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Water and Soil Pollution Restoration
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Water and Soil Pollution Restoration

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Soil and Water".

Deadline for manuscript submissions: closed (10 August 2023) | Viewed by 22859

Special Issue Editors

Dr. Patrizia Brunetti

E-Mail Website
Guest Editor
IBPM Institute of Molecular Biology and Pathology, National Research Council, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
Interests: mechanisms accumulation; heavy metals in soil
Special Issues, Collections and Topics in MDPI journals
Dr. Giuseppe Capobianco

E-Mail Website
Guest Editor
Department of Chemical Materials, Environmental Engineering, Sapienza University of Rome, Rome, Italy
Interests: asbestos; phytoremediations; heavy metals; arsenic; pteris vittata; microplastics; water pollution; soil pollution; X-ray fluorescence (XRF); hyperspectral imaging (HSI)

Special Issue Information

Dear Colleagues,

Good quality of water and soil is essential for human health, to sustain the biodiversity of aquatic and soil ecosystems and to ensure healthy agriculture and food production.

For certain contaminants, such as arsenic, long-term exposure even to small quantities can lead to serious health problems over time.

We are pleased to invite you to submit research contributions relevant but not limited to the monitoring and removal or containment or treatment of different inorganic and organic contaminants such as heavy metal(oid)s, microplastics, toxins or pesticides from different matrices such as water soil, sludges or wastewater, which still remain a challenge.

Much progress has been made toward achieving physicochemical or nature-based solutions to monitor fast, manage, and remove pollutants, but many efforts will have to be made.

This Special Issue aims to provide recent research advancements in soil and water quality monitoring and decontamination by developing sustainable and cost-effective technologies, which are the main way to achieve the Green Deal’s “zero pollution “ambition.

We look forward to receiving your contributions.

Dr. Patrizia Brunetti
Dr. Giuseppe Capobianco
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biotechnology
  • phytoremediations
  • phytodepuration
  • fast pollutant monitoring
  • physicochemical remediation

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Published Papers (7 papers)

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Research

19 pages, 1361 KiB  
Article
Elucidating the Potential of Dye-Degrading Enterobacter cloacae ZA14 for Cultivation of Solanum lycopersicum Plants with Textile Effluents
by Zainab Naseem, Muhammad Naveed, Muhammad Imran, Muhammad Saqlain, Muhammad Asif, Mohsin Bashir, Saud Alamri, Manzer H. Siddiqui, Martin Brtnicky and Adnan Mustafa
Water 2023, 15(17), 3163; https://doi.org/10.3390/w15173163 - 4 Sep 2023
Cited by 6 | Viewed by 2346
Abstract
The presence of textile effluents in water bodies is a matter of concern due to toxicity caused by textile dyes, associated heavy metals and salts. Endophytic bacteria have been reported to reduce the phytotoxicity of textile wastewater (TWW) and improve crop potential. The [...] Read more.
The presence of textile effluents in water bodies is a matter of concern due to toxicity caused by textile dyes, associated heavy metals and salts. Endophytic bacteria have been reported to reduce the phytotoxicity of textile wastewater (TWW) and improve crop potential. The purpose of this study was to sequester dye-degrading endophytic bacteria with the ability to remediate textile effluents and promote tomato plant growth. Six strains showing the highest dye decolorization were screened from the dye decolorization assay. Selected strains also showed plant growth-promoting traits and improved tolerance to heavy metals and salt. The results revealed that Enterobacter cloacae ZA14 showed the highest decolorization (90%) using 200 mg L−1 of dye concentration, high minimum inhibitory concentration (MIC) of heavy metals and improved salt tolerance. In a sand culture experiment, the T4 (25% TWW (consisting of 25 mL TWW with 75 mL distilled water) + ZA14) treatment showed an increase in root length (9.3%), shoot length (5.5%), improved chlorophyll contents (7%), and membrane stability index (5%), whereas maximum oxidative stress was indicated by T10 (100% TWW) with an increase of 122% in MDA and 80% in H2O2 as compared to T1. An increase of 41% in ascorbate peroxidase (APX), 37% increase in sodium oxide dismutase (SOD), 27% in peroxidase (POD), and 24% in catalase (CAT) by T4 treatment showed the least production of antioxidants as compared to plants receiving 50%, 75% and 100% TWW along with ZA14 application. These results suggested that 25% TWW is beneficial for crop production with the use of an appropriate approach like Enterobacter cloacae ZA14 to mitigate textile effluents efficiently and to improve crop production. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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Figure 1

