一种改进的小波阈值去噪方法

在小波阈值去噪中,阈值的大小是一个重要的选择。为了克服传统的阈值在每个尺度上固定不变的缺陷,提出一种对传统的小波阈值去噪改进的方法,改进的阈值可以随着分解层数的变化而变化,在实际中可灵活应用。采用信噪比和均方误差作为评价去噪性能的参数,并与传统的阈值进行了比较,仿真结果表明:改进的小波阈值去噪方法其去噪效果优于传统固定阈值、Stein无偏似然估计阈值、启发式阈值和极大极小阈值的小波阈值去噪方法,具有较高的实用价值

粤港澳大湾区PM_2.5本地与非本地污染来源解析

粤港澳大湾区（简称"大湾区"）建设是我国新时代重大国家战略之一.虽然大湾区空气质量在我国处于领先地位,但与世界先进湾区相比还有较大差距.制定大湾区PM2.5精细化防控策略,需要在识别大湾区各城市PM2.5污染来源的基础上,量化PM2.5本地和非本地贡献及时空变化规律.基于此,本研究首次在大湾区15个站点同步开展持续一年的PM2.5采样和组分分析,并将正定矩阵因子分析模型与后向轨迹结合,建立一种定量识别PM2.5本地与非本地贡献的新方法.通过对大湾区不同季节所属空气域进行划分,厘清大湾区各城市PM2.5本地与非本地贡献的动态化特征.结果发现,在2015年,大湾区15个站点共解析出9种PM2.5污染源,分别为机动车、重油、老化海盐、扬尘源、二次硫酸盐、二次硝酸盐、金属冶炼、生物质燃烧和新鲜海盐.其中,二次硫酸盐和机动车是大湾区最主要的两个PM2.5污染源.不同站点非本地贡献占比为51%～72%,表明外来传输是大湾区PM2.5污染的主要来源.内陆和沿海站点污染源的本地与非本地贡献差异较为显著,主要原因是气象条件和排放特征的差异.值得注意的是,2015年大湾区超过一半的时间处于同一个空气域,而有43%的时间处于两个不同空气域.进一步在每个季节划分空气域,发现大湾区处于两个空气域时,秋、冬季节沿海站点易形成单独的空气域,此时非本地贡献较强（68%～72%）;春季内陆站点易形成单独的空气域,此时本地贡献较强（94%）.基于对PM2.5本地和非本地贡献变化情况的定量识别,能够为大湾区各城市制定动态的PM2.5排放控制策略提供科学支撑. Development of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is one of the national strategies in China. Although at the leading position of China, air quality in the GBA is still far worse than those in other renowned bay areas in the world, e.g. San Francisco, New York and Tokyo. To formulate refined PM2.5 prevention and control strategies in GBA, it is essential to identify PM2.5 emission sources in different cities of GBA, and to quantitatively characterize local and non-local contributions and their spatio-temporal variations. In this study, based on the first-ever regionally integrated PM2.5 speciation dataset simultaneously collected at fifteen stations across the GBA in the entire year of 2015, we developed a novel approach by combining Positive Matrix Factorization source apportionment with an optimized backward trajectory analysis, in an aim to quantify local and non-local contributions to PM2.5. Local and non-local contributions were further quantified in different air-sheds during different seasons, which provides important implications for city-level dynamic control of PM2.5 over the GBA. In 2015, nine source factors were identified, including vehicle exhaust, residual oil, aged sea salt, crustal soil, secondary sulfate, secondary nitrate, trace metals, biomass burning and fresh sea salt. Secondary sulfate was the largest contributor to PM2.5, followed by vehicle exhaust. Non-local contributions accounted for 51%~72% at different sites, suggesting PM2.5 over the GBA were mainly transported from outside. Significant differences in local and non-local relative contributions existed between inland and coastal areas, which was largely driven by emission and meteorological conditions. We also highlighted that GBA was in a single air-shed for more than half of time in 2015 and split into two air-sheds for 43% of time. Seasonal analysis revealed that in the two-air-shed pattern, non-local sources contributed 68%~72% over coastal stations which formed a separated air-shed in autumn and winter. In comparison, for the inland stations which formed a separated air-shed in spring, local contribution was predominant (94%). Based on the quantitative identification of local and non-local contributions and their seasonal and spatial variations, this study provides scientific guidance in formulating dynamic and region-specific PM2.5 control measures over the GBA. © 2020, Science Press. All right reserved

基于古地磁与~(230)Th定年的西沙西科1井乐东组生物礁沉积年代的初步研究

生物礁是重要的自然资源,在全球气候变化与碳循环中扮演了重要角色.磁性地层学是建立年代框架的有效手段,但是,由于生物礁沉积物中天然剩磁强度弱,南海地区生物礁的磁性地层学研究尚未很好展开.为此,本文利用西沙群岛西科1井乐东组生物礁沉积样品进行了详细的岩石磁学和磁性地层学研究.结果显示,西沙群岛乐东组记录了布容正极性时、奥杜维尔正极性时和松山负极性时.通过对比已有的钻孔资料,本文认为应基于岩石地层特征这一标准将西沙地区的乐东组埋深予以统一.在此基础上,综合磁性地层与~(230)Th定年结果,本文将乐东组的底界限定在~2.0 Ma.</p

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors