the data represent the subset most pertinent to human exposure and atmospheric transport, this PM_2.5 fraction was further subjected to chemical digestion and analysis.

Six sites (D4, D5, D7, D8, D9, and D10) were selected for chemical analysis out of the ten monitoring locations due to their high PM concentrations, AQI classifications (which range from “Unhealthy” to “Extremely Hazardous”), and proximity to sensitive receptors like residential areas, schools, transportation hubs, and medical facilities. This targeted selection approach was used to ensure spatial representation throughout the most affected areas of the mining corridor while concentrating on high-exposure zones where possible health hazards are highest.

The PM₁₀ sampler is a rectangular, wheeled device with an internal pump mechanism and an inlet pipe, as seen in Figure 2(a). It gathers ambient air’s respirable particulate matter (≤10 µm), mostly coarse dust produced by environmental and mechanical processes. This study made use of it. The cyclone separation concept utilized in PM₁₀ measurements was also applied inFigure 2(b). The cyclone assembly uses centrifugal force to remove bigger particles when ambient air enters through the inlet. While finer particles go via a filter and gasket before the cleaned air exits to the suction mechanism, these particles are gathered in the sample bottle. The diagram illustrates a two-step procedure that ensures efficient collection of respirable dust: mechanical separation and filtration.

Furthermore, the PM_2.5 sampler (Figure 2(c)) is a rectangular apparatus with an intake assembly intended to specifically collect tiny particulate matter (≤2.5 µm), which presents serious health risks because of deep lung penetration. Its front panel shows an oilless vacuum pump for continuous air intake and filtering, while its enclosure displays tubing, filters, and a chamber. This device, which focuses on health-relevant tiny particles, is frequently used in pollution studies and air quality monitoring.

Figure 2. (a) & (b): PM₁₀ sampler and schematic diagram; (c): PM_2.5 sampler.

Standard procedures (IS: 5182, Part 4, 6 & 23) were adopted for the studies. Prior to field sampling, the filter papers were equilibrated by exposing them in an airtight desiccator containing active desiccant, temperature controlled (15˚C - 27˚C) and relative humidity of 0% - 50% for 24 hrs. After equilibration, the initial weight (Wi) of all filters (Whatman & Teflon) was recorded using an analytical balance and given unique identification numbers, retained in filter holders, and properly sealed to prevent contact with moisture. All samples were collected for 8 hrs at a constant air flow rate in an interval of 1.0 to 1.2 m³/min, respectively. After sampling, the samples were carefully placed in filter holders, sealed tightly to prevent the escape of particles, and transported to the Environmental Engineering Laboratory of the Mining Engineering Department, National Institute of Technology, Rourkela (NITR), for gravimetric analysis. After the filter papers were gravimetrically analysed, they were preserved for mineralogical characterization of PM sampled.

3.2.1. Procedures for Quality Assurance and Control (QA/QC)

To guarantee data accuracy and dependability, quality assurance and control (QA/QC) protocols were used for both ICP-MS analysis and particulate matter (PM) sampling. In order to preserve flow rate accuracy within ±5% of the intended range for PM measurements, all samplers (Envirotech APM 460 NL and APM 550) were calibrated using a standard flow calibrator both before and throughout the sampling session. Leak checks were performed both before and after sampling, and flow rates were noted in order to calculate average volumetric flow. In order to account for background contamination, field blanks and laboratory blanks—unused filter papers that underwent the same handling and conditioning—were examined, and blank corrections were made as needed. To evaluate measurement precision, duplicate (replicate) sampling was conducted at certain locations, with acceptable variability kept under ±10%. Gravimetric measurements were carried out using a calibrated analytical balance with the proper sensitivity, and filters were equilibrated under regulated temperature and humidity conditions both before and after sampling to reduce weighing errors.

Reagent blanks, method blanks, and certified reference materials (CRMs) were used in QA/QC procedures for ICP-MS analysis in order to confirm analytical accuracy. Multi-element standard solutions with appropriate correlation coefficients (R² ≥ 0.999) were used to create calibration curves. Drift adjustments were made as needed, and the calibration of the instrument was regularly confirmed using calibration check standards. To guarantee analytical precision, duplicate analyses of digested samples were carried out, usually within ±5% - 10% relative standard deviation. Only concentrations above detection limits were reported, and method detection limits (MDLs) for trace elements were established using standard techniques (e.g., three times the standard deviation of blanks). Consistent replication measurements, acceptable recovery rates for CRMs (usually 85% - 115%), and appropriate blank values were among the requirements for data acceptance. To preserve overall data integrity, any data that did not fit these requirements were either reanalyzed or eliminated.