Figure 1
<p>Potential of various endophytic strains to decolorize direct blue (200 mg L<sup>−1</sup>) azo dye isolated from (<b>A</b>) textile wastewater sample and (<b>B</b>) plant sample. Data showed means of three replicates at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 2
<p>The combined effect of endophytic strains and textile wastewater on (<b>a</b>) chlorophyll content (SPAD value), (<b>b</b>) relative water content and (<b>c</b>) membrane stability index of tomato plants. In each figure, the data is mean of three replicates ± SE and the bars sharing similar letters do not differ significantly at <span class="html-italic">p</span> &lt; 0.05; T1 = control (DW); T2 = ZA14; T3 = 25% TWW; T4 = ZA14 + 25% TWW; T5 = 50% TWW; T6 = ZA14 + 50% TWW; T7 = 75% TWW; T8 = ZA14 + 75% TWW; T9 = 100 TWW; T10 = ZA14 + 100% TWW.</p> Full article ">Figure 3
<p>The combined effect of endophytic strains and textile wastewater on the production of oxidative stress markers; (<b>a</b>) MDA, (<b>b</b>) H<sub>2</sub>O<sub>2</sub>, (<b>c</b>) proline and (<b>d</b>) and glycine betaine in tomato plants. In each figure, the data is mean of three replicates ± SE and the bars sharing similar letters do not differ significantly at <span class="html-italic">p</span> &lt; 0.05; T1 = control (DW); T2 = ZA14; T3 = 25% TWW; T4 = ZA14 + 25% TWW; T5 = 50% TWW; T6 = ZA14 + 50% TWW; T7 = 75% TWW; T8 = ZA14 + 75% TWW; T9 = 100 TWW; T10 = ZA14 + 100% TWW.</p> Full article ">Figure 4
<p>Combined effect of endophytic strains and textile wastewater on production of secondary metabolites; (<b>a</b>) total flavonoids, (<b>b</b>) total phenols and (<b>c</b>) total anthocyanins in tomato plants. In each figure, the data is mean of three replicates ± SE and the bars sharing similar letters do not differ significantly at <span class="html-italic">p</span> &lt; 0.05; T1 = control (DW); T2 = ZA14; T3 = 25% TWW; T4 = ZA14 + 25% TWW; T5 = 50% TWW; T6 = ZA14 + 50% TWW; T7 = 75% TWW; T8 = ZA14 + 75% TWW; T9 = 100 TWW; T10 = ZA14 + 100% TWW.</p> Full article ">Figure 5
<p>The combined effect of endophytic strains and textile wastewater on production of antioxidants; (<b>a</b>) APX, (<b>b</b>) SOD, (<b>c</b>) POD and (<b>d</b>) and CAT in tomato plants. In each figure, the data is mean of three replicates ± SE and the bars sharing similar letters do not differ significantly at <span class="html-italic">p</span> &lt; 0.05; T1 = control (DW); T2 = ZA14; T3 = 25% TWW; T4 = ZA14 + 25% TWW; T5 = 50% TWW; T6 = ZA14 + 50% TWW; T7 = 75% TWW; T8 = ZA14 + 75% TWW; T9 = 100 TWW; T10 = ZA14 + 100% TWW.</p> Full article ">
15 pages, 5443 KiB  
Article
Multi-Analytical Approach to Evaluate Elements and Chemical Alterations in Pteris vittata Plants Exposed to Arsenic
by Giuseppe Capobianco, Maria Luisa Antenozio, Giuseppe Bonifazi, Patrizia Brunetti, Maura Cardarelli, Mariangela Cestelli Guidi, Lucilla Pronti and Silvia Serranti
Water 2023, 15(7), 1333; https://doi.org/10.3390/w15071333 - 28 Mar 2023
Cited by 5 | Viewed by 2075
Abstract
The aim of this study was the development of a new multi-analytical approach to evaluate chemical alterations and differences in the element content in relation to arsenic (As) in the As hyperaccumulator fern P. vittata. P. vittata plants were grown on two [...] Read more.
The aim of this study was the development of a new multi-analytical approach to evaluate chemical alterations and differences in the element content in relation to arsenic (As) in the As hyperaccumulator fern P. vittata. P. vittata plants were grown on two natural As-rich soils with either high or moderate As (750 and 58 mg/kg). Dried samples from plant tissues were then analysed by means of micro-energy dispersive X-ray fluorescence spectrometry (μ-XRF), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and hyperspectral imaging (HSI) with a multivariate approach. The As and micro- and macronutrients content was evaluated by μ-XRF and a significant correlation between As, potassium (K), iron (Fe), calcium (Ca) and manganese (Mn) contents were found at both moderate and high As levels. The same samples were then analysed by ATR-FTIR spectroscopy and HSI (SWIR range, 1000–2500 nm). Interestingly, by FTIR analysis it was found that the main differences between the control and the As-contaminated samples are due to the intensity of the absorption band related to polysaccharides (i.e., cellulose, hemicellulose and pectin), lignin, lipid and amide groups. The same chemical alterations were detected by an HSI analysis and all the FTIR and HSI data were validated by a PCA analysis. These results suggest a possible complexation of As ions with the amide group. Moreover, the proposed μ-XRF, HSI and ATR-FTIR combining approach could be a promising strategy to monitor in-field phytoremediation approaches by directly controlling the As content in plants. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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Figure 1

