Abstract
As the threat posed by global climate change becomes more acute, action must be taken to mitigate carbon emission. Carbon
footprint, as a widely used term and concept, is increasingly being recognized as a valuable indicator in the field of GHG and
carbon emissions management. However, few attempts have been made to investigate precise relationship between carbon
footprint and influential factors. In this paper, STIRPAT model was employed to reveal the dynamic relationships between
carbon footprint and influential factors by means of the ridge regression for a case study of Wuhan city, Hubei province in central
China. The results are as follows: (1) Carbon footprint for energy consumption has increased from 188.46 ten thousands hm2 in
1995 to 331.50 ten thousands hm2 in 2009, which of the annual average growth rate was 4.12%. (2) Coal consumption accounted
for the largest share in carbon footprint for energy consumption. Petroleum and natural gas consumption showed fluctuating
trend. (3) According to STIRPAT model, population and economic development were the main influential factors of carbon
footprint for energy consumption. 1% increase of population has resulted in 3.229% increase in carbon footprint for energy
consumption, and 1% increase of per capita GDP in 0.261%. (4) The relationship between per capita GDP and carbon footprint
for energy consumption did not prove the environmental Kuznets curve (EKC). (5) Comparing with other provincial cities in
China, the per capita carbon footprint in Wuhan city is lower than Beijing, Shanghai, Tianjin, while much more than Chongqing
city.