A comparison between 2010 and 2006 air quality and meteorological conditions, and emissions and boundary conditions used in simulations of the AQMEII-2 North American domain

A multi-model assessment for the 2006 and 2010 simulations under the Air Quality Model Evaluation International Initiative (AQMEII) phase 2 over North America: Part I. Indicators of the sensitivity of O3 and PM2.5 formation regimes

“…6def). Analyses of the emissions support this finding, indicating NA/U.S.-wide decreases in summertime average NO x daily emissions between 2006 and 2010, especially near point sources and urban centers (Pouliot et al, 2015;Stoeckenius et al, 2015;Yahya et al, 2015b). There is however a dipole in the sign of NO xand VOC-limited changes between northern NA1-NA2 and NA3.…”

“…The chemical 2006 and 2010 ICs and BCs are from global 3-h Monitoring Atmospheric Composition and Climate e Interim Implementation (MACC-II; http://www.gmesatmosphere.eu/) fields (Inness et al, 2013). Further details regarding both the 2006e2010 emission and IC and BC changes for the AQMEII-2 NA domain are found in this issue (Pouliot et al, 2015;Stoeckenius et al, 2015;Yahya et al, 2015b).…”

Numerical Model-Based Artificial Neural Network Model and Its Application for Quantifying Impact Factors of Urban Air Quality

“…In some cases, severe air pollution is caused by unfavorable weather rather than abrupt increase of emissions (Cheng et al, 2007;Zheng et al, 2015), and the reduction of emission does not always result in the decrease of pollutant concentrations (Stoeckenius et al, 2015). Synoptic-scale circulation governs local meteorological conditions and is effective to identify air pollution level (Oanh et al, 2005).…”

Preface

“…This Atmospheric Environment AQMEII issue has therefore been organized as follows. The first set of papers Soares et al, 2015;Giordano et al, 2015;Stoeckenius et al, 2015) focuses on setting-up the case study by presenting the common emissions and boundary conditions used by all modeling groups and a comparison of the observed meteorological and air quality conditions in 2006 and 2010 over North America. These model input and overview papers are followed by collective analysis papers describing operational, diagnostic and probabilistic evaluation of participating models (Im et al, 2014a,b;Brunner et al, 2015;Wang et al, 2015a;Campbell et al, 2015), with some papers specifically focusing on the role of feedback effects on model meteorological and chemical performance (Makar et al, 2015a,b;Kong et al, 2015;, the role of assumptions about aerosol optical properties on simulated aerosol optical depth , and the role of different chemical mechanisms on simulated gas phase concentrations .…”