ALBERT

Description: Coastal regions have historically represented a significant challenge for air quality investigations because of water-land boundary transition characteristics and a paucity of measurements available over water. Prior studies have identified the formation of high levels of ozone over water bodies, such as the Chesapeake Bay, that can potentially recirculate back over land to significantly impact populated areas. Earth-observing satellites and forecast models face challenges in capturing the coastal transition zone where small-scale meteorological dynamics are complex and large changes in pollutants can occur on very short spatial and temporal scales. An observation strategy is presented to synchronously measure pollutants over land and over water to provide a more complete picture of chemical gradients across coastal boundaries for both the needs of state and local environmental management and new remote sensing platforms. Intensive vertical profile information from ozone lidar systems and ozonesondes, obtained at two main sites, one over land and the other over water, are complemented by remote sensing and in situ observations of air quality from ground-based, airborne (both personned and unpersonned), and shipborne platforms. These observations, coupled with reliable chemical transport simulations, such as the National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC), are expected to lead to a more fully characterized and complete landwater interaction observing system that can be used to assess future geostationary air quality instruments, such as the National Aeronautics and Space Administration (NASA) Tropospheric Emissions: Monitoring of Pollution (TEMPO), and current low-Earth-orbiting satellites, such as the European Space Agencys Sentinel-5 Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).

Description: The San Joaquin Valley (SJV) of California experiences high concentrations of PM2.5 (particulate matter with aerodynamic diameter 2.5 m) during episodes of meteorological stagnation in winter. Modeling PM2.5 NH4NO3 during these episodes is challenging because it involves simulating meteorology in complex terrain under low wind speed and vertically stratified conditions, representing complex pollutant emissions distributions, and simulating daytime and nighttime chemistry that can be influenced by the mixing of urban and rural air masses. A rich dataset of observations related to NH4NO3 formation was acquired during multiple periods of elevated NH4NO3 during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaign in SJV in January and February 2013. Here, NH4NO3 is simulated during the SJV DISCOVER-AQ study period with the Community Multiscale Air Quality (CMAQ) model version 5.1, predictions are evaluated with the DISCOVER-AQ dataset, and process analysis modeling is used to quantify HNO3 production rates. Simulated NO3- generally agrees well with routine monitoring of 24-h average NO3-, but comparisons with hourly average NO3- measurements in Fresno revealed differences at higher time resolution. Predictions of gas-particle partitioning of total nitrate (HNO3 + NO3-) and NHx (NH3 + NH4+) generally agreed well with measurements in Fresno, although partitioning of total nitrate to HNO3 was sometimes overestimated at low relative humidity in afternoon. Gas-particle partitioning results indicate that NH4NO3 formation is limited by HNO3 availability in both the model and ambient. NH3 mixing ratios are underestimated, particularly in areas with large agricultural activity, and the spatial allocation of NH3 emissions could benefit from additional work, especially near Hanford. HNO3 production via daytime and nighttime pathways is reasonably consistent with the conceptual model of NH4NO3 formation in SJV, and production peaked aloft between about 160 and 240 m in the model. During a period of elevated NH4NO3, the model predicted that the OH + NO2 pathway contributed 46% to total HNO3 production in SJV and the N2O5 heterogeneous hydrolysis pathway contributed 54%. The relative importance of the OH + NO2 pathway for HNO3 production is predicted to increase as NOx emissions decrease.