Environment Systems and Decisions

, Volume 36, Issue 1, pp 92–103 | Cite as

Energy use, blue water footprint, and greenhouse gas emissions for current food consumption patterns and dietary recommendations in the US

  • Michelle S. Tom
  • Paul S. Fischbeck
  • Chris T. Hendrickson
Article

Abstract

This article measures the changes in energy use, blue water footprint, and greenhouse gas (GHG) emissions associated with shifting from current US food consumption patterns to three dietary scenarios, which are based, in part, on the 2010 USDA Dietary Guidelines (US Department of Agriculture and US Department of Health and Human Services in Dietary Guidelines for Americans, 2010, 7th edn, US Government Printing Office, Washington, 2010). Amidst the current overweight and obesity epidemic in the USA, the Dietary Guidelines provide food and beverage recommendations that are intended to help individuals achieve and maintain healthy weight. The three dietary scenarios we examine include (1) reducing Caloric intake levels to achieve “normal” weight without shifting food mix, (2) switching current food mix to USDA recommended food patterns, without reducing Caloric intake, and (3) reducing Caloric intake levels and shifting current food mix to USDA recommended food patterns, which support healthy weight. This study finds that shifting from the current US diet to dietary Scenario 1 decreases energy use, blue water footprint, and GHG emissions by around 9 %, while shifting to dietary Scenario 2 increases energy use by 43 %, blue water footprint by 16 %, and GHG emissions by 11 %. Shifting to dietary Scenario 3, which accounts for both reduced Caloric intake and a shift to the USDA recommended food mix, increases energy use by 38 %, blue water footprint by 10 %, and GHG emissions by 6 %. These perhaps counterintuitive results are primarily due to USDA recommendations for greater Caloric intake of fruits, vegetables, dairy, and fish/seafood, which have relatively high resource use and emissions per Calorie.

Keywords

Energy use Blue water footprint GHG emissions Food consumption Diet 

Supplementary material

10669_2015_9577_MOESM1_ESM.docx (107 kb)
Supplementary material 1 (DOCX 107 kb)