3.2.2. Basis of Trace-Metal Concentration Reporting

The digestate concentrations (mg/L) obtained from the microwave-assisted acid digestion of PM₁₀-loaded filter sheets and dilution of the extracts to a fixed volume (100 mL) before ICP-MS analysis are used to express the trace-metal values reported in this study. Therefore, rather than the direct mass of metals per unit volume of ambient air, the given values represent the concentration of each element in the examined solution.

Therefore, these values should not be construed as ambient atmospheric metal concentrations because they are not air-volume-normalized (e.g., µg/m³). The given trace-metal values are not standardized to the observed air volume; rather, they are raw digestion outputs (amount of metal found in the filter extract or per filter). Results must be given as air-volume-normalized values (µg/m³), which take into consideration the volume of air collected and enable comparison with standards, in order to represent ambient atmospheric concentrations. Digestate or per-filter values should be regarded as intermediate analytical results rather than exposure-relevant measures, since they merely characterize the chemical content of the sample. To put it briefly, ambient air concentrations should be measured in µg/m³; other bases cannot be easily compared to air quality standards. Rather, they show the distribution and relative abundance of constituents linked to particulate matter collected on each filter, allowing for cross-site comparison and the identification of possible emission sources. All values are air-volume-normalized concentrations (µg/m³), which are determined by dividing the total volume of air sampled through the filter by the mass of each metal measured in the digestate. In order to establish comparability with ambient air quality standards and to enable meaningful interpretation in terms of human exposure, the mass per filter obtained from the digestion step was adjusted to the observed air volume.

After 8 hrs of sampling, the filter papers from both samplers were carefully taken out and placed in their respective holders, numbered, and sealed to prevent the escape of particles. Before gravimetric investigation, the filters were placed in a desiccator (DC) for 24 hours (equilibration) to remove absorbed moisture during sampling, after which the final weight of each filter was determined using an Analytical Balance and recorded as Wf. The appearance of the filter papers before and after 8 hrs of sampling can be seen in Figure 3, and it presents the equilibration of all filter papers after field sampling by means of the desiccator.

Calculations:

The volume flow rate of air (V) for both samplers can be computed as:

where,

V = Volume of air flow sampled in m³,

Q = Average flow rate of air in m³/min, and

T = Total time of sampling in min.

The total concentration of PM_2.5 and PM₁₀ in ambient air samples was calculated by the given equation:

where,

PM_2.5 = Mass concentration of PM_2.5 in μg/m³,

PM₁₀ = Mass concentration of PM₁₀ in μg/m³,

Wi = Initial weight of filter paper in g,

Wf = Final wt. of filter paper in g,

V = Volume of air flow sampled in m³, and

10⁶ = Conversion of g to µg.

The concentration of PM₁₀ and PM_2.5 for all the sampling points was determined following the above-mentioned procedures and is presented in Table 1, while the filter papers’ appearance prior to and before the sampling of airborne particulates (PM₁₀ & PM_2.5) at a few sampling stations is shown in Figure 3, respectively. The results of PM concentrations found from each of the 10 sampling stations, corresponding air quality index (AQI) values, and associated health concerns are presented in Table 1.

(Top to bottom left—Whatman GFA 8'' × 10'' filters, for PM₁₀); Top to bottom, right—Teflon filters for PM_2.5. Labels on each filter denote the sampling station at which the sample was gathered.

Figure 3. Filter papers’ appearance prior to and after 8 hrs of sampling.

In order to assess the potential health impacts of particulate matter, the filter papers (PM₁₀) were subjected to mineral characterization. Prior to trace element analysis, each filter paper was acid digested using a microwave digestion procedure (US EPA Method 3052). During digestion, each filter paper was cut using scissors and placed in an acid-washed (10% HNO₃) microwave bottle according to their id. Nitric acid (HNO₃) and hydrochloric acid (HCl) were added to each sample in each vessel and sealed air-tight, in corresponding volumes of 9 ± 1 ml and 4 ± 1 ml, respectively. The vessels were then placed in the microwave digestion system and allowed to stay for 15 min at 180˚C ± 5˚C.

Table 1. Concentration found for PM (PM₁₀ and PM_2.5) after 8 hours of sampling.

Table 2. Chemical composition of particulate matter (PM).

