An evaluation of empirical and statistically based smoke plume injection height parametrisations used within air quality models

Air quality models are used to assess the impact of smoke from wildland fires, both prescribed and natural, on ambient air quality and human health. However, the accuracy of these models is limited by uncertainties in the parametrisation of smoke plume injection height (PIH) and its vertical distribution. We compared PIH estimates from the plume rise method (Briggs) in the Community Multiscale Air Quality (CMAQ) modelling system with observations from the 2013 California Rim Fire and 2017 prescribed burns in Kansas. We also examined PIHs estimated using alternative plume rise algorithms, model grid resolutions and temporal burn profiles. For the Rim Fire, the Briggs method performed as well or better than the alternatives evaluated (mean bias of less than ±5-20% and root mean square error lower than 1000 m compared with the alternatives). PIH estimates for the Kansas prescribed burns improved when the burn window was reduced from the standard default of 12 h to 3 h. This analysis suggests that meteorological inputs, temporal allocation and heat release are the primary drivers for accurately modelling PIH.

Satellites See the World’s Atmosphere

Satellite meteorology is a relatively new branch of the atmospheric sciences. The field emerged in the late 1950s during the Cold War and built on the advances in rocketry after World War II. In less than 70 years, satellite observations have transformed the way scientists observe and study Earth. This paper discusses some of the key advances in our understanding of the energy and water cycles, weather forecasting, and atmospheric composition enabled by satellite observations. While progress truly has been an international achievement, in accord with a monograph observing the centennial of the American Meteorological Society, as well as limited space, the emphasis of this chapter is on the U.S. satellite effort.

Scientific assessment of background ozone over the U.S.: Implications for air quality management

Ozone (O3) is a key air pollutant that is produced from precursor emissions and has adverse impacts on human health and ecosystems. In the U.S., the Clean Air Act (CAA) regulates O3 levels to protect public health and welfare, but unraveling the origins of surface O3 is complicated by the presence of contributions from multiple sources including background sources like stratospheric transport, wildfies, biogenic precursors, and international anthropogenic pollution, in addition to U.S. anthropogenic sources. In this report, we consider more than 100 published studies and assess current knowledge on the spatial and temporal distribution, trends, and sources of background O3 over the continental U.S., and evaluate how it inflattainment of the air quality standards. We conclude that spring and summer seasonal mean U.S. background O3 (USB O3), or O3 formed from natural sources plus anthropogenic sources in countries outside the U.S., is greatest at high elevation locations in the western U.S., with monthly mean maximum daily 8-hour average (MDA8) mole fractions approaching 50 parts per billion (ppb) and annual 4th highest MDA8s exceeding 60 ppb, at some locations. At lower elevation sites, e.g., along the West and East Coasts, seasonal mean MDA8 USB O3 is in the range of 20-40 ppb, with generally smaller contributions on the highest O3 days. The uncertainty in U.S. background O3 is around ±10 ppb for seasonal mean values and higher for individual days. Noncontrollable O3 sources, such as stratospheric intrusions or precursors from wildfires, can make significant contributions to O3 on some days, but it is challenging to quantify accurately these contributions. We recommend enhanced routine observations, focused fi studies, process-oriented modeling studies, and greater emphasis on the complex photochemistry in smoke plumes as key steps to reduce the uncertainty associated with background O3 in the U.S.

Interannual Variability in Baseline Ozone and Its Relationship to Surface Ozone in the Western U.S

Baseline ozone refers to observed concentrations of tropospheric ozone at sites that have a negligible influence from local emissions. The Mount Bachelor Observatory (MBO) was established in 2004 to examine baseline air masses as they arrive to North America from the west. In May 2012, we observed an O3 increase of 2.0-8.5 ppbv in monthly average maximum daily 8-hour average O3 mixing ratio (MDA8 O3) at MBO and numerous other sites in the western U.S. compared to previous years. This shift in the O3 distribution had an impact on the number of exceedance days. We also observed a good correlation between daily MDA8 variations at MBO and at downwind sites. This suggests that under specific meteorological conditions, synoptic variation in O3 at MBO can be observed at other surface sites in the western U.S. At MBO, the elevated O3 concentrations in May 2012 are associated with low CO values and low water vapor values, consistent with transport from the upper troposphere/lower stratosphere (UT/LS). Furthermore, the Real-time Air Quality Modeling System (RAQMS) analyses indicate that a large flux of O3 from the UT/LS in May 2012 contributed to the observed enhanced O3 across the western U.S. Our results suggest that a network of mountaintop observations, LiDAR and satellite observations of O3 could provide key data on daily and interannual variations in baseline O3.

Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM2.5: A case study for July 2011

We employed an optimal interpolation (OI) method to assimilate AIRNow ozone/PM2.5 and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) data into the Community Multi-scale Air Quality (CMAQ) model to improve the ozone and total aerosol concentration for the CMAQ simulation over the contiguous United States (CONUS). AIRNow data assimilation was applied to the boundary layer, and MODIS AOD data were used to adjust total column aerosol. Four OI cases were designed to examine the effects of uncertainty setting and assimilation time; two of these cases used uncertainties that varied in time and location, or "dynamic uncertainties." More frequent assimilation and higher model uncertainties pushed the modeled results closer to the observation. Our comparison over a 24-hr period showed that ozone and PM2.5 mean biases could be reduced from 2.54 ppbV to 1.06 ppbV and from -7.14 µg/m³ to -0.11 µg/m³, respectively, over CONUS, while their correlations were also improved. Comparison to DISCOVER-AQ 2011 aircraft measurement showed that surface ozone assimilation applied to the CMAQ simulation improves regional low-altitude (below 2 km) ozone simulation.

IMPLICATIONS

This paper described an application of using optimal interpolation method to improve the model's ozone and PM2.5 estimation using surface measurement and satellite AOD. It highlights the usage of the operational AIRNow data set, which is available in near real time, and the MODIS AOD. With a similar method, we can also use other satellite products, such as the latest VIIRS products, to improve PM2.5 prediction.

Preliminary evaluation of a regional atmospheric chemical data assimilation system for environmental surveillance

We report the progress of an ongoing effort by the Air Resources Laboratory, NOAA to build a prototype regional Chemical Analysis System (ARLCAS). The ARLCAS focuses on providing long-term analysis of the three dimensional (3D) air-pollutant concentration fields over the continental U.S. It leverages expertise from the NASA Earth Science Division-sponsored Air Quality Applied Science Team (AQAST) for the state-of-science knowledge in atmospheric and data assimilation sciences. The ARLCAS complies with national operational center requirement protocols and aims to have the modeling system to be maintained by a national center. Meteorology and chemistry observations consist of land-, air- and space-based observed and quality-assured data. We develop modularized testing to investigate the efficacies of the various components of the ARLCAS. The sensitivity testing of data assimilation schemes showed that with the increment of additional observational data sets, the accuracy of the analysis chemical fields also increased incrementally in varying margins. The benefit is especially noted for additional data sets based on a different platform and/or a different retrieval algorithm. We also described a plan to apply the analysis chemical fields in environmental surveillance at the Centers for Disease Control and Prevention.

The contribution of Saharan dust in PM(10) concentration levels in Anatolian Peninsula of Turkey

Sahara-originated dust is the most significant natural source of particulate matter; however, this contribution is still unclear in the Eastern Mediterranean especially in Western Turkey, where significant industrial sources and metropolitan areas are located. The Real-time Air Quality Modeling System (RAQMS) is utilized to explore the possible effects of Saharan dust on high levels of PM10 measured in Turkey. RAQMS model is compared with 118-air quality stations distributed throughout Turkey (81 cities) for April 2008. MODIS aerosol product (MOD04 for Terra and MYD04 for Aqua) is used to see columnar aerosol loading of the atmosphere at 550 nm (Aerosol optical depth (AOD) values found to be between 0.6 and 0.8 during the episode). High-resolution vertical profiles of clouds and aerosols are provided from CALIOP, on board of CALISPO satellite. The results suggest a significant contribution of Sahara dust to high levels of PM10 in Turkey with RAQMS and in situ time series showing similar patterns. The two data sets are found to be in agreement with a correlation of 0.87.