3 research outputs found
Modeling NH4NO3 over the San Joaquin Valley During the 2013 DISCOVER-AQ Campaign
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
Characterizing CO and NO y Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling.
Modeled source attribution information from the Community Multiscale Air Quality model was coupled with ambient data from the 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality Baltimore field study. We assess source contributions and evaluate the utility of using aircraft measured CO and NO y relationships to constrain emission inventories. We derive ambient and modeled ΔCO:ΔNO y ratios that have previously been interpreted to represent CO:NO y ratios in emissions from local sources. Modeled and measured ΔCO:ΔNO y are similar; however, measured ΔCO:ΔNO y has much more daily variability than modeled values. Sector-based tagging shows that regional transport, on-road gasoline vehicles, and nonroad equipment are the major contributors to modeled CO mixing ratios in the Baltimore area. In addition to those sources, on-road diesel vehicles, soil emissions, and power plants also contribute substantially to modeled NO y in the area. The sector mix is important because emitted CO:NO x ratios vary by several orders of magnitude among the emission sources. The model-predicted gasoline/diesel split remains constant across all measurement locations in this study. Comparison of ΔCO:ΔNO y to emitted CO:NO y is challenged by ambient and modeled evidence that free tropospheric entrainment, and atmospheric processing elevates ambient ΔCO:ΔNO y above emitted ratios. Specifically, modeled ΔCO:ΔNO y from tagged mobile source emissions is enhanced 5-50% above the emitted ratios at times and locations of aircraft measurements. We also find a correlation between ambient formaldehyde concentrations and measured ΔCO:ΔNO y suggesting that secondary CO formation plays a role in these elevated ratios. This analysis suggests that ambient urban daytime ΔCO:ΔNO y values are not reflective of emitted ratios from individual sources
Modeling NH4NO3 Over the San Joaquin Valley During the 2013 DISCOVER‐AQ Campaign
The San Joaquin Valley (SJV) of California experiences high concentrations of particulate matterNH4NO3during episodes of meteorological stagnation in winter. A rich data set of observations related toNH4NO3formation was acquired during multiple periods of elevated NH4NO3during the DerivingInformation on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality(DISCOVER-AQ)field campaign in SJV in January and February 2013. Here NH4NO3is simulated during the SJVDISCOVER-AQ study period with the Community Multiscale Air Quality (CMAQ) model, diagnostic modelevaluation is performed using the DISCOVER-AQ data set, and integrated reaction rate analysis is used toquantify HNO3production rates. Simulated NO3 generally agrees well with routine monitoring of 24-hraverage NO3 , but comparisons with hourly average NO3 measurements in Fresno revealed differences athigher time resolution. Predictions of gas-particle partitioning of total nitrate (HNO3+NO3 ) and NHx(NH3+NH4+) generally agree well with measurements in Fresno, although partitioning of total nitrate toHNO3is sometimes overestimated at low relative humidity in afternoon. Gas-particle partitioning resultsindicate that NH4NO3formation is limited by HNO3availability in both the model and ambient. NH3mixingratios are underestimated, particularly in areas with large agricultural activity, and additional work on thespatial allocation of NH3emissions is warranted. During a period of elevated NH4NO3, the model predictedthat the OH + NO2pathway contributed 46% to total HNO3production in SJV and the N2O5heterogeneoushydrolysis pathway contributed 54%. The relative importance of the OH + NO2pathway for HNO3productionis predicted to increase as NOx emissions decrease