Final Report Summary - OMNISCIENTIS (Odour MoNitoring and Information System based on CItizEN and Technology Innovative Sensors)
Executive Summary:
1. Publishable Summary
1.1. Executive summary
The EU-funded 'Odour monitoring and information system based on citizen and technology innovative sensors' (http://www.omniscientis.eu/ OMNISCIENTIS) project has made significant inroads in this regard with the aim of mitigating odour annoyance.
To begin with, documents were developed describing the desired specifications for odour measurement, dispersion modelling and information technologies. In parallel, the needs and expectations of all stakeholders, including citizens, regulatory authorities and industrial bodies, were taken into consideration. Citizens' feedback on odour acceptability levels were gathered through smartphones and using the living lab approach. They were further combined with measurements from e-nose and odour dispersion models.
Project members developed an Odour Information System that produces validated monitoring statistics and impact levels for local authorities to support environment-related decision-making and for citizens to give them feedback on their complaints. A mobile application is also available, used by citizens to perform odour related observations. Over 5000 observations were sent until now.
Besides, two in-situ e-nose sensors and a meteorological station were installed and calibrated in the industrial site in Belgium, serving as pilot. Further 18 industrial parameters are collected in real time and 15 odour field surveys have been performed to understand odour sources and characteristics. The e-nose technology was optimised through tests and improvements to better understand relevant odour parameters at the second pilot site, a pig farm in Austria.
Researchers adapted the GRAL-System pollutant dispersion model to develop a fast odour dispersion modelling system using harmonised real-time meteorological data and industrial emission measurements. It was validated with the odour emission rates, olfactometry campaigns and citizens observations. Most of the GRAL-solver components were implemented in Cuda with a speed improved by a factor superior of 100.
Project activities were disseminated via project website and factsheets, 3 scientific papers, 13 international conferences and 3 user workshops involving selected citizens, technicians and authorities.
Local environmental governance was enhanced through citizen empowerment via monthly meetings and specific methodologies. Better and timely feedback on undesirable odours arising from certain emissions will help in setting evidence-based acceptable odour limits.
Ultimately, a particular attention have been addressed by all partners and in particular by involved SMEs in order to ensure the exploitation of the results and enabling the identification of concrete commercial opportunities that may be pursued after the project.
Project Context and Objectives:
1.2. Summary description of project context and objectives
1.2.1 Motivations
Odour sources (e.g. industry, landfills or from livestock breeding) are recognized as strong or even severe nuisance. They are listed as the second source of complaints by ADEME1 in France and Environmental Policy in Wallonia. Odour cannot be monitored or regulated like a pollutant, its perception is linked to a sense, and it is very important to evaluate the impact and effect of perception and annoyance.
In contrast to air pollutants or noise, odour monitoring limitation and regulation are a complex issue and non-homogenous concepts and approaches support the odour regulation in Europe.
Industrial usually develop strategies to mitigate the olfactory impact of their production processes on the neighbours, in the framework of the existing regulations (use of masking products, adjustment of the production to cope with legal constraints).
Though, citizens are up to now, “victims” appealing against odour nuisance. Sometimes they are asked to contribute to solve the problem in “passive” observatories, allowing them to complain, but the feed-back is poor and the information they provide is not used to validate the input for models or for getting more confidence in results of evaluating odour sources or odour dispersion models. Feedback might be provided on past complaints by telling them, “you were wrong”, because the wind has been in the opposite direction!
Figure 1 OMNISCIENTIS stakeholders
The OMNISCIENTIS project is concerned with a triangle of stakeholders: (i) the source of nuisance (e.g. industry, farming, waste water plant, chemical plant, etc.), (ii) the citizens living in the neighbourhood and (iii) the authorities at various levels (City, Environmental Administration, legislative bodies, etc).
The main goal of the project is:
• To involve all stakeholders in the endeavour of odour nuisance mitigation;
• to develop an odour information system, based on:
o citizens’ observations assisted by real time odour measurements (the odour rate at the sources and odour at receptors), meteorological measurements and odour dispersion modelling;
o transparent and fast presentation of relevant information, available for all stakeholders to improve the performance of the entire system;
• to improve citizens observation by smart interactive monitoring requests and feedback;
• to encourage the active participation of citizens.
The OMNISCIENTIS Consortium is highly motivated to promote not only technically driven solutions but also socio-scientific approaches addressing key questions:
• How could technologies help solving social and political problems addressed by local residents?
• How could a sociological approach involve citizens and strengthen local decision-making?
• How to address odours annoyance transforming potentially conflicting parties in a collaborative relationship?
Consequently, OMNISCIENTIS shall focus on enabling the empowerment of citizens to care for their environment and participate in local governance.
1.2.2 Description of the context
OMNISCIENTIS, a R&D European funded project proposes a win-win strategy:
• A global approach involving local authorities, industrials and citizens
• An objective diagnose and identification of odour sources
• A technical and user-driven solution
The critical challenge of OMNISCIENTIS was the integration of citizens as "community-based" observation providers, giving the odour perception and discomfort in real time and getting the feed-back in real time from a learning monitoring system. In order to support this novel approach, the OMNISCIENTIS project developed a comprehensive solution, using recent technological developments in communication technologies, atmospheric modelling and sensors to build a service oriented system, as sketched in Figure 2.
Figure 2 – Overview of the OMNISCIENTIS solution
Due to the nature of odour perception (one odour hour is defined as an hour during which at least 6 minutes of odour perception can be identified), an ideal odour dispersion model should offer a time resolution which is capable to represent short term odour peaks during one hour (see Figure 2). Hourly mean values, as they are commonly used by dispersion models, cannot represent these peaks. The dispersion models used for odour modelling were originally developed and tested for air pollutants. In odour modelling applications the so called "peak to mean" ratio is usually used, in order to represent odour perception by multiplying the computed hourly mean concentration by a constant factor. This factor is chosen by experience, i.e. adjustment of modelled odour plumes with odour monitoring. Model outputs obtained from hourly mean values for meteorology and emissions are only useful, if flow and emissions can be considered as almost constant during this hour. In odour nuisance related problems such assumptions are frequently not acceptable and therefore, such a model output cannot be compared with results of field inspection campaigns or observations of odour by citizens.
This Omniscientis solution comprises:
- A mobile application, OdoMap, letting citizens act as human sensors.
- Atmospheric dispersion pollution models adapted to the odour domain, with speed improved by a factor of 100 (!!). It is now capable of near real-time performance.
- A citizen observatory, a socio-technical mediation and a community based monitoring approach to empower citizens.
- An innovative electronic nose in-situ sensors network.
- A web-oriented service platform, OdoMis, integrating in real time all the different inputs (e-noses, citizens’ observations, emissions,…). It offers validated monitoring statistics and impact levels, supporting local authorities in their environmental decision making, offering to the industrials a diagnosis of the odour annoyance and giving citizens a feedback on their complaints.
Results has been tested and validated in two pilots: one in an industrial site (Belgium) and the other one in a pig farm (Austria).
1.2.3 Scientific and technical objectives
This “toolbox” of technological and methodological components described aims to achieve the following scientific and technical objectives:
- Develop and Implement an Odour Information System
Omniscientis integrates services to collect data and information from human observatories (citizens), from the source of odour (in-situ sensors networks of electronic noses) and from the processing of the specific odour dispersion model. It provides technological tools to enable and enhance the transparency of the information, the reliability in the stakeholders’ relationships, knowledge management, accountability of the stakeholders (in particular of the citizens and the citizens’ associations) and responsiveness in the management of the nuisances.
- Provide a medium to empower citizens to take care about their environment and participate to local governance.
The project focuses on the citizens’ role for two reasons: odour nuisances are measured as perceptions and using human observatories implies sociological aspects. This enables the citizens to locally participate to environmental governance. The project aims to work on socio-technical mediation and the community-based monitoring approach. To allow and facilitate the collection of the data, the geo-localisation of the information and an automatic integration in the Information System, the project develops a user-friendly geo-mobile application for smart phones.
- Develop a new odour dispersion model capable of near real-time performance
In order to represent adequately odour perception by dispersion modelling an odour dispersion model should use odour emission information, wind and turbulence measurements from a few minutes averaging period and also to provide in the same time scale results. Therefore, the dispersion algorithms which were developed and tested in air pollution applications (order 1 hour) need to be tested and adapted to accommodate for fast odour applications. Due to the short simulation periods and to provide citizens a near real-time feedback, the software code execution needs tremendous acceleration.
- Develop an Innovative electronic nose in-situ sensors network
The specific odour dispersion model needs specific data at the source of the nuisance. The project develops an innovative monitoring system based on in-situ sensors network of electronic nose. The innovation consists in their improved pattern recognition, high time resolution to represent the variations in emissions and smart combination of process-related sensors and finally on their ability to process these various sensor information and send odour rate in real time to the information system.
- Enhance and share the scientific knowledge on odour emission, flow, perception and management
Monitoring and modelling of odours with an adequate time resolution, which captures the nature of odour perception and the publication of these results enhances the scientific knowledge. Moreover, the development of the new odour dispersion model, new sensors and its future application facilitate analysis and understanding of odour related problems.
In line with INSPIRE, SEIS and COPERNICUS initiatives, the odour information system provides an open collaborative platform to easily share new and collected data and information, collaborate and transfer knowledge to the different stakeholders.
- Perform impact studies on local governance in environmental problems
The impact of the system on local decision-making, public education and information and the effective public participation in local governance for environmental issues can be studied. Models for Citizen’s empowerment in decision processed are developed.
