TY - JOUR
T1 - Apples to kangaroos
T2 - A framework for developing internationally comparable carbon emission factors for crop and livestock products
AU - Hawkins, Jacob
AU - Ma, Chunbo
AU - Schilizzi, Steven
AU - Zhang, Fan
PY - 2016/12/15
Y1 - 2016/12/15
N2 - Consumption-based greenhouse gas accounting, which encompasses emissions from a nation's domestic final consumption as well as emissions embodied in imports, is gaining favor in the climate change literature for its effectiveness and consideration of equity. Unfortunately, the calculation of emissions embodied in the trade of agricultural food products is hindered by a lack of consistent and comparable emission factors. Food import quantities for every country are readily available through the United Nations Food and Agriculture Organization. Unfortunately, the carbon emission factors necessary to calculate the embodied emissions in imported foods are largely unavailable or unreliable for many countries. On top of this, different methodologies for determining carbon emission factors provide varying estimates based on different assumptions. The differences in these assumptions and methodologies can mean that attempts to compare and combine emissions based on factors from different countries become less of a comparison of apples-to-apples and more of an apples-to-oranges or even apples-to-kangaroos exercise. This study proposes a method to combine the Food and Agriculture Organization's available greenhouse gas data, production data, and agricultural yields and scaling it against benchmarks in the literature to estimate a time-series of crop and livestock carbon emission factors that are internally consistent within the Food and Agriculture Organization's data set and comparable from nation to nation. The framework provided is then used to produce a sample set of carbon emission factors for Chinese agricultural import suppliers to determine the embodied greenhouse gases in China's food imports.
AB - Consumption-based greenhouse gas accounting, which encompasses emissions from a nation's domestic final consumption as well as emissions embodied in imports, is gaining favor in the climate change literature for its effectiveness and consideration of equity. Unfortunately, the calculation of emissions embodied in the trade of agricultural food products is hindered by a lack of consistent and comparable emission factors. Food import quantities for every country are readily available through the United Nations Food and Agriculture Organization. Unfortunately, the carbon emission factors necessary to calculate the embodied emissions in imported foods are largely unavailable or unreliable for many countries. On top of this, different methodologies for determining carbon emission factors provide varying estimates based on different assumptions. The differences in these assumptions and methodologies can mean that attempts to compare and combine emissions based on factors from different countries become less of a comparison of apples-to-apples and more of an apples-to-oranges or even apples-to-kangaroos exercise. This study proposes a method to combine the Food and Agriculture Organization's available greenhouse gas data, production data, and agricultural yields and scaling it against benchmarks in the literature to estimate a time-series of crop and livestock carbon emission factors that are internally consistent within the Food and Agriculture Organization's data set and comparable from nation to nation. The framework provided is then used to produce a sample set of carbon emission factors for Chinese agricultural import suppliers to determine the embodied greenhouse gases in China's food imports.
KW - Agriculture
KW - Carbon emission factor
KW - China
KW - Consumption-based accounting
KW - Embodied emission
UR - http://www.scopus.com/inward/record.url?scp=84995387436&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2016.08.060
DO - 10.1016/j.jclepro.2016.08.060
M3 - Article
AN - SCOPUS:84995387436
SN - 0959-6526
VL - 139
SP - 460
EP - 472
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
ER -