Trace Gas Measurements Research Articles

Age of air from in situ trace gas measurements: insights from a new technique

Abstract. The age of air is an important transport diagnostic that can be derived from trace gas measurements and compared to global chemistry climate model output. We describe a new technique to calculate the age of air, measuring transport times from the Earth's surface to any location in the atmosphere based on simultaneous in situ measurements of multiple key long-lived trace gases. The primary benefits of this new technique include (1) optimized ages of air consistent with simultaneously measured SF6 and CO2; (2) age of air from the upper troposphere through the stratosphere; (3) estimates of the second moment of age spectra that have not been well constrained from measurements; and (4) flexibility to be used with measurements across multiple instruments, platforms, and decades. We demonstrate the technique on aircraft and balloon measurements from the 1990s, the last period of extensive stratospheric in situ sampling, and several recent missions from the 2020s, and compare the results with previously published and modeled values.

Detecting and sourcing GHGs and atmospheric trace gases in a municipal waste treatment plant using coupled chemistry and isotope compositions

Landfill operations and waste processing facilities are important and highly heterogeneous sources of both greenhouse gases (GHGs) and non-GHG air pollutants in the atmosphere. This arises the need for detailed apportionment of waste sources in order to locate and subsequently reduce emissions from landfills. Here, a time series of in situ measurements of atmospheric trace gases and spatial allocation of specific emission source types under different processing phases and environmental conditions were conducted in and in the surroundings of a Municipal Solid Waste Treatment Plant (MSWTP) in south-western Poland. Results revealed that several individual GHG sources dominated across the waste processing facility and that GHGs concentrations displayed spatial seasonality. An increase in the ground-level CH4 concentrations, from ∼ 30.3 to 56.3 ppmv, was observed close (∼5 – 10 m) to the major emission sources within the MSWTP. While hotspot areas generally yielded elevated CH4 concentrations near the soil surface, these were relatively low (2.4 to 8.9 ppmv) along the facility’s fence line. The study of the corresponding δ13C delineated the extent of dispersion plumes downwind emission hotspots, characterized by a 13C depletion (around 4.0 ‰) in the atmospheric CH4 and CO2. For CH4, emissions were isotopically discriminated between the extraction wells at active quarters/cells (δ13C = –58.3 ± 1.1 ‰) and biogas produced in the biological waste treatment installation (δ13C = –62.7 ± 0.7 ‰). Most of the trace compounds (non-methane hydrocarbons, halocarbons, oxygen-bearing organic gases, ketones, nitrogenous and sulphurous gases, and other admixture compounds) detected at the ground surface were linked to the CH4- and CO2-rich spots. Despite the relatively high variability in the concentrations of organic and inorganic compounds observed at the MSWTP active zones, our results suggest that they do not have a meaningful impact on the surrounding air quality.

The Influence of Stratospheric Hydration From the Hunga Eruption on Chemical Processing in the 2023 Antarctic Vortex

AbstractWe use measurements of trace gases from the Microwave Limb Sounder and polar stratospheric clouds (PSCs) from the Cloud‐Aerosol Lidar with Orthogonal Polarization to investigate how the extraordinary stratospheric water vapor enhancement from the 2022 Hunga eruption affected polar processing during the 2023 Antarctic winter. Although the dynamical characteristics of the vortex itself were generally unexceptional, the excess moisture initially raised PSC formation threshold temperatures above typical values. Cold conditions, especially in early July, prompted ice PSC formation and unusually severe irreversible dehydration at higher levels (500–700 K), while atypical hydration occurred at lower levels (380–460 K). Heterogeneous chemical processing was more extensive, both vertically (up to 750–800 K) and temporally (earlier in the season), than in prior Antarctic winters. The resultant HCl depletion and ClO enhancement redefined their previously observed ranges at and above 600 K. Albeit unmatched in the satellite record, the early‐winter upper‐level chlorine activation was insufficient to induce substantial ozone loss. Chlorine activation, denitrification, and dehydration processes ran to completion by July/August, with trace gas evolution mostly following the climatological mean thereafter, but with chlorine deactivation starting slightly later than usual. While cumulative ozone losses at 410–550 K were relatively large, probably because of the delayed chlorine deactivation, they were not unprecedented. Thus, ozone depletion was unremarkable throughout the lower stratosphere. Although Hunga enhanced PSC formation and chemical processing in early winter, saturation of lower stratospheric denitrification, dehydration, and chlorine activation (as is typical in the Antarctic) prevented an exceptionally severe ozone hole in 2023.

