Spatial characteristics and optimization of urban living space carbon suitability index (ULS-CSI) in Tianjin, China DOI Creative Commons

Zhaowei Yin,

Xiaoping Zhang, Peng Chen

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Авг. 26, 2024

The global climate crisis is escalating, and urban living Space (ULS) a significant contributor to carbon emissions. How improve the suitability of ULS while promoting social economic development issue. This study aims develop an evaluation system for comparing analyzing inequality spatial differences in different areas. To achieve this goal, space index (ULS-CSI) based on organizational (SOI) has been proposed. ULS-CSI was calculated at area scale Tianjin using information from Land Use Database 2021. emissions coefficient method used calculate (ULSCE). Moran’I LISA analysis were quantify ULS-CSI. results showed that residential (RLA) highest scale, with 1.14 × 10 11 kg, accounting 33.74%. green leisure (GLA) absorption 5.76 5 32.33%. SOI areas have heterogeneity as such building area, road network density land use characteristics are significantly Areas superior CSI primarily situated Heping, Hexi, Nankai, Beichen, 83.90%. Conversely, under basic threshold included Xiqing, Jinnan, Dongli, 16.10%. Spatial portrayed positive correlation, indicating autocorrelation degree 500 m, Moran ’I value 0.1733. Although these findings reflect affecting more perfect data needed complexity structural factors scale. helpful planning differentiated reduction strategies promote low-carbon healthy development.

Язык: Английский

Can carbon trading policy boost upgrading and optimization of industrial structure? An empirical study based on data from China DOI Creative Commons

Chen Dao-ping,

Felix Haifeng Liao,

Hong Tan

и другие.

Humanities and Social Sciences Communications, Год журнала: 2024, Номер 11(1)

Опубликована: Сен. 17, 2024

Язык: Английский

Процитировано

3
Spatiotemporal patterns and the influence mechanism of urban landscape pattern on carbon emission performance: Evidence from Chinese cities DOI
Shan Li,

Z. T. Sun,

Rongbing Wen

и другие.

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 106042 - 106042

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

1
The spatial‐temporal evolution of urban development patterns in Chinese cities: Dynamics and interpretations DOI
LI Wen-zheng, Stephan Schmidt

Growth and Change, Год журнала: 2024, Номер 55(2)

Опубликована: Май 3, 2024

Abstract This paper examines the spatial‐temporal evolution of urban spatial structure across 269 Chinese prefectural cities from 2002 to 2019. Our analysis identifies a consistent trend toward more polycentric configuration in 25 mega‐cities during this period, primarily due population growth and supportive policy environment. However, evolutionary pathways small‐ medium‐sized unfolded rather complex diverse manner, with some becoming while majority adhering monocentric trajectory. In these cases, is usually associated pattern, characterized by rapid expansion core, development attributed specific policies that support emergence subcenters. We conclude development, potentially suitable for alleviate diseconomies scale, may be less appropriate as it constrain agglomeration economies. suggest implementation regional should considerate local historical paths contextual factors. Finally, we propose stylized framework accurately reflect nature cities.

Язык: Английский

Процитировано

0
Research on Low-carbon Layout and Planning of Urban Space Driven by Sustainable Development DOI Creative Commons

Youxiang Huan

Renewable Energy and Power Quality Journal, Год журнала: 2024, Номер unknown, С. 35 - 44

Опубликована: Июль 21, 2024

Carbon dioxide emissions, leading to global warming, have threatened human development. It is urgent control and slow down greenhouse gas emissions maintain ecologically sustainable The energy demand pollutant generated in the process of urban development are main reasons climate environmental change. Scientific planning for cities construction low-carbon models first work deal with issues. In view these problems, article takes Guangyuan City as an example city construction, through transforming city's industrial structure, strengthening science technology innovation, establishing improving system other methods implement specific city, build a clean, low- carbon new life mode, Make from 2015 reach exploitable hydropower installed capacity 65% 80% 2020. this paper, we propose series spatial layout strategies, which not only in-depth analysis key problems China's urbanization process, such consumption, etc., but also targeted solutions. By implementing can effectively meet challenges brought about by promote Chinese more direction.

Язык: Английский

Процитировано

0
Spatial characteristics and optimization of urban living space carbon suitability index (ULS-CSI) in Tianjin, China DOI Creative Commons

Zhaowei Yin,

Xiaoping Zhang, Peng Chen

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Авг. 26, 2024

The global climate crisis is escalating, and urban living Space (ULS) a significant contributor to carbon emissions. How improve the suitability of ULS while promoting social economic development issue. This study aims develop an evaluation system for comparing analyzing inequality spatial differences in different areas. To achieve this goal, space index (ULS-CSI) based on organizational (SOI) has been proposed. ULS-CSI was calculated at area scale Tianjin using information from Land Use Database 2021. emissions coefficient method used calculate (ULSCE). Moran’I LISA analysis were quantify ULS-CSI. results showed that residential (RLA) highest scale, with 1.14 × 10 11 kg, accounting 33.74%. green leisure (GLA) absorption 5.76 5 32.33%. SOI areas have heterogeneity as such building area, road network density land use characteristics are significantly Areas superior CSI primarily situated Heping, Hexi, Nankai, Beichen, 83.90%. Conversely, under basic threshold included Xiqing, Jinnan, Dongli, 16.10%. Spatial portrayed positive correlation, indicating autocorrelation degree 500 m, Moran ’I value 0.1733. Although these findings reflect affecting more perfect data needed complexity structural factors scale. helpful planning differentiated reduction strategies promote low-carbon healthy development.

Язык: Английский

Процитировано

0