Editorial

3 pages, 219 KiB

Open AccessEditorial

Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution

by Lucica Barbeş and Alina Bărbulescu

Toxics 2022, 10(5), 261; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics10050261 - 18 May 2022

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Nowadays, ambient air pollution levels and trends have become a topic of interest worldwide because primary atmospheric pollutants (APPs) are risk factors for the population and ecosystems [...] Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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15 pages, 808 KiB

Open AccessFeature PaperArticle

Impact of Soil Pollution on Melliferous Plants

by Alina Bărbulescu, Lucica Barbeș and Cristian Ştefan Dumitriu

Toxics 2022, 10(5), 239; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics10050239 - 09 May 2022

Cited by 6 | Viewed by 2014

Abstract

This study aims at providing bee products and derivatives of medicinal plant consumers with a multifaceted perspective on mineral elements occurring in the soils of two forest zones in the vicinity of North Dobrogea (Romania) by (1) analyzing the pollution levels of the [...] Read more.

This study aims at providing bee products and derivatives of medicinal plant consumers with a multifaceted perspective on mineral elements occurring in the soils of two forest zones in the vicinity of North Dobrogea (Romania) by (1) analyzing the pollution levels of the soils at three sites (denoted by DS, PH, and ST) in the study region, using different indicators; (2) providing the results of the transfer of metals from the soil to Sambucus nigra L. (SnL), Hypericum perforatum (Hp), and Tilia tomentosa (Tt). The statistical analysis of the series collected at these locations shows no difference between the elements’ concentrations (as a whole). Still, the values of the geo-accumulation index (I_geo) classify the soils as being soils that are moderately to highly contaminated with Cd (and not contaminated with Cu, Mn, or Zn) with respect to the European background values. The cumulative indices—the degree of contamination (DC), the pollution load index (PLI), the Nemerow integrated pollution index (NIPI), and the potential ecological risk index (PERI) indicated the highest contamination in DS (which is a tourist area). To assess the accumulation of different metals in plants, the enrichment factors (EF) were computed. In over 75% of cases, EF was above 1, indicating a high degree of enrichment with different metals. The highest values were those for Cu (41.10 in DS for SnL), and Cd (12.85 in DS for Tt). The results showed that there were different degrees of accumulation between microelements and trace elements in the plants. Tt acted as a bioaccumulator for almost all of the studied elements (K, Mg, Na, Fe, Mn, Cu, Zn, and Cd). Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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44 pages, 42980 KiB

Open AccessArticle

Neuro-Particle Swarm Optimization Based In-Situ Prediction Model for Heavy Metals Concentration in Groundwater and Surface Water

by Kevin Lawrence M. De Jesus, Delia B. Senoro, Jennifer C. Dela Cruz and Eduardo B. Chan

Toxics 2022, 10(2), 95; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics10020095 - 18 Feb 2022

Cited by 15 | Viewed by 2609

Abstract

Limited monitoring activities to assess data on heavy metal (HM) concentration contribute to worldwide concern for the environmental quality and the degree of toxicants in areas where there are elevated metals concentrations. Hence, this study used in-situ physicochemical parameters to the limited data [...] Read more.

Limited monitoring activities to assess data on heavy metal (HM) concentration contribute to worldwide concern for the environmental quality and the degree of toxicants in areas where there are elevated metals concentrations. Hence, this study used in-situ physicochemical parameters to the limited data on HM concentration in SW and GW. The site of the study was Marinduque Island Province in the Philippines, which experienced two mining disasters. Prediction model results showed that the SW models during the dry and wet seasons recorded a mean squared error (MSE) ranging from 6 × 10⁻⁷ to 0.070276. The GW models recorded a range from 5 × 10⁻⁸ to 0.045373, all of which were approaching the ideal MSE value of 0. Kling–Gupta efficiency values of developed models were all greater than 0.95. The developed neural network-particle swarm optimization (NN-PSO) models for SW and GW were compared to linear and support vector machine (SVM) models and previously published deterministic and artificial intelligence (AI) models. The findings indicated that the developed NN-PSO models are superior to the developed linear and SVM models, up to 1.60 and 1.40 times greater than the best model observed created by linear and SVM models for SW and GW, respectively. The developed models were also on par with previously published deterministic and AI-based models considering their prediction capability. Sensitivity analysis using Olden’s connection weights approach showed that pH influenced the concentration of HM significantly. Established on the research findings, it can be stated that the NN-PSO is an effective and practical approach in the prediction of HM concentration in water resources that contributes a solution to the limited HM concentration monitored data. Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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13 pages, 1489 KiB

Open AccessArticle

Heavy Metal Assessments of Soil Samples from a High Natural Background Radiation Area, Indonesia

by Eka Djatnika Nugraha, June Mellawati, Wahyudi, Chutima Kranrod, Makhsun, Hirofumi Tazoe, Haeranah Ahmad, Masahiro Hosoda, Naofumi Akata and Shinji Tokonami

Toxics 2022, 10(1), 39; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics10010039 - 15 Jan 2022

Cited by 7 | Viewed by 3260

Abstract

Mamuju, Indonesia, is an area with high natural background radiation. This study assesses heavy metal content in soil samples from this area to determine the level of public and environmental hazard it presents. This study analyzes natural radionuclide elements using high purity germanium [...] Read more.

