Temporal deposition of copper and zinc in the sediments of metal removal constructed wetlands.

The objective of this study was to explore the effects of time, seasons, and total carbon (TC) on Copper (Cu) and Zinc (Zn) deposition in the surface sediments. This study was performed at the H-02 constructed wetland on the Savannah River Site (Aiken, SC, USA). Covering both warm (April-September) and cool (October-March) seasons, several sediment cores were collected twice a year from the H-02 constructed wetland cells from 2007 to 2013. Total concentrations of Cu and Zn were measured in the sediments. Concentrations of Cu and Zn (mean ± standard deviation) in the surface sediments over 7 years of operation increased from 6.0 ± 2.8 and 14.6 ± 4.5 mg kg-1 to 139.6 ± 87.7 and 279.3 ± 202.9 mg kg-1 dry weight, respectively. The linear regression model explained the behavior and the variability of Cu deposition in the sediments. On the other hand, using the generalized least squares extension with the linear regression model allowed for unequal variance and thus produced a model that explained the variance properly, and as a result, was more successful in explaining the pattern of Zn deposition. Total carbon significantly affected both Cu (p = 0.047) and Zn (p < 0.001). Time effect on Cu deposition was statistically significant (p = 0.013), whereas Zn was significantly affected by the season (p = 0.009).

1. Introduction

Constructed wetlands are green, man-made alternatives to treat urban, industrial, and agricultural runoff, storm water, and municipal and industrial wastewater [1-3]. Compared to wastewater treatment facilities, and owing to their low construction and operational costs, constructed wetlands are relatively cheaper and require less maintenance [4-6]. The design of constructed wetlands simulates natural wetlands and provides similar but more controlled ecosystem functions [7,8]. These functions include the biogeochemical cycling of carbon and nutrients and removal of contaminants such as heavy metals [9-11].

Heavy metals could enter constructed wetlands through point sources such as industrial wastewater [12], and nonpoint sources such as agricultural runoff of products incorporating heavy metals (e.g., micronutrient fertilizers, pesticides, etc) [13]. The removal of heavy metals from wastewater in the free surface wetlands is often achieved through several processes such as sedimentation, filtration, adsorption, and uptake by macrophytes and other organisms [14]. Thus, heavy metal enrichment in wetland soils is expected.

Wetland sediments are considered as sinks to contaminants such as metals [15,16]. While the transport of heavy metals from the wastewater to the underlying sediments is highly desirable prior to discharge into natural water bodies, the deposition of heavy metals in the wetland sediments should be closely monitored overtime, to ensure that it will not become toxic to benthic organisms and microorganisms, where the trophic transfer could likely happen [17-19]. Also, as wetlands mature, their efficiency in contaminant and nutrient removal may decline [20,21].

Heavy metals, especially Cu and Zn, are strongly associated with organic matter [22-24]. Wetlands tend to have a higher deposition rate of organic matter compared to other ecosystems, due to the high rate of carbon fixation through photosynthesis, coupled with the slow decomposition rates due to the dominant anaerobic conditions [9]. Thus, wetland sediments with higher organic matter content will likely become enriched with metals over time, which occurs through several processes such as complexation and sorption to humic substances [25].

Redox potential and pH have major effects on the biogeochemical cycling of heavy metals. In wetland systems, two distinct redox zones could be identified; an aerobic zone close to the surface and an anaerobic zone that lies deeper in the sediments [9]. The availability of organic matter in the anaerobic zones enhances the biotic reduction of iron and sulfates, which results in the precipitation of Cu and Zn into metal sulfides and/or their adsorption onto iron hydroxides. Under acidic conditions, most metals will be outcompeted by the abundant H+ ions for adsorption onto negatively charged surfaces such as clay minerals and organic matter. On the other hand, neutral to alkaline sediments in the wetland systems result in metal fixation and reduce the toxicity to macrophytes through adsorption onto negatively charged surfaces [3].

The efficiency of a constructed wetland in the removal of contaminants is usually assessed by measuring and comparing the concentrations of these contaminants in the inflow and the outflow effluent. Few studies investigated metal retention in constructed wetlands and sediments over time and seasons [25-27]. The design of the constructed wetlands plays a major role in determining the sustainability of the system in contaminant removal [28]. Hydraulic parameters, macrophytes and substrates used to provide a continuous supply of organic matter and nutrients important for plant growth, could also affect the performance and efficiency of a wetland system [29].

The H-02 wetland was constructed in 2007 to treat storm runoff and industrial effluent generated from the Tritium facility on the Savannah River Site (Aiken, SC, USA). The wetland follows the traditional free surface flow design and aims at the removal of heavy metals from the effluent prior to discharge to the Upper Three Runs Creek which eventually reaches the Savannah River. The objective of this study was to report and evaluate the potential temporal, seasonal, and TC effects on the deposition of Cu and Zn in the H-02 wetland sediments over the course of 7 years (from 2007 to 2013). We used linear models (lm) and the linear model with a generalized least squares (gls) extension to resolve residual heterogeneity and help understand the deposition behavior of Cu and Zn in the H-02 wetland.

