LCA Food 2012 in Saint Malo, France! - Manifestations et colloques ...

PARALLEL SESSION 4B: DIET 8 th Int. Conference on LCA in the
Agri-Food Sector, 1-4 Oct 2012
salmon, cheese, milk and eggs on a per kcal basis are relatively similar, but applying the NuVal based “nutritional
weighting” clear differentiates these foods on a per nutritional kcal basis.
The influence of a “nutritionally weighted” functional unit is perhaps clearer in more extreme comparisons.
Coca-Cola reports that their product delivered in 2 L plastic bottles has a carbon footprint of 0.25 kg
CO2e/ L (Coca-Cola Co., 2010), which, on a caloric content basis, is a factor of 3 smaller than whole milk.
Coca-Cola receives a NuVal score of 1, however, so on a nutritionally weighted basis, the carbon footprint of
Coca-Cola is 17 times greater than that of whole milk.
5. Conclusion
We propose a functional unit that addresses a primary function of food, which is to deliver healthpromoting
nutrition. The NuVal score, which evaluates multiple nutritional properties of food, provides a
convenient basis for more comprehensive comparisons of life cycle environmental sustainability performance
across diverse food types.
Table 3. Life Cycle Greenhouse Gas Emissions for a variety of foods, expressed on different functional unit
bases. Values in parentheses are the ranking (high to low impact) of foods in each column.
per dry weight per serving per g protein per kcal food energy
kg CO2e/ kcal food
per kcal w/ NuVal "nutritional
weighting"
kg CO2 eq/ kg DW kg CO2e/ serving kg CO2e/ g protein energy kg CO2 e/ nutritional kcal*
beef 73.43 (1) 2.55 (1) 0.12 (1) 0.01274 (1) 0.03981 (1)
lamb 56.47 (2) 1.98 (2) 0.10 (3) 0.00915 (2) 0.03389 (2)
pork 17.19 (3) 0.70 (3) 0.032 (10) 0.00278 (4) 0.00751 (4)
chicken 11.58 (8) 0.40 (4) 0.018 (13) 0.00201 (9) 0.00543 (6)
tuna 10.18 (9) 0.22 (8) 0.010 (20) 0.00223 (6) 0.00385 (8)
salmon 11.95 (7) 0.19 (9) 0.015 (15) 0.00224 (5) 0.00258 (10)
cheese 13.60 (4) 0.24 (7) 0.035 (8) 0.00213 (7) 0.00927 (3)
skim milk 11.96 (6) 0.27 (5) 0.032 (9) 0.00316 (3) 0.00390 (7)
whole milk 9.27 (10) 0.27 (6) 0.035 (6) 0.00180 (11) 0.00346 (9)
egg 12.58 (5) 0.15 (10) 0.024 (11) 0.00208 (8) 0.00631 (5)
brown rice 1.33 (20) 0.048 (11) 0.014 (16) 0.00033 (20) 0.00041 (20)
white rice 1.33 (19) 0.045 (12) 0.016 (14) 0.00033 (19) 0.00070 (16)
dry beans 1.11 (21) 0.033 (17) 0.004 (26) 0.00030 (21) 0.00032 (21)
apple 1.96 (17) 0.039 (15) 0.11 (2) 0.00054 (17) 0.00057 (18)
orange 2.45 (15) 0.043 (13) 0.035 (7) 0.00069 (15) 0.00069 (17)
strawberries 4.20 (13) 0.027 (18) 0.057 (4) 0.00119 (13) 0.00119 (13)
tomatoes 5.93 (11) 0.040 (14) 0.037 (5) 0.00182 (10) 0.00189 (11)
potato 0.79 (25) 0.035 (16) 0.008 (24) 0.00022 (25) 0.00024 (25)
broccoli 3.46 (14) 0.016 (19) 0.013 (18) 0.00109 (14) 0.00109 (14)
lettuce 4.51 (12) 0.011 (20) 0.022 (12) 0.00135 (12) 0.00137 (12)
winter squash 0.80 (24) 0.009 (22) 0.010 (21) 0.00024 (23) 0.00026 (23)
beets 0.74 (26) 0.010 (21) 0.007 (25) 0.00019 (26) 0.00020 (26)
cucumber 2.45 (16) 0.005 (24) 0.014 (17) 0.00069 (16) 0.00074 (15)
cabbage 1.53 (18) 0.005 (23) 0.009 (23) 0.00049 (18) 0.00050 (19)
carrots 0.98 (22) 0.003 (25) 0.012 (19) 0.00029 (22) 0.00030 (22)
onions 0.92 (23) 0.001 (26) 0.009 (22) 0.00023 (24) 0.00025 (24)
Of course, there are always inherent limitations to scoring systems that attempt to incorporate multiple attributes,
and NuVal is no exception. The NuVal score is based on empirically derived weighting factors that
currently remain confidential; thus, the nutritional factors that are the major drivers of the NuVal score are
not immediately apparent.
This approach to establishing a nutritional equivalency metric for environmental impact studies of food is
intended to stimulate and encourage discussion and further exploration of an important topic. Given limitations
to the approach presented here, extreme care must be taken in fully communicating, and further considering,
the meaning of a “nutritionally weighted kcal.” Other similar nutritional indicators, such as the Nutrient
Rich Foods Index (Drewnowski, 2010), may warrant consideration. Ultimately, it may be more beneficial
to consider nutritional equivalency and environmental impact of foods by aggregating to the whole diet
level. Given a diversity of research goals and the complexity of food and agricultural systems, there are
likely many ‘correct’ answers to the question of food functional equivalency; our hope is that the approach
presented here provides practitioners with an additional tool to consider.
6. References
Ahuja J.K.A., Montville J.B., Omolewa-Tomobi G., Heendeniya K.Y., Martin C.L., Steinfeldt L.C., Anand J., Adler M.E., LaComb
R.P., Moshfegh A.J., 2012. USDA Food and Nutrient Database for Dietary Studies, 5.0. U.S. Department of Agriculture, Agricultural
Research Service, Food Surveys Research Group, Beltsville, MD.
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