Based on data of daily air temperature during 1951-2013,long-term variation characteristics of cooling degree days( CDD) in Xi'an and Chang'an in summer were analyzed by using CDD to evaluate cooling energy consum...Based on data of daily air temperature during 1951-2013,long-term variation characteristics of cooling degree days( CDD) in Xi'an and Chang'an in summer were analyzed by using CDD to evaluate cooling energy consumption and 26 ℃ as the basic temperature of CDD. The results indicated that the changing trends of CDD in Xi'an and Chang'an were basically identical within a year,and the demand for cooling refrigeration was large mainly from June to August,especially in July. The maximum of urban-rural difference of CDD between Xi'an and Chang'an appeared in June.In order to achieve the same temperature,energy needed by the urban area was 5-7 ℃·d more than the suburb from June to August. Temperature and the cooling energy consumption were closely related,and the correlation degree increased with the rise of temperature. The effects of temperature increase of 1 ℃ on cooling energy consumption rate in Xi'an were more obvious than that in Chang'an. In both Xi'an and Chang'an,the effects of temperature increase of 1 ℃ on cooling energy consumption rate in July and August were greater than that in May,June and September.Evaluation models of cooling energy consumption in summer in Xi'an and Chang'an were built using temperature anomaly and CDD variability and can be applied to business systems.展开更多
The building sector is facing a challenge in achieving carbon neutrality due to climate change and urbanization.Urban building energy modeling(UBEM)is an effective method to understand the energy use of building stock...The building sector is facing a challenge in achieving carbon neutrality due to climate change and urbanization.Urban building energy modeling(UBEM)is an effective method to understand the energy use of building stocks at an urban scale and evaluate retrofit scenarios against future weather variations,supporting the implementation of carbon emission reduction policies.Currently,most studies focus on the energy performance of archetype buildings under climate change,which is hard to obtain refined results for individual buildings when scaling up to an urban area.Therefore,this study integrates future weather data with an UBEM approach to assess the impacts of climate change on the energy performance of urban areas,by taking two urban neighborhoods comprising 483 buildings in Geneva,Switzerland as case studies.In this regard,GIS datasets and Swiss building norms were collected to develop an archetype library.The building heating energy consumption was calculated by the UBEM tool—AutoBPS,which was then calibrated against annual metered data.A rapid UBEM calibration method was applied to achieve a percentage error of 2.7%.The calibrated models were then used to assess the impacts of climate change using four future weather datasets out of Shared Socioeconomic Pathways(SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).The results showed a decrease of 22%–31%and 21%–29%for heating energy consumption,an increase of 113%–173%and 95%–144%for cooling energy consumption in the two neighborhoods by 2050.The average annual heating intensity dropped from 81 kWh/m^(2) in the current typical climate to 57 kWh/m^(2) in the SSP5-8.5,while the cooling intensity rose from 12 kWh/m^(2) to 32 kWh/m^(2).The overall envelope system upgrade reduced the average heating and cooling energy consumption by 41.7%and 18.6%,respectively,in the SSP scenarios.The spatial and temporal distribution of energy consumption change can provide valuable information for future urban energy planning against climate change.展开更多
基金Supported by Foundation for Young Scholars of Shaanxi Meteorological Bureau in 2016 and 2017(2016Y-7,2017Y-11)
文摘Based on data of daily air temperature during 1951-2013,long-term variation characteristics of cooling degree days( CDD) in Xi'an and Chang'an in summer were analyzed by using CDD to evaluate cooling energy consumption and 26 ℃ as the basic temperature of CDD. The results indicated that the changing trends of CDD in Xi'an and Chang'an were basically identical within a year,and the demand for cooling refrigeration was large mainly from June to August,especially in July. The maximum of urban-rural difference of CDD between Xi'an and Chang'an appeared in June.In order to achieve the same temperature,energy needed by the urban area was 5-7 ℃·d more than the suburb from June to August. Temperature and the cooling energy consumption were closely related,and the correlation degree increased with the rise of temperature. The effects of temperature increase of 1 ℃ on cooling energy consumption rate in Xi'an were more obvious than that in Chang'an. In both Xi'an and Chang'an,the effects of temperature increase of 1 ℃ on cooling energy consumption rate in July and August were greater than that in May,June and September.Evaluation models of cooling energy consumption in summer in Xi'an and Chang'an were built using temperature anomaly and CDD variability and can be applied to business systems.
基金This paper is supported by the National Natural Science Foundation of China(NSFC)through Grant No.51908204the Natural Science Foundation of Hunan Province of China through Grant No.2020JJ3008Supports of the Sweden’s innovation agency(VINNOVA-MIRAI)and the Crafoord Foundation are acknowledged.
文摘The building sector is facing a challenge in achieving carbon neutrality due to climate change and urbanization.Urban building energy modeling(UBEM)is an effective method to understand the energy use of building stocks at an urban scale and evaluate retrofit scenarios against future weather variations,supporting the implementation of carbon emission reduction policies.Currently,most studies focus on the energy performance of archetype buildings under climate change,which is hard to obtain refined results for individual buildings when scaling up to an urban area.Therefore,this study integrates future weather data with an UBEM approach to assess the impacts of climate change on the energy performance of urban areas,by taking two urban neighborhoods comprising 483 buildings in Geneva,Switzerland as case studies.In this regard,GIS datasets and Swiss building norms were collected to develop an archetype library.The building heating energy consumption was calculated by the UBEM tool—AutoBPS,which was then calibrated against annual metered data.A rapid UBEM calibration method was applied to achieve a percentage error of 2.7%.The calibrated models were then used to assess the impacts of climate change using four future weather datasets out of Shared Socioeconomic Pathways(SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).The results showed a decrease of 22%–31%and 21%–29%for heating energy consumption,an increase of 113%–173%and 95%–144%for cooling energy consumption in the two neighborhoods by 2050.The average annual heating intensity dropped from 81 kWh/m^(2) in the current typical climate to 57 kWh/m^(2) in the SSP5-8.5,while the cooling intensity rose from 12 kWh/m^(2) to 32 kWh/m^(2).The overall envelope system upgrade reduced the average heating and cooling energy consumption by 41.7%and 18.6%,respectively,in the SSP scenarios.The spatial and temporal distribution of energy consumption change can provide valuable information for future urban energy planning against climate change.