A system for developing and projecting PM2.5spatial fields to correspond to just meeting national ambient air quality standards

作者：Kelly, James T.^*; Jang, Carey J.; Timin, Brian; Gantt, Brett; Reff, Adam; Zhu, Yun; Long, Shicheng; Hanna, Adel

来源：Atmospheric Environment: X , 2019, 2: 100019.

DOI：10.1016/j.aeaoa.2019.100019

• Air quality modeling
• Base-line concentrations
• Computationally efficient
• Cross validation
• National ambient air quality standards
• PM2.5 projection
• Predictive capabilities
• Spatial prediction modeling

PM2.5concentration fields that correspond to just meeting national ambient air quality standards (NAAQS) are useful for characterizing exposure in regulatory assessments. Computationally efficient methods that incorporate predictions from photochemical grid models (PGMs) are needed to realistically project baseline concentration fields for these assessments. Thorough cross validation (CV) of hybrid spatial prediction models is also needed to better assess their predictive capability in sparsely monitored areas. In this study, a system for generating, evaluating, and projecting PM2.5spatial fields to correspond with just meeting the PM2.5NAAQS is developed and demonstrated. Results of ten-fold CV based on standard and spatial cluster withholding approaches indicate that performance of three spatial prediction models improves with decreasing distance to the nearest neighboring monitor, improved PGM performance, and increasing distance from sources of PM2.5heterogeneity (e.g., complex terrain and fire). An air quality projection tool developed here is demonstrated to be effective for quickly projecting PM2.5spatial fields to just meet NAAQS using realistic spatial response patterns based on air quality modeling. PM2.5tends to be most responsive to primary PM2.5emissions in urban areas, whereas response patterns are relatively smooth for NOx and SO2emission changes. On average, PM2.5is more responsive to changes in anthropogenic primary PM2.5emissions than NOx and SO2emissions in the contiguous U.S.

• 出版日期2019-4
• 单位University of North Carolina at Chapel Hill; The University of North Carolina at Chapel Hill; The University of North carolina at Chapel Hill; 华南理工大学