2. Methods

2.1. Study site

A schematic diagram of the H-02 wetland system showed the sediment core sampling sites in both wetland cells 1 and 2 (S1 Fig). A detailed description of the free-surface wetland system can be found in Xu and Mills, 2018 [11] and Xu, et al 2019 [30]. Briefly, the Tritium facility discharges wastewater through source pipes into a rectangular pool where water is retained to provide hydrological control. The wastewater then goes through a splitter box that roughly splits the flow equally into two adjacent rectangular wetland cells (WC1 and WC2) of about 2240 m2 area each. The wetlands are lined with geo-synthetic impermeable material, covered with 46–61 cm of native wetland soil that has been amended with gypsum (source of sulfur (S)), fertilizer, and organic matter to provide a substrate that would support the growth of plants and microbial communities [11]. The cells were planted with the macrophyte, giant bulrush (Schoenoplectus californicus), which also contributes to immobilizing metals in wetland sediments by providing organic ligands that act as binding sites, while providing a carbon source for sulfate reducing bacteria, which in turn, help sequestering Cu and Zn from the water column through the formation of mineral ZnS and CuS [31]. Water stays for 48 hours in each wetland cell before leaving at the other end through a pipe which discharges water into the Upper Three Runs Creek before eventually ending into the Savannah River.

2.2. Sediment core collection and processing

Sediment cores were collected from each wetland cell for metal analysis twice a year, once during the warm seasons (April-September), and once during the cool seasons (October-March) starting from June 2007. Each wetland cell was divided into 3 transects. The focus was on the first and last transects as they represent the locations at which water enters (inflow) and leaves (outflow) each wetland cell. The cores were put on ice, transferred to the lab, and stored upright at 4⁰C until the next day to allow the flocculent layer to settle. Surface standing water was carefully siphoned off from the cores avoiding disturbing the flocculent layer. The siphoned cores were stored in the freezer for at least a week prior to further processing. Then each core was extruded into several sections based on changes in color and texture. In most cases, cores had three distinct layers; a top layer which contains the upper sediment layer mixed with flocculent material that is rich in organic matter, a middle clay-like textured layer, and a bottom sandy-textured layer. Extruded core sections were transferred to 50 mL metal free tubes and freeze dried (Labconco Corporation; Kansas City, MO, USA) until constant weight. Dried sediments were passed through a 2 mm sieve.

2.3. Chemical analysis

US EPA methods 3051A [32] and 6020A [33] were both used to process the sediments and analyze total metal concentrations, respectively. Briefly, microwave acid digestion (CEM MARSxpress, Matthews, NC, USA) in 10 mL concentrated HNO3 at 180°C for 10 minutes was performed on freeze-dried sediments, and ICP-OES (Optima 4300 DV, PerkinElmer, Waltham, MA, USA) was used to measure the total concentrations of Cu and Zn in diluted digests. Standard reference material, digestion blanks, duplicates, and spikes were used as measures of QA/QC throughout the analytical process. Method detection limits for Cu and Zn were, respectively, 2.05 and 2.06 ng g-1. Marine sediment standard reference material MESS-3 (National Research Council of Canada ((NRC - CNRC); Ottawa, Canada) had an average percent recovery of 92.2 and 93.0% for Cu and Zn, respectively (n = 2). Relative percent differences among replicates were 13.2% for Cu and 11.7% for Zn (n = 4). Average spike percent recoveries for Cu and Zn were 116.6% and 112.2%, respectively (n = 3). Total carbon (TC) and total nitrogen (TN) were measured in the freeze-dried sediments using the US EPA method 9060A [34].

2.4. Statistical analysis

2.4.1. Data processing

Dates of sediment core sampling were split into two main categories; “warm” or “cool” based on the temperatures in Aiken (SC, USA). Months from April to September and from October to March fell into the warm and cool seasons, respectively. We split the full data set into several lists based on wetland cell (1 or 2), transect (inflow or outflow), and sediment core depth (top, middle, and bottom). For non-available data, we replaced these values with the average of that variable in the corresponding list. In instances where below detection limit data were encountered, we replaced those with half the detection limit.

2.4.2. Data exploration

Metals, TC and TN concentrations were log-transformed to the base 10 to minimize the effect of potential outliers on the analysis [35]. Data exploration included constructing several conditioning plots that showed the relationship between the explanatory and the response variables. Metals (Cu and Zn) and TN and TC as well, were far more abundant in the top layer in the sediment cores compared to the lower layers which had similar and much lower TC and metal content. Thus, the major focus of this analysis was on the surface (top) layer of the sediment-named surface sediments hereafter. Previous work performed in the H-02 wetland has also shown that the surface layer had significantly higher Cu and Zn concentrations compared to the other two lower layers which were not significantly different from one another [36].

Also, since the outflow location is more critical for monitoring metal concentrations as the effluent leaves the wetland into the regulatory Upper Three Runs Creek, our focus was on samples collected from the outflow location in both wetland cells. Since TC and TN are proxies of organic matter, which is highly responsible for metal complexation, we initially included both parameters as fixed effects in model construction. Data analysis and modeling were performed using R-studio 4.0.2 [37].

2.4.3. Model selection

Model selection was performed following the processed mentioned in [38]. The process is described in detail elsewhere (S1 Text, S2 Fig). Briefly, after eliminating fixed variables of high correlation (S1 Table, S3 Fig, S1 Text), the linear model (lm) was tested for residual homogeneity. In case of residual heterogeneity, a variance covariance structure was used, and once the homogeneity of residuals was achieved, the backward selection method was applied to include the significant fixed effects and their interactions. Model validation involved testing residual normality, homogeneity, and independence.

3. Results

3.1. Deposition of Cu and Zn in the surface sediments

Average total Cu and Zn concentrations measured in the surface sediments increased between the years 2007 and 2013 (Table 1). Results are reported as (mean ± standard deviation). Total Cu and Zn concentrations in the surface sediments were respectively 6.0 ± 2.8 and 14.6 ± 4.5 mg kg-1 dry weight at the beginning of the H-02 wetland operation. After 7 years, total Cu and Zn concentrations increased by almost 23.2 and 19.2 times to reach 139.6 ± 87.7 and 279.3 ± 202.9 mg kg-1 dry weight of Cu and Zn, respectively (Table 1).

