Reducing musculoskeletal disorders in iron ore mine operators: A fuzzy-based intervention approach.

BACKGROUND: This study focuses on evaluating the exposure to whole-body vibration (WBV) and association of musculoskeletal disorders (MSDs) with various risk factors among dumper operators in the mining industry. Despite the issue's significance, prior research has been limited. OBJECTIVE: The study introduces a novel fuzzy-based approach for identifying, selecting, and prioritizing safety measures to mitigate MSD risks. METHODS: Data collection comprised face-to-face interviews, anthropometric measurements, Rapid Upper Limb Assessment (RULA) scoring for posture assessment, and the Nordic Musculoskeletal questionnaire for assessment of MSD prevalence. Multiple linear and logistic regression models were used to analyse the contributing risk factors to MSDs and WBV exposure. These risk factors formed the basis for a practical approach to select appropriate safety measures based on fuzzy based aggregation method of expert's judgment aimed at mitigating the risk of MSDs. RESULTS: The results revealed that the risk factors such as poor work posture, WBV exposure and poor seat design were significantly associated with neck (adjusted odds ratio aOR = 4.81), upper limb and shoulder (aOR = 3.28), upper back (aOR = 5.09), and lower back pain (aOR = 3.67) at p < 0.05. Using these factors to formulate safety measures to reduce MSD risk, the minimization of sharp turns and abrupt changes in elevation in designing the haul roads, scheduled maintenance practices, and ergonomic seat design were found as important safety measures in this study. CONCLUSION: Our unique methodological approach in occupational health research could be highly beneficial for tailoring safety measures at the unit level with minimal effort.

Development of an intervention program to reduce whole-body vibration exposure based on occupational and individual determinants among dumper operators.

Objectives. Studies related to a systematic approach for intervention design to reduce whole-body vibration (WBV) exposure are scarce. This study presents a systematic approach to identifying, selecting and prioritizing safety interventions to fulfill that research gap. Methods. A total of 130 vibration readings for dumper operators were taken from two surface iron ore mines to identify significant determinants of WBV exposure. Initially, age, weight, seat design, awkward posture, machine's age, load tonnage, dumper speed and haul road condition were hypothesized as determinants. Data were collected through standardized questionnaires and field-based observation. A multivariate statistical approach was applied for the practical use of the intervention program. Results. As some of the hypothesized factors were correlated, exploratory factor analysis (EFA) followed by multiple linear regression (MLR) was used to investigate their association with WBV exposure. As per EFA results, hypothesized factors were clubbed under individual, ergonomics and occupational factors. Occupational and ergonomics factors were found to be significantly associated with WBV exposure through MLR and used to form safety interventions to reduce WBV exposure. Conclusions. Our methodological approach is original in the occupational health research area and can be helpful to tailor the safety interventions for the unit level with minimum effort.

Assessment of seasonal variability of PM, BC and UFP levels at a highway toll stations and their associated health risks.

As a part of their occupation, workers at toll stations are exposed to traffic emissions during the working shift, which sometimes stretches to 12 h. To assess the exposure and subsequent health risk of these workers, a study was performed on a highway toll station in India. PM1, PM2.5, PM10, BC and UFP concentration were determined inside a toll collectors' cabin and outside in a free-flowing traffic section (125 m from the toll cabin). The concentrations varied in the following range: PM1 (40.69-226.13 µg m-3), PM2.5 (49.71-247.36 µg m-3), PM10 (83.15-458.14 µg m-3) and BC (2.1-87.5 µg m-3) and UFP: 101-53705 pt cm-3. The mean concentration inside the cabin was 1.34 (PM1), 1.35 (PM2.5), 1.16 (PM10) and 2.91 (BC) times the concentration outside for the summer season. The corresponding levels in the winter season were 1.14 (PM1), 1.11 (PM2.5), 1.11 (PM10), 2.50 (BC) and 1.82 (UFP). In addition to the exhaust emission, the non-exhaust emissions such as resuspension of crustal particles, fly ash and bioaerosols were identified. Using the Multiple Path Particle Dosimetry model for two groups - adults (18-21 years) and adults (21+ years), it was estimated that the pulmonary deposition of in-cabin workers were 50% (PM2.5) -75% (PM1) higher than the workers outside the cabin. Particle mass deposition was found to be higher for adults (21+ years) than adults (18-21 years) for both the seasons. The study quantitatively assessed the health risk faced by the workers in terms of exposure concentration and deposition in respiratory tract. More such studies at different traffic mix and climate can provide better estimates of health risk of toll workers that can be used to devise appropriate strategies for control of it.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5: 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10: 171 µg m-3 versus 235 µg m-3; CO: 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Evaluation of vertical and horizontal distribution of particulate matter near an urban roadway using an unmanned aerial vehicle.

