Understanding the efficiency and variability of photochemical ozone (O3) production from western wildfire plumes is important to accurately estimate their influence on North American air quality. A set of photochemical measurements were made from the NOAA Twin Otter research aircraft as a part of the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment. We use a zero-dimensional (0-D) box model to investigate the chemistry driving O3 production in modeled plumes. Modeled afternoon plumes reached a maximum O3 mixing ratio of 140 ± 50 ppbv (average ± standard deviation) within 20 ± 10 min of emission compared to 76 ± 12 ppbv in 60 ± 30 min in evening plumes. Afternoon and evening maximum O3 isopleths indicate that plumes were near their peak in NOx efficiency. A radical budget describes the NOx volatile - organic compound (VOC) sensitivities of these plumes. Afternoon plumes displayed a rapid transition from VOC-sensitive to NOx-sensitive chemistry, driven by HOx (=OH + HO2) production from photolysis of nitrous acid (HONO) (48 ± 20% of primary HOx) and formaldehyde (HCHO) (26 ± 9%) emitted directly from the fire. Evening plumes exhibit a slower transition from peak NOx efficiency to VOC-sensitive O3 production caused by a reduction in photolysis rates and fire emissions. HOx production in evening plumes is controlled by HONO photolysis (53 ± 7%), HCHO photolysis (18 ± 9%), and alkene ozonolysis (17 ± 9%).
© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).CORRESPONDING AUTHOR: Ben Kaldunski, ben.kaldunski@gmail.com; bkaldunski@wisc.edu
Satellite-based and high-altitude airborne remotely sensed air quality data complement land-based and routinely commercial-flight and other measurement-campaign acquired remotely sensed and in situ observations. It is important to optimize the combination and placement of these wide ranges of measurements and data acquisition options for cost-effectiveness. Under this initiative we attempt to quantify the gain by a regional state-of-the-science chemical data assimilation and chemical transport modeling system when incremental sets of observation are acquired into the system. This study represents a first step in a series of steps to ingest such proposed incremental additions of observation. The efficacy of such proposals is quantified systematically by Observation Simulation System Experiments (OSSEs). We compared two end-to-end regional air quality forecasting simulations using: (a) the Weather Forecasting and Research (WRF) regional application initialized by the U.S. national Weather Service (NWS) Global Forecasting System (GFS) coupled with the U.S. Environmental Protection Agency Community Multi-scale Air Quality (CMAQ) chemical model (Byun and Schere 2006), and (b) the same as above but with a new GFS enhanced by assimilating a fictitious addition of Atmospheric Infrared Sounder (AIRS) retrieved radiances at 13 km spatial resolution at nadir from a proposed geostationary satellite positioned over 75oW staring over the U. S. Both sensitivity runs were performed in 12 km horizontal grid resolution and with daily initialization for 12 days between July 29 and August 9 2005. Noticeable forecast skill improvement in surface concentration for O-3 and particulate matter smaller than 2.5 mu m in diameter (PM2.5) was achieved.
