Assessment of Stormwater Quality in the Context of Traffic Congestion: A Case Study in Egypt
Round 1
Reviewer 1 Report
The manuscript provides important and useful findings on storm water quality as affected by traffic density.
I would like the authors to address the following
Methodology: what was the rationale for assigning weights (wi) to the respective parameters (Table 3)? For example, why was nitrate assigned weight of 2 and chloride 3 considering the contribution of nitrates to eutrophication of water bodies besides being an indicator of faecal contamination?
Results:
Statistical analysis should be carried out to determine the significance of the relationships between storm water quality and traffic density
Author Response
Authors Response to Reviewer 1 Comments
Comments and Suggestions for Authors
The manuscript provides important and useful findings on stormwater quality as affected by traffic density.
I would like the authors to address the following
Comment 1: Methodology: What was the rationale for assigning weights (wi) to the respective parameters (Table 3)? For example, why was nitrate assigned a weight of 2 and chloride 3 considering the contribution of nitrates to the eutrophication of water bodies besides being an indicator of fecal contamination?
Authors' response: All comments have been into consideration and the text has been modified as:
A weight of wi = 3 to 4 is assigned to contaminants that have a significant impact on water quality, whereas a weight of wi = 1 to 2 is assigned to contaminants that have little or no impact. Thus, weight = 2 is given to the following water parameters: pH, EC, SO4, CO3, HCO3, Cl, Mg, Ca, Na, and K. However, the weight attributed to TDS, TSS, TN, TP, Ni, Fe, Cu, and Al is 3. While the weights for NO3, NH4, BOD, and COD are set at 4. Additionally, the weights for Cr, Cd, Mn, Zn, and Pb are 4.
Table 3. The relative weight of stormwater physicochemical parameters.
|
Water parameter |
Unit |
wi |
Wi (%) |
|
pH |
_ |
2 |
2.56 |
|
EC |
µs/cm |
2 |
2.56 |
|
NO3 |
mg/L |
4 |
5.13 |
|
NH4 |
mg/L |
4 |
5.13 |
|
SO4 |
mg/L |
2 |
2.56 |
|
CO3 |
mg/L |
2 |
2.56 |
|
HCO3 |
mg/L |
2 |
2.56 |
|
Cl |
mg/L |
2 |
2.56 |
|
BOD |
mg/L |
4 |
5.13 |
|
COD |
mg/L |
4 |
5.13 |
|
TDS |
mg/L |
3 |
3.85 |
|
TSS |
mg/L |
3 |
3.85 |
|
TN |
mg/L |
3 |
3.85 |
|
TP |
mg/L |
3 |
3.85 |
|
Na |
mg/L |
2 |
2.56 |
|
K |
mg/L |
2 |
2.56 |
|
Mg |
mg/L |
2 |
2.56 |
|
Ca |
mg/L |
2 |
2.56 |
|
Al |
mg/L |
3 |
3.85 |
|
Cr |
mg/L |
3 |
3.85 |
|
Cd |
mg/L |
3 |
3.85 |
|
Fe |
mg/L |
3 |
3.85 |
|
Cu |
mg/L |
3 |
3.85 |
|
Mn |
mg/L |
4 |
5.13 |
|
Ni |
mg/L |
3 |
3.85 |
|
Zn |
mg/L |
4 |
5.13 |
|
Pb |
mg/L |
4 |
5.13 |
|
|
Sum |
78 |
100 |
Comment: 2 Results:
Statistical analysis should be carried out to determine the significance of the relationships between stormwater quality and traffic density.
Authors response: Statistical analysis has been carried out in Table 7 to show the significance of the relationships between stormwater quality and traffic density and Figs. 4 and 5 have been modified.
|
A |
B |
|
C |
D |
|
E |
F |
Figure 4. Variation between measured stormwater quality parameters, Egyptian water quality criteria (Egypt Decree [41,42]), and the MADT.
|
G |
H |
|
I |
J |
|
K |
L |
Continue Figure 4. Variation between measured stormwater quality parameters, Egyptian water quality criteria (Egypt Decree [41,42]), and the MADT.
|
A |
B |
|
C |
D |
|
E |
F |
Figure 5. Variation between measured stormwater heavy metals concentrations, Egyptian water quality criteria [41,42], and the MADT.
|
G |
H |
Continue Figure 5. Variation between measured stormwater heavy metals concentrations, Egyptian water quality criteria [41,42], and the MADT.