Figure 1
<p>A <span class="html-italic">P. vittata</span> plant grown in naturally As-rich soil under greenhouse conditions. The arrow indicates the pinna collected for preparing pinna powder.</p> Full article ">Figure 2
<p>Representative image of S1 and S2 samples analysed by FTIR, μ-XRF and HSI.</p> Full article ">Figure 3
<p>(<b>A</b>) FTIR spectra of S1 samples: average (on the bottom), 1° derivative spectra (in the middle) and 2° derivative spectra (on the top) at T0 (black), at T75 (blue) and at T90 (red) days. (<b>B</b>) FTIR spectra of S2 samples: average (on the bottom), 1° derivative spectra (in the middle) and 2° derivative spectra (on the top) at T0 (black), at T75 (blue) and at T90 (red) days.</p> Full article ">Figure 4
<p>Score (<b>A</b>) and loading (<b>B</b>) plots from first derivative spectra and score (<b>C</b>) and loading (<b>D</b>) plots from second derivative spectra of S1 samples, respectively. The numbers indicated in (<b>B</b>) and (<b>D</b>) correspond to the following spectral ranges: (1) 2950–2820 cm<sup>−1</sup> (C-H stretching); (2) 1770–1740 cm<sup>−1</sup> (COOH stretching/carbonyl (C=O) stretching); (3) 1680–1650 cm<sup>−1</sup> (N-H stretching and C=O stretching of amide I); (4) 1510–1450 cm<sup>−1</sup> (C=C-C aromatic ring stretching/C-C aromatic stretching (conjugated with C=O), asymmetric C-H bending from lipids, protein, lignin; (5) 1100–960 cm<sup>−1</sup> (carbonyl (C=O) stretching (fatty acid)/C-O and C-C (pectin)/C-O-C symmetric stretching/C-O, C=C and C-C-O stretching of cellulose and hemicellulose).</p> Full article ">Figure 5
<p>Score (<b>A</b>) and loading (<b>B</b>) plots from first derivative spectra and score (<b>C</b>) and loading (<b>D</b>) plots from second derivative spectra of S2 samples, respectively. The numbers indicated in (<b>B</b>) and (<b>D</b>) correspond to the following spectral ranges: (1) 2920–2820 cm<sup>−1</sup> (C-H stretching); (2) 1740–1700 cm<sup>−1</sup> (COOH stretching/carbonyl (C=O) stretching); (3) 1620–1550 cm<sup>−1</sup> (N-H stretching and C=O stretching of amide I)/carbonyl (C=O) stretching, C-C aromatic stretching, NH2 group bending/C-C aromatic ring stretching phenolic compounds, N-H bending and C-N stretching of protein; (4) 1150–900 cm<sup>−1</sup> C-C(C=O)-O stretching or C-O-C asymmetric stretching (hemicellulose) C-O bonds in the ester linkages of cutin/carbonyl (C=O) stretching (fatty acid)/C-O and C-C (pectin)/C-O-C symmetric stretching/C-O, C=C and C-C-O stretching of cellulose and hemicellulose.</p> Full article ">Figure 6
<p>Average (<b>A</b>,<b>B</b>) raw and preprocessed (<b>C</b>,<b>D</b>) spectra of samples analysed by hyperspectral imaging (HSI) in the SWIR range.</p> Full article ">Figure 7
<p>PC1–PC2 score plot (<b>A</b>,<b>B</b>) and loading plot (<b>C</b>,<b>D</b>) referred to the selected samples.</p> Full article ">Figure 8