Table 1

Concentration of Cu and Zn in the surface sediment averaged by year, data presented as mean concentration ± standard deviation and (minimum—maximum) concentrations (mg kg-1 dry sediment).

Year	Total Cu (mg kg-1)	Total Zn (mg kg-1)
2007	6.0 ± 2.8 (4.0–8.0)	14.6 ± 4.5 (11.4–17.7)
2008	18.5 ± 13.2 (6.0–32.2)	34.3 ± 18.9 (14.0–51.4)
2009	119.9 ± 139.9 (4.4–349.9)	177.2 ± 186.2 (7.8–4635)
2010	50.2 ± 28.2 (11.7–85.3)	90.6 ± 52.0 (23.6–170.3)
2011	43.7 ± 23.4 (19.8–93.1)	62.6 ± 33.9 (4.0–106.2)
2012	129.7 ± 61.1 (27.0–195.9)	204.4 ± 96.0 (43.6–296.2)
2013	139.6 ± 87.7 (33.5–274.2)	279.3 ± 202.9 (60.5–674.4)

For year 2007, n = 2, 2008, n = 3, 2009, n = 5, and for years 2010–2013, n = 8.

3.2. Modeling Cu deposition in the surface sediments

The optimum model for Cu deposition in surface sediments was the linear regression model (lm) (Table 2). This model included neither random effects nor variance covariate terms. Backward selection process showed that the optimum fixed structure included; year, log10TC and a year by log10TC interaction term (Table 2). Model validation showed that the normalized residuals were both homogenous (S4 Fig, Bartlett’s test for homogeneity: p = 0.8729) and normally distributed (S5 Fig, Shapiro-Wilk test for normality: p = 0.9358). The seasonal effects were not statistically significant (p = 0.9099) and thus were removed from the final model. Also, Pearson normalized residuals plotted against all main effects (season, year, cell, TC and TN) showed homogeneous distribution (S6 Fig).

Table 2

Model parameters for Cu and Zn.

Metal	Model	Random term/variance covariate structure	Fixed term (p at α = 0.05)	Coefficient	p-value
Cu	lm	Cu	Intercept	226.5	0.013
			Year	0.11	0.013
			Log10TC	258.30	0.047
			Year: Log10TC	-0.13	0.048
Zn	gls	VarIdent (Year)	Intercept	1.51	<0.001
		VarIdent (Season)	Season/Cool	-0.17	0.0093
		VarFixed (Log10TC)	Log10TC	1.04	<0.001

lm: Linear model, gls: Linear model with generalized least squares extension.

Regardless of the year, Cu was positively and significantly (p = 0.047) correlated with log10TC (Table 2, Fig 1). There is a significant (p = 0.013) and progressively increasing trend in Cu deposition in the surface sediments throughout the years of the study (Fig 2). However, the deposition of Cu did not show significant differences between the warm and the cool seasons (p = 0.88, Fig 2).

Fig 1

Relationship between log10TC and log10Cu.

Fig 2

Conditioning plot showing the pattern of log10Cu deposition in surface sediments (mg kg-1) throughout the years 2007–2013 in the warm vs the cool seasons.

The interaction between the year and log10TC on log10Cu was statistically significant (p = 0.048) and varied across the years (Table 2, Fig 3). Indeed, year to year variation in log10TC deposition resulted in different slopes as depicted in Fig 3. For example, the year 2007 had a slope of 0.83 and much lower log10Cu values compared to the following year where the slope was 2.6 greater than in the former year. This could be attributed to the significant increase in TC deposition in 2008 (after one year operation). In later years, the slope tended to be lower (1.25, 1.29, and 1.13, for the years 2009, 2010, and 2013, respectively). The slope was at it’s lowest in the years 2011 and 2012 with 0.60 and 0.64, respectively (Fig 3).

Fig 3

The effect of the interaction between year and log10TC on log10Cu.

3.3. Modeling Zn deposition in the surface sediments

The optimum model for Zn was the linear model with a generalized least square model (gls) extension, which allowed introducing a variance covariance structure for the main effects; season, year, and log10TC (Table 2), in order to describe the heterogeneity in the residuals. The varident structure was used for both season and year while the varfixed structure was used in the case of log10TC.

Model validation showed that the normalized residuals were both homogeneous (S7 Fig, Bartlett’s test for homogeneity: p = 0.90) and normally distributed (S8 Fig, Shapiro-Wilk test for normality: p = 0.87). The plot of normalized residuals against the main effects did not show any significant patterns, which confirmed residual independence (S9 and S10 Figs).

The effect of total carbon (Log10TC) on the deposition of Zn in the surface sediment was positive and statistically significant (p <0.001, Table 2) regardless of the year (Fig 4).

Fig 4

Relationship between log10TC and log10Zn.

There was a significant seasonal effect on the deposition of Zn in the surface sediment (p = 0.0093, Table 2). The effect of the cool season was 0.17 times less than the effect of the warm season on Zn deposition (Table 2, Fig 5)

Fig 5

Conditioning plot showing the pattern of log10Zn deposition in surface sediments (mg kg-1) throughout the years 2007–2013 in the warm vs the cool seasons.

