Accounting for Reductions: The Carbon Footprint of a Package-Free Grocery Store

Accounting for Reductions: The Carbon Footprint of a Package-Free Grocery Store
In 2020, a fabulous group of students in the Bren School of Environmental Science & Management at UC Santa Barbara conducted a research study on our circular model. The goal for this study was to quantify the carbon footprint of a package-free grocery store and identify additional opportunities for emission reductions. Keep reading to find out what they learned!

Executive Summary

Background, Objectives, and Significance

Nada offers sustainably sourced foods, zero waste lifestyle products, and a package-free shopping experience. The business is also committed to environmental and social justice. One of the ways Nada is working to further reduce its environmental impacts is quantifying the carbon footprint of its business model. The objectives of this carbon footprint accounting study are to:
  1.   Establish an annual carbon footprint baseline
  2.   Identify and evaluate options for emissions mitigation
The results from this study will shed light on the hotspots of carbon emissions within its supply chain, and inform Nada of strategies to reduce the emissions of the whole supply chain.

Scoping and data sources

In this study, Scope 1, Scope 2, two categories from Scope 3 (upstream transportation and purchased goods & services), and food waste diversion emission savings are calculated for Nada in 2019 and 2020. Scope 1 emissions came from on-site refrigerators, which leak refrigerants over time. Information about appliances were acquired from equipment SPEC sheets and charge capacity information was provided by the manufacturer. Scope 2 emissions are indirect emissions through purchased electricity. Energy consumption of Nada was extracted through Nada’s monthly utility bills through 2019 and 2020. Upstream transportation includes transportation emissions that occurred when transporting products from suppliers to Nada’s storefront. Purchased goods and services includes all the emissions that occurred during the production of the products purchased by Nada. All the data used to calculate Scope 3 emissions were extracted from Nada’s purchasing invoices from 2019 and 2020. To calculate the emission savings from Nada’s food waste diversion program, discounted food item data was acquired from Nada.  

Introduction

Since the mid-20th century, global temperature has increased at an unprecedented rate (IPCC, 2018). This warming trend has been the result of human activities that lead to greenhouse gas emissions. Greenhouse gases trap heat and affect the transfer of infrared energy through the atmosphere (Kweku et al., 2017). This warming effect leads to the rise in global temperature. Global warming has a plethora of long-term effects that are devastating and even irreversible. Some examples include: more frequent extreme weather events, sea level rise, changes in precipitation pattern, longer growing seasons, and ocean acidification (IPCC, 2018).

To slow the rise in global temperature, intergovernmental collaboration has emerged to take action on climate change. The most notable is the Paris Agreement, which aims to limit global warming to well below 2 degrees Celsius, compared to pre-industrial levels. Currently 195 countries have signed the Paris Agreement, and 190 have submitted their Nationally Determined Contributions (NDCs), which are plans for national climate actions. 

In addition to efforts at the national level, the private sector also has crucial roles to play. Corporations have arguably the most power to reduce greenhouse gas emissions, as they produce almost everything that people buy, use, and throw away. Emissions are produced during almost every part of supply chains. Therefore, the opportunities for emission reductions in supply chains are huge. Many multinational corporations have committed to climate mitigation actions. For example, Volvo has announced to completely phase out internal combustion engines by 2030, including hybrids; Amazon announced that it will achieve carbon neutrality by 2040 across its business.

In order to effectively reduce greenhouse gas emissions globally, it is important to understand where emissions are coming from. When broken down by economic sectors, about 21% to 37% of annual anthropogenic greenhouse gas emissions can be traced to the food system. Emissions are a byproduct of food production, and they occur at every stage in the food supply chain. At the farm stage, greenhouse gases (GHGs) are released through land use change, application of nitrogen fertilizers, soil and livestock processes, and fossil fuel combustion to power machinery (Garnett, 2011). After food leaves the farm, emissions are largely the result of transportation, refrigerant leakage, and waste (Garnett, 2011; Mbow et al., 2019; Scholz et al., 2015)

Background

A major problem in the food system is waste, both from packaging material and food. Packaging waste not only represents a significant source of pollution, but also a significant loss of financial and material resources. About 95% of the material value of plastic packaging — or between $100 and $150 billion dollars annually — is lost to the global economy after a single use. Food waste, food that is uneaten and sent to landfill, is responsible for methane generation, a greenhouse gas with a warming effect several orders of magnitude stronger than that of CO2 (Sisto, et al., 2017). 

In order to reduce emissions from the food system, one innovative grocery store business model has emerged in recent years: zero-waste grocery stores. These stores offer the customers a plastic-free, bring-your-own-container shopping experience, bringing customers organically grown products from local suppliers, while minimizing food waste within the store. 

Because of the significant contribution to global emissions by the food system, businesses that are part of the food system also have important roles to play in reducing carbon emissions. Grocery stores are in a unique position to promote change in the food system, because they are the point of contact between consumers and producers of food, and have influence on both the behaviors of customers and the practices of food suppliers. They can reduce supply chain emissions by choosing suppliers based on location and food production practices, being selective of the product they sell, and reducing food waste within the store.

 

Food System and Equality

Food waste not only contributes to climate change, it also represents inequality within the food system. Waste represents resource depletion and environmental degradation without providing utility to society. The issues of resource depletion, environmental degradation, and climate change do not impact global communities equally. Climate change impacts reinforce existing patterns of inequity; they exacerbate transnational and intergenerational inequality (Füssel, 2010; Hartmann-Boyce et al., 2018). Environmental burdens are disproportionately borne by the poor and marginalized; with climate change, it is the same (Füssel, 2010). Because patterns of consumption drive environmental degradation, resource depletion, and climate change, the highest spenders contribute most to climate change. Meanwhile, the victims are those who are least culpable — and least equipped to adapt (Füssel, 2010).

Although these trends exist at local levels and within national borders, they are most extreme at the global level. High-income countries consume more and produce more emissions and waste — while the most countries vulnerable to climate change countries generally have the lowest environmental impact. (Füssel, 2010). The food we consume is one example of how consumption patterns are exacerbating the environmental inequities around the world. Diets in urbanized, high-income economies have changed, with beef, dairy, and ultra-processed foods becoming daily staples in the average diet (Füssel, 2010). These foods typically have high environmental impacts, and are highly energy and emission intensive (Tilman, 2014). Additionally, in these high-income countries, obesity rates are highest in poor and marginalized communities (Füssel, 2010). Meanwhile, in countries with minimal environmental impact, low food security, and low income, obesity prevalence is low (Füssel, 2010).

These findings suggest that the most culpable and the least vulnerable to climate change are high-income groups and countries, and those who are privileged by their race, gender, sexuality, or ability status (Füssel, 2010; Reckien et al., 2017; Hartmann-Boyce et al., 2018). The social threat of climate change is the expectation that climate change impacts would reasonably vary by income, age, race, and gender, among other marginalized identities (Hartmann-Boyce et al., 2018). Food insecurity is experienced by individuals in these groups at higher rates, and climate change is expected to worsen the disparity (Hartmann-Boyce et al., 2018). Furthermore, these groups are commonly excluded from decision-making processes at loci of power (Füssel, 2010).

In observation of the social threat of climate change, non-negotiable planetary boundaries, the zero waste movement, and consumer trends, it is possible that overconsumption is poised to become a trendy, mainstream environmental concern. One of the consequences of overconsumption and production in developed nations is waste. Waste is increasingly at the attention of Canadian policymakers. In 2019, the Canadian federal government began researching the plastics value chain to inform a promised ban on single-use plastics. In 2020, British Columbia announced plans for bans of single-use plastics, following several municipalities in the province. However, the COVID-19 pandemic strained government resources and required the prioritization of public health over waste mitigation (Silva et al., 2020). In many cases, the pandemic led directly to the postponement of waste reduction targets (Silva et al., 2020).

From an economic perspective, waste represents a significant loss of financial and material resources. About 95% of the material value of plastic packaging — or between $100 and $150 billion dollars annually — is lost to the global economy after a single use. In Canada alone, the number is nearly $8 billion. However, current market structures and the low cost of waste disposal are barriers to circularity (Veleva et al., 2017). Policymaking lags behind technological and scientific advances; meanwhile, inflexible business models and entrenched supply chains resist change in the private sector.

Similarly, climate change is a global public harm resulting from the inertia of political and economic systems in response to emerging knowledge and technologies (Veleva et al., 2017). However, as economic perspectives shift, the range of policy options has become diversified. Notably, the 2016 Kigali Amendments to the Montreal Protocol initiated the phase-out of several potent greenhouse gases (GHGs), including refrigerant mixtures containing hydrofluorocarbons (HFCs) (Hu et al., 2017). At the national level, the Canadian government is working to implement carbon polluting pricing systems. Provincially, British Columbia has established a carbon tax of $40 per tCO2e. However, as with plastic waste, some more ambitious carbon targets have been relaxed as a result of the 2020 COVID-19 pandemic.

