How scholars and the public perceive a “low carbon city” in China
China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cai, Bofeng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: Self-assembled 3D hierarchical MnCO - Rajendiran, Rajmohan ELSEVIER, 2020, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:149 ; year:2017 ; day:15 ; month:04 ; pages:502-510 ; extent:9 |
| Links: |
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| DOI / URN: |
10.1016/j.jclepro.2017.02.122 |
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ELV015327108 |
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| 520 | |a China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. | ||
| 520 | |a China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. | ||
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10.1016/j.jclepro.2017.02.122 doi GBV00000000000377.pica (DE-627)ELV015327108 (ELSEVIER)S0959-6526(17)30345-1 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Cai, Bofeng verfasserin aut How scholars and the public perceive a “low carbon city” in China 2017transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. Scholar Elsevier China Elsevier Perception Elsevier Public Elsevier Low-carbon city Elsevier Geng, Yong oth Yang, Weishan oth Yan, Pingzhong oth Chen, Qianli oth Li, Dong oth Cao, Libin oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:149 year:2017 day:15 month:04 pages:502-510 extent:9 https://doi.org/10.1016/j.jclepro.2017.02.122 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 149 2017 15 0415 502-510 9 |
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10.1016/j.jclepro.2017.02.122 doi GBV00000000000377.pica (DE-627)ELV015327108 (ELSEVIER)S0959-6526(17)30345-1 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Cai, Bofeng verfasserin aut How scholars and the public perceive a “low carbon city” in China 2017transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. Scholar Elsevier China Elsevier Perception Elsevier Public Elsevier Low-carbon city Elsevier Geng, Yong oth Yang, Weishan oth Yan, Pingzhong oth Chen, Qianli oth Li, Dong oth Cao, Libin oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:149 year:2017 day:15 month:04 pages:502-510 extent:9 https://doi.org/10.1016/j.jclepro.2017.02.122 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 149 2017 15 0415 502-510 9 |
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10.1016/j.jclepro.2017.02.122 doi GBV00000000000377.pica (DE-627)ELV015327108 (ELSEVIER)S0959-6526(17)30345-1 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Cai, Bofeng verfasserin aut How scholars and the public perceive a “low carbon city” in China 2017transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. Scholar Elsevier China Elsevier Perception Elsevier Public Elsevier Low-carbon city Elsevier Geng, Yong oth Yang, Weishan oth Yan, Pingzhong oth Chen, Qianli oth Li, Dong oth Cao, Libin oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:149 year:2017 day:15 month:04 pages:502-510 extent:9 https://doi.org/10.1016/j.jclepro.2017.02.122 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 149 2017 15 0415 502-510 9 |
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10.1016/j.jclepro.2017.02.122 doi GBV00000000000377.pica (DE-627)ELV015327108 (ELSEVIER)S0959-6526(17)30345-1 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Cai, Bofeng verfasserin aut How scholars and the public perceive a “low carbon city” in China 2017transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. Scholar Elsevier China Elsevier Perception Elsevier Public Elsevier Low-carbon city Elsevier Geng, Yong oth Yang, Weishan oth Yan, Pingzhong oth Chen, Qianli oth Li, Dong oth Cao, Libin oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:149 year:2017 day:15 month:04 pages:502-510 extent:9 https://doi.org/10.1016/j.jclepro.2017.02.122 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 149 2017 15 0415 502-510 9 |
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10.1016/j.jclepro.2017.02.122 doi GBV00000000000377.pica (DE-627)ELV015327108 (ELSEVIER)S0959-6526(17)30345-1 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Cai, Bofeng verfasserin aut How scholars and the public perceive a “low carbon city” in China 2017transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. Scholar Elsevier China Elsevier Perception Elsevier Public Elsevier Low-carbon city Elsevier Geng, Yong oth Yang, Weishan oth Yan, Pingzhong oth Chen, Qianli oth Li, Dong oth Cao, Libin oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:149 year:2017 day:15 month:04 pages:502-510 extent:9 https://doi.org/10.1016/j.jclepro.2017.02.122 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 149 2017 15 0415 502-510 9 |
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China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. |
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China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. |
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China is actively promoting low-carbon city development. Understanding the perception of a low-carbon city by the entire society is vital for effective policy implementation. However, the essence of a “Low Carbon City” is not consistently understood by the society. In this article, big data mining and a bibliometric approach were adopted to establish several indicators so that scholars (based on literature) and the public (based on social network) perceptions on low carbon cities can be uncovered. The major findings are as follows: The numbers of literature and social networking posts with “low carbon” & “city” as key words have increased during the period 2010–2016 and reached a peak in 2013. The literature mainly defines low-carbon cities from a macro-economic aspect. However, the public express their concerns with respect to the quality of life or how their behaviors could be affected. Cities with high PPI (Publication Popularity Indicator) or WPI (Weibo Popularity Indicator) values are mainly clustered in the three Chinese main economic regions (Jing-Jin-Ji region, Yangtze River delta region and Pearl River delta region). Cities with high CPII (Comprehensive Popularity Intensity Indicator) values are not always clustered in the three main economic regions but are located dispersedly. This implies that cities can make great progresses in low carbon development irrespective of their economic levels and spatial locations. Three cities (Shuangyashan, Chongzuo and Guyuan) had zero PPI, WPI and CPII values, reflecting that they have not been considered for low carbon development by the scientific community or the public. It is obvious that some cities have been ignored in the context of low carbon development or they have not taken any initiatives with respect to low carbon development. The CPII used in this paper could be a useful indicator for monitoring and evaluating the perception of low carbon development at the city level. |
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