Measurement of traffic emissions has gained a lot of interest in recent times due to its contribution to urban pollution. This paper reports the outcome from an unmanned aerial vehicle (UAV) based measurement of PM concentration near an urban roadway at Kolkata, India. A total of 54 flights were carried out for simultaneous measurements of PM1, PM2.5 and PM10 mass concentration and meteorological parameters in vertical as well as in horizontal direction. Results for the vertical flight up to 100 m showed that the PM1, PM2.5 and PM10 concentrations at higher altitudes are less (mean; 24.6, 39.9 and 103.8 µg m-3) compared to the respective ground level concentrations (mean; 26.3, 50.4 and 201.9 µg m-3). For all the three particle sizes, the majority of the cases of higher PM concentration at higher altitudes happened during the evening flight. Low mixing height and low wind speed are suggested to be the reasons for the poor dispersion of pollutants in the evening. While there was a 7-10% fall of fine particles (PM1 and PM2.5) mass concentrations up to 90 m away from the road, no trend could be seen for PM10. The random forest model to predict the UAV/Ground concentration ratio showed high accuracy (R2 = 0.82-0.95) for all three particle sizes. This is an important finding from this study, which shows how UAV measurement data can be used to generate models that can predict the higher altitude concentrations from the ground based measurements.

Association between Whole-Body Vibration exposure and musculoskeletal disorders among dumper operators: A case-control study in Indian iron ore mines.

BACKGROUND: Dumper operators in mines worldwide are subjected to Musculoskeletal Disorders (MSDs) due to whole-body vibration exposure. This study evaluated the working-life-Whole-Body Vibration (WBV)-exposure and their association with various MSDs among dumper operators in mines which remains poorly addressed. METHODS: This case-control study in Indian iron ore mines was conducted to compare randomly selected 65 dumper operators and 65 office workers. Data were collected through face-to-face interviews using the Nordic Musculoskeletal Questionnaire (NMQ) and were analysed using logistic regression models. RESULTS: The study revealed that majority of the dumper operators were exposed to WBV exceeding the ISO-2631 limits. Compared with controls, the dumper operators had a much higher risk of upper back pain (age-overweight-adjusted odds ratio ORao = 5.37, 95% CI = 1.78-16.20), lower back pain (ORao = 2.72, 95% CI = 1.25-5.94), knee and leg pain (ORao = 3.68, 95% CI = 1.22-11.11), and having 2+ MSDs (ORao = 5.05, 95% CI = 1.88-13.51, vs. no MSDs). Working-life-WBV-exposure was higher among dumper operators having upper back pain (mean (SD) = 7.1 (1.91) vs. 5.7 (1.91), p < 0.01) and lower back pain (mean (SD) = 6.63 (2.10) vs. 5.55 (1.71), p < 0.01) compared to those without these MSDs. Older age was associated with higher risk of MSD pains. CONCLUSION: Dumper operators have excess MSDs due to high working-life-WBV-exposure. Their MSDs and working-life-WBV-exposure should be regularly evaluated and reduced.

Association of air pollution and meteorological variables with COVID-19 incidence: Evidence from five megacities in India.

Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM2.5, PM10 and CO), Ground level ozone (O3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM2.5, PM10, CO, O3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r=0.54;0.25) and unlock period (r=0.66;0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10-11% and 4-6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases.

In-vehicle PM2.5 personal concentrations in winter during long distance road travel in India.