References

  1. Buzby J, Hodan W, Jeffrey H (2014) The estimated amount, value, and calories of postharvest food losses at the retail and consumer levels in the United States, EIB-121. US Department of Agriculture, Economic Research ServiceGoogle Scholar
  2. Centers for Disease Control and Prevention, National Center for Health Statistics (2014) Questionnaires, datasets, and related documentation. Retrieved from National Health and Nutrition Examination Survey. http://www.cdc.gov/nchs/nhanes/nhanes_question naires.htm
  3. Centers for Disease Control and Prevention, Division of Nutrition, Physical Activity, and Obesity (2015a, May 15) About Child & Teen BMI. Retrieved from Centers for Disease Control and Prevention. http://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childens_bmi.html#How%20is%20BMI%20used%20with%20children%20and%20teens
  4. Centers for Disease Control and Prevention, Division of Nutrition, Physical Activity, and Obesity (2015b, May 15) About Adult BMI. Retrieved from Centers for Disease Control and Prevention. http://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html#Why
  5. Dixon J (2010) The effect of obesity on health outcomes. Mol Cell Endocrinol 316(2):104–108CrossRefGoogle Scholar
  6. Eshel G, Martin P (2006) Diet, energy and global warming. Earth Interact 10(9):1–17CrossRefGoogle Scholar
  7. Foster C, Green K, Bleda M, Dewick P, Evans B, Flynn A, Mylan J (2006) Environmental impacts of food production and consumption: a report to the department for environment, food, and rural affairs. Manchester Business School, Defra, LondonGoogle Scholar
  8. Freedman MR, King J, Kennedy E (2001) Executive summary. Obes Res 9(S3):1S–5S. doi:10.1038/oby.2001.113 CrossRefGoogle Scholar
  9. Harris JA, Benedict FG (1919) A biometric study of basal metabolism in man. Carnegie Institute of Washington, Washington, DCGoogle Scholar
  10. Heller M, Keoleian G (2014) Greenhouse gas emission estimates of US dietary choices and food loss. J Ind Ecol 19(3):391–401. doi:10.1111/jiec.12174 CrossRefGoogle Scholar
  11. Henry CJK (2005) Basal metabolic rate studies in humans: measurement and development of new equations. Public Health Nutr 8(7A):1133–1152CrossRefGoogle Scholar
  12. Hoekstra AY, Chapagain AK, Aldaya MM, Mekonnen MM (2011) The water footprint assessment manual: setting the global standard. Earthscan, LondonGoogle Scholar
  13. Lipinski B et al (2013) Reducing food loss and waste. Working paper, installment 2 of creating a sustainable food future. Washington, DC: World Resources Institute. http://www.worldresourcesreport.org
  14. Lieberman M, Marks A (2012) Mark’s basic medical biochemistry: a clinical approach, 4th edn. Lippincott Williams & Wilkins, Philadelphia, PAGoogle Scholar
  15. Livingston E, Kohlstadt I (2005) Simplified resting metabolic rate—predicting formulas for normal-sized and obese individuals. Obes Res 13(7):1255–1262CrossRefGoogle Scholar
  16. Marlow H, Hayes W, Soret S, Carter R, Schwab E, Sabate J (2009) Diet and the environment: does what you eat matter? Am J Clin Nutr 89(5):1699S–1703SCrossRefGoogle Scholar
  17. Meier T, Christen O (2013) Environmental impacts of dietary recommendations and dietary styles: Germany as an example. Environ Sci Technol 47(2):877–888CrossRefGoogle Scholar
  18. Mekonnen M, Hoekstra A (2011) The green, blue, and grey water footprint of crops and derived crop products. Hydrol Earth Syst Sci. 15, 1577–1600. http://waterfootprint.org/en/resources/water-footprint-statistics/#CP1
  19. Mekonnen M, Hoekstra A (2012) A global assessment of the water footprint of farm animal products. Ecosystems. 15(3):401–415. http://waterfootprint.org/en/resources/water-footprint-statistics/#CP1
  20. Merrigan K, Griffin T, Wilde P, Robien K, Goldberg J, Dietz W (2015) Designing a sustainable diet. Science 350(6257):165–166CrossRefGoogle Scholar
  21. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO (1990) A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr 51(2):241–247Google Scholar
  22. Müller M, Bosy-Westphal A, Klaus S, Kreymann G, Lührmann P, Neuhäuser-Berthold M, Noack R et al (2004) World Health Organization equations have shortcomings for predicting resting energy expenditure in persons from a modern, affluent population: generation of a new reference standard from a retrospective analysis of a German database of resting energy expenditure. Am J Clin Nutr 80(5):1379–1390Google Scholar
  23. Owen O, Kavle E, Owen R, Polansky M, Caprio S, Mozzoli M, Kendrick Z et al (1986) A reappraisal of caloric requirements in healthy women. Am J Clin Nutr 44(1):1–19Google Scholar
  24. Owen O, Holup J, D’Alessio D, Craig E, Polansky M, Smalley K, Kavle E et al (1987) A reappraisal of the caloric requirements of men. Am J Clin Nutr 46(6):875–885Google Scholar
  25. Pelletier N, Tyedmers P, Sonesson U, Scholz A, Ziegler F, Flysjo A, Kruse S, Cancino B, Silverman H (2009) Not all Salmon are created equal: life cycle assessment (LCA) of global Salmon farming systems. Environ Sci Tech 43:8730–8736CrossRefGoogle Scholar
  26. Renault D, Wallender W (2000) Nutritional water productivity and diets. Agric Water Manag 45(3):275–296CrossRefGoogle Scholar
  27. Roza A, Shizgal H (1984) The Harris–Benedict equation reevaluated. Am J Clin Nutr 40(1):168–182Google Scholar
  28. Schofield WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39:5–41Google Scholar
  29. Svanes E, Vold M, Hanssen O (2011) Environmental assessment of cod (Gadus morhua) from autoline fisheries. Int J Life Cycle Assess 16:611–624CrossRefGoogle Scholar
  30. Thompson D, Edelsberg J, Colditz G (1999) Lifetime health and economic consequences of obesity. Arch Intern Med 159(18):2177–2183CrossRefGoogle Scholar
  31. Thompson D, Brown J, Nichols G, Elmer P, Oster G (2001) Body mass index and future heathcare costs: a retrospective cohort study. Obes Res 9(3):210–218CrossRefGoogle Scholar
  32. Tilman D, Clark M (2014) Global diets link environmental sustainability and human health. Nature 515(7528):518–522CrossRefGoogle Scholar
  33. United Nations Environment Programme (UNEP) Global Environmental Alert Service (2012) Growing greenhouse gas emissions due to meat production. United Nations Environment Programme, GenevaGoogle Scholar
  34. US Census Bureau (2013) Population estimates, historical data. US Census Bureau, US Department of Commerce, Washington, DCGoogle Scholar
  35. US Department of Agriculture, Economic Research Service (2014) Loss-adjusted food availability data set. Retrieved from Food Availability (Per Capita) Data System. http://www.ers.usda.gov/data-products/food-availability-(per-capita)-data-system/.aspx#26705
  36. US Department of Agriculture and US Department of Health and Human Services (2010) Dietary guidelines for Americans, 2010, 7th edn. US Government Printing Office, Washington, DCGoogle Scholar
  37. Vanham D, Bidoglio G (2014) The water footprint of agricultural products in European river basins. Environ Res Lett 9(6):064007. doi:10.1088/1748-9326/9/6/064007 CrossRefGoogle Scholar
  38. Vanham D, Mekonnen M, Hoekstra A (2013a) The water footprint of the EU for different diets. Ecol Ind 32:1–8CrossRefGoogle Scholar
  39. Vanham D, Hoekstra A, Bidoglio G (2013b) Potential water saving through changes in European diets. Environ Int 61:45–56CrossRefGoogle Scholar
  40. Weber C, Matthews H (2008) Food-miles and the relative climate impacts of food choices in the United States. Environ Sci Technol 42(10):3508–3513CrossRefGoogle Scholar
  41. Weijs P (2008) Validity of predictive equations for resting energy expenditure in US and Dutch overweight and obese class I and II adults aged 18-65 y. Am J Clin Nutr 88(4):959–970Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Civil and Environmental EngineeringCarnegie Mellon UniversityPittsburghUSA
  2. 2.Departments of Engineering and Public Policy and Social and Decision SciencesCarnegie Mellon UniversityPittsburghUSA

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