3.4. Deposition of Cu and Zn in the lower sediment layers

Although the major focus of this study was on the surface sediments, we reported the concentrations of Cu and Zn in the middle and bottom layers as mean ± 95% confidence intervals (S2 and S3 Tables). Whether averaged by season, location, or by wetland cell, metal concentrations over the years in the middle layer seemed to consistently range between 5.2 ± 5.8 and 19.7 ± 43.0 mg kg-1 for Cu, and between 9.5 ± 4.1 and 28.2 ± 54.1 mg kg-1 for Zn. Likewise, metal concentrations in the bottom layer ranged between 4.4 ± 1.6 and 7.4 ± 7.5 mg kg-1 for Cu, and between 5.6 ± 3.9 and 14.0 ± 7.6 mg kg-1 for Zn.

4. Discussion

This study explored the potential effects of time (7 years), seasons, and organic carbon on Cu and Zn deposition behavior in the surface sediment in the H-02 constructed wetland. The ongoing sampling and analysis of sediment cores are essential to monitor the performance of constructed wetlands over years and seasons. Indeed, this work is a part of several ongoing studies that focus on evaluating the efficiency of the H-02 constructed wetland system in the removal of metals [11,30,36].

4.1. Actual concentrations of Cu and Zn in the sediments over the years

The consistent increase in Cu and Zn in the surface sediments over the years implies that the wetland is still successful in the removal of Cu and Zn from the effluent water. Previous work, conducted between the years 2007 and 2018, showed that the H-02 wetland system efficiency in Cu and Zn removal from the Trituim Facility effluent was, respectively, 63.8% and 70.5% [11].

According to our previous work [30], the H-02 wetland system is hypothesized to perform in a 3-stage pattern in terms of metal removal efficiency; a steady metal removal performance (plateau stage), a decline in metal removal efficiency (trough stage) and another plateau stage were the metal removal efficiency increases again [30]. In the present study, the deposition patterns of Cu and Zn in the sediments started off by imitating the first plateau stage of operation. Continuous monitoring of metal concentrations in the sediments and water is essential to monitor the efficiency of the H-02 wetland system and to support the abovementioned hypothesis.

4.2. Deposition of Cu and Zn in the sediments

Although the data from different seasons, wetland cells, or locations were variable, it clearly showed that Cu and Zn deposition increased in the surface sediments throughout the years. On the other hand, metal deposition in the lower sediments-middle and bottom layers- was much lower compared to the surface sediments and seemed not to change over the years. This is expected due to the design of the H-02 wetland system which operates as a free surface flow system, which implies that the majority of metals removed from the water column would thereby be retained in the top sediment, which is rich in organic matter [36]. Similarly, metal concentrations significantly decreased with depth in a free water surface constructed wetland that treated industrial effluent [27].

4.3. Effect of time, seasons, and carbon on Cu and Zn deposition in the surface sediments

Wetlands are among the largest reserves of carbon in the environment [39]. Thus, a positive association is expected between carbon and metal deposition. In the present study, linear regression analysis showed a significant and positive correlation between total carbon and Cu and Zn concentration in the surface sediment. Similarly, several studies reported a significant, strong, and positive correlation between organic matter content and Cu and Zn concentrations in the sediments [22,23].

The deposition of Cu significantly increased over time in the surface sediments of the H-02 wetland. However, the negative interaction between year and log10TC means that the effect of log10TC on log10Cu concentration is, in fact, decreasing over time. This could be attributed to the slower rate of organic matter addition to the wetland as the H-02 wetland matures, which will potentially lead to a trough stage as hypothesized by Xu et al 2019 [30]. In an experiment that aimed at understanding the long-term ecosystem effects of riverine wetlands, it was reported that organic carbon content increased by 14% in the first 10 years of operation and then increased by only 8% in the following 5 years [40].

While both metals, Cu and Zn, showed similar increasing deposition patterns in the surface sediments over the years and seasons, regression models showed differences in how the main effects explained these patterns. Seasonal changes significantly affected Zn deposition but not Cu. Cool seasons tended to have lower Zn concentrations in the sediments as compared to the warm seasons. Harris et al 2020 found no seasonal effects on total Cu and Zn concentration in the surface sediments of the H-02 wetland [36]. This is an interesting discrepancy as the samples in that study were collected more recently. Therefore, further studies aiming at model validation are required.

Seasonal variation in metal removal and retention in the wetland system could be tied to the sulfur cycle. In the H-02 wetland system, sulfur dynamics were more prominent in warmer months where metals tended to form insoluble sulfides under anoxic conditions, while adsorption onto organic matter was more likely responsible for metal removal from the wastewater and subsequent retention in the sediments in the cooler months [30]. Harris et al 2020, found that the acid volatile sulfide (AVS) content in the surface sediments was season dependant, and was less abundant in the cooler months, which enhanced metal mobility and thus resulted in lower metal retention in the sediments in the form of metal sulfides [36]. In another study, the concentrations of Cu in the sediments of a natural March were dependent on the season, where Cu concentrations were higher in late summer to early fall, whereas Zn concentrations were the highest during summer and fall, and both metals had lowest concentrations in winter [25].

4.4. Modeling the deposition of metals in sediments

In this study, we used the generalized linear model to understand the effects of time and seasons on Cu and Zn deposition in the sediments. Likewise, generalized linear model helped identifiying sources of metal contamination in water and the surface sediment over time and seasons [41]. The deposition of Zn in Norwegian marine sediments over 25 years helped identifying the historical point sources responsible for metal pollution using the generalized additive models [42]. Symader and Bierl, 2000 adopted time series analysis to evaluate metal concnetration temporal variabilities over 6 years in the sediments of a river in Germany, which eventually helped understand the sediment chemistry [43].

