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首页> 外文会议>Air Waste Management Association's annual conference exhibition >CAMx4 Model Performance for 3 Annual Applications (2001-3) Supporting Regional Haze and PM2.5 Regulations
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CAMx4 Model Performance for 3 Annual Applications (2001-3) Supporting Regional Haze and PM2.5 Regulations

机译：CAMX4模型表现为3年度申请（2001-3）支持区域雾霾和PM2.5条例

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The United States Environmental Protection Agency (EPA) recently passed the regional haze rule to improve visibility in Class I areas by 2060. Additionally, many counties in the Eastern United States will be classified as non-attainment for the National Ambient Air Quality Standard (NAAQS) for the PM2.5 annual standard. EPA guidance recommends the application of 3-D Eulerian grid models for an entire calendar year to fully capture the seasonal variation in PM2.5 formation in various regions of the United States. EPA guidance states that an attainment test for the PM2.5 NAAQS will require the use of chemically speciated PM relative reduction factors by season. The components of the Federal Land Manager’s visibility equation match up very closely to the prominent chemical constituents of PM2.5: nitrate ion, sulfate ion, ammonium ion, organic carbon, elemental carbon, and soil. Since PM2.5 consists of a variety of species that may dominate the total mass in different times of the year, it is critical that Eulerian grid models appropriately capture seasonal variations in formation processes, transport, emissions, and deposition. This paper outlines modeling system performance for 24 hr averaged chemically speciated PM2.5 by month for 3 consecutive annual simulations (January 2001 to December 2003). Monitors with chemically speciated PM2.5 data in the Upper Midwest are used for model performance evaluation. PM2.5 sulfate ion is over-predicted during the summer months in all 3 simulations. PM2.5 nitrate ion is over-predicted in the fall and winter months in all 3 simulations. Over-predictions for the entire year are seen for PM2.5 ammonium ion in all 3 simulations. PM2.5 organic carbon is under-predicted during the entire year and shows large under-predictions in the summer months. PM2.5 sulfate and organic carbon showed the most variability in performance from year to year. PM2.5 nitrate and ammonium are surprisingly consistent in performance from year to year. The performance for PM2.5 elemental carbon is fairly good throughout the year and PM2.5 soil performance is adequate for applications in the Eastern United States. The modeling system performance strengths match up well with near-term intended regulatory applications for sulfur dioxide and nitrogren oxides emissions strategy development.
机译：美国环境保护局（EPA）最近通过了2060年的地区区域雾霾规则来提高I级地区的知名度。此外，美国东部的许多县将被归类为国家环境空气质量标准（NAAQS） ）对于PM2.5年度标准。 EPA指南推荐的3-d欧拉网格模型的整个历年的应用，充分抓住在美国的各地区PM2.5形成的季节性变化。环保署指导指出，PM2.5 NAAQ的达到试验将需要在季节使用化学标准的PM相对降低因子。联邦土地管理者的知名度方程的部件匹配非常接近PM2.5的突出的化学成分：硝酸根离子，硫酸根离子，铵离子，有机碳，元素碳和土壤。由于PM2.5因此由各种各样的物种组成，可能在一年中不同时间占主导地位，因此欧拉网格模型至关重要，以适当地捕获地层过程，运输，排放和沉积的季节性变化。本文概述了24小时平均的系统性能，以34小时平均化学规格PM2.5连续3年度仿真（2001年1月至2003年12月）。上部中西部的化学标准PM2.5数据的监视器用于模型性能评估。在所有3个模拟中，在夏季，PM2.5硫酸根离子过度预测。在所有3个模拟中，在秋季和冬季，PM2.5硝酸硝酸离子过度预测。在所有3个模拟中，在所有3个铵离子中看到整年过度预测。在整年期间预测PM2.5有机碳，并在夏季显示大量预测。 PM2.5硫酸盐和有机碳显示出年度迄今为止的性能最大程度。 PM2.5硝酸铵和铵在年度迄今为止的性能方面令人惊讶。全年PM2.5元素碳的性能相当良好，PM2.5土壤性能适用于美国东部的应用。模型系统性能优势与二氧化硫和硝基氧化氮排放策略发育的近期预期的监管应用相匹配。

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