- Assistance to authorities in environmental problems
The OMNISCIENTIS information system is intended to be an integral approach and set-up, which can be used after site specific adaptions by authorities for the control of odour nuisance and the evaluation of measures. The communication part and the monitoring and modelling methodologies may be used in a similar way for other environmental problems such as noise or air pollution.
- Contribute to harmonization of legislation at EU level
Based on a review of the actual status of legislations to manage and control odour nuisances and based on the odour information system implemented, the project aims to make recommendations and provide outputs for the future European Norm (EN) standard CEN/TC 264/WG 27 "Measurement of odour impact by field inspection“. This new standard will provide methods for odour impact measurements around an odour emitting facility. Software tools to conduct such measurements are not yet available.
Project Results:
1.3. Main results
1.3.1 Technological results
1.3.1.1 Mobile application
One of the main objectives of the project is to bring citizens technological solutions letting them to perform observations. OdoMap is a result of an analysis and development phase in which smartphones are tools letting citizens and experts to perform odour measurements. Experts’ tool support methodologies (dynamic and static) described in the European standard CEN TC 264 WG27. 21 smartphones with an early version of OdoMap preinstalled (1.1.0) were distributed among watchmen in September 2013. In successive releases several bugs were fixed and new functionalities added.
Aiming to reach the largest number of people, an hybrid application has been developed with standard web technologies (HTML5, JavaScript and CSS), and could be deployed in any operating system. Like apps, they are created once for multiple device operating systems. They combine the advantages of both native and web applications: using native containers allows users to access the device’s native service such as camera, GPS and local device storage and it saves development time as it only have to be coded once. For the moment it runs on Android and iOS and is available on the Google Play and the Apple Store. The last version (1.4.1) includes a set of functionalities that could be easily migrated and adapted to other domains of expertise in which data has to be collected. It includes:
• Authentication service, allowing secure access to dedicated content and to personal data even if the device is offline. Unless user logs out, system automatically remembers user and pass details for next access
• Training module, with specific instructions about how to perform odour observations: methodology, schedule and number of weekly observations.
• Access to meteorological data from weather station located in the study site in real time.
• An odour observation tool, allowing citizens and experts to record their observations. It exists three versions: one for resident watchmen and two for experts, to perform static and dynamic campaigns. It is mainly composed by a map viewer, adapted data forms to be filled in during an observation and a historic registry showing all observations classified in chronological order. In addition it includes a chrono, a legend, a help section and a layer selector to select the base layer.
• Communication tools permitting any authorized stakeholder (administration, expert or industry) to send a message through the OdoMis web platform to be displayed in all or selected watchmen’s smartphones. On the one side the announcement panel is displayed in all the menu pages of the mobile applications. On the other the push alerts let to notify users even where they are not actively using our application.
• Calendar, showing the most important events. It serves to remind the watchmen and panellist the upcoming observations campaigns or any other relevant activity.
Among the advanced characteristics it includes an automatic registration location of GPS or best geolocation accuracy available (Wi-Fi or 3G) and of date/time. Supports working in offline conditions, so user can still add and make edits to his data. Automatic synchronization is performed between the spatial database and the server once a network connection is available.
The user shall not have to deal with the technical complexity of heterogeneous interfaces, so ergonomic aspects and usability has seriously been taken into account since the beginning. Therefore during this time a few watchmen (4 of them) needed assistance to solve problems with their smartphones. Most of the times, it was caused by using an old version of the application, so that the observations could not be sent to the Omniscientis servers. Almost 5000 observations were recorded. The application has also been used by the experts during 15 field terrain inspections, most of them conducted during the validation phase. This represents more than 400 measurements.
1.3.1.2 Platform
One of the key points of the platform, OdoMIS, it is to be the interchange node between different kinds of information (raw data and added-value data) and between different types of local stakeholders. Indeed, citizens, experts, local authorities and manufacturers use the platform to discover, share, visualize and analyse a large quantity of information such as odour observations collected thanks to the mobile application, data coming from weather station, data coming from industrial processes, data collected by e-noses, and odour plumes computed by specific algorithms….
The platform is designed to integrate a large panel of services and to add or develop easily new services. Aiming to improve simple and intuitive use of the platform by the stakeholders, a flat design was been applied. Thanks to the used technology, the OdoMIS platform provides a new experience for the users in the context of the odour management. Depending on their privileges, the users have access to the following services (Figure 3):
Figure 3 – Architecture of the OdoMIS platform
• Submit observations - The platform allows users to record observations thanks to an user-friendly form.
• Discover observations - The platform allows users to show the recorded observations. Experts have access to all observation and watchmen have access to only their observations. Specific tools have been integrated aiming to facilitate the navigation (selectors, filters, sorting).
• Monitoring in real time - The platform shows in real time the ten last recorded observations on a map viewer and allows to interact with data.
• Sensors - The platform allows to discover the different in situ sensors: weather station, e-noses. In addition, several specific sensors that can be used to estimate the quantity of odour emitted in the atmosphere by the industry are also available. The OGC standard, Sensor Observation Service, is used to provide access from sensor‘s observations to sensor systems in a standard way
• Processing - The platform allows to run model developed during the Omniscientis project and to display the result - odour plume - in a map viewer. This service is based on the OGC standard, Web Processing Service. As shown by the Figure 4, the web processing service developed for the OdoMIS collects several types of information before to run the model. The result is then displayed on a map viewer thanks to another OGC standard, the Web Map Service. It is noted that the model takes into account the digital elevation model to produce the plume.
Figure 4 – WPS
• Messaging - The platform allows to send notifications to the users’ mobile phones where the mobile application is installed. It is also possible to configure the message to be displayed by the mobile application.
• Statistics - The platform allows to discover multiple types of statistics. Firstly, the use indicators describe the rate of activity of the users with the mobile application (ex. number of observations recorded by the different watchmen during the last 20 days…). Secondly, a set of indicators showing the main trends in term of odour, type of odour, intensity and discomfort have been implemented
• Campaign - The platform allows to show the results of the campaign carried out by the experts. This service display all observations recorded during a campaign with their features - with or without the use of a map viewer.
Generic services are also available through the OdoMIS platform:
• Internationalization - This functionality allows to change the language of the site. Thanks to the technology used, it is very simple to add new language to the platform.
• Download data (observations and statistics) in csv format
• Authentication - This service manage the user’s access.
In addition, a warning system in real-time has been developed aiming to alert experts and manufacturers of recorded observations that are characterized by the presence of odour with high discomfort or/and high intensity.
1.3.1.3 Odour Information System Integrated and interoperable
As a general result of this project, OMNISCIENTIS delivers a highly configurable system composed of various components compliant with Open Standards (OGC) that allow to collect, store, access and display sensors measurements, mobile observations and cartographic layers. It also allows to launch and orchestrate geospatial processing services.
The Odour Information System is a set of Web Services adhering to a REST architecture defined by W3C. All the Web Interfaces are compliant with the most recent OGC Specifications that have either been adopted and are in a stable phase of development.
A central web portal allows access to a set of distributed secured Web Services. The advantages of such architecture are the flexibility and scalability to adapt to new environments. For instance, one of the components could easily make evolve or migrate its technology without affecting the rest of the system.
The OMNISCIENTIS distributed architecture is presented in the next figure:
Figure 5 - Overview of the distributed architecture of Omniscientis
The solution is “thematic-neutral” and that allows to easily instantiate and adapt in various thematic domains, by connection of specific components.
• Collection of sensor data: generic client deployed in the pilot site, and developed in JAVA are able to read, transform and sent data measured by the meteorological and e-nose stations as well as measurements from the industrial plant using the SOS OGC standard. Through an “insert observations” operation, data is sent to the server in a XML file complaint with a very specific data profile defined by the standard and self-describing the observation: time, type of sensor and measure, unit, etc. An adaptation could be easily and quickly done to send the data to a new SOS server.
• SOS server: receives all the measurements from the sensors data clients, and provides a means for accessing and sharing. Through HTTP methods (GET, DELETE,…) the platform and the mobile application interact with the server: request of sensors available, perform temporal requests, etc. The implementation is based on the 52º North SOS, and could easily be added to existing deployments and receive request from any client connected to internet.
• WPS: answers a need of executing geoprocessing operations via web services and is a key feature of the Omniscientis project. Using the provided input parameters and those that are automatically got from the SOS Server, the process implemented in another server (described in detail in section 1.3.1.5) is executed. For the moment this is executed in asynchronous mode, so the client has to wait for a few minutes while the process is completed. When is it completed and successful, a single binary (ASCII) output is produced. Automatically a mapfile is created and the plume is offered through a WMS service (OGC Standard). Once again, this plume could be publicly accessed through the internet (Figure 4).
• Platform: as described in section 1.3.1.2 serves as a unique and central access point for all the users. An authentication system based in a HTTP’s “basic and digest” authentication framework secure the access.
1.3.1.4 E-nose network
According to the evaluation of the different odour sources at each site, possibilities of e-nose installations were studied for the cases of the Burgo Ardennes paper mill and the pig farm in Styria.
In the case of the paper mill, severe conditions of temperature and gas composition impede e-nose installation into the main stacks. Emission rates from the sources were therefore inferred from industrial process variables (called tags). Thirteen odour sources were identified and measured for their odour rate. The state in real-time of each source is known by industrial process variables (both on-off value and pressure threshold). The odour rate is deduced by the following algorithm:
if [tag1]=1; [tag2]>100 then [odour rate] = x (as an example).
