Case Study: Sourdough Crackers

Project summary

Regenerative agriculture utilizes techniques like conservation tillage, cover crops and crop rotation to build up and sequester carbon in the soil. If yields can be maintained similar to conventional agriculture, then this could be the future of food production. So when a startup snack food manufacturer asked us to quantify the carbon benefits of their crackers made with wheat and other ingredients produced using organic/regenerative methods, we quickly leveraged our tools and database to put together a  life cycle assessment (LCA) study comparing crackers made with conventional and organic inputs.

System modeled in this study

The diagram below illustrates the supply chain for a packaged box of sourdough crackers. 

The functional unit is a packaged box of crackers (net weight: 4 oz). The system boundary is cradle-to-gate from the perspective of the cracker manufacturer. We used the same supply chain to compare a box of crackers made with conventionally produced wheat and sunflower seed (these are the two primary agricultural inputs to the cracker production) vs. a box of crackers made with organically produced wheat and sunflower seeds. We had actual secondary data for the conventional production systems in our life cycle inventory (LCI) database. We modified these conventional systems to create hypothetical LCA models for organic production systems in order to quantify the benefit of switching to organics. 

Organic farming systems are generally characterized by the types of inputs used, such as fertilizers and pesticides that are not synthetically produced and are non-toxic. Based on information from the actual farms that produce the organic ingredients considered in this study, we know that these organic systems also use regenerative farming methods to build and preserve soil carbon. Therefore, we refer to these systems as “organic/regenerative” in this report (or just “organic” for short).

General assumptions

An initial LCA study often starts with a number of assumptions and placeholders that are later refined using higher-quality data. For the two cracker production systems modeled in this study, the data available initially included the list of ingredients (including the weights of ingredients), the production and processing locations of the ingredients, and the co-packer location where the final production and packaging take place. We used secondary data from our LCI database to model the production and processing of the conventionally produced ingredients.

In addition, we made several assumptions and used a number of placeholders as documented below in order to fill in the necessary preliminary data for organic production, waste disposal, processing, packaging, and various minor ingredients:

  • For the organic/regenerative farming systems, the on-farm energy use and yield are assumed to be the same as conventional systems for which we have data in our LCI database. Past LCA studies (including one of our own) have shown that organic farming systems often suffer from lower yields relative to a conventional system; however, farming techniques are improving and we expect our assumptions to be replaced with actual data from the specific farms in a future iteration of this LCA study.
  • For the organic/regenerative farming systems, the primary fertilizer is assumed to be manure-based compost supplying the same total nitrogen per acre annually as the synthetic fertilizers used in a comparable conventional system. We elaborate on this further in the “Farm-level LCAs” section below.
  • For the baking process at the co-packer facility, crackers are assumed to use comparable energy as bread rolls for which we have data in our LCI database.
  • Sunflower oil production is assumed to be located near the seed farm, and the waste is composted close to the production facility.
  • Although extensive, the LCI database has a finite number of entries, so substitution of products with similar profiles follow: we swapped malt for the yeast extract, acetic acid for lactic acid (since they have similar fermentation processes), and soda powder for baking powder.  Each of these substitutions are for an ingredient that comprises 1% or less of the formulation.  
  • Packaging material is assumed to consist of a 29.08g paperboard carton and a 5g polyethylene (HDPE) plastic liner.

LCA tools and LCI database

We used our new carbon modeling tool, CarbonScope, to conduct the two product LCAs in this project. FoodCarbonScope was used for the farm-level LCAs of the hypothetical organic/regenerative wheat and sunflower seed crop systems. The LCI database underlying the analysis is CarbonScopeData.

Farm-level LCAs

Since we did not have detailed production data for the two primary agricultural inputs used in the manufacture of the crackers — organic wheat and organic sunflower seeds — we created hypothetical organic/regenerative systems based on the conventional production systems for which we had data in CarbonScopeData. We assumed that the energy use and yield per acre would remain the same between conventional and organic systems, and the primary differences would be in the fertilizer application and soil carbon sequestration. The organic farms are assumed to use manure-based compost, based in part on information received from one of the farms, as the primary fertilizer (NPK percentages =  1.5:1:1.5). 

