理想声源辐射声场的数值分析

通过声场的特性和规律分析可以识别和定位噪声源,对噪声控制以及声源的设计提供参考。数值方法是求解有源声场的重要工具,复杂的声辐射一般可分解为简单的声辐射叠加。研究了单极子、偶极子、活塞等几种理想声源辐射声场的解析解,并用有限元法计算数值解,得到相应的辐射声场,包括声压、速度、指向性等量,有限元法得到的数值结果与解析解吻合;利用有限元法计算了点声源的线性阵列与平面阵列等典型的叠加声场。对各种声源的特性和辐射声场的规律以及在工程领域中的应用进行了归纳。国家自然科学基金项目(51505261);;山东省自然科学基金项目(ZR2015AM013

The Social Status of the Female in China and Its Influence Factors

女性对自身社会地位的主观评估主要取决于对自我能力的认可程度、母亲和自己的受教育水平、以及所居住区域的性别文化性质。对自己的能力树立信心是女性社会地位提高的一个与心理或性格相关联的先决条件,而教育投入则是提升女性社会地位一块不可或缺的重要基石。大男子区域文化不仅不合理地降低女性的社会地位,而且还让处于不平等社会地位中的女性感到自我满足。要进一步改善我国妇女的社会地位,就必须在注意提高妇女自信的心理素质和自强的教育素质的同时,从社区和社会层面消除以男权为核心的传统性别文化。The subjective self-assessment of the Women mainly depends on self- approval degree of ability, the educational level of themselves and their mothers and the sexual cultural nature of the inhabitant areas It is a precondition related to the psychology and the personality for women to establish their own confidence on their ability in order to raise their social status, while the educational input is the important and indispensable basis in promoting the social status of women The big man regional culture will not merely reduce the social status of women unreasonably, but also make the women who are in the unfair status feel satisfied In order to improve the social status of women in our country, we should dispel the traditional sexual culture with the male power as th core from the aspects community and society while raising the psychological quality and educational qualit

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