An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature
Abstract Cooling energy consumption of buildings is not only used for decreasing temperature, but for dehumidification. Therefore, cooling degree day (CDD) based on only temperature is insufficient for estimating the cooling energy consumption in buildings. In the present study, we aim to propose an...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-05-01
|
| Series: | Meteorological Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/met.2005 |
| _version_ | 1828436652103565312 |
|---|---|
| author | Jingfu Cao Mingcai Li Ruixue Zhang Min Wang |
| author_facet | Jingfu Cao Mingcai Li Ruixue Zhang Min Wang |
| author_sort | Jingfu Cao |
| collection | DOAJ |
| description | Abstract Cooling energy consumption of buildings is not only used for decreasing temperature, but for dehumidification. Therefore, cooling degree day (CDD) based on only temperature is insufficient for estimating the cooling energy consumption in buildings. In the present study, we aim to propose an efficient climate index (i.e., CDD based on wet bulb temperature [WBT], WCDD) based on the combination of cooling energy consumption in a building and joint probability of temperature and humidity. In addition, the adaptation of the new WCDD was verified in 14 cities of different climate zones in China. The results showed that CDD based on dry bulb temperature (DBT) (DCDD) can only explain 17%–60% of cooling energy consumption, whereas WCDD explaining 86%–97% of cooling energy consumption in the different climate zones. The optimal base WBTs are generally 17.74, 19.44, 21.04 and 22.56°C for the four climate zones, respectively. The present study reveals that WCDD by combining effects of temperature and humidity on cooling energy consumption can be much more efficiently used to estimate the cooling energy consumption compared with DCDD. More importantly, the WCDD is suitable for reflecting the cooling energy consumption for different climate zones. The collaborative changes of temperature and humidity under the conditions of climate change should be fully considered to take measures for decreasing the energy consumption for decreasing temperature and dehumidification. |
| first_indexed | 2024-12-10T19:31:22Z |
| format | Article |
| id | doaj.art-35d2360ba96242949fe1bac0064f91c1 |
| institution | Directory Open Access Journal |
| issn | 1350-4827 1469-8080 |
| language | English |
| last_indexed | 2024-12-10T19:31:22Z |
| publishDate | 2021-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Meteorological Applications |
| spelling | doaj.art-35d2360ba96242949fe1bac0064f91c12022-12-22T01:36:14ZengWileyMeteorological Applications1350-48271469-80802021-05-01283n/an/a10.1002/met.2005An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperatureJingfu Cao0Mingcai Li1Ruixue Zhang2Min Wang3Tianjin Key Laboratory for Oceanic Meteorology Tianjin 300073 ChinaTianjin Key Laboratory for Oceanic Meteorology Tianjin 300073 ChinaInstitute of Building Environment and Energy Efficiency, China Academy of Building Research Beijing 100013 ChinaInstitute of Building Environment and Energy Efficiency, China Academy of Building Research Beijing 100013 ChinaAbstract Cooling energy consumption of buildings is not only used for decreasing temperature, but for dehumidification. Therefore, cooling degree day (CDD) based on only temperature is insufficient for estimating the cooling energy consumption in buildings. In the present study, we aim to propose an efficient climate index (i.e., CDD based on wet bulb temperature [WBT], WCDD) based on the combination of cooling energy consumption in a building and joint probability of temperature and humidity. In addition, the adaptation of the new WCDD was verified in 14 cities of different climate zones in China. The results showed that CDD based on dry bulb temperature (DBT) (DCDD) can only explain 17%–60% of cooling energy consumption, whereas WCDD explaining 86%–97% of cooling energy consumption in the different climate zones. The optimal base WBTs are generally 17.74, 19.44, 21.04 and 22.56°C for the four climate zones, respectively. The present study reveals that WCDD by combining effects of temperature and humidity on cooling energy consumption can be much more efficiently used to estimate the cooling energy consumption compared with DCDD. More importantly, the WCDD is suitable for reflecting the cooling energy consumption for different climate zones. The collaborative changes of temperature and humidity under the conditions of climate change should be fully considered to take measures for decreasing the energy consumption for decreasing temperature and dehumidification.https://doi.org/10.1002/met.2005cooling energy consumptionDCDDjoint probabilityoptimal temperatureWCDD |
| spellingShingle | Jingfu Cao Mingcai Li Ruixue Zhang Min Wang An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature Meteorological Applications cooling energy consumption DCDD joint probability optimal temperature WCDD |
| title | An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature |
| title_full | An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature |
| title_fullStr | An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature |
| title_full_unstemmed | An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature |
| title_short | An efficient climate index for reflecting cooling energy consumption: Cooling degree days based on wet bulb temperature |
| title_sort | efficient climate index for reflecting cooling energy consumption cooling degree days based on wet bulb temperature |
| topic | cooling energy consumption DCDD joint probability optimal temperature WCDD |
| url | https://doi.org/10.1002/met.2005 |
| work_keys_str_mv | AT jingfucao anefficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT mingcaili anefficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT ruixuezhang anefficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT minwang anefficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT jingfucao efficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT mingcaili efficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT ruixuezhang efficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature AT minwang efficientclimateindexforreflectingcoolingenergyconsumptioncoolingdegreedaysbasedonwetbulbtemperature |