Skip to main content
SpringerLink
Log in

Eco-efficient Dairy Waste Treatment: Validating a Sustainable System Dynamics Framework

  • Research
  • Published:
Operations Research Forum Aims and scope Submit manuscript

Abstract

Dairy wastes in third-world countries are not adequately utilized to generate valuable by-products and trade them commercially for financial and environmental benefits. This paper focuses on such wastes and considers waste processing operations using the system dynamics (SD) simulation approach. Primary data used to build the SD model was collected from the farm records, a questionnaire, and a follow-up interview with management members. This model illustrates advancements in the dairy sector and equips a system dynamics framework with the necessary degree of validation to address the intricate challenge of waste management in dairy operations. The study deployed system dynamics methodology and replicated the real-life dairy farm processes in the Vensim simulation platform using 3 years of data. Five specific scenarios were experimented with to justify waste management processes (current operation, different allocations to bio-fertilizer, biogas, and raw dung), resulting in increased revenue and reduced landfill requirements. The ability to process waste was found to be limited by seasonality constraints. A comparison of scenarios enabled us to demonstrate that for a mid-sized dairy farm, the valuable by-products as a mix of bio-fertilizer and biogas lead to improved economic gains while protecting the environment. Thus, this work fills a crucial substantive and methodological gap in this research area. This study can assist academicians, policymakers, entrepreneurs, and responsible managers understand a solid dairy waste management system for emerging economies. The model also ignores variations in cattle types, such as milch cow, heifer (breedable), calves, and bull.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Availability of Data and Material

The material used to calibrate the model is available in Annexures 1A and 1B (pages 25–30).

Code Availability

The model was built using Vensim™ (Version 6.0a-1) https://vensim.com/vensim-6-0a-released/, and the calibrated model is available at the link: https://github.com/ivanwtaylor/Dairy-Waste/.

References

  1. Shamsuddoha M, Nedelea A, Veronica G (2009) Dairy farming - an alternative income-generating activity. Journal Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Horticulture 66(2):352–355

    Google Scholar 

  2. Zhang J, Wang M, Yin C, Dogot T (2021) The potential of dairy manure and sewage management pathways towards a circular economy: a meta-analysis from the life cycle perspective. Sci Total Environ 146396. https://doi.org/10.1016/j.scitotenv.2021.146396

  3. Ghisellini P, Protano G, Viglia S, Gaworski M, Setti M, Ulgiati S (2014) Integrated agricultural and dairy production within a circular economy framework. A comparison of Italian and Polish farming systems. J Environ Account Manag 2(4):367–384

    Google Scholar 

  4. Islam KN, Sarker T, Taghizadeh-Hesary F, Atri AC, Alam MS (2021) Renewable energy generation from livestock waste for a sustainable circular economy in Bangladesh. Renew Sustain Energy Rev 139:110695

    Article  Google Scholar 

  5. Shamsuddoha M, Nasir T, Hossain NUI (2023) A sustainable supply chain framework for dairy farming operations: a system dynamics approach. Sustainability 15(10):8417

    Article  Google Scholar 

  6. FAOSTAT (2021) Available at: http://www.fao.org/faostat/en/#data. Accessed 30 Jul 2021

  7. Ahmed R, Kim I-K (2003) Patterns of daily rainfall in Bangladesh during the summer monsoon season: case studies at three stations. Phys Geogr 24(4):295–318. https://doi.org/10.2747/0272-3646.24.4.295

    Article  Google Scholar 

  8. Geography of Bangladesh, Wikipedia Available at: https://en.wikipedia.org/wiki/Geography_of_Bangladesh. Accessed 20 Jul 2021

  9. Department of Livestock (DLS) (2020) Available at: http://www.dls.gov.np/reportsdetail/8/2020/92112723. Accessed 30 Jul 2021

  10. Hemme TO, Khan AR (2004) A review of milk production in Bangladesh with particular emphasis on small-scale producers. Available at: https://ageconsearch.umn.edu/record/23774/. Accessed 25 Jul 2021

  11. Saadullah M (2011) Smallholder dairy production and marketing in Bangladesh. Retrieved from http://www.ilri.cgiar.org/InfoServ/Webpub/fulldocs/South_South/ch06.htm. Accessed 30 Jun 2021

