The quantiles of annual maximum wind speed (AMWS) can be estimated for different meteorological stations of interest by using at-site frequency analysis and extreme value theory. These estimates are of immense importance for the codification of wind speed. However, the historical data of wind speed at the number of meteorological stations are sometimes unavailable and often insufficient due to the shorter length, especially in developing countries like Pakistan. The scarcity of the data increases the uncertainty of the quantiles estimates regarding policy implications. To cope with the problem, an approach of Regional Frequency Analysis (RFA) is opted here. In this study, RFA of AMWS using linear-moments (Lmoments) is carried out by considering wind speed data of nine meteorological stations of province Punjab, Pakistan. No station is found to be discordant. A single homogenous region is constituted from these nine stations using a subjective approach based on their geographical locations. Heterogeneity measures justify that these nine stations of Punjab form a single homogeneous region. Regional quantiles estimates are found through the most appropriate probability distribution among generalized normal (GNO), generalized logistic (GLO), Pearson Type 3 (P3), generalized Pareto (GPA), Weibull (WEI), log Pearson Type 3 (LP3) and generalized extreme value (GEV) distributions. Z-statistic and L-moment ratio diagram suggest that GLO and GNO distributions are better choices than others. Robustness of both distributions is evaluated through relative bias (RB) and relative root mean square error (RRMSE). Findings indicate that overall, GLO distribution is better than GNO. Further, we also find at-site quantiles from dimensionless quantities (regional quantiles) using the sample mean and median as scaling factors. Quantiles' estimates calculated from this study can be used in codified structural designs for policy implications. K E Y W O R D S linear-moments, Monte Carlo simulation, quantile estimates, wind speed

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Coal is a major source of energy in developing countries. Its underground mining exposes workers to respirable dust containing silica, causing respiratory illness. The objectives of this study include measuring this dust and the percentage of its silica content and evaluating the prevalence of respiratory diseases among coal cutters. A walkthrough survey performa, SKC Airchek 52 (SKC Inc., eighty four, PA, USA) air sampling pumps, an anemometer, hygrometer, multi-gas detector, a thermometer and modified International Union Against Tuberculosis and Lung Disease (IUATLD) respiratory questionnaire were used to collect data from 64 workers working in 5 different mines of Chakwal District in Punjab, Pakistan. Mine E, with the lowest ventilation volumetric flow rate (18m 3 /s), has the highest dust concentration (6.10 mg/m 3 , silica content 2.699%). Conversely, mine A, with the highest ventilation volumetric flow rate (45 m 3 /s), has the lowest dust concentration (2.58 mg/m 3 , 1.33 % silica content). Survey results show that 71% of workers inherited this occupation, 94% did not smoke, 99% did not use any dust mask, 47% have diagnosed tuberculosis and 8% asthma. About 57, 48, 44 and 42 workers reported cough, phlegm, chest tightness and shortness of breath, respectively. The 89% workers were told by their physicians that dust exposure was the reason for their respiratory ailment.

There is not enough data available on occupational health and safety issues of underground coal miners in Pakistan. This study focuses on spinal disorders in association with personal and occupational factors. The Nordic Musculoskeletal Questionnaire was used for a cross-sectional study of 260 workers of 20 mines located in four districts of Punjab, Pakistan. Regression models were created for upper back pain and lower back pain of workers whose mean age is 19.8 years (±SD 1.47). Results identify the coal cutting as the most harmful work with odds ratios (ORs) 13.06 (95% confidence interval (CI) 13.7–21.5) for lower back pain and 11.2 (95% CI 3.5–19.4) for upper back pain in participants. Those with greater years of work experience had higher odds of upper back pain (2.4, 95% CI 1.4–3.5) and lower back pain (3.3, 95% CI 1.1–4.4). Number of repetitions (mean value 25.85/minute with ±SD 9.48) are also significant for spinal disorder with ORs of 4.3 (95% CI 3.2–7.4) for lower back and 1.3 (95% CI 1.0–2.4) for upper back. Many other occupational and personal factors are positively associated with the back pain in underground coal mines workers, requiring immediate ergonomic intervention.

Background: In subcontinental underground mines, coal mining is carried out manually and requires many laborers to practice traditional means of coal excavation. Each task of this occupation disturbs workers’ musculoskeletal order. In order to propose and practice possible ergonomic interventions, it is necessary to know what tasks (drilling and blasting, coal cutting, dumping, transporting, timbering and supporting, loading and unloading) cause disorder in either upper limbs, lower limbs, or both. Methods: To this end, R-programming, version R 3.1.2 and SPSS, software 20, were used to calculate data obtained by studying 260 workers (working at different tasks of coal mining) from 20 mines of four districts of Punjab, Pakistan. In addition, a Standard Nordic Musculoskeletal Questionnaire (SNMQ) and Rapid Upper Limb Assessment (RULA) sheet were used to collect data and to analyze postures respectively. Results: In multi regression models, significance of the five tasks for upper and lower limb disorder is 0.00, which means that task based prevalence of upper and lower limb disorders are common in underground coal mines. The results of the multiple bar chart showed that 96 coal cutters got upper limb disorders and 82 got lower limb disorders. The task of timbering and supporting was shown to be dangerous for the lower limbs and relatively less dangerous for the upper limbs, with 25 workers reporting pain in their lower limbs, and 19 workers reporting pain in their upper limbs. Documented on the RULA sheet, all tasks got the maximum possible score (7), meaning that each of these tasks pose a threat to the posture of 100% of workers. The majority of participants (182) fell in the age group of 26 to 35 years. Of those workers, 131 reported pain in the lower limbs and slight discomfort (128) in the upper limbs. The significance value of age was 0.00 for upper limb disorder and was 0.012 for lower limb disorder. Frequency graphs show age in direct proportion to severity of pain while in inverse proportion with number of repetitions performed per min. Conclusions: All findings infer that each task of underground coal mining inflicts different levels of disorder in a workers’ musculoskeletal structure of the upper and lower limbs. It highlighted the need for urgent intervention in postural aspects of each task.