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首页> 外文期刊>Environmental Science & Technology >Propagation of Uncertainty in Hourly Utility NO{sub}x Emissions through a Photochemical Grid Air Quality Model: A Case Study for the Charlotte, NC, Modeling Domain
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Propagation of Uncertainty in Hourly Utility NO{sub}x Emissions through a Photochemical Grid Air Quality Model: A Case Study for the Charlotte, NC, Modeling Domain

机译：通过光化学网格空气质量模型的小时效用NO {sub} x排放不确定性的传播：北卡罗来纳州夏洛特市的一个案例研究

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摘要

One of the major hypothesized sources of uncertainties in air quality model inputs is the emission inventory. A probabilistic hourly NO{sub}X emission inventory for 32 units of nine coal-fired power plants in the Charlotte domain for the year 1995 was propagated through the Multistage Air Quality Simulation Platform (MAQSIP). The inventory was developed using time series techniques. Time series for a 4-d episode were simulated and propagated through the air quality model 50 times in order to represent the ranges of uncertainty in hourly emissions and predicted ozone levels. Intra-unit autocorrelation in emissions and inter-unit dependence were accounted for. The range of uncertainty in predicted ozone was greater when inter-unit dependence was included as compared to when units were treated as statistically independent. Uncertainties in maximum ozone hourly or 8-h concentrations at a specific location could be attributed to a specific power plant based upon regression analysis. Out of 3969 grid cells in the modeling domain, there were 43 and 1654 grid cells with a probability greater than 0.9 of exceeding a 1-h 120 ppb standard and an 8-h 80 ppb standard, respectively. The time series of predicted ozone values had similar autocorrelation as compared to monitored data. The implications of these results for air quality management are addressed.
机译：假设的空气质量模型输入不确定性的主要来源之一是排放清单。通过多级空气质量模拟平台（MAQSIP）传播了1995年夏洛特地区9个燃煤电厂的32个机组的每小时NO {sub} X概率每小时排放清单。使用时间序列技术开发了清单。模拟了4天事件的时间序列，并通过空气质量模型传播了50次，以表示每小时排放量和预测臭氧水平的不确定性范围。排放中的单元内自相关和单元间相关性被考虑在内。当包含单元间依赖性时，与将单元视为统计独立时相比，预测臭氧的不确定性范围更大。根据回归分析，特定地点每小时最大臭氧浓度或8小时浓度的不确定性可归因于特定电厂。在建模领域的3969个网格单元中，分别有43个和1654个网格单元的概率分别超过1小时120 ppb标准和8小时80 ppb标准。与监测数据相比，预测臭氧值的时间序列具有相似的自相关。解决了这些结果对空气质量管理的影响。

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