Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seas...Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seasonality remain largely unknown for the central Amazon.This study meas-ured litterfall production,leaf nutrient remobilization,and leaf area index on a forest plateau in the central Amazon.Litterfall was measured at monthly intervals during 2014,while nitrogen,phosphorus,potassium,calcium and mag-nesium concentrations of leaf litter and canopy leaves were measured in the dry and rainy seasons,and remobilization rates determined.Leaf area index was also recorded in the dry and rainy seasons.Monthly litterfall varied from 33.2(in the rainy season)to 87.6 g m^(-2) in the dry season,while leaf area index increased slightly in the rainy season.Climatic seasonality had no effect on concentrations of nitrogen,calcium,and magnesium,whereas phosphorous and potassium responded to rainfall seasonality oppositely.While phosphorous increased,potassium decreased during the dry season.Over seasons,nitrogen,potassium,and phosphorous decreased in leaf litter;calcium increased in leaf litter,while magnesium remained unaffected with leaf aging.Regardless,the five nutrients had similar remobilization rates over the year.The absence of climate seasonality on nutrient remobilization suggests that the current length of the dry season does not alter nutrient remobilization rates but this may change as dry periods become more prolonged in the future due to climate change.展开更多
A robust phenomenon termed the Arctic Amplification(AA)refers to the stronger warming taking place over the Arctic compared to the global mean.The AA can be confirmed through observations and reproduced in climate mod...A robust phenomenon termed the Arctic Amplification(AA)refers to the stronger warming taking place over the Arctic compared to the global mean.The AA can be confirmed through observations and reproduced in climate model simulations and shows significant seasonality and inter-model spread.This study focuses on the influence of surface type on the seasonality of AA and its inter-model spread by dividing the Arctic region into four surface types:ice-covered,ice-retreat,ice-free,and land.The magnitude and inter-model spread of Arctic surface warming are calculated from the difference between the abrupt-4×CO_(2)and pre-industrial experiments of 17 CMIP6 models.The change of effective thermal inertia(ETI)in response to the quadrupling of CO_(2) forcing is the leading mechanism for the seasonal energy transfer mechanism,which acts to store heat temporarily in summer and then release it in winter.The ETI change is strongest over the ice-retreat region,which is also responsible for the strongest AA among the four surface types.The lack of ETI change explains the nearly uniform warming pattern across seasons over the ice-free(ocean)region.Compared to other regions,the ice-covered region shows the maximum inter-model spread in JFM,resulting from a stronger inter-model spread in the oceanic heat storage term.However,the weaker upward surface turbulent sensible and latent heat fluxes tend to suppress the inter-model spread.The relatively small inter-model spread during summer is caused by the cancellation of the inter-model spread in ice-albedo feedback with that in the oceanic heat storage term.展开更多