Table 7. Statistical analysis for the measured stormwater quality parameters in the light of WHO and Egyptians water quality standards.
|
Water parameter |
Unit |
A1 |
A2 |
B1 |
B2 |
C1 |
C2 |
Max. |
Min. |
S. D |
Average |
WHO [43] |
Egypt Decree [41,42] |
|
pH |
_ |
7.63 |
6.63 |
6.94 |
6 |
6.23 |
6.22 |
7.63 |
6 |
6.6 |
0.6 |
6.5-8.4 |
7.5 |
|
EC |
µs/cm |
515 |
612 |
297 |
289 |
421 |
458 |
612 |
289 |
432.0 |
114.6 |
500 |
1000 |
|
NO3 |
mg/L |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
50 |
45 |
|
NH4 |
mg/L |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.2 |
0 |
0.5 |
0.5 |
|
SO4 |
mg/L |
250 |
259 |
200 |
200 |
300 |
259 |
300 |
200 |
244.7 |
35.3 |
250 |
250 |
|
CO3 |
mg/L |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
N.D. |
300 |
|
HCO3 |
mg/L |
140.23 |
139.1 |
148.9 |
140.12 |
140.2 |
139.12 |
148.9 |
139.1 |
141.3 |
3.4 |
500 |
500 |
|
Cl |
mg/L |
39.25 |
39.2 |
36 |
30.3 |
39.3 |
39.2 |
39.3 |
30.3 |
37.2 |
3.3 |
250 |
250 |
|
BOD |
mg/L |
40 |
38 |
25 |
26 |
45 |
45 |
45 |
25 |
36.5 |
8.2 |
6 |
6 |
|
COD |
mg/L |
50 |
59.7 |
49.2 |
38.5 |
100 |
100 |
100 |
38.5 |
66.2 |
24.7 |
10 |
10 |
|
TDS |
mg/L |
329.6 |
320.15 |
190 |
189 |
269.44 |
250.3 |
329.6 |
189 |
258.1 |
55.6 |
500 |
1000 |
|
TSS |
mg/L |
817 |
750 |
200 |
200 |
790 |
759 |
817 |
200 |
586.0 |
273.8 |
800 |
800 |
|
TN |
mg/L |
1.2 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.2 |
1.17 |
1.2 |
0.0 |
3.5 |
3.5 |
|
TP |
mg/L |
5.02 |
4.99 |
4.55 |
4.02 |
6 |
6.12 |
6.12 |
4.02 |
5.1 |
0.7 |
2 |
2 |
|
Na |
mg/L |
90.03 |
91.2 |
119.22 |
90.16 |
70 |
70 |
119.22 |
70 |
88.4 |
16.5 |
200 |
200 |
|
K |
mg/L |
43.15 |
50.12 |
47.02 |
45.16 |
39.13 |
52.1 |
52.1 |
39.13 |
46.1 |
4.3 |
12 |
12 |
|
Mg |
mg/L |
46.25 |
40.23 |
50.04 |
48.12 |
40.25 |
50.19 |
50.19 |
40.23 |
45.8 |
4.2 |
30 |
30 |
|
Ca |
mg/L |
588.41 |
520.19 |
410.03 |
380.03 |
425 |
429.13 |
588.41 |
380.03 |
458.8 |
72.1 |
75 |
75 |
|
Al |
mg/L |
13.83 |
12.6 |
4.25 |
4 |
7.2 |
8.33 |
13.83 |
4 |
8.4 |
3.8 |
0.2 |
0.2 |
|
Cr |
mg/L |
0.99 |
0.99 |
0.04 |
0.11 |
0.85 |
0.86 |
0.99 |
0.04 |
0.6 |
0.4 |
0.1 |
0.05 |
|
Cd |
mg/L |
0.04 |
0.02 |
0.04 |
0.04 |
0.3 |
0.002 |
0.3 |
0.002 |
0.1 |
0.1 |
0.01 |
0.003 |
|
Fe |
mg/L |
7.6 |
6.23 |
7.2 |
8.2 |
6.23 |
5.99 |
8.2 |
5.99 |
6.9 |
0.8 |
0.3 |
0.3 |
|
Cu |
mg/L |
1.82 |
1.82 |
2 |
1.01 |
1.25 |
1 |
2 |
1 |
1.5 |
0.4 |
0.05 |
0.05 |
|
Mn |
mg/L |
0.33 |
0.39 |
0.37 |
0.33 |
0.24 |
1.39 |
1.39 |
0.24 |
0.5 |
0.4 |
0.5 |
0.4 |
|
Ni |
mg/L |
0.02 |
0.01 |
0 |
0 |
0.01 |
0.002 |
0.02 |
0 |
0.0 |
0.0 |
0.2 |
0.02 |
|
Zn |
mg/L |
3.91 |
3.44 |
3.03 |
2.45 |
3.34 |
3.84 |
3.91 |
2.45 |
3.3 |
0.5 |
0.1 |
3 |
|
Pb |
mg/L |
0 |
0 |
0 |
0 |
0 |
0.12 |
0.12 |
0 |
0 |
0 |
0.2 |
0.01 |
N.D., not detected; Max., maximum; Min., minimum; S.D., standard deviation; A1, Fasil-A1; A2, Fasil-A2; B1, El Dokki-B1; B2, El Dokki-B2; C1, Hadak E.-C1; and C2, Hadak E.-C2.
