Report
Teaser, summary, work performed and final results
Periodic Reporting for period 2 - COMTESSA (Camera Observation and Modelling of 4D Tracer Dispersion in the Atmosphere)
Teaser
Turbulence is one of the long-standing big challenges in the atmospheric sciences. Kinetic energy produced at the largest atmospheric scales cascades down to the molecular scale where it dissipates, as described by L. F. Richardson’s (1922) poem: “Big whirls have little...
Summary
Turbulence is one of the long-standing big challenges in the atmospheric sciences. Kinetic energy produced at the largest atmospheric scales cascades down to the molecular scale where it dissipates, as described by L. F. Richardson’s (1922) poem: “Big whirls have little whirls that feed on their velocity, and little whirls have lesser whirls and so on to viscosity – in the molecular sense.†A related aspect of turbulence is its effect on tracer dispersion. Turbulence controls the dilution of pollution emitted into the atmospheric boundary layer (ABL). It determines how quickly tracers released at the surface are transported away – and this can limit the exchange process itself, with profound influence on fluxes of, e.g., water vapour or carbon dioxide (CO2).
A substance (a “passive scalarâ€) injected into a turbulent flow exhibits complex dynamical behaviour. Its distribution is chaotic, and the probability density function (PDF) of the scalar concentration field exhibits large fluctuations, which can depart substantially from Gaussian behaviour. While the PDF’s mean is often well accessible to measurements, little is known about its higher moments (variance, skewness, kurtosis). Yet, the higher moments are crucial if the relationship between the concentration fluctuations and their consequences is non-linear. For instance, toxicity, flammability and odour detection depend on exceedances of concentration thresholds. Non-linear chemical reactions are influenced by tracer fluctuations if the reaction and turbulence time scales are similar. E.g., the ozone formation in a pollution plume depends on how the plume mixes with the ambient air.
In field experiments, the concentration PDF has been measured mainly close to the ground but few data sets exist for higher altitudes. Based on these experiments, different functional forms for the concentration PDF were proposed based on purely empirical or partially theoretical ground. They, however, lack consistency and this is not surprising, given the small number of campaigns that could investigate the concentration fluctuations compared to the much larger number of experiments that allowed deriving the concentration means – and even for the means the understanding is poor for the stably stratified ABL (with downward directed surface heat flux). There, turbulence is weak and intermittent and air pollutants can sometimes accumulate to dangerous levels. Despite progress for the continuously turbulent stable boundary layer, theory of turbulence and wave structure under intermittent conditions is not well developed. Even the definition of the (typically shallow) height of the stable ABL is problematic and no unique single definition is accepted.
Dispersion modelling is limited by a lack of theoretical understanding as well as of experimental data. In past experiments, artificial tracers were released into the atmosphere and resulting atmospheric concentrations measured, mainly at discrete sampling locations. However, we notice two major shortcomings of most of these experiments: 1) The data collected were typically sufficient to derive the mean of the concentration PDF but insufficient to resolve its higher moments. To resolve this issue, large data sets of high-resolution (both in time and space) concentration measurements are needed. 2) There is a lack of experiments under highly stable conditions. In COMTESSA, we are executing a set of ground-breaking atmospheric tracer dispersion experiments to collect unprecedented four-dimensional (4D) tracer concentration data. These experiments are combined with state-of-the-art data analysis and modelling of turbulent dispersion, resulting in the development of new model parameterizations.
The experiments observe sulphur dioxide (SO2) puffs and plumes (both released artificially as well as from existing strong SO2 sources) with about nine simultaneously measuring cameras equipped with ultraviolet (UV) and infrared (IR) filters. Th
Work performed
In the first half of the COMTESSA project, we developed six ultraviolet (UV) and three thermal infrared (TIR) cameras, we set-up a Large Eddy Simulation model, used a radiative transfer model to produce virtual camera pictures, and performed first tests with a tomography algorithm using artificial (virtual) campaign data. Most importantly, during summer 2017, we carried out the first measurement campaign, while another one is currently being prepared and will take place in July 2018. In the following, we describe the work carried out in the five different activity fields as described in the project proposal:
1) Improvement of cameras
The original plan of the project was to purchase the UV and TIR SO2 cameras from a daughter company of NILU, Nicarnica Aviation, the sole vendor of such instruments. Unfortunately, F. Prata who is a leading expert on UV/TIR camera development and C. Bernardo who was the engineer responsible for building the SO2 cameras, both left the company before we could purchase the cameras. It became clear that after their leave the company was not able to build the UV and IR cameras according to our specifications. We therefore decided to build the cameras ourselves, directly at NILU. Fortunately, we could sub-contract some of the hardware and software development to C. Bernardo’s new company. As a result, the camera development was a close collaboration between NILU staff and C. Bernardo.
We built six UV SO2 camera systems. We choose a double-camera setup with two high sensitive UV cameras (PCO.ultraviolet), with high transmission band-path filters centered at ~310 nm and ~330 nm, which are placed behind 25 or 12 mm UV lenses. The framerates of the cameras is 7.3 Hz (full resolution) - 27 Hz (v4 binning). A co-aligned spectrometer (AvaSpec-ULS2048x64, Avantes) is used in combination with large SO2 containing glass cells for calibration of the measurements. A mechanical shutter is built in for automated dark measurements. Auxiliary instruments built into the camera comprise of a 10 MP visible camera, an accurate dual axis digital inclinometer (absolute accuracy 0.02°), +/-30° range, which can be set at two mounting positions, and a GPS receiver to determine the exact camera position and pose. We also built three TIR SO2 camera systems, which each integrate three co-located IR cameras (Xenics Gobi-384-GigE), equipped with three filters (centered at 8.62 µm, 10.00 µm and 10.87 µm) mounted behind a 40 mm f/1 lens. Images can be recorded with a maximum framerate of 84 Hz; co-adding of images (2, 4, ...) is done to reduce the signal-to-noise ratio. For calibration of the IR cameras a rotating black-body shutter is moved in front of the three camera lenses when the system temperature changes. Similar to the UV cameras, the TIR SO2 cameras contain three peripheral instruments, i.e. a visible camera, an inclinometer and a GPS. For both, the UV and the TIR cameras, system temperatures and humidity are recorded continuously. A separate computer box for each camera contains a high performance fanless embedded computer with a 1 TB solid-state disk, an AC/DC power supply, and polarity protection, so that the system can be operated with 220 V as well as with 12 V battery power.
Both camera systems are connected to a computer running software to control camera operation and record data. Due to the change of plans with respect to buying/building the cameras, the hardware construction took longer than planned but was finished in about month 19 of the project, just before the first campaign. The software for controlling the cameras was at that time still rudimentary but has been improved considerably since then. Now, the software is at a stage where the different instruments are time-synchronized to UTC using the integrated GPS and controlled by the same computer programme. The GPS location is stored as binary raw data to enable post-processing to receive cm-accuracy relative position of the cameras. Further wor
Final results
During the first COMTESSA campaign, we used UV cameras to monitor the dispersion of a tracer in the real atmosphere. This was the first time this has been done. We were limited by the bad weather but could nevertheless demonstrate that turbulence parameters (e.g., characterizing meandering, relative and absolute dispersion) can be retrieved from such data.
The experiment will be repeated in July 2018 on a larger scale and using also IR cameras. Given better weather conditions than in 2017, we should be able to obtain statistically robust dispersion parameters that can be used to test theory and large eddy simulations. Eventually, we hope to obtain data during an even larger range of meteorological conditions (e.g., different stability conditions) in future campaigns.
Website & more info
More info: https://comtessa-turbulence.net/.