为有效提高碳排放配额分配的合理性,并且避免年度结算时碳排放量超标导致环境污染加剧问题,提出基于奖惩因子的季节性碳交易机制,以园区综合能源系统(park integrated energy system,PIES)为对象进行低碳经济调度。首先,构建包含能量层...为有效提高碳排放配额分配的合理性,并且避免年度结算时碳排放量超标导致环境污染加剧问题,提出基于奖惩因子的季节性碳交易机制,以园区综合能源系统(park integrated energy system,PIES)为对象进行低碳经济调度。首先,构建包含能量层–碳流层–管理层的综合能源系统(integrated energy system,IES)运行框架,建立电气热多能流供需动态一致性模型;其次,分析系统内“日–季节–年度”碳排放特性,打破传统应用指标法的配额分配方法,采用灰色关联分析法建立碳排放配额分配模型,并基于奖惩阶梯碳价制定季节性碳交易机制;最后,以系统内全寿命周期运行成本及碳交易成本最小为目标,对执行季节性碳交易机制的PIES进行低碳经济调度,分析长时间尺度下季节性储能参与调度的减碳量。搭建IEEE 33节点电网5节点气网7节点热网的PIES,并基于多场景进行算例分析,验证此调度方法能够实现零碳经济运行,保证系统供能可靠性,为建立零碳园区奠定理论基础。展开更多
利用昆明站1991-2020年近30年逐日降水数据计算昆明雨季(5-10月)的起止时期,进一步确定昆明市雨季的长短。又基于云南省和昆明市的统计年鉴数据,使用年末总人口、城市建成区面积、城镇化率、人均GDP等城市发展因子确定昆明的城市发展进...利用昆明站1991-2020年近30年逐日降水数据计算昆明雨季(5-10月)的起止时期,进一步确定昆明市雨季的长短。又基于云南省和昆明市的统计年鉴数据,使用年末总人口、城市建成区面积、城镇化率、人均GDP等城市发展因子确定昆明的城市发展进程,将昆明市的城市发展进程划分为缓慢发展期(1991-2003年)和快速发展期(2004-2020年),进而分析比较两段时期中昆明市雨季长短的特征和差异,采用统计分析、小波分析和M-K突变检验等综合分析方法,系统分析了昆明市雨季长短的时间变化特征,并用灰色关联度分析方法分析了昆明市雨季长短与城市发展的关联性。结果表明,1991-2020年昆明市的雨季开始日呈逐渐偏晚的趋势,而雨季结束日呈逐渐偏早的趋势,总体上雨季长度呈逐渐缩短的趋势;小波系数分析结果显示,在8年以下的时间尺度上,昆明市雨季长短变化的周期不存在明显的规律性,在17年时间尺度上的周期变化明显,呈偏短-偏长-偏短-偏长-偏短的5个循环交替,2003-2008年、 2014-2017年雨季增长,1991-2002年、 2009-2012年、 2018-2020年雨季缩短,2018-2020年等值线未闭合说明还有进一步缩短的趋势。通过M-K检验表明昆明市的雨季长短在1991-2020年间出现4次突变,分别发生在2002年、 2008年、 2012年和2017年。从昆明城市发展与雨季长短的关系来看,昆明城市发展缓慢期的雨季长短的变化趋势较为平稳,而城市发展快速期2004年以后,昆明市雨季长度缩短的变化明显,并随着城市发展进程的加快其极端波动性更加明显。运用SPSS(Statistical Product and Service Solutions)软件对未来10年昆明的雨季长短进行预测,结果显示未来10年昆明雨季长短将持续偏短的趋势。在灰色关联度分辨率为0.5时,表征城市发展进程的4个因子对昆明雨季长短变化均产生不同程度影响,其关联度系数都在0.70以上,表明昆明城市发展与雨季长短显著关联性,其中影响最大的因子是年末总人口,最小为人均GDP,灰色关联度分别为0.88和0.70,属于高度关联和显著关联。对4个因子的关联系数进行排序为:年末总人口>城镇化率>城市建成区面积>人均GDP。展开更多
为研究温度变化对天然状态及饱和状态下粉质黏土强度以及变形的影响,以典型季冻区广泛分布的粉质黏土为研究对象,通过全球数字系统(global digital system,GDS)非饱和土三轴测试系统对天然状态下非饱和土以及GDS温控式静/动三轴测试系...为研究温度变化对天然状态及饱和状态下粉质黏土强度以及变形的影响,以典型季冻区广泛分布的粉质黏土为研究对象,通过全球数字系统(global digital system,GDS)非饱和土三轴测试系统对天然状态下非饱和土以及GDS温控式静/动三轴测试系统对饱和粉质黏土,在不同温度条件下进行三轴试验。对试验结果进行研究分析可得:非饱和以及饱和粉质黏土的应力-应变曲线均呈现出应变硬化的特性。非饱和粉质黏土的黏聚力随温度降低表现出不断增加的趋势,而内摩擦角随温度降低逐渐减小,但整体变化趋势较小。饱和土的黏聚力与非饱和土变化趋势相同,随温度的降低其黏聚力逐渐增加,但相同温度时其黏聚力小于非饱和土,其内摩擦角则呈先减小后增加的转变趋势。无竖向压力作用时,相同围压条件下,非饱和与饱和粉质黏土轴向变形量随温度降低而增加,相同温度条件下,两者的轴向变形量随围压的增加会有所减小。试验成果可为季冻区粉质黏土地层工程的设计施工提供理论依据。展开更多
基金supported by the Ministerio da Ciencia,Tecnologia e Inovacoes (MCTI-INPA),Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq,grant number:303913/2021-5)Fundagao de Amparo a Pesquisa do Estado do Amazonas (FAPEAM)Coordenagao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES code 0001).
