Comprehensive analysis of the Economy-Energy-Carbon Emission(EECE)system is beneficial for promoting sustainable social development.This study analyzes the system development of major watersheds in China from 2010 to ...Comprehensive analysis of the Economy-Energy-Carbon Emission(EECE)system is beneficial for promoting sustainable social development.This study analyzes the system development of major watersheds in China from 2010 to 2019.The research fully considers the system’s internal and external inputs and outputs and proposes an evaluation index system for regional EECE coupling and coordinated development.Then,using the difference in system weight allocation to improve the coupling and coordination model,the study explores the dynamic system’s coupling and coordination.The results show that(1)The development of the system structure is relatively stable,but the overall development status is not ideal;(2)The downstream of China’s main river basins has obvious economic advantages,while the energy system fluctuates greatly.The efficiency of the carbon emission system will decrease in areas with rapid economic development.The coupling and coordination level of the EECE system is better in the Yangtze River Basin than in the Yellow River Basin;(3)From the perspective of dynamic coordinated development,the main river basins have been divided into two states since 2012,but it is relatively stable overall.Regional dynamic coordination is often at a disadvantage in regions with rapid economic and energy development;(4)The coupling coordination degree of the two river basins has significant positive spatial autocorrelation.Most provinces’significant spatial clustering characteristics of the coupling coordination degree are High-High type.Low-Low type provinces are mainly concentrated downstream.The research process has certain reference significance for the collaborative governance of complex regional systems.展开更多
The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and i...The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.展开更多
Lithium production in China mainly depends on hard rock lithium ores,which has a defect in resources,environment,and economy compared with extracting lithium from brine.This paper focuses on the research progress of e...Lithium production in China mainly depends on hard rock lithium ores,which has a defect in resources,environment,and economy compared with extracting lithium from brine.This paper focuses on the research progress of extracting lithium from spodumene,lepidolite,petalite,and zinnwaldite by acid,alkali,salt roasting,and chlorination methods,and analyzes the resource intensity,environmental impact,and production cost of industrial lithium extraction from spodumene and lepidolite.It is found that the sulfuric acid method has a high lithium recovery rate,but with a complicated process and high energy consumption;alkali and chlorination methods can directly react with lithium ores,reducing energy consumption,but need to optimize reaction conditions and safety of equipment and operation;the salt roasting method has large material flux and high energy consumption,so require adjustment of sulfate ratio to increase the lithium yield and reduce production cost.Compared with extracting lithium from brine,extracting lithium from ores,calcination,roasting,purity,and other processes consume more resources and energy;and its environmental impact mainly comes from the pollutants discharged by fossil energy,9.3-60.4 times that of lithium extracted from brine.The processing cost of lithium extraction from lepidolite by sulfate roasting method is higher than that from spodumene by sulfuric acid due to the consumption of high-value sulfate.However,the production costs of both are mainly affected by the price of lithium ores,which is less competitive than that of extracting lithium from brine.Thus,the process of extracting lithium from ores should develop appropriate technology,shorten the process flow,save resources and energy,and increase the recovery rate of related elements to reduce environmental impact and improve the added value of by-products and the economy of the process.展开更多
Precise identification and categorization of building materials are essential for informing strategies related to embodied carbon reduction,building retrofitting,and circularity in urban environments.However,existing ...Precise identification and categorization of building materials are essential for informing strategies related to embodied carbon reduction,building retrofitting,and circularity in urban environments.However,existing building material databases are typically limited to individual projects or specific geographic areas,offering only approximate assessments.Acquiring large-scale and precise material data is hindered by inadequate records and financial constraints.Here,we introduce a novel automated framework that harnesses recent advances in sensing technology and deep learning to identify roof and facade materials using remote sensing data and Google Street View imagery.The model was initially trained and validated on Odense's comprehensive dataset and then extended to characterize building materials across Danish urban landscapes,including Copenhagen,Aarhus,and Aalborg.Our approach demonstrates the model's scalability and adaptability to different geographic contexts and architectural styles,providing high-resolution insights into material distribution across diverse building types and cities.These findings are pivotal for informing sustainable urban planning,revising building codes to lower carbon emissions,and optimizing retrofitting efforts to meet contemporary standards for energy efficiency and emission reductions.展开更多
基金supported by the Chengdu University of Technology“Double First-Class”initiative Construction Philosophy and Social Sciences Key Construction Project(No.ZDJS202202)the Research on the realization path and strategy of strategic mineral resources supply security under the new road of Chinese modernization(No.SCKCZY2023-ZD002)The Second Tibetan Plateau Scientific Expedition and Research(No.2021QZKK0305)。