5. Conclusions

Deposition of heavy metals (Cu and Zn) in the sediment of the H-02 constructed wetland was dependent on total carbon, time, and seasons. Total carbon had a significant effect on the deposition of both metals in the surface sediment. Seasonal effects only impacted Zn deposition were cool seasons tended to accumulate less Zn. While this study focused on the prediction of the deposition patterns of total Cu and Zn in the surface sediments of the H-02 constructed wetland system, more work is needed to study the speciation and the partitioning of Cu and Zn to organic matter and clay minerals, especially in the surface sediment. Also, these studies could help understand the long-term interaction between the biogeochemical cycle of Cu and Zn and the sulfur cycle.

Heavy metal accumulation in the H-02 wetland system is an going work, and future studies should include more advanced staistical approaches including machine learning tools, which could be used to model the non-linear behavior of metal accumulation in the wetland sediments. Model validation is also necessary to assess model efficiency in predicting the depostion patterns of total metal concentrations. Future work should also include studies that focus on the effect of Cu and Zn accumulation in the surface sediments on the benthic organisms and the microbial community over time.

A schematic diagram of the H-02 Wetland system.

(DOCX)

Click here for additional data file.

Flowchart of the model selection process.

(DOCX)

Click here for additional data file.

Relationship between log transformed total carbon (log10TC) and total nitrogen (log10TN).

(DOCX)

Click here for additional data file.

Standardized residuals vs fitted values for the linear model (lm) for Cu.

(DOCX)

Click here for additional data file.

Pearson’s normalized residuals denoted by E for the linear model (lm) for Cu.

(DOCX)

Click here for additional data file.

Pearson’s normalized residuals for the linear model (lm) for Cu plotted against seasons (warm and cool), cells (1 and 2), and the years of the study (2007–2013).

(DOCX)

Click here for additional data file.

Standardized residuals vs fitted values for the linear model with generalized least squares extension (gls) for Zn.

(DOCX)

Click here for additional data file.

Pearson’s normalized residuals for the linear model with generalized least squares extension (gls) for Zn.

(DOCX)

Click here for additional data file.

Pearson’s normalized residuals for the linear model with generalized least squares extension (gls) for Zn plotted against seasons (warm and cool), cells (1 and 2), and the years of the study (2007–2013).

(DOCX)

Click here for additional data file.

Pearson’s normalized residuals for the linear model with generalized least squares extension (gls) for Zn plotted against log10TC and log10TN.

(DOCX)

Click here for additional data file.

Variance inflation factors (VIF) of fixed effects included in the generalized linear model for Cu.

(DOCX)

Click here for additional data file.

Concentration of Cu (mg kg-1 dry weight) in each sediment layer (Top, Middle, and Bottom) per year.

(DOCX)

Click here for additional data file.

Concentration of Zn (mg kg-1 dry weight) in each sediment layer (Top, Middle, and Bottom) per year.

(DOCX)

Click here for additional data file.

Model selection.

(DOCX)

Click here for additional data file.

(R)

Click here for additional data file.

(CSV)

Click here for additional data file.

(R)

Click here for additional data file.

(XLSX)

Click here for additional data file.

11 May 2021

PONE-D-21-10299

Temporal Deposition of Copper (Cu) and Zinc (Zn) in the Sediments of Metal Removal Constructed Wetlands

PLOS ONE

Dear Dr. Elhaj Baddar,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jun 25 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Zaher Mundher Yaseen

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In your Methods section, please provide additional location information of the sampling sites, including geographic coordinates for the data set if available.

3. In your Methods section, please provide additional information regarding the permits you obtained for the work. Please ensure you have included the full name of the authority that approved the field site access and, if no permits were required, a brief statement explaining why.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

Reviewer #4: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I read the manuscript and found it very good, as it represents a scientific research of original data with an applied character that simulates the environmental treatment of heavy elements (Cu and Zn). Field experiments, statistics and chemical analyses have been performed in high technical standard and results were presented in a clear manner mostly except for some places of the manuscript. The manuscript meets all applicable standards for the ethics of experimentation and research integrity. However, I recommend to accept the manuscript after major revision and the following points should be addressed:

1. Title must be concise and informative, so the abbreviation Cu and Zn should be deleted and title become “Temporal Deposition of Copper and Zinc in the Sediments of Metal Removal Constructed Wetlands”.

2. Line 59: The expression “media/soils” doesn’t be accepted, please change it in another style.

3. Line 103-104: The author stated “Briefly, the Tritium facility discharges wastewater through source pipes into a rectangular pool where water is retained to provide hydrological control”. How much is the tritium wastewater discharged through source pipes into a rectangular basin?

4. Line 123-124: Surface standing water was carefully siphoned off from the cores avoiding disturbing the flocculent layer. To what extent surface standing water can be siphoned?

5. Line 129-130: Dried sediments were passed through a 2 mm sieve. I think after sediments be dried will need gentle grinding to be sieved easily. Line 176-177: In the model selection process, we followed the protocol mentioned in Zuur et al. 2009, (Zuur et al. 177 2009). Please, it is better is not to repeat the reference “Zuur et al. 2009” twice, try to reformulate the statement. Line 181: Please do not use do not use the active voice and the pronoun “we” as mentioned in “Therefore, we only kept log10TC in the model”.by the same way, look at Line 184; “Fourth, we refitted the model with the generalized”; Line 188; “Fifth, we specified the optimum fixed structure using the backward selection”; Lines191 and 192 “first, we evaluated the homogeneity of residuals using graphic tools and the Bartlett’s test of homogeneity. Second, we checked the normality graphically and by using the….”; and lines 194-195 “We used α at 0.05 as the significance level”.

6. Line 198: I suggest to change that title to “Deposition of Cu and Zn on the interface water-sediments”.

7. In both models, we find ambiguity in which layers the copper and zinc are deposited more? and why?

8. Please explain the role of Total carbon in the absorption process and its absorption capacity.

9. The best was to analyze the minerals and diagnose the type of clay minerals. As is known, every clay mineral has specific value of cation exchange capacity.

