Monitoring of cotton dust and health risk assessment in small-scale weaving industry

The present study describes the estimation of particulate matter (cotton dust) with different sizes, i.e., PM(1.0), PM(2.5), PM(4.0), and PM(10.0 μm) in small-scale weaving industry (power looms) situated in district Hafizabad, Punjab, Pakistan, and the assessment of health problems of workers associated with these pollutants. A significant difference was found in PM(1.0), PM(2.5), PM(4.0), and PM(10.0) with reference to nine different sampling stations with p values <0.05. Multiple comparisons of particulate matter with respect to size, i.e. PM(1.0), PM(2.5), PM(4.0), and PM(10.0), depict that PM(1.0) differs significantly from PM(2.5), PM(4.0), and PM(10.0), with p values <0.05 and that PM(2.5) differs significantly from PM(1.0) and PM(10.0), with p values <0.05, whereas PM(2.5) differs non-significantly from PM(4.0), with a p value >0.05 in defined sampling stations on an average basis. Majority of the workers were facing several diseases due to interaction with particulate matter (cotton dust) during working hours. Flue, cough, eye, and skin infections were the most common diseases among workers caused by particulate matter (cotton dust).     

Analyzing the role of information and telecommunication technology in human development: panel data analysis

Environmental Science and Pollution Research - Economic growth in modern-day world get attention primarily through innovation and higher productivity, which places technology and knowledge at the...     

Chemical characterization and source apportionment of fine and coarse particulate matter in Lahore,Pakistan

Lahore, Pakistan is an emerging megacity that is heavily polluted with high levels of particle air pollution. In this study, respirable particulate matter (PM_2.5 and PM₁₀) were collected every sixth day in Lahore from 12 January 2007 to 19 January 2008. Ambient aerosol was characterized using well-established chemical methods for mass, organic carbon (OC), elemental carbon (EC), ionic species (sulfate, nitrate, chloride, ammonium, sodium, calcium, and potassium), and organic species. The annual average concentration (±one standard deviation) of PM_2.5 was 194 ± 94 μg m^?3 and PM₁₀ was 336 ± 135 μg m^?3. Coarse aerosol (PM_10?2.5) was dominated by crustal sources like dust (74 ± 16%, annual average ± one standard deviation), whereas fine particles were dominated by carbonaceous aerosol (organic matter and elemental carbon, 61 ± 17%). Organic tracer species were used to identify sources of PM_2.5 OC and chemical mass balance (CMB) modeling was used to estimate relative source contributions. On an annual basis, non-catalyzed motor vehicles accounted for more than half of primary OC (53 ± 19%). Lesser sources included biomass burning (10 ± 5%) and the combined source of diesel engines and residual fuel oil combustion (6 ± 2%). Secondary organic aerosol (SOA) was an important contributor to ambient OC, particularly during the winter when secondary processing of aerosol species during fog episodes was expected. Coal combustion alone contributed a small percentage of organic aerosol (1.9 ± 0.3%), but showed strong linear correlation with unidentified sources of OC that contributed more significantly (27 ± 16%). Brick kilns, where coal and other low quality fuels are burned together, are suggested as the most probable origins of unapportioned OC. The chemical profiling of emissions from brick kilns and other sources unique to Lahore would contribute to a better understanding of OC sources in this megacity.     

Assessment of physicochemical parameters of wastewater samples

Water samples from selected locations of Nullah Lai and Koh-e-Noor textile mill in the metropolitan city of Rawalpindi and Islamabad, Pakistan, were collected. Physicochemical parameters and heavy metals were determined using standard analytical procedures in comparison with sites, locations and subsequent interval of 3 months. The results of the physicochemical analysis at different locations of Nullah Lai and Koh-e-Noor textile mill with an interval of 3 months were obtained in the following range: pH (7.16–8.29), temperature (17.8–28.8 °C), conductivity (1,005–3,347 μS/m), TDS (754.3–2,519.5 mg/L), turbidity (272.8–487.05 NTU), total hardness (300–452 mg/L), nitrates (10.11–22.95 ppm), calcium (74.31–139.2 ppm), chloride (127.72–396.16 ppm), sulphate (15.97–87.38 ppm), NaCl (210.5–631.1 ppm), Ni (0.30–0.72 ppm), Cd (0.005–0.03 ppm), Cr (0.2–7.4 ppm), Pb (0.12–0.73 ppm), Zn (0.03–0.08 ppm) and Cu (0.01–0.06 ppm). The highest value of physicochemical parameters (compared with Nullah Lai) was obtained in locations of Koh-e-Noor textile mill. The results obtained exceeded the maximum allowable limit set by the World Health Organization for drinking purpose but can be used for irrigation purposes after suitable treatment and purification.     

Evaluating the groundwater potential of Wadi Al-Jizi,Sultanate of Oman,by integrating remote sensing and GIS techniques

Environmental Science and Pollution Research - Groundwater resources are highly stressed due to their overuse, especially in the arid region. This study is aimed at discovering potential...     

The role of disinfectants and sanitizers during COVID-19 pandemic: advantages and deleterious effects on humans and the environment

Environmental Science and Pollution Research - Disinfectants and sanitizers are essential preventive agents against the coronavirus disease 2019 (COVID-19) pandemic; however, the pandemic crisis...     

Assessment of four turbulence models in simulation of large-scale pool fires in the presence of wind using computational fluid dynamics (CFD)

Pool fires are the most common of all process industry accidents. Pool fires often trigger explosions which may result in more fires, causing huge losses of life and property. Since both the risk and the frequency of occurrence of pool fires are high, it is necessary to model the risks associated with pool fires so as to correctly predict the behavior of such fires.Among the parameters which determine the overall structure of a pool fire, the most important is turbulence. It determines the extent of interaction of various parameters, including combustion, wind velocity, and entrainment of the ambient air. Of the various approaches capable of modeling the turbulence associated with pool fires, computational fluid dynamics (CFD) has emerged as the most preferred due to its ability to enable closer approximation of the underlying physical phenomena.A review of the state of the art reveals that although various turbulence models exist for the simulation of pool fire no single study has compared the performance of various turbulence models in modeling pool fires. To cover this knowledge-gap an attempt has been made to employ CFD in the assessment of pool fires and find the turbulence model which is able to simulate pool fires most faithfully. The performance of the standard k–? model, renormalization group (RNG) k–? model, realizable k–? model and standard k–ω model were studied for simulating the experiments conducted earlier by Chatris et al. (2001) and Casal (2013). The results reveal that the standard k–? model enabled the closest CFD simulation of the experimental results.