Mid-infrared methane standoff sensor using a frequency channel attention based convolutional neural network filter

Highly sensitive standoff methane detection is vital for atmospheric science, environmental protection, and production safety. We develop a mid-infrared methane standoff sensor using a cooperative target based on tunable diode laser absorption spectroscopy (TDLAS). To enhance sensor sensitivity, we propose a one-dimensional frequency channel attention-based convolutional neural network (1D-FCACNN) filter, which can effectively denoise the methane absorbance signals and its second harmonic signals. The filter model is adequately trained on a simulated spectrum dataset, which we constructed based on data augmentation. In comparison with reported filtering algorithms, the proposed filter shows the best performance in both measuring modes and evaluation metrics. Real-time measurements show that the measuring accuracy and limit of detection (LOD) of the proposed sensor reach a minimum of 30.40 ppb and 5.04 ppb over a 10-meter optical range, a significant improvement compared to previous reports of methane standoff sensors. The proposed methane standoff sensor proves the feasibility of enhancing the performance of TDLAS gas sensors with the attention mechanism, bringing a new option for high-sensitivity measurements of methane and other atmospheric trace gases.

Combining Top‐Down and Bottom‐Up Approaches to Evaluate Recent Trends and Seasonal Patterns in UK N2O Emissions

AbstractAtmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modeling. Atmospheric nitrous oxide (N2O) measurements made in the United Kingdom (UK) and Republic of Ireland are used to derive monthly N2O emissions for 2013–2022 using two different inverse methods. We find mean UK emissions of 90.5 ± 23.0 (1σ) and 111.7 ± 32.1 (1σ) Gg N2O yr−1 for 2013–2022, and corresponding trends of −0.68 ± 0.48 (1σ) Gg N2O yr−2 and −2.10 ± 0.72 (1σ) Gg N2O yr−2, respectively, for the two inverse methods. The UK National Atmospheric Emissions Inventory (NAEI) reported mean N2O emissions of 73.9 ± 1.7 (1σ) Gg N2O yr−1 across this period, which is 22%–51% smaller than the emissions derived from atmospheric data. We infer a pronounced seasonal cycle in N2O emissions, with a peak occurring in the spring and a second smaller peak in the late summer for certain years. The springtime peak has a long seasonal decline that contrasts with the sharp rise and fall of N2O emissions estimated from the bottom‐up UK Emissions Model (UKEM). Bayesian inference is used to minimize the seasonal cycle mismatch between the average top‐down (atmospheric data‐based) and bottom‐up (process model and inventory‐based) seasonal emissions at a sub‐sector level. Increasing agricultural manure management and decreasing synthetic fertilizer N2O emissions reduces some of the discrepancy between the average top‐down and bottom‐up seasonal cycles. Other possibilities could also explain these discrepancies, such as missing emissions from NH3 deposition, but these require further investigation.

Symmetric optical multipass matrix systems and the general rapid design methodology

We proposed an original type of multipass cell named symmetric optical multipass matrix system (SMMS), in which the same matrix patterns of various sizes can be formed on both sides. According to its special symmetric configurations, the SMMS design problem is modeled as a variant of the classical traveling salesman problem, which can be rapidly solved by evolutionary optimization algorithms. Two sets of 3-mirror SMMSs are designed, analyzed and built, which show superior characteristics of high stability, desirable beam quality and adjustable optical path lengths. Additionally, they can support simultaneous detection of multiple species with multi-laser channels. The proposed method is further extended to design a 4-mirror SMMS, which verifies the universality and robustness of the design methodology. The experimental observations are in consistent with the theoretical calculations. The newly proposed SMMSs have a broad application prospect in trace gas measurement.

