Assessment of groundwater vulnerability in an urban area: a comparative study based on DRASTIC, EBF, and LR models.

The groundwater vulnerability assessment is known as a useful tool for predicting and prevention of groundwater pollution. This study targets the DRASTIC, evidential belief function (EBF), and logistic regression (LR) models to assess vulnerability in Kabul aquifers, Afghanistan Country. The growth of urban sprawl, groundwater overexploitation, and lack of suitable municipal sewage systems as anthropogenic sources have been the main potential to increase groundwater contaminants such as nitrate in the study area. The vulnerability map has been developed based on various effective factors including altitude, slope (percentage rise), aspect, curvature, land-use type, drainage density, distance from river, annual mean precipitation, net recharge, geology/lithology units, the impact of the vadose zone, aquifer media, depth to water (unsaturated zone), saturated zone, drawdown, and hydraulic conductivity. To identify groundwater pollution, the spatial variation of nitrate concentration data in 2018 was considered indication of groundwater pollution. Based on descriptive statistics, the value of 2.65 mg/l (the median of the pixel values of nitrate map) was selected as a threshold to differentiate the occurrence and non-occurrence of pollution. The groundwater quality data were selected and randomly divided into two datasets for training and validation, including 70% and 30%, respectively. The success-rate and prediction-rate curves were computed based on the receiver operating characteristic (ROC) curve and the area under the curve (AUC) to estimate the efficiency of models. The ROC-AUC of success rates for EBF, LR, and DRASTIC models were estimated to be 67%, 66%, and 52%, respectively. Moreover, the ROC-AUC of the prediction rates of the EBF, LR, and DRASTIC models were obtained 61%, 63%, and 55%, respectively. Based on correlation between mean nitrate concentration and the mean vulnerability indexes in each model, the EBF model is the most compatible with the current developed vulnerability zones as the role of mankind in changing the environment in real conditions in comparison to LR and DRASTIC models.

Characteristics, distribution, source apportionment, and potential health risk assessment of polycyclic aromatic hydrocarbons in urban street dust of Kerman metropolis, Iran.

In this study, the concentrations of street dust-bound polycyclic aromatic hydrocarbons (PAHs) in Kerman metropolis as a typical arid urban area were determined to investigate the contamination, molecular composition, toxicity, and sources of PAHs. Sixteen individual PAHs on the United States Environmental Protection Agency priority list were analyzed using gas chromatography-mass spectrometry in street dust samples from 30 sites. ∑PAHs ranged between 165 and 5314.7 µg·kg-1 with a mean of 770.8 µg·kg-1. The most abundant individual PAHs were fluoranthene, phenanthrene, pyrene, and chrysene, respectively. High molecular weight PAHs (4-6 rings) made 74.8% of ∑PAHs mass and were dominant in all sites. Source apportionment was performed using ring classification, diagnostic ratios, and principal component analysis-multiple linear regression. The results indicated that primary contributors of PAHs in the street dust of Kerman could be liquid fossil fuel combustion, natural gas combustion, and petrogenic sources, accounting for 82.4%, 11.5%, and 6.1%, respectively. The calculated incremental lifetime cancer risk is 8.13 × 10-4 for children and 6.27 × 10-4 for adults. Hence, both children and adults in Kerman are potentially exposed to a high carcinogenic risk via ingestion and dermal contact.