2013
DOI: 10.1016/j.enpol.2013.06.014
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An exploration of residents’ low-carbon awareness and behavior in Tianjin, China

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Cited by 105 publications
(57 citation statements)
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“…The sample members reported some private behaviors, such as using chopsticks more than once and using public transit or walking for travel, but discussing pro-environmental topics with others or participating in pro-environmental activities was less likely to be reported. Bai and Liu (2013) pointed out that the reason for this difference is likely China's long-term neglect of lowcarbon development in its context that prioritizes economic development. Low-carbon development has lacked attention and importance, and opportunities for pro-environmental behaviors have been limited.…”
Section: Discussionmentioning
confidence: 99%
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“…The sample members reported some private behaviors, such as using chopsticks more than once and using public transit or walking for travel, but discussing pro-environmental topics with others or participating in pro-environmental activities was less likely to be reported. Bai and Liu (2013) pointed out that the reason for this difference is likely China's long-term neglect of lowcarbon development in its context that prioritizes economic development. Low-carbon development has lacked attention and importance, and opportunities for pro-environmental behaviors have been limited.…”
Section: Discussionmentioning
confidence: 99%
“…Low-carbon development has lacked attention and importance, and opportunities for pro-environmental behaviors have been limited. Bai and Liu (2013) concluded that it has been difficult for people to commit to public pro-environmental behaviors. Similarly, a lack of propaganda on low-carbon and pro-environmental development relates to the lack of pro-environmental awareness, which is increasingly considered the reason for the lack of pro-environmental behaviors.…”
Section: Discussionmentioning
confidence: 99%
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“…In order to find out the impacts of socio-economic factors on household CO 2 emissions, many variables, such as population, affluence, energy intensity, the urbanization level, employment rate, and the share of the tertiary industry, are considered. A large amount of research has shown that household energy requirements, carbon emissions and carbon footprint are closely related to income [42], level of education [43], age [36], gender [38], occupation [14], household size [44], urbanization [45], car ownership [43], urban density [46,47], consumption patterns [48,49], and imports [50]. Different methods, such as index decomposition analysis (IDA) [51], logarithmic mean Divisia index (LMDI) [52], and Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT)model [53,54] were adopted.…”
Section: Introductionmentioning
confidence: 99%