E-noses were developed to measure odour variation in ambient air in the direction of the most impacted zones. A new array of gas sensors was tested successfully for sensitivity and selectivity to odours from the site and particularly from the waste water treatment plant (identified as the main odour source in terms of concentration/frequency ratio). Two devices were placed on site and monitor odour variations in real time. The first one was installed near the waste water treatment plant in direction of Dampicourt and the second one a bit further from the site in direction of Virton. The calibration phase consists in submitting odour samples to the sensor array and to put into relation their responses with odour concentration. Based on these measures, calibration algorithms were developed to quantify continuously the odours perceived by the sensors. Algorithms were updated regularly to compensate the drift of the sensors. The odour concentrations inferred by e-noses gave fairly good results (see Figure 6 for example).
The development of the odour monitoring system is established around Burgo-Ardennes. Thanks to these tools, odours are monitored from their emissions to their olfactory impact:
- Odour emission rates are continuously inferred from the industrial process variables
- Thanks to the meteorological data and these odour emission rates, dispersion model calculates the extent of the olfactory impact.
- Odour information at reception is inferred from e-noses and watchmen observations.
Processing and evaluation of industrial process variables as well as both e-noses drove to the elaboration of algorithms for odour quantification. These algorithms are now integrated into OdoMis for running the odour impact of the whole system every 6 minutes.
Figure 6: Predicted odour concentration from the e-nose 1 in Burgo-Ardennes compared to odour concentration measured by olfactometry
In the second case of the pig farm, all odour emission sources present acceptable conditions for e-nose use. A new sensor array was successfully tested for their sensitivity to pig farm odours. Three fixed e-noses were installed on site, two of them at emission in the two main stacks, with a pitot wing monitoring the flow rate, and the third one in the field at immission. A reduced calibration (4 samples) was achieved due to the distance from the olfactory laboratory. Algorithms were provided for the three e-noses. Fairly good results were obtained in terms of odour variation, but an enhanced calibration with more samples could help to achieve better results. However, problems with the farmer impede to obtain further results.
1.3.1.5 Odour dispersion modelling
Due to the subjective nature of odour perception, fast modelling techniques were used together with measurements to assist and adjust the information given by citizens and to be able to give citizens an immediate odour exposure feedback. Therefore a transient “real odour dispersion model" capable to resolve odour nuisance, based on the pollutant dispersion model 'GRAL-C' (Öttl and Uhrner, Atmospheric Envrionment, 2011) of the Graz University of Technology (TUG) was further developed, modified, accelerated and tested to be applied for odour simulations. Main parts of the GRAL-System were transferred so that they can run on GPUs (Graphical Processing Units) instead of CPUs.
The model development comprised the development of interfaces to use short term measurements (wind, turbulence and odour), the adaptation and validation of the dispersion algorithms using tracer experiments towards shorter simulation periods (order minutes instead of 1 hour), the acceleration of the computations by reorganizing and converting the original FORTRAN code to CUDA to be run on GPU. Finally, the model output and post-processing of the model output was adapted to be used in the OMNISCIENTIS odour information system and for odour specific applications. An important work was to further improve the existing model and the testing of the transient model performance. Due to the lack of transient odour validation data, first test runs were performed for a tracer release experiment from a tall stack in an urban environment. These tests undertaken with the CPU version formed the basis to compare the CPU and GPU dispersion parts. Test simulations for winter time PM10 using well established emission inventories generated during the EU project PMinter (www.pminter.eu see also book reference below) from the European scale down to the local scale (own processing of traffic and domestic heating emissions) indicate excellent results of the new transient model. Here, a coupled modelling approach using a chemistry transport model to simulate secondary formed aerosols and the impact of regional scale transport together with GRAL to simulate the impact of locally emitted primary PM10 mainly originating from domestic heating and traffic were utilized. In Figure 6 comparisons between PM10 concentration measurements and simulated off-line coupled result at the air quality monitoring station Klagenfurt Völkermarkter Straße (Austria) are shown. The new transient dispersion model was independently tested in air quality applications using 30 min and 60 min means and compared with PM10 air quality measurements. Further details and results of this work, the data used and the modelling approach are given in the book written by Uhrner et al., 2014, listed below.
Figure 7: Simulated and monitored total PM10 at Völkermarkter Straße in Klagenfurt using an off-line coupled WRF-Chem/GRAL-transient approach. Ambient temperature (T), simulated and monitored wind speed (WS) are shown as well.
A model suite consisting of three configurations or main set-ups with near real-time performance was finally developed. All three GPU configurations were successfully tested and validated within air quality applications and the two OMNISCIENTIS pilots.
A simple and very fast GPU configuration was developed for flat terrain applications neglecting the impact of buildings. The benefit of this approach is the minimized efforts in data preparation and the possibility to carry out computations for large domains. Moreover, the speed-up compared with a single state of the art CPU processor is approximately 400 with this set-up.
Based on the first configuration, pre-calculated flow fields and terrain information can be used in the second main modelling set-up, the flow field library approach. This set-up requires the analysis and classification of local complex flow conditions prior to the odour simulations. A big advantage of this approach is that the solution is already existing and typical problems such as convergence problems cannot occur during run-time.
The third configuration is intended to be used in applications to account for the presence of buildings. The presence of tall buildings (e.g. factories, stacks, or even skyscrapers) may lead to the so-called building downwash effect which leads to increased vertical mixing of air layers and hence odour. However, the presence of buildings may also impose a shielding effect in way that people living further downstream of an odour source may be less affected. In this set-up the complex flow between the buildings is accounted and computed during run-time.
In all three configurations the computation times were below 5 minutes for flow and dispersion within the pilot applications.
The GPU versions were regularly tested and compared with the FORTRAN version. The results from both models are comparable. Small differences are mainly attributable to the higher number of particles used with the GPU version. The speed-up of the GPU version and/or the possibility to track more particles (higher particle density), see Figure 7, is a clear benefit of the GPU version. The speed-up of this version is about two orders of magnitude compared to the CPU one using a single state of the art processor.
Figure 8: Comparison of results obtained from 360.000 particles and 144 million particles. The images show the concentration with equal contrast settings.
1.3.2 Sociological results
Within the project, a “community-based” approach was applied in order to involve the citizens in a Local Environmental Governance (relying on the odour monitoring systems). The idea was to design a physical and intellectual space for shared understanding and collaboration between all stakeholders impacted by the environmental problem of odour emission.
Based on the development of the Information Technology (IT) system allowing odour emission measurement as well as the collection of citizen feedbacks, a Living Lab (LL) approach has been implemented in the Belgian pilot, in the area around Virton. This Living Lab approach involved citizens, public authorities, industry and environmental non-governmental organisations (NGOs).
According to the definition of the European Commission, Living Labs are “open innovation environments in real-life settings, in which user-driven innovation is fully integrated within the co-creation process of new services, products and societal infrastructures”. Based on this definition and considering, in our case, citizens as one of the end-users of the IT system, the proposed approach was focused on citizens empowerment in the Local Environmental Governance.
Living Lab stakeholders where first identified and characterised, in terms of fears, expectations, involvement and willingness to engage. Based on this first study, several working groups where organised in order to build trust and establish a common goal.
During the pilot performed in Burgo Ardennes, a first group has been constituted with Public Authorities (mainly neighbour cities), Citizens and people from Burgo Ardennes. They have developed a common knowledge on odour annoyance.
This group has worked together during the project and is willing to continue after on a regular basis. They also want to enlarge the existing group and are already working on the identification of possible means to do it.
Some basic functioning rules have been identified and agreed among these stakeholders (governance principles and required role to achieve their common objective). Citizens are engaged in collecting and sending data to Burgo Ardennes on their feeling about odour emission. Burgo Ardennes has already identified some improvements in order to reduce odour emission and is willing to continue the work which was initiated during the project. Public authorities are also involved and ready to participate in the future in the governance which is emerging.
During the project some key factors that have to be taken into account for future developments of such an approach have also emerged. First of all representativeness is a critical issue. Indeed the LL was composed mostly of non-working people, as working people have less time to participate to such community. In this sense it is difficult to guarantee sustainability of decision made by such a community if its members do not represent all the interests. In order to avoid representativeness issue, social media could be an alternative in order to allow online and off-line participation.
In the Omniscientis project, citizens encountered difficulties to define what they would like to achieve together, because of a lack of knowledge about odour emissions. Proposing some simple actions (such as company tour or “open doors”), prior to any community based work, helps to build a common knowledge on the considered problematic, and then makes it easier to work together.
Finally a special attention has to be paid to the Local authorities’ position. In a Living Lab perspective, local authorities are considered as a main stakeholder. It has to be recognized that, during the project, local authorities have played a minimal role in the Omniscientis Living Lab. At the end of the project, and only at the end, local authorities appear to be the actor that should become the leader of the future governance.
Governance implies a common purpose, joint action, a framework of shared values, continuous interaction and the wish to achieve collective benefits that cannot be gained by acting independently. Although the proposed methodology has to be adapted according to the previous remarks, the efficiency of the methodologies used within the Living Lab could be assessed in consideration of these governance requirements.
Potential Impact:
1.4. Potential impact
1.4.1 Impacts on citizens empowerment
The major benefits and added value of a successful OMNISCIENTIS project are available for citizens, industries, experts and public authorities:
1. Neighbours of a plant with regular odour emissions were frequently not able to communicate the occurrence of odour in their living environment in an appropriate way. They could complain but if they did so, this was happening in a non-structured way, sometimes some hours or even days later.
Hence Omniscientis aims to integrate citizens in a communication system with appropriate tools to support bidirectional exchanges. Web-based Services Platform allows proactive and reactive requests for collection of information on odour nuisance by the citizens. Such a system have alert capabilities allowing industrials and authorities to inform the citizens if some process parameters are drifting and, in the other direction, citizens receive message and alerts in theirs smartphones. It allows citizens to alert the industry if they observe odours in the neighbourhood. In case of intense nuisances, plant managers receive alert mails.
