ALBERT

Description: Open-path Fourier transform infrared spectroscopy (OP-FTIR) is susceptible to environmental variables which can become sources of errors for gas quantification. In this study, we assessed the effects of water vapour, temperature, path length, and wind speed on quantitative uncertainties of nitrous oxide (N2O) and carbon dioxide (CO2) derived from OP-FTIR spectra. The presence of water vapour in spectra underestimated N2O mole fractions by 3 % and 12 %, respectively, from both lab and field experiments using a classical least squares (CLS) model when the reference and sample spectra were collected at the same temperature (i.e. 30 ∘C). Differences in temperature between sample and reference spectra also underestimated N2O mole fractions due to temperature broadening and the increased interferences of water vapour in spectra of wet samples. Changes in path length resulted in a non-linear response of spectra and bias (e.g. N2O and CO2 mole fractions were underestimated by 30 % and 7.5 %, respectively, at the optical path of 100 m using CLS models). For N2O quantification, partial least squares (PLS) models were less sensitive to water vapour, temperature, and path length and provided more accurate estimations than CLS. Uncertainties in the path-averaged mole fractions increased in low-wind conditions (

Description: In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Description: A massive mangrove dieback event occurred in 2015–2016 along ∼1000 km of pristine coastline in the Gulf of Carpentaria, Australia. Here, we use sediment and wood chronologies to gain insights into geochemical and climatic changes related to this dieback. The unique combination of low rainfall and low sea level observed during the dieback event had been unprecedented in the preceding 3 decades. A combination of iron (Fe) chronologies in wood and sediment, wood density and estimates of mangrove water use efficiency all imply lower water availability within the dead mangrove forest. Wood and sediment chronologies suggest a rapid, large mobilization of sedimentary Fe, which is consistent with redox transitions promoted by changes in soil moisture content. Elemental analysis of wood cross sections revealed a 30- to 90-fold increase in Fe concentrations in dead mangroves just prior to their mortality. Mangrove wood uptake of Fe during the dieback is consistent with large apparent losses of Fe from sediments, which potentially caused an outwelling of Fe to the ocean. Although Fe toxicity may also have played a role in the dieback, this possibility requires further study. We suggest that differences in wood and sedimentary Fe between living and dead forest areas reflect sediment redox transitions that are, in turn, associated with regional variability in groundwater flows. Overall, our observations provide multiple lines of evidence that the forest dieback was driven by low water availability coinciding with a strong El Niño–Southern Oscillation (ENSO) event and was associated with climate change.

Description: We present the inter-comparison of delta slant column densities (SCDs) and vertical profiles of nitrous acid (HONO) derived from measurements of different multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments and using different inversion algorithms during the Second Cabauw Inter-comparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) in September 2016 at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). The HONO vertical profiles, vertical column densities (VCDs), and near-surface volume mixing ratios are compared between different MAX-DOAS instruments and profile inversion algorithms for the first time. Systematic and random discrepancies of the HONO results are derived from the comparisons of all data sets against their median values. Systematic discrepancies of HONO delta SCDs are observed in the range of ±0.3×1015 molec. cm−2, which is half of the typical random discrepancy of 0.6×1015 molec. cm−2. For a typical high HONO delta SCD of 2×1015 molec. cm−2, the relative systematic and random discrepancies are about 15 % and 30 %, respectively. The inter-comparison of HONO profiles shows that both systematic and random discrepancies of HONO VCDs and near-surface volume mixing ratios (VMRs) are mostly in the range of ∼±0.5×1014 molec. cm−2 and ∼±0.1 ppb (typically ∼20 %). Further we find that the discrepancies of the retrieved HONO profiles are dominated by discrepancies of the HONO delta SCDs. The profile retrievals only contribute to the discrepancies of the HONO profiles by ∼5 %. However, some data sets with substantially larger discrepancies than the typical values indicate that inappropriate implementations of profile inversion algorithms and configurations of radiative transfer models in the profile retrievals can also be an important uncertainty source. In addition, estimations of measurement uncertainties of HONO dSCDs, which can significantly impact profile retrievals using the optimal estimation method, need to consider not only DOAS fit errors, but also atmospheric variability, especially for an instrument with a DOAS fit error lower than ∼3×1014 molec. cm−2. The MAX-DOAS results during the CINDI-2 campaign indicate that the peak HONO levels (e.g. near-surface VMRs of ∼0.4 ppb) often appeared in the early morning and below 0.2 km. The near-surface VMRs retrieved from the MAX-DOAS observations are compared with those measured using a co-located long-path DOAS instrument. The systematic differences are smaller than 0.15 and 0.07 ppb during early morning and around noon, respectively. Since true HONO values at high altitudes are not known in the absence of real measurements, in order to evaluate the abilities of profile inversion algorithms to respond to different HONO profile shapes, we performed sensitivity studies using synthetic HONO delta SCDs simulated by a radiative transfer model with assumed HONO profiles. The tests indicate that the profile inversion algorithms based on the optimal estimation method with proper configurations can reproduce the different HONO profile shapes well. Therefore we conclude that the features of HONO accumulated near the surface derived from MAX-DOAS measurements are expected to represent the ambient HONO profiles well.

