An approach to characterize within-grid concentration variability in air quality models

被引:9
作者
Ching, Jason [1 ]
Majeed, Mohammed A. [2 ]
机构
[1] Univ N Carolina Chapel Hill, Inst Environm, Hillsborough, NC 27278 USA
[2] Delaware Dept Nat Resources & Environm Control, Div Air Qual, New Castle, DE USA
基金
美国国家环境保护局;
关键词
Subgrid variability; Fine-scale AQ modeling; Concentration variability; Exposure assessments; HETEROGENEOUS LAND SURFACES; SUBGRID VARIABILITY; SCALE; DISPERSION; IMPACT; CHEMISTRY; VELOCITY; CMAQ;
D O I
10.1016/j.atmosenv.2011.11.006
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A new methodology to obtain subgrid air quality concentration variability (SGV) as distribution functions is described. Grid-based air quality models provide deterministic single value outcomes and thus do not represent concentration spatial details which can vary widely especially within urban and highly industrialized areas. While such spatial details can be obtained by running grid-based regional-scale air quality models at finer resolution or by employing local-scale models, such implementation may be impractical for performing a variety of applications, e.g., health exposure assessments. Strategically we propose a paradigm that can provide operational AQ models with supplemental estimates of SGV distributions as analytic functions provided on hourly and grid-by-grid bases. We illustrate and discuss this prototype implementation for a case study of benzene for several 12-km grid cells in the Wilmington, Delaware area. For this effort the contribution to SGV is limited to that from fine grid emissions distributions. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:348 / 360
页数:13
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