Round 1

Reviewer 1 Report

Cost Benefit Analysis of Municipal Sludge

General Comments:

This is a well-written manuscript with practical and valuable application to sustainable biosolids/sludge management. The manuscript presents an economic evaluation of transportation and agricultural application of biosolids across a range of climate zones in South Africa.

The methodology is laid out in a straightforward and transparent way, and agronomic assumptions are reasonable and well-grounded. Inputs include estimated crop yield, fertilizer recommendations, and biosolids nutrient availability for each climate zone, and hauling and spreading costs. Although developed for South Africa, the methodology should have widespread applicability.

General Suggestions:

The methodology is conservative, focused on costs and factors that are easily measured or well documented. This approach is robust and appropriate, but does not include benefits of biosolids application that are difficult to measure economically. These include increased soil organic matter and improved soil quality typical of biosolids-amended sites, and the avoided costs of non-beneficial disposal. I suggest that the authors acknowledge that these benefits add to the value of the biosolids, even though they do not fit into their economic analysis. This could be included in the Conclusions. In some circumstances biosolids managers may want to increase haul distances beyond those recommended in light of these additional, but hard to measure factors.

This methodology can be a useful tool for biosolids managers in their site selection process for agricultural application. Do the authors have an on-line or downloadable calculator based on the methodology that would allow managers to input their own biosolids and crop/fertilizer data to make the calculation site specific? This would be of value across South Africa and beyond.

Specific Comments:

Line 34. Should be Olsen-P

Line 11. Rate of truck

Lines 223-227. The acronyms in lines 225-227 do not match those in the equation in line 223. I suggest checking these and all other acronyms for consistency.

Line 288. Edit to add “, lower N availability,” after “lower crop nutrient requirements”

Line 290. Replace “price” with “value”

Table 4 heading. Unit should be $ rather than R for Total value of available nutrients from sludge (TVANA)

Table 6 column headings. Units should be $ rather than R? I also wonder if Table 6 is even necessary. I suggest that the authors think about removing it.

 

Author Response

Response to Reviewer 1 Comments

 

General comments
Point 1: The methodology is conservative, focused on costs and factors that are easily measured or well documented. This approach is robust and appropriate, but does not include benefits of biosolids application that are difficult to measure economically. These include increased soil organic matter and improved soil quality typical of biosolids-amended sites, and the avoided costs of non-beneficial disposal. I suggest that the authors acknowledge that these benefits add to the value of the biosolids, even though they do not fit into their economic analysis. This could be included in the Conclusions. In some circumstances biosolids managers may want to increase haul distances beyond those recommended in light of these additional, but hard to measure factors.


 

Response 1: Agree absolutly. Thanks. Point well taken and the following has been added to the revised manuscript (lines 401 – 406 in revised version). “. The methodology used in the current investigation was conservative for it relied only on measureable factors by excluding other biosolid benefits that are difficult to measure. Some of the benefits that are difficult to measure and has been excluded include: improved soil quality in biosolid-amended soils and avoided costs of non-beneficial disposal. Hence, in light of these additional but hard to measure factors, the over haul distance could increase beyond the recommended distance.”  

 

Point 2: This methodology can be a useful tool for biosolids managers in their site selection process for agricultural application. Do the authors have an on-line or downloadable calculator based on the methodology that would allow managers to input their own biosolids and crop/fertilizer data to make the calculation site specific? This would be of value across South Africa and beyond.

 

Response 2: A software by the name Sludge Application Rate Advisor model “SARA” has been developed. Some wastewater treatment plants in South Africa has already started to use it specially for sludge classification because it has a section on sludge classification, which will inform the quality of the sludge from the microbial, pollutant and stability perspective. It will be deployed soon in the South African Water Research Commission website and in our Institution web site, University of Pretoria, Department of Plant and Soil Science.

 

 

Specific comments
 

Point 3: Line 34. Should be Olsen-P

 

Response 3: Thank you. Rectified (line 34 in revised version)

 

 

Point 4: Line 111. Rate of truck

 

Response 4: Thank you. Rectified (lines 111, 198, 199 in revised version)

 

Point 5: Lines 223-227. The acronyms in lines 225-227 do not match those in the equation in line 223. I suggest checking these and all other acronyms for consistency.

