Michael Lichtenstern

The Deep Convective Clouds and Chemistry (DC3) Field Campaign

AbstractThe Deep Convective Clouds and Chemistry (DC3) field experiment produced an exceptional dataset on thunderstorms, including their dynamical, physical, and electrical structures and their impact on the chemical composition of the troposphere. The field experiment gathered detailed information on the chemical composition of the inflow and outflow regions of midlatitude thunderstorms in northeast Colorado, west Texas to central Oklahoma, and northern Alabama. A unique aspect of the DC3 strategy was to locate and sample the convective outflow a day after active convection in order to measure the chemical transformations within the upper-tropospheric convective plume. These data are being analyzed to investigate transport and dynamics of the storms, scavenging of soluble trace gases and aerosols, production of nitrogen oxides by lightning, relationships between lightning flash rates and storm parameters, chemistry in the upper troposphere that is affected by the convection, and related source character...

Magnetic maps of indoor environments for precise localization of legged and non-legged locomotion

The magnetic field in indoor environments is rich in features and exceptionally easy to sense. In conjunction with a suitable form of odometry, such as signals produced from inertial sensors or wheel encoders, a map of this field can be used to precisely localize a human or robot in an indoor environment. We show how the use of this field yields significant improvements in terms of localization accuracy for both legged and non-legged locomotion. We suggest various likelihood functions for sequential Monte Carlo localization and evaluate their performance based on magnetic maps of different resolutions. Specifically, we investigate the influence that measurement representation (e.g., intensity-based, vector-based) and map resolution have on localization accuracy, robustness, and complexity. Compared to other localization approaches (e.g., camera-based, LIDAR-based), there exist far fever privacy concerns when sensing the indoor environments magnetic field. Furthermore, the required sensors are less costly, compact, and have a lower raw data rate and power consumption. The combination of technical and privacy-related advantages makes the use of the magnetic field a very viable solution to indoor navigation for both humans and robots.

Operation of marine diesel engines on biogenic fuels: modification of emissions and resulting climate effects.

The modification of emissions of climate-sensitive exhaust compounds such as CO(2), NO(x), hydrocarbons, and particulate matter from medium-speed marine diesel engines was studied for a set of fossil and biogenic fuels. Applied fossil fuels were the reference heavy fuel oil (HFO) and the low-sulfur marine gas oil (MGO); biogenic fuels were palm oil, soybean oil, sunflower oil, and animal fat. Greenhouse gas (GHG) emissions related to the production of biogenic fuels were treated by means of a fuel life cycle analysis which included land use changes associated with the growth of energy plants. Emissions of CO(2) and NO(x) per kWh were found to be similar for fossil fuels and biogenic fuels. PM mass emission was reduced to 10-15% of HFO emissions for all low-sulfur fuels including MGO as a fossil fuel. Black carbon emissions were reduced significantly to 13-30% of HFO. Changes in emissions were predominantly related to particulate sulfate, while differences between low-sulfur fossil fuels and low-sulfur biogenic fuels were of minor significance. GHG emissions from the biogenic fuel life cycle (FLC) depend crucially on energy plant production conditions and have the potential of shifting the overall GHG budget from positive to negative compared to fossil fuels.

Simultaneous Localization and Mapping for pedestrians using distortions of the local magnetic field intensity in large indoor environments

We present a Simultaneous Localization and Mapping (SLAM) algorithm based on measurements of the ambient magnetic field strength (MagSLAM) that allows quasi-real-time mapping and localization in buildings, where pedestrians with foot-mounted sensors are the subjects to be localized. We assume two components to be present: firstly a source of odometry (human step measurements), and secondly a sensor of the local magnetic field intensity. Our implementation follows the FastSLAM factorization using a particle filter. We augment the hexagonal transition map used in the pre-existing FootSLAM algorithm with local maps of the magnetic field strength, binned in a hierarchical hexagonal structure. We performed extensive experiments in a number of different buildings and present the results for five data sets for which we have ground truth location information. We consider the results obtained using MagSLAM to be strong evidence that scalable and accurate localization is possible without an a priori map.

Aerosol layers from the 2008 eruptions of Mount Okmok and Mount Kasatochi: In situ upper troposphere and lower stratosphere measurements of sulfate and organics over Europe

In 2008 Mt. Okmok and Mt. Kasatochi started erupting on 12 July and 7 August, respectively, in the Aleutians, depositing emissions of trace gases and aerosols as high as 15.2 km into the atmosphere. During an aircraft campaign, conducted over Europe in October/November 2008, the volcanic aerosol was measured by an Aerodyne Aerosol Mass Spectrometer (AMS), capable of particle chemical composition measurements covering a size diameter range between 40 nm and 1 µm. In the volcanic aerosol layer enhanced submicron particulate sulfate concentrations of up to 2.0 µg m-3 standard temperature and pressure (STP) were observed between 8 and 12 km altitude while background values did not exceed 0.5 µg m-3 (STP). 21 % of the volcanic aerosol consisted of carbonaceous material that increased by a factor of 1.9 in mass compared to the free troposphere. Enhanced gaseous sulfur dioxide concentrations measured by an ion trap chemical ionization mass spectrometer (IT-CIMS) of up to 1.3 µg m-3 were encountered. An onboard radiation measurement system simultaneously detected an enhanced aerosol signal. Furthermore, two German lidar stations identified an aerosol layer before and after the campaign. Data analysis shows that the aerosol layer was observed mainly in the lowermost stratosphere. Correlation of particulate sulfate concentration and sulfur dioxide mixing ratios indicate that after 3 month residence time in the stratosphere not all sulfur dioxide has been converted into sulfate aerosol. The significant fraction of organic material might have implications on heterogeneous chemistry in the stratosphere which need to be explored more thoroughly