文摘Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seasonality remain largely unknown for the central Amazon.This study meas-ured litterfall production,leaf nutrient remobilization,and leaf area index on a forest plateau in the central Amazon.Litterfall was measured at monthly intervals during 2014,while nitrogen,phosphorus,potassium,calcium and mag-nesium concentrations of leaf litter and canopy leaves were measured in the dry and rainy seasons,and remobilization rates determined.Leaf area index was also recorded in the dry and rainy seasons.Monthly litterfall varied from 33.2(in the rainy season)to 87.6 g m^(-2) in the dry season,while leaf area index increased slightly in the rainy season.Climatic seasonality had no effect on concentrations of nitrogen,calcium,and magnesium,whereas phosphorous and potassium responded to rainfall seasonality oppositely.While phosphorous increased,potassium decreased during the dry season.Over seasons,nitrogen,potassium,and phosphorous decreased in leaf litter;calcium increased in leaf litter,while magnesium remained unaffected with leaf aging.Regardless,the five nutrients had similar remobilization rates over the year.The absence of climate seasonality on nutrient remobilization suggests that the current length of the dry season does not alter nutrient remobilization rates but this may change as dry periods become more prolonged in the future due to climate change.
基金the National Natural Science Foundation of China(Grant No.41922044)the National Key Research and Development Program of China(Grants Nos.2019YFA0607000,2022YFE0106300)+2 种基金the National Natural Sci-ence Foundation of China(Grants Nos.42075028 and 42222502)Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.SML2021SP302)the fundamental research funds for the Norges Forskningsråd(Grant No.328886).
文摘A robust phenomenon termed the Arctic Amplification(AA)refers to the stronger warming taking place over the Arctic compared to the global mean.The AA can be confirmed through observations and reproduced in climate model simulations and shows significant seasonality and inter-model spread.This study focuses on the influence of surface type on the seasonality of AA and its inter-model spread by dividing the Arctic region into four surface types:ice-covered,ice-retreat,ice-free,and land.The magnitude and inter-model spread of Arctic surface warming are calculated from the difference between the abrupt-4×CO_(2)and pre-industrial experiments of 17 CMIP6 models.The change of effective thermal inertia(ETI)in response to the quadrupling of CO_(2) forcing is the leading mechanism for the seasonal energy transfer mechanism,which acts to store heat temporarily in summer and then release it in winter.The ETI change is strongest over the ice-retreat region,which is also responsible for the strongest AA among the four surface types.The lack of ETI change explains the nearly uniform warming pattern across seasons over the ice-free(ocean)region.Compared to other regions,the ice-covered region shows the maximum inter-model spread in JFM,resulting from a stronger inter-model spread in the oceanic heat storage term.However,the weaker upward surface turbulent sensible and latent heat fluxes tend to suppress the inter-model spread.The relatively small inter-model spread during summer is caused by the cancellation of the inter-model spread in ice-albedo feedback with that in the oceanic heat storage term.
基金the National Natural Science Foundation of China[grant numbers 41931181 and 42075048]the Youth Innovation Promotion Association of the Chinese Academy of Sciences[grant number 2022075].
