Climate Change Adaptation Strategy in the Food Industry—Insights from Product Carbon and Water Footprints
Abstract
:1. Introduction
2. Case Studies
2.1. Smith’s Potato Chips
2.2. OneHarvest Calypso™ Mango
2.3. Treasury Wine Estates Selected Single and Multi-Regional Products
3. Materials and Methods
3.1. General Approach
3.2. System Description
3.3. Carbon Footprint Assessment
3.4. Water Footprint Assessment
4. Results
5. Discussion
- Water footprint reduction: Under climate change there may be heightened societal concern about water scarcity and increasing reputational and/or market access risks/opportunities associated with water footprint labelling [59].
- Carbon footprint reduction: As with the previous issue, climate change may lead to heightened societal concern about the GHG emissions associated with products and therefore increasing reputational and/or market access risks/opportunities associated with carbon footprint labelling [59].
- Water scarcity: Water scarcity is a concern in many parts of the world and this has the potential to be exacerbated under climate change. Water scarcity represents a physical risk to irrigation dependent agricultural production systems as well as the operation of food processing facilities. Under extreme circumstances, water scarcity has the potential to completely disrupt value chains [60].
- Water pricing: Water scarcity also has the potential to lead to increased water pricing, which is a financial risk, especially to operations which use large water volumes [60].
- Energy pricing: In addition to water pricing, climate change has the potential to impact energy prices as businesses in the energy sector respond to government policies and seek to constrain high emission sources of energy, and commercialize new energy technologies [60].
- GHG regulation: GHG regulations, such as carbon taxes and emissions trading schemes, represent a further climate change related financial risk.
- Data uncertainty: LCA is an iterative process. To be cost effective, a screening analysis is usually first undertaken, which identifies critical elements in the value chain which can then be studied in more detail. As a final hotspot analysis, parts of the value chain with significant data uncertainty were identified [61].
5.1. Smith’s Potato Chips
5.2. OneHarvest Calypso™ Mango
5.3. Treasury Wine Estates Selected Single and Multi-Regional Products
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Life Cycle Stage | CWU | WF | CF | Hotspots | ||||||
---|---|---|---|---|---|---|---|---|---|---|
% | % | % | WF | CF | Water Scarcity | Water Pricing | Energy Pricing | GHG Regulation | Data Uncertainty | |
Potato cultivation | ||||||||||
Irrigation | 87 | 96 | X | X | X | X | ||||
Fertilizer prod. | 1 | 1 | 13 | X | ||||||
Fertilizer use | 10 | X | ||||||||
Fuels | 13 | X | X | X | ||||||
Other inputs | ||||||||||
Other ingredients | 10 | 2 | 18 | X | X | |||||
Packaging | 9 | |||||||||
Transport to factory | 7 | |||||||||
Smith’s operations | ||||||||||
Electricity | 13 | X | X | X | ||||||
Natural gas | 8 | X | X | X | ||||||
Water intake | 1 | |||||||||
Other | 1 | 1 | ||||||||
Distribution | 9 | X | X | X |
Life Cycle Stage | CWU | WF | CF | Hotspots | ||||||
---|---|---|---|---|---|---|---|---|---|---|
% | % | % | WF | CF | Water Scarcity | Water Pricing | Energy Pricing | GHG Regulation | Data Uncertainty | |
Orchard irrigation | 98 | 63 | X | X | X | X | ||||
Orchard energy use | 2 | 22 | X | X | X | X | ||||
Orchard fertilizer. | ||||||||||
Production | 2 | 7 | ||||||||
Emission | 2 | |||||||||
Other inputs | 12 | 5 | ||||||||
Packing & cooling | 1 | 4 | ||||||||
Packaging | 1 | 20 | X | X | ||||||
Ripening | 4 | |||||||||
Distribution | 55 | X | X | X |
Life Cycle Stage | CWU | WF | CF | Hotspots | ||||||
---|---|---|---|---|---|---|---|---|---|---|
% | % | % | WF | CF | Water Scarcity | Water Pricing | Energy Pricing | GHG Regulation | Data Uncertainty | |