 

Nada

One company that is catalyzing change in the food space is Nada Grocery, otherwise known as “Nada”, a package-free, zero waste grocery store. In 2018, they opened Nada in Vancouver, Canada with the goal to reconnect people to their food and provide an environmental and health conscious option for consumers. Nada offers sustainably sourced foods, zero waste lifestyle products, and a package-free shopping experience. The business model also minimizes food waste through careful food handling protocol.

Nada strives to minimize food and packaging waste, and is among an emerging category of zero-waste grocery stores. Nada has a “BYOC” (bring your own container) policy and gives nearly-expired products a new life as ready-to-eat meals served in the on-site cafe. To keep prices low, Nada purchases surplus and imperfect produce directly from farmers. In addition, the procurement strategy at Nada emphasizes local, transparent, and ethical sourcing.

Despite the innovation at Nada and other zero-waste stores, there are elements of the global food system that are out of store owners’ control. The complexity and inertia of the food system complicates the mission of achieving a truly waste-free supply chain. In addition, customer expectations and habits are often not aligned with the requirements of zero-waste shopping. Now, in the midst of the global COVID-19 pandemic, concerns about hygiene and an increased demand for online ordering and home delivery have driven Nada to make sweeping changes to its business activities. 

With the knowledge of the food systems contribution to climate change, Nada wanted to take action and discover ways they could reduce their own carbon emissions and potentially be a model for other grocery stores. However, Nada was unaware of the magnitude and distribution of their own emissions. They needed to understand what areas of their business were the most carbon intensive in order to make data-driven decisions of where to mitigate emissions. With its newer, more agile business model and commitment to environmental and social justice, Nada created a vision to understand their own carbon emissions and implement strategies that not only lower their own emissions, but educate and inspire their customers and other grocery retailers to do the same.

Nada strives to remain at the forefront of sustainability and to be a leader in their community, using their business for good and paving the way to a more just and regenerative food system. Many of Nada’s efforts are focused around reducing plastic and food waste, and sourcing from local, socially and environmentally responsible farmers and suppliers who use best practices to produce their products or grow their crops. Over 100 of Nada’s suppliers are located within the Lower Mainland and Vancouver Island, however with thoughts on expansion, their impact and influence are set to grow. Through our analyses, we considered five areas in which Nada has the ability to effect change. Described below are those areas and how Nada can pull various levers that will subsequently lower their emissions in that space. Outlined below are details about supply chain emissions, food waste, product mix, and product sourcing. All of these explain where there is space to reduce emissions and how Nada has already reduced or can reduce emissions in the category. 

Supply Chain Emissions 

“Food miles”, or the distance food travels between its production and consumption, is one aspect to consider when analyzing the life cycle emissions of food products. In the US it is estimated that food travels over 2000km before it reaches the consumer. Though this may be shocking to some, the actual impact food miles have on a product’s total life cycle emissions vary depending on a variety of factors. Some key points to consider are what type of food is being shipped, how the food is grown, the electric grid mix where it was grown, what types of energy inputs the farmers are using, how far the food travels, and what type of vehicles the food is being transported on (Avetisyan et al., 2014). Ruminants, for example, are highly emission intensive in the production phase, and so the transportation and distribution stage of red meat contributes a very low amount to the overall life cycle emissions, typically around 1 percent (Clune et al., 2017). Fruits and vegetables, on the other hand, are less emission intensive during production, leading to a greater proportion of their emissions coming from their associated food miles (Weber & Matthews, 2008). The energy efficiency in the production of the same product is also not equal everywhere and can vary spatially. For example, some producers may use 100% renewable energy in their farm operations, while others may depend heavily on fossil fuels. To illustrate this point, an LCA study comparing the emissions associated with lamb production in NZ and the UK, found that importing lamb from NZ resulted in less overall emissions in comparison to local UK lamb production, despite the long distance it had to travel (Saunders et al., 2006). This was largely due to the high energy and emission intensity of lamb production in the UK from its high reliance on fossil fuels (Saunders et al., 2006). The type of transportation food is being shipped on will also impact the relative contribution of food miles to a product’s overall emissions. For example, shipping products by air is typically much more emissions intensive than shipping products by rail or by water. Average airfreight emission factors ( CO2e/tonne-km) are typically 10 to 100 times larger than rail and water transport (Cefic, 2011).

Given the complexities in assessing the overall impact of food miles on a product’s life cycle emissions, it can be difficult to quantify the impact of local sourcing on emissions without knowing other attributes of the retailer, such as who they’re sourcing from, how much food is going to waste, and what types of food they are sourcing. In this case of Nada, however, most of these are known. Though they have yet to implement any strict tracking methods, Nada does its best to source their food from responsible farmers with sustainable, low impact growing practices. They also produce zero food waste, diverting 100% of any food waste from the landfill through discounting, donating, and composting any food items they cannot sell or donate for whatever reason. Nada also carefully curates the food products they have stocked in store, maintaining a food portfolio of largely fresh produce and very little red meat. Lastly, Nada strives to support its local community as much as possible, with over 75% of their suppliers in 2020 within 150km of their storefront. Because Nada is mindful of the environmental impact of every part of their operation, the impact of food miles and sourcing local has a larger overall effect on emissions than it may have in a traditional grocery store.

Food Waste

Food waste is responsible for 8% of all global greenhouse gas emissions. Grocery stores and supermarkets are responsible for 12% of that waste, while an additional 5% does not even make it from the supplier to the store. Food waste is typically generated in storefronts through damaged, expired, or imperfect products, and includes food that spoils, expires, or is otherwise left uneaten between the point of sale (the grocery store) and the point of intended consumption (e.g., a place of residence) (Ranganathan et al., 2016). These items are normally destined for the landfill, where they generate additional emissions during decomposition. 

Food waste reduction has two implications for the climate and food system: avoided emissions and increased efficiency. Because the production of food itself generates greenhouse gases, saving food from disposal increases the efficiency of the food system (Garnett, 2011). In addition, in the landfill, uneaten food releases greenhouse gases (Sisto et al., 2017)These emissions are referred to as ''empty emissions'' as the products are not used for the intended purpose. ''Empty'' emissions include all the emissions released in production, transportation upstream, transportation to landfill, and landfill decomposition (Porter & Raey, 2014). The impact of food waste is so costly — and the potential benefits of minimization so high — that the UN Sustainable Development Goals includes the target of reducing food waste at the retail and consumer levels by 50% globally

Nada has tried to minimize both storefront and supply chain food waste losses through their in-store Café, sale of imperfect foods, discounting of imperfect or expiring foods to both employees and customers, and donation. Through these programs, Nada has eliminated all food waste since opening their storefront. Our analysis looks at the carbon savings Nada’s programs are providing and how Nada can be an example to other grocery stores.

Although packaging waste is out of the scope of this project, it remains a consideration for grocery retailers and consumers when making purchasing decisions. Packaging waste has become a mainstream environmental issue in North America in recent years. In 2020, the British Columbia provincial government announced plans for sweeping bans of single-use items, such as straws, following several municipalities in the province. Packaging waste includes a range of materials — including glass, aluminum, cardboard, paper, and plastic — that are disposed by end users.

Packaging is the most common use for plastic; nearly half of all primary production of plastic was devoted to packaging in 2015 (
Geyer et al., 2017). Most of this plastic is discarded after a single use, remaining in circulation for less than one year (Geyer et al., 2017). After disposal, most plastic waste accumulates in landfills; as of 2015, most (79%) of the plastic ever made had either been landfilled or leaked into the environment (Geyer et al., 2017). In Canada, only 9% of plastic waste is recycled, and the primary contributor (43%) to plastic waste is packaging. However, only 3% of the carbon emissions across the supply chain of food come from packaging. Additionally, there is debate about whether in some cases packaging reduces carbon emissions through avoiding food wasted from being damaged because of a lack of protection from packaging. 

Product Mix

Food production of any kind will emit some amount of greenhouse gases, however literature shows that different foods can have a wide range of carbon emissions associated with them (Tilman & Clark, 2015). The three main contributors to GHG emissions from agriculture are methane from ruminant livestock, nitrous oxide from fertilizer use, and land clearing (Tilman & Clark, 2015). This research indicates that certain diets that prioritize low carbon-intense food (e.g., vegetables) and limit the consumption of high carbon-intense foods, can lower the amount of greenhouse gases emitted by the food system.

