Concept to assess the human perception of odour by estimating short-time peak concentrations from one-hour mean values. Reply to a comment by Janicke et al.

Schauberger, Günther; Piringer, Martin; Schmitzer, Rainer; Kamp, Martin; Sowa, Andreas; Koch, R.; Eckhof, Wilfried; Grimm, Ewald; Kypke, Joachim; Hartung, Eberhard

doi:10.1016/j.atmosenv.2012.02.017

Cited by 41 publications

(25 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The most comprehensive observations were made with lidars measuring the backscattered signal from smoke particles (Jørgensen and Mikkelsen, 1993;Mikkelsen et al, 2002;Jørgensen et al, 2010). Other studies have used lidars to measure SO 2 concentrations (Schröter et al, 2003). A particular advantage of lidars is that they can measure concentrations throughout the ABL and not only near the Earth's surface, where most in situ measurements have been made.…”

Section: Introductionmentioning

confidence: 99%

Observation of turbulent dispersion of artificially released SO2 puffs with UV cameras

et al. 2018

View full text Add to dashboard Cite

Abstract. In atmospheric tracer experiments, a substance is released into the turbulent atmospheric flow to study the dispersion parameters of the atmosphere. That can be done by observing the substance's concentration distribution downwind of the source. Past experiments have suffered from the fact that observations were only made at a few discrete locations and/or at low time resolution. The Comtessa project (Camera Observation and Modelling of 4-D Tracer Dispersion in the Atmosphere) is the first attempt at using ultraviolet (UV) camera observations to sample the three-dimensional (3-D) concentration distribution in the atmospheric boundary layer at high spatial and temporal resolution. For this, during a three-week campaign in Norway in July 2017, sulfur dioxide (SO2), a nearly passive tracer, was artificially released in continuous plumes and nearly instantaneous puffs from a 9 m high tower. Column-integrated SO2 concentrations were observed with six UV SO2 cameras with sampling rates of several hertz and a spatial resolution of a few centimetres. The atmospheric flow was characterised by eddy covariance measurements of heat and momentum fluxes at the release mast and two additional towers. By measuring simultaneously with six UV cameras positioned in a half circle around the release point, we could collect a data set of spatially and temporally resolved tracer column densities from six different directions, allowing a tomographic reconstruction of the 3-D concentration field. However, due to unfavourable cloudy conditions on all measurement days and their restrictive effect on the SO2 camera technique, the presented data set is limited to case studies. In this paper, we present a feasibility study demonstrating that the turbulent dispersion parameters can be retrieved from images of artificially released puffs, although the presented data set does not allow for an in-depth analysis of the obtained parameters. The 3-D trajectories of the centre of mass of the puffs were reconstructed enabling both a direct determination of the centre of mass meandering and a scaling of the image pixel dimension to the position of the puff. The latter made it possible to retrieve the temporal evolution of the puff spread projected to the image plane. The puff spread is a direct measure of the relative dispersion process. Combining meandering and relative dispersion, the absolute dispersion could be retrieved. The turbulent dispersion in the vertical is then used to estimate the effective source size, source timescale and the Lagrangian integral time. In principle, the Richardson–Obukhov constant of relative dispersion in the inertial subrange could be also obtained, but the observation time was not sufficiently long in comparison to the source timescale to allow an observation of this dispersion range. While the feasibility of the methodology to measure turbulent dispersion could be demonstrated, a larger data set with a larger number of cloud-free puff releases and longer observation times of each puff will be recorded in future studies to give a solid estimate for the turbulent dispersion under a variety of stability conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

Observation of turbulent dispersion of artificially released SO2 puffs with UV cameras

et al. 2018

View full text Add to dashboard Cite

show abstract

“…These criteria are defined by an odour threshold concentration of 0.25 ou E m −3 (= odour detection threshold of 1 ou E m −3 divided by the constant factor of 4) and an exceedance probability P = 10% for residential and mixed areas and P = 15% for commercial, industrial, agricultural areas. The constant factor of 4 is applied for all stability conditions and distances from the emission source, and it attends the purpose of assessing odour perception on the basis of a one-hour mean value [24]. Because the farm lies mostly in a rural environment, the exceedance probability P = 15% was selected.…”

Section: Odour Impact Criterionmentioning

confidence: 99%

A Comparative Analysis of Methods for Determining Odour-Related Separation Distances around a Dairy Farm in Beijing, China

