Assessment of the status of work zone air environment due to opencast coal mining

In India coal production will have to be increased to meat theenergy demand at a very high rate. By 2000 AD the coolproduction from opencast (O/C) mining will rise to 250 Mt. whichwill be about 70% of the total coal production. The increasing trend of O/C mining leads to cause air pollution problem. A surveywas conducted to assess the status of work zone air envirnmentdue to opencast coal mining in Jharia Coalfield. Keeping in viewof place of dust generation air quality monitoring stations wereselected. Methodology adapted for sampling and analysis of airpollutants have been described. Four season data revealed thatmaximum concentration of SPM was observed at dragline sectionand the next high concentration was at haul roads. At all thelocations SPM and RPM concentrations exceeded the permissiblelimits specified by Indian Pollution Control Board. Shift wiseand location wise analysis for getting higher concentration ofSO₂ and NO_x have been discussed. Wind velocity anddirections, mixing heights, ventilation coefficient of the areahave been analyzed. Huge dust generation creates vision problemto HEMM operators. The methodology adopted may be utilised onindustrial scale for various sites.     

Assessment of respirable dust exposures in an opencast coal mine

All major opencast mining activities produce dust. The major operations that produce dust are drilling, blasting, loading, unloading, and transporting. Dust not only deteriorates the environmental air quality in and around the mining site but also creates serious health hazards. Therefore, assessment of dust levels that arise from various opencast mining operations is required to prevent and minimize the health risks. To achieve this objective, an opencast coal mining area was selected to generate site-specific emission data and collect respirable dust measurement samples. The study covered various mining activities in different locations including overburden loading, stock yard, coal loading, drilling, and coal handling plant. The dust levels were examined to assess miners' exposure to respirable dust in each of the opencast mining areas from 1994 to 2005. The data obtained from the dust measurement studies were evaluated by using analysis of variance (ANOVA) and the Tukey-Kramer procedure. The analyses were performed by using Minitab 14 statistical software. It was concluded that, drilling operations produce higher dust concentration levels and thus, drill operators may have higher incidence of respiratory disorders related to exposure to dust in their work environment.     

Determination of road dust loadings and chemical characteristics using resuspension

The contribution of fugitive dust from traffic to air pollution can no longer be ignored in China. In order to obtain the road dust loadings and to understand the chemical characteristics of PM₁₀ and PM_2.5 from typical road dust, different paved roads in eight districts of Beijing were selected for dust collection during the four seasons of 2005. Ninety-eight samples from 28 roads were obtained. The samples were resuspended using equipment assembled to simulate the rising process of road dust caused by the wind or wheels in order to obtain the PM₁₀ and PM_2.5 filter samples. The average road dust loading was 3.82 g m^− 2, with the highest of 24.22 g m^− 2 being in Hutongs in the rural–urban continuum during winter. The road dust loadings on higher-grade roads were lower than those on lower-grade roads. Attention should be paid to the pollution in the rural–urban continuum areas. The sums of element abundances measured were 16.17% and 18.50% for PM₁₀ and PM_2.5 in road dust. The average abundances of OC and EC in PM₁₀ and PM_2.5 in road dust were 11.52%, 2.01% and 12.50%, 2.06%, respectively. The abundance of elements, water-soluble ions, and OC, EC in PM₁₀ and PM_2.5 resuspended from road dust did not change greatly with seasons and road types. The soil dust, construction dust, dust emitted from burning coal, vehicle exhaust, and deposition of particles in the air were the main sources of road dust in Beijing. Affected by the application of snow-melting agents in Beijing during winter, the amount of Cl⁻ and Na⁺ was much higher during that time than in the other seasons. This will have a certain influence on roads, bridges, vegetations, and groundwater.     

