Modeling Approach to Assess Odor Levels from Industrial Facilities

A&WMA Southern Section Conference 2015, Callaway Gardens, GA

Milena Borissova

Odor – Basic FactsOdor – RegulationsOdor – ModelingAERMOD modeling systemSample Case StudyDiscussions and Conclusions

Agenda

An odor is caused by one or more volatilized chemical compounds that humans or other animals perceive by the sense of olfaction

The odorant molecules trigger reaction from the olfactory neurons neurons mediate signals to the

olfactory bulb bulb sends electric signals to the brain to form specific smell perception

There are different types of olfactory neurons responding to different odorants

Odor - Basic Facts

Odor sensation usually depends on the odorant concentration. A single

odorant is typically recognized by multiple neurons, and different

odorants may be recognized by combinations of neurons.

The combined signals create specific patterns, identified by the brain as

odors. The olfactory system does not interpret a single compound, but

instead the whole odorous mix

Odor sensation not necessarily corresponds to concentration or intensity

of any single constituent.

Odors could be harmful: causing headaches, nausea, and all stress

symptoms

Odor - Basic Facts (cont.)

Most odors consist of organic compounds – acetone, benzene; others do not containing carbon atoms – hydrogen sulfide (H2S), ammonia (NH3)

Habituation effect – after continuous odor exposure, the sense of smell dissipates quickly, but recovers rapidly after the stimulus is removed.

Brain tends to ignore continuous stimulus and focus on differences and changes in a particular sensation.

An objective and analytical measure of odor is impossible. Odor sensation and perception are very individual and are related to gender, age, state of health, and personal history.

Odor - Basic Facts (cont.)

Odor emission complex mixture of many odorous compounds.

=> Analytical monitoring of individual chemical compounds is not practical.

=> For measuring odors, sensory methods, instead of instrumental, are normally used.

Today odor sensory methods are available for both monitoring emissions from sources establishing odor quantities in ambient air.

For monitoring purposes odor has 5 properties related to threshold and tolerance: Concentration, Intensity, Quality, Hedonic Tone, and Character

Measuring Odor

Odor concentration is the odor's characteristics of pervasiveness. To measure odor sensation, an odor is diluted to certain amounts such that it reaches a detection or recognition threshold. • The detection threshold is the concentration of an odor in air when 50% of a population can distinguish

between the odorous sample and an odor free blank.

• The recognition threshold is the concentration of an odor in air in which 50% of a population can discern the type of odor from an odorous sample and odor free blank. The recognition odor threshold is usually a factor of 2 to 5 times higher than the detection threshold.

The measurement of odor concentration is the most widespread method to quantify odors. The method is based on dilution of an odor sample to the detection threshold. The numerical value of the odor concentration is equal to the dilution factor that is necessary to reach the detection threshold – Dilution-to-Threshold method (D/T). Odor concentration is expressed odor units (OU); odor threshold concentration is 1 OUE by definition.

n-Butanol is used as calibration gas for odor concentration measurements:

1 OU/m3 ≡ 40 ppb/v n-butanol

Odor Properties – Concentration

Odor Properties – Concentration

Butanol Scale

D/T (OU) Word Category

2 Noticeable

7 Objectionable

15 Nuisance

31 Nauseating

Odor intensity is the perceived strength of odor sensation. This intensity property is used to locate the source of odors and perhaps most directly related to odor nuisance.

Perceived strength of the odor sensation is measured in conjunction with odor concentration. This can be modeled by the Weber-Fechner law:

I = a × log(c) + bI - the perceived intensity,

a - the Weber-Fechner coefficient, odorant specific

c - the chemical concentrations,

b - the intercept constant

Odor intensity can be divided into the following categories according to intensity: 0 – no odor; 1 – very weak (odor threshold); 2 – weak; 3 – distinct; 4 – strong; 5 – very strong; 6 – intolerable

Odor Properties – Intensity

Currently world-wide there is no regulatory system to enforce odor controls.

Odor guidelines in the form of either a nuisance law (common in certain states in the USA) as National Air Quality Standards (Australia, New Zealand, Europe, Canada). The laws range wildly between states and between countries, partly because

of the "gray line" that exists between whether odors are a nuisance or whether the odor has negative health effect.