<p>(<b>A</b>) Scheme of the samples used for calibration (Cal) and for validation (Test). (<b>B</b>) Result of the PLS-DA classification model obtained from the validation set.</p> Full article ">
19 pages, 3178 KiB  
Article
Phytoremediation Potential of Native Hyperaccumulator Plants Growing on Heavy Metal-Contaminated Soil of Khatunabad Copper Smelter and Refinery, Iran
by Raheleh Siyar, Faramarz Doulati Ardejani, Parviz Norouzi, Soroush Maghsoudy, Mohammad Yavarzadeh, Reza Taherdangkoo and Christoph Butscher
Water 2022, 14(22), 3597; https://doi.org/10.3390/w14223597 - 8 Nov 2022
Cited by 31 | Viewed by 6014
Abstract
The characterization of prospective plants is one of the critical issues in the efficiency and success of the phytoremediation process. Due to adaption and tolerance to different environmental stresses, native plant species have priority in this method. This study examined fifty plants of [...] Read more.
The characterization of prospective plants is one of the critical issues in the efficiency and success of the phytoremediation process. Due to adaption and tolerance to different environmental stresses, native plant species have priority in this method. This study examined fifty plants of five species, namely Launaea acanthodes, Artemisia sp., Cousinia congesta, Peganum harmala, and Stipa sp., growing near a smelter and refinery in Iran to identify potential species for phytoextraction and phytostabilization. Therefore, Pb, Ni, Mn, Mo, S, and Cu concentrations in sampled plants and soils were analyzed. Three different pollution indices, namely metal accumulation index (MAI), translocation factor (TF), and bioconcentration factor (BCF) were used for evaluating the metal concentrations in roots and shoots of each plant species. The results indicated that Artemisia sp., with values of 3.21, 1.09, and 1.14 for MAI, BCF, and TF, respectively, is appropriate for phytoextraction in the study area. Plants such as Launaea acanthodes and Cousinia congesta with high BCF and low TF values showed the potential for phytostabilization. Investigating the indices for different elements demonstrated that Launaea acanthodes had a BCF value greater than 1 and a TF value less than 1; therefore, this plant could be used in the phytoremediation of arsenic through the phytostabilization technique. Furthermore, copper has very low bioavailability in these plant species. In addition, these native plant species were highly capable of accumulating sulfur from the soil because the BCF and TF indices for all inspected species were higher than 1; for Launaea acanthodes, the relevant TF value was about 10. The proposed native plant could be applied in practical applications of phytoremediation for soil remediation of contaminated sites around the metal factories and mines in southeastern Iran. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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Figure 1