Mamuju, Indonesia, is an area with high natural background radiation. This study assesses heavy metal content in soil samples from this area to determine the level of public and environmental hazard it presents. This study analyzes natural radionuclide elements using high purity germanium (HPGe) gamma spectrometry and performs heavy metals analysis using a flame atomic absorption spectrometry (FAAS). Moreover, pollution indices and descriptive analyses were used to assess heavy metal contamination in the environment and the correlation between heavy metals and radionuclides. The results demonstrate that soil samples in several areas of Mamuju contain a high concentration of the natural radionuclides ²²⁶Ra and ²³²Th, and that heavy metal concentrations in the soil decrease in the sequence Zn > Pb > Cr > Cu > Ni > Cd. This study revealed that soil samples from Mamuju are moderately contaminated. There was a strong positive relationship between ²²⁶Ra, ²³²Th, ambient dose equivalent rate, and Pb. Ecological risk index (RI) and cumulative pollution index (IPI) values in Mamuju are 2.05 and 125, respectively, which are possible hazards to human health as a result. Pb concentration in the Mamuju soil samples ranged from 109 to 744 mg kg⁻¹, exceeding the worldwide average of 27 mg kg⁻¹. Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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18 pages, 3887 KiB

Open AccessArticle

Assessing the Water Pollution of the Brahmaputra River Using Water Quality Indexes

by Alina Barbulescu, Lucica Barbes and Cristian Stefan Dumitriu

Toxics 2021, 9(11), 297; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics9110297 - 06 Nov 2021

Cited by 8 | Viewed by 8570

Abstract

Water quality is continuously affected by anthropogenic and environmental conditions. A significant issue of the Indian rivers is the massive water pollution, leading to the spreading of different diseases due to its daily use. Therefore, this study investigates three aspects. The first one [...] Read more.

Water quality is continuously affected by anthropogenic and environmental conditions. A significant issue of the Indian rivers is the massive water pollution, leading to the spreading of different diseases due to its daily use. Therefore, this study investigates three aspects. The first one is testing the hypothesis of the existence of a monotonic trend of the series of eight water parameters of the Brahmaputra River recorded for 17 years at ten hydrological stations. When this hypothesis was rejected, a loess trend was fitted. The second aspect is to assess the water quality using three indicators (WQI)–CCME WQI, British Colombia, and a weighted index. The third aspect is to group the years and the stations in clusters used to determine the regional (spatial) and temporal trend of the WQI series, utilizing a new algorithm. A statistical analysis does not reject the hypothesis of a monotonic trend presence for the spatially distributed data but not for the temporal ones. Hierarchical clustering based on the computed WQIs detected two clusters for the spatially distributed data and two for the temporal-distributed data. The procedure proposed for determining the WQI temporal and regional evolution provided good results in terms of mean absolute error, root mean squared error (RMSE), and mean absolute percentage error (MAPE). Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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17 pages, 4539 KiB

Open AccessArticle

Full Factorial Design for Gold Recovery from Industrial Solutions

by Maria Mihăilescu, Adina Negrea, Mihaela Ciopec, Petru Negrea, Narcis Duțeanu, Ion Grozav, Paula Svera, Cosmin Vancea, Alina Bărbulescu and Cristian Ștefan Dumitriu

Toxics 2021, 9(5), 111; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics9050111 - 20 May 2021

Cited by 14 | Viewed by 2757

Abstract

Gold is one of the precious metals with multiple uses, whose deposits are much smaller than the global production needs. Therefore, extracting maximum gold quantities from industrial diluted solutions is a must. Am-L-GA is a new material, obtained by an Amberlite XAD7-type commercial [...] Read more.

Gold is one of the precious metals with multiple uses, whose deposits are much smaller than the global production needs. Therefore, extracting maximum gold quantities from industrial diluted solutions is a must. Am-L-GA is a new material, obtained by an Amberlite XAD7-type commercial resin, functionalized through saturation with L-glutamic acid, whose adsorption capacity has been proved to be higher than those of other materials utilized for gold adsorption. In this context, this article presents the results of a factorial design experiment for optimizing the gold recovery from residual solutions resulting from the electronics industry using Am-L-GA. Firstly, the material was characterized using atomic force microscopy (AFM), to emphasize the material’s characteristics, essential for the adsorption quality. Then, the study showed that among the parameters taken into account in the analysis (pH, temperature, initial gold concentration, and contact time), the initial gold concentration in the solution plays a determinant role in the removal process and the contact time has a slightly positive effect, whereas the pH and temperature do not influence the adsorption capacity. The maximum adsorption capacity of 29.27 mg/L was obtained by optimizing the adsorption process, with the control factors having the following values: contact time ~106 min, initial Au(III) concentration of ~164 mg/L, pH = 4, and temperature of 25 °C. It is highlighted that the factorial design method is an excellent instrument to determine the effects of different factors influencing the adsorption process. The method can be applied for any adsorption process if it is necessary to reduce the number of experiments, to diminish the resources or time consumption, or for expanding the investigation domain above the experimental limits. Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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17 pages, 1878 KiB