44 of the 50 states have regulations that deal directly or indirectly with odors from concentrated animal feeding operations

Odor Regulations

Measuring nomenclature is adopted in modeling – express odorant quantities in OU using specific scales

The mechanisms of odorant dispersion in the atmosphere are the same as the dispersion of other pollutants – criteria, TAPs, VOCs, therefore the commonly known dispersion models are utilized; no odor specific models have been developed

For modeling purposes a specific chemical is identified as dominant and selected as a surrogate of the odorant. We could model more than one chemical compound, but have no means to combine their composite impact as single odorant impact

Odor and Dispersion Modeling

This study deals with ambient air odorants dispersion (not indoor)

The selected model is the latest version of the EPA’s regulatory system – the AERMOD 15181 suite

Odor impact depend on:• Odorant emission rates• Source type• Averaging time / model time resolution• Meteorological conditions• Terrain and land use features• Modeling options

Odor and Dispersion Modeling

AERMOD modeling system is a steady-state Gaussian dispersion model comprised of several modules:

Meteorological module – AERMET Terrain module – AERMAP Dispersion module – AERMOD Additional pre/post-processors: AERMINUTE,

AERSURFACE, AERPLOT, LEADPOST

More about each module will be discussed in terms of the case study that follows

AERMOD Modeling System

H2S AERMOD MODELINGTest Case for Fictional Industrial

Facility at Callaway Gardens

Industrial area source complex from a typical Pulp and Paper facility assumed to be located at Callaway Gardens – Callaway site

Sources of fugitive type: Polishing Pond, Stabilization Basin, Step Aerator, and Clarifier

Emission rates: H2S concentrations at the sources were collected in 3 consecutive monitoring campaigns, lasting about an hour

Continuous hourly H2S emission rates derived to initialize the model and used as a surrogate of the odorant emissions

Source Description

Source Description

Meteorological data for 2014:• Surface data – hourly and ASOS 1-minute winds: Columbus Metropolitan

airport, Columbus, GA; station is approximately 22.5 miles to the south of project site

• Upper Air data: Falcon Field station, Atlanta, GA

Surface micrometeorological parameters derived from land characteristics of the Callaway site, allowing for seasonal variations and assuming 2014 is a year of average precipitation

ADJ_U* option used – non-default model option, intended to improve AERMOD performance in light wind, stable atmospheric conditions

Meteorology

H2S AERMOD MODELING

50 meter (164 ft) spaced receptor points were placed within 1km-wide belt around the facility boundary

The largest impacts from ground level sources are anticipated close to the sources

Terrain elevations and hill heights were extracted with AERMAP

Minimum source-to-receptor distance varies within 90 – 200 meters

Receptor Grid

Receptor Grid

AERMOD v.15181 ran in Non-default LOWWIND3 mode, with rural dispersion coefficients

No parametrization for chemical transformations

Constant hourly emission rates assuming year-round continuous operations; no seasonal variations to account for different evaporation rates, operational loads…

Sources represented as ground level release with no initial dispersion; emission rates are independent of wind speed

Odor impacts are expressed in terms of H2S concentrations in OU, calculated on the butanol scale

AERMOD Dispersion

Maximum Predicted Impacts

Averaging Period

Concentration (OU)

Odor Character

Number of Noticeable

level Exceedances

1-Hour 20.33 Nuisance 830

8-Hour 6.89 Noticeable 137

24-Hour 3.49 Noticeable 25

Annual 0.69 Undetectable 0

Maximum impacts occur during the cold season, on the hours of light winds and stable atmospheric conditions – clear, cold, and calm January mornings just before sunrise

Maximum 1-hour Concentrations

Concentration (OU)

No. of Receptors

2 653

7 65

15 4

31 0

Maximum impact occurs on Jan 26, hour 8; WS = 0.57 m/s (1.3 mph) just before the morning inversion broke

Maximum 1-hour Exceedances

Change of Concentrations

0 720 1440 2160 2880 3600 4320 5040 5760 6480 7200 7920 8640

-22

-20

-18

-16

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

22

Concentration Change in Time [dC/dt] at the Receptor of the Peak Impact

Time (hours)

Con

cent

rati

on C

hang

e (O

IU/h

r)

Positive values indicate increase of concentrations relative to the hour before

The peak impacts are predicted to the west of the facility boundary and can be classified to reach level nuisance with probability less than 10%

Highest impacts are localized close to the sources – at the facility boundary

Odor events at nuisance level are equally possible throughout the entire year; reaching levels of nauseating is unlikely

Summary of Results

Discussions and Conclusions

Benefits of modeling:

Modeling is less expensive and faster than monitoring and allows for variations

Modeling provides continuous analysis for long periods and different atmospheric conditions

Monitoring of fugitive sources emissions – very difficult, at this time rarely performed

Discussions

Areas of possible Improvement: Sub-hourly emissions and meteorology would characterize the odor events

better

Variable emission rates and variable source parameters (area) would provide more realistic representation.

Better speciation; only H2S was analyzed. New odor specific model would be best

Local site-specific odor calibration study would be huge improvement

Local meteorological data are essential for accurate assessment

Guidelines and regulations

Conclusions

Questions?