Figure 1
<p>Location of the study area in Iran (<b>A</b>), detail map of the Khatunabad area and sampling points (satellite image from Landsat 8) (<b>B</b>), livestock around the smelter (<b>C</b>), farming around the smelter (<b>D</b>), two main towers of the smelter and vegetation destruction through heavy metal contamination (<b>E</b>), and zoom view of the copper smelter and refinery (<b>F</b>).</p> Full article ">Figure 2
<p>Selected plant species: <span class="html-italic">Artemisia</span> sp. (<b>A</b>), <span class="html-italic">Peganum harmala</span> (<b>B</b>), <span class="html-italic">Cousinia congesta</span> (<b>C</b>), <span class="html-italic">Launaea acanthodes</span> (<b>D</b>), and <span class="html-italic">Stipa</span> sp. (<b>E</b>).</p> Full article ">Figure 3
<p>Result of principal component analysis (PCA) in soil samples that shows the difference between natural origin and anthropogenic origin of different elements.</p> Full article ">Figure 4
<p>The zoning map of plant uptake values based on the MAI in the Khatunabad plain.</p> Full article ">Figure 5
<p>A diagram comparing the BCF, TF, and MAI values for samples of native plants based on the average of all the elements.</p> Full article ">Figure 6
<p>The BCF, TF, and MAI factors for Mn, Mo, Cu, and As in the native plant species.</p> Full article ">Figure 7
<p>The BCF, TF, and MAI factors for Zn, S, Pb, and Ni in the native plant species.</p> Full article ">
16 pages, 3175 KiB  
Article
A Green Approach Based on Micro-X-ray Fluorescence for Arsenic, Micro- and Macronutrients Detection in Pteris vittata
by Giuseppe Capobianco, Giuseppe Bonifazi, Silvia Serranti, Rosita Marabottini, Maria Luisa Antenozio, Maura Cardarelli, Patrizia Brunetti and Silvia Rita Stazi
Water 2022, 14(14), 2202; https://doi.org/10.3390/w14142202 - 12 Jul 2022
Cited by 2 | Viewed by 2620
Abstract
In this study, benchtop micro-X-ray fluorescence spectrometry (µXRF) was evaluated as a green and cost-effective multielemental analytical technique for P. vittata. Here, we compare the arsenic (As) content values obtained from the same samples by µXRF and inductively coupled plasma-optical emissions spectrometry [...] Read more.
In this study, benchtop micro-X-ray fluorescence spectrometry (µXRF) was evaluated as a green and cost-effective multielemental analytical technique for P. vittata. Here, we compare the arsenic (As) content values obtained from the same samples by µXRF and inductively coupled plasma-optical emissions spectrometry (ICP–OES). To obtain samples with different As concentrations, fronds at different growth time points were collected from P. vittata plants grown on two natural As-rich soils with either high or moderate As (750 and 58 mg/kg). Dried samples were evaluated using multielement-µXRF analysis and processed by PCA. The same samples were then analysed for multielement concentrations by ICP–OES. We show that As concentrations detected by ICP–OES, ranging from 0 to 3300 mg/kg, were comparable to those obtained by µXRF. Similar reliability was obtained for micro- and macronutrient concentrations. A positive correlation between As and potassium (K) contents and a negative correlation between As and iron (Fe), calcium (Ca) and manganese (Mn) contents were found at both high and moderate As. In conclusion, we demonstrate that this methodological approach based on μXRF analysis is suitable for monitoring the As and element contents in dried plant tissues without any chemical treatment of samples and that changes in most nutrient concentrations can be strictly related to the As content in plant tissue. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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Figure 1