Vineyard | ||||||||||
Irrigation | 97 | 97 | X | X | X | X | ||||
Electricity | 1 | |||||||||
Fuels | 1 | |||||||||
Other | ||||||||||
Winery | ||||||||||
Electricity | 1 | 2 | ||||||||
Water intake | 1 | X | ||||||||
Organic waste | 3 | |||||||||
Other | 1 | |||||||||
T‘port to bottling | 1 | |||||||||
Bottling | ||||||||||
Packaging | 1 | 1 | 23 | X | X | X | X | |||
Electricity | 1 | |||||||||
Distribution | 1 | 1 | 68 | X | X |
Category | Range kg·CO2e·kg−1 | Examples |
---|---|---|
A | <1 | Tea, mineral water, vegetable soup, boiled potato, soda, black coffee, cooked lentil, beer, potato salad, cooked onion, fresh clementine, quiche Lorraine, fresh orange, cooked pasta, fresh apple, whole wheat bread, white sugar, cooked white rice |
B | From 1 to <2 | Honey, canned applesauce, sunflower oil, red wine, canned beans drained, pasteurized orange juice, walnuts, raw tomatoes, semi-skimmed milk, raw carrot, raw endive, green salad without dressing, fruit yogurt, frozen potato fries, canned ravioli, cream cheese with 20% fat, tabbouleh |
C | From 2 to <5 | Pain au chocolat, olive oil, scalloped potatoes, plain yogurt, banana, vegetable oil spread, crackers, sardines canned in oil, canned stew, slated potato chips, brioche, cream, smoked salmon, fried breaded fish, pie or fruit tart, pizza, boiled egg |
D | From 5 to <10 | Canned tuna, baked cod, poultry cutlet, roasted chicken, cooked ham, sausage, cheeseburger, cooked bacon, camembert |
E | >10 | Gruyere 45% fat, cooked shrimp, chopped steak with 15% fat, lamb chops, unsalted butter |
Category | Range L·H2Oe·kg−1 | Examples |
---|---|---|
A | < 5 | Fresh milk (New Zealand), whole wheat (South-eastern NSW, Australia), fresh milk (South Gippsland, Australia), white wine (Portugal), fresh tomato (Bundaberg, Australia), fresh tomato (NSW Tablelands, Australia), whole wheat (Chang basin, China) |
B | From 5 to <50 | Soda from Australian sugar, beef cuts (Bathurst, Australia), fresh milk (Heilongjiang, China), maize (Songliao basin, China), maize (Chang basin, China), maize (Beijing region, China), beef cuts (North coast NSW weaners, grass fattened and feedlot finished, Australia), beef cuts (inland NSW weaners, grass fattened and feedlot finished, Australia), fresh tomato (Sydney region, Australia), Peanut M&M® (Australia), lamb cuts (western Victoria, Australia), beef cuts (Scone, Australia) |
C | From 50 to <500 | Fresh tomato (Beijing region, China), fresh tomato (Shouguang, China), whole wheat (Murrumbidgee region, Australia), maize (Hai basin, China), beef cuts (Parkes, Australia), maize (Huai basin, China), Dolmio® pasta sauce (Australia), maize (Huang basin, China), whole wheat (Huai basin, China), whole wheat (Beijing region, China), fresh milk (California, USA) |
D | >500 | Beef cuts (Gundagai, Australia), whole wheat (Huang basin, China), whole wheat (Hai basin, China) |
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Ridoutt, B.; Sanguansri, P.; Bonney, L.; Crimp, S.; Lewis, G.; Lim-Camacho, L. Climate Change Adaptation Strategy in the Food Industry—Insights from Product Carbon and Water Footprints. Climate 2016, 4, 26. https://doi.org/10.3390/cli4020026
Ridoutt B, Sanguansri P, Bonney L, Crimp S, Lewis G, Lim-Camacho L. Climate Change Adaptation Strategy in the Food Industry—Insights from Product Carbon and Water Footprints. Climate. 2016; 4(2):26. https://doi.org/10.3390/cli4020026
Chicago/Turabian StyleRidoutt, Bradley, Peerasak Sanguansri, Lawrence Bonney, Steven Crimp, Gemma Lewis, and Lilly Lim-Camacho. 2016. "Climate Change Adaptation Strategy in the Food Industry—Insights from Product Carbon and Water Footprints" Climate 4, no. 2: 26. https://doi.org/10.3390/cli4020026
APA StyleRidoutt, B., Sanguansri, P., Bonney, L., Crimp, S., Lewis, G., & Lim-Camacho, L. (2016). Climate Change Adaptation Strategy in the Food Industry—Insights from Product Carbon and Water Footprints. Climate, 4(2), 26. https://doi.org/10.3390/cli4020026