Brancher

Yang

et al. 2019

Atmosphere

Self Cite

View full text Add to dashboard Cite

Concentrated animal feeding operations (CAFOs) such as dairy farms are a source of odorous compound emissions. In this study, by identifying relevant odour sources within a 300-head dairy farm and quantifying their emissions, we determined the separation distances to avoid odour annoyance around the dairy farm with two empirical models (Austrian and German Verein Deutscher Ingenieure (VDI) model) and a dispersion model (AERMOD). Besides, this study ponders on the selection of an appropriate meteorological station that best represents the area surrounding the farm. Results show that the maximum separation distances of an exceedance probability of P = 15% determined by the two empirical and the dispersion models are 524 m, 440 m and 655 m, while the minimum values are 202 m, 135 m, and 149 m, respectively. The NE–SW stretching separation distances match well with the wind rose. The mean ratios of separation distances determined by the two empirical models to that of the dispersion model are 1.23 and 0.95. Moreover, statistics of the separation distances indicate good accordance between the empirical models and the dispersion model.

show abstract

“…for example with respect to toxicity, flammability and odour detection (e.g. Hilderman et al, 1999;Schauberger et al, 2012;Gant and Kelsey, 2012) and non-linear chemical reactions (Brown and Bilger, 1996;Vilà-Guerau de Arellano et al, 2004;Cassiani et al, 2013). The complete description of turbulence remains one of the unsolved problems of physics.…”

Section: Introductionmentioning

confidence: 99%

Can statistics of turbulent tracer dispersion be inferred from camera observations of SO2 in the ultraviolet?

Kylling

Ardeshiri

Cassiani

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Turbulence is one of the unsolved problems of physics. Atmospheric turbulence and in particular its effect on tracer dispersion may be measured by cameras sensitive to the absorption of ultraviolet (UV) sun-light by sulfur dioxide (SO2), a gas that can be considered a passive tracer over short transport distances. We present a method to simulate UV camera measurements of SO2 with a 3D Monte Carlo radiative transfer model which takes input from a large eddy simulation (LES) of a SO2 plume released from a point source. From the simulated images the apparent absorbance and various plume density statistics (centerline position, meandering, absolute and relative dispersion, skewness, and fractal dimension) were calculated. These were compared with corresponding quantities obtained directly from the LES. Mean differences of centerline position, absolute and relative dispersion, and skewness between the simulated images and the LES were found to be smaller than a quarter of one camera pixel, with standard deviations between 1/2 and 3/2 camera pixel. Furthermore sensitivity studies were made to quantify how changes in solar azimuth and zenith angles, aerosol loading (background and in plume), and surface albedo impact the UV camera image plume statistics. Changing the values of these parameters within realistic limits have negligible effect on the centerline position, meandering, absolute and relative dispersions, and skewness of the SO2 plume. Thus, we demonstrate that UV camera images of SO2 plumes may be used to derive plume statistics of relevance for the study of atmospheric turbulent dispersion.

show abstract

Concept to assess the human perception of odour by estimating short-time peak concentrations from one-hour mean values. Reply to a comment by Janicke et al.

Cited by 41 publications

References 28 publications

Observation of turbulent dispersion of artificially released SO<sub>2</sub> puffs with UV cameras

Observation of turbulent dispersion of artificially released SO<sub>2</sub> puffs with UV cameras

A Comparative Analysis of Methods for Determining Odour-Related Separation Distances around a Dairy Farm in Beijing, China

Can statistics of turbulent tracer dispersion be inferred from camera observations of SO<sub>2</sub> in the ultraviolet?

Contact Info

Product

Resources

About

Concept to assess the human perception of odour by estimating short-time peak concentrations from one-hour mean values. Reply to a comment by Janicke et al.

Cited by 41 publications

References 28 publications

Observation of turbulent dispersion of artificially released SO&lt;sub&gt;2&lt;/sub&gt; puffs with UV cameras

Observation of turbulent dispersion of artificially released SO&lt;sub&gt;2&lt;/sub&gt; puffs with UV cameras

A Comparative Analysis of Methods for Determining Odour-Related Separation Distances around a Dairy Farm in Beijing, China

Can statistics of turbulent tracer dispersion be inferred from camera observations of SO&lt;sub&gt;2&lt;/sub&gt; in the ultraviolet?

Contact Info

Product

Resources

About

Observation of turbulent dispersion of artificially released SO<sub>2</sub> puffs with UV cameras

Observation of turbulent dispersion of artificially released SO<sub>2</sub> puffs with UV cameras

Can statistics of turbulent tracer dispersion be inferred from camera observations of SO<sub>2</sub> in the ultraviolet?