During travel, passengers are exposed to high concentrations of PM which constitute a significant fraction of daily personal exposures. We carried out comprehensive mobile monitoring for a distance of 400km on an Indian National Highway during the winter season to evaluate the PM2.5 Personal Concentrations (PC) and mass exposure in three traffic microenvironments (public bus, car with AC (Car CW) and car without AC (Car OW)) and to quantify the key factors that influence it. The mean concentrations were highest inside Car OW (175.3±142.7µgm-3) followed by bus (134.0±113.9µgm-3) and lowest in Car CW (78.8±37.1µgm-3). PC during in-city highway sections were greater than out-city highway sections during Bus and Car OW journeys. PC were higher during morning than evening journeys in Bus and Car OW. Mean PC in different seating positions in Bus followed the trend: middle>rear>front. Results of the Linear Mixed-Effects Models (LMM) indicated that journey timings were the significant predictors of PC for Bus and Car OW. The exposures per unit time followed trend: Car OW>Bus>Car CW. Total mass of inhaled exposures however followed a different trend: Bus>Car OW>Car CW, because Bus needed longer duration to cover the entire distance. Car CW users experienced both the least PC and mass exposures. We estimated that the road repairing works contributed ~22% in Bus and Car OW, and ~12% in Car CW increment in mass exposures. These findings indicate that management of exposures needs to consider mass exposures in addition to PC, for curtailing the adverse health effects relating to long distance journeys. Highway authorities should focus on early completion of construction and repairing activities to reduce exposures to passengers.

A comparison of personal exposure to air pollutants in different travel modes on national highways in India.

People often travel a long distance on highways to the nearest city for professional/business activities. However, relatively few publications on passenger exposure to pollutants on highways in India or elsewhere are available. The aim of this study was to examine the contribution of different travel modes to passengers' pollutant exposure for a long distance travel on a national highway in India. We measured PM2.5 and CO exposure levels of the passengers over 200km on a national highway using two portable air monitors, EVM-7 and EPAM-5000. Personal concentration exposures and per min-, per hour-, per trip- and round trip mass exposures for three travel modes were calculated for 9 trips. Association between pollutants and weather variables were evaluated using levels Spearman correlation. ANOVA was carried out to evaluate the influence of travel mode, the timing of trips, temperature and RH on personal exposures. On an average, PM2.5 personal concentration exposure levels were highest in the car (85.41±61.85µgm-3), followed by the bus (75.08±55.39µgm-3) and lowest in the car (ac) (54.43±34.09µgm-3). In contrast, CO personal exposure was highest in the car (ac) (1.81±1.3ppm). Travel mode explained the highest variability for CO (18.1%), CO2 (9.9%), PM2.5 (1.2%) exposures. In-city mass exposures were higher than trip averages; PM2.5:1.21-1.22, 1.13-1.19 and 1.03-1.28 times; CO: 1.20-1.57, 1.37-2.10 and 1.76-2.22 times for bus, car and car (ac) respectively. Traveling by car (ac) results in the lowest PM2.5 exposures, although it exposes the passenger to high CO level. Avoiding national highways passing through cities can reduce up to 25% PM2.5 and 50% CO mass exposures. This information can be useful for increasing environmental awareness among the passengers and for framing better pollution control strategies on highways.

Suitability of different growth substrates as source of nitrogen for sulfate reducing bacteria.

Sulfate reducing bacteria (SRB) mediated treatment of acid mine drainage is considered as a globally accepted technology. However, inadequate information on the role of nitrogen source in the augmentation of SRB significantly affects the overall treatment process. Sustenance of SRB depends on suitable nitrogen source which is considered as an important nutrient. This review focuses on the different nitrogen rich growth substrates for their effectiveness to support SRB growth and sulfate reduction in passive bioreactors. Compounds like NH4Cl, NH4HCO3, NO3 (-), aniline, tri-nitrotoluene, cornsteep liquor, peptone, urea, and chitin are reported to have served as nitrogen source for SRB. In association with fermentative bacteria, SRB can metabolize these complex compounds to NH4 (+), amines, and amino acids. After incorporation into cells, these compounds take part in the biosynthesis of nucleic acids, amino acids and enzyme co-factor. This work describes the status of current and the probable directions of the future research.

Whole-body Vibration Exposure of Drill Operators in Iron Ore Mines and Role of Machine-Related, Individual, and Rock-Related Factors.

BACKGROUND: This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. METHODS: The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration (m/s(2))], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. RESULTS: More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient ß = -0.052, standard error SE = 0.023), manufacturer (ß = 1.093, SE = 0.227), rock hardness (ß = 0.045, SE = 0.018), uniaxial compressive strength (ß = 0.027, SE = 0.009), and density (ß = -1.135, SE = 0.235). CONCLUSION: Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system.