RESUMEN
Analysis of formaldehyde measurements by the Pandora spectrometer systems between 2016 and 2019 suggested that there was a temperature dependent process inside Pandora head sensor that emitted formaldehyde. Some parts in the head sensor were manufactured from thermal plastic polyoxymethylene homopolimer (E.I. Du Pont de Nemour & Co., USA: POM-H Delrin®) and were responsible for formaldehyde production. Laboratory analysis of the four Pandora head sensors showed that internal formaldehyde production had exponential temperature dependence with a damping coefficient of 0.0911±0.0024 °C-1 and the exponential function amplitude ranging from 0.0041 DU to 0.049 DU. No apparent dependency on the head sensor age and heating/cooling rates was detected. The total amount of formaldehyde internally generated by the POM-H Delrin components and contributing to the direct sun measurements were estimated based on the head sensor temperature and solar zenith angle of the measurements. Measurements in winter, during colder (<10°C) days in general and at high solar zenith angles (> 75 °) were minimally impacted. Measurements during hot days (>28°C) and small solar zenith angles had up to 1 DU (2.69×1016 molecules/cm2) contribution from POM-H Delrin parts. Multi-axis differential slant column densities were minimally impacted (< 0.01 DU) due to the reference spectrum collected within a short time period with a small difference in head sensor temperature. Three new POM-H Delrin free Pandora head sensors (manufactured in summer 2019) were evaluated for temperature dependent attenuation across the entire spectral range (300 to 530 nm). No formaldehyde or any other absorption above the instrumental noise was observed across the entire spectral range.
RESUMEN
The San Joaquin Valley (SJV) of California experiences high concentrations of particulate matter NH4NO3 during episodes of meteorological stagnation in winter. A rich data set of observations related to NH4NO3 formation was acquired during multiple periods of elevated NH4NO3 during the Deriving Information 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 NH4NO3 is simulated during the SJV DISCOVER-AQ study period with the Community Multiscale Air Quality (CMAQ) model, diagnostic model evaluation is performed using the DISCOVER-AQ data set, and integrated reaction rate analysis is used to quantify HNO3 production rates. Simulated NO3- generally agrees well with routine monitoring of 24-hr 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 agree well with measurements in Fresno, although partitioning of total nitrate to HNO3 is 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 additional work on the spatial allocation of NH3 emissions is warranted. During a period of elevated NH4NO3, the model predicted that the OH + NO2 pathway contributed 46% to total HNO3production 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.
RESUMEN
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.