The authors are thankful to Reviewer 1 for his important comments and efforts to improve this manuscript.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Please see my comments in the attached file.
Comments for author File: Comments.pdf
the English needs to be revised by a native.
Author Response
Authors response to Reviewer 2 comments
Comment 1: What is the unit of Monthly Average Daily Traffic?
Authors response: All comments have been into consideration and the text has been modified using the track change tool.
cars. (Revised in the text)
Comment 2: Please rewrite this sentence.
Authors response: done:
The indicators of the stormwater quality for irrigation total dissolved solids (TDS), sodium adsorption ratio (SAR), soluble sodium percentage (SSP), permeability index (PI), magnesium adsorption ratio (MAR), and Kelley's ratio (KR) show excellent stormwater for irrigation while total hardness (TH) and residual sodium bicarbonate (RSBC) indicate poor irrigation water quality.
Comment 3: Please revise this sentence as it seems to point out a global issue.
Authors response: done:
Over the past few years, Egypt has struggled with an annual water deficit of almost 7 km3 by 2025, the nation woruld "run out of water" completely [7].
Comment 4: Please add relevant references
Authors response: Done [1]
- Abdelazim, N. Conventional water resources and agriculture in Egypt. In: The handbook of environmental chemistry 2019. Vol. 74. Cham: Springer; p. 233–241.
Comment 5: Why in the table caption only reference no. 28 is cited? apart from that, is this table necessary for this study?
Authors response: revised, Table reference is [27,28]
Comment 6: Needs more explanations to be connected with the present study.
Authors response: Done:
For the people, getting where they are going and carrying any estimates of how long it will take them to get there is difficult. There could be additional issues and delays for the individuals at work [40]. Therefore, these traffic congests contribute to polluting air and road surfaces as stated in Table 1.
Comment 6: Including
Authors response: Added to the text.
Comment 7: or rainfall depth?
Authors response: Revised to rainfall depth
Comment 8: Regarding my previous comment, "rainfall depth" or "rainfall rate"? In the legend of the figure, it's indicated as mm/d, but the left vertical axes show it in mm. Kindly review this for consistency.
Authors response: Revised and modified.
Comment 9: This section can be omitted to enhance brevity, while still providing a reference in the preceding sentence.
Authors response: This section is deleted.
Comment 10: Have these land uses been separated?
Authors response: Yes
Comment 11: The figure legend requires correction, as it currently states that rainwater was sampled, whereas, in reality, it was stormwater that was sampled.
Authors response: It is corrected.
Comment 12: Satormwater
Comment 13: Please rewrite
Authors response: Revised.
The samples of stormwater were obtained in a one-liter high-density polyethylene bottle, pre-cleaned with 10% nitric acid, rinsed repeatedly with bi-distilled water, stabilized with ultrapure nitric acid (0.5% HNO3), and stored at a temperature of around 4 °C.