We made a few additional and reasonable assumptions about compost:

  • Compost mineralizes and releases 10% of the total compost nitrogen per year.
  • Compost has been applied long enough that sufficient amounts of total mineralized nitrogen,  phosphorus and potassium are available to the crops each year.
  • Compost added each year must supply the equivalent of 20% of the synthetic nitrogen through mineralization; the other 80% would come from previous years’ compost applications.

The table below summarizes the key parameters used in the farm-level LCAs of the two commodities. The wheat farming system is considered “transitional” because it is still within a 20-year period following a switch from conventional to organic production. The sunflower seed farming system is considered to be in “steady-state” because the organic production was established more than 20 years ago. The climate and moisture regimes were set based on the locations of the farms. The soil type was set based on information supplied by the farms. The last column in the table sets the carbon inputs to soil as one of four discrete levels (low, medium, high, high-organic), and we chose the “high” level based on our understanding of the farming systems. These parameters are based on IPCC tier 1 methodology, and are used in the farm-level LCAs by FoodCarbonScope to estimate changes in soil carbon during the transition from conventional to organic/regenerative farming.

Of the two crop systems, only the wheat gets credit for soil carbon sequestration as it transitions from a conventional system to an organic/regenerative system. Soil carbon generally increases during such a transition as illustrated below and is calculated using the parameters summarized above. The numbers in the diagram below are for illustration only and do not represent the actual systems modeled in this study. 

The table below summarizes the cradle-to-farmgate LCA results for the two agricultural commodities considered in this study:

Product LCA results

The table below compares the life-cycle impacts of a box of crackers made with organic ingredients produced using regenerative methods vs. crackers made with conventionally produced ingredients. Organic production results in 30% lower greenhouse gas emissions (quantified as Kg CO2e), and all of this is attributable to the difference in agricultural methods. This difference arises from the “Inflows” category which includes the purchased agricultural commodities. The LCA results clearly show the benefits of switching to organic/regenerative production, but with the caveat that credit for soil carbon accumulation can only be taken during the transition period.

The other interesting insight from the results is that packaging dominates the life-cycle impacts of the products. When the ingredients are plant-based with fairly low carbon emissions, transportation and packaging can sometimes take on an outsized role. The table below shows the top four contributors to carbon emissions in the life cycle of the organic cracker product. Two of these are the packaging materials. The paperboard used to make the carton contributes about half of the total carbon footprint of the finished product. 

Conclusion

This LCA study has demonstrated the significant potential for reducing the cradle-to-gate greenhouse gas emissions of the client’s cracker product by sourcing agricultural commodities from farms that are using organic/regenerative methods. It should be noted that the actual supply-chain data for the production was supplemented with several assumptions and placeholders, so these results should be treated as the first step in the process of quantifying and optimizing the climate impacts of the cracker products.

Case Study: Coffee Drinks

Project summary

Americans lead the world in coffee consumption with 400 million cups of coffee consumed per day. Per-capita coffee consumption is even higher in European countries. With coffee consumption comes carbon emissions, and we thought it would be interesting to do a life-cycle comparison of the environmental impacts of three popular coffee drinks that you could order at a neighborhood cafe: a latte with 2% milk, a latte with soy milk, and a cappuccino with 2% milk.

Systems modeled in the study

The diagrams below illustrate the supply chains for both lattes modeled in this study. Milk is sourced relatively locally in half-gallon containers, whereas soy milk is produced more distantly and in smaller containers.  The cappuccino’s ingredients and sourcing are inherently similar to that for the latte with 2% milk, but just with less milk added and more power used for frothing the milk. The functional unit for the LCA is a 12oz latte and a 6oz cappuccino. The cappuccino has 6oz less milk in it, but otherwise has the same coffee/water ratio. Although we could have modeled the cappuccino with a shorter cup, we decided to use the same cup size for all drinks because coffee cups of different sizes are surprisingly similar in weight. The system boundary is cradle-to-grave in all cases, with the to-go cup disposed of at the cafe.

