With food supply chains contributing to 26% of global greenhouse gas emissions, there is increased focus on decreasing the GHG emissions in an economically viable manner. Existing methods involve carrying out life cycle analysis (LCA) of the product using emissions factors from databases. While this is a scalable approach, there are limitations in terms of accuracy and emissions factors being averages and not being current. We address these limitations by proposing a framework that includes a suite of tools such as satellite data, physical models, static, and LCA tools to estimate the GHG emissions. Further, the framework jointly optimizes GHG emissions and costs while selecting suppliers and routes. We illustrate the working of this framework using a global pizza supply chain and present the sustainability-cost trade offs during supplier and route selection.