Biomass burning pollution in the summer time Arctic atmosphere : Development and deployment of a novel airborne CI-ITMS instrument for PAN detection

The present work aims for a better understanding of the reactive nitrogen and ozone budgets of the Arctic summer atmosphere. Special focus is paid to the organic nitrogen compound PAN (Peroxyacetyl nitrate), which as temporary reservoir species plays a key role especially during longrange transport of pollutants. For the first time, a chemical ionization - ion trap mass spectrometer (CI-ITMS) was equipped with an I- ion source for the detection of PAN. The new FASTPEX (Fast Measurement of Peroxyacyl nitrates) instrument successfully was deployed aboard the research aircraft Falcon during POLARCAT - GRACE campaign (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport - Greenland Aerosol and Chemistry Experiment) in summer 2008, which was conducted within the framework of the International Polar Year (IPY) 2007 - 2009. Continuous in-flight calibrations were performed using a newly set-up isotopic PAN calibration source. An in-flight intercomparison during GRACE showed very good agreement between the PAN measurements of the new FASTPEX instrument and the PAN measurements aboard the research aircraft NASA DC8. The GRACE measurements revealed that the Arctic free troposphere in summer is heavily perturbed by aged inflow from the boreal fire regions of Canada and Siberia. PAN was found to be the dominant reactive nitrogen species at altitudes between ca. 4 and 9km. While nitrogen oxide (NO) in the free troposphere was close to the detection limit of several pmol/mol, PAN was abundant at median mixing ratios of ca. 300pmol/mol. Low photochemical ozone formation was observed in imported pollution plumes. This is the result of fast conversion of NOx (NOx =NO+NO2) to PAN in young fire emissions, in combination with the high thermal stability of PAN during subsequent transport towards Greenland. A detailed case study provided first observational evidence of an efficient transport pathway for surface emissions into the lowermost stratosphere, which was previously suggested by model simulations. The anthropogenic pollution was detected by enhanced mixing ratios of PAN and CO above the tropopause. Air mass trajectory calculations showed that the Asian emissions were lifted within a warm conveyor belt (WCB) and reached the lowermost stratosphere within a few days after emission

Towards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scans

The retrieval of turbulence parameters with profiling Doppler wind lidars (DWLs) is of high interest for boundary layer meteorology and its applications. DWLs provide wind measurements above the level of meteorological masts while being easier and less expensive to deploy. Velocity-azimuth display (VAD) scans can be used to retrieve the turbulence kinetic energy (TKE) dissipation rate through a fit of measured azimuth structure functions to a theoretical model. At the elevation angle of 35.3° it is also possible to derive TKE. Modifications to existing retrieval methods are introduced in this study to reduce errors due to advection and enable retrievals with a low number of scans. Data from two experiments are utilized for validation: first, measurements at the Meteorological Observatory Lindenberg–Richard-Aßmann Observatory (MOL-RAO) are used for the validation of the DWL retrieval with sonic anemometers on a meteorological mast. Second, distributed measurements of three DWLs during the CoMet campaign with two different elevation angles are analyzed. For the first time, the ground-based DWL VAD retrievals of TKE and its dissipation rate are compared to in situ measurements of a research aircraft (here: DLR Cessna Grand Caravan 208B), which allows for measurements of turbulence above the altitudes that are in range for sonic anemometers. From the validation against the sonic anemometers we confirm that lidar measurements can be significantly improved by the introduction of the volume-averaging effect into the retrieval. We introduce a correction for advection in the retrieval that only shows minor reductions in the TKE error for 35.3° VAD scans. A significant bias reduction can be achieved with this advection correction for the TKE dissipation rate retrieval from 75° VAD scans at the lowest measurement heights. Successive scans at 35.3 and 75° from the CoMet campaign are shown to provide TKE dissipation rates with a good correlation of R>0.8 if all corrections are applied. The validation against the research aircraft encourages more targeted validation experiments to better understand and quantify the underestimation of lidar measurements in low-turbulence regimes and altitudes above tower heights

Quantifying methane emissions from coal mining ventilation shafts using an unmanned aerial vehicle (UAV)-based active AirCore system

A large quantity of CH4 is emitted to the atmosphere via ventilation shafts of underground coal mines. According to the European Pollutant Release and Transfer Register (E-PRTR), hard coal mines in the Upper Silesia Coal Basin (USCB) are a strong contributor (447 kt CH4 in 2017) to the annual European CH4 emissions. However, atmospheric emissions of CH4 from coal mines are poorly characterized, as they are dispersed over large areas. As part of the Carbon Dioxide and CH4 Mission (CoMet) pre-campaign, a study of the USCB's regional CH4 emissions took place in August 2017. We flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 mole fractions downwind of a single coal mining ventilation shaft. Besides CH4, we also measured CO2, CO, atmospheric temperature, pressure, and relative humidity. Wind-speed and wind-direction measurements were made using a lightweight balloon-borne radiosonde. Fifteen UAV flights were performed flying perpendicular to the wind direction at several altitude levels, to effectively build a ‘curtain’ of CH4 mole fractions in a two-dimensional plane at a distance between 150 and 350 m downwind of a single ventilation shaft. Furthermore, we have developed an inverse Gaussian approach for quantifying CH4 emissions from a point source using the UAV-based observations, and have applied it as well as the mass balance approach to both simulated data and actual flight data to quantify CH4 emissions. The simulated data experiments revealed the importance of having multiple transects at different altitudes, appropriate vertical spacing between the individual transects, and proper distance between the center height of the plume and the center flight transect. They also showed that the inverse Gaussian approach performed better than the mass balance approach. Our estimate of the CH4 emission rates from the sampled shaft ranges from 0.5 to 14.5 kt/year using a mass balance approach, and between 1.1 and 9.0 kt/year using an inverse Gaussian method. The average difference between the mass balance and the inverse Gaussian approach was 2.3 kt/year. Based on the observed correlation between CO2 and CH4 (R-squared > 0.69), the CO2 emissions from the shaft were estimated to be between 0.3 and 9.8 kt/year. This study demonstrates that the UAV-based active AirCore system provides an effective way of quantifying coal mining shaft emissions of CH4 and CO2