Figure 1
<p>A <span class="html-italic">P. vittata</span> plant grown in naturally As-rich soil under greenhouse conditions. The arrow indicates the pinna collected for preparing pinna powder.</p> Full article ">Figure 2
<p>Workflow of “pinna powder” preparation. A pinna for each frond was collected from 4 ferns (<b>A</b>), dried at 37 °C for 48 h (<b>B</b>), and ground in a mortar (pinna powder, <b>C</b>).</p> Full article ">Figure 3
<p>Sample preparation into stubs before XRF analysis (<b>A</b>). Representative image at the stereomicroscope of powder texture after milling process (<b>B</b>).</p> Full article ">Figure 4
<p>Representation of principal component analysis applied to μXRF data.</p> Full article ">Figure 5
<p>PCA (<b>A</b>) score and (<b>B</b>) loading (PC1, PC2) plots of µXRF and ICP–OES data for T0 samples for plants grown on soil S1, S2.</p> Full article ">Figure 6
<p>3D PCA (<b>A</b>) score and (<b>B</b>) loading (PC1, PC3, PC5) plots of µXRF and ICP–OES data for T0, T30 and T60 for plants grown on soil S1.</p> Full article ">Figure 7
<p>3D PCA (<b>A</b>) score and (<b>B</b>) loading (PC1, PC2, PC3) plots of the µXRF and ICP–OES data for T0, T30 and T45 for plants grown on soil S2.</p> Full article ">Figure 8
<p>Flowchart demonstrating technical steps used in the approaches of μXRF and ICP–OES analyses.</p> Full article ">
15 pages, 1914 KiB  
Article
In Situ Remediation of Arsenic-Contaminated Groundwater by Injecting an Iron Oxide Nanoparticle-Based Adsorption Barrier
by Sadjad Mohammadian, Hadi Tabani, Zahra Boosalik, Amir Asadi Rad, Beate Krok, Andreas Fritzsche, Kamal Khodaei and Rainer U. Meckenstock
Water 2022, 14(13), 1998; https://doi.org/10.3390/w14131998 - 22 Jun 2022
Cited by 5 | Viewed by 3128
Abstract
Arsenic contamination of groundwater occurs due to both geogenic and anthropogenic processes. Conventional arsenic remediation techniques require extraction of groundwater into pump-and-treat systems, which are expensive and require long operational times. Hence, there is a need for cost-effective remediation. In this study, we [...] Read more.
Arsenic contamination of groundwater occurs due to both geogenic and anthropogenic processes. Conventional arsenic remediation techniques require extraction of groundwater into pump-and-treat systems, which are expensive and require long operational times. Hence, there is a need for cost-effective remediation. In this study, we assessed and validated the in situ remediation of arsenic contamination in groundwater resources using permeable reactive barriers (PRBs) made of injectable, colloidal iron oxide nanoparticles in the laboratory and in field-scale pilot tests. Sand-packed, flow-through column studies were used in order to assess the sorption behavior of the iron oxide nanoparticles using field materials (sand, groundwater) in the laboratory. The breakthrough curves were analyzed using a reactive transport model considering linear and nonlinear adsorption isotherms and were fitted best with a chemical nonequilibrium consideration. The results were used to design a pilot-scale field test. The injected 28 m3 of nanoparticles (ca. 280 kg dry weight of iron oxide) were successfully delivered to the aquifer via an injection well. No mobile iron was detected downstream, confirming that a stable in situ barrier was formed that did not move with the groundwater flow. Arsenic concentrations in groundwater were reduced to the aimed 50% of the background value, despite the relatively short contact time between arsenic and the iron oxide in the barrier, due to the high flow velocity of 1.21 m/day. We compared the results of the laboratory and field tests and concluded that the single-parameter models based on retardation factor and/or adsorption capacity fail to predict the longevity of the barrier and the evolution of arsenic breakthrough with time, most likely because they do not consider the chemical nonequilibrium effects. Therefore, we propose that upscaling the laboratory findings to field design must be carried out with care and be coupled with detailed reactive transport models. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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Figure 1