Validation of two air quality models for Indian mining conditions

All major mining activity particularly opencast mining contributes to the problem of suspended particulate matter (SPM)directly or indirectly. Therefore, assessment and prediction are required to prevent and minimize the deterioration of SPM due tovarious opencast mining operations. Determination of emission rate of SPM for these activities and validation of air quality models are the first and foremost concern. In view of the above, the study was taken up for determination of emission rate for SPMto calculate emission rate of various opencast mining activitiesand validation of commonly used two air quality models for Indianmining conditions. To achieve the objectives, eight coal and three iron ore mining sites were selected to generate site specific emission data by considering type of mining, method of working, geographical location, accessibility and above all resource availability. The study covers various mining activitiesand locations including drilling, overburden loading and unloading, coal/mineral loading and unloading, coal handling orscreening plant, exposed overburden dump, stock yard, workshop, exposed pit surface, transport road and haul road. Validation of the study was carried out through Fugitive Dust Model (FDM) and Point, Area and Line sources model (PAL2) by assigning the measured emission rate for each mining activity, meteorologicaldata and other details of the respective mine as an input to the models. Both the models were run separately for the same set ofinput data for each mine to get the predicted SPM concentrationat three receptor locations for each mine. The receptor locationswere selected such a way that at the same places the actual filedmeasurement were carried out for SPM concentration. Statisticalanalysis was carried out to assess the performance of the modelsbased on a set measured and predicted SPM concentration data. The value of coefficient of correlation for PAL2 and FDM was calculated to be 0.990-0.994 and 0.966-0.997, respectively, which shows a fairly good agreement between measured and predicted values of SPM concentration. The average index of agreement values for PAL2 and FDM was found to be 0.665 and0.752, respectively, which represents that the prediction by PAL2 and FDM models are accurate by 66.5 and 75.2%, respectively. These indicate that FDM model is more suited for Indian mining conditions.     

Characteristics of Hazardous Airborne Dust Around an Indian Surface Coal Mining Area

Surface coal mining creates more air pollution problems with respect to dust than underground mining . An investigation was conducted to evaluate the characteristics of the airborne dust created by surface coal mining in the Jharia Coalfield. Work zone air quality monitoring was conducted at six locations, and ambient air quality monitoring was conducted at five locations, for a period of 1 year. Total suspended particulate matter (TSP) concentration was found to be as high as 3,723 μg/m³, respirable particulate matter (PM10) 780 μg/m³, and benzene soluble matter was up to 32% in TSP in work zone air. In ambient air, the average maximum level of TSP was 837 μg/m³, PM10 170 μg/m³ and benzene soluble matter was up to 30%. Particle size analysis of TSP revealed that they were more respirable in nature and the median diameter was around 20 μm. Work zone air was found to have higher levels of TSP, PM10 and benzene soluble materials than ambient air. Variations in weight percentages for different size particles are discussed on the basis of mining activities. Anionic concentration in TSP was also determined. This paper concludes that more stringent air quality standards should be adopted for coal mining areas and due consideration should be given on particle size distribution of the air-borne dust while designing control equipment.     

Generation and Quantification of Hazardous Dusts from Coal Mining in the Indian Context

The increasing trend of opencast coal mining in India tends to release huge amounts of dust. But there is no well-defined method of estimating dust emission due to different coal mining activities. This paper examines the sources of dust emission due to coal mining activities, and focuses on the quantification of dust emission with the development and use of emission factors. Because of their site-specific nature, emission factors developed for one site may not give the correct results for another site. In the present investigation, prediction equations are utilized for the development of emission factors. For the applications of this concept, one large opencast coal project of Bharat Coking Coal Ltd. (BCCL) was investigated, and the total amount of dust emitted due to different mining activities was calculated by the utilization of emission factor data, which was estimated to be 9368.2 kg/day. This paper also focuses on the significance of this study in the field of environmental protection and likely impacts of such study. The paper concludes that once the amount of dust generation is estimated, the impact on air quality can be assessed appropriately and a proper air-pollution control strategy can be developed.     

Assessment of Dust Generation Due to Opencast Coal Mining– An Indian Case Study

Every mine in India has to obtain environmental clearance fromthe Govt. Air pollution is one of the most important parametersto be considered in preparing an EIA. However, there is no welldefined method for predicting thr air pollution impact due tomining. Increasing trend of opencast (O/C) mining leads toproduction of huge quantities of dust. Emission factor data havebeen utilised to quantify the generation of dust. The projectunder study is one of the largest opencast project (OCP) forcoking coal. The main sources of air pollution have beenidentified. The rate of emission per unit of a given activityknown as an emission factor has been utilised, taking localfactors into account. It has been estimated that due to topsoilremoval, overburden (O/B) removal, extraction of coal, sizereduction generated 7.8 t of dust per day. Wind erosiongenerated 1.6 t of dust per day and the whole operationproduced dust which accounted for 9.4 mt/day. They cause airpollution in the work zone and surrouding locations. Themethodology adopted may be used to quantify generation for otherprojects also.     