  12. Raha SK, Talukder RK (2004) Vertical integration in the dairy sector in Bangladesh The Case of Bangladesh Milk Producers Co-operative Union Ltd. Bangladesh J Polit Econ 20(1)

  13. Adghim M, Abdallah M, Saad S, Shanableh A, Sartaj M (2020) Assessment of the biochemical methane potential of mono-and co-digested dairy farm wastes. Waste Manage Res 38(1):88–99. https://doi.org/10.1177/0734242X19871999

    Article  Google Scholar 

  14. Awan U, Sroufe R (2022) Sustainability in the circular economy: insights and dynamics of designing circular business models. Appl Sci 12(3):1521

    Article  Google Scholar 

  15. Vasco-Correa J, Khanal S, Manandhar A, Shah A (2018) Anaerobic digestion for bioenergy production: global status, environmental and techno-economic implications, and government policies. Biores Technol 247:1015–1026. https://doi.org/10.1016/j.biortech.2017.09.004

    Article  Google Scholar 

  16. Cox JF, Blackstone JH, Spencer MS (1995) APICS Dictionary, vol 8, 8th edn. American Production and Inventory Control Society, Falls Church, VA

    Google Scholar 

  17. Kocabasoglu C, Prahinski C, Klassen RD (2007) Linking forward and reverse supply chain investments: the role of business uncertainty. J Oper Manag 25:1141–1160

    Article  Google Scholar 

  18. Srinivas H (2007) The 3R concept and waste minimisation. Retrieved from http://www.gdrc.org/uem/waste/3r-minimization.html. Accessed 20 Jun 2021

  19. Kumar S, Nigmatullin A (2011) A system dynamics analysis of food supply chains–a case study with non-perishable products. Simul Model Pract Theory 19(10):2151–2168

    Article  Google Scholar 

  20. Ruteri JM, Xu Q (2009) Supply chain management and challenges facing the food industry sector in Tanzania. Int J Bus Manag 4(12):70–80

    Google Scholar 

  21. Georgiadis P, Vlachos D, Iakovou E (2005) A system dynamics modeling framework for the strategic supply chain management of food chains. J Food Eng 70(3):351–364. https://doi.org/10.1016/j.jfoodeng.2004.06.030

    Article  Google Scholar 

  22. Bottani E, Vignali G, Mosna D, Montanari R (2019) Economic and environmental assessment of different reverse logistics scenarios for food waste recovery. Sustain Prod Consum 20:289–303. https://doi.org/10.1016/j.spc.2019.07.007

    Article  Google Scholar 

  23. Minegishi S, Thiel D (2000) System dynamics modeling and simulation of a particular food supply chain. Simul Pract Theory 8(5):321–339

    Article  Google Scholar 

  24. Gross A, Bromm T, Polifka S, Schierhorn F (2022) The carbon footprint of milk during the conversion from conventional to organic production on a dairy farm in central Germany. Agron Sustain Dev 42(3):37

    Article  Google Scholar 

  25. Holzworth DP, Huth NI, deVoil PG, Zurcher EJ, Herrmann NI, McLean G, Keating BA (2014) APSIM–evolution towards a new generation of agricultural systems simulation. Environ Model Softw 62:327–350

    Article  Google Scholar 

  26. Andersen E, Elbersen B, Godeschalk F, Verhoog D (2007) Farm management indicators and farm typologies as a basis for assessments in a changing policy environment. J Environ Manage 82(3):353–362. https://doi.org/10.1016/j.jenvman.2006.04.021

    Article  Google Scholar 

  27. Rivera-Huerta A, de la Salud Rubio Lozano M, Ku-Vera JC, Güereca LP (2022) Emission factors from enteric fermentation of different categories of cattle in the Mexican tropics: a comparison between 2006 and 2019 IPCC. Clim Change 172(3–4):23

    Article  Google Scholar 

  28. Snow VO, Lovatt SJ (2008) A general planner for agro-ecosystem models. Comput Electron Agric 60(2):201–211

    Article  Google Scholar 

  29. Atalan A (2023) Forecasting drinking milk price based on economic, social, and environmental factors using machine learning algorithms. Agribusiness 39(1):214–241

    Article  Google Scholar 

  30. Capper JL, Cady RA (2020) The effects of improved performance in the US dairy cattle industry on environmental impacts between 2007 and 2017. J Anim Sci 98(1):1–14. https://doi.org/10.1093/jas/skz291

