Health impact assessment of auto rickshaw and cab drivers due to exposure to vehicular pollution in Delhi: an integrated approach

Environmental Science and Pollution Research - Vehicular emission is an important contributor to air pollution in the urban environment and impacts the health of commuters as well as drivers. The...     

Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.     

Do drivers of renewable energy consumption matter for BRICS economies? Nexus among technological innovation,environmental degradation,economic growth,and income inequality

Environmental Science and Pollution Research - In light of increasing concerns about climate change and energy security, renewable energy has been seen as the most promising solution to fulfil...     

Treatment of organic pollutants by homogeneous and heterogeneous Fenton reaction processes

Nowadays, the water ecosystem is being polluted due to the rapid industrialization and massive use of antibiotics, fertilizers, cosmetics, paints, and other chemicals. Chemical oxidation is one of the most applied processes to degrade contaminants in water. However, chemicals are often unable to completely mineralize the pollutants. Enhanced pollutant degradation can be achieved by Fenton reaction and related processes. As a consequence, Fenton reactions have received great attention in the treatment of domestic and industrial wastewater effluents. Currently, homogeneous and heterogeneous Fenton processes are being investigated intensively and optimized for applications, either alone or in a combination of other processes. This review presents fundamental chemistry involved in various kinds of homogeneous Fenton reactions, which include classical Fenton, electro-Fenton, photo-Fenton, electro-Fenton, sono-electro-Fenton, and solar photoelectron-Fenton. In the homogeneous Fenton reaction process, the molar ratio of iron(II) and hydrogen peroxide, and the pH usually determine the effectiveness of removing target pollutants and subsequently their mineralization, monitored by a decrease in levels of total organic carbon or chemical oxygen demand. We present catalysts used in heterogeneous Fenton or Fenton-like reactions, such as H₂O₂–Fe³⁺(solid)/nano-zero-valent iron/immobilized iron and electro-Fenton-pyrite. Surface properties of heterogeneous catalysts generally control the efficiency to degrade pollutants. Examples of Fenton reactions are demonstrated to degrade and mineralize a wide range of water pollutants in real industrial wastewaters, such as dyes and phenols. Removal of various antibiotics by homogeneous and heterogeneous Fenton reactions is exemplified.     

Trends over 1999–2014 in the concentrations of Ba,Cs, Co,Mo, Pb,Sb, Tl,and W in urine of US children aged 6–11 years

Data from National Health and Nutrition Examination Survey for children aged 6–11 years for 1999–2014 were used to study time trends and factors affecting the urinary levels of barium, cobalt, cesium, molybdenum, lead, antimony, thallium, and tungsten. Adjusted levels in urine declined every two years by 5.9% for barium, by 1.2% for cesium, by 18.2% for lead, and by 14% for antimony. For every additional smoker smoking inside a home, the levels of barium increased by 10.6% and for lead by 10%, but for tungsten levels decreased by 7.7%.     

Higher Cd adsorption on biogenic elemental selenium nanoparticles

Cadmium (Cd) is a carcinogenic metal contaminating the environment and ending up in wastewaters. There is therefore a need for improved methods to remove Cd by adsorption. Biogenic elemental selenium nanoparticles have been shown to adsorb Zn, Cu and Hg, but these nanoparticles have not been tested for Cd removal. Here we studied the time-dependency and adsorption isotherm of Cd onto biogenic elemental selenium nanoparticles using batch adsorption experiments. We measured ζ-potential values to assess the stability of nanoparticles loaded with Cd. Results show that the maximum Cd adsorption capacity amounts to 176.8 mg of Cd adsorbed per g of biogenic elemental selenium nanoparticles. The ζ-potential of Cd-loaded nanoparticles became less negative from ?32.7 to ?11.7 mV when exposing nanoparticles to an initial Cd concentration of 92.7 mg L^?1. This is the first study that demonstrates the high Cd uptake capacity of biogenic elemental selenium nanoparticles, of 176.8 mg g^?1, when compared to that of traditional adsorbents such as carboxyl-functionalized activated carbon, of 13.5 mg g^?1. An additional benefit is the easy solid–liquid separation by gravity settling due to coagulation of Cd-loaded biogenic elemental selenium nanoparticles.     

Artificial neural network modeling of the river water quality—A case study

The paper describes the training, validation and application of artificial neural network (ANN) models for computing the dissolved oxygen (DO) and biochemical oxygen demand (BOD) levels in the Gomti river (India). Two ANN models were identified, validated and tested for the computation of DO and BOD concentrations in the Gomti river water. Both the models employed eleven input water quality variables measured in river water over a period of 10 years each month at eight different sites. The performance of the ANN models was assessed through the coefficient of determination (R²) (square of the correlation coefficient), root mean square error (RMSE) and bias computed from the measured and model computed values of the dependent variables. Goodness of the model fit to the data was also evaluated through the relationship between the residuals and model computed values of DO and BOD. The model computed values of DO and BOD by both the ANN models were in close agreement with their respective measured values in the river water. Relative importance and contribution of the input variables to the model output was evaluated through the partitioning approach. The identified ANN models can be used as tools for the computation of water quality parameters.     