文摘为有效提高碳排放配额分配的合理性,并且避免年度结算时碳排放量超标导致环境污染加剧问题,提出基于奖惩因子的季节性碳交易机制,以园区综合能源系统(park integrated energy system,PIES)为对象进行低碳经济调度。首先,构建包含能量层–碳流层–管理层的综合能源系统(integrated energy system,IES)运行框架,建立电气热多能流供需动态一致性模型;其次,分析系统内“日–季节–年度”碳排放特性,打破传统应用指标法的配额分配方法,采用灰色关联分析法建立碳排放配额分配模型,并基于奖惩阶梯碳价制定季节性碳交易机制;最后,以系统内全寿命周期运行成本及碳交易成本最小为目标,对执行季节性碳交易机制的PIES进行低碳经济调度,分析长时间尺度下季节性储能参与调度的减碳量。搭建IEEE 33节点电网5节点气网7节点热网的PIES,并基于多场景进行算例分析,验证此调度方法能够实现零碳经济运行,保证系统供能可靠性,为建立零碳园区奠定理论基础。
文摘利用昆明站1991-2020年近30年逐日降水数据计算昆明雨季(5-10月)的起止时期,进一步确定昆明市雨季的长短。又基于云南省和昆明市的统计年鉴数据,使用年末总人口、城市建成区面积、城镇化率、人均GDP等城市发展因子确定昆明的城市发展进程,将昆明市的城市发展进程划分为缓慢发展期(1991-2003年)和快速发展期(2004-2020年),进而分析比较两段时期中昆明市雨季长短的特征和差异,采用统计分析、小波分析和M-K突变检验等综合分析方法,系统分析了昆明市雨季长短的时间变化特征,并用灰色关联度分析方法分析了昆明市雨季长短与城市发展的关联性。结果表明,1991-2020年昆明市的雨季开始日呈逐渐偏晚的趋势,而雨季结束日呈逐渐偏早的趋势,总体上雨季长度呈逐渐缩短的趋势;小波系数分析结果显示,在8年以下的时间尺度上,昆明市雨季长短变化的周期不存在明显的规律性,在17年时间尺度上的周期变化明显,呈偏短-偏长-偏短-偏长-偏短的5个循环交替,2003-2008年、 2014-2017年雨季增长,1991-2002年、 2009-2012年、 2018-2020年雨季缩短,2018-2020年等值线未闭合说明还有进一步缩短的趋势。通过M-K检验表明昆明市的雨季长短在1991-2020年间出现4次突变,分别发生在2002年、 2008年、 2012年和2017年。从昆明城市发展与雨季长短的关系来看,昆明城市发展缓慢期的雨季长短的变化趋势较为平稳,而城市发展快速期2004年以后,昆明市雨季长度缩短的变化明显,并随着城市发展进程的加快其极端波动性更加明显。运用SPSS(Statistical Product and Service Solutions)软件对未来10年昆明的雨季长短进行预测,结果显示未来10年昆明雨季长短将持续偏短的趋势。在灰色关联度分辨率为0.5时,表征城市发展进程的4个因子对昆明雨季长短变化均产生不同程度影响,其关联度系数都在0.70以上,表明昆明城市发展与雨季长短显著关联性,其中影响最大的因子是年末总人口,最小为人均GDP,灰色关联度分别为0.88和0.70,属于高度关联和显著关联。对4个因子的关联系数进行排序为:年末总人口>城镇化率>城市建成区面积>人均GDP。
文摘为研究温度变化对天然状态及饱和状态下粉质黏土强度以及变形的影响,以典型季冻区广泛分布的粉质黏土为研究对象,通过全球数字系统(global digital system,GDS)非饱和土三轴测试系统对天然状态下非饱和土以及GDS温控式静/动三轴测试系统对饱和粉质黏土,在不同温度条件下进行三轴试验。对试验结果进行研究分析可得:非饱和以及饱和粉质黏土的应力-应变曲线均呈现出应变硬化的特性。非饱和粉质黏土的黏聚力随温度降低表现出不断增加的趋势,而内摩擦角随温度降低逐渐减小,但整体变化趋势较小。饱和土的黏聚力与非饱和土变化趋势相同,随温度的降低其黏聚力逐渐增加,但相同温度时其黏聚力小于非饱和土,其内摩擦角则呈先减小后增加的转变趋势。无竖向压力作用时,相同围压条件下,非饱和与饱和粉质黏土轴向变形量随温度降低而增加,相同温度条件下,两者的轴向变形量随围压的增加会有所减小。试验成果可为季冻区粉质黏土地层工程的设计施工提供理论依据。