Comment 14: The sentence is not complete
Authors response: revised as:
The water samples were analyzed for physicochemical characteristics water temperature, Electrical Conductivity (EC), and total dissolved solids (TDS). The chemical parameters are pH, total hardness (TH), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total nitrogen (TN), total suspended solids (TSS), Na+, Ca2+, K+, and Mg2+ (major cations), and CO32-, and SO42– (major anions). Inductively coupled plasma was used for the determination of the heavy metals Al, Cr, Cd, Fe, Cu, Mn, Ni, Zn, and Pb; and major cations Na+, Ca2+, K+, and Mg2+ according to ASTM D8110-17 (Model: ICAP 7400).
Comment 15: It is hard to understand. please rewrite
Authors response: revised as:
In accordance with ASTM D5907-18, the filtrated sample (liquid phase) was then evaporated to constant weight at 180 °C.
Comment 16: there is no "Q" in the equation 2
Authors response: It is delated
Comment 17: please rewrite including the symbols
Authors response: Done
Comment 18: are the third and forth columns physicochemical parameters? furthermore, columns 1-4 are repeated in Table 7. perhaps Tables 1 and 7 could be merged
Authors response: Table 3 is revised as:
Table 3. The relative weight of stormwater physicochemical parameters.
|
Water parameter |
Unit |
wi |
Wi (%) |
|
pH |
_ |
2 |
2.56 |
|
EC |
µs/cm |
2 |
2.56 |
|
NO3 |
mg/L |
4 |
5.13 |
|
NH4 |
mg/L |
4 |
5.13 |
|
SO4 |
mg/L |
2 |
2.56 |
|
CO3 |
mg/L |
2 |
2.56 |
|
HCO3 |
mg/L |
2 |
2.56 |
|
Cl |
mg/L |
2 |
2.56 |
|
BOD |
mg/L |
4 |
5.13 |
|
COD |
mg/L |
4 |
5.13 |
|
TDS |
mg/L |
3 |
3.85 |
|
TSS |
mg/L |
3 |
3.85 |
|
TN |
mg/L |
3 |
3.85 |
|
TP |
mg/L |
3 |
3.85 |
|
Na |
mg/L |
2 |
2.56 |
|
K |
mg/L |
2 |
2.56 |
|
Mg |
mg/L |
2 |
2.56 |
|
Ca |
mg/L |
2 |
2.56 |
|
Al |
mg/L |
3 |
3.85 |
|
Cr |
mg/L |
3 |
3.85 |
|
Cd |
mg/L |
3 |
3.85 |
|
Fe |
mg/L |
3 |
3.85 |
|
Cu |
mg/L |
3 |
3.85 |
|
Mn |
mg/L |
4 |
5.13 |
|
Ni |
mg/L |
3 |
3.85 |
|
Zn |
mg/L |
4 |
5.13 |
|
Pb |
mg/L |
4 |
5.13 |
|
|
Sum |
78 |
100 |
Wi is the relative weight of the ith parameter; and, wi is the weight of each parameter.
Comment 19: It appears that "wi" and "Wi" might have been used incorrectly in this context.
Authors response: Revised
Comment 20: The WQI values can be grouped NOT "The calculated (WQI) values are grouped". also, please add the reference at the end of this sentence as well.
Authors response: Revised as:
The calculated (WQI) values can be grouped into six categories as shown in Table 4 [37].
Comment 21: suitability for
Authors response: Revised
Authors response: Done
2.5. Evaluation of the suitability of irrigation water quality
Comment 22: How much significant it was? Furthermore figure 4G represents the TSS not heavy metals
Authors response: Fig. 4 is modified as:
Figure 4. Variation between measured stormwater quality parameters, Egyptian water quality criteria (Egypt Decree [41,42]), and the MADT.
Comment 23: Only part G is referred. what about other parts of figure 4? they should be referenced and discussed in the text
Authors response: Revised as:
Figure 4 A shows the variation of MADT for the studied sites and the pH indicating acid stormwater at El Dokki-B2, Hadak E.-C1, Hadak E.-C2. Figure 4 B shows the variation of MADT for the studied sites and the EC indicating low EC values for the stormwater at the smallest MADT at El Dokki-B2 and El Dokki-B2. On the other hand, the variation of MADT has no effect on the HCO3, Cl, NH4, and TN concentrations as shown in Figures 4C, 4D, 4E, and 4I respectively. In addition, the variation of BOD, COD, and TP concentrations with the MADT for the studied sites show small variation as these pollutants come from point pollutant sources and do not depend on the traffic congestion as shown in Figures 4K, 4L, and 4J respectively. Figure 4G shows the significant correlations between MADT and heavy metals. The results indicated that the concentration of TSS in stormwater is influenced by the traffic intensity where sites A and C show significantly higher pollution of TSS because the traffic intensity at A is more than twice that of B and C.