 

Response 5: Thank you for picking up the TYPO. The acronyms have been corrected. Other acronyms in the manuscript has also been checked for consistency (lines 222 – 224 in revised manuscript)

 

 

Point 6: Line 288. Edit to add “, lower N availability,” after “lower crop nutrient requirements”

 

Response 6: Thank you. Phrase added. (lines 285 – 286 in revised manuscript)

 

 

Point 7: Line 290. Replace “price” with “value”

 

Response 7: Thank you. Replaced (lines 287 in revised manuscript).

 

 

Point 8: Table 4 heading. Unit should be $ rather than R for Total value of available nutrients from sludge (TVANA)

 

Response 8: Thank you. “R” replaced with “$” (Table 4 heading in revised manuscript).

 

 

Point 9: Table 6 column headings. Units should be $ rather than R? I also wonder if Table 6 is even necessary. I suggest that the authors think about removing it.

 

Response 9: We believe that retaining the Table would help the reader understand visually how the decision on the maximum economic distance was reached. Nonetheless, if the reviewer believes that the background information is enough, we may consider removing it. The typo error “R” has been replaced with “$” (Table 6 heading in revised version).

Author Response File: Author Response.docx

Reviewer 2 Report

After reading the entire manuscript, I have no comments whatsoever, only an assessment of its good quality.

I confirm that:

• In this study cost benefit analysis of sludge were conducted to investigate the ideal perimeter around water care works, where sludge could be economically transported using commercial inorganic fertilizer as a benchmark
• Linguistically (English language) well written
• The introduction is understandable and explains the meaning of the work and state of the art of knowledge in this area.
• There is little published work that a sludge can be economically transported to use it as a low-grade fertilizer in comparison to commercial inorganic fertilizer price, transport and spreading costs
• Materials and methods clearly comprehensibly written and in goo relation to the manuscript topic.
• It is important to note that sludge is a low-grade nutrient and its economic value as fertilizer also diminishes with an increase in distance between the wastewater treatment plant and the farm. This is mainly due to an increase in transportation cost
• The results and the discussion are understandable, authors compared the obtained results to other studies which were supplement the lack of knowledge in this area.
• Conclusion short with strict conclusion show concrete applications and confirmation of the obtained results.

 

 

Author Response

Thank you.

No comments was provided for our attention.

Reviewer 3 Report

An interesting analysis that tackles an important question of feasibility.  The authors are on track to creating a tool that will help make the case for use of municipal sludge as a resource, and need to take the nice work they have done and pull it together to allow this very practical analysis to be used for real applications.  Some specific comments on the mansucript:

