Characterization of pollution transport into Texas using OMI and TES satellite,GIS and in situ data,and HYSPLIT back trajectory analyses: implications for TCEQ State Implementation Plans

Transport of pollution from remote sources into the state of Texas has been shown by modeling techniques, satellite, and in situ data. Attaining a better understanding of the impact (i.e., temporally) of remote pollution sources will provide a more robust/quantifiable basis for State Implementation Plans (SIPs) that govern air quality. Utilizing Tropospheric Emission Spectrometer (TES) and Ozone Monitoring Instrument (OMI) and in situ data for ozone (O₃) and nitrogen dioxide (NO₂) and Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT), we assess whether high-pollution events in Texas are primarily sourced locally (i.e., within Texas) or remotely. We focus on TES and OMI dates that exemplify high O₃ and NO₂, over Texas’s lower troposphere from August 5, 2006, to June 21, 2009. For all dates and altitudes, 4-day back trajectory analyses, exemplified by high TES O₃, show that remotely sourced from the Gulf of Mexico, Southeast USA, Midwest USA, Northeast USA, the Atlantic Ocean, Pacific Ocean, Mexico to Texas. The only exception is air at 1 km on July 22, 2006, which shows that air at this altitude is sourced within Texas. Throughout half of the eastern portion of Texas, TES shows O₃ enhancements in the boundary layer and OMI shows O₃ and NO₂ enhancements via tropospheric column profiles (O₃ between 75 and 90 ppbv; NO₂ ≥5.5 molecules cm^?2). These enhancements complement the HYSPLIT 4-day trajectory analyses, which gives further indication that they are influenced by transport from remote sources. Dates with co-located satellite and in situ data (e.g., August 2, 2005) further exemplify the need to consider satellite and in situ data and modeling data/forecasts when creating SIPs for compliance with Environmental Protection Agency and the Texas Commission on Environmental Quality air quality standards. Despite the fact that quantifying local versus remote sources is in its early stages, Texas has become increasingly compliant with Environmental Protection Agency (EPA) regulations. Environmental Systems Research Institute’s ArcGIS exemplifies the noticeable decrease in the number of days that locales in Texas exceed EPA’s limit for O₃. From 2005 to 2009, population standard deviation and standard error of the mean, and true sample deviation of the sample mean for O₃ and NO₂, at all 16 monitoring sites distributed throughout Texas, are temporally consistent and small—reinforcing the reliability of in situ data as they are consistent throughout. This investigation has global implications for regions within countries that enforce air quality mandates. Such governing bodies should consider utilizing data assimilation (of in situ data) for air quality prediction as a part of the governmental process that produces such laws. This could potentially keep regions more accountable for emissions both locally and far from high source points.