We develop a mechanistic model to analyze the impact of sulfur dioxide emissions from coal-fired power plants on average sulfate concentrations in the central United States. A multivariate Ornstein-Uhlenbeck (OU) process is used to approximate the dynamics of the underlying space-time chemical transport process, and its distributional properties are leveraged to specify novel probability models for spatial data (i.e., spatially-referenced data with no temporal replication) that are viewed as either a snapshot or a time-averaged observation of the OU process. Air pollution transport dynamics determine the mean and covariance structure of our atmospheric sulfate model, allowing us to infer which process dynamics are driving observed air pollution concentrations. We use these inferred dynamics to assess the regulatory impact of flue-gas desulfurization (FGD) technologies on human exposure to sulfate aerosols.
翻译:我们开发了一个机械模型,分析燃煤发电厂排放的二氧化硫对美国中部平均硫酸盐浓度的影响。一个多变的Ornstein-Uhlenbeck(OU)过程用来估计基础空间-时间化学运输过程的动态,其分布特性被用来确定空间数据的新概率模型(即空间参照数据,无时间复制),这些模型既可被视为对UU工艺的快速观察,也可视为对UU工艺的时平均观测。空气污染迁移动态决定了我们大气硫酸盐模型的中位和常态结构,使我们能够推算出哪些过程动态驱动观察到的空气污染浓度。我们利用这些推论的动力来评估氟气脱硫技术对人类接触硫酸气喷雾剂的监管影响。