    Article  Google Scholar 

  31. Fakhimi M, Mustafee N, Stergioulas LK (2016) An investigation into modeling and simulation approaches for sustainable operations management. Simulation 92(10):907–919

    Article  Google Scholar 

  32. Tsaples G, Tarnanidis T (2020) A system dynamics model and interface for the simulation and analysis of milk supply chains. In: Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications (pp 108–135). IGI Global

  33. Onggo BS, Utomo DS (2021) Dairy supply chain in west Java: modelling using agent-based simulation and reporting using the stress guidelines. In: 10th Operational Research Society Simulation Workshop 2021 (pp 295–304). Operational Research Society

  34. Forrester JW (1961) Industrial dynamics. The MIT Press, Cambridge (MA)

    Google Scholar 

  35. Sterman JD (2000) Business dynamics: systems thinking and modeling for a complex world. Irwin McGraw-Hill, Boston

    Google Scholar 

  36. Wolstenholme EF (1982) System dynamics in perspective. J Oper Res Soc 547–556

  37. Yin RK (1994) Case study research: design and methods, 2nd edn. Sage, Newbury Park, CA

    Google Scholar 

  38. Richardson GP (1986) Problems with causal-loop diagrams. Syst Dyn Rev 2(2):158–170

    Article  Google Scholar 

  39. Maani KE, Cavana RY (2007) Systems thinking, system dynamics: managing change and complexity (Vol 2nd). Auckland: Pearson Education (NZ) and Prentice-Hall

  40. Aghalaya SN, Elias AA, Pati RK (2012) Analyzing reverse logistics in the Indian pharmaceuticals industry: a systems approach. Paper presented at the 26th Australian and New Zealand Academy of Management (ANZAM) Conference 2012 Perth

  41. Barlas Y, Carpenter S (1990) Philosophical roots of model validation: two paradigms. Syst Dyn Rev 6(2):148–166. https://doi.org/10.1002/sdr.4260060203

    Article  Google Scholar 

  42. Barlas Y (1996) Formal aspects of model validity and validation in system dynamics. Syst Dyn Rev 12(3):183–210. https://doi.org/10.1002/(SICI)1099-1727(199623)12:3%3C183::AID-SDR103%3E3.0.CO;2-4

    Article  Google Scholar 

  43. Forrester JW, Senge PM (1980) Tests for building confidence in system dynamics models. TIMS Studies in Management Sciences 14:209–228

    Google Scholar 

  44. Lane DC, Oliva R (1998) The greater whole: towards a synthesis of system dynamics and soft systems methodology. Eur J Oper Res 107(1):214–235

    Article  Google Scholar 

  45. Homer J (2019) A comment on John Sterman’s “system dynamics at sixty: the path forward.” Syst Dyn Rev 35(1):5–7

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the managers and farmers at Nahar Dairy farm who have provided various inputs for the dairy farms, milk processing units, and perceptions about the multiple by-products generated from the dairy waste.

Author information

Authors and Affiliations

  1. Western Illinois University, Macomb, USA

    Mohammad Shamsuddoha

  2. OP Jindal Global University, Sonipat, Haryana, India

    Saroj Koul

  3. Policy Dynamics Inc., Kitchener, Canada

    Ivan W. Taylor

Authors
  1. Mohammad Shamsuddoha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saroj Koul
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ivan W. Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization, M.S., and I.W.T.; methodology, M.S., S.K., and I.W.T.; software, M.S., S.K., and I.W.T.; validation, M.S., S.K., and I.W.T.; formal analysis, M.S., S.K., and I.W.T.; literature review and investigation, M.S., and S.K.; writing—original draft preparation, M.S., and S.K.; writing—review and editing, I.W.T. and S.K.; supervision, I.W.T. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Saroj Koul.

Ethics declarations

Ethics Approval

Not applicable.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Competing Interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 16 KB)

Annexure. Settings and Nomenclature

Annexure. Settings and Nomenclature

1.1 Annexure 1A

Table 3 Parameter setting standard for all scenarios
Full size table

1.2 Annexure 1B Nomenclature

1.2.1 Mature Cow Module

figure a
  1. 1.

    aging to cow = Calves / AVERAGE TIME TO MATURE, Units: Cow/Month

  2. 2.