The digested samples were filtered using Whatman filter 42 and the filtrates were diluted to 100 ml in a volumetric flask of 100 ml capacity and finally placed in a refrigerator at 4˚C for analysis. The six filtrates of the six microwave-digested filter papers were analysed using ICPMS, LSX-213. The filter papers digested were D4, D5, D7, D8, D9, & D10. The analytical results of trace elements found in the PM sampled are presented in Table 2.

The given trace-metal results should not be construed as ambient atmospheric concentrations (µg/m³) because they represent digestate concentrations (mass per filter) and have not been adjusted to the observed air volume.

The air we breathe is a mixture of gases with some measure of solid and liquid particles. Air contamination initiates in ambient air when substances are present in levels greater than their standard surrounding levels to produce quantifiable effects on humans, fauna, vegetation, resources, et cetera. Air contamination has been a widely recognized issue, and it is currently a significant environmental problem worldwide. In India, air quality pollution has become an important topic of controversy at all levels due to increased anthropogenic activities, especially the burning of coal, natural gas, fossil fuels, industrial activities, mining, and related activities, etc. These activities release a wide range of air pollutants, viz. CO, NOx, VOCs, PM, and SO₂, etc. [34]. Mining operations create significant amounts of airborne respirable particulate matter because of the nature of operations, which causes pulmonary diseases in miners. The increasing trend of opencast mining to meet the ever-growing demands of the public leads to the release of a tremendous amount of dust [35][36]. These airborne dust particles or PM, normally below 100 microns in size, are natural nuisances and the main cause of health hazards. The systematic results of PM₁₀, PM_2.5 along with their standards have been presented in Figure 4.

It could be seen that PM_2.5 levels of samples D1 - D4 and D10 were below the Central Pollution Control Board Standards of 60 μg/m³. In any case, PM_2.5 levels for D5 - D9 were observed to be far above the CPCB standard, with D5 having the highest estimation of 148.68 μg/m³. The PM₁₀ concentration at all stations sampled was above the acceptable limits of the National Ambient Air Quality Standard (NAAQS) of CPCB.

Figure 4. Graphical display of PM_2.5 (left) and PM₁₀ (right) vs. NAAQS values.

The main sources of air pollution (PM₁₀ and PM_2.5) generation in the study area, as per field observation for 15 days in the study area coupled with sampling results, are haul roads. It was observed that over 1500 dumpers from more than 20 active iron and manganese mines transport run of mines and concentrates along the Koira-Tensa and Tensa-Barsua road networks on a 24-hourly basis. It is commendable to note that these pollutants (PM₁₀ & PM_2.5) are mostly engendered from 6:00 pm to 6:00 am. During these hours, the Tensa-Barsua and Tensa-Koira roads, as well as Koira Township, get heavily trafficked with dumpers loaded with concentrates and run of mines from all locations. Figure 5 presents dumpers’ traffic along the Tensa road network during loading.

Figure 5. Queuing of dumpers during loading operations in Tensa.

Chemical analysis of 6 out of 10 filter papers investigated from delicate regions such as the health centre (D7), school zones (D4 & D10), bus station (D5), and inhabited areas (D8 & D9) displayed elevated levels in descending order as Ba, Al, Fe, Zn, Mn, Cr, Ni, Se, Co, As, Cd, Hg, and Pb. The cations were among the predominant constituents in descending order as K, Na, Ca, and Mg. Ni. Considering the constituents of airborne particulates sampled, miners and inhabitants of the study area are at risk of suffering from respiratory health hazards or diseases.

The first figure (Figure 6(a)) demonstrates that Fe is the predominant element, with concentrations reaching a strong peak at station D5 (~160 mg/L). Na, Al, and K, on the other hand, show moderate but variable values throughout the sampling locations. Mg and Mn, on the other hand, are continuously low. With Fe dominance closely associated with iron-bearing geology and mining activity in the corridor, this variability points to limited mineralogical inputs.

The second figure (Figure 6(b)), peaks at station D10 (~0.32 mg/L), showing Cr as the element with the highest concentration. While As is generally low, below 0.1 mg/L, Ni exhibits substantial, varied amounts among the stations. While Ni and As are only present at negligible levels, the increased Cr levels at D10 indicate lithological enrichment or localized contamination.

