Monitoring potential photochemical interference in laser-induced fluorescence measurements of atmospheric OH

In situ laser-induced fluorescence measurements of atmospheric OH are susceptible to interference from laser generated OH, particularly in the troposphere. To quantify this interference we implement the addition of perfluoropropene, C_3F_6, for the chemical removal of OH from the ambient air. The removal rate of OH by C_3F_6 is determined in the laboratory using the discharge flow technique. Over the temperature range 249 to 296 K the rate constant is (6.0±0.8) × 10^(−13) exp[(370±40)/T] cm^³ molecule^(−1) s^(−1), independent of pressure. In situ measurements using C_3F_6 addition are performed in both aircraft-borne and ground-based experiments. These studies show that laser excitation of the ^²Σ^+(v=1)← ^²Π(v=0) transition (282 nm) at high pulse repetition rates and low peak power can provide reliable and sensitive measurements of tropospheric OH

Soot Superaggregates from Flaming Wildfires and Their Direct Radiative Forcing

Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension D(sub f) approximately equals 1.8 mobility diameter D(sub m) (is) less than or equal to 1 micron, and aerodynamic diameter D(sub a) (is) less than or equal to 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic D(sub f) approximately equals 2.6,D(sub m) (is) greater than 1 micron, and D(sub a) is less than or equal to 300 nm that form via the cluster-dense aggregation mechanism.We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. We estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (D(sub f) approximately equals 1.8) aggregates, and approximately equals 90% more warming than the volume-equivalent spherical soot particles simulated in climate models

Cloud condensation nuclei activity, closure, and droplet growth kinetics of Houston aerosol during the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS)

In situ cloud condensation nuclei (CCN) measurements were obtained in the boundary layer over Houston, Texas, during the 2006 Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS) campaign onboard the CIRPAS Twin Otter. Polluted air masses in and out of cloudy regions were sampled for a total of 22 flights, with CCN measurements obtained for 17 of these flights. In this paper, we focus on CCN closure during two flights, within and downwind of the Houston regional plume and over the Houston Ship Channel. During both flights, air was sampled with particle concentrations exceeding 25,000 cm^(−3) and CCN concentrations exceeding 10,000 cm^(−3). CCN closure is evaluated by comparing measured concentrations with those predicted on the basis of measured aerosol size distributions and aerosol mass spectrometer particle composition. Different assumptions concerning the internally mixed chemical composition result in average CCN overprediction ranging from 3% to 36% (based on a linear fit). It is hypothesized that the externally mixed fraction of the aerosol contributes much of the CCN closure scatter, while the internally mixed fraction largely controls the overprediction bias. On the basis of the droplet sizes of activated CCN, organics do not seem to impact, on average, the CCN activation kinetics

Survey of whole air data from the second airborne Biomass Burning and Lightning Experiment using principal component analysis

Hydrocarbon and halocarbon measurements collected during the second airborne Biomass Burning and Lightning Experiment (BIBLE-B) were subjected to a principal component analysis (PCA), to test the capability for identifying intercorrelated compounds within a large whole air data set. The BIBLE expeditions have sought to quantify and understand the products of burning, electrical discharge, and general atmospheric chemical processes during flights arrayed along the western edge of the Pacific. Principal component analysis was found to offer a compact method for identifying the major modes of composition encountered in the regional whole air data set. Transecting the continental monsoon, urban and industrial tracers (e.g., combustion byproducts, chlorinated methanes and ethanes, xylenes, and longer chain alkanes) dominated the observed variability. Pentane enhancements reflected vehicular emissions. In general, ethyl and propyl nitrate groupings indicated oxidation under nitrogen oxide (NOx) rich conditions and hence city or lightning influences. Over the tropical ocean, methyl nitrate grouped with brominated compounds and sometimes with dimethyl sulfide and methyl iodide. Biomass burning signatures were observed during flights over the Australian continent. Strong indications of wetland anaerobics (methane) or liquefied petroleum gas leakage (propane) were conspicuous by their absence. When all flights were considered together, sources attributable to human activity emerged as the most important. We suggest that factor reductions in general and PCA in particular may soon play a vital role in the analysis of regional whole air data sets, as a complement to more familiar methods