Comment 24: Columns 1-4 are repeated in Table 4
Authors response: the table is revised and modified as:
Table 7. Statistical analysis for the measured stormwater quality parameters in the light of WHO and Egyptian water quality standards.
|
Water parameter |
Unit |
A1 |
A2 |
B1 |
B2 |
C1 |
C2 |
Max. |
Min. |
S. D |
Average |
WHO [43] |
Egypt Decree [41,42] |
|
pH |
_ |
7.63 |
6.63 |
6.94 |
6 |
6.23 |
6.22 |
7.63 |
6 |
6.6 |
0.6 |
6.5-8.4 |
7.5 |
|
EC |
µs/cm |
515 |
612 |
297 |
289 |
421 |
458 |
612 |
289 |
432.0 |
114.6 |
500 |
1000 |
|
NO3 |
mg/L |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
50 |
45 |
|
NH4 |
mg/L |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.2 |
0 |
0.5 |
0.5 |
|
SO4 |
mg/L |
250 |
259 |
200 |
200 |
300 |
259 |
300 |
200 |
244.7 |
35.3 |
250 |
250 |
|
CO3 |
mg/L |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
N.D. |
300 |
|
HCO3 |
mg/L |
140.23 |
139.1 |
148.9 |
140.12 |
140.2 |
139.12 |
148.9 |
139.1 |
141.3 |
3.4 |
500 |
500 |
|
Cl |
mg/L |
39.25 |
39.2 |
36 |
30.3 |
39.3 |
39.2 |
39.3 |
30.3 |
37.2 |
3.3 |
250 |
250 |
|
BOD |
mg/L |
40 |
38 |
25 |
26 |
45 |
45 |
45 |
25 |
36.5 |
8.2 |
6 |
6 |
|
COD |
mg/L |
50 |
59.7 |
49.2 |
38.5 |
100 |
100 |
100 |
38.5 |
66.2 |
24.7 |
10 |
10 |
|
TDS |
mg/L |
329.6 |
320.15 |
190 |
189 |
269.44 |
250.3 |
329.6 |
189 |
258.1 |
55.6 |
500 |
1000 |
|
TSS |
mg/L |
817 |
750 |
200 |
200 |
790 |
759 |
817 |
200 |
586.0 |
273.8 |
800 |
800 |
|
TN |
mg/L |
1.2 |
1.17 |
1.17 |
1.17 |
1.17 |
1.17 |
1.2 |
1.17 |
1.2 |
0.0 |
3.5 |
3.5 |
|
TP |
mg/L |
5.02 |
4.99 |
4.55 |
4.02 |
6 |
6.12 |
6.12 |
4.02 |
5.1 |
0.7 |
2 |
2 |
|
Na |
mg/L |
90.03 |
91.2 |
119.22 |
90.16 |
70 |
70 |
119.22 |
70 |
88.4 |
16.5 |
200 |
200 |
|
K |
mg/L |
43.15 |
50.12 |
47.02 |
45.16 |
39.13 |
52.1 |
52.1 |
39.13 |
46.1 |
4.3 |
12 |
12 |
|
Mg |
mg/L |
46.25 |
40.23 |
50.04 |
48.12 |
40.25 |
50.19 |
50.19 |
40.23 |
45.8 |
4.2 |
30 |
30 |
|
Ca |
mg/L |
588.41 |
520.19 |
410.03 |
380.03 |
425 |
429.13 |
588.41 |
380.03 |
458.8 |
72.1 |
75 |
75 |
|
Al |
mg/L |
13.83 |
12.6 |
4.25 |
4 |
7.2 |
8.33 |
13.83 |
4 |
8.4 |
3.8 |
0.2 |
0.2 |
|
Cr |
mg/L |
0.99 |
0.99 |
0.04 |
0.11 |
0.85 |
0.86 |
0.99 |
0.04 |
0.6 |
0.4 |
0.1 |
0.05 |
|
Cd |
mg/L |
0.04 |
0.02 |
0.04 |
0.04 |
0.3 |
0.002 |
0.3 |
0.002 |
0.1 |
0.1 |
0.01 |
0.003 |
|
Fe |
mg/L |
7.6 |
6.23 |
7.2 |
8.2 |
6.23 |
5.99 |
8.2 |
5.99 |
6.9 |
0.8 |
0.3 |
0.3 |
|
Cu |
mg/L |
1.82 |
1.82 |
2 |
1.01 |
1.25 |
1 |
2 |
1 |
1.5 |
0.4 |
0.05 |
0.05 |
|
Mn |
mg/L |
0.33 |
0.39 |
0.37 |
0.33 |
0.24 |
1.39 |
1.39 |
0.24 |
0.5 |
0.4 |
0.5 |
0.4 |
|
Ni |
mg/L |
0.02 |
0.01 |
0 |
0 |
0.01 |
0.002 |
0.02 |
0 |
0.0 |
0.0 |
0.2 |
0.02 |
|
Zn |
mg/L |
3.91 |
3.44 |
3.03 |
2.45 |
3.34 |
3.84 |
3.91 |
2.45 |
3.3 |
0.5 |
0.1 |
3 |
|
Pb |
mg/L |
0 |
0 |
0 |
0 |
0 |
0.12 |
0.12 |
0 |
0 |
0 |
0.2 |
0.01 |
N.D., not detected; Max., maximum; Min., minimum; S.D., standard deviation; A1, Fasil-A1; A2, Fasil-A2; B1, El Dokki-B1; B2, El Dokki-B2; C1, Hadak E.-C1; and C2, Hadak E.
Comment 25: It is hard to find a relationship from this figure as it predominantly illustrates variations in these parameters rather than a distinct correlation. please revise the caption
Authors response: Revised as statistical analysis is carried out and the error bars are added to the Figures.
Comment 26: How can you ensure that the measured pollutants were primarily a result of traffic-related sources? As indicated in lines 148-149, air pollution is a significant issue in the studied area. Therefore, theoretically, these measurements could also be linked to air pollution.