The two locations differ significantly, according to the mineralogical characterization. Strong Fe dominance is seen in Tensa stations (D4 - D7), which is compatible with iron-rich geology. Koira stations (D8 - D10), on the other hand, have distinct Cr enrichment, especially at D10, suggesting distinct mineralogical origins. The impact of the mining corridor and the possibility of airborne particulate contamination are highlighted by elevated Fe and Cr values. Because of their possible effects on health, trace metals like Ni, As, and Mn are nevertheless important for toxicological evaluation even though their concentrations are still low.

(a) (b)

Figure 6. (a) & (b): Mineralogical characterization plot of PM vs. sampling stations in Tensa and Koira.

The AQI is a guide developed by the USEPA for reporting daily air quality in an area. It tells one how clean or unhealthy the ambient air is, and what associated health effects might be a concern as the index value increases. The AQI focuses on health effects a person may experience within a few hours or days after exposure (breathing) to unhealthy air. The AQI is normally calculated for four major air pollutants that are regulated by the Clean Air Act in the United States of America (USA) viz. particle pollution, ground-level ozone, sulfur dioxide, and carbon monoxide. Thus, to protect public health, the EPA has established National Air Quality Standards (NAQS) for each pollutant mentioned above. In this research, AQI has been determined for airborne particulates (particle pollution) only.

The AQI is a measurement that runs from 0 to 500. The higher the AQI value, the greater the concentration of air pollution and health concern in the area. For instance, an AQI value of 50 signifies good air quality with minimal or no potential to negatively impact public health, while a value of 300 means the air quality is hazardous, and that any exposure may result in serious health effects. An AQI value of 100 normally parallels the national air quality standard for the pollutant, which is the concentration set by the EPA to protect public health. Therefore, AQI values at 100 or below are generally accepted to be satisfactory. When AQI values exceed 100, the air quality is considered to be unhealthy, initially for certain sensitive groups of people, then for everyone as AQI values increase.

The purpose of the AQI is to help people understand what the local air quality means for their health. To make it easier to understand, the AQI is divided into six levels of health concern, as presented in Table 3.

Table 3. The six levels of health concern into which the AQI is divided.

The Air Quality Index (AQI) values for both PM₁₀ and PM_2.5 sampled were determined using the AirNow AQI Calculator on AirNow Web site developed by USEPA and its federal, tribal, state, and local partners (available at: http://www.airnow.gov/). AQI values were determined by entering the concentration found from each sampling station into the AirNow App and clicking the calculate option on the right. The result for PM₁₀ revealed values as follows: D1 and D2: 78—moderately contaminated; D3: 104—undesirable; D4: 158—unhealthy; D5: out of reach (>500)—exceedingly hazardous; D6: 315—hazardous; D7: 491—hazardous; D8: out of reach (>500)—exceedingly hazardous; D9: 221—exceptionally unhealthy; and D10: out of reach (>500)—extremely hazardous. Also, the index values found for PM_2.5 were D1: 113—undesirable for sensitive groups; D2: 137—undesirable; D3: 176—unhealthy; D4: 150—undesirable for sensitive groups; D5: 199, D6: 168, D7: 174, D8: 167; D9: 194—unhealthy; and D10: 134—undesirable for sensitive groups.

From the viewpoint of air quality studies conducted in KJMA, it is appropriate to say that the air quality in Koira Townships, Tensa, and Barsua has been highly degraded with PM₁₀ and PM_2.5 on a daily basis. Results from the studies demonstrated that PM₁₀ levels are far beyond the affirmed limits according to NAAQS at all the sampling sites. Essentially, PM_2.5 was observed to be high in several areas studied. The Air Quality Index (AQI) for PM₁₀ displayed results ranging from moderately contaminated—D1 and D2; undesirable—D3; unhealthy—D4; exceptionally unhealthy—D9; hazardous—D6, D7; to extremely hazardous—D5, D8, and D10. Similarly, the index values found for PM_2.5 displayed results ranging from undesirable for sensitive groups—D1, D4, D10; undesirable—D2; unhealthy—D5, D6, D7, D8, D9, respectively. Additionally, significant concentrations of some metals and heavy metals were found using ICP-MS analysis, which revealed significant amounts of chemical constituents, some of which are hazardous to human wellbeing. Continuous exposure to this environment could give rise to prolonged respiratory illnesses such as silicosis, siderosis or welder’s lung, damage to the heart and liver, and may catalyze radicals that are injurious to biological molecules, cells, tissues, and organisms. Thus, candid preventive and/or mitigation measures ought to be taken by the mine to reduce the levels of pollutants emanating from mining-related activities below acceptable or permissible threshold values or limits. The prime sources of PM discharge in the mining area and adjoining environment—Barsua, Tensa, and Koira—are the haul road networks used by more than 1500 dumpers during transportation of concentrates of iron ore, bauxite, manganese ore, etc., from the processing plant to train stations for shipment to steel plants.