Description: Low-cost sensors have the potential to facilitate the exploration of air quality issues on new temporal and spatial scales. Here we evaluate a low-cost sensor quantification system for methane through its use in two different deployments. The first was a 1-month deployment along the Colorado Front Range and included sites near active oil and gas operations in the Denver-Julesburg basin. The second deployment was in an urban Los Angeles neighborhood, subject to complex mixtures of air pollution sources including oil operations. Given its role as a potent greenhouse gas, new low-cost methods for detecting and monitoring methane may aid in protecting human and environmental health. In this paper, we assess a number of linear calibration models used to convert raw sensor signals into ppm concentration values. We also examine different choices that can be made during calibration and data processing and explore cross sensitivities that impact this sensor type. The results illustrate the accuracy of the Figaro TGS 2600 sensor when methane is quantified from raw signals using the techniques described. The results also demonstrate the value of these tools for examining air quality trends and events on small spatial and temporal scales as well as their ability to characterize an area – highlighting their potential to provide preliminary data that can inform more targeted measurements or supplement existing monitoring networks.

Description: Formation of secondary organic aerosol (SOA) is initiated by the oxidation of volatile organic compounds (VOCs) in the gas phase whose products subsequently partition to the particle phase. Non-volatile molecules have a negligible evaporation rate and grow particles at their condensation rate. Semi-volatile molecules have a significant evaporation rate and grow particles at a much slower rate than their condensation rate. Particle phase chemistry may enhance particle growth if it transforms partitioned semi-volatile molecules into non-volatile products. In principle, changes in molecular composition as a function of particle size allow non-volatile molecules that have condensed from the gas phase (a surface-limited process) to be distinguished from those produced by particle phase reaction (a volume-limited process). In this work, SOA was produced by β-pinene ozonolysis in a flow tube reactor. Aerosol exiting the reactor was size-selected with a differential mobility analyzer, and individual particle sizes between 35 and 110 nm in diameter were characterized by on- and offline mass spectrometry. Both the average oxygen-to-carbon (O ∕ C) ratio and carbon oxidation state (OSc) were found to decrease with increasing particle size, while the relative signal intensity of oligomers increased with increasing particle size. These results are consistent with oligomer formation primarily in the particle phase (accretion reactions, which become more favored as the volume-to-surface-area ratio of the particle increases). Analysis of a series of polydisperse SOA samples showed similar dependencies: as the mass loading increased (and average volume-to-surface-area ratio increased), the average O ∕ C ratio and OSc decreased, while the relative intensity of oligomer ions increased. The results illustrate the potential impact that particle phase chemistry can have on biogenic SOA formation and the particle size range where this chemistry becomes important.

Description: The ability of particle-phase chemistry to alter the molecular composition and enhance the growth rate of nanoparticles in the 2–100 nm diameter range is investigated through the use of a kinetic growth model. The molecular components included are sulfuric acid, ammonia, water, a non-volatile organic compound, and a semi-volatile organic compound. Molecular composition and growth rate are compared for particles that grow by partitioning alone vs. those that grow by a combination of partitioning and an accretion reaction in the particle phase between two organic molecules. Particle-phase chemistry causes a change in molecular composition that is particle diameter dependent, and when the reaction involves semi-volatile molecules, the particles grow faster than by partitioning alone. These effects are most pronounced for particles larger than about 20 nm in diameter. The modeling results provide a fundamental basis for understanding recent experimental measurements of the molecular composition of secondary organic aerosol showing that accretion reaction product formation increases linearly with increasing aerosol volume-to-surface-area. They also allow initial estimates of the reaction rate constants for these systems. For secondary aerosol produced by either OH oxidation of the cyclic dimethylsiloxane (D5) or ozonolysis of β-pinene, oligomerization rate constants on the order of 10−3 to 10−1 M−1 s−1 are needed to explain the experimental results. These values are consistent with previously measured rate constants for reactions of hydroperoxides and/or peroxyacids in the condensed phase.