2020 Nada Scope Emissions

Figure 1. Greenhouse gas emissions associated with different foods. Source: (Tilman & Clark, 2015)

When broken down further taking the entire life cycle of food into account, we see that the largest impact in terms of reducing emissions can be made by specifically choosing what foods are eaten as well as the growing practices used to grow the food or raise the livestock (Figure 2).
Green House Gas Emissions Across The Food Chain
Figure 2. Greenhouse gas emissions of different foods broken down by supply chain phases. Source: (Ritchie, 2020)

Therefore, the most impactful role that grocery stores can play in the climate crisis is to source a product mix that has lower greenhouse gas emissions associated with them and source these products from farmers who use practices that regenerate the ecosystem (no-till, crop diversity, and cover cropping) (Montgomery, 2020). Nada does their best to both limit the amount of carbon-intensive products in their store and source from farmers who use climate smart farming practices. On the consumer side, large differences in emission intensities of different foods means that dietary shift is one of the most effective ways to reduce your individual carbon footprint. Long-term dietary change requires sustained contact with a similar community. Evidence suggests that identity- or role-based decision-making (i.e., “I am the type of person who lives a sustainable lifestyle”) may cascade into other, positive environmental behaviors (Truelove et al., 2014; Elf et al., 2019). Association with a like-minded group also contributes to behavior change (Elf et al., 2019). Pro-environmental behaviors are affirming when they lead to positive feelings, instead of guilt or shame (Elf et al., 2019). The presence of a trusted, reputable source of information may also be associated with positive, long-term behavior change (Elf et al., 2019).

Sourcing

Another area where grocery stores could reduce their carbon footprint is sourcing. By sourcing from less carbon intensive suppliers, grocery stores could reduce the greenhouse gases generated from their supply chain. Although different food items have inherently different carbon footprints, the same food item can also have varying levels of emissions depending on the growing practice. Certain activities during the production of food crops lead to large amounts of greenhouse gas emissions. The most notable is the use of nitrogen fertilizers. In one study that examined the carbon footprint of growing different food crops through different farming practices (conventional, integrated, and organic), researchers found that nitrogen fertilizers account for over 75% of the total emissions. Additionally, once nitrogen fertilizer use is accounted for, there is no significant difference between conventional, integrated, and organic farming practices (Hillier et al., 2009). This presents a lever for grocery stores to reduce their carbon footprint, because it is largely within a grocery store’s control to be selective of the supplier they source from. However, it is often challenging for grocery stores to use this lever, as it requires data about the carbon footprint of the potential suppliers. 

Significance

Since its inception, sustainability has been at the forefront of Nada’s mission. Nada has made local headlines for its commitment to the zero waste movement and its ingenuity in reducing in-store waste. Up until this point, however, Nada’s focus had been on reducing waste, while it’s carbon footprint and emissions had not been addressed. This project serves as the first step for Nada to begin thinking about their contributions to climate change and how they can play a role in reducing emissions. By establishing a baseline greenhouse gas inventory, Nada can pinpoint the emission hotspots within the store’s operations and value chain and start addressing the areas where they can reduce their carbon footprint. Additionally, the retail sector has more influence over their supply chain than ever, and can use their unique position connecting manufacturers, producers, and consumers to shift us towards more sustainable patterns of consumption  (Naidoo & Gasparatos 2018). As a proven leader in sustainability, this project can help Nada leverage their position and expand their influence to educate and inform their stakeholders about climate change, and inspire them to look at their own carbon footprints and reduce their emissions. As climate change becomes more mainstream, there is increasing pressure from stakeholders for retailers to disclose their emissions, however with no consistent and standard methodology in calculating the carbon footprint of a retail store, this can often be difficult (Naidoo & Gasparatos 2018). This project can be used as a baseline to establish a consistent and effective methodology of measuring grocery store emissions that can be replicated by others in the future. Nada can also use the information gained in this study to help influence other grocery stores to begin measuring, reporting, and reducing their own carbon footprints, taking their entire value chain of emissions into account. This will be one more step towards achieving their goal of creating a more just food system that builds up local communities, connects people with their food, and is resilient to climate change. 


Our team, “NadaTrace”, working alongside Nada, has helped bring us closer to this vision. We conducted a carbon footprint analysis of Nada’s operations and supply chain, analyzed the climate impact of its waste savings, and recommended viable options for emissions reduction. 

Objectives

The goal of this project is to establish a baseline carbon footprint for Nada so that they can identify strategies to reduce their emissions and continue to lead their community as an impact-driven grocery store. Though they already have many systems in-store to reduce their waste, their emissions are unknown. This project will address this knowledge gap and help Nada to continue championing sustainability in grocery stores. Specifically, this project has two objectives:
  1. Establish an annual carbon footprint baseline
  2. Identify and evaluate options for emissions mitigation

Methodology

Life Cycle Assessment

The process of tracing and estimating the impact of each stage in production, use, and end-of-life outcomes is called life cycle assessment (LCA). Numerous life cycle assessments of individual food products underscore the importance of transportation and product type (Sim, 2007; Craig et al. 2012). Meat and dairy products and air-freighted foods are usually associated with the highest emissions (Sim, 2007). LCAs focused on packaging tend to find that its most important role is the prevention of food waste (Russell, 2014; Humbert et al., 2009; Wikström et al., 2014). That is to say, if packaging aids in the reduction of food spoilage or waste, the presence of packaging may reduce emissions (Williams et al., 2012). Packaging itself is rarely the primary contributor to emissions (Russell, 2014).

Carbon Accounting

This analysis followed the Greenhouse Gas Protocol’s reporting standards (WRI, 2004). These standards include Scope 1, ‘direct’ emissions and Scope 2, ‘indirect’ emissions. Additionally, 2 categories were included from Scope 3 ‘indirect value chain’ emissions, Upstream Transportation and Purchased Goods and Services. Scope 1 and 2 are required however, Scope 3 is optional. Scope 3 includes 15 different categories, but it is most valuable to focus on only the top greenhouse gas generating activities. Below describes each Scope’s methodology and assumptions. 

Scope 1: Direct Emissions

Scope 1, or ‘direct,’ emissions include on-site emissions and emissions produced by owned property. This category also includes unintentional gas leaks, which are termed fugitive emissions (Bajpai, 2018). Many of these fugitive gases are potent greenhouse gases. Environmental policymakers are increasingly turning their attention to fugitive emission mitigation (Bajpai, 2018). Through an inventory of the store’s equipment, we determined that Nada’s only Scope 1 emissions are fugitive refrigerant gases.

Refrigerators and freezers are known to leak over their operational lifetime. Historically, ozone-depleting substances (ODS) were used as refrigerants. However, these refrigerants were phased out beginning in the late 1980s, as a result of the Montreal Protocol of 1987 (Hu et al., 2017). As ozone-depleting substances were phased out, they were largely replaced by hydrofluorocarbons (HFCs), which act as powerful greenhouse gases in the atmosphere. Other common contemporary refrigerants include perfluorocarbons, ammonia, carbon dioxide, propane, and isobutane. Although leakage quantities each year are small, these substances may have very high 100-year global warming potentials—making them up to 1000s of times more powerful than CO2 at warming the planet. 

There are eight on-site sources of refrigerant leaks (Table R1). Data about appliances were acquired from equipment SPEC sheets and charge capacity information was provided by the manufacturer. The refrigerants include R290, R134A, and R404A. The age of all but two freezers were known with certainty. The estimated range for the remaining two freezers was five to ten years. Five years of age was assumed to avoid biasing results to the lower end of uncertainty, although the relative impact on total Scope 1 emissions was insignificant in a sensitivity test for age. 
To quantify the global warming impact of fugitive emissions on owned property, our team performed a mass balance of equations according to technical guidelines (IPCC, 2004). In accordance with guidelines for stand-alone commercial applications, a 15% annual loss rate was applied for each year since the appliance was manufactured. The estimated quantity of each refrigerant leaked in each year was converted to CO2 equivalents using global warming potentials on a 100-year time scale.

Methodological weaknesses include lack of measurement and assumptions about leak rates and appliance age. In practice, it is rare for fugitive emissions to be measured.  In the absence of data, we are only able to provide an estimate of Scope 1, with uncertainty around the true value.

Scope 2: Indirect Emissions (Purchased Electricity)

Scope 2 is a category of emissions including those that result from the generation of purchased electricity. Both Scope 1 and 2 are required reporting categories for carbon footprints according to the Greenhouse Gas Protocol. Our team identified purchased electricity as the sole source of Scope 2 emissions for Nada. Purchased emissions tend to vary with local characteristics, such as building efficiency and grid mix.

In Vancouver, BC, the local electricity grid is supplied largely (92%) by hydroelectricity generation. Hydropower is a renewable, low-carbon energy source. The utility company, BC Hydro, reports a market-based emission factor of 11 tonnes CO2e per gigawatt-hour. In addition, the store is located in a LEED Gold Certified building, which meets high performance standards for energy efficiency.
To calculate annual purchased electricity emissions, our team acquired Nada’s monthly utility bills through 2019 and 2020. Using this data, we determined the annual energy consumption of the store. Then, in accordance with carbon foot-printing guidelines, applied the market-based emissions factor to calculate carbon equivalency.
Sources of uncertainty in this methodology include: (1) measurement error, associated with ineffective metering and (2) error associated with the consistency and reliability of the electricity emissions factor. However, because this analysis is rooted in measured data, it is an area of high confidence within the overall carbon footprint.

