Modelling Local Food Policy and Greenhouse Gas Emission Due to Transportation

Abstract

(ProQuest: ... denotes formulae omitted.)1.IntroductionLocal food advocates assert many attributes of food that span sociological, health, safety, quality, economic and environmental considerations (Feenstra, 1997; Weatherell et al., 2003; Zepeda and Leviten-Reid, 2004; Roininen et al., 2006; Feagan, 2007; Darby et al., 2008; Kemp et al., 2010; Martinez et al., 2010). As the academic community increasingly tests these ideas, this article explores the assertion that food systems generate greenhouse gas savings compared to conventional food systems that make up mainstream food value chains. More specifically, this study looks at the current methods for modeling and accounting for greenhouse gasses generated in the transportation of food throughout the value chain when comparing food systems (LFS) to conventional food systems (CFS) and proposes a framework that is readily accessible to regional economists.A food system, as defined here, entails the entire chain from production to consumption. A LFS is one that is further defined by geographic proximity. Though no clear consensus exists on what constitutes food (Hand and Martinez, 2010; Martinez et al., 2010), the concept of local entails the notion of closer geographic connections between producers and sellers. For those advocating environmental attributes of foods, the shortened travel distance is a key basis of positive environmental outcomes of food (Pirog et al., 2001). For the proponents of LFS, the overtness of shorter travel distance is sufficient in proclaiming that food generates less transit-related greenhouse gas (GHG) than conventional foods (Edwards-Jones et al., 2008; Weber and Matthews, 2008; Coley et al., 2009). In light of increasing public scrutiny of anthropogenic contributions to climate change, policies pursuing reduced CO2 emissions, such as food promotion, will likely become more common. As such, tools for gauging environmental outcomes of policy direction are needed. For regional or sub-national policy considerations, few tools exist for guiding policy.In this study and in related studies (Martinez et al., 2010; Low et al., 2015), differences in food miles delineate LFS and CFS. Hence, the method of estimation and inclusiveness of food miles is of paramount importance in estimating the GHG generation. While some food system studies have gone beyond transportation as the sole source of GHG to encompass processing and storage (Van Hauwermeiren et al., 2007), or even production (Meisterling et al., 2009), others have limited consideration to transportation miles (Pirog et al., 2001; Wallgren, 2006; Weber and Matthews, 2008). This study follows the treatment of food miles in calculations of GHG emissions across LFS and CFS and highlights the role of accounting for food miles.There is no single source for estimating the distances food travels from producer to consumer that also takes into account stops along the way for processing, warehousing and distribution. Limited resources for measuring comparative food miles has resulted in widely varying estimates that can range between one- and two-thousand miles, depending on methods used in estimation and food commodities measured (Hendrickson, 1996; Pirog et al., 2001; Weber and Matthews, 2008). The modes and relative energy efficiency of transportation modes is also an important consideration (Meisterling et al., 2009), as efficiencies can be gained from long-haul trucks or trains that may offset long travel distance GHG generation from less-efficient delivery modes. That is, studies that assume that LFS miles generate the same carbon emissions per mile as CFS miles may overstate the GHG savings of LFS if those miles are less fuel-efficient than CFS miles. For example, the Transportation Research Board (2010) estimates that the typical fuel consumption of a Class 2 truck (pickup, or mid-sized utility truck) is nearly six times higher per ton-mile than a Class 8 combination truck. …