Dataset Information

Industrial Odor Source Identification Based on Wind Direction and Social Participation.

ABSTRACT: Industrial odors have been a major concern in many communities in Colorado (USA). Odor source identification is important for any mitigation strategy. The aim of this work was to identify odor sources using wind direction and odor data collected by social participation. For more than one year residents reported time, date, location and description of the odor occurrence by means of a smartphone technology. The odor spatial distribution and wind roses generated from local stations were used to identify odor sources. The majority of odor reports happened in North Denver (57%) and Greeley (33%). North Denver analysis showed that a single facility that manufactures pet food was responsible for the pet food odor (the most reported odor, 81 reports). Dead animal and sewage odors were associated with a North Denver meat and grease recycling facility, and the Metro Wastewater treatment plant, respectively. Roofing tar odor was probably associated with a facility that treats crossties and utility poles with creosote. Another odor that was often described as a refinery odor was less likely to be associated with the Denver oil refinery and more likely to be associated with one of the four facilities in the northwest of Globeville that uses asphalt and creosote materials. In Greeley, most reports (133 reports) happened in LaSalle, a small town in the southern part of Greeley. All reports from LaSalle described one offensive odor that was produced by a biogas facility east of LaSalle. The feasibility of odor source identification using wind direction and social participation was demonstrated. A regional cooperation to reduce odor problems in North Denver is highly recommended.

SUBMITTER: Eltarkawe M

PROVIDER: S-EPMC6479448 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Industrial Odor Source Identification Based on Wind Direction and Social Participation.

Eltarkawe Mohamed M Miller Shelly S

International journal of environmental research and public health 20190408 7

Industrial odors have been a major concern in many communities in Colorado (USA). Odor source identification is important for any mitigation strategy. The aim of this work was to identify odor sources using wind direction and odor data collected by social participation. For more than one year residents reported time, date, location and description of the odor occurrence by means of a smartphone technology. The odor spatial distribution and wind roses generated from local stations were used to id ...[more]

PMID: 30965562

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Project description:BACKGROUND:Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird's flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird's direction) throughout a bird's journey. RESULTS:We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight. CONCLUSIONS:Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.

Dataset Information

Industrial Odor Source Identification Based on Wind Direction and Social Participation.

Publications

Industrial Odor Source Identification Based on Wind Direction and Social Participation.

Similar Datasets

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