Scope 3: Value Chain Emissions

Scope 3, or “value chain” emissions include any source of emissions that are pertinent to the business, but do not fall within the company’s direct control. This is not a required reporting category for carbon footprints, but Scope 3 accounting provides insight into the life cycle impacts of the company’s value chain. There are 15 categories within Scope 3, all of which are elective under the Greenhouse Gas Protocol. This analysis of Nada included two categories: of Upstream Transportation and Purchased Goods and Services.

Upstream Transportation & Distribution

Upstream transportation & distribution emissions were defined as greenhouse gases that result from the distribution of purchased goods between Tier 1 suppliers and Nada. Tier 1 suppliers, under our definition, include food distributors. Emissions in this category include those released through transportation-related activities, such as fossil fuel combustion in the engine of a distribution vehicle. Emissions vary depending on the mode of transportation; air transport is generally the most carbon intensive, while marine transport is typically the least carbon intensive option. Other sources of variation include vehicle characteristics and product weight.

In the absence of data about supplier vehicles, shipping weights, and shipping distance, the team relied on a simplified, but consistent, model of upstream transportation. Supplier location data was acquired in part through Nada records, online research, and approximation. When a shipping address was not available, the center of the local township or city was used as a substitute. In the absence of data relating to supplier distribution, shipping distance was estimated using Google Maps to route an efficient path between the supplier and Nada. The distance was recorded as this value in kilometers, and one trip was assumed to be this distance. Shipping weight was approximated per supplier, using the weight of the top product by spend as a proxy. Spend in Canadian dollars was converted to weight using this conversion ratio. Carbon intensity was approximated by the Ecoinvent emission factor for a 2.5-to-16 tonne lorry (0.33 kg CO2e/tonne-kilometer). 

Purchased Goods and Services

The official name of this GHG Protocol emissions category is “Purchased Goods and Services”, which we refer to as Purchased Goods. This category includes the supply chain emissions released into the environment by every process in the production of consumer goods. This includes, for instance, on-farm combustion of fossil fuels or methane released by ruminants.

Order quantities and total expenditures on purchased goods were acquired through the compilation of purchase order invoices for 2019 and 2020. Each product was sorted into a CEDA (Comprehensive Environmental Data Archive) industry category. The sorting process was informed by CEDA meta data descriptions and additional product research. The resulting data, including total expenditures by product category, was used to approximate carbon dioxide equivalency, in kg CO2e.

To prepare the purchased goods data for CEDA GHG emission factors, three price conversions were performed. Expenditures in Canadian dollars were converted to USD using average conversion rates for the appropriate year. The expenditure in USD was then deflated to 2014 prices, as this was the base year for CEDA emission factors. Expenditures for 2019 and 2020 were both deflated using the 2014/2019 deflation ratio provided by the CEDA 5.06 Price Indices table. The 2014 wholesale price was then converted to producer cost with a CEDA industry-specific conversion rate. Finally, life cycle product emissions were estimated using the CEDA emissions factors, which were reported in kilograms per dollar (2014 producer cost) of carbon dioxide equivalents using 100-year global warming potentials.

Food Waste Diversion

Food waste diversion — the practice of preventing food from decomposing in a landfill — is associated with efficient use of resources and avoided emissions.  We adopted an adaptive methodology for comparing different food outcomes at Nada with disposal in landfill. Two food outcomes were observed: (1) incorporation into Café products and (2) composting. Composting is the practice of repurposing food waste through natural decomposition and nutrient recycling. 

To calculate the diverted emissions two analyses were performed, one for Café and one for compost. For Café diversion emissions, the total kg of food that was used by the Café was multiplied by 3 different landfill diversion emission factors, a high, medium and low estimate. Due to the high uncertainty of food waste emissions, we chose to provide 3 different types of scenarios from North American studies (Porter & Reay, 2015). The low estimate emission factor only accounts for food diverted from landfill, but not other external factors such as transport or avoided burden (Hall et al., 2009). The medium emission factor accounts for landfill diversion and all embedded emissions, which was provided by “To Good to Go” (Truelove et al. 2014). The high emissions factor takes an avoided burden approach, accounting for all embedded emissions, diverted from landfill emissions and all emissions from avoided food purchases (Cuéllar & Webber, 2010). These 3 scenarios will provide a range of potential carbon offsets from Nada’s food waste diversion Café program.

To calculate the carbon savings of compost, the total kg of compost from both Nada and the Café was added together and multiplied by EPA emission factors for compost; one for CH4 emitted by compost and one for the carbon savings. The final food diversion emissions were added together to get Nada’s food waste emissions savings in a single year. Due to data management changes over the course of the study period, we were unable to calculate the impact of imperfect and blemished food sales over 2019 and 2020.

Results

Scope 1: Direct Emissions

In the baseline year, 2019, fugitive emissions totaled to 666 kg CO2e. Because of R290’s low global warming potential, its relative impact on overall Scope 1 emissions was less than 0.1% in 2019 (Table R1). Most of the impact (86%) was the result of R404A leakage, which contributed 570 kg CO2e to the footprint in 2019. The relative impact of R134A leakage was lower (14%), at 96 kg CO2e.

Table R1. Scope 1 Emissions at Nada Grocery (2019):  Three refrigerants were identified as contributors to Scope 1 emissions: R290, R134A, and R404A. The majority of appliances (6) use R290 as a refrigerant. Despite contributing a relatively low quantity toward the overall leakage mass, R134A and R404A contributed 14% and 86%, respectively, to the overall climate impact of Scope 1 emissions.

Refrigerant 

No.  of Appliances

100-Year Global warming Potential (GWP 100)

Contribution to 2019 footprint (kg CO2e)

Contribution to 2019 footprint (Share of Scope 1 total)

R290

6

3(Hoornweg et al., 2018)

0.21

< 0.1 %

R134A

1

1,300 (Sisto et al., 2017)

96

14 %

R404A

1

3,922 (Russell, 2014)

570

86 %

TOTAL

8

n/a

666

100 %


In 2020, fugitive emissions decreased by 15% (an artefact of the 15% annual loss rate assumption) to 566 kg CO2e. As the appliances age, their carbon footprint continues to decrease.

Scope 2: Indirect Emissions (Purchased Electricity)

In 2019, purchased electricity emissions totaled 978 kg CO2e and accounted for 0.29% of the total annual footprint. In 2020, Nada’s emissions from purchased electricity decreased by 10.6% from 978 kg to 875 kg CO2e (Table R2).

Table R2. Scope 2 Emissions from Nada Grocery in (2019 & 2020). From 2019 to 2020, Nada’s scope 2 emissions from purchased electricity decreased by 10.6% from 978 kg CO2e to 875 kg CO2e. 

2019 (Baseline)

2020

% change

Purchased electricity emissions (kg CO2e)

978

875

-10.6%


Scope 3: Value Chain Emissions

In 2019, Scope 3’s total emissions were ~319,000 kg CO2e accounting for over 99% of all GHG emissions. Purchased goods and services accounted for over 80% of the emissions, with ~265,000 kg CO2e. Transportation emissions were approximately ~54,000 kg CO2e. The total Scope 3 emission broken down by top 5 contributing subcategories per category are shown in Figure 3. 

In 2020, Scope 3’s total emissions were ~ 250,000 kg CO2e, which was a 27% decrease from 2019. Although Scope 3 emissions decreased from 2019 to 2020, the emission distribution stayed relatively the same. Scope 3 still accounted for 99% of all carbon emissions in 2020. The emission breakdown for 2020 can be found in Figure 4. 

2019 Scope Emissions

Figure 3. 2019’s Scope 3 emissions broken down by the top 5 contributing subgroups per category.
2020 Scope Emissions
Figure 4. 2020’s Scope 3 emissions broken down by the top 5 contributing subgroups per category. 
 

Upstream Transportation

In 2019, Nada purchased products from 106 different vendors, though the emissions from the majority of these vendors were an extremely small percent (<1%) of Nada’s upstream transportation & distribution emissions. For 2019, the total emissions from the Scope 3 category, upstream transportation & distribution were 53,570 kg CO2e. The vendor that contributed the most to Nada’s emissions in this category was ULINE, emitting 31,228 kg CO2e in 2019, and making up about 58% of the total emissions in the upstream transportation & distribution category. The top 5 emitters made up over 80% of the emissions within this category, while the top 10 emitters made up over 90% of the emissions. The top 10 emitters for 2019, ranked in order of emissions were ULINE, Discovery Organics, Dean’s Milkman, Tree Island Gourmet Yogurt, Rehoboth Farm, Left Coast Naturals, Klippers Organics, Nelson Naturals, Brush Naked, and Giddy Yo (Table R3). When normalized to emissions per dollar, ULINE stands alone at 3.54 kgCO2e/CAD, with Tree Island Gourmet Yogurt the next closest at 0.61 kgCO2e/CAD.