Aerosol interference with open-path eddy covariance measurement in a lake environment

Open-path eddy covariance (OPEC) is widely used for measuring trace gas fluxes between the surface and the atmosphere. At a lake in Eastern China (Lake Taihu), the CO2 flux measured with OPEC was often negative at night (with values as low as −22.1 μmol m−2 s−1) and was coherent across the whole lake, as if the lake were a large sink of atmospheric CO2. The purpose of this study is to investigate the cause of this negative flux phenomenon. In addition to OPEC, we also used closed-path eddy covariance (CPEC) and the transfer coefficient (TC) method to measure the flux. The results show that the persistent negative CO2 flux phenomenon was observed with OPEC but not with CPEC or TC. Because air drawn into the CPEC analyzer was filtered but the OPEC analyzer was influenced by aerosol contamination, the most logical explanation was that particles deposited on the optical lens of the OPEC analyzer changed its cross-sensitivity to water vapor. The direct evidence of this interference was a strong positive correlation between the OPEC analyzer's signal strength and the CO2 mixing ratio observed at 10 Hz. We suggest that it is possible to perform post-field correction to this negative flux bias using the 10 Hz signal strength data. In comparison, an OPEC system at a nearby land site did not experience aerosol interference due to low water vapor flux at night and lack of hygroscopic growth of particles on the optical lens in low humidity conditions. The type of aerosol interference reported here may also occur in high humidity and high pollution conditions elsewhere.

In-flight characterization of a compact airborne quantum cascade laser absorption spectrometer

Abstract. Here, we report on the development of a new quantum cascade laser infrared absorption spectroscopy (QLAS) instrument, the Airborne Tropospheric Tracer In-situ Laser Absorption spectrometer (ATTILA), for atmospheric trace-gas measurements on board of the German High-Altitude Long-range Observatory (HALO) aircraft. Its small and light design makes it suitable for airborne measurements up to approximately 150 hPa of ambient pressure (13–14 km). The dual laser instrument can measure several trace gases simultaneously in two 36.4 m path astigmatic Herriott cells with a data acquisition frequency of 1 Hz. We describe the measurement method and the data acquisition of ATTILA and its in-flight performance by focusing on potential sources of influences on the signal, which we investigated with a dedicated test flight during which the instrument sampled from a constant source. We show that linear critical influences associated with challenging movement patterns can be corrected afterwards, while nonlinear limitations can be minimized by appropriate calibration frequencies and integrated time intervals. During the recent aircraft campaign CAFE Brazil (Chemistry of the Atmosphere Field Experiment in Brazil) from December 2022 to January 2023, carbon monoxide (CO) measurements from ATTILA show a good agreement of a R2 of 0.89 with simultaneous CO measurements from an established IR spectrometer for airborne measurements, the TRacer In Situ TDLAS (tunable diode laser absorption spectroscopy) for Atmospheric Research (TRISTAR), at a 10 s time resolution. First dynamical characteristics and tracer distributions of CO and methane (CH4) over the Amazon rainforest can be identified with ATTILA measurements with a total measurement uncertainty of 10.1 % and 17.5 % for calibration gas mixing ratios of 153 and 1990 ppbv and a data accuracy of 0.3 % and 5.5 % for a data acquisition frequency of 1 Hz for CO and CH4, respectively.

TT-type resonator-based differential photoacoustic spectroscopy for trace gas detection.

A novel TT-type resonator was proposed for the first time, to our knowledge, to realize differential photoacoustic (PA) detection for trace gas measurement. The special design of the TT-type resonator allows us to install the microphone at the resonant center of the acoustic field to maximize the use of the absorption-induced PA signal. To meet the requirement of low gas consumption and easy integration, the TT-type resonator-based PA cell was fabricated as a fiber-coupled module with an inner volume of only 1.1 ml. For validation, the TT-type PA cell was integrated to a photoacoustic spectroscopy (PAS) system for acetylene detection. As a result, a linearity of 0.99999 was achieved in a concentration range from 0 to 5000 ppm with a noise equivalent sensitivity of 101 ppb. The proposed TT-type resonator contributes a new style of PA cell structure to the field of PAS gas detection, combining the advantages of easy integration, low gas consumption, differential detection, and photoacoustic enhancement together.