Intercomparability of X_(CO_2) and X_(CH_4) from the United States TCCON sites

The Total Carbon Column Observing Network (TCCON) has become the standard for long-term column-averaged measurements of CO_2 and CH_4. Here, we use a pair of portable spectrometers to test for intra-network bias among the four currently operating TCCON sites in the United States (US). A previous analytical error analysis has suggested that the maximum 2σ site-to-site relative (absolute) bias of TCCON should be less than 0.2% (0.8ppm) in X_(CO_2) and 0.4% (7ppb) in X_(CH_4). We find here experimentally that the 95% confidence intervals for maximum pairwise site-to-site bias among the four US TCCON sites are 0.05–0.14% for X_(CO_2) and 0.08–0.24% for X_(CH_4). This is close to the limit of the bias we can detect using this methodology

Assessment of errors and biases in retrievals of X_(CO2), X_(CH4), X_(CO), and X_(N2O) from a 0.5 cm^(-1) resolution solar-viewing spectrometer

Bruker™ EM27/SUN instruments are commercial mobile solar-viewing near-IR spectrometers. They show promise for expanding the global density of atmospheric column measurements of greenhouse gases and are being marketed for such applications. They have been shown to measure the same variations of atmospheric gases within a day as the high-resolution spectrometers of the Total Carbon Column Observing Network (TCCON). However, there is little known about the long-term precision and uncertainty budgets of EM27/SUN measurements. In this study, which includes a comparison of 186 measurement days spanning 11 months, we note that atmospheric variations of X_(gas) within a single day are well captured by these low-resolution instruments, but over several months, the measurements drift noticeably. We present comparisons between EM27/SUN instruments and the TCCON using GGG as the retrieval algorithm. In addition, we perform several tests to evaluate the robustness of the performance and determine the largest sources of errors from these spectrometers. We include comparisons of X_(CO2), X_(CH4), X_(CO), and X_(N2)O. Specifically we note EM27/SUN biases for January 2015 of 0.03, 0.75, –0.12, and 2.43 % for X_(CO2), X_(CH4), X_(CO), and X_(N2)O respectively, with 1σ running precisions of 0.08 and 0.06 % for X_(CO2) and X_(CH4) from measurements in Pasadena. We also identify significant error caused by nonlinear sensitivity when using an extended spectral range detector used to measure CO and N_2O

Aerosol single scattering albedo dependence on biomass combustion efficiency: Laboratory and field studies

Single scattering albedo (ω) of fresh biomass burning (BB) aerosols produced from 92 controlled laboratory combustion experiments of 20 different woods and grasses was analyzed to determine the factors that control the variability in ω. Results show that ω varies strongly with fire-integrated modified combustion efficiency (MCEFI)—higher MCEFI results in lower ω values and greater spectral dependence of ω. A parameterization of ω as a function of MCEFI for fresh BB aerosols is derived from the laboratory data and is evaluated by field observations from two wildfires. The parameterization suggests that MCEFI explains 60% of the variability in ω, while the 40% unexplained variability could be accounted for by other parameters such as fuel type. Our parameterization provides a promising framework that requires further validation and is amenable for refinements to predict ω with greater confidence, which is critical for estimating the radiative forcing of BB aerosols

Quality controls, bias, and seasonality of CO2columns in the boreal forest with Orbiting Carbon Observatory-2, Total Carbon Column Observing Network, and EM27/SUN measurements