• The authors indicate that no previous analysis of maximum distance for economic sludge  transportation exists.  However, similar analysis for other resources must exist and should be cited here.
• The authors will benefit from looking to the Industrial Symbiosis literature for case-studies and models that provide the foundation for their work.  Sludge and many other waste-to-resource applications have been considered, modeled, and demonstrated
• Table 2 should show the amount of nutrient added for P and K both as a kg/ha value and as a percentage of ideal, so the reader can understand the extent of over/under dosing
• The sludge recommendation (Eq. 1) fails to account for the variation of how much is released in each year of a sludge application cycle.  An average will result in over-fertilized crops in one year and under-fertilized in others, unless the excess is consistently maintained in the soil after mineralization and not lost in runoff.
• Pg 8 the authors related MED to TVANS, however these are in different units (km vs $/ha).  Clarify this paragraph.  It is also unclear in the model here how MED relates to TCS, or how non-linear costs related to distance are accounted for (e.g. it will not cost 10x more to move sludge 100 km than 10 km, the cost will probably be roughly identical, or a few cents different in gas and driver time)
• There is no Eq. 5.  Maybe this is meant to be the equation for MED, which is not expressed at any point through an equation; due to theis absence, Table 6 appears to be created without any link to real information.
• After Equation 6, an integrated equation should be developed that shows the relationship between all the different terms.  As written, Eq 1-6 are a set of very simple assumptions about relationships, which are useful in their simplicity only if they can be integrated to infer relationships between parameters.
• The extreme difference in value of available nutrients between arid and humid is poorly explained.  The sludge application rate is dictated by crop nitrogen requirement, but so would be the fertilizer application rate.  So the fertilization value should be the same regardless.
• What are the error bars on your study?  Your analysis is written as though you get wildly different numbers between Jo-burg and Nelspruit, but the recommendations are 13.8 vs 13.5 t/ha.  These numbers do not seem likely to be statistically different from one another if you do any sort of sensistivity analysis on the model.
• Paragraph at line 311 is a repeat
• There are some typographic errors and minor grammatical mistakes throughout that will benefit from an extra proofread of the final version.
• One fundamental assumption that is made in this paper, that needs to be justified and backed with significant literature, is the idea that sludge can be taken and applied to fields without any further treatment (this assumption arises in the cost of sludge including only transport and spreading costs).  It seems that some treatment would be needed for safe contact with humans, waterways, and croplands, and these costs need to be factored in, or their exclusion justified robustly.
• It is generally unclear in the tables throughout the paper which values are obtained from the literature and which are calculated through the model.  While it is interesting to see the various information broken down into steps, the connection between real data inputs and model calculations is lost through the thread.  There seem to be rather a lot of significant figures in some of the output values relative to the input values.

Overall, this paper presents a number of interesting ideas, but needs to bring them together into a more comprehensive model.  The authors need to apply a sensitivity analysis to their model; this will help with drawing more detailed conclusions about what factors have major influence.  It would be ideal to see this presented as a single equation "tool" that a practitioner could use to input their known parameters (nutrient needs, climate zone, distance, etc) and get outputs that give them a sense of their economic feasibility, or conversely to put in price points and find out "how close by do I need my sludge to come from?"  Adding this layer, along with a few details and clarifications as discussed above will take this paper to the next step of being an excellent publication and resource to the community.

Author Response

Response to Reviewer 3 Comments

 

General comments

Point 1: The authors indicate that no previous analysis of maximum distance for economic sludge transportation exists.  However, similar analysis for other resources must exist and should be cited here.




Response 1: In our motivation, we stated that there is little published work, if available about the maximum distance that a sludge can be economically transported. Though we considered including similar analysis for other resources, the assumptions built around and the implications thereof are quite different, which makes it redundant. Hence, we do not see the need as it does not add value at all to the manuscript.

 

 

Point 2: The authors will benefit from looking to the Industrial Symbiosis literature for case-studies and models that provide the foundation for their work.  Sludge and many other waste-to-resource applications have been considered, modelled, and demonstrated.

 

Response 2:  The authors agree with suggestion from the reviewer with regard to the benefits that we could get from looking to the Industrial Symbiosis literature for case studies and models that provide the foundation for our work. We are aware of the various waste-to-resource applications. In this study of ours, our study is focusing on the economic feasibility of using biosolid as an alternative fertilizer and the maximum economic distance that a biosolid could be overhauled. The only precondition is the sludge quality has to be of class A1a (suitable for agriculture use microbially, contaminant, and stability) or class D, according to EPA classification.  

 

 

Point 3: Table 2 should show the amount of nutrient added for P and K both as a kg/ha value and as a percentage of ideal, so the reader can understand the extent of over/under dosing

 

 

Response 3: The amount of P and K (kg/ha) added is already presented in Table 2. The relative contribution (%) of P and K from sludge applied to satisfy crop N requirement, however is soil (geology) dependent (for potassium, it depends on the amount of ammonium extractable potassium in the soil and for phosphorus it depends on the Bray or Olsen or Throug extractable phosphorous in the soil). Hence, including the percentage will provide misleading information. The database model (SARA mode) that we developed using the equations in this manuscript takes all these into account to determine the amount of ideal P and K added to the farm as biosolid as applied according to crop N requirement. If the reviewer, however, insists on including the percentage contribution assuming zero contribution from the soil, which is not real, we may consider including it. 