For the interested citizens, who may want to participate in measuring campaigns, they collect data via a geo-mobile application and a dedicated website by providing inputs, letting them to act as human sensors. In this way they contribute to populate the data repository for diagnosis and validations purposes, and enhancing the information system.
On the other side, through a Living Lab, citizens are enabled to participate actively together with all stakeholders involved, including local authorities and industrial, in defining priorities, share insights and follow actions plans related to odours. Through mobile app and web they have direct access to near real time data, such as meteorological data, e-noses measurements or even available industrial process status.
2. From a point of view of industrials, who are confronted with the complaints from neighbours living around a plant, OMNISCIENTIS contributes to understand better the relation between emissions and odours observed in the surroundings. Electronic noses allow getting better information on the time behaviour of sources. This information is today not available using standardized measuring methods because they need sampling times of 1/2 h. Fast modelling capabilities allow to retrace the plume depending on short term variations of emissions and weather conditions. The information system allows getting quick feed-back and alert from the citizens, thus enabling the industrial to modify, if possible, rapidly plant parameters in an appropriate way in order to avoid the exposure to strong odours. On the other side the system allows to show in more details the actual location of an odour source.
3. The experts benefit on several levels:
• get detailed information on the time-behaviour of odour sources
• facilitate measuring campaigns as described in new European standards from CEN TC 264/WG 27 by allowing to integrate citizens observations in a data depository which will enable experts to analyse more and better data
• fast and specialized odour dispersion models can finally be used to provide forecasting under expected meteorological conditions and/or compute yearly mean exposure frequencies.
4. Public authorities benefit by getting a faster and more detailed understanding of odour observations around a plant. They are able to define commonly agreed limit values, based on objectively measurable exposure values.
So we expect that our system contributes on empowering citizens on environmental monitoring and in their active participation for environmental management. Our approach could be easily exported and adapted to any other environmental issue. This has three main impacts at a sociological level:
- Empowerment relies upon principles of democracy and equality, so participation of citizens is good on its own. Furthermore it is argued that because the act of participation, people improves their skills which enable them to function more effectively as individuals.
- Empowerment improves the process of decision-making, the quality of decisions made and services delivered. In fact, through working with external parties, organizations can gather ‘intelligence’ and use it to improve service provision or decision-making.
- Empowerment gains support for policies and management processes in which a participation process in engaged. Participants that take part in and learn about systems builds, improve their trust besides organizations and decision-making structure.
1.4.2 Impacts on odour regulatory framework
The situation today in Europe is a very disparate legislation level and a very disparate technical background. Some countries are not limiting odour emission or impact at all, some countries have developed some specific limit values, which can be different from one type of odour source to another, some other countries have very elaborated and complete technical guidelines and limit values derived from these guidelines.
Some countries are specifying in detail the type of tools to be used for controlling the respect of limits; others, even if they have defined such values, are not specifying at all the minimum technical requirements for such tools.
Together with already existing European standards and the future standard for conducting field inspections, elaborated by the CEN-TC264-WG27, these new tools allow the definition of an harmonised European Framework for the evaluation of odour nuisance and exposure limit values.
The key issues of such a future guideline could be defined as follows:
• Emission rates in future permits should be derived from the expected exposure level
• The acceptable exposure level could be defined as a maximum number of odour hours as defined in the future standard on field inspections.
• The verification, that such exposure levels are respected requires tools for conducting field inspections and dispersion modelling, for example as developed in OMNISCIENTIS
• The definition of acceptable emission rates requires clear technical requirements, a dispersion model and the necessary input data.
Some technical key requirements are, from the point of view of the OMNISCIENTIS consortium:
• The time resolution of input data and modelling have to be better than 6 minutes (derived from the definition of an odour hour)
o The meteorological data as input for the model have to have the same time-resolution and have to be measured nearby the emission source or have to be representative for the local situation (see the definition of representativity in the future CEN standard)
o Emission data need also the same time-resolution (for the verification of existing sources) or have to be considered as constant in time with a maximal emission rate. If different time behaviour is used, it has to be justified (for projects asking for authorisation).
• The measurement of emissions has to be performed using existing European standards for canalised sources
• For non-canalised sources, in particular for surface sources and diffuse sources, a field inspection with backward modelling is recommended.
• The minimum requirements of a dispersion model are:
o Lagrangian model or equivalent, no simple Gaussian model
o Maximum time step 6 minutes
o Particle resolution (for lagrangian models) higher than 1 000 000 particles
o Minimum diagnostic wind field modelling depending on local conditions. Use of prognostic modelling can be required.
o Characteristics of such local conditions can be derived from German rules
Additional considerations:
• In the case of complaints, citizens could be involved by using an odour management system as developed in OMNISCIENTIS, allowing local governance and the resolution of problems.
• The European wide definition of the principal way for defining acceptable exposure levels based on the definition of an acceptable number of odour hours would harmonise this key element of a future guideline. Today, many and very disparate definitions are existing all over Europe; most of them cannot be verified in a technically valid way. For example a limit exposure concentration of 5 OU not to be exceeded for 98 % of the time of a year cannot be verified without a corresponding, very detailed meteorological dataset and a corresponding dispersion model.
2. Dissemination and Exploitation
2.1.1 Target audiences
The target audiences for the Omniscientis project are extremely vast, ranging from the citizens suffering from olfactory nuisances, industrial entities generating the nuisances, the regulating Authorities, up to the experts and scientific community interested in studying the technical, economic and social aspects of the odours. These audiences can be categorized as follows:
• The regulating authorities producing the laws, regulations, directives or controlling the application and observance of these rules;
• The experts drafting the standards for measuring the odour impact, recommending mitigation practices, etc;
• The industry generating the olfactory nuisances and implementing mitigation measures;
• The citizens (neighbours) suffering from the nuisances;
• The associations in charge of representing the interests of the neighbours and the Society in the context of improved quality of life;
• The local authorities (mayor, governor, minister, etc) responsible for the fair balance between the social and economic interests in their area of competence;
• The scientists conducting research work in the domains of technical solutions for odour measurement and forecasting or for odour mitigation techniques;
• The sociologists doing studies on nuisance problems in the Society or conducting mediation actions.
The challenge of the Omniscientis Dissemination is to address adequately all these stakeholders and their specific, sometimes contradictory, interests.
2.1.2 Main dissemination activities
Our results were mainly disseminated via the project website. Furthermore two different brochures, two posters and a roll-up were designed to be shown at the thirteen international conferences attended. We also produced 5 scientific papers and organized two workshops and a conference inviting citizens, scientific community and policy makers.
2.1.2.1 OMNISCIENTIS official website
The OMINSCIENTIS website provides quickly to a wide audience the basic information concerning the project and is available at www.omniscientis.eu.
It includes:
• A homepage and an about section, providing general information on the project
• News and events announcements (conferences, workshops) related with the project
• Direct link to the OMNISCIENTIS information system where observations and results from the project are available
• Public download section for OMNISCIENTIS project
• Protected access to project-internal documents was granted to the reviewers and members of the user group
Figure 9 – Screen shots of website
2.1.2.2 OMNISCIENTIS video
During the project the European Commission produced a video promoting new earth observation systems using monitoring and information systems by citizens. In this context OMNISCIENTIS, CITI-SENSE and CITCLOPS are presented as example of successful citizens observatories projects.
Figure 10 – Frame of the video
2.1.2.3 OMNISCIENTIS factsheet and brochure
In December 2012 a first factsheet was produced, presenting in an A4 double page document the project to a large and open public. The factsheet highlighted the sociological dimension of the project.
A brochure has also been designed, published and printed during summer 2014 for dissemination purposes, with messages related with OMNISCIENTIS outcomes and benefits for target users and potential customers. To reach more people, it was produced in French and English.
Figure 11 - OMNISCIENTIS leaflet
2.1.2.4 OMNISCIENTIS users’ workshops and final event
The Consortium organized two workshops dedicated to users and a Final Event, in order to present results of the project, discuss various issues with the users and get a formal feedback from the users on specific questions of interest for the project and the future exploitation of the results. These workshops helped in creating a cooperation network among the user participants and in increasing the impact of the project.
Each event had a specific purpose, as presented in the following lines:
• The first workshop was organized in Arlon (Belgium), at the University of Liege (Faculty of Sciences and Management of the Environment), on Monday the 7th of October 2013. The workshop was divided into three successive sessions:The first session introduced the involvement of the citizens, from the perspective of the European Union and the Government of the Walloon Region of Belgium; the second session was dedicated to the exchange between the workshop participants, organized in smaller groups, followed by a time for providing to the assembly the feedback of the groups about their ideas, findings, and suggestions and the third session reported on live experiences, where citizens are participating to the decision making in environmental issues; the session ended with a presentation of the OMNISCIENTIS project.
• Second workshop was held in Graz (Austria) in April 24th 2014. It addressed the challenges of the olfactory nuisances and the on-going regulations and standardisation activities. With a high attendance of experts on the domain, it was organized in three themes: odour regulatory framework, methodologies for measuring odours and holistic approach to odour nuisance monitoring.
• On 23 September the final conference of Omniscientis took place in Brussels. It provided an open forum in which citizens, policymakers, industrials and researchers exchanged ideas, ideas and experiences on odour management.
At the core of the one-day conference was the question on how to create collaborative ecosystems based on transparency of the information, reliability in the stakeholder's relationship and responsiveness in the management of the nuisances.