In 2020, Nada purchased products from 102 different vendors, again, with the majority of the emissions in upstream transportation & distribution concentrated in the top 10 vendors. In 2020, the total emissions from upstream transportation & distribution were 50,490 kg CO2e. This was about a 6% reduction from the year 2019. The vendor that contributed the most to Nada’s emissions in this category in 2020 was ULINE, the same as in 2019. In 2020, however, ULINE’s emissions in this category actually increased from 31.2 metric tons of CO2e, to 35.5 metric tons of CO2e, about a 12% increase. Their overall percent contribution to this category also increased to just over 70% of the emissions. The top 10 emitters combined for 2020 made up just over 95% of Nada’s total upstream transportation & distribution emissions, while the top 5 made up over 88%. Ranked in order of emissions, the top 10 emitters in this category for 2020 were ULINE, Dean’s Milkman, Tree Island Gourmet Yogurt, Rehoboth Farm, Discovery Organics, Factory Direct Vinegar, Left Coast Naturals, Giddy Yo, A Bread Affair, and Klippers Organics (Table R4). Again, ULINE is by far the most emission intensive supplier when emissions are normalized per CAD, at 2.75 kgCO2e/CAD, while Tree Island Gourmet Yogurt comes in at second again with the same emission intensity from 2019 of 0.61 kgCO2e/CAD.


The top 5 emitters in both 2019 and 2020 remained the same, with a slightly different order after ULINE at the top. The top 10 emitters for both years were also nearly the same with only two changes. In 2020, Factory Direct Vinegar, a vendor Nada did not purchase from in 2019, was the 6th largest contributor to the upstream transportation & distribution emissions, while A Bread Affair came in at 9th, after ranking 22nd in the previous year. The 8th and 9th top emitters in 2019, Nelson’s Naturals and Brush Naked, fell to 16th and 22nd respectively, in 2020. 

Table R3. Top 10 contributors to Upstream Transportation & Distribution emissions in 2019.

Vendor

Metric Tons CO2e

% Contribution

1. ULINE

31.2

58

2. Discovery Organics

3.6

7

3. Dean's Milkman

3.5

6

4. Tree Island Gourmet Yogurt

3.4

6

5. Rehoboth Farm

2.7

5

6. Left Coast Naturals

1.8

3

7. Klippers Organics

1.2

2

8. Nelson's Naturals

0.9

2

9. Brush Naked

0.6

1

10. Giddy Yo

0.6

1


Table R4. Top 10 contributors to Upstream Transportation & Distribution emissions in 2020.

Vendor

Metric Tons CO2e

% Contribution

1. ULINE

35.5

70

2. Dean's Milkman

2.8

5

3. Tree Island Gourmet Yogurt

2.5

5

4. Rehoboth Farm

2.0

4

5. Discovery Organics

1.9

4

6. Factory Direct Vinegar

1.3

3

7. Left Coast Naturals

0.8

2

8. Giddy Yo

0.5

1

9. A Bread Affair

0.4

1

10. Klippers Organics

0.4

1


Purchased Goods and Services

In 2019, Nada’s carbon footprint from purchased goods and services was 265,000 kg CO2e, which accounted for 83% of the total carbon footprint. Among the 36 CEDA categories used, the top five by contribution to total purchased goods and services emissions were:
  • Vegetable and melon farming
  • Fruit and tree nut farming
  • Grain farming
  • Oilseed farming
  • Other crop farming.
The respective emissions for these categories are listed in Table R5. The biggest contributor by far is vegetable and melon farming, which accounted for 31% of the total purchased goods and services emissions in 2019.


In 2020, Nada’s carbon footprint from purchased goods and services dropped to 200,000 kg CO2e, which is 79% of the total carbon footprint. When compared to 2019 purchased goods and services emissions, the 2020 emissions were smaller, but the percentage to the total carbon did not change significantly. Among the 36 CEDA categories used, the top five by contribution to total purchased goods and services emissions remained the same as in 2019. The respective emissions for these categories are listed in Table R6. In 2020, the largest emitting category, vegetable and melon farming, contributed to 30% of the total purchased goods and services emissions.  

Table R5. Scope 3 Purchased Goods & Services (2019): Top 5 product categories in terms of contribution to total footprint. 

Product Category

Category Emissions (kg CO2e)

% of Total Emissions

1. Vegetable and melon farming

82,000

31%

2. Fruit and tree nut farming

45,000

17%

3. Grain farming

38,000

14%

4. Oilseed farming

29,000

11%

5. Other crop farming

19,000

7%

All other categories

52,000

20%

Total purchased goods and services emissions

265,000

 


Table R6. Scope 3 Purchased Goods & Services (2020): Top 5 product categories in terms of contribution to total footprint. 

Product Category

Category Emissions (kg CO2e)

% of Total Emissions

1. Vegetable and melon farming

61,000

30%

2. Fruit and tree nut farming

34,000

17%

3. Grain farming

28,000

14%

4. Oilseed farming

25,000

13%

5. Other crop farming

13,000

6%

All other categories

39,000

20%

Total purchased goods and services emissions

200,000

 


Food Waste Diversion

In 2019, Nada diverted between 4,100 to 12,000 kg CO2e from going to the landfill. Compost emission savings were 750 kg CO2e, while Café emission savings ranged from 3,300 to 11,000 kg CO2e (Table R7). While food waste diversion offset less than 3% of Nada’s total 2019 carbon footprint, food waste diversion completely offset Scope 1 and 2 emissions in all 3 scenarios. Food waste diversion offsets were 2.7 times more than Scope 1 and 2 emissions, shown in Figure 3. Although food waste diversion is small when compared to the carbon footprint as a whole, offsetting Scope 1 and 2 is a great start for food waste diversion programs.

Table R7. Food waste diversion High, Medium, Low estimates (2019).

Café

Compost

Total Emission Savings

High Estimate

11,000

750

11,750

Medium Estimate

5,300

750

6,050

Low Estimate

3,300

750

4,050


In 2020, Nada diverted 11,500 to 36,000 kg CO2e from the landfill. Compost diverted 1,500 kgCO2e from landfill, while the Café ranged from 10,000 to 35,000 kg CO2e diverted (Table R8). 2020 diverted emissions were over 3 times that of 2019 emissions and 5-18 times that of 2020’s Scope 1 and 2 emissions. While there was a large increase in diverted emissions, compared to the entire footprint, food waste offset about 4-14% of emissions. Although not as large of an offset as predicted, these are still extremely valuable savings when looking at the store as a whole. Compared to 2019, there was a large increase in both Café and compost diversion. This increase leads us to believe that more food was being composted or used in the Café in 2020 due to the limitations of the shopping due to COVID-19 safety protocols. Other food waste programs, like discounted damaged goods also stopped due to a shift to online delivery service, which may have led to more imperfect food being used in the Café. All of these could have led to a large increase in compost and Café emission savings.

Table R8. Food waste diversion High, Medium, Low estimates (2020).

Café

Compost

Total Emission Savings

High Estimate

35,000

1,500

36,500

Medium Estimate

16,000

1,500

17,500

Low Estimate

10,000

1,500

11,500


Overall food waste diversion programs, although small compared to Nada’s overall carbon footprint, offset more than Scope 1 and 2 emissions in both years. Food waste diversion programs are a viable way to offset Scope 1 and 2 emissions, as well as some Scope 3 emissions. 

Discussion and Recommendations

The carbon footprint accounting guidelines categorizes a reporting entity’s emissions into Scope 1, 2, and 3 (direct emissions, indirect emissions, and value chain emissions respectively). Although this is a well-established methodology of conducting a carbon footprint, there have been criticisms around the problem of “framing” that arises in all carbon footprint accounting studies. When deciding whether certain emissions fall within or outside of a reporting entity’s boundary, judgements have to be made about ownership, control, and responsibility [v10]. In other words, the setting of an entity’s operational boundaries can be arbitrary and malleable to some extent. It is possible to manipulate the scope in which certain emissions fall. For example, a reporting entity could sell assets and lease them back. In this way, those assets would be outside of the reporting entity’s boundaries, thus moving from direct emissions to value chain emissions. The authors suggested a new approach of framing carbon accounting disclosure. This approach looks at each reporting entity’s business model holistically, and dissects it into mutually-exclusive stakeholder relations that involve carbon emissions. Using this approach, reporting entities would disclose the emissions from each stakeholder relation. The authors argue that this business model approach would increase the visibility of carbon generating relations, and avoid arbitrariness.