 

 

Point 4: The sludge recommendation (Eq. 1) fails to account for the variation of how much is released in each year of a sludge application cycle.  An average will result in over-fertilized crops in one year and under-fertilized in others, unless the excess is consistently maintained in the soil after mineralization and not lost in runoff.

 

 

Response 4: As stated by the reviewer in the later sentence, any excess is maintained to the next season. The mineralization rate presented in equation 1, is dynamic and varies depending on the sludge application timing (whether it is for the first time, second or third or fourth round on the site). This is handled in our Database model (SARA model). The model requires the year of application as an input.

A long term model simulation on N mineralization rate and equilibrium for all South African agro-ecological zones and soil types has already been and done and is published in the Journal of ecological modelling (refer below). Similarly, potential nitrate leaching studies from sludge applied according to recommendations generated using the database model has also been published (refer below).

Ogbazghi, Z.M. E.H. Tesfamariam and J.G. Annandale. 2016. Modelling N mineralization from sludge-amended soils across agro-ecological zones: A case study from South Africa. J. Ecol. Modelling 322:19-30.

Ogbazghi, Z.M., E.H. Tesfamariam and J.G. Annandale. 2019. Modelling maize grain yield and nitrate leaching from sludge-amended soils across agro-ecological zones: A case study from South Africa. Water SA 45:663-671.  https://doi.org/10.4314/wsa.v45i4.04

 

 

Point 5: Pg 8 the authors related MED to TVANS, however these are in different units (km vs $/ha).  Clarify this paragraph.  It is also unclear in the model here how MED relates to TCS, or how non-linear costs related to distance are accounted for (e.g. it will not cost 10x more to move sludge 100 km than 10 km, the cost will probably be roughly identical, or a few cents different in gas and driver time)

 

Response 5: A phrase “The total cost (TCS) incured for a maximum economic distance...” has been added to clarify the paragraph.

How MED relates to TCS is clarified by the phrase added in the revised manuscript. It has also been clearly stated how TCS is computed in Eq. 3 The non-linear cost related to distance are accounted for or computed using the equation presented on line 225 (TRCS = DNr).     

 

 

Point 6: There is no Eq. 5.  Maybe this is meant to be the equation for MED, which is not expressed at any point through an equation; due to the absence, Table 6 appears to be created without any link to real information.

 

Response 6: It is a typo. The MED as stated on lines 231-233 is the distance (km) where the total costs of sludge (TCS) is ≤ TVANS. This distance is computed through iteration by computing the total cost of sludge for each km until you reach to the distance where the the TCS is ≤ TVANS and that is how Table 6 is generated. Our SARA model does this iteration until it reaches this threshold value. Hence we have rectified the typo “Eq 6” by replacing it with “Eq. 5”.

 

 

Point 7: After Equation 6, an integrated equation should be developed that shows the relationship between all the different terms.  As written, Eq 1-6 are a set of very simple assumptions about relationships, which are useful in their simplicity only if they can be integrated to infer relationships between parameters.

 

Response 7: The equations are presented step wise in a logical manner in order to provide the reader a clear relationship among them. Hence, trying to put them together via a flow diagram to show their relationship is not a trivial work but will be redundant.  

 

 

Point 8: The extreme difference in value of available nutrients between arid and humid is poorly explained.  The sludge application rate is dictated by crop nitrogen requirement, but so would be the fertilizer application rate.  So the fertilization value should be the same regardless.

 

Response 8: The sludge application rate is not only influenced by the crop nitrogen requirement but also by the sludge decomposition rate, which is influenced by soil temperature and soil water. This is explained in detail in the manuscript on lines 146 – 164. The explanation provided in lines 292 – 298 with regard to the difference in nutrient availability between Johannesburg and Nelspruit also applies between arid and humid zones.

The difference in the value of available nutrients among the six South African agro-ecological zones, which forms the backbone of information in this manuscript is explained in detail in our previous publication (Ogbazghi et al., 2016), which has been referred in this manuscript several times.