Leading experts presented their results of the project, particularly in the fields of odour modelling, e-nose sensors networks and odour information systems. Interesting discussion was also held on citizens’ involvement and participatory methodological frameworks.
List of Websites:
www.omniscientis.eu
CONTACT
Philippe Ledent - SPACEBEL
philippe.ledent@spacebel.be
+32 4361 81 11
1. Publishable Summary
1.1. Executive summary
The EU-funded 'Odour monitoring and information system based on citizen and technology innovative sensors' (http://www.omniscientis.eu/ OMNISCIENTIS) project has made significant inroads in this regard with the aim of mitigating odour annoyance.
To begin with, documents were developed describing the desired specifications for odour measurement, dispersion modelling and information technologies. In parallel, the needs and expectations of all stakeholders, including citizens, regulatory authorities and industrial bodies, were taken into consideration. Citizens' feedback on odour acceptability levels were gathered through smartphones and using the living lab approach. They were further combined with measurements from e-nose and odour dispersion models.
Project members developed an Odour Information System that produces validated monitoring statistics and impact levels for local authorities to support environment-related decision-making and for citizens to give them feedback on their complaints. A mobile application is also available, used by citizens to perform odour related observations. Over 5000 observations were sent until now.
Besides, two in-situ e-nose sensors and a meteorological station were installed and calibrated in the industrial site in Belgium, serving as pilot. Further 18 industrial parameters are collected in real time and 15 odour field surveys have been performed to understand odour sources and characteristics. The e-nose technology was optimised through tests and improvements to better understand relevant odour parameters at the second pilot site, a pig farm in Austria.
Researchers adapted the GRAL-System pollutant dispersion model to develop a fast odour dispersion modelling system using harmonised real-time meteorological data and industrial emission measurements. It was validated with the odour emission rates, olfactometry campaigns and citizens observations. Most of the GRAL-solver components were implemented in Cuda with a speed improved by a factor superior of 100.
Project activities were disseminated via project website and factsheets, 3 scientific papers, 13 international conferences and 3 user workshops involving selected citizens, technicians and authorities.
Local environmental governance was enhanced through citizen empowerment via monthly meetings and specific methodologies. Better and timely feedback on undesirable odours arising from certain emissions will help in setting evidence-based acceptable odour limits.
Ultimately, a particular attention have been addressed by all partners and in particular by involved SMEs in order to ensure the exploitation of the results and enabling the identification of concrete commercial opportunities that may be pursued after the project.
Project Context and Objectives:
1.2. Summary description of project context and objectives
1.2.1 Motivations
Odour sources (e.g. industry, landfills or from livestock breeding) are recognized as strong or even severe nuisance. They are listed as the second source of complaints by ADEME1 in France and Environmental Policy in Wallonia. Odour cannot be monitored or regulated like a pollutant, its perception is linked to a sense, and it is very important to evaluate the impact and effect of perception and annoyance.
In contrast to air pollutants or noise, odour monitoring limitation and regulation are a complex issue and non-homogenous concepts and approaches support the odour regulation in Europe.
Industrial usually develop strategies to mitigate the olfactory impact of their production processes on the neighbours, in the framework of the existing regulations (use of masking products, adjustment of the production to cope with legal constraints).
Though, citizens are up to now, “victims” appealing against odour nuisance. Sometimes they are asked to contribute to solve the problem in “passive” observatories, allowing them to complain, but the feed-back is poor and the information they provide is not used to validate the input for models or for getting more confidence in results of evaluating odour sources or odour dispersion models. Feedback might be provided on past complaints by telling them, “you were wrong”, because the wind has been in the opposite direction!
Figure 1 OMNISCIENTIS stakeholders
The OMNISCIENTIS project is concerned with a triangle of stakeholders: (i) the source of nuisance (e.g. industry, farming, waste water plant, chemical plant, etc.), (ii) the citizens living in the neighbourhood and (iii) the authorities at various levels (City, Environmental Administration, legislative bodies, etc).
The main goal of the project is:
• To involve all stakeholders in the endeavour of odour nuisance mitigation;
• to develop an odour information system, based on:
o citizens’ observations assisted by real time odour measurements (the odour rate at the sources and odour at receptors), meteorological measurements and odour dispersion modelling;
o transparent and fast presentation of relevant information, available for all stakeholders to improve the performance of the entire system;
• to improve citizens observation by smart interactive monitoring requests and feedback;
• to encourage the active participation of citizens.
The OMNISCIENTIS Consortium is highly motivated to promote not only technically driven solutions but also socio-scientific approaches addressing key questions:
• How could technologies help solving social and political problems addressed by local residents?
• How could a sociological approach involve citizens and strengthen local decision-making?
• How to address odours annoyance transforming potentially conflicting parties in a collaborative relationship?
Consequently, OMNISCIENTIS shall focus on enabling the empowerment of citizens to care for their environment and participate in local governance.
1.2.2 Description of the context
OMNISCIENTIS, a R&D European funded project proposes a win-win strategy:
• A global approach involving local authorities, industrials and citizens
• An objective diagnose and identification of odour sources
• A technical and user-driven solution
The critical challenge of OMNISCIENTIS was the integration of citizens as "community-based" observation providers, giving the odour perception and discomfort in real time and getting the feed-back in real time from a learning monitoring system. In order to support this novel approach, the OMNISCIENTIS project developed a comprehensive solution, using recent technological developments in communication technologies, atmospheric modelling and sensors to build a service oriented system, as sketched in Figure 2.
Figure 2 – Overview of the OMNISCIENTIS solution
Due to the nature of odour perception (one odour hour is defined as an hour during which at least 6 minutes of odour perception can be identified), an ideal odour dispersion model should offer a time resolution which is capable to represent short term odour peaks during one hour (see Figure 2). Hourly mean values, as they are commonly used by dispersion models, cannot represent these peaks. The dispersion models used for odour modelling were originally developed and tested for air pollutants. In odour modelling applications the so called "peak to mean" ratio is usually used, in order to represent odour perception by multiplying the computed hourly mean concentration by a constant factor. This factor is chosen by experience, i.e. adjustment of modelled odour plumes with odour monitoring. Model outputs obtained from hourly mean values for meteorology and emissions are only useful, if flow and emissions can be considered as almost constant during this hour. In odour nuisance related problems such assumptions are frequently not acceptable and therefore, such a model output cannot be compared with results of field inspection campaigns or observations of odour by citizens.
This Omniscientis solution comprises:
- A mobile application, OdoMap, letting citizens act as human sensors.
- Atmospheric dispersion pollution models adapted to the odour domain, with speed improved by a factor of 100 (!!). It is now capable of near real-time performance.
- A citizen observatory, a socio-technical mediation and a community based monitoring approach to empower citizens.
- An innovative electronic nose in-situ sensors network.
- A web-oriented service platform, OdoMis, integrating in real time all the different inputs (e-noses, citizens’ observations, emissions,…). It offers validated monitoring statistics and impact levels, supporting local authorities in their environmental decision making, offering to the industrials a diagnosis of the odour annoyance and giving citizens a feedback on their complaints.
Results has been tested and validated in two pilots: one in an industrial site (Belgium) and the other one in a pig farm (Austria).
1.2.3 Scientific and technical objectives
This “toolbox” of technological and methodological components described aims to achieve the following scientific and technical objectives:
- Develop and Implement an Odour Information System
Omniscientis integrates services to collect data and information from human observatories (citizens), from the source of odour (in-situ sensors networks of electronic noses) and from the processing of the specific odour dispersion model. It provides technological tools to enable and enhance the transparency of the information, the reliability in the stakeholders’ relationships, knowledge management, accountability of the stakeholders (in particular of the citizens and the citizens’ associations) and responsiveness in the management of the nuisances.
- Provide a medium to empower citizens to take care about their environment and participate to local governance.
The project focuses on the citizens’ role for two reasons: odour nuisances are measured as perceptions and using human observatories implies sociological aspects. This enables the citizens to locally participate to environmental governance. The project aims to work on socio-technical mediation and the community-based monitoring approach. To allow and facilitate the collection of the data, the geo-localisation of the information and an automatic integration in the Information System, the project develops a user-friendly geo-mobile application for smart phones.
- Develop a new odour dispersion model capable of near real-time performance
In order to represent adequately odour perception by dispersion modelling an odour dispersion model should use odour emission information, wind and turbulence measurements from a few minutes averaging period and also to provide in the same time scale results. Therefore, the dispersion algorithms which were developed and tested in air pollution applications (order 1 hour) need to be tested and adapted to accommodate for fast odour applications. Due to the short simulation periods and to provide citizens a near real-time feedback, the software code execution needs tremendous acceleration.
- Develop an Innovative electronic nose in-situ sensors network
The specific odour dispersion model needs specific data at the source of the nuisance. The project develops an innovative monitoring system based on in-situ sensors network of electronic nose. The innovation consists in their improved pattern recognition, high time resolution to represent the variations in emissions and smart combination of process-related sensors and finally on their ability to process these various sensor information and send odour rate in real time to the information system.
- Enhance and share the scientific knowledge on odour emission, flow, perception and management
Monitoring and modelling of odours with an adequate time resolution, which captures the nature of odour perception and the publication of these results enhances the scientific knowledge. Moreover, the development of the new odour dispersion model, new sensors and its future application facilitate analysis and understanding of odour related problems.
In line with INSPIRE, SEIS and COPERNICUS initiatives, the odour information system provides an open collaborative platform to easily share new and collected data and information, collaborate and transfer knowledge to the different stakeholders.