Although this criticism for the framing problem is valid and should be further investigated and debated, it does not particularly concern this carbon accounting analysis for Nada. The problem with arbitrariness in setting operational boundaries is that reporting entities could take advantage of the fact that Scope 3 emissions are optional to report, and find loopholes to move certain emissions from Scope 1 to Scope 3. However, in the case of this study, Nada chose to report on the two Scope 3 categories that typically represent the majority of grocery stores’ carbon footprint. Ultimately, Nada’s goal through this study is to increase visibility on which supplier relations and products contribute the most carbon emissions, thus taking the first step to reduce emissions throughout the supply chain by leveraging supplier relations. In this sense, this study is aiming for the same goal as the authors that suggested the business model framing approach.

Our results show that the majority of Nada’s carbon footprint comes from Scope 3, which in both years made up over 99% of the entire carbon footprint. Specifically, upstream transportation represented about 17% in 2019, and 20% in 2020, while purchased goods and services represented about 83% and 79% in 2019 and 2020, respectively. The next logical step would be to reduce emissions from the hotspots. The hotspot for upstream transportation is the supplier ULINE, which contributed 58% and 70% of total upstream transportation emissions in 2019 and 2020, respectively and was by far the most emission intensive supplier on a per dollar basis.

However, sources of uncertainty exist in our methodology for upstream transportation emissions. First, the product weights were not available, and we approximated the weights from each supplier by the product that represented the most spend from Nada. Second, the type of vehicles used by each supplier is unknown; therefore, the emission factors are unknown. We assumed that all transportation trips used the same vehicle (3.5t – 16t lorry, Ecoinvent).

The hotspots for purchased goods and services were the following product categories:
  • Vegetable and melon farming
  • Fruit and tree nut farming
  • Grain farming
  • Oilseed farming
  • Other crop farming
However, our results did not reveal top contributing suppliers for purchased goods and services. This is because our methodology uses the CEDA database, which has information on the average carbon emissions of certain food producing and processing industries, but does not differentiate between suppliers within the same industry. In other words, by using the CEDA database, our study quantified all of the value chain emissions that stem from the production of the food products purchased by Nada. At the same time, our study sacrificed the granularity of differentiating low-carbon suppliers from high-carbon suppliers from the same industry. Therefore, the next logical step for Nada should be to further increase the visibility of emissions that arise from each supplier relation. This means choosing one or more of the top emitting food categories, and working with all the suppliers from those categories to conduct supplier specific carbon accounting studies.

Impacts of local sourcing 

Although Nada sources locally as much as possible, how this impacts their overall emissions and comparing this to a traditional grocery store is difficult. Because our study only looks 1 tier up at the upstream transportation from the distributor to Nada, any comparison to the overall food miles of a traditional grocery store would not be fair. We do know, however, that the majority of Nada’s suppliers are local, which is typically not the case with most large traditional retailers (Wells, 2016). To see the potential impact of sourcing locally, we used average food miles from a study that estimated and compared the distance traveled of locally sourced food and conventionally sourced food (Pirog et al., 2003). In this study, Pirog et al., looked at 16 different types of produce and calculated each item’s food miles based on if it was locally or conventionally sourced. For comparison purposes, we used the farthest distance of a locally grown product to define “local”, which in this case was 75 miles. By this definition, 70% of Nada’s suppliers are local, while 30% are not. To model a store that sources locally, we applied the average local distance (56 miles) from the Pirog et al. study, to all of Nada’s local suppliers, and the average conventional distance (1,494 miles) to all of Nada’s non-local suppliers, and recalculated upstream transportation emissions. To model a conventional grocery store we used the average conventional distance for all of Nada’s suppliers and recalculated the upstream transportation emissions again. When comparing these two models, we found that there was a 94% reduction in upstream transportation emissions when comparing the conventional model to the model based on Nada’s suppliers (Figure 5) Though this is a very rough approximation with many assumptions that may or may not hold true, it shows that under certain circumstances, food miles and local sourcing can have a very large impact on a store’s upstream transportation emissions, with its overall impact dependent on the various other factors mentioned previously. 
Impact of Local Sourcing
Figure 5.  Comparing the upstream transportation emissions using a standardized distance for local and non-local suppliers. Suppliers are considered ‘local’ if they are within 120km of the store. All suppliers who fit this definition were assigned the same distance of 90km. All suppliers who did not were assigned a distance of 2404km. Conventional stores are assumed to be 100% non-local and Nada’s suppliers are 70% local. 

For Nada, we recommend they continue their efforts to source as locally as possible. Given that Nada sources from farmers with sustainable practices and environmentally conscious suppliers, stock relatively few meat items in store, and generate zero food waste, the emissions from the upstream transportation of their products likely contribute a larger overall percentage to their total carbon footprint than it would in a conventional grocery store. It is thus important that Nada continue to source locally, as well as try to find substitutes for those few suppliers who are located farther away, particularly ULINE. For certain products like avocados and bananas, it will be impossible to source locally, so for these products it is important for Nada to source these from responsible farms with sustainable, regenerative practices, and try when possible to have them shipped by ocean freight or rail as opposed to airfreight.  

Implications of food waste diversion

Nada has diverted over 35,000 kg of CO2e between 2019 and 2020 through their Café and compost efforts alone. Although we were not able to quantify the food waste emission savings from donations or the sale of imperfect products to employees and customers, the emission savings from the Café and compost alone were already impactful. Nada’s buying practices can easily be an example to other stores, buying imperfect food at a discount while turning the product into something they were already going to sell. These buying practices are not only lucrative to other stores but make a huge impact on carbon emissions as a whole. The Café is a great example for how to incorporate imperfect foods, damaged items, and other food waste potential products. The Café generates product and profit, while diverting over 75% of potential food waste. Most grocery stores have sigureure brands that are made in house. Nada has found a way to successfully eliminate food waste, while also providing these products at a lower cost to the store. Nada’s Café program is one of the most effective and simplest programs for grocery stores around the world to adopt. By following Nada’s Café model, grocery stores can significantly reduce food waste, while also providing in house items with lower costs.

While compost was a small portion of Nada’s food waste, it is still a viable program that other stores can adopt to divert greenhouse gas emissions produced by food waste. Nada’s compost program has a smaller impact than other grocery stores should expect because the Café diverts as much food waste as it can before going to compost. Nada has demonstrated that composting can be done effectively at a grocery store level. Overall, Nada’s food waste diversion programs are a great blueprint for all other grocery stores on how eliminating all food waste can be achievable.

Nada has the proper systems in place to reduce food waste and the greenhouse gas emissions that inherently come with running a grocery store. The results show that Nada is able to offset their direct emissions with their food waste prevention programs. In the hierarchy of food waste diversion, Nada is successfully performing the top 3 favorable diversion strategies, prevention, reuse, and recycle, while avoiding recovery for energy and disposal altogether (Papargyropoulou et al., 2014). Net savings have the highest potential when prevention, such as Nada’s imperfect or discounted food, and re-use, i.e., the Café, are used (Moult et al., 2018). Although these emission savings may not be a large percentage of Nada’s overall carbon footprint, they do however offset most of the emissions Nada has direct control over. These programs provide a great example to other grocery retailers for ways to reduce food waste that is in their control. Nada could set an example for grocery stores around North America for how to reduce grocery store food waste. 

We recommend that Nada continues their food waste diversion programs, as well as promote the carbon savings the programs produce. By promoting the benefits of the food waste diversion programs, Nada could influence both their customers and suppliers to implement similar programs. The European Commission has reported that retailers like Nada have a growing influence both up and downstream of the supply chain. Nada has the unique opportunity to influence suppliers and consumers about food waste through education and sharing of their different food waste diversion programs. Nada has proven that their food waste programs are a viable way to divert emissions and has a great opportunity to expand its influence beyond the building doors.

Implications of Products Mix

As a result of our literature review and our understanding that different foods have varying carbon emissions, we made the decision to look at Nada’s purchased goods and services to see how the product mix that they sourced and sold in their stores impacted their emissions. When we broke down the emissions by the products they sourced we see that the majority come from vegetable and melon farming, fruit and tree nut farming, oilseed farming and grain farming. Nada is a unique grocery store that already carries a product mix in their store that promotes a plant-based low carbon-intense diet and doesn’t carry many animal products.

 Top 5 Categories By Spend

Figure 6. Nada sources and carries a selection of foods that are lower in greenhouse gas emissions. A majority of their spend goes to produce, snack foods, and nuts. 

In order to see how this compared to a conventional grocery store, we performed a back of the envelope calculation to see how the carbon emissions from Nada’s product mix compared to the emissions from a conventional grocery store’s product mix. Using data from literature that showed the breakdown of what product categories conventional grocery stores carry (i.e. the percent of meat, dairy, produce), we calculated the carbon footprint of a conventional grocery store using Ceda categories and applying the percent breakdowns to those categories (FMI, 2020). We performed the same analysis using the percent breakdown of products that Nada sold in their store in 2020. We found that Nada’s carbon footprint from products carried was 36% lower than the carbon footprint of a conventional grocery store. This implies that Nada’s efforts to source and sell an intentional product mix has been effective in lowering their carbon footprint. 

