Shuai Pan

The impact of observation nudging on simulated meteorology and ozone concentrations during DISCOVER-AQ 2013 Texas campaign

Accurate meteorological fields are imperative for correct chemical transport modeling. Observation nudging, along with objective analysis, is generally considered a lowcost and effective technique to improve meteorological simulations. However, the meteorological impact of observation nudging on chemistry has not been well characterized. This study involved two simulations to analyze the impact of observation nudging on simulated meteorology and ozone concentrations during the 2013 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Texas campaign period, using the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. The results showed improved correlations between observed and simulated parameters. For example, the index of agreement (IOA) improved by about 9 % for surface temperature and 6–11 % for surface zonal (U-WIND) and meridional (V-WIND) winds when observation nudging was employed. Analysis of a cold front event indicated that nudging improved the timing of wind transition during the front passage. Observation nudging also reduced the model biases for the planetary boundary layer height predictions. Additionally, the IOA for CMAQ simulated surface ozone improved by 6 % during the simulation period. The high-ozone episode on 25 September was a post-front ozone event in Houston. The small-scale morning wind shifts near the Houston Ship Channel combined with higher aloft ozone early morning likely caused the day’s ozone exceedance. While observation nudging did not recreate the wind shifts on that day and failed to reproduce the observed high ozone, analyses of surface and aircraft data found that observation nudging helped the model yield improved ozone predictions. In a 2 h period during the event, substantially better winds in the sensitivity case noticeably improved the ozone. The average IOA for ozone in the period increased from just over 0.4 to near 0.7. Further work on improving the capability of nudging to reproduce local meteorological events such as stagnations and wind reversals could enhance a chemical transport model’s skill for predicting high-ozone events.

Identification of chemical fingerprints in long-range transport of burning induced upper tropospheric ozone from Colorado to the North Atlantic Ocean

This study investigates a significant biomass burning (BB) event occurred in Colorado of the United States in 2012 using the Community Multi-scale Air Quality (CMAQ) model. The simulation reasonably reproduced the significantly high upper tropospheric O3 concentrations (up to 145ppb) caused by BB emissions. We find the BB-induced O3 was primarily affected by chemical reactions and dispersion during its transport. In the early period of transport, high NOx and VOCs emissions caused O3 production due to reactions with the peroxide and hydroxyl radicals, HO2 and OH. Here, NOx played a key role in O3 formation in the BB plume. The results indicated that HO2 in the BB plume primarily came from formaldehyde (HCHO+hv=2HO2+CO), a secondary alkoxy radical (ROR=HO2). CO played an important role in the production of recycled HO2 (OH+CO=HO2) because of its abundance in the BB plume. The chemically produced HO2 was largely converted to OH by the reactions with NO (HO2+NO=OH+NO2) from BB emissions. This is in contrast to the surface, where HO2 and OH are strongly affected by VOC and HONO, respectively. In the late stages of transport, the O3 concentration was primarily controlled by dispersion. It stayed longer in the upper troposphere compared to the surface due to sustained depletion of NOx. Sensitivity analysis results support that O3 in the BB plume is significantly more sensitive to NOx than VOCs.

Effects of Biomass Burning Emissions on Air Quality Over the Continental USA: A Three-Year Comprehensive Evaluation Accounting for Sensitivities Due to Boundary Conditions and Plume Rise Height

We report a comprehensive evaluation of the impacts of biomass burning on regional ozone and fine particulate matter (PM2.5) over the continental USA, southern Canada, and northern Mexico during 2012–2014 using the Community Multiscale Air Quality (CMAQ) chemical transport model. Inputs included the Fire INventory from National Center for Atmospheric Research (FINN) for fire emissions, Biogenic Emission Inventory System (BEIS) for biogenics, the US Environmental Protection Agency (USEPA)’s National Emissions Inventory of 2011 (NEI2011) for anthropogenic sources, and Weather Research and Forecasting (WRF) model fields for meteorology. In situ data were taken from the Texas Commission on Environmental Quality (TCEQ)’s Continuous Ambient Monitoring Stations (CAMS) and the USEPA’s Air Quality System (AQS) networks. This study has marked improvements over the previous biomass burning evaluations, which are as follows: (a) a significantly longer simulation episode; (b) use of 3-D dynamic boundary conditions; (c) grid nudging to improve meteorological fields; and (d) physically representative fire plume rise model. Observations showed ozone hot spots of 60–70 parts per billion (ppb) across the Western Mountain region and California. The model was able to reproduce these only in 2012, underpredicting in California otherwise. Monthly mean biomass impacts of 2–3 ppb, averaged over daylight hours (6:00–18:00 CST), were predicted for California and Idaho in 2012 and 2013. The largest impacts were predicted for summer 2013, adding 3 ppb in northern Mexico and southeastern Canada, and 1 ppb in Florida, New Mexico, and Colorado. For April 2014, the model predicted 1–2 ppb disparities in ozone over the southern USA; a 1–2 ppb impact in southeastern Oregon, northwestern Nevada, and southern Idaho during July 2014; and in August, up to 3 ppb changes in western California, Central Oregon, Idaho, southwestern Canada, and southern Georgia. The model was unable to accurately capture the high PM2.5 concentrations across the domain. Large monthly mean fire impacts of up to 10 μg m−3 were predicted for southeastern Canada in July 2012 and June and July 2013, and for Alabama, Georgia, Idaho, and southwestern Canada for October 2013. In June 2014, the model significantly underpredicted when the biomass impact was minimal, indicating that uncertainty in biomass emissions was not the probable cause for model-measurement error.

First Top‐Down Estimates of Anthropogenic NOx Emissions Using High‐Resolution Airborne Remote Sensing Observations

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor (Ce), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated Ce and meteorology played an important role in the calculation of oak pollen emissions. While Ce was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based Ce used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.

Quantifying the Impact of Biomass Burning Emissions on Major Inorganic Aerosols and Their Precursors in the U.S.

The primary sources for inorganic aerosols from biomass burning are rather negligible; but they are predominantly formed chemically following emission of their precursors (e.g., SO2, NH3, HOx, and NOx). The biomass burning contributions to some of the precursors can be considerable. Accordingly, we quantify the impact of the emissions on major inorganic aerosols in April-October 2012-2014 using a regional model simulation verified by extensive surface observations throughout the US. Simulated CO enhancements on an hourly basis are used to classify the US into weak-moderate (5 20 ppbv). This separation not only facilitates the identification of the spatial frequency of the impact but also helps to filter out non-impacted periods, enabling us to focus on long-term contributions. Despite the nonlinear responses of several trace gases to emissions, we observe increases (weak-moderate, strong) in daily surface SO42- (1.16±0.32, 6.57±4.65 nmol/m3), NO3- (0.36±0.63, 4.70±7.05 nmol/m3) and NH4+ (2.70±0.92, 17.82±15.17 nmol/m3) on a national scale. These primarily resulted from i) increases in daily surface SO2 (0.02±0.01, 0.10±0.07 ppbv), afternoon OH (1.28±4.24, 12.82±23.76 ppqv), and H2O2 (0.06±0.02, 0.10±0.08 ppbv), which may have accelerated the conversion of S(IV) to S(VI), and ii) increases in daily surface NH3 (1.08±0.73, 8.61±7.73 nmol/m3) and HNO3 (1.44±0.48, 7.15±4.25 nmol/m3), which could have produced more particle-phase NH4NO3. In the West, where atmospheric moisture is limited, enhanced SO42- leaves less available water for NH4NO3 to become ions. Our results suggest that the major inorganic aerosols enhancement (mass) can reach to 23% of that of the carbonaceous aerosols.