Barbara Dix (1), Rainer Volkamer (1,2), Sunil Baidar (1,2), Theodore Koenig (1,2), Sean Coburn (1,2), Ivan Ortega (1,2), Greg Huey (3), Eric Apel (4), Lucy Carpenter (5), Mathew Evans (5), Tomas Sherwin (5), Doug Kinnison (4), Jean-Francois Lamarque (4), Alfonso Saiz-Lopez (6), Brad Pierce (7), Daniel Jacob (8), Johan Schmidt (8), Elliot Atlas (9), Laura Pan (4), Ross Salawitch (10), and the TORERO and CONTRAST Team
We use ozone and carbon monoxide measurements from the Tropospheric Emission Spectrometer (TES), model estimates of Ozone, CO, and ozone pre-cursors from the Real-time Air Quality Modeling System (RAQMS), and data from the NASA DC8 aircraft to characterize the source and dynamical evolution of ozone and CO in Asian wildfire plumes during the spring ARCTAS campaign 2008. On the 19 April, NASA DC8 O-3 and aerosol Differential Absorption Lidar (DIAL) observed two biomass burning plumes originating from North-Western Asia (Kazakhstan) and South-Eastern Asia (Thailand) that advected eastward over the Pacific reaching North America in 10 to 12 days. Using both TES observations and RAQMS chemical analyses, we track the wildfire plumes from their source to the ARCTAS DC8 platform. In addition to photochemical production due to ozone pre-cursors, we find that exchange between the stratosphere and the troposphere is a major factor influencing O-3 concentrations for both plumes. For example, the Kazakhstan and Siberian plumes at 55 degrees North is a region of significant springtime stratospheric/tropospheric exchange. Stratospheric air influences the Thailand plume after it is lofted to high altitudes via the Himalayas. Using comparisons of the model to the aircraft and satellite measurements, we estimate that the Kazakhstan plume is responsible for increases of O-3 and CO mixing ratios by approximately 6.4 ppbv and 38 ppbv in the lower troposphere (height of 2 to 6 km), and the Thailand plume is responsible for increases of O-3 and CO mixing ratios of approximately 11 ppbv and 71 ppbv in the upper troposphere (height of 8 to 12 km) respectively. However, there are significant sources of uncertainty in these estimates that point to the need for future improvements in both model and satellite observations. For example, it is challenging to characterize the fraction of air parcels from the stratosphere versus those from the fire because of the low sensitivity of the TES CO estimates used to mark stratospheric air versus air parcels affected by the smoke plume. Model transport uncertainties, such as too much dispersion, results in a broad plume structure from the Kazakhstan fires that is approximately 2 km lower than the plume observed by aircraft. Consequently, the model and TES data do not capture the photochemical production of ozone in the Kazakhstan plume that is apparent in the aircraft in situ data. However, ozone and CO distributions from TES and RAQMS model estimates of the Thailand plume are within the uncertainties of the TES data. Therefore, the RAQMS model is better able to characterize the emissions from this fire, the mixing of ozone from the stratosphere to the plume, and the photochemical production and transport of ozone and ozone pre-cursors as the plume moves across the Pacific.
Performance of an air quality prediction may suffer with problems due to uncertainties in meteorological forecasts, lack of event-based real-life emissions variations such as forest fires, and inaccurate dynamic boundary conditions representing effects of long-range transport events. The main objective of this article is to demonstrate the combined synergistic effect of incremental reduction of uncertainties in the model inputs for improving air quality predictions. Effects of improved meteorological inputs, emissions, and initial and boundary conditions, through the use of in-situ measurements and satellite-retrieved information are studied for the continental US domains utilizing the Community Multiscale Air Quality (CMAQ) model. In this extended abstract, only the impacts of improved initial and boundary conditions are discussed.
We examine the photochemical processes governing the production of ozone in smoke from large Siberian fires that formed in July 2006 using colocated O3and CO profiles as measured by the Tropospheric Emission Spectrometer as well as NO2and aerosol optical depths as measured by the Ozone Monitoring Instrument. The Real‐Time Air Quality Model (RAQMS) is used to explain the observed variations of O3. Enhanced levels of ozone up to 90 parts per billion (ppbv) are observed near and away from the Siberian fires (60°N and 100°E) when sunlight and NOxare available. We also observe significantly low O3amounts (less then 30 ppbv) in the smoke plume from Siberian fires in conjunction with optically thick aerosols. Despite this wide variance in observed ozone values, the mean ozone value for all observations of the smoke plume is close to background levels of approximately 55 ppbv in the free troposphere. Using RAQMS we show that optically thick aerosols in the smoke plume can substantially reduce the photochemical production of ozone and this can explain why the observed mean ozone amount for all plume observations is not much larger than background values of 55 ppbv. However, the anonymously low ozone amounts of 30 ppbv or less point toward other unresolved processes that reduce ozone below background levels in the plume.