From field observation and studies conducted, Koira Township is by far the most polluted with airborne particulates (PM₁₀ and PM_2.5). Ambient Air Quality Monitoring (AAQM) studies carried out during morning and evening hours in the study area revealed that PM emission during the evening hours (5:00 pm to 6:00 am) is 10 times higher than those of the morning hours (7:00 am to 4:00 pm). This is due to the restriction on dumper movement during the morning hours; over 23 active mines in the studied area transport ore concentrate from 5:00 pm to 6:00 am, while dumpers are seen in a queue for loading from 7:00 am to 4:00 pm. Dumpers seen plying the road in the area are actually loaded with run of mines (ROM) from the production sites of mines to mineral processing plants for processing.

The presence of both primary and secondary forests in the study area, coupled with residential trees, helps to reduce PM levels before they reach sensitive zones. However, the magnitude of PM generation due to the constant stream of dumpers makes it tedious to contain PM in the area. The finer PM was observed to stay in suspension within the surrounding air for a much longer duration, traveling several kilometres from the discharge sources. As the PM emission is due to several mines’ workings, it is very difficult to effectively control the emission. Thus, collaborative effort is required from all mines and the State Pollution Control Board (SPCB) to effectively control and mitigate PM generation and concentration in the mining areas and the neighbouring environs.

The Barsua-Tensa-Koira mining corridor in Odisha has elevated PM₁₀ and PM_2.5 concentrations, dangerous AQI levels, and a metal-enriched particle burden. Therefore, the following recommendations are necessary:

Integrated dust control at haul roads and significant emission sources should be prioritized. Continuous mechanical sweeping and high-frequency water spraying using stationary and mobile mist cannons should be used along major transport corridors since haulage operations were found to be the main cause of particulate formation [2]. On unpaved roads, the use of environmentally friendly chemical dust suppressants can further lessen fine particle resuspension. To reduce turbulence-induced dust dispersion, strict enforcement of speed restrictions, controlled traffic scheduling, and staggered dumper movement are required, especially during peak nighttime operations (5:00 pm - 6:00 am) [37].Ore should be transported in covered vehicles, and dumpers should have regular maintenance to reduce exhaust and fugitive emissions. Engineering measures, including wind barriers, enclosures surrounding crushing and screening equipment, and dust extraction systems equipped with baghouse filters, should be built at operational sites. Conveyor transfer sites need to have localized suppression systems installed and sealed. Compaction, moisture conditioning, vegetative cover, and windbreak structures should be used to stabilize stockpiles, and concurrent backfilling and progressive mine reclamation should be used to reduce exposed surfaces that produce dust [38][39].It is equally important to strengthen public health protections and environmental monitoring. In order to capture peak emission trends, seasonal and diurnal monitoring should be added to the establishment of Continuous Ambient Air Quality Monitoring Stations (CAAQMS) in sensitive receptors such as schools, hospitals, and residential areas. In townships, real-time AQI display devices would improve risk communication and community awareness. Workers and high-risk residents should have access to comprehensive occupational health surveillance programs that include biomonitoring for trace metal exposure, radiographic exams, and periodic pulmonary function tests. Enforcing the use of approved respiratory protection equipment is necessary, as is adhering to exposure limits that meet both national and international requirements [24][25].Afforestation of reclaimed areas will support long-term environmental stability, and the expansion of multi-tier greenbelts utilizing native, dust-tolerant species along haul routes and mine peripheries can offer ecological buffering. Cumulative effect evaluations covering all active mines should be required by regulatory bodies, and NAAQS compliance should be strengthened. Achieving long-term reductions in particulate pollution will require coordinated governance involving mining operators, the State Pollution Control Board, and community stakeholders, along with incentives for electric or low-emission haulage fleets and emission-based fines.

Immediate and coordinated mitigation actions are necessary due to the continuously high concentrations of PM₁₀ and PM_2.5, especially in Koira Township, and the known presence of hazardous trace elements. In order to protect the environment and public health, sustainable mining operations in the area will require integrated dust management, strict monitoring, enhanced occupational health protection, and vigorous regulatory enforcement.