We developed a physically-based environmental account of US food production systems and integrated these data into the environmental-input-output life cycle assessment (EIO-LCA) model. The extended ...model was used to characterize the food, energy, and water (FEW) intensities of every US economic sector. The model was then applied to every Bureau of Economic Analysis metropolitan statistical area (MSA) to determine their FEW usages. The extended EIO-LCA model can determine the water resource use (kGal), energy resource use (TJ), and food resource use in units of mass (kg) or energy content (kcal) of any economic activity within the United States. We analyzed every economic sector to determine its FEW intensities per dollar of economic output. This data was applied to each of the 382 MSAs to determine their total and per dollar of GDP FEW usages by allocating MSA economic production to the corresponding FEW intensities of US economic sectors. Additionally, a longitudinal study was performed for the Los Angeles-Long Beach-Anaheim, CA, metropolitan statistical area to examine trends from this singular MSA and compare it to the overall results. Results show a strong correlation between GDP and energy use, and between food and water use across MSAs. There is also a correlation between GDP and greenhouse gas emissions. The longitudinal study indicates that these correlations can shift alongside a shifting industrial composition. Comparing MSAs on a per GDP basis reveals that central and southern California tend to be more resource intensive than many other parts of the country, while much of Florida has abnormally low resource requirements. Results of this study enable a more complete understanding of food, energy, and water as key ingredients to a functioning economy. With the addition of the food data to the EIO-LCA framework, researchers will be able to better study the food-energy-water nexus and gain insight into how these three vital resources are interconnected. Applying this extended model to MSAs has demonstrated that all three resources are important to a MSA's vitality, though the exact proportion of each resource may differ across urban areas.
To respond to anthropogenic effects on the global climate system, higher education institutions are assessing and aiming to reduce their greenhouse gas emissions. The objective of this paper was to ...evaluate the carbon footprint of Clemson University’s campus using a streamlined life cycle assessment approach. The carbon footprint sets a baseline for source specific evaluation and future mitigation efforts at Clemson University. Greenhouse gas emission sources presented in this carbon footprint include steam generation, refrigerants, electricity generation, electricity life cycle, various forms of transportation, wastewater treatment, and paper usage. This case study describes the approach used to quantify each greenhouse gas emission source, and discusses data assumptions and life cycles phases included to improve carbon footprint comparison with other higher education institutions. Results show that Clemson University’s carbon footprint for 2014 is approximately 95,000 metric tons CO2-equivalent, and 4.4 metric tons CO2-equivalent per student. Scope 1 emissions accounted for about 19% of the carbon footprint, while Scope 2 and 3 emissions each contributed nearly 41%. The largest sources of greenhouse gas emissions were electricity generation (41%), automotive commuting (18%), and steam generation (16%). Electricity generation from coal was 29% of the electricity generation resource mix and accounted for three-quarters of Clemson University’s GHG emissions associated with electricity.
•A case study of Clemson University presents a streamlined life cycle assessment approach to quantify the campus’s carbon footprint.•Life cycle phases and data assumptions for each greenhouse gas emission source are discussed to provide a basis for comparison to other higher education institutions.•Scope 1 emissions accounted for about 19% of the carbon footprint, while Scope 2 and 3 emissions each contributed nearly 41% to the carbon footprint.•Applying the electricity provider’s specific electricity generation resource mix has a significant impact on the final carbon footprint.
Greenhouse gas (GHG) inventories have become a popular means for colleges and universities to better understand their environmental impact and quantify sustainability efforts. Clemson University is ...one of the many institutions that signed the American College & University Presidents Climate Commitment, which explicitly calls for a comprehensive inventory of GHG emissions to be created. In the past, Clemson University has contracted an external consulting firm to quantify Clemson’s GHG emissions, however, a transparent method of calculating emissions is needed. Carbon footprinting is an effective method to measure GHG emissions, and carbon footprinting of higher education institutions is currently an underdeveloped research area. As a contribution to efforts on the subject, this research presents the carbon footprint for Clemson University’s main campus. This footprint was built using a consumption-based, hybrid life cycle assessment approach and included scope 1 (direct), 2 (indirect from electricity), and 3 (other indirect) GHG emissions. The scope 1 emissions include steam generation, refrigerant usage, univeristy owned vehicles, univeristy owned aircraft, fertilizer application, and wastewater treatment. Scope 2 is electricity generation. Then, scope 3 includes electricity life cycle, transmission and distibution losses, commuting, univeristy related travel, paper usage, waste and recycling transportation, wastewater treatment chemicals, and water treatment. The total carbon footprint of Clemson University’s main campus in 2014 was calculated to be 95,000 metric tons CO2-e, sources of uncertainty include data quality and the streamlined life cycle assessment approach. This research found that 49% of GHG emissions were from electricity related activities, while fossil fuel dependent activities such as automotive commuting (18%), steam generation (16%), and university related travel (13%) added significantly to the footprint. Overall, creating a reproducible baseline carbon footprint can be used to compare Clemson against other higher education institutions, while helping develop goals, strategies, and policies to reduce emissions. The high emissions related to electricity could be decreased through increased renewable energy sourcing. Therefore, as a further component of this research, LiDAR data was utilized in GIS to demonstrate campus rooftop photovoltaic potential.
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