Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data

In 2007, China surpassed the USA to become the largest carbon emitter in the world. China has promised a 60%–65% reduction in carbon emissions per unit GDP by 2030, compared to the baseline of 2005. Therefore, it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies. This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data. By applying the Exploratory Spatial-Temporal Data Analysis(ESTDA) framework, this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013. The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units. The results show that, firstly, high accuracy was achieved by the model in simulating carbon emissions. Secondly, the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82% and 5.72%, respectively. The overall carbon footprints and carbon deficits were larger in the North than that in the South. There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units. Thirdly, the relative lengths of the Local Indicators of Spatial Association(LISA) time paths were longer in the North than that in the South, and they increased from the coastal to the central and western regions. Lastly, the overall decoupling index was mainly a weak decoupling type, but the number of cities with this weak decoupling continued to decrease. The unsustainable development trend of China's economic growth and carbon emission load will continue for some time.     

商圈功能多样性对其活力的影响研究

探究功能多样性如何影响商圈活力,可为城市用地功能结构优化调整和商圈功能改造提供理论支撑,进而促进城市混合功能有序开发、提升城市活力.已有关于功能多样性与活力的研究,大多集中在城市、街道活力等方面,对于商圈活力研究很少涉及,且大多利用单一的熵指数反映功能多样性.在利用夜光数据对活力的研究中,大多选取城市或更大区域尺度作为...     

光强对欧洲舌齿鲈稚鱼眼组织基因表达的影响

大多数海水鱼类靠视觉器官识别并捕捉饵料,光强对其视觉器官基因表达影响的研究较少.     

四川山地暖季夜间暴雨的空间分布以及对海拔高度的依赖性

四川盆地是我国夜雨发生频次最高的地区，夜间暴雨是夜雨中可致灾并加剧防范难度的一类特殊气象灾害，但以往对四川山地夜间暴雨精细特性的相关研究较少。利用四川省2010—2019年2 165个国家及区域气象站逐小时降水资料，分区统计了四川暖季（5—9月）暴雨日夜间降水占日降水量的比例、夜间暴雨频次和夜间平均暴雨强度的基本特征，并通过趋势分析和地理加权回归等统计方法，分析了其空间分布及其与海拔高度的关系，获得以下结果：（1）四川暴雨日夜间降水占日降水量比例呈现自南向北递减的趋势，以海拔2 800 m为分界，表现为随海拔高度升高呈先增大、后减小的垂直分布特征，川西南山地与其他山地区域整体上升的变化趋势明显不同。（2）夜间暴雨频次较多的测站沿川西与川西南山地陡峭地形呈线性分布，夜间暴雨频次随海拔高度升高总体呈现减小的特征，川西山地和川西南山地的频次最大值分别出现在海拔800 m和500 m。（3）四川夜间平均暴雨强度整体随海拔的升高而减小，大值区主要位于川西山地和川东北山地，海拔700 m高度处的峰值强度主要由川西山地贡献。（4）川西山地夜间暴雨特征呈次数较多且每次强度大，川西南山地夜间暴雨为次数多但单次降水量较小，而川东北夜间暴雨的强度较大但次数较少。以上结果有助于深化对山地夜间暴雨精细特征的认识。     

光质对条斑紫菜自由丝状体生长和生理指标的影响

光质是影响藻类生长发育的重要因子。本文旨在研究栽培型条斑紫菜(Neopyropia yezoensis)自由丝状体在不同光质(白光、红光、蓝光、绿光)下生长率、形态、超微结构、色素含量及抗氧化酶活性的差异。结果显示:培养21 d后,白光显著提高条斑紫菜自由丝状体特定生长率和叶绿素a含量,其次是红光和绿光,蓝光最差。和白光组相比,蓝光组藻体藻红蛋白(PE)含量最高,红光、绿光组藻体藻蓝蛋白(PC)含量较高。白光组藻体正常黑褐色,细胞壁最厚。红、绿光组藻体绿色,直径和细胞壁厚度与白光组相近。蓝光组藻体鲜艳红色,直径最小,细胞壁最薄,且超微结构显示类囊体上质体小球数量最多。蓝光照射后,藻体丙二醛(MDA)含量最高,超氧化物歧化酶(SOD)活性最低。研究表明,白光最有利于条斑紫菜自由丝状体生长,其次是红光和绿光,蓝光则有不利影响。     

建设渤海跨海通道的生态影响述评

海洋生态系统能够提供各种生态服务,对人类的生存与发展具有重要意义。然而随着对海洋开发强度的增加,尤其近些年大型涉海工程的建设,给海洋生态带来严重威胁。作为一项世界级的大型海洋交通工程,渤海跨海通道项目从20世纪90年代初提出至今已经历近30年的时间。为深入探讨其建设可能给海洋生态带来的风险,本文从海洋污染、水下噪音、人造光、微塑料等几个方面分析和讨论了其可能给海洋生物的生理、行为、迁移以及海洋保护区及其周边渔业管理等带来的影响,并在此基础上提出了海洋通道建设影响评估框架,以期为跨海通道建设评估提供理论依据和参考。