Ogbazghi, Z.M. E.H. Tesfamariam and J.G. Annandale. 2016. Modelling N mineralization from sludge-amended soils across agro-ecological zones: A case study from South Africa. J. Ecol. Modelling 322:19-30.

 

 

Point 9: What are the error bars on your study?  Your analysis is written as though you get wildly different numbers between Jo-burg and Nelspruit, but the recommendations are 13.8 vs 13.5 t/ha.  These numbers do not seem likely to be statistically different from one another if you do any sort of sensitivity analysis on the model.

 

Response 9: As stated in our response to point 8, the recommendation rates were generated from mean data of more than 20 years of study. We used the recommendation rates as we got them from our published work (Ogbazghi et al., 2016) with the aim to do a cost benefit analysis of municipal sludge as a low-grade nutrient source. Hence, we did not use error bars and statistical difference comparisons. Such work could be done separately by generating various scenarios for various agro-ecological zones, soil types, and crop types, which is beyond the scope of this manuscript. 

                                                     

 

Point 10: Paragraph at line 311 is a repeat.

 

Response 10:  Thank you. Deleted.

 

 

Point 11: There are some typographic errors and minor grammatical mistakes throughout that will benefit from an extra proofread of the final version.

 

Response 11: Thanks. We have incorporated some typographic errors and mistakes that has been highlighted by reviewer 1 and we have done additional corrections from our side.

 

Point 12: One fundamental assumption that is made in this paper, that needs to be justified and backed with significant literature, is the idea that sludge can be taken and applied to fields without any further treatment (this assumption arises in the cost of sludge including only transport and spreading costs).  It seems that some treatment would be needed for safe contact with humans, waterways, and croplands, and these costs need to be factored in, or their exclusion justified robustly.

 

Response 12: We have clearly stated in the Introduction section about the concerns raised related to the use of biosolids in agriculture (lines 37 – 40; 42 - 46) and the need for a set of criteria for sludge agricultural use suitability classification (lines 40 – 42). It has also been clearly stated that the current study deals with a sludge, which has been classified as suitable for agricultural use (lines 46 – 48). Therefore, this manuscript does not apply to sludge which does not qualify for agricultural use according to the criteria set by sludge guidelines, as stated in the manuscript. Hence, this paper deals only with a product after processing and does not include the additional costs incurred during sludge treatment, which is quite broad and complex to incorporate in this manuscript. However, information generated from this manuscript could be integrated with  other broader models that integrate the whole cost benefit analysis of sludge treatment processes, which is also outside the scope of the manuscript.  

 

 

Point 13: It is generally unclear in the tables throughout the paper which values are obtained from the literature and which are calculated through the model.  While it is interesting to see the various information broken down into steps, the connection between real data inputs and model calculations is lost through the thread.  There seem to be rather a lot of significant figures in some of the output values relative to the input values.

 

Response 13: The captions for each Table clearly states where the inputs are obtained as shown below. So we are not sure which Table is referred to.

Table 1 Fertilizer price in March 2020 in the Market, South Africa

Table 2 Sludge recommendation rates (metric tons ha^-1) for maize grown on farms around selected South African cities across five South African agro-ecological zones. (Sludge recommendation rates are estimated based on crop N requirements.)

Table 3 Potential maize yield and annual commercial fertilizer and sludge application rate recommendations for selected sites across South African agro-ecological zones for soils with clay content of >25% (FSSA, 2007).

Table 4 The total value of available nutrients from sludge (TVANS) applied to 1 ha agricultural land of rain-fed maize according to crop N requirement across sites within ago-ecological zone in South Africa.

Table 5 The total costs of sludge (TCS) Vs total cost of commercial fertilizer (TCCF) across sites to meet rain-fed maize nutrient requirements planted to 1 ha land within 1 km perimeter of wastewater treatment plant

Table 6 The total value of available nutrient (TVANS) from sludge compared to the total costs of sludge (TCS) at varying distances (d) for 1 ha of agricultural farm.

