Saliba Youssef, Bărbulescu Alina
Doctoral School, Technical University of Civil Engineering of Bucharest, 122-124 Lacul Tei Av., 020396 Bucharest, Romania.
Department of Civil Engineering, Transilvania University of Brașov, 5 Turnului Str., 900152 Brașov, Romania.
Toxics. 2024 Feb 25;12(3):177. doi: 10.3390/toxics12030177.
This study offers a detailed analysis of the fine particulate matter (PM) series in the Arabian Gulf zone, employing three interpolation models, Inverse Distance Weighting (IDW), Bicubic Spline Smoothing (BSS) and Spatio-Temporal Kriging (STK). Unique advancements include the use of complete temporal records in IDW, the management of edge effects in S with synthetic buffer points, and the application of STK to detrended data residuals. The results indicated that the BBS, particularly adept at handling boundary conditions, significantly outperformed the other methods. Compared to IDW, the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) decreased by 21%, 15%, and 21%, respectively, in BSS. Compared to STK, MAE, RMSE, and MAPE were lower with around 60%, 61%, and 58%, respectively in BSS. These findings underscore the efficacy of the BSS method in spatial interpolation for environmental monitoring, contributing to enhanced PM analysis and public health management in the region.
本研究对阿拉伯湾地区的细颗粒物(PM)系列进行了详细分析,采用了三种插值模型,即反距离加权法(IDW)、双三次样条平滑法(BSS)和时空克里金法(STK)。独特的进展包括在IDW中使用完整的时间记录,利用合成缓冲点处理S中的边缘效应,以及将STK应用于去趋势化数据残差。结果表明,特别擅长处理边界条件的BSS明显优于其他方法。与IDW相比,BSS中的平均绝对误差(MAE)、均方根误差(RMSE)和平均绝对百分比误差(MAPE)分别降低了21%、15%和21%。与STK相比,BSS中的MAE、RMSE和MAPE分别低约60%、61%和58%。这些发现强调了BSS方法在环境监测空间插值中的有效性,有助于加强该地区的PM分析和公共卫生管理。