文摘Comprehensive analysis of the Economy-Energy-Carbon Emission(EECE)system is beneficial for promoting sustainable social development.This study analyzes the system development of major watersheds in China from 2010 to 2019.The research fully considers the system’s internal and external inputs and outputs and proposes an evaluation index system for regional EECE coupling and coordinated development.Then,using the difference in system weight allocation to improve the coupling and coordination model,the study explores the dynamic system’s coupling and coordination.The results show that(1)The development of the system structure is relatively stable,but the overall development status is not ideal;(2)The downstream of China’s main river basins has obvious economic advantages,while the energy system fluctuates greatly.The efficiency of the carbon emission system will decrease in areas with rapid economic development.The coupling and coordination level of the EECE system is better in the Yangtze River Basin than in the Yellow River Basin;(3)From the perspective of dynamic coordinated development,the main river basins have been divided into two states since 2012,but it is relatively stable overall.Regional dynamic coordination is often at a disadvantage in regions with rapid economic and energy development;(4)The coupling coordination degree of the two river basins has significant positive spatial autocorrelation.Most provinces’significant spatial clustering characteristics of the coupling coordination degree are High-High type.Low-Low type provinces are mainly concentrated downstream.The research process has certain reference significance for the collaborative governance of complex regional systems.
基金supported by the National Natural Science Foundation of China (71991484,42271471,72088101,and 41830645)Danish Agency for Higher Education and Science (International Network Project,0192-00056B)the Fundamental Research Funds for the Central Universities (Peking University).
文摘The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.
基金financially supported by the National Natural Science Foundation of China(71991484,41971265,72088101,and 71991480)the National Key R&D program of China(2021YFC2901801)。
文摘Lithium production in China mainly depends on hard rock lithium ores,which has a defect in resources,environment,and economy compared with extracting lithium from brine.This paper focuses on the research progress of extracting lithium from spodumene,lepidolite,petalite,and zinnwaldite by acid,alkali,salt roasting,and chlorination methods,and analyzes the resource intensity,environmental impact,and production cost of industrial lithium extraction from spodumene and lepidolite.It is found that the sulfuric acid method has a high lithium recovery rate,but with a complicated process and high energy consumption;alkali and chlorination methods can directly react with lithium ores,reducing energy consumption,but need to optimize reaction conditions and safety of equipment and operation;the salt roasting method has large material flux and high energy consumption,so require adjustment of sulfate ratio to increase the lithium yield and reduce production cost.Compared with extracting lithium from brine,extracting lithium from ores,calcination,roasting,purity,and other processes consume more resources and energy;and its environmental impact mainly comes from the pollutants discharged by fossil energy,9.3-60.4 times that of lithium extracted from brine.The processing cost of lithium extraction from lepidolite by sulfate roasting method is higher than that from spodumene by sulfuric acid due to the consumption of high-value sulfate.However,the production costs of both are mainly affected by the price of lithium ores,which is less competitive than that of extracting lithium from brine.Thus,the process of extracting lithium from ores should develop appropriate technology,shorten the process flow,save resources and energy,and increase the recovery rate of related elements to reduce environmental impact and improve the added value of by-products and the economy of the process.
基金supported by the National Natural Science Foundation of China(71991484,71991480)the Fundamental Research Funds for the Central Universities of Peking University,the Independent Research Fund Denmark(iBuildGreen)+1 种基金the European Union under grant agreement No.101056810(CircEUlar)the China Scholarship Council(202006730004 and 202107940001).
文摘Precise identification and categorization of building materials are essential for informing strategies related to embodied carbon reduction,building retrofitting,and circularity in urban environments.However,existing building material databases are typically limited to individual projects or specific geographic areas,offering only approximate assessments.Acquiring large-scale and precise material data is hindered by inadequate records and financial constraints.Here,we introduce a novel automated framework that harnesses recent advances in sensing technology and deep learning to identify roof and facade materials using remote sensing data and Google Street View imagery.The model was initially trained and validated on Odense's comprehensive dataset and then extended to characterize building materials across Danish urban landscapes,including Copenhagen,Aarhus,and Aalborg.Our approach demonstrates the model's scalability and adaptability to different geographic contexts and architectural styles,providing high-resolution insights into material distribution across diverse building types and cities.These findings are pivotal for informing sustainable urban planning,revising building codes to lower carbon emissions,and optimizing retrofitting efforts to meet contemporary standards for energy efficiency and emission reductions.
