Dispersion Modeling Approach to Assess the Odour Impact from an Industrial Source at Residential Buildings in Urban Areas

Transcription

1 Dispersion Modeling Approach to Assess the Odour Impact from an Industrial Source at Residential Buildings in Urban Areas Attilio Poli Envirosolutions & Consulting, Singapore Better Air Quality 2012 Hong Kong, 5-7 December 2012

2 A real world problem Odorous Emission Source Only 150 meters distance Residential Buildings

3 Odour Basic concepts Detection threshold the lowest odorant concentration necessary for detection by a certain percentage of the population, normally 50%. This concentration is defined as 1 odour unit. Intensity the perceived strength of an odour above its threshold. It is determined by an odour panel and is described in categories which progress from not perceptible, then very weak, through to extremely strong

4 Odour Basic concepts Character what the odour smells like. It allows one to distinguish between different odours. For example, ammonia gas has a pungent and irritating smell. The character of an odour may change with dilution Hedonic Tone the degree to which an odour is perceived as pleasant or unpleasant. It may differ widely from person to person, and is also strongly influenced by previous experience and emotions at the time of odour perception

5 Odour: factors influencing complaints Frequency Intensity Duration Objective Offensiveness Location Subjective Chemical odours associated with industry may be offensive and, moreover, are associated to possible impacts on human health.

6 Odour study in 5 steps Stack Sampling & Analysis using Dynamic Olfactometry Electronic Nose Monitoring at Stacks and at Receptors Collection of meteorological and emission parameters Modelling of odour impacts using at full year of meteorological data; Recommendations of appropriate odour acceptability criteria.

7 Sampling and Analysis of Odorous Assessment using the binary forcedchoiced method from a panel of odour observers. Panel selected based on sensitivity to the reference odorant n-butanol. Odour analysis carried out in an odour quality control room. Samples are collected using a 40L nalophan air bag by drawing air through a calibrated air sampling pump with a flow rate of 2.5 l/min over a 15 minutes sampling period. The air samples are then analysed using a dynamic olfactometer.

8 Emission Data Stack Exit Velocity [m/s] Temperature [ C] Concentration (Ou/m3) Stack Stack Stack Stack Stack Stack Stack Stack Stack Stack

9 Electronic Nose Monitoring Transportable GC to speciate and quantify organic compounds Electronic nose allows detecting the presence of volatiles and their relative weight Unless the substances to be searched are previously known and suitably fingerprinted with the specific used equipment, it is not possible to state the individual compounds detected Continuous monitoring at stack gives relevant information on the time pattern

10 Electronic Nose Monitoring - Results 24 hours monitoring at each stack Samples taken also at receptor location on occasion of a complaint

11 Local Meteorology two complaints episodes

12 Local Meteorology One year hourly data Wind speed [m/s] Wind direction [10 sector] Ambient temperature [ C] Cloud cover [Eights]

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14 Air Dispersion Modeling Emissions Meteo Data Receptors Air Quality Modeling

15 Air Quality Model Selected Model: ADMS 4.2 US EPA accepted alternative model new generation Gaussian air dispersion model includes specific modules useful for the project Odours Dispersion around buildings Plume rise Time varying emissions

16 Air Quality Modeling Simulated Scenarios Business as Usual (BaU) conditions: emission rates coming from the dynamic olfactometry. Worst Case Normal Conditions (WCNC) related with maintenance and/or cleaning regularly occurring. Applying a factor of 2.5 to BaU emissions WCNC taken as baseline scenario Simulated Heights: 2m, 10m, 20m, 30m, 40m, 50m Mitigation Measures Scenarios Scenario 1 - Stack Height increase (10 m) Scenario 2 - Exit Velocity increase (20 m/s ) Scenario 3 - Temperature increase (45 C) Scenario 4 - Mixed Exit Velocity and Temperature increase (20 m/s and 35 C) Scenario 5 - Mixed Exit Velocity and Temperature increase (20 m/s and 28 C)

17 Baseline Scenario Worst Case Normal Conditions

18 Scenario 1 WSCNC & 10m Stack Height

19 Scenario 2 WSCNC & 20 m/s Exit velocity

20 Scenario 3 WSCNC & Temperature increase (45 ºC) 30 m 40 m 50 m

21 Mixed Scenario Exit velocity (20 m/s) & Temperature increase (45 ºC) 30 m 40 m 50 m

22 Conclusions Preliminary investigations (weather conditions and electronic nose findings) indicated that plant exhausts were possible to cause odour issues and then the right target of the neighbourhood complaints Modeling results tallied with monitoring findings and location of complaints (higher floors of the surrounding buildigs) Air Quality Modeling methodology has proven as an effective approach to understand the problem and to test alternative mitigation measures The mixed implementation of Good Engineering Practices (GEP) has been found as the most effective (eliminating annoyance) and efficient (in terms of costs) to get the problem solved

23 Thank you for your attention Thank you for your attention Attilio A. Poli