    AVERAGE MILK = 450, Units: liter/Month/Cow [400,550]

  3. 3.

    AVERAGE TIME TO MATURE = 18, Units: Month [14, 25]

  4. 4.

    birthing behavior = WITH LOOKUP (Time,([(0,0)(36,0.1)],(0,0),(6,0.059),(12,0.083),(18,0.09),(24,0.07),(30,0.039),(36,0.039))), Units: Cows/Cow/Month

  5. 5.

    calf births = Mature Cow*birthing behavior, Units: Cow/Month

  6. 6.

    Calves = INTEG (calf births-aging to cow,INITIAL CALVES), Units: Cow

  7. 7.

    culled cows = Mature Cow*culling behavior, Units: Cow/Month

  8. 8.

    culling behavior = WITH LOOKUP (Time, ([(0,0)-(36,0.2)],(0,0.006),(6,0.05),(12,0.002), (18,0.074),(24,0.073),(30,0.047),(36,0.047))), Units: Cows/Cow/Month

  9. 9.

    INITIAL CALVES = 265, Units: Cows [200,5000], INITIAL COWS = 465, Units: Cow

  10. 10.

    INITIAL MILK = 0, Units: liter [0,2000]

  11. 11.

    Mature Cow = INTEG (aging to cow-culled cows,INITIAL COWS), Units: Cow

  12. 12.

    Milk in Storage = INTEG (milking—milk sales,INITIAL MILK), Units: liters

  13. 13.

    milk sales = Milk in Storage*MILK SALES RATE, Units: liters/Month

  14. 14.

    MILK SALES RATE = 1, Units: liters/liter/Month

  15. 15.

    milking = Mature cow * AVERAGE MILK, Units: liters/month

1.2.2 Dairy Waste Module

figure b
  1. 1.

    AVERAGE CALVE WASTE=840/6, Units: kg/Cow/Month, 6 times less than a mature cow

  2. 2.

    AVERAGE COW WASTE=840, Units: kg/(Cow*Month)

  3. 3.

    Calves= INTEG (calf births-aging to cow, INITIAL CALVES), Units: Cow

  4. 4.

    Min((-aging to Cow+Cattle to farm),2000)

  5. 5.

    Landfill= INTEG (raw dung to landfill,0), Units: kg

  6. 6.

    Mature Cow= INTEG (aging to cow-culled cows, INITIAL COWS), Units: Cow

  7. 7.

    total landfill=Land fill+Waste Drained Out, Units: kg/Month

  8. 8.

    total waste produced=AVERAGE CALVE WASTE*Calves+AVERAGE COWWASTE*Mature Cow, Units: kg/Month

  9. 9.

    waste collected=total waste produced*IF THEN ELSE(MODULO(Time, 12 )<5, WASTE COLLECTION DRY SEASON, IF THEN ELSE(MODULO(Time, 12 )<8, WASTE COLLECTION RAINY SEASON, WASTE COLLECTION DRY SEASON)), Units: kg/Month

  10. 10.

    WASTE COLLECTION DRY SEASON=0.18, Units: fraction

  11. 11.

    WASTE COLLECTION RAINY SEASON=0.16, Units: fraction

  12. 12.

    Waste Drained Out= INTEG (waste draining,0), Units: kg

  13. 13.

    waste draining=total waste produced-waste collected, Units: kg/Month

1.2.3 Bio-fertilizer Module

figure c
  1. 1.

    Fertilizer = INTEG (fertilizer convert rate-selling fertilizer-fertilizer to land fill, INITIAL FERTILIZER), Units: kg

  2. 2.

    fertilizer convert rate = dairy waste usage*PROPORTION OF DAIRY WASTE USE FOR FERTILIZER, Units: kg/Month

  3. 3.

    FERTILIZER PRICE = 0.0035, Units: dollars/kg

  4. 4.

    fertilizer revenue = selling fertilizer*FERTILIZER PRICE, Units: dollars/Month

  5. 5.

    fertilizer to land fill = Fertilizer*(1-PROPORTION OF FERTILIZER SOLD)/TIME TO PROCESS FERTILIZER, Units: kg/Month

  6. 6.

    INITIAL FERTILIZER = 0, Units: kg

  7. 7.

    PROPORTION OF DAIRY WASTE USE FOR FERTILIZER = 0.3, Units: fraction [0,0.8], 30% for fertilizer/slurry

  8. 8.