Figure 1: System diagram for a to-go latte with 2% milk
Figure 2: System diagram for a to-go latte with soymilk

LCA tool and LCI database

We used our new carbon modeling tool, CarbonScope, to conduct the LCAs in this project. The life-cycle inventory (LCI) database underlying the analysis is CarbonScopeData.

Results

The three life-cycle impact categories considered in this study are embodied carbon (Kg CO2e), embodied energy (MJ) and embodied water (L). We first consider the embodied carbon associated with a Latte made with 2% milk, grouping all processes as associated with the primary ingredient.   Figure 3 shows that the largest component is from the milk, with the second largest impact from the packaging.   Despite being sourced from afar, coffee’s impact is  relatively small.    

Figure 3: Embodied carbon by process

Replacing to-go materials with one’s own trusted travel mug would allow one to enjoy a free latte every 6th time from a carbon equivalence perspective, if we ignore the impact of producing and then repeatedly washing the mug.  But for now we will for now focus on the highest impact ingredient: the milk.  Our first alternative replaces the 2% milk with soymilk, and the second is the cappuccino, which uses only 3 ounces of milk instead of the 9 used by a latte.

The table below summarizes the LCA results.  While a latte with soy milk has less embodied water than milk, there is no effective difference in the embodied carbon.  Part of this is due to the longer supply chain for soymilk, the greater share of the smaller package, and the inherent energy intensity of soymilk production.  Other alternative milks would have different impacts.  

We then consider a different drink for the third alternative.  The cappuccino shows the significantly lower environmental impacts from consuming less milk, only having 55% of the embodied carbon and, not-surprisingly, one-third the water.  The increased energy usage from frothing the milk is more than offset by reducing the milk used.

Overall, this study shows that milk (or soymilk) dominates the carbon footprint of a latte. The coffee itself is a minor contributor. So habitual latte drinkers should not fret about their coffee addiction (at least from an environmental perspective), but they might consider switching to a less milky drink, and everyone can consider bringing back reusable mugs when it is again safe to do so.

Case Study: Organic vs Conventional Farming

organic farming

Project summary

Given the growing importance of organic food production, there is a pressing need to understand the relative environmental impacts of organic and conventional farming methods. This study applied standards-based life cycle assessment (LCA) to compare the cradle-to-farm gate greenhouse gas emissions of 12 crop products grown in California using both organic and conventional methods.

Systems modeled in the study

We modeled 12 different crops produced using both organic and conventional methods in California. The system boundary was defined as cradle-to-farmgate. In addition to analyzing steady-state scenarios in which the soil organic carbon stocks are at equilibrium, this study modeled a hypothetical scenario of converting each conventional farming system to a corresponding organic system and examined the impact of soil carbon sequestration during the transition.

LCA tool and LCI database

We used our comprehensive food/agriculture LCA tool, FoodCarbonScope, to conduct the LCAs in this project. The life-cycle inventory (LCI) database underlying the analysis is CarbonScopeData.

Results

The results showed that steady-state organic production has higher emissions per kilogram than conventional production in seven out of the 12 cases (10.6% higher overall, excluding one outlier). Transitional organic production performed better, generating lower emissions than conventional production in seven cases (17.7% lower overall) and 22.3% lower emissions than steady-state organic. The results demonstrated that converting additional cropland to organic production may offer significant GHG reduction opportunities over the next few decades by way of increasing the soil organic carbon stocks during the transition. Non-organic systems could also improve their environmental performance by adopting management practices to increase soil organic carbon stocks.

