The life cycle of diesel fuel in non-passenger vehicles was assessed for all registered vehicles in Qatar as of November 2017. The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model was used as a source of normalized data to evaluate diesel fuel emissions for all non-passenger vehicle categories. This work aims at estimating the emissions from all non-passenger diesel vehicles in Qatar and evaluating the impact of the fuel life cycle assessment. The emissions of CO2, NOx, CO, SO2, VOC, black carbon (BC), organic carbon, fine particulates PM2.5, and coarse particulates PM10 were evaluated. SO2 emissions were found to be dominant during the well to pump (WTP) stage of the life cycle assessment (LCA) process, while the pump to wheel (PTW) stage was found to be dominated by CO, VOC, PM10, PM2.5, and BC emissions. NOx and organic carbon emissions were virtually the same during both stages. Total greenhouse gas emissions amounted to 5367 kt of CO2 equivalent (CO2-eq) in 2017 as compared with that in 2014 (5277 kt), the only reported value in Qatar for transportation emissions. In addition, several mitigation strategies are proposed to ensure sustainability in the transport sector and to minimize the negative impact of diesel fuel emissions in the country.

The aim of this study was to determine the levels of Cd, As, Hg, Pb, and Cr in the edible part of eleven most consumed fish species collected from the north-east coast of Persian Gulf, Iran, during 2017. An inductively coupled plasma atomic emission spectroscopy (ICP-AES) instrument was used to measure the concentration of heavy metals. The results were compared within acceptable limits for human consumption set by various health institutions. The order of heavy metals about total accumulation was Cr>As>Pb> Cd> Hg. The mean heavy metals concentrations of fish species muscle decreased in the order of Acanthopagrus latus> Planiliza subviridis> Lutjanus lemniscatus > Alectis indica> Epinephelus areolatus> Otolithes ruber> Epinephelus chlorostigma> Lethrinus crocineus> Euryglossa orientalis > Cynoglossus arel > Grammoplites suppositus. Probably the difference in the concentration of metals between samples depends on fish species, diet, and habitat. These species were declared to exhibit a low probability of causing non-cancerous diseases. The comparison of the accumulation and hazard risk of consuming the five heavy metals existing in the eleven species that were sampled from the coasts of Khuzestan, Maah-shar Harbour, with the WHO and USEPA guidelines showed that although consuming these fish species does not threaten the consumers' health, pregnant women and children should be cautious about consuming them. The HI was calculated for 70 kg body weight of adults and 14.5 kg body weight of children. The amount of optimal consumption is different for different weights of consumers.

Lead-acid battery recycling is one of the organized process which helps in overcoming the demand of lead for the production of the storage batteries. During recycling, a large amount of effluent is generated which contains lead beyond the permissible limit and harmful for the environment. This effluent was treated by adsorption as an alternative technique by using another waste (pressmud) as an adsorbent obtained from the sugar industry. Properties of the pressmud were determined through Fourier transform infrared spectroscopy, scanning electron microscope and X-ray diffraction analysis. Taguchi method L16 orthogonal array (4^3) was used for batch adsorption study for the parameters, initial pH, adsorbent dose and contact time. The optimum value for the adsorption of Pb(II) onto pressmud was found at effluent pH 4.5, adsorbent dose 1.0 g/50mL and time 240 min from the Signal-to-Noise ratio analysis. Kinetic and isotherm studies were also carried out to understand the mechanism of adsorption. Langmuir isotherm fitted best to the experimental data with R2=0.994 and kinetics of adsorption followed the pseudo-second-order model with R2=0.993.

This study on the heavy metal content of a local drinking water source in South-east Nigeria was carried out in 3 sampling stations between May 2019 and October 2019. Pollution indices and health risk assessment for non-carcinogenic were used to check the water’s suitability for human consumption. The indices were heavy metal pollution index (HPI) and Contamination Index (Cd). Eight metals were evaluated with standard methods and compared with Nigerian and WHO drinking water standards. Some metals like iron, lead and cadmium exceeded the recommended limits. The stations Heavy Metal Pollution Index ranged between 511.4 and 512.4 while the monthly values ranged between 279.8 and 547.6; all exceeding the threshold value of 100. Contamination Index ranged between 3.12 and 3.32 (stations) and -0.80 to 4.80 (month) indicating high contamination potential and low to high contamination potentials respectively. All the hazard indices also exceeded one (1). Stations 1 and 2 were higher in all the indices. All the indices were linked the high values of iron, lead and cadmium, influenced by sand mining activities. The pollution indices and Health Risk Assessment converged to show that the waters of Iyiakwu River are not fit for human consumption. The children are more vulnerable since it the main source of drinking water in the area.

Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily CO concentration as a function of 12 input variables. Then, forward selection (FS) technique was applied to reduce the number of input variables. After converting 12 input variables to 7 using the FS, they were fed to SVM models (FS-(-SVM) and FS-(-SVM)). Finally, a comparison among SVM models operation and previously developed techniques, i.e. classical regression model and artificial intelligent methods such as ANN and adaptive neuro-fuzzy inference system (ANFIS) was carried out. Determination of coefficient (R2) and mean absolute error (MAE) for -SVM (-SVM) were 0.87 (0.40) and 0.87 (0.41), respectively, while they were 0.90 (0.39) and 0.91 (0.35) for ANN and ANFIS, respectively. Results of developed SVM models indicated that both FS-(-SVM) and FS-(-SVM) regression techniques were superior. Furthermore, it was founded that the performance of FS-(-SVM) and FS-(-SVM) models were generally a bit better than the best FS-ANFIS and FS-ANN solutions for short term forecasting of CO concentrations.

Emerging contaminants are distributed in to the environment from various anthropogenic activities. These Emerging contaminants (ECs) are mainly composed of products, such as pharmaceuticals, personal care products (PCPs), surfactants, plasticizers, pesticides etc. The present conventional system of waste treatment are not designed to treat these contaminants. Complex structure of these pollutants and their existence at low concentration makes them untraceable and hence found to be difficult in removal of these by present waste treatment. These chemicals are considered as threat to human health and environment. Therefore, disposal and treatment of these chemicals of emerging concern have been a key concern in the field of water treatment and its reuse. Biosensors can be used for biomonitoring of these contaminants with of biological system. Bioremediation plays an important role in the treatment of these pollutants of emerging concern. This review discusses about the sources, effects, and challenges in biomonitoring and bioremediation related to these emerging contaminants.

The human health impacts caused due to exposure to criteria outdoor air pollutants PM2.5, PM10 and NO2 were assessed in present study. The human health effects associated with exposure to atmospheric air pollution in NCT Delhi were estimated utilizing the AirQ+ v1.3 software tool integrated with Ri-MAP during the study period 2013-2018 considering 80% of the whole population subjected to air pollution exposure. Taking into account the World Health Organization (WHO) (2016) guidelines, the inter-annual average concentrations of PM2.5, PM10, and NO2, concentration response relationships and population attributable fraction (AF) or impact fraction (IF) concepts were adopted. The excess number of cases (ENCs) of Mortality (all) natural cases 30+ years, acute lower respiratory infection (ALRI), lung cancer (LC), ischaemic heart disease (IHD), stroke, incidence of chronic bronchitis in children, postneonatal infant mortality, chronic obstructive pulmonary disease (COPD), prevalence of bronchitis in children, incidence of asthma symptoms in asthmatic children in the year 2013 were 48332, 2729, 5645, 26853, 22737, 120754, 34510, 5125, 9813, 3054, 17203 and 682, respectively. Within half of a decade i.e. in year 2018, the ENCs of Mortality (all) natural cases 30+ years, ALRI, COPD, LC, IHD, stroke, incidence of chronic bronchitis in children, postneonatal infant mortality, prevalence of bronchitis in children, incidence of asthma symptoms in asthmatic children increased significantly and were 72254, 3471, 6547, 7568, 32358, 28233, 150110, 50810, 9019, 862, 29570 and 1189, respectively.

With an increase in the global pollution, there is requirement for an alternative to the fossil fuels. Non-edible vegetable oils are highly promising for producing liquid fuels like diesel. Jatropha is a potential feedstock for biodiesel, currently utilized in India and many parts of the world. The optimization of reaction conditions such as temperature, time, catalyst and molar ratio for biodiesel production is important in reactor design. However, oils have characteristics reaction properties for optimum yield. Therefore, there is the need to identify such parameters in Jatropha oil ethyl esters production. Preparation of biodiesel from Jatropha oil ethyl esters using conventional homogeneous process. Optimization of Jatropha ethyl esters using Response surface methodology is done and data so obtained are fed to the design experiment software for analysis. The Jatropha ethyl esters yield was 92.62%. Maximum production of Jatropha oil ethyl ester was achieved with the process parameters viz molar ratio 8.5, reaction time 89.67min, reaction temperature 70.1°C and catalyst.0.62wt%.

The aim of this study was to compare the selected aquatic plants ability to remove nitrate from wastewater. Excess of these nutrients in water can directly affect human health (methemoglobinaemia) or indirectly through the products of secondary pollution include eutrophication. Negative impact of nutrients excess in surface water often causes the destruction of water ecosystems, and therefore, common substances of these elements must be monitored and managed. Spectrophotometric technique was commonly used for quick and simple analyses of nutrients in waste water. There are calibration curves for each nutrient and for the determination of their concentration. Phytotechnology is one of the biological wastewater treatment methods or processes to eliminate nitrate contaminant from aquatic system. So as to avoid the eutrophic formation of fresh water and to determine the efficiency of nitrate utilization by specific aquatic plants which include Utricularia aurea and Salvinia molesta were collected from a eutrophic lake at Theerthamkara, Kerala. The samples were allowed to grow in nitrate solution for about one month at different concentrations. The optical density (OD) of nitrate solution at 410 nm was measured on alternative days of the experiment by using UV spectrophotometer. After 33 days of treatment periods, the maximum amount of nitrate removed in terms of percentage was found to be 95% by Utricularia aurea and 92% by Salvinia molesta at 100 ppm nitrate concentration. The results revealed that the aquatic plant (carnivorous) based system of phytotechnology was productively removed the nitrate load from the synthetic wastewater containing nitrate.