Seasonal CO$_{2}$ exchange in the boreal forest plays an important role in the global carbon budget and in driving interannual variability in seasonal cycles of atmospheric CO$_{2}$. Satellite-based observations from polar orbiting satellites like the Orbiting Carbon Observatory-2 (OCO-2) offer an opportunity to characterize boreal forest seasonal cycles across longitudes with a spatially and temporally rich data set, but data quality controls and biases still require vetting at high latitudes. With the objective of improving data availability at northern, terrestrial high latitudes, this study evaluates quality control methods and biases of OCO-2 retrievals of atmospheric column-averaged dry air mole fractions of CO$_{2}$ (X$_{CO2}$) in boreal forest regions. In addition to the standard quality control (QC) filters recommended for the Atmospheric Carbon Observations from Space (ACOS) B8 (B8 QC) and ACOS B9 (B9 QC) OCO-2 retrievals, a third set of quality control filters were specifically tailored to boreal forest observations (boreal QC) with the goal of increasing data availability at high latitudes without sacrificing data quality. Ground-based reference measurements of X$_{CO2}$ include observations from two sites in the Total Carbon Column Observing Network (TCCON) at East Trout Lake, Saskatchewan, Canada, and Sodankylä, Finland. OCO-2 retrievals were also compared to ground-based observations from two Bruker EM27/SUN Fourier transform infrared spectrometers (FTSs) at Fairbanks, Alaska, USA. The EM27/SUN spectrometers that were deployed in Fairbanks were carefully monitored for instrument performance and were bias corrected to TCCON using observations at the Caltech TCCON site. The B9 QC were found to pass approximately twice as many OCO-2 retrievals over land north of 50° N than the B8 QC, and the boreal QC were found to pass approximately twice as many retrievals in May, August, and September as the B9 QC. While boreal QC results in a substantial increase in passable retrievals, this is accompanied by increases in the standard deviations in biases at boreal forest sites from ∼1.4 parts per million (ppm) with B9 QC to ∼1.6 ppm with boreal QC. Total average biases for coincident OCO-2 retrievals at the three sites considered did not consistently increase or decrease with different QC methods, and instead, responses to changes in QC varied according to site and satellite viewing geometries. Regardless of the quality control method used, seasonal variability in biases was observed, and this variability was more pronounced at Sodankylä and East Trout Lake than at Fairbanks. Long-term coincident observations from TCCON, EM27/SUN, and satellites from multiple locations would be necessary to determine whether the reduced seasonal variability in bias at Fairbanks is due to geography or instrumentation. Monthly average biases generally varied between −1 and +1 ppm at the three sites considered, with more negative biases in spring (March, April, and May – MAM) and autumn (September and October – SO) but more positive biases in the summer months (June, July, and August – JJA). Monthly standard deviations in biases ranged from approximately 1.0 to 2.0 ppm and did not exhibit strong seasonal dependence, apart from exceptionally high standard deviation observed with all three QC methods at Sodankylä in June. There was no evidence found to suggest that seasonal variability in bias is a direct result of air mass dependence in ground-based retrievals or of proximity bias from coincidence criteria, but there were a number of retrieval parameters used as quality control filters that exhibit seasonality and could contribute to seasonal dependence in OCO-2 bias. Furthermore, it was found that OCO-2 retrievals of X$_{CO2}$ without the standard OCO-2 bias correction exhibit almost no perceptible seasonal dependence in average monthly bias at these boreal forest sites, suggesting that seasonal variability in bias is introduced by the bias correction. Overall, we found that modified quality controls can allow for significant increases in passable OCO-2 retrievals with only marginal compromises in data quality, but seasonal dependence in biases still warrants further exploration

Differential column measurements using compact solar-tracking spectrometers

We demonstrate the use of compact solar-tracking Fourier transform spectrometers (Bruker EM27/SUN) for differential measurements of the column-averaged dry-air mole fractions of CH_4 and CO_2 within urban areas. Using Allan variance analysis, we show that the differential column measurement has a precision of 0.01 % for X_(CO_2) and X_(CH_4) with an optimum integration time of 10 min, corresponding to Allan deviations of 0.04 ppm and 0.2 ppb,respectively. The sensor system is very stable over time and after relocation across the continent. We report tests of the differential column measurement,and its sensitivity to emission sources, by measuring the downwind-minus-upwind column difference ΔX_(CH_4) across dairy farms in the Chino area, California, and using the data to verify emissions reported in the literature. Ratios of spatial column differences ΔX_(CH_4)∕ΔX_(CO_2) were observed across Pasadena within the Los Angeles basin, indicating values consistent with regional emission ratios from the literature. Our precise, rapid measurements allow us to determine significant short-term variations (5–10 min) of X_(CO_2) and X_(CH_4) and to show that they represent atmospheric phenomena. Overall, this study helps establish a range of new applicationsfor compact solar-viewing Fourier transform spectrometers. Byaccurately measuring the small differences in integrated column amounts acrosslocal and regional sources, we directly observe the mass loadingof the atmosphere due to the influence of emissions in theintervening locale. The inference of the source strength is muchmore direct than inversion modeling using only surface concentrationsand less subject to errors associated with small-scale transportphenomena