Correction of stratospheric age of air (AoA) derived from sulfur hexafluoride (SF6) for the effect of chemical sinks

Abstract. Observational monitoring of the stratospheric transport circulation, the Brewer–Dobson circulation (BDC), is crucial to estimate any decadal to long-term changes therein, a prerequisite to interpret trends in stratospheric composition and to constrain the consequential impacts on climate. The transport time along the BDC (i.e. the mean stratospheric age of air, AoA) can best be deduced from trace gas measurements of tracers which increase linearly with time and are chemically passive. The gas sulfur hexafluoride (SF6) is often used to deduce AoA because it has been increasing monotonically since the ∼1950s, and previously its chemical sinks in the mesosphere have been assumed to be negligible for AoA estimates. However, recent studies have shown that the chemical sinks of SF6 are stronger than assumed and become increasingly relevant with rising SF6 concentrations. To adjust biases in AoA that result from the chemical SF6 sinks, we here propose a simple correction scheme for SF6-based AoA estimates accounting for the time-dependent effects of chemical sinks. The correction scheme is based on theoretical considerations with idealized assumptions, resulting in a relation between ideal AoA and apparent AoA which is a function of the tropospheric reference time series of SF6 and of the AoA-dependent effective lifetime of SF6. The correction method is thoroughly tested within a self-consistent data set from a climate model that includes explicit calculation of chemical SF6 sinks. It is shown within the model that the correction successfully reduces biases in SF6-based AoA to less than 5 % for mean ages below 5 years. Tests using only subsampled data for deriving the fit coefficients show that applying the correction scheme even with imperfect knowledge of the sink is far superior to not applying a sink correction. Furthermore, we show that based on currently available measurements, we are not able to constrain the fit parameters of the correction scheme based on observational data alone. However, the model-based correction curve lies within the observational uncertainty, and we thus recommend using the model-derived fit coefficients until more high-quality measurements are able to further constrain the correction scheme. The application of the correction scheme to AoA from satellites and in situ data suggests that it is highly beneficial to reconcile different observational estimates of mean AoA.

Classifying and quantifying decadal changes in wet deposition over Southeast and East Asia using EANET, OMI, and GPCP

South East and East Asia are regions which have undergone rapid economic development, contributing a significant amount of urban and biomass burning emissions. While the connections between emissions, deposition, and impacts on the Earth System are theoretically understood, they are observationally and ill-constrained, especially with respect to the effects of a changing climate and the Monsoon. This work shows the results of a new classification scheme and Asian-Wide monthly wet deposition product based upon 16 years of surface wet deposition observations and remotely sensed trace gas and precipitation measurements throughout South East and East Asia. Specific information corresponding to underlying driving and physical processes including in-situ processing, long-range transport, and local emission sources are all considered. Scientific findings are made specifically with respect to the increased impacts of urban-scale change, long-range transport, and enhanced deposition under moderate to low precipitation conditions. Previously accepted definitions of clean and polluted areas are challenged and updated based upon more detailed analysis of the observed physical and chemical relationships and simple models. The spatial and temporal distribution of the resulting modeled wet deposition is shown to impact the oceans more significantly, and regions of land not previously thought to be heavily impacted.

Assessment of smoke plume height products derived from multisource satellite observations using lidar-derived height metrics for wildfires in the western US

Abstract. As wildfires intensify and fire seasons lengthen across the western US, the development of models that can predict smoke plume concentrations and track wildfire-induced air pollution exposures has become critical. Wildfire smoke plume height is a key indicator of the vertical placement of plume mass emitted from wildfire-related aerosol sources in climate and air quality models. With advancements in Earth observation (EO) satellites, spaceborne products for aerosol layer height or plume injection height have recently emerged with increased global-scale spatiotemporal resolution. However, to evaluate column radiative effects and refine satellite algorithms, vertical profiles of regionally representative aerosol properties from wildfires need to be measured directly. In this study, we conducted the first comprehensive evaluation of four passive satellite remote-sensing techniques specifically designed for retrieving plume height. We compared these satellite products with the airborne Wyoming Cloud Lidar (WCL) measurements during the 2018 Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign in the western US. Two definitions, namely, “plume top” and “extinction-weighted mean plume height”, were used to derive the representative heights of wildfire smoke plumes, based on the WCL-derived vertical aerosol extinction coefficient profiles. Using these two definitions, we performed a comparative analysis of multisource satellite-derived plume height products for wildfire smoke. We provide a discussion related to which satellite product is most appropriate for determining plume height characteristics near a fire event or estimating downwind plume rise equivalent height, under multiple aerosol loadings. Our findings highlight the importance of understanding the sensitivity of different passive remote-sensing techniques on space-based wildfire smoke plume height observations, in order to resolve ambiguity surrounding the concept of “effective smoke plume height”. As additional aerosol-observing satellites are planned in the coming years, our results will inform future remote-sensing missions and EO satellite algorithm development. This bridges the gap between satellite observations and plume rise modeling to further investigate the vertical distribution of wildfire smoke aerosols.