Authors response: revised as:
In addition, the heavy traffic and other human activities that produce air pollutants such as ozone, carbon dioxide, hydrocarbons, Sulphur oxides, and suspended particulate matter contribute to a decrease in the pH indicating acid stormwater (Figure 4A).
Comment 27: How was this correlation analysis performed?
Authors response: the text has been revised as:
For the six stormwater samples from Fasil-A1-A2, El Dokki-B1-B2, and Hadak E.-C1-C2, using the Excel program the correlation matrix between the researched physio-chemical parameters and WQI was performed and examined as shown in Table10.
Comment 28: To what extent can these conclusions be considered reliable? As the stormwater quality changes significantly during a specific event, when the single samples were collected? it is a big issue in the present study.
Authors' response: The text was revised as:
The careful selection of the location for single sample collection is a crucial issue because the stormwater quality changes significantly during a specific event. The location should be favorable for the stormwater and satisfy the following criteria: (i) the outfall locations, including longitude and latitude recurving water are certain, (ii) the site drainage map, (iii) estimation of the impervious area within each outfall drainage area, (iv) facility improvement which may affect the discharge described, (v) the facility's history of large leaks or spills of toxic or hazardous pollutants within the last three years, as well as the location and description of any existing structures and nonstructural pollutants sources like onsite materials that may come into contact with stormwater runoff, are all factors that should be considered. The obtained sampling data from stormwater flows, which is a useful tool to identify pollutant sources, best management practices, and plans for preventing stormwater pollution can be developed to prioritize eradicating these sources. There are alternatives, such as removing particle-bound pollution using non-structural preventive methods before it enters storm drain water, including street sweeping. Installing an adequate stormwater sewerage system is also advised to collect rainwater. In addition, the use of renewable energy throughout the manufacturing and battery production processes will lower CO2 emissions, and battery electric vehicles are more energy-efficient. To deal with the traffic congestion solutions, (i) smart road design is recommended, (ii) by substituting a few open roadway lanes for bus lanes, carpool lanes, or even sidewalks, a civil engineer's plan can decrease the overall number of vehicles on the road because some potential drivers might decide to use another mode of transportation that is more cost-effective or better suits their lifestyle, and (iii) according to the United States Public Interest Research Group (USPIRG) report for 2022 that emphasizes the need for increased funding for public transportation alternatives across the country. Increased public transit usage is justified by claims of decreased oil consumption (USPIRG calculates that even current public transportation use saves billions of gallons annually), decreased traffic, and a milder national environmental impact. Finally, carrying out seasonal monitoring for stormwater quality is an important issue for the best management practices and policies for reducing stormwater pollution.
