为构建适用于体育场馆类微观建筑水系统的水-能-碳足迹关联模型,分析了各类体育场馆的特点,采用排放因子法对体育场馆开展包括生活水系统、空调水系统及体育水系统在内的模型搭建,解析了取水、给水、用水及排水的能源消耗与碳排放过程...为构建适用于体育场馆类微观建筑水系统的水-能-碳足迹关联模型,分析了各类体育场馆的特点,采用排放因子法对体育场馆开展包括生活水系统、空调水系统及体育水系统在内的模型搭建,解析了取水、给水、用水及排水的能源消耗与碳排放过程。采用数据质量评价与随机分析相结合的方法进行数值不确定性分析;采用情景分析法与敏感性分析法进行情景不确定性分析,识别并量化影响因素。以2022年北京冬奥会延庆赛区的国家雪车雪橇中心场馆为例的分析结果表明:水在全生命周期中制冰项与供暖项碳排放量最高,分别为161.2,114.3 t CO_(2),在先进技术+清洁能源情景下可减少65.4%的碳排放量,变异系数为0.183~0.187。使用绿色电力、采用节水器具、中水回用、提高能源利用效率等措施可达到稳定的减排效果。展开更多
A process-based ecosystem productivity model BEPS (Boreal Ecosystem Productivity Simulator) was updated to simulate half-hourly exchanges of carbon, water and energy between the atmosphere and terrestrial ecosystem at...A process-based ecosystem productivity model BEPS (Boreal Ecosystem Productivity Simulator) was updated to simulate half-hourly exchanges of carbon, water and energy between the atmosphere and terrestrial ecosystem at a temperate broad-leaved Korean pine forest in the Changbai Mountains, China. The BEPSh model is able to capture the diurnal and seasonal variability in carbon dioxide, water vapor and heat fluxes at this site in the growing season of 2003. The model validation showed that the simulated net ecosystem productivity (NEP), latent heat flux (LE), sensible heat flux (Hs) are in good agreement with eddy covariance measurements with an R2 value of 0.68, 0.86 and 0.72 for NEP, LE and Hs, respectively. The simulated annual NEP of this forest in 2003 was 300.5 gC/m2, and was very close to the observed value. Driving this model with different climate scenarios, we found that the NEP in the Changbai Mountains temperate broad-leaved Korean pine mixed forest ecosystem was sensitive to climate variability, and the current carbon sink will be weakened under the condition of global warming. Furthermore, as a process-based model, BEPSh was also sensitive to physiological parameters of plant, such as maximum Rubisco activity (Vcmax) and the maximum stomatal conductance (gmax), and needs to be carefully calibrated for other applications.展开更多
Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting...Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen （CN） interactions （CLM4.5-CN） to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 （BRSa3） site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production （GPP） and latent heat flux （LE） for the dry season, and improved the carbon （C） and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m^-2 d^-1, net ecosystem exchange by 1.96 g C m^-2 d^-1, LE by 5.0 W m^-2, and soil moisture by 0.03 m^3 m^-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses （including GPP and LE） to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.展开更多
文摘为构建适用于体育场馆类微观建筑水系统的水-能-碳足迹关联模型,分析了各类体育场馆的特点,采用排放因子法对体育场馆开展包括生活水系统、空调水系统及体育水系统在内的模型搭建,解析了取水、给水、用水及排水的能源消耗与碳排放过程。采用数据质量评价与随机分析相结合的方法进行数值不确定性分析;采用情景分析法与敏感性分析法进行情景不确定性分析,识别并量化影响因素。以2022年北京冬奥会延庆赛区的国家雪车雪橇中心场馆为例的分析结果表明:水在全生命周期中制冰项与供暖项碳排放量最高,分别为161.2,114.3 t CO_(2),在先进技术+清洁能源情景下可减少65.4%的碳排放量,变异系数为0.183~0.187。使用绿色电力、采用节水器具、中水回用、提高能源利用效率等措施可达到稳定的减排效果。
基金This work was supported by the National Natural Science Foundation of China,the Chinese Academy of Sciences,the Ministry of Science and Technology(Grant Nos.30225012,KZCX1SW-01-01A and 2002CB412500).
文摘A process-based ecosystem productivity model BEPS (Boreal Ecosystem Productivity Simulator) was updated to simulate half-hourly exchanges of carbon, water and energy between the atmosphere and terrestrial ecosystem at a temperate broad-leaved Korean pine forest in the Changbai Mountains, China. The BEPSh model is able to capture the diurnal and seasonal variability in carbon dioxide, water vapor and heat fluxes at this site in the growing season of 2003. The model validation showed that the simulated net ecosystem productivity (NEP), latent heat flux (LE), sensible heat flux (Hs) are in good agreement with eddy covariance measurements with an R2 value of 0.68, 0.86 and 0.72 for NEP, LE and Hs, respectively. The simulated annual NEP of this forest in 2003 was 300.5 gC/m2, and was very close to the observed value. Driving this model with different climate scenarios, we found that the NEP in the Changbai Mountains temperate broad-leaved Korean pine mixed forest ecosystem was sensitive to climate variability, and the current carbon sink will be weakened under the condition of global warming. Furthermore, as a process-based model, BEPSh was also sensitive to physiological parameters of plant, such as maximum Rubisco activity (Vcmax) and the maximum stomatal conductance (gmax), and needs to be carefully calibrated for other applications.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41305066 and 41575096)
文摘Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen （CN） interactions （CLM4.5-CN） to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 （BRSa3） site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production （GPP） and latent heat flux （LE） for the dry season, and improved the carbon （C） and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m^-2 d^-1, net ecosystem exchange by 1.96 g C m^-2 d^-1, LE by 5.0 W m^-2, and soil moisture by 0.03 m^3 m^-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses （including GPP and LE） to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.
