WATERWATER IINNOVATENNOVATE

Pascal HarperProduct Manager

2

Application Areas for

• Greenfield Sites– Incorporate odour emissions into process selection.

• Process Upgrades– Model comparisons between current and upgrade scenarios.– Provide variable emission rate data for OCU design (peak to

mean ratios).

• Odour Management Planning– Diurnal profiling of odour emissions.– Changes to process operation influencing odours (liquor return

rates/timings).

3

4

Odour modelling currently:

• Neglects formation and emission

• Doesn’t consider perception

• Focuses on dispersion using:

– emission rate estimation• simple measurements, lit. data, educated guesses

– steady state values• ER almost always treated as a constant in modelling

Background

5

• Emission rates are driven by:

– High mass transfer coefficient KL (wind/flow turbulence)

– High surface area A

– High odorant concentration in liquid phase CL (quality)

• Emission rate variations can be significant

H

CCAKER GLL

Importance of Emission Rates

6

• Analytical metric required for:– Modelling formation / transformation in the liquid phase– Modelling mass transfer from liquid to atmosphere– Modelling dispersion in the atmosphere

• Sensory metric required for:– Modelling human perception & likeliness of complaint

• ODOURsim® uses H2S as proxy for odour– Often the dominant odorant in wastewater– Easy to measure– Formation / transformation / mass transfers models available– Correlates with sensory measurements

Choice of Metric

7

ODOUR Correlation - Primary Treatment Processes

C(ou) = 10759C(H2S)0.9078

R2 = 0.978

1

10

100

1000

10000

100000

1000000

0.01 0.1 1 10 100

H2S (ppm)

Od

ou

r (o

u m

-3)

8

• Describes H2S behaviour in liquid phase

• Based on Hvitved-Jacobsen sewer model– Biofilms and suspended biomass– Considers anaerobic - aerobic

conditions– Useful for H2S formation

• Modified by:– Adding mechanism for H2S to

SO42- oxidation

• Describes movement of H2S & O2 into and out of liquid phase

• Based on mass transfer models for VOCs & O2 in the literature– quiescent surfaces, weirs/drop

structures, channels, dissolved air aeration, surface aeration, trickling filters

Liquid Phase Formation Model

Mass Transfer Emission Model

Model Basics

9

- Model Application

• Applied to hypothetical situation:– 10 km sewer

• Flows part-full at flows < daily average (Aerobic)• Flows full at flows > daily average (Anaerobic)

– Feeds simple primary treatment only STW

• Studies:– Effects of wind-driven PST emissions– Effects of flow & quality driven emissions

10

• Wind blowing over liquid surface drives emissions– Induces turbulence (and increases surface area) through formation of

waves

• Model simulation:– Used constant sulphide concentration in PST– Calculate emission rate vs. wind speed for 1 years Met. Data

– Apply results to dispersion model:• Using constant emission rate (the average for year)• Using variable emission rate linked to wind speed

0

5

10

15

20

25

30

35

40

Emission rate (g s-1 m-2)

% o

f hou

rs

avg

- Wind-Driven PST Emissions

11

Demonstrates importance of linking emission rate to wind speed for liquid surface emissions.

The constant (average) ER over-predicts odour footprint:• ER value too high at low wind speeds when dispersal poor• ER value too low at high wind speeds when dispersal good

- Wind-Driven PST Emissions

12

• Diurnal variations in influent wastewater drives emissions

– High flows induce turbulence over weirs – High sulphide concentrations in liquid phase

due to anaerobic conditions in the sewer

• Model simulation:

– Use constant wind speed over PSTs– Calculate emission rate vs diurnal flow and

load over 24 hrs– Observe:

• peaks in surface emissions due to elevated sulphide levels

• peaks in weir section emissions due to high flows

– Apply results to dispersion model using range emission rates calculated

0.00

0.05

0.10

0.15

0.20

0.25

0 4 8 12 16 20 24

Time (hour)

Co

ncen

trati

on

(g

m-3

)

0

0.2

0.4

0.6

0.8

1

1.2

Flo

w (

m3 s

-1)

SO

SH2S

Flow

0.0E+00

5.0E-05

1.0E-04

1.5E-04

2.0E-04

2.5E-04

0 4 8 12 16 20 24

Time

Em

issio

n R

ate

(g

s-1)

0

0.05

0.1

0.15

0.2

0.25

0.3

Flo

w (

m3 s

-1)

Surface ER

Weir ER

Total ER

Flow

- Flow and Quality Driven Emissions

13

Demonstrates the importance of linking emission rate to flow and quality parameters for weir and surface emissions.

There is a potential for large error in dispersion model predictions if single spot ER measurements used

- Flow & Quality Driven Emissions

14

Outcomes

• Emission rate variability is real

• Emission rate variability is driven by flow, quality, wind speed and temperature effects

• Emission rate variations have a significant impact on dispersion model predictions

• Emission rate variations should be included in dispersion model predictions– Percentile predictions have limited meaning if significant source of

variability is ignored

15

ODOURsim®

- Data Requirements

16

Case study

• Sampled Wastewater characteristics

– TCOD, SCOD, SH2S, pH, Temperature

• Micrometeorological Study carried out

– Measured H2S concentrations on site

– Measured wind velocity and direction– AERMOD model used to fit emissions

• Emission rates calculated by ODOURsim® used as hourly emission file in AERMOD

17

- Emission variation over 48 hrs

18

ODOURsim

UKWIR

Micromet

- Calibration Comparison

19

ODOURsim

UKWIR

Micromet

- Validation Comparison

20

Static emission ratesODOURsim® variable

emission rates

98 percentile contour plots