Developing a localized and consistent model framework for climate loss and damage assessment is crucial for the policy-making of climate change mitigation and adaptation.This study introduces a comprehensive,multidisc...Developing a localized and consistent model framework for climate loss and damage assessment is crucial for the policy-making of climate change mitigation and adaptation.This study introduces a comprehensive,multidisciplinary Integrated Assessment Model(IAM)framework for evaluating climate damage in China,utilizing BCC-SESM climate model and FUND sectoral climate damage model under the SSP2-RCPs scenario.Employing a bottom-up approach,the research estimates climate damage across eight major sectors,recalibrates sectoral climate damage functions and parameters for China,and elucidates distinctions among direct climate loss,market climate loss,and aggregate climate loss.The findings reveal that the total climate damage function for China follows a quadratic pattern in response to temperature rise.By 2050,the estimated climate damage is projected to be 5.4%,5.7%,and 8.2%of GDP under RCP2.6,RCP4.5,and RCP8.5,respectively.Additionally,both direct and market climate losses are projected to remain below 2%of GDP by 2050,while the aggregate climate loss could reach as high as 8.2%,which is predominantly attributed to non-market sectors.From a sectoral perspective,under the RCP8.5 scenario,human health damage constitutes the largest share(61.9%)of the total climate loss by 2050,followed by sea-level rise damage(18.6%).This study sheds lights on the adaptation policy that should attach importance to the non-market sectors,particularly focusing on human health and sea-level rise.展开更多
In order to facilitate and coordinate spatial data sharing and exchange,many organisations have developed spatial data infrastructures(SDIs).SDI governance plays a pivotal role in the development and evolution of an S...In order to facilitate and coordinate spatial data sharing and exchange,many organisations have developed spatial data infrastructures(SDIs).SDI governance plays a pivotal role in the development and evolution of an SDI,but as SDIs are complex adaptive systems,governing is a challenge.This research therefore proposes a complexity perspective to SDI governance by exploring the use of agent-based modelling to simulate and examine SDI governance interactions.In this agent-based simulation,we examine interactions between SDI stakeholders,data availability and the effects of different governance styles(hierarchical,network and laissez-faire governance)and budget policies.The simulation shows that it is possible to mimic SDI governance dynamics through agent-based modelling.By running different scenarios,it appears that a network approach is more successful compared to a hierarchical or laissez-faire approach.Expert validation shows that overall the results of the simulation are credible and insightful,although improvements can be made to make the model more realistic.With agent-based modelling,SDI governance becomes more tangible and visible,which facilitates discussion and understanding.Agent-based modelling therefore appears to be a helpful new approach in a better understanding of the complexities and dynamics of SDI governance.展开更多
基金funded by the National Natural Science Foundation of China (42175171)Humanities and Social Science Research Project of the Ministry of Education of China (20XJC790002)National Key R&D Program of China (2016YFA0602602).
文摘Developing a localized and consistent model framework for climate loss and damage assessment is crucial for the policy-making of climate change mitigation and adaptation.This study introduces a comprehensive,multidisciplinary Integrated Assessment Model(IAM)framework for evaluating climate damage in China,utilizing BCC-SESM climate model and FUND sectoral climate damage model under the SSP2-RCPs scenario.Employing a bottom-up approach,the research estimates climate damage across eight major sectors,recalibrates sectoral climate damage functions and parameters for China,and elucidates distinctions among direct climate loss,market climate loss,and aggregate climate loss.The findings reveal that the total climate damage function for China follows a quadratic pattern in response to temperature rise.By 2050,the estimated climate damage is projected to be 5.4%,5.7%,and 8.2%of GDP under RCP2.6,RCP4.5,and RCP8.5,respectively.Additionally,both direct and market climate losses are projected to remain below 2%of GDP by 2050,while the aggregate climate loss could reach as high as 8.2%,which is predominantly attributed to non-market sectors.From a sectoral perspective,under the RCP8.5 scenario,human health damage constitutes the largest share(61.9%)of the total climate loss by 2050,followed by sea-level rise damage(18.6%).This study sheds lights on the adaptation policy that should attach importance to the non-market sectors,particularly focusing on human health and sea-level rise.
基金This work is part of the research programme Maps4Society with project number 13717(GOV4SDI)which is(partly)financed by the Dutch Research Council(NWO).
文摘In order to facilitate and coordinate spatial data sharing and exchange,many organisations have developed spatial data infrastructures(SDIs).SDI governance plays a pivotal role in the development and evolution of an SDI,but as SDIs are complex adaptive systems,governing is a challenge.This research therefore proposes a complexity perspective to SDI governance by exploring the use of agent-based modelling to simulate and examine SDI governance interactions.In this agent-based simulation,we examine interactions between SDI stakeholders,data availability and the effects of different governance styles(hierarchical,network and laissez-faire governance)and budget policies.The simulation shows that it is possible to mimic SDI governance dynamics through agent-based modelling.By running different scenarios,it appears that a network approach is more successful compared to a hierarchical or laissez-faire approach.Expert validation shows that overall the results of the simulation are credible and insightful,although improvements can be made to make the model more realistic.With agent-based modelling,SDI governance becomes more tangible and visible,which facilitates discussion and understanding.Agent-based modelling therefore appears to be a helpful new approach in a better understanding of the complexities and dynamics of SDI governance.