- Perform impact studies on local governance in environmental problems
The impact of the system on local decision-making, public education and information and the effective public participation in local governance for environmental issues can be studied. Models for Citizen’s empowerment in decision processed are developed.
- Assistance to authorities in environmental problems
The OMNISCIENTIS information system is intended to be an integral approach and set-up, which can be used after site specific adaptions by authorities for the control of odour nuisance and the evaluation of measures. The communication part and the monitoring and modelling methodologies may be used in a similar way for other environmental problems such as noise or air pollution.
- Contribute to harmonization of legislation at EU level
Based on a review of the actual status of legislations to manage and control odour nuisances and based on the odour information system implemented, the project aims to make recommendations and provide outputs for the future European Norm (EN) standard CEN/TC 264/WG 27 "Measurement of odour impact by field inspection“. This new standard will provide methods for odour impact measurements around an odour emitting facility. Software tools to conduct such measurements are not yet available.
Project Results:
1.3. Main results
1.3.1 Technological results
1.3.1.1 Mobile application
One of the main objectives of the project is to bring citizens technological solutions letting them to perform observations. OdoMap is a result of an analysis and development phase in which smartphones are tools letting citizens and experts to perform odour measurements. Experts’ tool support methodologies (dynamic and static) described in the European standard CEN TC 264 WG27. 21 smartphones with an early version of OdoMap preinstalled (1.1.0) were distributed among watchmen in September 2013. In successive releases several bugs were fixed and new functionalities added.
Aiming to reach the largest number of people, an hybrid application has been developed with standard web technologies (HTML5, JavaScript and CSS), and could be deployed in any operating system. Like apps, they are created once for multiple device operating systems. They combine the advantages of both native and web applications: using native containers allows users to access the device’s native service such as camera, GPS and local device storage and it saves development time as it only have to be coded once. For the moment it runs on Android and iOS and is available on the Google Play and the Apple Store. The last version (1.4.1) includes a set of functionalities that could be easily migrated and adapted to other domains of expertise in which data has to be collected. It includes:
• Authentication service, allowing secure access to dedicated content and to personal data even if the device is offline. Unless user logs out, system automatically remembers user and pass details for next access
• Training module, with specific instructions about how to perform odour observations: methodology, schedule and number of weekly observations.
• Access to meteorological data from weather station located in the study site in real time.
• An odour observation tool, allowing citizens and experts to record their observations. It exists three versions: one for resident watchmen and two for experts, to perform static and dynamic campaigns. It is mainly composed by a map viewer, adapted data forms to be filled in during an observation and a historic registry showing all observations classified in chronological order. In addition it includes a chrono, a legend, a help section and a layer selector to select the base layer.
• Communication tools permitting any authorized stakeholder (administration, expert or industry) to send a message through the OdoMis web platform to be displayed in all or selected watchmen’s smartphones. On the one side the announcement panel is displayed in all the menu pages of the mobile applications. On the other the push alerts let to notify users even where they are not actively using our application.
• Calendar, showing the most important events. It serves to remind the watchmen and panellist the upcoming observations campaigns or any other relevant activity.
Among the advanced characteristics it includes an automatic registration location of GPS or best geolocation accuracy available (Wi-Fi or 3G) and of date/time. Supports working in offline conditions, so user can still add and make edits to his data. Automatic synchronization is performed between the spatial database and the server once a network connection is available.
The user shall not have to deal with the technical complexity of heterogeneous interfaces, so ergonomic aspects and usability has seriously been taken into account since the beginning. Therefore during this time a few watchmen (4 of them) needed assistance to solve problems with their smartphones. Most of the times, it was caused by using an old version of the application, so that the observations could not be sent to the Omniscientis servers. Almost 5000 observations were recorded. The application has also been used by the experts during 15 field terrain inspections, most of them conducted during the validation phase. This represents more than 400 measurements.
1.3.1.2 Platform
One of the key points of the platform, OdoMIS, it is to be the interchange node between different kinds of information (raw data and added-value data) and between different types of local stakeholders. Indeed, citizens, experts, local authorities and manufacturers use the platform to discover, share, visualize and analyse a large quantity of information such as odour observations collected thanks to the mobile application, data coming from weather station, data coming from industrial processes, data collected by e-noses, and odour plumes computed by specific algorithms….
The platform is designed to integrate a large panel of services and to add or develop easily new services. Aiming to improve simple and intuitive use of the platform by the stakeholders, a flat design was been applied. Thanks to the used technology, the OdoMIS platform provides a new experience for the users in the context of the odour management. Depending on their privileges, the users have access to the following services (Figure 3):
Figure 3 – Architecture of the OdoMIS platform
• Submit observations - The platform allows users to record observations thanks to an user-friendly form.
• Discover observations - The platform allows users to show the recorded observations. Experts have access to all observation and watchmen have access to only their observations. Specific tools have been integrated aiming to facilitate the navigation (selectors, filters, sorting).
• Monitoring in real time - The platform shows in real time the ten last recorded observations on a map viewer and allows to interact with data.
• Sensors - The platform allows to discover the different in situ sensors: weather station, e-noses. In addition, several specific sensors that can be used to estimate the quantity of odour emitted in the atmosphere by the industry are also available. The OGC standard, Sensor Observation Service, is used to provide access from sensor‘s observations to sensor systems in a standard way
• Processing - The platform allows to run model developed during the Omniscientis project and to display the result - odour plume - in a map viewer. This service is based on the OGC standard, Web Processing Service. As shown by the Figure 4, the web processing service developed for the OdoMIS collects several types of information before to run the model. The result is then displayed on a map viewer thanks to another OGC standard, the Web Map Service. It is noted that the model takes into account the digital elevation model to produce the plume.
Figure 4 – WPS
• Messaging - The platform allows to send notifications to the users’ mobile phones where the mobile application is installed. It is also possible to configure the message to be displayed by the mobile application.
• Statistics - The platform allows to discover multiple types of statistics. Firstly, the use indicators describe the rate of activity of the users with the mobile application (ex. number of observations recorded by the different watchmen during the last 20 days…). Secondly, a set of indicators showing the main trends in term of odour, type of odour, intensity and discomfort have been implemented
• Campaign - The platform allows to show the results of the campaign carried out by the experts. This service display all observations recorded during a campaign with their features - with or without the use of a map viewer.
Generic services are also available through the OdoMIS platform:
• Internationalization - This functionality allows to change the language of the site. Thanks to the technology used, it is very simple to add new language to the platform.
• Download data (observations and statistics) in csv format
• Authentication - This service manage the user’s access.
In addition, a warning system in real-time has been developed aiming to alert experts and manufacturers of recorded observations that are characterized by the presence of odour with high discomfort or/and high intensity.
1.3.1.3 Odour Information System Integrated and interoperable
As a general result of this project, OMNISCIENTIS delivers a highly configurable system composed of various components compliant with Open Standards (OGC) that allow to collect, store, access and display sensors measurements, mobile observations and cartographic layers. It also allows to launch and orchestrate geospatial processing services.
The Odour Information System is a set of Web Services adhering to a REST architecture defined by W3C. All the Web Interfaces are compliant with the most recent OGC Specifications that have either been adopted and are in a stable phase of development.
A central web portal allows access to a set of distributed secured Web Services. The advantages of such architecture are the flexibility and scalability to adapt to new environments. For instance, one of the components could easily make evolve or migrate its technology without affecting the rest of the system.
The OMNISCIENTIS distributed architecture is presented in the next figure:
Figure 5 - Overview of the distributed architecture of Omniscientis
The solution is “thematic-neutral” and that allows to easily instantiate and adapt in various thematic domains, by connection of specific components.
• Collection of sensor data: generic client deployed in the pilot site, and developed in JAVA are able to read, transform and sent data measured by the meteorological and e-nose stations as well as measurements from the industrial plant using the SOS OGC standard. Through an “insert observations” operation, data is sent to the server in a XML file complaint with a very specific data profile defined by the standard and self-describing the observation: time, type of sensor and measure, unit, etc. An adaptation could be easily and quickly done to send the data to a new SOS server.
• SOS server: receives all the measurements from the sensors data clients, and provides a means for accessing and sharing. Through HTTP methods (GET, DELETE,…) the platform and the mobile application interact with the server: request of sensors available, perform temporal requests, etc. The implementation is based on the 52º North SOS, and could easily be added to existing deployments and receive request from any client connected to internet.
• WPS: answers a need of executing geoprocessing operations via web services and is a key feature of the Omniscientis project. Using the provided input parameters and those that are automatically got from the SOS Server, the process implemented in another server (described in detail in section 1.3.1.5) is executed. For the moment this is executed in asynchronous mode, so the client has to wait for a few minutes while the process is completed. When is it completed and successful, a single binary (ASCII) output is produced. Automatically a mapfile is created and the plume is offered through a WMS service (OGC Standard). Once again, this plume could be publicly accessed through the internet (Figure 4).
• Platform: as described in section 1.3.1.2 serves as a unique and central access point for all the users. An authentication system based in a HTTP’s “basic and digest” authentication framework secure the access.
1.3.1.4 E-nose network
According to the evaluation of the different odour sources at each site, possibilities of e-nose installations were studied for the cases of the Burgo Ardennes paper mill and the pig farm in Styria.
In the case of the paper mill, severe conditions of temperature and gas composition impede e-nose installation into the main stacks. Emission rates from the sources were therefore inferred from industrial process variables (called tags). Thirteen odour sources were identified and measured for their odour rate. The state in real-time of each source is known by industrial process variables (both on-off value and pressure threshold). The odour rate is deduced by the following algorithm:
if [tag1]=1; [tag2]>100 then [odour rate] = x (as an example).