Conventional Grocery Stores vs. Nada

Figure 7. Nada releases 36% less carbon emissions to the atmosphere than a conventional grocery store when comparing the product mix that each store carries and offers to their customers. This only represents the carbon emissions associated with the percent of food categories that each store carries. 

We recommend that Nada continue to source and offer an intentional product mix to consumers as it is one way Nada has lowered carbon emissions involved in food production. Through their continued efforts, Nada can influence upstream suppliers through product choices as well as downstream consumers through offering a specific product mix and education around why this is important. However uncertainty around consumer buying patterns and behavior pose issues for the problem of additionality; where carbon emissions are just shifted to a different area but not reduced globally. We don’t know if consumers are going to other stores to purchase their meat and more carbon intensive products. There is space for Nada to improve their communication to consumers about the “why” behind their sourcing decisions and in turn change consumer behavior to make purchasing decisions with the environmental impacts of foods in mind. 

This comparison between Nada and a conventional grocery’s store product mix can also be used to inform other grocery stores of the reductions in carbon emissions they can produce with changes in the product mix that they offer. Although doing an exact comparison does pose issues because there are differences in the business model, supply chain, and operations of a conventional grocery store and Nada, the product mix that Nada sources can be used as a model for other grocery stores as a high level framework for conventional grocery stores. With this hypothetical comparison we can imagine the potential reductions in carbon emissions that could occur as a result of conventional grocery stores offering a product mix to consumers that focuses on foods with lower carbon footprints. 

Implications of Supplier Selection

This study reveals the food categories that contribute the most carbon emissions in Nada’s supply chain. However, currently Nada is unable to reduce the carbon footprint from those categories by choosing the least carbon intensive suppliers, as this requires data on the carbon footprint of individual suppliers. Therefore, the next logical step in reducing the carbon footprint of Nada’s purchased goods and services is to engage with suppliers and acquire supplier-specific data. This is a challenging task for Nada, because in the past suppliers have been reluctant to respond to surveys. This could be caused by a number of reasons. Suppliers might fear that Nada will no longer source from them if they disclose carbon footprint information; or suppliers could simply lack the know-how to quantify their carbon footprint. Although it is unknown what caused the reluctance, Nada should take precautions when engaging suppliers, minimizing any conceivable difficulty or fear of the suppliers. 

As a general strategy, we recommend Nada work with the current suppliers and encourage them to adopt farming practices that minimize the use of nitrogen fertilizers; and make it convenient for suppliers to quantify their own carbon footprint by only asking for specific, easy to acquire information, such as the quantity/type of fertilizers used and the acreage of land fertilized. 

Conclusion

With climate change looming as the global population continues to grow, and the demand for food continues to rise, it is crucial that we find ways to reduce the emissions associated with the food system. For most people, grocery stores are the vehicle that connects people to their food. Grocery stores thus play a crucial role in transforming the food system, and have a unique opportunity to better connect people to their food and help them make more sustainable food choices.


This study quantified the carbon footprint of Nada in 2019 and 2020. The emissions emitted from Nada from refrigerant leakage, purchased electricity, upstream transportation and purchased goods & services, are reported. The emission reduction through Nada’s food waste diversion program is also quantified. We found that upstream transportation and purchased goods & services contributed the majority of the entire carbon footprint, and that the emission reduction from food waste diversion was larger than Nada’s emissions from refrigerant leakage and purchased electricity combined, in both 2019 and 2020.

Recommendations:
  • Acquire supplier specific data on emission factors and work with suppliers to implement data tracking practices and low carbon growing practices. 
  • Continue to prioritize local sourcing; when not feasible ship via ocean freight or rail as opposed to airfreight
  • Continue their current food waste diversion strategies and share them with other grocery retailers and educate customers of the savings.
  • Prioritize offering a product mix that is composed of foods with low carbon emissions and include education to customers about why this reduces carbon emissions. 
Through our analysis on Nada’s operations and initiatives, we found that Nada has a lower carbon footprint because of programs they have in place such as food waste diversion strategies and sourcing specific, low-carbon products from local suppliers. Nada has been successful in influencing and educating upstream suppliers as well as downstream consumers on environmental and social issues. As a B Corporation and mission-driven company, Nada has made it part of their business model to prioritize these issues and created a business where these areas can be prioritized. Nada can continue to improve on their mission through engaging with suppliers and acquiring supplier specific information from their top suppliers to gain a better understanding of their carbon footprint as well as collaborate with the suppliers to implement best farming practices that promote the best environmental and social outcomes. 

However the successes and recommendations for Nada can have larger implications than just improving Nada’s own carbon footprint. Although there are fundamental differences between Nada and conventional grocery stores, the strategies developed in this report can be applied as a framework for other grocery stores to inform decision making and potential goals to reduce the magnitude of impact the food system has on climate change.  

References

Amazon Sustainability. (2021). All in: staying the course on our commitment to sustainability. 


Allwood, J.M., Bosetti, V., Dubash, N.K., Gómez-Echeverri, L., and von Stechow, C. (2014) Glossary. In Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R.] 


Avetisyan, M., Hertel, T., & Sampson, G. (2014). Is local food more environmentally friendly? The GHG emissions impacts of consuming imported versus domestically produced food. Environmental and Resource Economics58(3), 415-462.


Bajpai, P. (2018). Fugitive Emissions and Valve Stem Packing. In Biermann's Handbook of Pulp and Paper (Third Edition)


BC Hydro. (2021). BCHydro Power Smart. 


BC Hydro (2015). Generation type, rates & CO2 emissions. BCHydro Power Smart. 


Cefic, E. C. T. A. (2011). Guidelines for measuring and managing CO2 emission from freight  transport operations. Cefic Report, 1(2011), 1-18.


Clune, S., Crossin, E., & Verghese, K. (2017). Systematic review of greenhouse gas emissions for different fresh food categories. Journal of Cleaner Production140, 766-783.

Craig, A. J., Blanco, E. E., & Sheffi, Y. (2012). A supply chain view of product carbon footprints: results from the banana supply chain. Massachusetts Institute of Technology: Engineering Systems Division Working Paper Series. 


Cue ́llar, A.D., Webber, M.E. (2010). Wasted Food, Wasted Energy: The Embedded Energy in Food Waste in the United States. Environmental Science & Technology, 44(16), 6464–6469.


European Commission. (2013). Sustainable Food – Environment – European Commission. 


Electricity facts. (2020). Government of Canada. 


Elf, P., Gatersleben, B., & Christie, I. (2019). Facilitating positive spillover effects: New insights from a mixed-methods approach exploring factors enabling people to live more sustainable lifestyles. Frontiers in psychology9, 2699.


Ettinger, J., Walton, P., Painter, J., & DiBlasi, T. (2021). Climate of hope or doom and gloom? Testing the climate change hope vs. fear communications debate through online videos. Climatic Change164(1), 1-19.


Feeding America. (2021). How we fight food waste in the US. 


Frischknecht R., Jungbluth N., Althaus H.-J., Doka G., Dones R., Heck T., Hellweg S., Hischier R., Nemecek T., Rebitzer G. and Spielmann M., 2005, The ecoinvent database: Overview and methodological framework, International Journal of Life Cycle Assessment 10, 3–9.


Füssel, H. M. (2010). How inequitable is the global distribution of responsibility, capability, and vulnerability to climate change: A comprehensive indicator-based assessment. Global Environmental Change20(4), 597-611.


Garnett, T. (2011). Where are the best opportunities for reducing greenhouse gas emissions in the food system (including the food chain)? Food policy36, S23-S32.


Geyer, R., Jambeck, J. R., & Law, K. L. (2017). Production, use, and fate of all plastics ever made. Science advances3(7).


Government of Canada. (2020) Canada’s 4th Biennial Report to the United Nations Framework Convention on Climate Change (UNFCCC). Environment and Climate Change Canada. 


Government of Canada. (2020). Putting a price on pollution: Carbon pollution pricing systems across Canada. 


Hall, K.D., Guo, J., Dore, M., Chow, C.C., (2009) The Progressive Increase of Food Waste in America and its Environmental Impact. PLoS One, 4(11), e7940. 


Hartmann-Boyce, J., Bianchi, F., Piernas, C., Riches, S. P., Frie, K., Nourse, R., & Jebb, S. A. (2018). Grocery store interventions to change food purchasing behaviors: a systematic review of randomized controlled trials. The American journal of clinical nutrition, 107(6), 1004-1016.


Hernandez, J. (2020). “B.C. approves civic bylaws banning single-use plastics, provincewide bans on the way.”  CBC Radio-Canada. 


Hill, H. (2008). Food miles: Background and marketing (pp. 1-12). Attra.