Open AccessEditor’s ChoiceArticle

Assessment of Metals Concentrations in Soils of Abu Dhabi Emirate Using Pollution Indices and Multivariate Statistics

by Yousef Nazzal, Alina Bărbulescu, Fares Howari, Ahmed A. Al-Taani, Jibran Iqbal, Cijo M. Xavier, Manish Sharma and Cristian Ștefan Dumitriu

Toxics 2021, 9(5), 95; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics9050095 - 25 Apr 2021

Cited by 31 | Viewed by 3357

Abstract

The aim of this study was twofold. Firstly, we performed a land capability class determination of the agricultural soils from the Abu Dhabi Emirate, the United Arab Emirates, based on the concentrations of 17 chemical elements determined in the soil samples collected from [...] Read more.

The aim of this study was twofold. Firstly, we performed a land capability class determination of the agricultural soils from the Abu Dhabi Emirate, the United Arab Emirates, based on the concentrations of 17 chemical elements determined in the soil samples collected from 84 locations. Secondly, we assess the soil pollution with different metals, using several pollution indices. The results of Principal Component Analysis (PCA) shows that four principal components (PCs) are responsible for describing the total metals concentrations’ variance, the highest contribution on PC1 being that of Mn, and Cr, on PC2 that of Fe, on PC3 that of Cu, and on PC4 that of Al. After determining the optimal number of clusters, we classified the sites into three clusters, while the studied metals were grouped function on their concentrations. Then, we used five indices to assess the pollution level of the soil at the study sites and in the clusters. The geo—accumulation index (I_geo) indicates uncontamination/moderately contamination with Cu in cluster 1, uncontaminated/moderately contaminate soils with Cd, Cu, and Ni in cluster 2, and uncontaminated/moderately contaminated soil with Cu and moderately contaminated with Pb, Zn, and Ni in cluster 3. By comparison, the enrichment factors overestimate the pollution of the studied sites. The pollution load index (PLI) indicates a baseline level of pollution at 14 sites and the deterioration of the soil quality at four sites. The Nemerow pollution index provides similar results as PLI. Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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12 pages, 2345 KiB

Open AccessEditor’s ChoiceArticle

Contamination Assessment of Heavy Metals in Agricultural Soil, in the Liwa Area (UAE)

by Ahmed A. Al-Taani, Yousef Nazzal, Fares M. Howari, Jibran Iqbal, Nadine Bou Orm, Cijo Madathil Xavier, Alina Bărbulescu, Manish Sharma and Cristian-Stefan Dumitriu

Toxics 2021, 9(3), 53; https://0-doi-org.brum.beds.ac.uk/10.3390/toxics9030053 - 10 Mar 2021

Cited by 41 | Viewed by 5035

Abstract

The Liwa area is a primary food production area in the United Arab Emirates (UAE) and has intensively been used for agriculture. This study investigates the pollution levels with heavy metals in agricultural soils from the Liwa area. Thirty-two soil samples were analyzed [...] Read more.

The Liwa area is a primary food production area in the United Arab Emirates (UAE) and has intensively been used for agriculture. This study investigates the pollution levels with heavy metals in agricultural soils from the Liwa area. Thirty-two soil samples were analyzed for Mn, Zn, Cr, Ni, Cu, Pb, Cd, Co, and As. Results revealed that heavy metal levels varied in the ranges 220.02–311.21, 42.39–66.92, 43.43–71.55, 32.86–52.12, 10.29–21.70, 2.83–8.84, 0.46–0.69, 0.03–0.37 mg/kg for Mn, Zn, Cr, Ni, Cu, Pb, Cd, Co, and As, respectively. All samples presented low As concentrations with an average of 0.01 mg/kg. The variations in bulk metal contents in the soil samples were related to multiple sources, including agrochemicals, atmospheric dust containing heavy metals, and traffic-related metals. Enrichment factor analysis indicates that Cd, Ni, Zn, and Cr were highly enriched in soils, and they could originate from non-crustal sources. Based on the geo-accumulation index (I_geo), the soil samples appeared uncontaminated with Mn, Cr, Zn, Pb, Co, As, Cu, uncontaminated to moderately contaminated with Ni and moderately contaminated with Cd. The contamination factors suggest low contamination, except for Ni, which showed moderate contamination. The average pollution load index (PLI) revealed unpolluted to low pollution of all soil samples. The ecological risk assessment (PERI) showed that all heavy metals posed a low risk, except for Cd which exhibited a high ecological risk. Full article

(This article belongs to the Special Issue Statistical Assessment, Modeling, and Mitigation of Water and Soil Pollution)

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