10. It is better to make mineralogy study for the soil sample.

11. Line 351 “Heavy metal (Cu and Zn)”, I think lead and zinc represent a plural state, not singular, so it is better to write the term heavy metals, not heavy metal.

12. If you use British language, the Acknowledgments” write as “Acknowledgements”.

Salih M Awadh

salih.awad@sc.uobaghdad.edu.iq

Reviewer #2: 1. Avoid using the first person pronouns "I or we” in your writing, and the most common reason given for this is that readers may regard such writing as being subjective, whereas science is all about objectivity.

2. manuscript should have some novelty in its work

3. remove “map” from the title of Fig S1 and line 101

4. fig S1 need to add the size and the scale

5. My suggestion to add Figure of study area to the manuscript

6. the methods section very long , please minimize it

7. the conclusion section very short and need more info, you need make balance between sections

8. Fig S5, S7, S8 and S9 titles need modify according to the charts type.

Reviewer #3: This research predicted Copper (Cu) and Zinc (Zn) deposition patterns , the research examined and studied the effects of time, seasons, and total carbon (TC) on Copper (Cu) and Zinc (Zn) deposition in the surface sediments of the H-02 constructed wetland on the Savannah River Site .

This research Covering both warm (April-September) and cool (October-March) seasons, several sediment cores were collected twice a year from the constructed wetland cells over 7 years, from 2007 to 2013.

This research used the Generalized Least Squares (GLS) & Linear Regression Model (LRM), linear regression model explained the behaviour and the variability of Cu deposition in the sediments , using the (GLS) extension with the (LRM)allowed for unequal variance .

Reviewer #4: This is an original research paper on developing a pattern evaluation of heavy metals (Cu, Zn) settlement in the surface constructed wetland by time and Total Carbon (TC). The topic selected by the authors is appreciated in the specific domain of science and engineering for several purposes like contamination treatment at a lower price and lower environmental impact concern. Nonetheless, the work needs to be improved to reach the level of publication for readers of the respected PLOS ONE journal.

Abstract:

1. This needs precise information on how the outcomes of the linear regression model are going to be impacted.

2. Cu and Zn changed the value reported so TC needs to report as well.

3. Line 40: …On the other hand, using the generalized least squares extension with the linear regression model allowed for unequal variance, and thus was more successful in explaining Zn deposition pattern… what does mean ‘more successful’? rewrite it.

Introduction:

4. Line50: … relatively cheaper… how? Explain it in detail.

5. The review assessment has been poorly drafted. Add more recent (5 years) papers.

https://link.springer.com/article/10.1007/s11356-020-11775-z

https://www.sciencedirect.com/science/article/abs/pii/S0048969721001388

6. There is no text belong why the authors used generalized generalized least squares extension with the linear regression model while there are more advanced approaches available?

Methods:

7. Need more explanation in Study site: write all the tributary or contribution to the site.

8. Why authors used limited no. of influencing parameters? Is there any problem to get more no. of those parameters metrological and/or climatological?

9. Write all functions of the code used in the ‘Italic’ font.

Results and Discussion:

10. Need statistical examination such as min, max, sd, etc in Table 1

11. FigureS1: replace with more presentable with all needed information

12. Better draw PCA Biplot to analyzed the dim strength between the factors.

13. Add regression equation in all scatter plots for showing the correlation mathematically how stronger?

14. Table S2: better add into the respective graph

15. In discussion: add how this changed value (within the used years) have an impact on the environment and local community and what measure should take to mitigate it for example several adsorption studies have been applied:

https://www.sciencedirect.com/science/article/abs/pii/S0045653521006317

https://link.springer.com/article/10.1007/s11356-021-12836-7

Conclusion:

16. Add the weakness of the study.

17. Add future objective of the research including the applying machine learning approach to predict the sediment for example

https://www.sciencedirect.com/science/article/abs/pii/S0304389420314783

https://www.sciencedirect.com/science/article/abs/pii/S026974912036351X

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Salih Muhammad Awadh

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: Reviewer comment.docx

Click here for additional data file.

Submitted filename: PLOS ONE.docx

Click here for additional data file.

Submitted filename: Reviwe Temporal Deposition of Copper (Cu) and Zinc (Zn) in the Sediments of Metal Removal.docx

Click here for additional data file.

Submitted filename: PONE-D-21-10299_reviewer_Comments.pdf

Click here for additional data file.

28 Jun 2021

Response to Reviewers

Disclaimer: Please don’t mind the inconsistencies in line numbers on the track changes-version, this is a common issue in word

Reviewer 1

I consider this paper very good and is an important addition to the literature , this research predicted Copper (Cu) and Zinc (Zn) deposition patterns , the research examined and studied the effects of time, seasons, and total carbon (TC) on Copper (Cu) and Zinc (Zn) deposition in the surface sediments of the H-02 constructed wetland on the Savannah River Site .

This research Covering both warm (April-September) and cool (October-March) seasons, several sediment cores were collected twice a year from the constructed wetland cells over 7 years, from 2007 to 2013.

This research used the Generalized Least Squares (GLS) & Linear Regression Model (LRM), linear regression model explained the behaviour and the variability of Cu deposition in the sediments , using the (GLS) extension with the (LRM)allowed for unequal variance .

Here are several comments :

1- Interesting and within the journal scope manuscript and it is properly organized .

2- Have appropriate forms and have academic value.

3- Methodology flowchart for the modelling procedure is needed.

