Stochastic modeling of atmospheric pollution: a spatial time-series framework. Part II: application to monitoring monthly sulfate deposition over Europe |
| |
| Institution: | 1. State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, and Center for Environment and Health, Peking University, Beijing 100871, China;2. International Laboratory for Air Quality & Health (ILAQH), School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, Brisbane, QLD 4001, Australia |
| |
| Abstract: | A spatial time-series framework is adopted for stochastic modeling of monthly averaged sulfate deposition over Europe. The sulfur concentration data used in this study were measured at the European Monitoring and Evaluation Program (EMEP) monitoring network from January 1980 to December 1988. Parametric temporal trend and residual models, associated with long-term (linear trend or annual periodicity) and short-term (seasonal) concentration variability, respectively, are first established at monitoring stations. The resulting model parameters are regionalized in space to arrive at parametric trend and residual models at any unmonitored location. Stochastic simulation is performed for prediction and modeling of joint uncertainty regarding unknown sulfur concentration levels at unmonitored spatial locations and time instants. The case study illustrates the applicability of the proposed spatial time series framework to a real-world data set. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