Size distribution and source identification of total suspended particulate matter and associated heavy metals in the urban atmosphere of Delhi

A study of the atmospheric particulate size distribution of total suspended particulate matter (TSPM) and associated heavy metal concentrations has been carried out for the city of Delhi. Urban particles were collected using a five-stage impactor at six sites in three different seasons, viz. winter, summer and monsoon in the year 2001. Five samples from each site in each season were collected. Each sample (filter paper) was extracted with a mixture of nitric acid, hydrochloric acid and hydrofluoric acid. The acid solutions of the samples were analysed in five-particle fractions by atomic absorption spectrometry (AAS). The impactor stage fractionation of particles shows that a major portion of TSPM concentration is in the form of PM0.7 (i.e. <0.7microm). Similarly, the most of the metal mass viz. Mn, Cr, Cd, Pb, Ni, and Fe are also concentrated in the PM0.7 mode. The only exceptions are size distributions pertaining to Cu and Ca. Though, Cu is more in PM0.7 mode, its presence in size intervals 5.4-1.6microm and 1.6-0.7microm is also significant, whilst in case of Ca there is no definite pattern in its distribution with size of particles. The average PM10.9 (i.e. <10.9microm) concentrations are approximately 90.2%+/-4.5%, 81.4%+/-1.4% and 86.4%+/-9.6% of TSPM for winter, summer and monsoon seasons, respectively. Source apportionment reveals that there are two sources of TSPM and PM10.9, while three and four sources were observed for PM1.6 (i.e. <1.6microm) and PM0.7, respectively. Results of regression analyses show definite correlations between PM10.9 and other fine size fractions, suggesting PM10.9 may adequately act as a surrogate for both PM1.6 and PM0.7, while PM1.6 may adequately act as a surrogate for PM0.7.     

Assessment of indoor air concentrations of VOCs and their associated health risks in the library of Jawaharlal Nehru University,New Delhi

The present work investigated the levels of total volatile organic compounds (TVOC) and benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX) in different microenvironments in the library of Jawaharlal Nehru University in summer and winter during 2011–2012. Carcinogenic and non-carcinogenic health risks due to organic compounds were also evaluated using US Environmental Protection Agency (USEPA) conventional approaches. Real-time monitoring was done for TVOC using a data-logging photo-ionization detector. For BTEX measurements, the National Institute for Occupational Safety and Health (NIOSH) standard method which consists of active sampling of air through activated charcoal, followed by analysis with gas chromatography, was performed. Simultaneously, outdoor measurements for TVOC and BTEX were carried out. Indoor concentrations of TVOC and BTEX (except benzene) were higher as compared to the outdoor for both seasons. Toluene and m/p-xylene were the most abundant organic contaminant observed in this study. Indoor to outdoor (I/O) ratios of BTEX compounds were generally greater than unity and ranged from 0.2 to 8.7 and 0.2 to 4.3 in winter and summer, respectively. Statistical analysis and I/O ratios showed that the dominant pollution sources mainly came from indoors. The observed mean concentrations of TVOC lie within the second group of the Molhave criteria of indoor air quality, indicating a multifactorial exposure range. The estimated lifetime cancer risk (LCR) due to benzene in this study exceeded the value of 1?×?10^?6 recommended by USEPA, and the hazard quotient (HQ) of non-cancer risk came under an acceptable range.     

Application of ameliorated wood pulp to recover Cd(II), Pb(II), and Ni(II) from e-waste

In this study, dl-malic acid and hydrogen peroxide were used as leaching agents to remove metals from e-waste (printed-circuit boards) and itaconic acid-grafted poly(vinyl alcohol)-encapsulated wood pulp (IA-g-PVA-en-WP) to uptake metals from leachate with high proficiency [11.63 mg g^?1; 93.03 % for Cd(II), 11.90 mg g^?1; 95.18 % for Pb(II), and 12.14 mg g^?1; 97.08 % for Ni(II)]. Metals were recovered from the loaded biosorbent by desorption studies. The standard analytical techniques, such as elemental analysis, Fourier-transform-infrared spectroscopy, scanning electron microscopy, atomic force microscopy, and thermogravimetric analysis, were used to characterize the recovering agent (biosorbent). At equilibrium, the metal uptake data were fitted to Langmuir and D–R isotherms (R ² > 0.99) significantly, revealing, the homogeneous distribution of active sites on biosorbent’s backbone. The possible mechanism appeared to be ion exchanges of metal ions with H⁺ together with binding over functionalities (COO^?). Dimensionless equilibrium parameter (R _L) showed the favourability of metal uptake at lower concentration, while mean adsorption energy (E) certified the physical binding of metal on functionalities which was further confirmed by sticking probability and activation energy parameters. Reusability studies were also conducted to state the performance of biosorbent.