论文标题
美国年度硫酸盐浓度的机械模型
A Mechanistic Model of Annual Sulfate Concentrations in the United States
论文作者
论文摘要
我们开发了一种机械模型，以分析燃煤发电厂二氧化硫排放对美国中部硫酸盐平均浓度的影响。多变量Ornstein-uhlenbeck（OU）过程用于近似基础时空化学传输过程的动力学，并利用其分布性能指定空间数据的新概率模型（即，空间引用的数据，无时间复制），以将其视为一个被视为乘坐时间或时间的方法，以观察到一个时间或时间上的程序。空气污染运输动力学决定了我们大气硫酸盐模型的平均值和协方差结构，从而使我们能够推断出哪些过程动态正在推动观察到的空气污染浓度。我们使用这些推断的动力学来评估烟气脱硫（FGD）技术对人类暴露于硫酸盐气溶胶的调节影响。
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.