Description: The differential optical absorption spectroscopy (DOAS) method is a well-known remote sensing technique that is nowadays widely used for measurements of atmospheric trace gases, creating the need for harmonization and characterization efforts. In this study, an intercomparison exercise of DOAS retrieval codes from 17 international groups is presented, focusing on NO2 slant columns. The study is based on data collected by one instrument during the Multi-Axis DOAS Comparison campaign for Aerosols and Trace gases (MAD-CAT) in Mainz, Germany, in summer 2013. As data from the same instrument are used by all groups, the results are free of biases due to instrumental differences, which is in contrast to previous intercomparison exercises.While in general an excellent correlation of NO2 slant columns between groups of  〉  99.98 % (noon reference fits) and  〉  99.2 % (sequential reference fits) for all elevation angles is found, differences between individual retrievals are as large as 8 % for NO2 slant columns and 100 % for rms residuals in small elevation angles above the horizon.Comprehensive sensitivity studies revealed that absolute slant column differences result predominantly from the choice of the reference spectrum while relative differences originate from the numerical approach for solving the DOAS equation as well as the treatment of the slit function. Furthermore, differences in the implementation of the intensity offset correction were found to produce disagreements for measurements close to sunrise (8–10 % for NO2, 80 % for rms residual). The largest effect of  ≈  8 % difference in NO2 was found to arise from the reference treatment; in particular for fits using a sequential reference. In terms of rms fit residual, the reference treatment has only a minor impact. In contrast, the wavelength calibration as well as the intensity offset correction were found to have the largest impact (up to 80 %) on rms residual while having only a minor impact on retrieved NO2 slant columns.

Description: Observations of turbulence in the planetary boundary layer are critical for developing and evaluating boundary layer parameterizations in mesoscale numerical weather prediction models. These observations, however, are expensive and rarely profile the entire boundary layer. Using optimized configurations for 449 and 915 MHz wind profiling radars during the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA), improvements have been made to the historical methods of measuring vertical velocity variance through the time series of vertical velocity, as well as the Doppler spectral width. Using six heights of sonic anemometers mounted on a 300 m tower, correlations of up to R2 = 0. 74 are seen in measurements of the large-scale variances from the radar time series and R2 = 0. 79 in measurements of small-scale variance from radar spectral widths. The total variance, measured as the sum of the small and large scales, agrees well with sonic anemometers, with R2 = 0. 79. Correlation is higher in daytime convective boundary layers than nighttime stable conditions when turbulence levels are smaller. With the good agreement with the in situ measurements, highly resolved profiles up to 2 km can be accurately observed from the 449 MHz radar and 1 km from the 915 MHz radar. This optimized configuration will provide unique observations for the verification and improvement to boundary layer parameterizations in mesoscale models.

Description: In September 2014, a Pandora multi-spectral photometer operated by the SAGE-III project was sent to Lauder, New Zealand, to operate side-by-side with the National Institute of Water and Atmospheric Research's (NIWA) Network for Detection of Atmospheric Composition Change (NDACC) certified zenith slant column NO2 instrument to allow intercomparison between the two instruments and for evaluation of the Pandora unit as a potential SAGE-III validation tool for stratospheric NO2. This intercomparison spanned a full year, from September 2014 to September 2015. Both datasets were produced using their respective native algorithms using a common reference spectrum (i.e., 12:00 NZDT (UTC + 13) on 26 February 2015). Throughout the entire deployment period both instruments operated in a zenith-only observation configuration. Though conversion from slant column density (SCD) to vertical-column density is routine (by application of an air mass factor), we limit the current analysis to SCD only. This omission is beneficial in that it provides an intercomparison based on similar modes of operation for the two instruments and the retrieval algorithms as opposed to introducing an air mass factor dependence in the intercomparison as well. It was observed that the current hardware configurations and retrieval algorithms are in good agreement (R 〉 0.95). The detailed results of this investigation are presented herein.