Figure 1
<p>Top view of (<b>a</b>) the groundwater flow direction map of the site, and (<b>b</b>) the location of injection well and monitoring well in the testing area. The testing area is marked by the red square in the top part of <a href="#water-14-01998-f001" class="html-fig">Figure 1</a>A. The springs are shown in green, and available observation wells are in red.</p> Full article ">Figure 2
<p>(<b>a</b>) Breakthrough curves for arsenic at velocity of 0.375 cm/min with and without addition of Goethite nanoparticles. Inlet concentration (C<sub>in</sub>) was 110 µg arsenic per liter. The <span class="html-italic">x</span>-axis shows the time in pore volumes (PV), where 1 PV equals a contact time of 8 min. (<b>b</b>) Breakthrough curves for barium, copper, and magnesium during the same experiments. Data points and error bars depict means and standard deviations of arsenic concentrations from two experiments.</p> Full article ">Figure 3
<p>Fitted breakthrough curves using advection–dispersion equation considering two-site nonequilibrium model and Langmuir (<b>left</b>), Freundlich (<b>middle</b>), and linear (<b>right</b>) adsorption isotherms.</p> Full article ">Figure 4
<p>Comparison between observed arsenic concentrations at the injection (IW, black) and downstream (DW, grey) wells of the pilot site for different adsorption isotherms based on kinetic parameters from the column data (lines). The data points show the observed arsenic concentrations during field test.</p> Full article ">Figure 5
<p>Observed iron concentrations in groundwater samples taken from the downstream well.</p> Full article ">Figure 6
<p>Observed arsenic concentrations in the injection and the downstream wells after injection of the iron oxide nanoparticles. Time 0 indicates the day of the injection.</p> Full article ">
13 pages, 1751 KiB  
Article
Simulation of Denitrification Process of Calcium Nitrate Combined with Low Oxygen Aeration Based on Double Logarithm Mode
by Fan Wang, Fang Yang, Hongjie Gao, Yangwei Bai, Haiqing Liao and Haisheng Li
Water 2022, 14(2), 269; https://doi.org/10.3390/w14020269 - 17 Jan 2022
Cited by 26 | Viewed by 2603
Abstract
In situ remediation of sediment pollution is an important measure for the treatment of urban black-odorous water. In this study, the process of calcium nitrate dosing and low oxygen aeration was used to repair the sediment of black-odorous water body in a glass [...] Read more.
In situ remediation of sediment pollution is an important measure for the treatment of urban black-odorous water. In this study, the process of calcium nitrate dosing and low oxygen aeration was used to repair the sediment of black-odorous water body in a glass container. The variation trend and removal efficiency of ammonia nitrogen and nitrate nitrogen in sediment and overlying water were investigated during the process. By establishing the double logarithm model of calcium nitrate sediment repair process, the change law of ammonia nitrogen and nitrate nitrogen content in sediment under different calcium nitrate dosing conditions was studied, and the denitrification process of different calcium nitrate dosing and low oxygen aeration was simulated. The results showed that by establishing the double logarithm model of calcium nitrate sediment remediation process, when the dosage of calcium nitrate was 6%, the inhibition rate of calcium nitrate on nitrate nitrogen release was the largest. The stable inhibitory concentration of nitrate nitrogen was 11.65 mg/g, and the stable inhibited concentration of ammonia nitrogen was 382.95 mg/kg. The stable inhibitory concentration of nitrate nitrogen and ammonia nitrogen in overlying water was 8.34 mg/L and 16.47 mg/L. Moreover, excessive calcium nitrate (8%) may increase the risk of microbial ecological environment in sediment and weaken the inhibitory effect. The optimum parameters were the calcium nitrate dosage of 6%, the reaction time of 21 days, and the aeration rate of 30 mL/min. Under these conditions, the removal effect of ammonia nitrogen in sediment and overlying water was further improved, and the concentration of nitrate nitrogen was effectively controlled. The stable inhibitory content of nitrate nitrogen in sediment was 5.55 mg/g, and the stable inhibitory content of ammonia nitrogen was 982.79 mg/kg. The stable inhibitory concentration of nitrate nitrogen and ammonia nitrogen in overlying water was 6.55 mg/L and 118.20 mg/L. Based on a simulation, this study provides important technical support for the formulation of a refined endogenous pollution control scheme by controlling the process of calcium nitrate remediation and low oxygen aeration. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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<p>Variation of ammonia nitrogen/nitrate nitrogen content in sediments.</p> Full article ">Figure 2
