Research progress of the POP fugacity model: a bibliometrics-based analysis

Environmental Science and Pollution Research - With the emergence of environmental issues regarding persistent organic pollutants (POPs), fugacity models have been widely used in the concentration...     

Influence of urban spatial and socioeconomic parameters on PM2.5 at subdistrict level: A land use regression study in Shenzhen, China

The intraurban distribution of PM_2.5 concentration is influenced by various spatial, socioeconomic, and meteorological parameters. This study investigated the influence of 37 parameters on monthly average PM_2.5 concentration at the subdistrict level with Pearson correlation analysis and land-use regression (LUR) using data from a subdistrict-level air pollution monitoring network in Shenzhen, China. Performance of LUR models is evaluated with leave-one-out-cross-validation (LOOCV) and holdout cross-validation (holdout CV). Pearson correlation analysis revealed that Normalized Difference Built-up Index, artificial land fraction, land surface temperature, and point-of-interest (POI) numbers of factories and industrial parks are significantly positively correlated with monthly average PM_2.5 concentrations, while Normalized Difference Vegetation Index and Green View Factor show significant negative correlations. For the sparse national stations, robust LUR modelling may rely on a priori assumptions in direction of influence during the predictor selection process. The month-by-month spatial regression shows that RF models for both national stations and all stations show significantly inflated mean values of R² compared with cross-validation results. For MLR models, inflation of both R² and R²_CV was detected when using only national stations and may indicate the restricted ability to predict spatial distribution of PM_2.5 levels. Inflated within-sample R² also exist in the spatiotemporal LUR models developed with only national stations, although not as significant as spatial LUR models. Our results suggest that a denser subdistrict level air pollutant monitoring network may improve the accuracy and robustness in intraurban spatial/spatiotemporal prediction of PM_2.5 concentrations.     

2021年11月17日江苏大丰海域M5.0地震震源区三维P波速度结构∗

使用近 20 年固定台站记录到的初至 P 波到时数据，利用双差地震层析成像方法反演了 2021 年 11 月 17 日江苏大丰海域 M5.0 地震震源区及邻区三维 P 波速度结构和震源位置参数。结合该地区的构造背景，研究了该地震孕育与发生的深部构造背景及速度结构与地震活动性之间的关系。结果表明：研究区 P 波速度结构存在明显的横向非均匀性，浅层的 P 波速度结构与地表地质构造及地形有较好的对应性，在造山带和隆起区表现为相对高速，盆地地区表现为相对低速。研究区地震活动性与速度结构存在明显的相关性，大丰海域地震和经过重定位后的中小地震均发生在 P 波速度梯度带上或者偏向高速一侧。综合速度结构水平和垂直剖面，震源机制解，震源的空间位置分析认为此次地震可能为右旋走滑型地震，发震断裂可能为苏北?滨海断裂，也可能与小海?陈家堡断裂及震源区其他的隐伏断裂有关。此次地震发生可能与震源区附近断裂交汇处应力积累，遇到高速的阻碍体，阻碍体发生破裂有关。研究区西部新生代印度?欧亚板块的碰撞挤压和东部菲律宾海板块和太平洋板块对欧亚大陆的俯冲可能是这一地震的外部地球动力学来源，而江苏陆区及近海大陆架因地形高程差异引起的重力势则可能是此次地震的内部驱动力。