Forecasting odours

A problem in common

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...

Nowadays, it is possible to predict the odour impact of an activity by using odour emission rates at the source coupled with dispersion modelling.

No way to prevent odour impact because linked to a release of odours from minutes to hours beforehand!!!

PrOlor

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!

Once the impact is observed at a real time, it is already too late to take actions to correct it.

Tomorrow at

18:00

there will be

from your

in

Further improvement

Dispersion Models

No prevention

Watch in a screen when there was an impact in the neighbourhood at the same time that it was happening

No control of processes

+

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.

Sensor gas emission monitoring

+

Pattern recognition

Forecasting odours

Conclusions

PrOlor

is based on the WRF+CALMET+CALPUFF model system, built and installed for Linux platforms

• 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.

Cluster LINUX of >30 processors and >48 Gigas RAM.. and scalable!!

• PrOlor is able to predict two days beforehand the odour impact in a receptor.

WRF

CALPUFF

CALMET

WRF

CALMET

CALPUFF

• 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.

The WRF output file is processed by the CALWRF, a format accepted for CALMET.

The Prolor system is currently used in a paper pulp factory and in a Rendering plant.

Digital Terrain Models used

PrOlor

Paper Pulp Factory

Animal byproducts

processing plant

• Modeling LOT gases

• It is difficult to check the effectiveness of the method, as it is based on actions that change the course of the future.

• 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.

SRTM 3: 90 m resolution

CNIG: 5 m resolution.

• Was necessary to develop own chemical transformation libraries.

• Take action!!

• The operator can comfortably check in an android smartphone. No need to stay close to the office to take actions.

• Maximize/minimize flow at the stack
• Delay/speed up productions units
• Plant in stand by/full production

• The paper pulp factory can now delay the production in some critical hours to minimize odour emission at those hours.

• 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

GLCC: 250 m resolution

Resolution of 250 m and contain 22 types of land uses defined according to the LCCS (Land Cover Classification System).

Meteorological downscaling is done in CALMET - an increase in the WRF output model resolution (200-1000 meters)

Input data needed to feed the CALPUFF modeling software

Calculation time: 3 hours!!

Supercomputation

• If a facility have the flexibility to delay or modify their production units, then a software like PrOlor will be very useful.

The New Tool for Prediction of Odour Incidents. A key frame for a better management of an industrial plant.

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

Thanks for your Attention!

Any question?

www.prolor.net

Carlos Diaz.