E-noses were developed to measure odour variation in ambient air in the direction of the most impacted zones. A new array of gas sensors was tested successfully for sensitivity and selectivity to odours from the site and particularly from the waste water treatment plant (identified as the main odour source in terms of concentration/frequency ratio). Two devices were placed on site and monitor odour variations in real time. The first one was installed near the waste water treatment plant in direction of Dampicourt and the second one a bit further from the site in direction of Virton. The calibration phase consists in submitting odour samples to the sensor array and to put into relation their responses with odour concentration. Based on these measures, calibration algorithms were developed to quantify continuously the odours perceived by the sensors. Algorithms were updated regularly to compensate the drift of the sensors. The odour concentrations inferred by e-noses gave fairly good results (see Figure 6 for example).
The development of the odour monitoring system is established around Burgo-Ardennes. Thanks to these tools, odours are monitored from their emissions to their olfactory impact:
- Odour emission rates are continuously inferred from the industrial process variables
- Thanks to the meteorological data and these odour emission rates, dispersion model calculates the extent of the olfactory impact.
- Odour information at reception is inferred from e-noses and watchmen observations.
Processing and evaluation of industrial process variables as well as both e-noses drove to the elaboration of algorithms for odour quantification. These algorithms are now integrated into OdoMis for running the odour impact of the whole system every 6 minutes.
Figure 6: Predicted odour concentration from the e-nose 1 in Burgo-Ardennes compared to odour concentration measured by olfactometry
In the second case of the pig farm, all odour emission sources present acceptable conditions for e-nose use. A new sensor array was successfully tested for their sensitivity to pig farm odours. Three fixed e-noses were installed on site, two of them at emission in the two main stacks, with a pitot wing monitoring the flow rate, and the third one in the field at immission. A reduced calibration (4 samples) was achieved due to the distance from the olfactory laboratory. Algorithms were provided for the three e-noses. Fairly good results were obtained in terms of odour variation, but an enhanced calibration with more samples could help to achieve better results. However, problems with the farmer impede to obtain further results.
1.3.1.5 Odour dispersion modelling
Due to the subjective nature of odour perception, fast modelling techniques were used together with measurements to assist and adjust the information given by citizens and to be able to give citizens an immediate odour exposure feedback. Therefore a transient “real odour dispersion model" capable to resolve odour nuisance, based on the pollutant dispersion model 'GRAL-C' (Öttl and Uhrner, Atmospheric Envrionment, 2011) of the Graz University of Technology (TUG) was further developed, modified, accelerated and tested to be applied for odour simulations. Main parts of the GRAL-System were transferred so that they can run on GPUs (Graphical Processing Units) instead of CPUs.
The model development comprised the development of interfaces to use short term measurements (wind, turbulence and odour), the adaptation and validation of the dispersion algorithms using tracer experiments towards shorter simulation periods (order minutes instead of 1 hour), the acceleration of the computations by reorganizing and converting the original FORTRAN code to CUDA to be run on GPU. Finally, the model output and post-processing of the model output was adapted to be used in the OMNISCIENTIS odour information system and for odour specific applications. An important work was to further improve the existing model and the testing of the transient model performance. Due to the lack of transient odour validation data, first test runs were performed for a tracer release experiment from a tall stack in an urban environment. These tests undertaken with the CPU version formed the basis to compare the CPU and GPU dispersion parts. Test simulations for winter time PM10 using well established emission inventories generated during the EU project PMinter (www.pminter.eu see also book reference below) from the European scale down to the local scale (own processing of traffic and domestic heating emissions) indicate excellent results of the new transient model. Here, a coupled modelling approach using a chemistry transport model to simulate secondary formed aerosols and the impact of regional scale transport together with GRAL to simulate the impact of locally emitted primary PM10 mainly originating from domestic heating and traffic were utilized. In Figure 6 comparisons between PM10 concentration measurements and simulated off-line coupled result at the air quality monitoring station Klagenfurt Völkermarkter Straße (Austria) are shown. The new transient dispersion model was independently tested in air quality applications using 30 min and 60 min means and compared with PM10 air quality measurements. Further details and results of this work, the data used and the modelling approach are given in the book written by Uhrner et al., 2014, listed below.
Figure 7: Simulated and monitored total PM10 at Völkermarkter Straße in Klagenfurt using an off-line coupled WRF-Chem/GRAL-transient approach. Ambient temperature (T), simulated and monitored wind speed (WS) are shown as well.
A model suite consisting of three configurations or main set-ups with near real-time performance was finally developed. All three GPU configurations were successfully tested and validated within air quality applications and the two OMNISCIENTIS pilots.
A simple and very fast GPU configuration was developed for flat terrain applications neglecting the impact of buildings. The benefit of this approach is the minimized efforts in data preparation and the possibility to carry out computations for large domains. Moreover, the speed-up compared with a single state of the art CPU processor is approximately 400 with this set-up.
Based on the first configuration, pre-calculated flow fields and terrain information can be used in the second main modelling set-up, the flow field library approach. This set-up requires the analysis and classification of local complex flow conditions prior to the odour simulations. A big advantage of this approach is that the solution is already existing and typical problems such as convergence problems cannot occur during run-time.
The third configuration is intended to be used in applications to account for the presence of buildings. The presence of tall buildings (e.g. factories, stacks, or even skyscrapers) may lead to the so-called building downwash effect which leads to increased vertical mixing of air layers and hence odour. However, the presence of buildings may also impose a shielding effect in way that people living further downstream of an odour source may be less affected. In this set-up the complex flow between the buildings is accounted and computed during run-time.
In all three configurations the computation times were below 5 minutes for flow and dispersion within the pilot applications.
The GPU versions were regularly tested and compared with the FORTRAN version. The results from both models are comparable. Small differences are mainly attributable to the higher number of particles used with the GPU version. The speed-up of the GPU version and/or the possibility to track more particles (higher particle density), see Figure 7, is a clear benefit of the GPU version. The speed-up of this version is about two orders of magnitude compared to the CPU one using a single state of the art processor.
Figure 8: Comparison of results obtained from 360.000 particles and 144 million particles. The images show the concentration with equal contrast settings.
1.3.2 Sociological results
Within the project, a “community-based” approach was applied in order to involve the citizens in a Local Environmental Governance (relying on the odour monitoring systems). The idea was to design a physical and intellectual space for shared understanding and collaboration between all stakeholders impacted by the environmental problem of odour emission.
Based on the development of the Information Technology (IT) system allowing odour emission measurement as well as the collection of citizen feedbacks, a Living Lab (LL) approach has been implemented in the Belgian pilot, in the area around Virton. This Living Lab approach involved citizens, public authorities, industry and environmental non-governmental organisations (NGOs).
According to the definition of the European Commission, Living Labs are “open innovation environments in real-life settings, in which user-driven innovation is fully integrated within the co-creation process of new services, products and societal infrastructures”. Based on this definition and considering, in our case, citizens as one of the end-users of the IT system, the proposed approach was focused on citizens empowerment in the Local Environmental Governance.
Living Lab stakeholders where first identified and characterised, in terms of fears, expectations, involvement and willingness to engage. Based on this first study, several working groups where organised in order to build trust and establish a common goal.
During the pilot performed in Burgo Ardennes, a first group has been constituted with Public Authorities (mainly neighbour cities), Citizens and people from Burgo Ardennes. They have developed a common knowledge on odour annoyance.
This group has worked together during the project and is willing to continue after on a regular basis. They also want to enlarge the existing group and are already working on the identification of possible means to do it.
Some basic functioning rules have been identified and agreed among these stakeholders (governance principles and required role to achieve their common objective). Citizens are engaged in collecting and sending data to Burgo Ardennes on their feeling about odour emission. Burgo Ardennes has already identified some improvements in order to reduce odour emission and is willing to continue the work which was initiated during the project. Public authorities are also involved and ready to participate in the future in the governance which is emerging.
During the project some key factors that have to be taken into account for future developments of such an approach have also emerged. First of all representativeness is a critical issue. Indeed the LL was composed mostly of non-working people, as working people have less time to participate to such community. In this sense it is difficult to guarantee sustainability of decision made by such a community if its members do not represent all the interests. In order to avoid representativeness issue, social media could be an alternative in order to allow online and off-line participation.
In the Omniscientis project, citizens encountered difficulties to define what they would like to achieve together, because of a lack of knowledge about odour emissions. Proposing some simple actions (such as company tour or “open doors”), prior to any community based work, helps to build a common knowledge on the considered problematic, and then makes it easier to work together.
Finally a special attention has to be paid to the Local authorities’ position. In a Living Lab perspective, local authorities are considered as a main stakeholder. It has to be recognized that, during the project, local authorities have played a minimal role in the Omniscientis Living Lab. At the end of the project, and only at the end, local authorities appear to be the actor that should become the leader of the future governance.
Governance implies a common purpose, joint action, a framework of shared values, continuous interaction and the wish to achieve collective benefits that cannot be gained by acting independently. Although the proposed methodology has to be adapted according to the previous remarks, the efficiency of the methodologies used within the Living Lab could be assessed in consideration of these governance requirements.
Potential Impact:
1.4. Potential impact
1.4.1 Impacts on citizens empowerment
The major benefits and added value of a successful OMNISCIENTIS project are available for citizens, industries, experts and public authorities:
1. Neighbours of a plant with regular odour emissions were frequently not able to communicate the occurrence of odour in their living environment in an appropriate way. They could complain but if they did so, this was happening in a non-structured way, sometimes some hours or even days later.