    PROPORTION OF FERTILIZER SOLD = 0.95, Units: fraction [0,0.5]

  9. 9.

    selling fertilizer = Fertilizer*PROPORTION OF FERTILIZER SOLD/TIME TO PROCESS FERTILIZER, Units: kg/Month

  10. 10.

    TIME TO PROCESS FERTILIZER = 0.25, Units: MONTHS [0,1]

1.2.4 Biogas Module

figure d
  1. 1.

    Biogas= INTEG (biogas conversion-biogas release-biogas used, INITIAL BIOGAS), Units: liters

  2. 2.

    biogas conversion= dairy waste usage* PROPORTION OF DAIRY WASTE USE FOR BIOGAS*BIOGAS CONVERSION RATE, Units: liters/Month

  3. 3.

    BIOGAS CONVERSION RATE= 40, Units: liters/kg

  4. 4.

    BIOGAS PRICE= 0.2, Units: dollars/liter

  5. 5.

    biogas release= biogas*(1-PROPORTION OF BIOGAS USED)/TIME TO SELL BIOGAS, Units: liters/Month

  6. 6.

    biogas revenue= BIOGAS PRICE*biogas used*PROPORTION OF USED BIOGAS SOLD, Units: dollars/Month

  7. 7.

    biogas used= Biogas*PROPORTION OF BIOGAS USED/TIME TO SELL BIOGAS, Units: liters/Month

  8. 8.

    dairy waste usage= Dairy Waste*DIARY WASTE USAGE RATE, Units: kg/Month

  9. 9.

    INITIAL BIOGAS= 0, Units: liters

  10. 10.

    PROPORTION OF BIOGAS USED= 0.3, Units: fraction

  11. 11.

    PROPORTION OF DAIRY WASTE USE FOR BIOGAS= 0, Units: fraction [0,0.5], 15% for biogas

  12. 12.

    PROPORTION OF USED BIOGAS SOLD= 0, Units: dmnl

  13. 13.

    TIME TO SELL BIOGAS= 1, Units: MONTHS

1.2.5 Raw Dung Module

figure e
  1. 1.

    dairy waste usage= Dairy Waste*DIARY WASTE USAGE RATE, Units: kg/Month

  2. 2.

    INITIAL RAW WASTES DUMPS= 600000, Units: kg

  3. 3.

    PROPORTION OF DAIRY WASTE USE FOR BIOGAS= 0, Units: fraction [0,0.5], 15% for biogas

  4. 4.

    PROPORTION OF DAIRY WASTE USE FOR FERTILIZER= 0.3, Units: fraction [0,0.8], 30% for fertilizer/slurry

  5. 5.

    PROPORTION OF RAW WASTE SOLD= 0.01, Units: fraction

  6. 6.

    Raw Dung= INTEG (raw wastes-raw waste to land fill-selling raw waste, INITIAL RAW WASTES DUMPS), Units: kg

  7. 7.

    raw waste revenue= selling raw waste*RAW WASTES PRICE, Units: dollars/month

  8. 8.

    raw waste to land fill= Raw dung*(1-PROPORTION OF RAW WASTE SOLD)/TIME TO SELL WASTE, Units: kg/Month

  9. 9.

    raw wastes= dairy waste usage*(1-PROPORTION OF DAIRY WASTE USE FOR BIOGAS-PROPORTION OF DAIRY WASTE USE FOR FERTILIZER), Units: kg/Month

  10. 10.

    dairy wastes*(1-PROPORTION OF DAIRY WASTE USE FOR BIOGAS-PROPORTION OF DAIRY WASTE USE FOR FERTILIZER) Reminder will go for raw waste

  11. 11.

    RAW WASTES PRICE= 0.1, Units: dollars/kg

  12. 12.

    selling raw waste= Raw Dung*PROPORTION OF RAW WASTE SOLD/TIME TO SELL WASTE, Units: kg/Month

  13. 13.

    TIME TO SELL WASTE= 1, Units: MONTHS

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shamsuddoha, M., Koul, S. & Taylor, I.W. Eco-efficient Dairy Waste Treatment: Validating a Sustainable System Dynamics Framework. Oper. Res. Forum 5, 12 (2024). https://doi.org/10.1007/s43069-023-00290-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s43069-023-00290-9

Keywords

Search

Navigation