<p>Variation of ammonia nitrogen/nitrate nitrogen concentrations in overlying water.</p> Full article ">Figure 3
<p>Variation of ammonia nitrogen/nitrate nitrogen content in sediments under aeration.</p> Full article ">Figure 4
<p>Variation of ammonia nitrogen/nitrate nitrogen concentrations in overlying water under aeration.</p> Full article ">Figure 5
<p>Double logarithm regression relationship between ammonia nitrogen/nitrate nitrogen content in sediment and test days.</p> Full article ">Figure 6
<p>Double logarithm regression relationship between ammonia nitrogen/nitrate nitrogen concentration in overlying water and test days.</p> Full article ">Figure 7
<p>Double logarithm regression relationship between ammonia nitrogen/nitrate nitrogen content in sediment and test days under aeration.</p> Full article ">Figure 8
<p>Double logarithm regression relationship between ammonia nitrogen/nitrate nitrogen concentration in overlying water and test days under aeration.</p> Full article ">
18 pages, 8258 KiB  
Article
Assessment of Potential Ecological Risk of Heavy Metals in Surface Soils of Laizhou, Eastern China
by Zhigang Zhao, Haishui Jiang, Linghao Kong, Tianyi Shen, Xionghua Zhang, Songsong Gu, Xiangcai Han and Yachao Li
Water 2021, 13(21), 2940; https://doi.org/10.3390/w13212940 - 20 Oct 2021
Cited by 8 | Viewed by 2873
Abstract
With the rapid industrialization and urbanization, more attention is turning to heavy metal contamination in the soil environment. To assess the potential environmental risk on soil, a comprehensive geochemistry study on heavy metal was performed in Laizhou, eastern China, using 3834 surface soil [...] Read more.
With the rapid industrialization and urbanization, more attention is turning to heavy metal contamination in the soil environment. To assess the potential environmental risk on soil, a comprehensive geochemistry study on heavy metal was performed in Laizhou, eastern China, using 3834 surface soil samples (0–20 cm, regular grid of 1 × 1 km2) and 60 layered soil samples (0–200 cm) were analyzed. The average concentrations of As, Cd, Cr, Cu, Hg, Ni, Zn and Pb were 7.60 mg·kg−1, 0.15 mg·kg−1, 45.50 mg·kg−1, 19.10 mg·kg−1, 44.00μg·kg−1, 18.70 mg·kg−1, 51.40 mg·kg−1 and 29.00 mg·kg−1, which were lower than the threshold levels of the Grade II criteria of China national environment quality standard for soil, but the contents of As, Cd, Hg, and Pb were higher than background values of eastern Shandong Province surface soil. Fractionation analysis showed that the potential bioavailability in surface soils decreases in the order of Cd > As > Cu > Ni > Zn > Cr > Pb > Hg. Soil assessments with enrichment factor, contamination factor, Nemerow composite index, geo-accumulation index and potential ecological risk index, indicate the soil in Laizhou is contaminated strongly with As, Cd and Hg and a moderately Cr, Ni, Cu and Zn. The level of Pb pollution is between moderate to high. Multivariate analyses suggest that Cr and Ni were derived mainly from natural sources, and As, Cd, Pb, while Hg mostly came from anthropogenic sources. Cu and Zn were from a mixture of anthropogenic and natural sources. Our results demonstrate that more attention should be paid to monitoring soil quality in the heavily polluted site. Full article
(This article belongs to the Special Issue Water and Soil Pollution Restoration)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Geographical location of study area with indication of the sampling sites (the geographical location map is derived from the administrative zoning map of Shandong Province, 2019).</p> Full article ">Figure 2
<p>Land use, parent material and topography in Laizhou ((<b>a</b>) from the SRTMDEM 90M; (<b>b</b>) was adapted from the geological map of Yantai city (map scale, 1:250,000); (<b>c</b>) was interpreted in GF-2 1M).</p> Full article ">Figure 3
<p>Horizontal distribution of heavy metal (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn) in the study area.</p> Full article ">Figure 4
<p>Vertical distribution plots of heavy mental in slightly and heavily polluted site.</p> Full article ">Figure 5
<p>Speciation of heavy metals in surface soils from four sites of the study area.</p> Full article ">Figure 6
<p>Box-plots display the distributions of the pollution indexes of heavy metals in surface soils of the study area. (<b>A</b>) enrichment factor (EF); (<b>B</b>) contamination factor (CF); (<b>C</b>) geo-accumulation index.</p> Full article ">Figure 7
<p>Potential Ecological Risk Classification of Heavy Metals in Surface Soil.</p> Full article ">Figure 8
<p>Degree of Composite Potential Ecological Risk of Heavy Metals in Surface Soil.</p> Full article ">Figure 9
<p>Loading plot of principal components (PCs) for heavy metals in surface soils of the study area using principal component analysis (PCA) after varimax rotation.</p> Full article ">
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