Effects of model resolution on the interpretation of satellite NO 2 observations

Abstract. Inference of NO x emissions (NO+NO 2 ) from satellite observations of tropospheric NO 2 column requires knowledge of NO x lifetime, usually provided by chemical transport models (CTMs). However, it is known that species subject to non-linear sources or sinks, such as ozone, are susceptible to biases in coarse-resolution CTMs. Here we compute the resolution-dependent bias in predicted NO 2 column, a quantity relevant to the interpretation of space-based observations. We use 1-D and 2-D models to illustrate the mechanisms responsible for these biases over a range of NO 2 concentrations and model resolutions. We find that predicted biases are largest at coarsest model resolutions with negative biases predicted over large sources and positive biases predicted over small sources. As an example, we use WRF-CHEM to illustrate the resolution necessary to predict 10 AM and 1 PM NO 2 column to 10 and 25% accuracy over three large sources, the Four Corners power plants in NW New Mexico, Los Angeles, and the San Joaquin Valley in California for a week-long simulation in July 2006. We find that resolution in the range of 4–12 km is sufficient to accurately model nonlinear effects in the NO 2 loss rate.

[1]  Kelly Chance,et al.  Global partitioning of NOx sources using satellite observations: relative roles of fossil fuel combustion, biomass burning and soil emissions. , 2005, Faraday discussions.

[2]  Oliver Wild,et al.  Global tropospheric ozone modeling: Quantifying errors due to grid resolution , 2006 .

[3]  J. Thornton,et al.  Ozone production rates as a function of NOx abundances and HOx production rates in the Nashville urban plume , 2002 .

[4]  Steffen Beirle,et al.  Megacity Emissions and Lifetimes of Nitrogen Oxides Probed from Space , 2011, Science.

[5]  Sanford Sillman,et al.  A regional scale model for ozone in the United States with subgrid representation of urban and power plant plumes , 1990 .

[6]  James F. Gleason,et al.  Algorithm for NO/sub 2/ vertical column retrieval from the ozone monitoring instrument , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[7]  J. Burrows,et al.  Satellite measurements of daily variations in soil NOx emissions , 2005 .

[8]  J. Pleim,et al.  Sub-grid-scale features of anthropogenic emissions of NOx and VOC in the context of regional eulerian models , 1996 .

[9]  Georg A. Grell,et al.  Fully coupled “online” chemistry within the WRF model , 2005 .

[10]  Steffen Beirle,et al.  Direct observation of two dimensional trace gas distribution with an airborne Imaging DOAS instrument , 2008 .

[11]  G. Grell,et al.  Satellite-observed US power plant NOx emission reductions and their impact on air quality - article no. L22812 , 2006 .

[12]  R. Cohen,et al.  Characterization of wildfire NO x emissions using MODIS fire radiative power and OMI tropospheric NO 2 columns , 2011 .

[13]  Steffen Beirle,et al.  Global distribution pattern of anthropogenic nitrogen oxide emissions: Correlation analysis of satellite measurements and model calculations , 2006 .

[14]  David J. Lary,et al.  A Method to Determine the Spatial Resolution Required to Observe Air Quality From Space , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[15]  K. Boersma,et al.  Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space , 2008 .

[16]  S. Beirle,et al.  Direct satellite observation of lightning-produced NO x , 2010 .

[17]  Thomas P. Kurosu,et al.  Global inventory of nitrogen oxide emissions constrained by space‐based observations of NO2 columns , 2003 .

[18]  J. Veefkind,et al.  Validation of Ozone Monitoring Instrument nitrogen dioxide columns , 2008 .

[19]  J. Burrows,et al.  Increase in tropospheric nitrogen dioxide over China observed from space , 2005, Nature.

[20]  Yongtao Hu,et al.  Dependence of ozone sensitivity analysis on grid resolution , 2006 .

[21]  A. Goldstein,et al.  The weekend effect within and downwind of Sacramento: Part 2. Observational evidence for chemical and dynamical contributions , 2006 .

[22]  Naresh Kumar,et al.  Multiscale air quality modeling : application to southern California , 1994 .

[23]  Eric Bucsela,et al.  Observation of slant column NO2 using the super-zoom mode of AURA-OMI , 2011 .

[24]  Alice B. Gilliland,et al.  A method for evaluating spatially-resolved NO x emissions using Kalman filter inversion, direct sensitivities, and space-based NO 2 observations , 2008 .

[25]  W. Stockwell,et al.  The second generation regional acid deposition model chemical mechanism for regional air quality modeling , 1990 .

[26]  R. Cohen,et al.  Interannual variability in soil nitric oxide emissions over the United States as viewed from space , 2010 .

[27]  Andrew K. Mollner,et al.  Rate of Gas Phase Association of Hydroxyl Radical and Nitrogen Dioxide , 2010, Science.

[28]  John P. Burrows,et al.  Inverse modelling of the spatial distribution of NO x emissions on a continental scale using satellite data , 2005 .

[29]  D. Blake,et al.  Impact of organic nitrates on urban ozone production , 2010 .

[30]  K. F. Boersma,et al.  Near-real time retrieval of tropospheric NO 2 from OMI , 2006 .

[31]  R. Cohen,et al.  Space-based constraints on spatial and temporal patterns of NO(x) emissions in California, 2005-2008. , 2010, Environmental science & technology.