We have created a flow-chart, please refer to figure S2 in the SI file

4- The data interpreted and analysed statistically in appropriate manner.

5- Presents results in a clear way .

6- The conclusions reached are properly validated by the results.

7- The paper (Approved) ,can accepted for publication with minor revisions .

We thank the reviewer for their comments.

Reviewer 2

I read the manuscript and found it very good, as it represents a scientific research of original data with an applied character that simulates the environmental treatment of heavy elements (Cu and Zn). Field experiments, statistics and chemical analyses have been performed in high technical standard and results were presented in a clear manner mostly except for some places of the manuscript. The manuscript meets all applicable standards for the ethics of experimentation and research integrity. However, I recommend to accept the manuscript after major revision and the following points should be addressed:

1. Title must be concise and informative, so the abbreviation Cu and Zn should be deleted and title become “Temporal Deposition of Copper and Zinc in the Sediments of Metal Removal Constructed Wetlands”.

We appreciate the reviewer’s comment. However, keeping the elemental formula for both metals improves the searchability and visibility of our article to other researchers.

2. Line 59: The expression “media/soils” doesn’t be accepted, please change it in another style.

We fixed this issue, please refer to line 67.

3. Line 103-104: The author stated “Briefly, the Tritium facility discharges wastewater through source pipes into a rectangular pool where water is retained to provide hydrological control”. How much is the tritium wastewater discharged through source pipes into a rectangular basin?

We thank the reviewer for this comment. We don’t have access to such data.

4. Line 123-124: Surface standing water was carefully siphoned off from the cores avoiding disturbing the flocculent layer. To what extent surface standing water can be siphoned?

Ideally, we were careful not to disturb/siphon the flocculant layer (soft organic rich floccule-like material). The amount of surface standing water in sediment core was variable depending on the water level in the wetland at the time of sampling.

5. Line 129-130: Dried sediments were passed through a 2 mm sieve. I think after sediments be dried will need gentle grinding to be sieved easily. The sediments were only sieved, no grinding was applied. Line 176-177: In the model selection process, we followed the protocol mentioned in Zuur et al. 2009, (Zuur et al. 177 2009). Please, it is better is not to repeat the reference “Zuur et al. 2009” twice, try to reformulate the statement. Line 181: Please do not use do not use the active voice and the pronoun “we” as mentioned in “Therefore, we only kept log10TC in the model”.by the same way, look at Line 184; “Fourth, we refitted the model with the generalized”; Line 188; “Fifth, we specified the optimum fixed structure using the backward selection”; Lines191 and 192 “first, we evaluated the homogeneity of residuals using graphic tools and the Bartlett’s test of homogeneity. Second, we checked the normality graphically and by using the….”; and lines 194-195 “We used α at 0.05 as the significance level”.

We have fixed all these issues, please refer to lines 192-197 in the manuscript and Text S1 in the SI file.

6. Line 198: I suggest to change that title to “Deposition of Cu and Zn on the interface water-sediments”.

We appreciate the reviewer comment, but we analysed the metals in the whole sediment cores and not just the very top part in contact with the standing water above.

7. In both models, we find ambiguity in which layers the copper and zinc are deposited more? and why?

Only surface sediments metal data were used in the model. We have mentioned the rationale behind this in the text (Lines 176-179), but briefly, the surface sediments have considerably higher Cu, Zn, and carbon content than the layers underneath.

8. Please explain the role of Total carbon in the absorption process and its absorption capacity.

We have not performed adsorption isotherm experiments that would help figure out the adsorption process or capacity. While this would be an interesting aspect, it was beyond the scope of the current study.

9. The best was to analyze the minerals and diagnose the type of clay minerals. As is known, every clay mineral has specific value of cation exchange capacity.

We thank and agree with the reviewer. However, we have not performed such analysis.

10. It is better to make mineralogy study for the soil sample.

We appreciate the reviewer comment, this would be an interesting analysis for another follow up study. In this work, we were particularly interested in heavy metal accumulation trend over the years and seasons.

11. Line 351 “Heavy metal (Cu and Zn)”, I think lead and zinc represent a plural state, not singular, so it is better to write the term heavy metals, not heavy metal.

We appreciate the reviewer comment, please refer to line 540.

12. If you use British language, the Acknowledgments” write as “Acknowledgements”.

We appreciate the reviewer comment, please refer to line 556.

Reviewer 3

Overall, the calibration and validation processes are acceptable. So, I found the manuscript in a favorable format to be published on PLOS ONE journal with the topic “Temporal Deposition of Copper (Cu) and Zinc (Zn) in the Sediments of Metal Removal Constructed Wetlands”. This research project has the scientific background enough to be published, and the authors present a fair amount of data and a reasonable list of references. However, there is some comments needed to be observing.

1. Avoid using the first person pronouns "I or we” in your writing, and the most common reason given for this is that readers may regard such writing as being subjective, whereas science is all about objectivity.

We have fixed all these issues, please refer to lines 192-197 in the manuscript and Text S1 in the SI file.

2. manuscript should have some novelty in its work

We thank the reviewer for the feedback. We think that this works novelty comes from our use of statistical tools and 7 years- worth of data to give us insights about the accumulation pattern of heavy metals in the surface sediments of the H-02 wetland. We believe that this is an invaluable tool which we could build upon for the next years to predict the performance and thus the efficiency of the H-02 wetland, and to protect the environment and the wildlife at the Savannah River site.

3. remove “map” from the title of Fig S1 and line 101

We have replaced the word “map” with: Schematic diagram”, line 112, please refer to Fig S1 title (line 570), and Fig S1 title in the SI Paper-Track changes file.