Hoornweg, D., & Bhada-Tata, P. (2018). What a Waste: A Global Review of Solid Waste Management. Urban development series;knowledge papers no. 15. World Bank, Washington, DC. 


Hu, L., Montzka, S. A., Lehman, S. J., Godwin, D. S., Miller, B. R., Andrews, A. E., ... & Tans, P. P. (2017). Considerable contribution of the Montreal Protocol to declining greenhouse gas emissions from the United States. Geophysical Research Letters, 44(15), 8075-8083.


Humbert, S., Rossi, V., Margni, M., Jolliet, O., & Loerincik, Y. (2009). Life cycle assessment of two baby food packaging alternatives: glass jars vs. plastic pots. The International Journal of Life Cycle Assessment, 14(2), 95-106.


IPCC, 2018: Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [V. Masson-Delmotte, P. Zhai, H. O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. 


IPCC, 2004: IPCC/TEAP Special Report: Safeguarding the Ozone Layer and the Global Climate System: Refrigeration [Devotta, S., Sicars, S., Agarwal, R., Anderson, J., Bivens, D., Colbourne, D., Hundy, G., König, H., Lundqvist, P., McInerney, E., Nekså, P., El-Talouny, A., Calvo, E., Elgizouli, I.]. 
Kweku, D. W., Bismark, O., Maxwell, A., Desmond, K. A., Danso, K. B., Oti-Mensah, E. A., ... & Adormaa, B. B. (2017). Greenhouse effect: greenhouse gases and their impact on global warming. Journal of Scientific research and reports, 1-9.


Lee-Anderson, S. (2019). Making the case for a zero plastic waste economy: Canada moves to ban single-use plastics in an effort to reduce plastic pollution. In Canadian ERA Perspectives: Developments in Environmental, Regulatory, and Aboriginal Law


Mbow, C., Rosenzweig, C., Barioni, L. G., Benton, T. G., Herrero, M., Krishnapillai, M., & Waha, K. (2019). Chapter 5: food security. IPCC Special Report on Climate Change and Land. 


Montgomery, D. R. (2020). Soil health and the revolutionary potential of Conservation Agriculture. In Rethinking Food and Agriculture (pp. 219-229). Woodhead Publishing.


Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J. B. R. Matthews, Y. Chen, X. Zhou, M. I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, T. Waterfield (eds.)]. In Press.


Moult, J.A., Allan, S.R., Hewitt, C.N., Berners-Lee, M. (2018) Greenhouse gas emissions of food waste disposal options for UK retailers. Food Policy, 77, 50-58.


Naidoo, M., & Gasparatos, A. (2018). Corporate environmental sustainability in the retail sector: Drivers, strategies and performance measurement. Journal of Cleaner Production, 203, 125-142.


Naturvårdsverket. (2013) Food Waste Volumes in Sweden. Swedish Environmental Protection Agency, Stockholm. 


Papargyropoulou, E., Lozano, R., Steinberger, J.K., Wright, N., Ujang, Z. (2014) The food waste hierarchy as a framework for the management of food surplus and food waste. Journal of Cleaner Production, 76, 106-115.


Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.


Pirog, R. S., & Benjamin, A. (2003). Checking the food odometer: Comparing food miles for local versus conventional produce sales to Iowa institutions.


Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987-992.


Port, S. D., and Reay, D. S. (2015). Addressing Food Supply Chain and Composition Inefficiencies: Potential for Climate Change Mitigation. Regional Environmental Change, 16(8). 


Progressive Grocer’s 72nd Annual Consumer Expenditures Study (CES):July 2019, pp. 22-38. See Progressive Grocer for full understanding of study methodology. Due to changes in reporting, there may not be direct comparisons to data from previous years. * Note: percentages derived by FMI from category sales figures and grand total figure published by Progressive Grocer. Percentages may not add to 100 due to rounding. Key Industry Facts – Prepared by FMI Information Service, January 2020


Quest Resource Management Group. (2021). Food waste statistic, the reality of food waste. 


Ranganathan, J., Vennard, D., Waite, R., Dumas, P., Lipinski, B., Searchinger. (2016). Shifting Diets for a Sustainable Food Future: Creating a Sustainable Food Future, Installment Eleven. World Resources Institute.


Reckien, D., Creutzig, F., Fernandez, B., Lwasa, S., Tovar-Restrepo, M., McEvoy, D., & Satterthwaite, D. (2017). Climate change, equity and the Sustainable Development Goals: an urban perspective. Environment and Urbanization29(1), 159-182.


Ritchie, H. (2020, January 24). You want to reduce the carbon footprint of your food? Focus on what you eat, not whether your food is local. Our World in Data. 


Russell, D. A. (2014). Sustainable (food) packaging–an overview. Food additives & contaminants: Part A31(3), 396-401.


Scholz, K., Eriksson, M., & Strid, I. (2015). Carbon footprint of supermarket food waste. Resources, Conservation and Recycling, 94, 56-65.


Saunders, C. M., Barber, A., & Taylor, G. J. (2006). Food miles-comparative energy/emissions performance of New Zealand's agriculture industry.


Seelig, M. I., Millette, D., Zhou, C., & Huang, J. (2019). A new culture of advocacy: An exploratory analysis of social activism on the web and social media. Atlantic Journal of Communication27(1), 15-29.


Silva, A. L. P., Prata, J. C., Walker, T. R., Campos, D., Duarte, A. C., Soares, A. M., ... & Rocha-Santos, T. (2020). Rethinking and optimising plastic waste management under COVID-19 pandemic: Policy solutions based on redesign and reduction of single-use plastics and personal protective equipment. Science of the Total Environment, 742, 140565.


Sim, S., Barry, M., Clift, R., & Cowell, S. J. (2007). The relative importance of transport in determining an appropriate sustainability strategy for food sourcing. The International Journal of Life Cycle Assessment12(6), 422-431.


Sisto, R., Sica, E., Lombardi, M., & Prosperi, M. (2017). Organic fraction of municipal solid waste valorisation in southern Italy: the stakeholders' contribution to a long-term strategy definition. Journal of Cleaner Production, 168, 302-310.


Suh, S. (2005). Comprehensive Environmental Data Archive (CEDA) 5.0. User's Guide. Institute of Environmental Science (CML), Leiden University, Leiden, The Netherlands.


The Government of British Columbia. (2020). British Columbia's Carbon Tax. 
Tilman, D. (1999). Global environmental impacts of agricultural expansion: the need for sustainable and efficient practices. Proceedings of the National Academy of Sciences, 96(11), 5995-6000.


Tilman, D., & Clark, M. (2015). Food, agriculture & the environment: can we feed the world & save the earth?. Daedalus, 144(4), 8-23.


Tilman, D., & Clark, M. (2014). Global diets link environmental sustainability and human health. Nature, 515(7528), 518-522


Truelove, H. B., Carrico, A. R., Weber, E. U., Raimi, K. T., & Vandenbergh, M. P. (2014). Positive and negative spillover of pro-environmental behavior: An integrative review and theoretical framework. Global Environmental Change29, 127-138. 


United Nations. (2015). Transforming our world: the 2030 Agenda for Sustainable Development


UNFCCC (2021). The Paris Agreement. United Nations Climate Change. 


United States Environmental Protection Agency, The Center for Corporate Climate Leadership. (2014). Greenhouse gas inventory guidance: Direct fugitive emissions from refrigeration, air conditioning, fire suppression, and industrial gases


United States Environmental Protection Agency, Office of Land and Emergency Management. (2017). "Containers and packaging: Product-specific data". 


United States Environmental Protection Agency. (2020, June 9). Greenhouse Gases at EPA. 


Veleva, V., Bodkin, G., & Todorova, S. (2017). The need for better measurement and employee engagement to advance a circular economy: Lessons from Biogen’s “zero waste” journey. Journal of Cleaner Production, 154, 517-529.


Volvo Cars. (2021, March 2). Volvo cars to be fully electric by 2030. Volvo Car USA. 

 


Weber, C. L. & Matthews, H. S. (2008). Food-miles and the relative climate impacts of food choices in the United States.


Wells, J.  (2017, April 2016). Growing pains: Why supermarkets are struggling to source local products. Grocery Dive.


Wikström, F., Williams, H., Verghese, K., & Clune, S. (2014). The influence of packaging attributes on consumer behaviour in food-packaging life cycle assessment studies-a neglected topic. Journal of Cleaner Production, 73, 100-108.


Williams, H., Wikstrom, F., Otterbring, T., Lofgren, M., Gustafsson, A. (2012). Reasons for household food waste with special attention to packaging. Journal of Cleaner Production 24, 141-148. 


WRI. (2004). GHG protocol corporate accounting and reporting standard. World Resources Institute and World Business Council for Sustainable Development  

For the full report, visit the UCSB Bren School of Environmental Science & Management website.