 

 

Point 14: Overall, this paper presents a number of interesting ideas, but needs to bring them together into a more comprehensive model.  The authors need to apply a sensitivity analysis to their model; this will help with drawing more detailed conclusions about what factors have major influence.  It would be ideal to see this presented as a single equation "tool" that a practitioner could use to input their known parameters (nutrient needs, climate zone, distance, etc) and get outputs that give them a sense of their economic feasibility, or conversely to put in price points and find out "how close by do I need my sludge to come from?"  Adding this layer, along with a few details and clarifications as discussed above will take this paper to the next step of being an excellent publication and resource to the community.

 

Response 15: Putting all the equations together with a flow diagram indicating how each equation is linked to the other with all the conditions set for various scenario is basically providing a pseudo code for programming, which is not the scope of this manuscript. Nonetheless, we have already developed a computer model with the acronym SARA (Sludge Application Rate Advisor), which includes sludge quality classification, cost benefit analyses (presented in this manuscript), and long term impacts (outside the scope of the manuscript). The model provides options to select crop type, soil information (real time soil nutrient content), agro-ecological zone, biosolid type and  nutrient content, distance between wastewater and farm, distance between farm and commercial inorganic fertilizer source etc. All this information is linked and integrated through a set of codes and conditional criteria, which is quite intensive and beyond the scope of this manuscript. This paper is meant to present the core equations and assumption behind the computation for the cost benefit analysis of municipal sludge as low-grade nutrient source.

Regarding the sensitivity analysis tests, we absolutely agree with the reviewer that such information is of paramount importance and we will do it with the SARA model, which is currently being validated using data from field experiments across South African agro-ecological zones. Hence, we will consider this on another manuscript, which deals with the SARA model calibration, validation and use for biosolid application in agricultural lands.    

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The authors seem to have elected not to address most concerns beyond typographical in this request for revision.  The multiple requests for clarity of sourcing of information or explanation of a broader logical flow should indicate to the authors that the storyline of the manuscript is not as clear and obvious to an outside reader as they assert.

For example:

• Table captions - there is a citation for one table, the rest do not have citations and the table captions do not make explicit where the values in the table come from.  Perhaps pointing to the equation that generated the values.
• Suggesting that creating a flow diagram of the information through the series of equations would be non-trivial but would be redundant is a contradiction.  If the reader is unable to follow the flow, it falls upon the authors to provide an adequate visualization of the process such that the reader doesn't have to draw that out for themselves to understand the relevance of the work.

Author Response

Response to Reviewer 3 Comments

 

General comments

Point 1: The authors seem to have elected not to address most concerns beyond typographical in this request for revision.  The multiple requests for clarity of sourcing of information or explanation of a broader logical flow should indicate to the authors that the storyline of the manuscript is not as clear and obvious to an outside reader as they assert.

Response 1:

We have added a flow diagram (Figure 1) indicating the relationship among the various equations used in the manuscript. We hope this would improve the readability of the manuscript.

 

Point 2: Table captions - there is a citation for one table, the rest do not have citations and the table captions do not make explicit where the values in the table come from.  Perhaps pointing to the equation that generated the values.

 

Response 2:

Additional information has been included to the Table captions pointing to the equation as well as literature used to compute the values presented in the columns.  

 

 

Point 3: Suggesting that creating a flow diagram of the information through the series of equations would be non-trivial but would be redundant is a contradiction.  If the reader is unable to follow the flow, it falls upon the authors to provide an adequate visualization of the process such that the reader doesn't have to draw that out for themselves to understand the relevance of the work.

 

Response 3:

A flow diagram (Figure 1) indicating the relationship among the various equations has been added in the revised manuscript.

Author Response File: Author Response.pdf

Round 3

Reviewer 3 Report

Thank you for the inclusion of the flow diagram.  I found that keeping it open in a separate window while re-reading the discussion significantly aided my understanding and contextualization of the various equations.

Thank you also for inclusion of references and clarification to the Table headings.

I still feel that the work would be improved by the inclusion of references to economic distance in transportation of other materials, and to contextualization within the Industrial Symbiosis literature to highlight the ways in which this work builds on these and therefore the ways in which is it novel.  I will leave the decision to include these concepts between the authors and editors.