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Tanya L. Otte

1. Introduction Complex, limited-area, multipollutant air quality models typically obtain meteorological fields from Eulerian (gridded) meteorological models. It is well known that the meteorological conditions exert a significant influence on air quality (e.g., Flaum et al. 1996 ; Milanchus et al. 1998 ). For nearly two decades, there has been a great interest in assessing the impact that meteorological modeled fields have on air quality model simulations. Pielke and Uliasz (1998) and

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Tanya L. Otte

1. Introduction For two decades, limited-area Eulerian (or gridded) air quality models have been forced by meteorological fields that are generated by Eulerian meteorological models, in part, because meteorological observations and archived forecast fields do not exist at high enough temporal and spatial resolutions to capture atmospheric variables (e.g., mixing depth, column temperature, and wind profiles) that are important for regional-scale chemical transport modeling. Meteorological models

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S. Kondragunta, P. Lee, J. McQueen, C. Kittaka, A. I. Prados, P. Ciren, I. Laszlo, R. B. Pierce, R. Hoff, and J. J. Szykman

1. Introduction Congressional mandate (H. R. 4. Energy Act of 2002) required the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) to develop and deploy an air quality modeling system capable of issuing nationwide hourly ozone and PM2.5 (particles smaller than 2.5 μ m in median diameter) forecast guidance. In response to the mandate, NOAA has developed an air quality forecast capability in partnership with the U.S. Environmental Protection Agency (EPA). The

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Zhan Zhao, Shu-Hua Chen, Michael J. Kleeman, Mary Tyree, and Dan Cayan

(SoCAB) ( Fig. 1a ). The annual average PM 2.5 concentration in SJV and SoCAB were 21.5 μ g m −3 and 19.7 μ g m −3 , respectively, during 2007/08. These concentrations were the highest nationwide ( Mahmud et al. 2010 ) and were much higher than the current National Ambient Air Quality Standard of 15 μ g m −3 . In the years 2005–07, all of the “top six” counties with the highest O 3 concentrations over the entire United States were located in SJV and SoCAB ( Howard et al. 2010 ). The pollutants

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Zhan Zhao, Shu-Hua Chen, Michael J. Kleeman, and Abdullah Mahmud

1. Introduction The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report ( Solomon et al. 2007 ) states that “most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.” Temperature is a decisive meteorological variable for regional climate and air quality. A temperature change can result in a change in atmospheric and oceanic circulations ( Nitta and

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Stephen F. Mueller

1. Introduction Air quality models are used extensively for environmental planning and determining compliance with air quality regulations. Model performance is typically evaluated against observations. As described by regulatory guidance issued by the U.S. Environmental Protection Agency (EPA), various error metrics are considered valuable for determining the ability of a model to capture accurately the important links between emissions and levels of air pollutants ( U.S. EPA 2007 ). All of

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Scott Beaver, Saffet Tanrikulu, Ahmet Palazoglu, Angadh Singh, Su-Tzai Soong, Yiqin Jia, Cuong Tran, Bruce Ainslie, and Douw G. Steyn

1. Introduction Photochemical air quality model (AQM; Russell and Dennis 2000 ) simulations are increasingly used for regulatory purposes ( Fine et al. 2003 ). They provide technical information to support air quality planning decisions. The resulting policies can affect billions of dollars worth of public health and economic activity annually ( Yang et al. 2005 ). Because of the large stakes involved, policy makers require confidence that simulation results are valid. For use in policy making

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Daiwen Kang, Rohit Mathur, Kenneth Schere, Shaocai Yu, and Brian Eder

1. Introduction The skill of an air quality forecast system is gauged by how well the modeling system predicts species concentrations in relation to threshold values. These events, which are referred to as “exceedances” and “nonexceedances,” can be evaluated using categorical metrics. Current categorical metrics used in model evaluations (e.g., Kang et al. 2005 ) measure the model’s ability to predict an exceedance using a fixed threshold mixing ratio (or “clear cut”), and the metrics are

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Hye-Ryun Oh, Chang-Hoi Ho, Doo-Sun R. Park, Jinwon Kim, Chang-Keun Song, and Sun-Kyong Hur

( Baek and Koo 2008 ; Gyeonggi Research Institute 2011 ). The government invested approximately 4 trillion South Korean won 1 in the act for the first 10 years. The second phase of the 10-Year Act commenced in 2015 ( http://eng.me.go.kr/eng/web/index.do?menuId=238 ). It includes various air quality control strategies, such as enforcing the installation of particulate filters in diesel engines, encouraging the use of eco-friendly (i.e., hybrid and electric) cars, and increasing air pollutant

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Xiangde Xu, Lian Xie, Xinghong Cheng, Jianming Xu, Xiuji Zhou, and Guoan Ding

1. Introduction As the date for the 2008 Olympic Summer Games was approaching, one of the biggest issues that faced the game’s organizers was accurately forecasting the air quality in the host city of Beijing, China. Forecasters at the Beijing Meteorological Bureau relied on coupled numerical weather prediction (NWP) and atmospheric chemistry models, such as “Models-3” ( Dennis et al. 1996 ), a widely used operational air quality forecast system developed by the U.S. Environmental Protection

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