The authors are thankful to Reviewer 2 for his important comments and efforts to improve this manuscript.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments for author File: Comments.pdf
Author Response
Authors response to Reviewer 3 comments
Comment 1: Based on my evaluation, I recommend that this manuscript be significantly improved before consideration for publication in the following aspects:
- Focus and Misalignment of Research Objectives: The manuscript's aim, as stated, is to investigate the effect of traffic congestion in urbanized areas on stormwater quality. However, the content of the manuscript primarily revolves around stormwater quality assessment and its suitability for reuse. This misalignment between the title, research aim, and the main body of the study significantly undermines the cohesiveness and clarity of the research, making it difficult for readers to comprehend the purpose and scope of the study.
Authors response: all comments have been taken into consideration and the manuscript title has been changed to:
Assessment of stormwater quality in the context of traffic congestion: A case study in Egypt.
The research methodology at the end of the introduction section has been modified to:
The aim of this study is to focus on an insightful picture of the stormwater quality for different uses in the context of traffic congestion. To accomplish this, (i) it is reviewed the earlier research on the effect of high traffic volume on stormwater quality, (ii) a case study for assessment of storm-water quality in Egypt is considered, where three urban catchments with varying traffic intensities in Faisal-A, Dokki-B, and Hadayek El-Ahram- C regions were examined, (iii) For the year 2021, the monthly average daily traffic (MADT) data were collected and analyzed for the studied three urban catchments; (iv) laboratory analysis (physical, chemical, and biological) was carried out for the collected stormwater for 6 samples during the winter season for each region, distributed as follows: Faisal-A (13 March and 12 December 2021), El Dokki-B two samples as (14 March and 20 January 2021), and Hadayek El-Ahram-C (3 January and 5 February 2021), (v) the stormwater quality is assessed using the water quality index (WQI) in comparison to the Egyptian water quality criteria [41,42] and the World Health Organization [43]. In addition, the stormwater quality indices for irrigation including total dissolved solids (TDS), sodium adsorption ratio (SAR), total hardness (TH), soluble sodium percentage (SSP), permeability index (PI), residual sodium bicarbonate (RSBC), magnesium adsorption ratio (MAR), and Kelley's ratio (KR) were applied, and finally (vi) conclusions and recommendations were presented.
Comment 2: Data Presentation and Statistical Rigor: Figure 4 attempts to illustrate the correlation between MADT (Mean Annual Daily Traffic) and stormwater constituents. However, the representation of a single MADT value per sampling site is not conducive to establishing meaningful correlations. This limited data approach lacks statistical rigor and does not provide the necessary foundation for drawing valid conclusions. The manuscript's conclusions based on this data presentation are therefore neither reliable nor scientifically sound.
Authors response: It is revised to:
The aim of this study is to focus on an insightful picture for the stormwater quality in the context of traffic congestion and in the conclusion section it is recommended:
To carry out seasonal monitoring for the stormwater quality in order to define the best management practices and policies for reducing stormwater pollution.
Comment 3: Statements in Results: The results section of the manuscript contains numerous assertions that lack proper substantiation. Critical scientific practice necessitates those statements be supported by empirical data, appropriate statistical analysis, or references to existing literature. The absence of such support raises concerns about the validity of the findings and the overall reliability of the study.
Authors response: The results section has been modified and strengthen.
Given these fundamental shortcomings, I believe that the manuscript, in its current state, does not meet the standards necessary for publication in a reputable journal such as Sustainability. I strongly recommend that the authors significantly revise and improve the manuscript to address the issues outlined above. In particular, a thorough reassessment of research objectives, data presentation, statistical analysis, and the results section is imperative.
Authors response: All the comments have been taken into consideration and the manuscript has been modified. The statistical analysis was carried out in Table 7 and the results section is imperative.
The authors are thankful to Reviewer 3 for his important comments and efforts to improve this manuscript
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
The Authors have made an effort to improve the manuscript. In my opinion, it can be suggested for publication in its current form.
Best regards
Reviewer 3 Report
I am satisfied with the current version.
I am satisfied with the current version.