The development of a novel method for directional dust monitoring

Dust monitoring using sticky pads was popularised in the 1980s. The discolouration caused by dust adhering to white adhesive material was measured with a smoke stain reflectometer. This loss of reflectance was expressed as the percentage effective area coverage (EAC%) per day. EAC% can be used as a measure of nuisance caused by dust. EAC% may also be measured with a hand-held Sticky Pad Reader (SPR). Sticky pads can be mounted on flat or cylindrical surfaces to measure dust by deposition or in flux. An alternative method was developed in the 1990s that measured total dust coverage using computer-based scanning. DustScan used a transparent adhesive film wrapped around a vertical cylinder with magnetic north marked. The sticky pad was sealed with another transparent sheet before scanning at 50 dots per inch (dpi). Dust levels were assessed by comparing the grey-scale values of pixels in the exposed area with an unexposed reference area. Insects and other extraneous material could be ‘masked out’ from the computer analysis. Dust coverage was expressed as percentage absolute area coverage (AAC%). DustScan has subsequently been developed commercially. A limited trial indicated that monitoring periods of 7–14 days were preferred to avoid dust saturation of the sticky pad. A method for calculating EAC% has been developed and shown to have a high degree of correspondence with an SPR. A trial for the Minerals Industry Research Organisation (MIRO) made comparisons between DustScan and other dust monitoring methods. Dust nuisance limits based on AAC% and EAC% are proposed.par     

Concentrations and bioaccessibility of metals in vegetation and dust near a mining haul road, Cape Krusenstern National Monument, Alaska

Vegetation, sub-surface peat, and road dust were sampled near the Delong Mountain Transportation System (DMTS) haul road in northwest Alaska in 2005-2006 to document aluminum, barium, cadmium, lead, and zinc concentrations, and to evaluate bioaccessibility of these metals. The DMTS haul road is the transport corridor between Red Dog Mine (a large-scale, lead-zinc mine and mill) and the coastal shipping port, and it traverses National Park Service lands. Compared to reference locations, total metal concentrations in four types of vegetation (birch, cranberry, and willow leaves, and cotton grass blades/stalks) collected 25 m from the haul road were enriched on average by factors of 3.5 for zinc, 8.0 for barium, 20 for cadmium, and 150 for lead. Triple rinsing of vegetation with a water/methanol mixture reduced metals concentrations by at most 50%, and cadmium and zinc concentrations were least affected by rinsing. Cadmium and zinc bioaccessibility was greater in vegetation (50% to 100%) than in dust (15% to 20%); whereas the opposite pattern was observed for lead bioaccessibility (<30% in vegetation; 50% in dust). Barium exhibited low-to-intermediate bioaccessibility in dust and vegetation (20% to 40%), whereas aluminum bioaccessibility was relatively low (<6%) in all sample types. Our reconnaissance-level study indicates that clean-up and improvements in lead/zinc concentrate transfer activities have been effective; however, as of 2006, metal dispersion from past and/or present releases of fugitive dusts along the DMTS road still may have been contributing to elevated metals in surface vegetation. Vegetation was most enriched in lead, but because bioaccessibility of cadmium was greater, any potential risks to animals that forage near the haul road might be equally important for both of these metals.     

Air quality assessment along Dhanbad - Jharia road

Road ambient air pollution status along Dhanbad – Jharia road isstudied and presented in this article. The selection of this areais made considering the importance of the road in Dhanbad district and the nature of activities taking place along the road, which reflect that the portion of road upto Dhansar can be considered as having commercial areas on both sides and that from Dhansar to Jharia as having industrial areas on both sides.For the assessment of the ambient air quality along the road monitoring is done at the following five locations: Indian Schoolof Mines (ISM), main gate; Bankmore; Dhansar police check post; Dhansar opencast project agent office and a residential house beside the Rajapur opencast project. The location of ISM, maingate is specially chosen as this represents a commercial shoppingcomplexes and the situation can be compared with that at Bankmore. Monitoring of ambient air quality is done following thestandard procedure prescribed in IS: 5182. In addition the concentration of lead, zinc, copper, iron, manganese, cadmium metals in SPM is also monitored. The ambient air quality is monitored in the months of September and November 1999, respectively, to represent monsoon and winter seasons. The SPM concentration observed at all the five locations in the winterseason is more than the permissible limits for commercial andindustrial areas. However, in the monsoon season, the SPM concentration is higher than the permissible limit at the twocommercial locations, i.e., ISM gate and Bankmore, while it isless than the prescribed limit for industrial areas at the remaining three locations. At the ISM gate and Bankmore the SPM generation is mainly by vehicular traffic while at other three locations it was in addition due to mining and other activities.