Cradle-to-farm gate GHG emissions for conventional (steady-state), organic (steady-state) and organic (transitional) production

Detailed report

Full text: https://www.cleanmetrics.com/pages/comparisonoftwelveorganicandconventionalfarmingsystems.pdf

Detailed LCA reports available here as “supplemental”: https://www.tandfonline.com/doi/abs/10.1080/10440046.2012.672378

Case Study: US Food Waste

WASHINGTON, DC - AUGUST 2: Food waste material processed by Compost Cab workers to create compost at Howard University Community Compost Cooperative on Wednesday, August 2 , 2017, in Washington, D.C. (Photo by Salwan Georges/The Washington Post via Getty Images)

Project summary

This pioneering study analyzed the climate change and economic impacts of food waste in the United States. Using loss-adjusted national food availability data for 134 food commodities, it calculated the greenhouse gas emissions due to wasted food using life cycle assessment (LCA) and the economic cost of the waste using retail prices.

Systems modeled in the study

We modeled a total of 134 food commodities using average US production data for each of them. The system boundary was defined as cradle-to-grave. The life-cycle model of material flow through the food system is depicted in Figure 1.

LCA tool and LCI database

We used our comprehensive food/agriculture LCA tool, FoodCarbonScope, to conduct the LCAs in this project. The life-cycle inventory (LCI) database underlying the analysis is CarbonScopeData.

Results

The analysis showed that avoidable food waste in the US exceeds 55 million metric tonnes per year, nearly 29% of annual production. This waste produces life-cycle greenhouse gas emissions of at least 113 million metric tonnes of CO2e annually, equivalent to 2% of national emissions, and costs $198 billion.

Detailed report

http://centmapress.ilb.uni-bonn.de/ojs/index.php/fsd/article/view/198/182

Case Study: Meat Eater’s Guide

Project summary

Environmental Working Group (EWG) is an influential non-profit organization that has published groundbreaking research on environmental health. Several years ago, they asked us to use our LCA tools, database and expertise to generate definitive results on the relative carbon footprints of a wide range of food commodities.

Systems modeled in the study

We modeled the full cradle-to-grave life cycles of 25 major food commodities, including typical food waste and cooking. Overall we conducted life-cycle assessments (LCAs) on 53 actual product systems in order to calculate average life-cycle impacts for the 25 commodities. This includes meats such as beef, lamb, poultry and seafood. The list also includes dairy products such as milk, yogurt and cheese, and plant-based foods such as beans, rice, vegetables and tofu.

LCA tool and LCI database

We used our comprehensive food/agriculture LCA tool, FoodCarbonScope, to conduct the LCAs in this project. The life-cycle inventory (LCI) database underlying the analysis is CarbonScopeData.

Results

This graphic from EWG summarizes the relative carbon footprints of food commodities in terms of car miles driven.

Eat Smart Chart. Eat smart your food choices affect the climate

Detailed report

https://static.ewg.org/reports/2011/meateaters/pdf/methodology_ewg_meat_eaters_guide_to_health_and_climate_2011.pdf

Case Study: Cycling Jerseys

Project summary

Peloton de Paris is Belgium’s first cycling café and a small business that is thoughtful about their impact on the planet. They have created their own line of cycling apparel that they sell worldwide, and asked us to conduct a comparative life-cycle assessment (LCA) of two of their cycling jerseys. Both are polyester based, but one uses virgin polyester and the other is made from recycled polyester.

Systems modeled in the study

The diagrams below illustrate the supply chains for the two jersey product systems modeled in this study. The functional unit for the LCAs is one cycling jersey. The system boundary is cradle-to-warehouse in both cases.

Life Cycle Inventory and System Boundaries for Anibal/Matrix Jersey

Life Cycle Inventory and System Boundaries for Fez/GreenFly Jersey

LCA tool and LCI database

We used our new carbon modeling tool, CarbonScope, to conduct the LCAs in this project. The life-cycle inventory (LCI) database underlying the analysis is CarbonScopeData.

Results

The three life-cycle impact categories considered in this study are embodied carbon (Kg CO2e), embodied energy (MJ) and embodied water (L). The table below summarizes the LCA results and shows the significantly lower environmental impacts from using recycled materials. The study also found that switching to ground transportation for delivering the jerseys to the warehouse in Belgium would further reduce the environmental footprints of the jerseys. 

Detailed report

https://www.cleanmetrics.com/pages/Peloton-LCA-final-report.pdf