Lightning-produced NO_x over Brazil during TROCCINOX: Airborne measurements in tropical and subtropical thunderstorms and the importance of mesoscale convective systems

International audienceDuring the TROCCINOX field experiments in February?March 2004 and February 2005, airborne in situ measurements of NO, NOy, CO, and O3 mixing ratios and the J(NO2) photolysis rate were carried out in the anvil outflow of thunderstorms over southern Brazil. Both tropical and subtropical thunderstorms were investigated, depending on the location of the South Atlantic convergence zone. Tropical air masses were discriminated from subtropical ones according to the higher equivalent potential temperature (?e) in the lower and mid troposphere, the higher CO mixing ratio in the mid troposphere, and the lower wind velocity and proper wind direction in the upper troposphere. During thunderstorm anvil penetrations, typically at 20?40 km horizontal scales, NOx mixing ratios were on average enhanced by 0.2?1.6 nmol mol?1. This enhancement was mainly attributed to NOx production by lightning and partly due to upward transport from the NOx-richer boundary layer. In addition, CO mixing ratios were occasionally enhanced, indicating upward transport from the boundary layer. For the first time, the composition of the anvil outflow from a large, long-lived mesoscale convective system (MCS) advected from northern Argentina and Uruguay was investigated in more detail. Over a horizontal scale of about 400 km, NOx, CO and O3 mixing ratios were significantly enhanced in these air masses in the range of 0.6?1.1, 110?140 and 60?70 nmol mol?1, respectively. Analyses from trace gas correlations and a Lagrangian particle dispersion model indicate that polluted air masses, probably from the Buenos Aires urban area and from biomass burning regions, were uplifted by the MCS. Ozone was distinctly enhanced in the aged MCS outflow, due to photochemical production and entrainment of O3-rich air masses from the upper troposphere ? lower stratosphere region. The aged MCS outflow was transported to the north, ascended and circulated, driven by the Bolivian High over the Amazon basin. In the observed case, the O3-rich MCS outflow remained over the continent and did not contribute to the South Atlantic ozone maximum

Quantification of CH4 coal mining emissions in Upper Silesia by passive airborne remote sensing observations with the Methane Airborne MAPper (MAMAP) instrument during the CO2 and Methane (CoMet) campaign

Methane (CH4) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide (CO2). Because of its short atmospheric lifetime relative to that of CO2, the reduction of the atmospheric abundance of CH4 is an attractive target for short-term climate mitigation strategies. However, reducing the atmospheric CH4 concentration requires a reduction of its emissions and, therefore, knowledge of its sources. For this reason, the CO2 and Methane (CoMet) campaign in May and June 2018 assessed emissions of one of the largest CH4 emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this study, we will focus on CH4 column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the weighting-function-modified differential optical absorption spectroscopy (WFM-DOAS) method. The column anomalies, combined with wind lidar measurements, are inverted to cross-sectional fluxes using a mass balance approach. With the help of these fluxes, reported emissions of small clusters of coal mine ventilation shafts are then assessed. The MAMAP CH4 column observations enable an accurate assignment of observed fluxes to small clusters of ventilation shafts. CH4 fluxes are estimated for four clusters with a total of 23 ventilation shafts, which are responsible for about 40 % of the total CH4 mining emissions in the target area. The observations were made during several overflights on different days. The final average CH4 fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH4 h−1 at the time of the campaign. The fluxes observed at one cluster during different overflights vary by as much as 50 % of the average value. Associated errors (1σ) are usually between 15 % and 59 % of the average flux, depending mainly on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement within the uncertainties. If only emissions reported annually are available for comparison with the observations, caution is advised due to possible fluctuations in emissions during a year or even within hours. To measure emissions even more precisely and to break them down further for allocation to individual shafts in a complex source region such as the USCB, imaging remote sensing instruments are recommended

Local-to-regional methane emissions from the Upper Silesian Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Coal mining accounts for ~12% of the total anthropogenic methane (CH4) emissions worldwide. The Upper Silesian Coal Basin (USCB), Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coal bed CH4 emissions into the atmosphere are poorly characterized. As part of the carbon dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May-June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150-300m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speed, and surface wind direction. We used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2Combining double low line0.7-0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified. As an alternative, we have developed three upscaling approaches, i.e., by scaling the European Pollutant Release and Transfer Register (E-PRTR) annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate, which are derived from the hourly emission inventory. These estimates are in the range of 256-383ktCH4yr-1 for the inverse Gaussian (IG) approach and 228-339ktCH4yr-1 for the mass balance (MB) approach. We have also estimated the total CO2 emissions from coal mining ventilation shafts based on the observed ratio of CH4/CO2 and found that the estimated regional CO2 emissions are not a major source of CO2 in the USCB. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) — Sensitivity studies and evaluation using airborne measurements of power plant emissions

The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ-scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results; ii) the evaluation of the mixing properties of five different turbulence models using the well-mixed criterion; and iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitivity study, we analyse the effects of stability class, roughness length, zero-plane displacement factor and source height on the three-dimensional plume extent as well as the distance between source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbulence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6% from the expected uniform concentration below 80% of the mixing layer height except for the default turbulence model of ARTM 3.0.0 with deviations by up to 18%, respectively. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland measured by the DLR Cessna aircraft during the CoMet campaign in 2018 allow to evaluate the model performance for the different turbulence models under unstable boundary layer conditions