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Forecasting odours

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by

Carlos Diaz

on 3 February 2016

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Transcript of Forecasting odours

Nowadays, it is possible to predict the
odour impact of an activity
by using
odour emission rates
at the source coupled with
dispersion modelling.
Forecasting odours
PrOlor
The New Tool for Prediction of Odour Incidents. A key frame for a better management of an industrial plant.
Watch in a screen when there was an impact in the neighbourhood at the same time that it was happening
Further improvement
A problem in common
David Cartelle Fernández, Carlos N. Díaz Jiménez*, Jose M. Vellón Graña, Ángel Rodríguez López.
NOSE2014
4th International Conference on Environmental Odour Monitoring & Control
14-17 September 2014, Venice Italy
Dispersion Models
Sensor gas emission monitoring
+
As the calculation capacity of the computers grew, it was
possible to calculate
and see the
odour plume
in nearly
real-time
with the help of a local weather station.
No way to prevent odour impact because
linked to a release of odours from minutes to hours beforehand!!!
Pattern recognition
+
Once the impact is observed at a real time, it is already
too late to take actions
to correct it.
No prevention
No control of processes
Many industrial activities can control their emission by means of operative actions:

decrease or delay in production.
Increase of the efficiency of the odour abatement system.
Use more chemicals.
Increasing the speed of air through the stack.
Etc...
If the industrial operator knows well in advance
when, where and which
is going to be the odour impact at the source, operative actions can be taken in order to prevent it!
Tomorrow at
18:00
there will be
from your
in
is based on the WRF+CALMET+CALPUFF model system, built and installed for Linux platforms
PrOlor
In prOlor, the WRF model is executed daily for a time horizon of 48h.
Data from the National Centers for Environmental Prediction (NCEP).
3 nested domains
Hourly data of over 20 meteorological parameters and at 27 different height levels.
Very high resolution: 3 km
WRF
CALMET
CALPUFF
WRF
Cluster LINUX of >30 processors and >48 Gigas RAM.. and scalable!!
Calculation time: 3 hours!!
CALMET
The WRF output file is processed by the CALWRF, a format accepted for CALMET.
Meteorological downscaling is done in CALMET - an increase in the WRF output model resolution (200-1000 meters)
CALPUFF
SRTM 3:
90 m
resolution
CNIG:
5 m
resolution.
GLCC: 250 m resolution
Digital Terrain Models used
Supercomputation
Input data needed to feed the CALPUFF modeling software
Resolution of 250 m and contain 22 types of land uses defined according to the LCCS (Land Cover Classification System).
The Prolor system is currently used in a
paper pulp factory
and in a
Rendering plant
.
Paper Pulp Factory
Modeling LOT gases
Was necessary to develop own chemical transformation libraries.
The paper pulp factory c
an now delay the production
in some critical hours to
minimize odour emission
at those hours.
Animal byproducts
processing plant
Everyday there is a new run and the operator can detect two days beforehand if there is going to be an impact in the population nearby.
Take action!!
Maximize/minimize flow at the stack
Delay/speed up productions units
Plant in stand by/full production

PrOlor
It is difficult to check the effectiveness of the method, as it is based on
actions that change the course of the future
.
The operator can comfortably check in an
android

smartphone
. No need to stay close to the office to take actions.
Conclusions
The online odour modelling software available in the market now is able to calculate impact in the receptors but there is
no time to take actions
beforehand.
Taking a
proactive approach
is the best way to save time, money and keep the industrial activity in compliance with the regulators and in peace with the neighbours.
PrOlor is able to
predict two days beforehand
the
odour impact
in a receptor.
If a facility have the
flexibility
to delay or modify their production units, then
a software like PrOlor will be very useful
.
Thanks for your Attention!
Any question?

Carlos Diaz.
www.prolor.net
Full transcript