4. fig S1 need to add the size and the scale

We have updated the figure with the required information

5. My suggestion to add Figure of study area to the manuscript

We have already provided a schematic diagram of the study area (please see Fig S1 in the SI file). Also, we don’t have access to an airborne image of the study area.

6. the methods section very long , please minimize it

We fixed this issue by moving model selection details to the SI file, please refer to Text S1 in the SI file and lines 192-197 in the manuscript.

7. the conclusion section very short and need more info, you need make balance between sections

We fixed this issue, please refer to lines 540-554.

8. Fig S5, S7, S8 and S9 titles need modify according to the charts type.

We have modified the titles, please notice that the figure numbers have been updated, please see Fig S6, S8, S9, and S10.

Reviewer 4

This is an original research paper on developing a pattern evaluation of heavy metals (Cu, Zn)

settlement in the surface constructed wetland by time and Total Carbon (TC). The topic

selected by the authors is appreciated in the specific domain of science and engineering for

several purposes like contamination treatment at a lower price and lower environmental impact

concern. Nonetheless, the work needs to be improved to reach the level of publication for

readers of the respected PLOS ONE journal.

Abstract:

1. This needs precise information on how the outcomes of the linear regression model are

going to be impacted.

We believe that we have provided precise and summarized details of the linear regression model in the abstract (lines 40-45), we would appreciate it if the reviewer would give us more clarification of what exactly we should be adding in the abstract.

2. Cu and Zn changed the value reported so TC needs to report as well.

We thank the reviewer for this comment. But since we were more focused on Cu and Zn accumulation, we dropped the TC from line 37.

3. Line 40: …On the other hand, using the generalized least squares extension with the

linear regression model allowed for unequal variance, and thus was more successful in

explaining Zn deposition pattern… what does mean ‘more successful’? rewrite it.

We added a clarifying sentence, please refer to lines 41-43.

Introduction:

4. Line50: … relatively cheaper… how? Explain it in detail.

We added a sentence to clarify our point, please refer to lines 50-51.

5. The review assessment has been poorly drafted. Add more recent (5 years) papers.

We added more recent references, please check lines 52, 54, 68-69, 77, 81, 82, 84

https://link.springer.com/article/10.1007/s11356-020-11775-z

https://www.sciencedirect.com/science/article/abs/pii/S0048969721001388

6. There is no text belong why the authors used generalized generalized least squares

extension with the linear regression model while there are more advanced approaches

available?

The generalized least squares (GLS) extension is used to handle residual heterogeneity. We added this clarification in line 115.

Methods:

7. Need more explanation in Study site: write all the tributary or contribution to the site.

There is no tributary or contribution to the site

8. Why authors used limited no. of influencing parameters? Is there any problem to get

more no. of those parameters metrological and/or climatological?

We thank the reviewer for their comment. We have not measured these parameters.

9. Write all functions of the code used in the ‘Italic’ font.

We have made the required changes. Please refer to Text S1 in the SI file.

Results and Discussion:

10. Need statistical examination such as min, max, sd, etc in Table 1

We have added the maximum, minimum, and replaced 95% confidence intervals with the standard deviation. Please refer to table 1 in the manuscript as well as lines 210 and 214.

11. FigureS1: replace with more presentable with all needed information

We have added the required information, please see Fig. S1 in the SI file.

12. Better draw PCA Biplot to analyzed the dim strength between the factors.

We appreciate the reviewer comment. However, in this work, we were more interested in addressing the accumulation behaviour of the metals in the wetland surface sediment over time and seasons. We will definitely consider PCA as a valuable tool in our upcoming work.

13. Add regression equation in all scatter plots for showing the correlation mathematically

how stronger?

We removed table S2 and added regression equations and correlation coefficients to the scatter plots. Please refer to “Fig3NEW” in the attachments.

14.Table S2: better add into the respective graph

Please see our response to comment 13 above.

15. In discussion: add how this changed value (within the used years) have an impact on

the environment and local community and what measure should take to mitigate it for

example several adsorption studies have been applied:

https://www.sciencedirect.com/science/article/abs/pii/S0045653521006317

https://link.springer.com/article/10.1007/s11356-021-12836-7

We thank the reviewer for this comment, but we have not performed any studies that would answer this question.

Conclusion:

16. Add the weakness of the study.

We have added weaknesses and future directions in the conclusion section (lines 548-562)

17. Add future objective of the research including the applying machine learning approach to predict the sediment for example

https://www.sciencedirect.com/science/article/abs/pii/S0304389420314783

https://www.sciencedirect.com/science/article/abs/pii/S026974912036351X

We have added a sentence that addressed this suggestion, please refer to lines 557-559

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

19 Jul 2021

Temporal Deposition of Copper (Cu) and Zinc (Zn) in the Sediments of Metal Removal Constructed Wetlands

PONE-D-21-10299R1

Dear Dr. Elhaj Baddar,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Zaher Mundher Yaseen

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #3: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #3: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I have reviewed the required amendments and found a good response from the researcher. He accomplished most of the basic points and answered some of them adequately. I therefore find the manuscript now is more quality, so I recommend to give an accept decision.

Additionally, I advise the author that I prefer to remove the chemical element symbols (Cu and Zn) from the manuscript title. It doesn’t mean thing to be included in the title.

Reviewer #3: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Salih Muhammad Awadh

Reviewer #3: No

Submitted filename: Review report.docx

Click here for additional data file.

26 Jul 2021

PONE-D-21-10299R1

Temporal deposition of copper and zinc in the sediments of metal removal constructed wetlands

Dear Dr. Elhaj Baddar:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Zaher Mundher Yaseen

Academic Editor

PLOS ONE