Urban–Rural Comparisons of Biogenic Volatile Organic Compounds and Ground-Level Ozone in Beijing

Ground-level ozone (O3) pollution has been a severe environmental and health problem for decades. The importance of biogenic volatile organic compounds (BVOCs) in the formation of tropospheric photochemistry O3 has been highlighted, especially in areas of rapid urbanization. We conducted simultaneous measurements of trace gases, including NO, NOX, O3, and BVOCs (i.e., isoprene and α-pinene), in the urban and rural forest areas of Beijing to determine the relationships between them. The results highlight the differences between the urban and rural forest areas of Beijing in terms of ambient air concentrations of BVOCs and O3, and the interrelationships between BVOCs, NOX, and ozone were quantified. Moreover, the isoprene concentration was found to be higher in the atmosphere of the urban site than of the rural site, which had higher α-pinene concentrations and higher O3 concentrations. The NOX concentration was higher at the urban site than at the rural site, and there was a significant exponential relationship between NOX and O3 at the urban site, indicating that the impact of NOx on O3 at the urban site was greater than that at the rural site. The O3 concentration increased with rising isoprene and α-pinene in both sites. In the case of substantially increased BVOC concentrations, declining NOX concentrations strongly promote the formation of O3. Consideration should be given to planting tree species with low-BVOC emissions, as they are crucial for mitigating O3 pollution in urban areas. Additionally, the relationships between BVOCs, NOX, and O3 should be considered in policymaking related to O3 control.

Modular Multiplatform Compatible Air Measurement System (MoMuCAMS): a new modular platform for boundary layer aerosol and trace gas vertical measurements in extreme environments

Abstract. The Modular Multiplatform Compatible Air Measurement System (MoMuCAMS) is a newly developed in situ aerosol and trace gas measurement platform for lower-atmospheric vertical profiling. MoMuCAMS has been primarily designed to be attached to a Helikite, a rugged tethered balloon type that is suitable for operations in cold and windy conditions. The system addresses the need for detailed vertical observations of atmospheric composition in the boundary layer and lower free troposphere, especially in polar and alpine regions. The MoMuCAMS encompasses a box that houses instrumentation, a heated inlet, a single-board computer to transmit data to the ground for in-flight decisions and a power distribution system. The enclosure can accommodate various combinations of instruments within its weight limit (e.g., 20 kg for a 45 m3 balloon). This flexibility represents a unique feature, allowing for the study of multiple aerosol properties (number concentration, size distribution, optical properties, chemical composition and morphology), as well as trace gases (e.g., CO, CO2, O3, N2O) and meteorological variables (e.g., wind speed and direction, temperature, relative humidity, pressure). Different instrumental combinations are therefore possible to address the specific scientific focus of the observations. It is the first tethered-balloon-based system equipped with instrumentation providing a size distribution for aerosol particles within a large range, i.e., from 8 to 3370 nm, which is vital to understanding atmospheric processes of aerosols and their climate impacts through interaction with radiation and clouds. Here we present a characterization of the specifically developed inlet system and previously unreported instruments, most notably the miniaturized scanning electrical mobility spectrometer and a near-infrared carbon monoxide monitor. As of December 2022, MoMuCAMS has been tested during two field campaigns in the Swiss Alps in winter and fall 2021. It was further deployed in Fairbanks, Alaska, USA, in January–February 2022, as part of the ALPACA (Alaskan Layered Pollution and Chemical Analysis) campaign and in Pallas, Finland, in September–October 2022, as part of the PaCE2022 (Pallas Cloud Experiment) study. Three cases from one of the Swiss Alpine studies are presented to illustrate the various observational capabilities of MoMuCAMS. Results from the first two case studies illustrate the breakup of a surface-based inversion layer after sunrise and the dilution of a 50–70 m thick surface layer. The third case study illustrates the capability of the system to collect samples at a given altitude for offline chemical and microscopic analysis. Overall, MoMuCAMS is an easily deployable tethered-balloon payload with high flexibility, able to cope with the rough conditions of extreme environments. Compared to uncrewed aerial vehicles (drones) it allows for observation of aerosol processes in detail over multiple hours, providing insights into their vertical distribution and processes, e.g., in low-level clouds, that were difficult to obtain beforehand.