Biofuel blending reduces particle emissions from aircraft engines at cruise conditions

Aviation-related aerosol emissions contribute to the formation of contrail cirrus clouds that can alter upper tropospheric radiation and water budgets, and therefore climate. The magnitude of air-traffic-related aerosol–cloud interactions and the ways in which these interactions might change in the future remain uncertain. Modelling studies of the present and future effects of aviation on climate require detailed information about the number of aerosol particles emitted per kilogram of fuel burned and the microphysical properties of those aerosols that are relevant for cloud formation. However, previous observational data at cruise altitudes are sparse for engines burning conventional fuels, and no data have previously been reported for biofuel use in-flight. Here we report observations from research aircraft that sampled the exhaust of engines onboard a NASA DC‐8 aircraft as they burned conventional Jet A fuel and a 50:50 (by volume) blend of Jet A fuel and a biofuel derived from Camelina oil. We show that, compared to using conventional fuels, biofuel blending reduces particle number and mass emissions immediately behind the aircraft by 50 to 70 per cent. Our observations quantify the impact of biofuel blending on aerosol emissions at cruise conditions and provide key microphysical parameters, which will be useful to assess the potential of biofuel use in aviation as a viable strategy to mitigate climate change.

Providing real-time assistance in disaster relief by leveraging crowdsourcing power

AbstractCrowdsourcing platforms for disaster management have drawn a lot of attention in recent years due to their efficiency in disaster relief tasks, especially for disaster data collection and analysis. Although the on-site rescue staff can largely benefit from these crowdsourcing data, due to the rapidly evolving situation at the disaster site, they usually encounter various difficulties and have requests, which need to be resolved in a short time. In this paper, aiming at efficiently harnessing crowdsourcing power to provide those on-site rescue staff with real-time remote assistance, we design and develop a crowdsourcing disaster support platform by considering three unique features, viz., selecting and notifying relevant off-site users for individual request according to their expertise; providing collaborative working functionalities to off-site users; improving answer credibility via “crowd voting.” To evaluate the platform, we conducted a series of experiments with three-round user trials and also a System Usability Scale survey after each trial. The results show that the platform can effectively support on-site rescue staff by leveraging crowdsourcing power and achieve good usability .

A prototyping environment for interaction between a human and a robotic multi-agent system

In this paper we describe our prototyping environment to study concepts for empowering a single user to control robotic multi-agent systems. We investigate and validate these concepts by experiments with a fleet of hovering robots. Specifically, we report on a first experiment in which one robot is equipped with an RGB-D sensor through which the user is enabled to directly interact with a multi-agent system without the need to carry any device.

Airborne quantification of upper tropospheric NOx production from lightning in deep convective storms over the United States Great Plains

The reported range for global production of nitrogen oxides (NOx = NO + NO2) by lightning remains large (e.g., 32 to 664 mol NOx flash−1), despite incorporating results from over 30 individual laboratory, theoretical, and field studies since the 1970s. Airborne and ground-based observations from the Deep Convective Clouds and Chemistry experiment in May and June 2012 provide a new data set for calculating moles of NOx produced per lightning flash, P(NOx), in thunderstorms over the United States Great Plains. This analysis utilizes a combination of in situ observations of storm inflow and outflow from three instrumented aircraft, three-dimensional spatial information from ground-based radars and satellite observations, and spatial and temporal information for intracloud and cloud-to-ground lightning flashes from ground-based lightning mapping arrays. Evaluation of two analysis methods (e.g., a volume-based approach and a flux-based approach) for converting enhancements in lightning-produced NOx from volume-based mixing ratios to moles NOx flash−1 suggests that both methods equally approximate P(NOx) for storms with elongated anvils, while the volume-based approach better approximates P(NOx) for storms with circular-shaped anvils. Results from the more robust volume-based approach for three storms sampled over Oklahoma and Colorado during DC3 suggest a range of 142 to 291 (average of 194) moles NOx flash−1 (or 117–332 mol NOx flash−1 including uncertainties). Although not vastly different from the previously reported range for storms occurring in the Great Plains (e.g., 21–465 mol NOx flash−1), results from this analysis of DC3 storms offer more constrained upper and lower limits for P(NOx) in this geographical region.

On the origin of pronounced O3 gradients in the thunderstorm outflow region during DC3

Unique in situ measurements of CO, O3, SO2, CH4, NO, NOx, NOy, VOC, CN, and rBC were carried out with the German Deutsches Zentrum fur Luft- und Raumfahrt (DLR)-Falcon aircraft in the central U.S. thunderstorms during the Deep Convective Clouds and Chemistry experiment in summer 2012. Fresh and aged anvil outflow (9–12 km) from supercells, mesoscale convective systems, mesoscale convective complexes, and squall lines were probed over Oklahoma, Texas, Colorado, and Kansas. For three case studies (30 May and 8 and 12 June) a combination of trace species, radar, lightning, and satellite information, as well as model results, were used to analyze and design schematics of major trace gas transport pathways within and in the vicinity of the probed thunderstorms.