Presentation by Jan Broeze at the 5th Global Science Conference on Climate-Smart Agriculture.

1. Climate-smart lunches
Conclusions on food waste
and associated GHG emissions
at the 5th Global CSA Conference
CLIFF-GRADS Programme: Daniele Eckert
Matzembacher (Brazil), Li Xue (China), Tabitha Nindi
(USA), Xia Liang (China), Norah Titiya Machinjiri
(Ethiopia)
CCAFS: Julianna White, Lini Wollenberg, Alexandra
Krendelsberger, Lili Szilagyi
Wageningen Research: Jan Broeze
Learn more: bit.ly/climate-smart-lunches

2. Dishes
• Tuesday: high GHG
emission foods
• Wednesday: healthy
& sustainable diet
(EAT-Lancet)
• Friday: meat
alternatives

4. Approach per ingredient:
• map supply chain
• production region
• supply chain
• estimate supplied product GHG emission factor with ACGE calculator:
• crop GHG factor is derived from default data set
• food loss factors along the chain are derived from default data
• transportation distances & modalities are estimated
Dish GHG emission factor = weighted average of ingredients’ emission factor
Agro-Chain Greenhouse gas Emissions (ACGE)
calculator will be made available on
https://ccafs.cgiar.org/

5. Rendang: meat dish with spices from West Sumatra
Main ingredients Total GHG emissions
per kg product
Beef 9.957
Red chili 0.251
Coconut milk 0.073
Shallot 0.189
Garlic 0.063
Galangal 0.063
Candle nut 0.042
Ginger 0.031
Turmeric 0.017
Lemongrass 0.038
Sunflower oil 0.318
Total: 11.043 kg CO2-eq. per kg prepared food
Main ingredients Total GHG
emissions per kg
Meat alternative 0.155
Red chili 0.206
Coconut milk 0.058
Shallot 0.154
Garlic 0.051
Galangal 0.051
Candle nut 0.035
Ginger 0.026
Turmeric 0.014
Lemongrass 0.031
Sunflower oil 0.262
Total: 1.042 kg CO2-eq. per kg prepared food
Rendang, meat alternative

6. Production & wastes Tuesday meal
Dish Serving Leftovers
(plates)
Surplus
(dishes)
Production
GHG
Leftovers
GHG
Surplus
GHG
Rendang (beef) 30.35 0.60 11.64 11.04 6.63 128.54
Stewed lamb 26.65 0.14 11.04 15.93 2.23 175.82
Vegetables 59.35 0.00 9.42 1.41 0.00 13.32
Nasi goreng 37.90 0.48 11.60 2.93 1.41 33.99
White rice 30.21 0.32 16.48 2.93 0.94 48.29
TOTALS 184.46 1.54 60.18 1043.06 11.20 399.96
Product volumes in kg associated GHG emissions in kg CO2-eq.

7. Comparing outcomes of the menus
Serving Food waste
(plates)
Food waste
(restaurant)
Production
GHG
Leftovers
GHG
(plates)
Surplus
GHG
(restaurant)
Tuesday (HIGH IMPACT MEAL)
184.46 1.54 60.18 1043.06 11.20 399.96
Wednesday (HEALTHY & SUSTAINABLE: EAT-LANCET)
148.40 6.09 25.28 490.75 18.24 86.36
Thursday (MEAT ALTERNATIVES)
143.70 4.74 22.31 269.01 6.59 47.59
Product volumes in kg associated GHG emissions in kg CO2-eq.
TOTAL waste-induced GHG emissions: 550 kg CO2-eq.

8. Results in perspective
• Low volumes of waste on the plate:
You behaved very responsible!
• Consequently: larger surpluses on the dishes
• Food waste associated GHG emissions are larger than hotel
shuttles and comparable airport taxi GHG emissions
114 shuttle rides x 5 km x 0.3 kg/km = 171 kg CO2-eq.
2x200 taxi rides x 11km x 0.15kg/km = 660 kg CO2-eq.
• Dietary choices have large effect!
Consumer behaviour key. Let’s support them!

9. Some reflections by the chef
• “We look at the volumes of surpluses.
If they are high, we propose to the conference organisation to reduce
the dish volumes for the next days.”
• “We strive for the best food waste valorisation within the limitations of
the HACCP food safety regulations.”
• “If beef becomes scarce, we may need to switch to alternatives.”
• “We are curious how the consumers will react to the meat alternatives.”
Sebastian Arnold
Chef at Ayana

10. Climate-smart lunches
Measuring the climate impact of
our diet choices
Learn more: bit.ly/climate-smart-lunches
Thank you for your participation!
jan.broeze@wur.nl