Apportionment and Inventory Optimization of Agriculture and Energy Sector Methane Emissions Using Multi‐Month Trace Gas Measurements in Northern Colorado

AbstractQuantifying sector‐resolved methane fluxes in complex emissions environments is challenging yet necessary to improve emissions inventories and guide policy. Here, we separate energy and agriculture sector emissions using a dynamic linear model analysis of methane, ethane, and ammonia data measured at a Northern Colorado site from November 2021 to January 2022. By combining these sector‐apportioned observations with spatially resolved inventories and Bayesian inverse methods, energy and agriculture methane fluxes are optimized across the study's ∼850 km2 sensitivity area. Energy sector fluxes are synthesized with previous literature to evaluate trends in energy sector methane emissions. Optimized agriculture fluxes in the study area were 3.5× larger than inventory estimates; we demonstrate this discrepancy is consistent with differences in the modeled versus real‐world spatial distribution of agricultural sources. These results highlight how sector‐apportioned methane observations can yield multi‐sector inventory optimizations in complex environments.

Designing a Long Optical Path Direct-Injection-Integrated Cavity for Laser Absorption Spectroscopy

Trace gas measurement has a wide range of applications needed in industrial, medical, and environmental protection. With the evolution of time, the demand for real-time, sensitivity, and accuracy of gas detection has been increasingly heightened. Off-axis integrated cavity output spectroscopy (OA-ICOS) is an effective method for the high-sensitivity detection of trace gases. It uses an integrated cavity with two highly reflective mirrors to provide a long optical path, which guarantees its high sensitivity. However, as the reflectivity of the mirrors increases, the intensity of the output light decreases, and the signal-to-noise ratio decreases. This contradiction makes it difficult to achieve a long optical path and a high signal-to-noise ratio together. To combat this issue, this paper proposes a type of integrated cavity using a direct-injection method. This structure, under equivalent mirror conditions, can maintain an effective absorption optical path very close to the original off-axis integrated cavity while increasing the output light intensity hundreds of times. This enhancement increases the sensitivity of OA-ICOS.

Assumptions about prior fossil fuel inventories impact our ability to estimate posterior net CO2 fluxes that are needed for verifying national inventories

Monitoring national and global greenhouse gas (GHG) emissions is a critical component of the Paris Agreement, necessary to verify collective activities to reduce GHG emissions. Top-down approaches to infer GHG emission estimates from atmospheric data are widely recognized as a useful tool to independently verify emission inventories reported by individual countries under the United Nation Framework Convention on Climate Change. Conventional top-down atmospheric inversion methods often prescribe fossil fuel CO2 emissions (FFCO2) and fit the resulting model values to atmospheric CO2 observations by adjusting natural terrestrial and ocean flux estimates. This approach implicitly assumes that we have perfect knowledge of FFCO2 and that any gap in our understanding of atmospheric CO2 data can be explained by natural fluxes; consequently, it also limits our ability to quantify non-FFCO2 emissions. Using two independent FFCO2 emission inventories, we show that differences in sub-annual emission distributions are aliased to the corresponding posterior natural flux estimates. Over China, for example, where the two inventories show significantly different seasonal variations in FFCO2, the resulting differences in national-scale flux estimates are small but are significant on the subnational scale. We compare natural CO2 flux estimates inferred from in-situ and satellite observations. We find that sparsely distributed in-situ observations are best suited for quantifying natural fluxes and large-scale carbon budgets and less suitable for quantifying FFCO2 errors. Satellite data provide us with the best opportunity to quantify FFCO2 emission errors; a similar result is achievable using dense, regional in-situ measurement networks. Enhancing the top-down flux estimation capability for inventory verification requires a coordinated activity to (a) improve GHG inventories; (b) extend methods that take full advantage of measurements of trace gases that are co-emitted during combustion; and (c) improve atmospheric transport models.

