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首页> 外文期刊>Journal of the air & waste management association >Revised Algorithm for Estimating Light Extinction from IMPROVE Particle Speciation Data
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Revised Algorithm for Estimating Light Extinction from IMPROVE Particle Speciation Data

机译:从IMPROVE粒子形态数据估算消光的修正算法

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摘要

The Interagency Monitoring of Protected Visual Environments (IMPROVE) particle monitoring network consists of approximately 160 sites at which fine participate matter (PM_(2.5)) mass and major species concentrations and course particulate matter (PM_(10)) mass concentrations are determined by analysis of 24-hr duration sampling conducted on a 1-day-in-3 schedule. A simple algorithm to estimate light extinction from the measured species concentrations was incorporated in the 1999 Regional Haze Rule as the basis for the haze metric used to track haze trends. A revised algorithm was developed that is more consistent with the recent atmospheric aerosol literature and reduces bias for high and low light extinction extremes. The revised algorithm differs from the original algorithm in having a term for estimating sea salt light scattering from Cl~- ion data, using 1.8 instead of 1.4 for the mean ratio of organic mass to measured organic carbon, using site-specific Rayleigh scattering based on site elevation and mean temperature, employing a split component extinction efficiency associated with large and small size mode sulfate, nitrate and organic mass species, and adding a term for nitrogen dioxide (NO_2) absorption for sites with NO_2 concentration information. Light scattering estimates using the original and the revised algorithms are compared with nephelometer measurements at 21 IMPROVE monitoring sites. The revised algorithm reduces the underprediction of high haze periods and the overprediction of low haze periods compared with the performance of the original algorithm. This is most apparent at the hazier monitoring sites in the eastern United States. For each site, the PM_(10) composition for days selected as the best 20% and the worst 20% haze condition days are nearly identical regardless of whether the basis of selection was light scattering from the original or revised algorithms, or from nephelometer-measured light scattering.
机译:受保护的视觉环境机构间监视(IMPROVE)粒子监视网络由大约160个站点组成,通过分析确定了精细参与物质(PM_(2.5))质量和主要物种浓度以及过程颗粒物质(PM_(10))质量浓度以3天1天的时间表进行24小时持续时间采样。 1999年的“区域雾霾规则”中纳入了一种简单的算法,可以根据所测物种的浓度估算光的消光程度,以此作为追踪雾霾趋势的雾度指标的基础。开发了一种修订算法,该算法与最新的大气气溶胶文献更加一致,并减少了高光和低光消光极限的偏差。修改后的算法与原始算法的不同之处在于,它具有一个根据Cl〜-离子数据估算海盐光散射的术语,即使用1.8而不是1.4表示有机物质量与所测有机碳的平均比率,并使用基于站点海拔和平均温度,采用与大,小尺寸模式的硫酸盐,硝酸盐和有机物质有关的拆分组分消光效率,并为具有NO_2浓度信息的站点添加二氧化氮(NO_2)吸收项。使用原始算法和修订算法对光散射的估计值与21个IMPROVE监测站点的浊度计测量值进行比较。与原始算法的性能相比,改进后的算法减少了高雾度时段的低估和低雾度时段的高估。这在美国东部的雾霾监测站最为明显。对于每个站点,雾天最佳20%和雾天20%最差的几天的PM_(10)组成几乎相同,无论选择的基础是来自原始算法还是经过修订的算法,还是来​​自浊度计-测量的光散射。

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