Mobile Laboratory Investigations of Industrial Point Source Emissions during the MOOSE Field Campaign

Industrial emissions of trace gases and VOCs can be an important contributor to air quality in cities. Disentangling different point sources from each other and characterizing their emissions can be particularly challenging in dense industrial areas, such as Detroit, Dearborn and surrounding areas in Southeast Michigan (SEMI). Here, we leverage mobile measurements of trace gases and speciated volatile organic compounds (VOCs) to identify emitting sites. We characterize their complicated emissions fingerprints based on a core set of chemical ratios. We report chemical ratios for 7 source types including automakers, steel manufacturers, chemical refineries, industrial chemical use (cleaning; coatings; etc.), chemical waste sites, compressor stations, and more. The source dataset includes visits to over 85 distinct point sources. As expected, we find similarities between the different types of facilities, but observe variability between them and even at individual facilities day-to-day. Certain larger sites are better thought of as a collection of individual point sources. These results demonstrate the power of mobile laboratories over stationary sampling in dense industrial areas.

Overview and statistical analysis of boundary layer clouds and precipitation over the western North Atlantic Ocean

Abstract. Due to their fast evolution and large natural variability in macro- and microphysical properties, the accurate representation of boundary layer clouds in current climate models remains a challenge. One of the regions with large intermodel spread in the Coupled Model Intercomparison Project Phase 6 ensemble is the western North Atlantic Ocean. Here, statistically representative in situ measurements can help to develop and constrain the parameterization of clouds in global models. To this end, we performed comprehensive measurements of boundary layer clouds, aerosol, trace gases, and radiation in the western North Atlantic Ocean during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. In total, 174 research flights with 574 flight hours for cloud and precipitation measurements were performed with the HU-25 Falcon during three winter (February–March 2020, January–April 2021, and November 2021–March 2022) and three summer seasons (August–September 2020, May–June 2021, and May–June 2022). Here we present a statistical evaluation of 16 140 individual cloud events probed by the fast cloud droplet probe and the two-dimensional stereo cloud probe during 155 research flights in a representative and repetitive flight strategy allowing for robust statistical data analyses. We show that the vertical profiles of distributions of the liquid water content and the cloud droplet effective diameter (ED) increase with altitude in the marine boundary layer. Due to higher updraft speeds, higher cloud droplet number concentrations (Nliquid) were measured in winter compared to summer despite lower cloud condensation nucleus abundance. Flight cloud cover derived from statistical analysis of in situ data is reduced in summer and shows large variability. This seasonal contrast in cloud coverage is consistent with a dominance of a synoptic pattern in winter that favors conditions for the formation of stratiform clouds at the western edge of cyclones (post-cyclonic). In contrast, a dominant summer anticyclone is concomitant with the occurrence of shallow cumulus clouds and lower cloud coverage. The evaluation of boundary layer clouds and precipitation in the Nliquid ED phase space sheds light on liquid, mixed-phase, and ice cloud properties and helps to categorize the cloud data. Ice and liquid precipitation, often masked in cloud statistics by a high abundance of liquid clouds, is often observed throughout the cloud. The ACTIVATE in situ cloud measurements provide a wealth of cloud information useful for assessing airborne and satellite remote-sensing products, for global climate and weather model evaluations, and for dedicated process studies that address precipitation and aerosol–cloud interactions.

Comparison of photoacoustic spectroscopy and cavity ring-down spectroscopy for ambient methane monitoring at Hohenpeißenberg

Abstract. With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10−9), methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a 5 d period at Hohenpeißenberg, Germany. As a reference device, a calibrated cavity ring-down spectrometer, Picarro G2301, from the meteorological observatory of the German Weather Service (DWD) was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to fluctuating environmental conditions, e.g. ambient humidity. The obtained results show that for PA sensor systems non-radiative relaxation effects induced by varying humidity are a non-negligible factor. Applying algorithm compensation techniques, which are capable of calculating the influence of non-radiative relaxation effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 % from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.