Hence Omniscientis aims to integrate citizens in a communication system with appropriate tools to support bidirectional exchanges. Web-based Services Platform allows proactive and reactive requests for collection of information on odour nuisance by the citizens. Such a system have alert capabilities allowing industrials and authorities to inform the citizens if some process parameters are drifting and, in the other direction, citizens receive message and alerts in theirs smartphones. It allows citizens to alert the industry if they observe odours in the neighbourhood. In case of intense nuisances, plant managers receive alert mails.
For the interested citizens, who may want to participate in measuring campaigns, they collect data via a geo-mobile application and a dedicated website by providing inputs, letting them to act as human sensors. In this way they contribute to populate the data repository for diagnosis and validations purposes, and enhancing the information system.
On the other side, through a Living Lab, citizens are enabled to participate actively together with all stakeholders involved, including local authorities and industrial, in defining priorities, share insights and follow actions plans related to odours. Through mobile app and web they have direct access to near real time data, such as meteorological data, e-noses measurements or even available industrial process status.
2. From a point of view of industrials, who are confronted with the complaints from neighbours living around a plant, OMNISCIENTIS contributes to understand better the relation between emissions and odours observed in the surroundings. Electronic noses allow getting better information on the time behaviour of sources. This information is today not available using standardized measuring methods because they need sampling times of 1/2 h. Fast modelling capabilities allow to retrace the plume depending on short term variations of emissions and weather conditions. The information system allows getting quick feed-back and alert from the citizens, thus enabling the industrial to modify, if possible, rapidly plant parameters in an appropriate way in order to avoid the exposure to strong odours. On the other side the system allows to show in more details the actual location of an odour source.
3. The experts benefit on several levels:
• get detailed information on the time-behaviour of odour sources
• facilitate measuring campaigns as described in new European standards from CEN TC 264/WG 27 by allowing to integrate citizens observations in a data depository which will enable experts to analyse more and better data
• fast and specialized odour dispersion models can finally be used to provide forecasting under expected meteorological conditions and/or compute yearly mean exposure frequencies.
4. Public authorities benefit by getting a faster and more detailed understanding of odour observations around a plant. They are able to define commonly agreed limit values, based on objectively measurable exposure values.
So we expect that our system contributes on empowering citizens on environmental monitoring and in their active participation for environmental management. Our approach could be easily exported and adapted to any other environmental issue. This has three main impacts at a sociological level:
- Empowerment relies upon principles of democracy and equality, so participation of citizens is good on its own. Furthermore it is argued that because the act of participation, people improves their skills which enable them to function more effectively as individuals.
- Empowerment improves the process of decision-making, the quality of decisions made and services delivered. In fact, through working with external parties, organizations can gather ‘intelligence’ and use it to improve service provision or decision-making.
- Empowerment gains support for policies and management processes in which a participation process in engaged. Participants that take part in and learn about systems builds, improve their trust besides organizations and decision-making structure.
1.4.2 Impacts on odour regulatory framework
The situation today in Europe is a very disparate legislation level and a very disparate technical background. Some countries are not limiting odour emission or impact at all, some countries have developed some specific limit values, which can be different from one type of odour source to another, some other countries have very elaborated and complete technical guidelines and limit values derived from these guidelines.
Some countries are specifying in detail the type of tools to be used for controlling the respect of limits; others, even if they have defined such values, are not specifying at all the minimum technical requirements for such tools.
Together with already existing European standards and the future standard for conducting field inspections, elaborated by the CEN-TC264-WG27, these new tools allow the definition of an harmonised European Framework for the evaluation of odour nuisance and exposure limit values.
The key issues of such a future guideline could be defined as follows:
• Emission rates in future permits should be derived from the expected exposure level
• The acceptable exposure level could be defined as a maximum number of odour hours as defined in the future standard on field inspections.
• The verification, that such exposure levels are respected requires tools for conducting field inspections and dispersion modelling, for example as developed in OMNISCIENTIS
• The definition of acceptable emission rates requires clear technical requirements, a dispersion model and the necessary input data.
Some technical key requirements are, from the point of view of the OMNISCIENTIS consortium:
• The time resolution of input data and modelling have to be better than 6 minutes (derived from the definition of an odour hour)
o The meteorological data as input for the model have to have the same time-resolution and have to be measured nearby the emission source or have to be representative for the local situation (see the definition of representativity in the future CEN standard)
o Emission data need also the same time-resolution (for the verification of existing sources) or have to be considered as constant in time with a maximal emission rate. If different time behaviour is used, it has to be justified (for projects asking for authorisation).
• The measurement of emissions has to be performed using existing European standards for canalised sources
• For non-canalised sources, in particular for surface sources and diffuse sources, a field inspection with backward modelling is recommended.
• The minimum requirements of a dispersion model are:
o Lagrangian model or equivalent, no simple Gaussian model
o Maximum time step 6 minutes
o Particle resolution (for lagrangian models) higher than 1 000 000 particles
o Minimum diagnostic wind field modelling depending on local conditions. Use of prognostic modelling can be required.
o Characteristics of such local conditions can be derived from German rules
Additional considerations:
• In the case of complaints, citizens could be involved by using an odour management system as developed in OMNISCIENTIS, allowing local governance and the resolution of problems.
• The European wide definition of the principal way for defining acceptable exposure levels based on the definition of an acceptable number of odour hours would harmonise this key element of a future guideline. Today, many and very disparate definitions are existing all over Europe; most of them cannot be verified in a technically valid way. For example a limit exposure concentration of 5 OU not to be exceeded for 98 % of the time of a year cannot be verified without a corresponding, very detailed meteorological dataset and a corresponding dispersion model.
2. Dissemination and Exploitation
2.1.1 Target audiences
The target audiences for the Omniscientis project are extremely vast, ranging from the citizens suffering from olfactory nuisances, industrial entities generating the nuisances, the regulating Authorities, up to the experts and scientific community interested in studying the technical, economic and social aspects of the odours. These audiences can be categorized as follows:
• The regulating authorities producing the laws, regulations, directives or controlling the application and observance of these rules;
• The experts drafting the standards for measuring the odour impact, recommending mitigation practices, etc;
• The industry generating the olfactory nuisances and implementing mitigation measures;
• The citizens (neighbours) suffering from the nuisances;
• The associations in charge of representing the interests of the neighbours and the Society in the context of improved quality of life;
• The local authorities (mayor, governor, minister, etc) responsible for the fair balance between the social and economic interests in their area of competence;
• The scientists conducting research work in the domains of technical solutions for odour measurement and forecasting or for odour mitigation techniques;
• The sociologists doing studies on nuisance problems in the Society or conducting mediation actions.
The challenge of the Omniscientis Dissemination is to address adequately all these stakeholders and their specific, sometimes contradictory, interests.
2.1.2 Main dissemination activities
Our results were mainly disseminated via the project website. Furthermore two different brochures, two posters and a roll-up were designed to be shown at the thirteen international conferences attended. We also produced 5 scientific papers and organized two workshops and a conference inviting citizens, scientific community and policy makers.
2.1.2.1 OMNISCIENTIS official website
The OMINSCIENTIS website provides quickly to a wide audience the basic information concerning the project and is available at www.omniscientis.eu.
It includes:
• A homepage and an about section, providing general information on the project
• News and events announcements (conferences, workshops) related with the project
• Direct link to the OMNISCIENTIS information system where observations and results from the project are available
• Public download section for OMNISCIENTIS project
• Protected access to project-internal documents was granted to the reviewers and members of the user group
Figure 9 – Screen shots of website
2.1.2.2 OMNISCIENTIS video
During the project the European Commission produced a video promoting new earth observation systems using monitoring and information systems by citizens. In this context OMNISCIENTIS, CITI-SENSE and CITCLOPS are presented as example of successful citizens observatories projects.
Figure 10 – Frame of the video
2.1.2.3 OMNISCIENTIS factsheet and brochure
In December 2012 a first factsheet was produced, presenting in an A4 double page document the project to a large and open public. The factsheet highlighted the sociological dimension of the project.
A brochure has also been designed, published and printed during summer 2014 for dissemination purposes, with messages related with OMNISCIENTIS outcomes and benefits for target users and potential customers. To reach more people, it was produced in French and English.
Figure 11 - OMNISCIENTIS leaflet
2.1.2.4 OMNISCIENTIS users’ workshops and final event
The Consortium organized two workshops dedicated to users and a Final Event, in order to present results of the project, discuss various issues with the users and get a formal feedback from the users on specific questions of interest for the project and the future exploitation of the results. These workshops helped in creating a cooperation network among the user participants and in increasing the impact of the project.
Each event had a specific purpose, as presented in the following lines:
• The first workshop was organized in Arlon (Belgium), at the University of Liege (Faculty of Sciences and Management of the Environment), on Monday the 7th of October 2013. The workshop was divided into three successive sessions:The first session introduced the involvement of the citizens, from the perspective of the European Union and the Government of the Walloon Region of Belgium; the second session was dedicated to the exchange between the workshop participants, organized in smaller groups, followed by a time for providing to the assembly the feedback of the groups about their ideas, findings, and suggestions and the third session reported on live experiences, where citizens are participating to the decision making in environmental issues; the session ended with a presentation of the OMNISCIENTIS project.
• Second workshop was held in Graz (Austria) in April 24th 2014. It addressed the challenges of the olfactory nuisances and the on-going regulations and standardisation activities. With a high attendance of experts on the domain, it was organized in three themes: odour regulatory framework, methodologies for measuring odours and holistic approach to odour nuisance monitoring.
• On 23 September the final conference of Omniscientis took place in Brussels. It provided an open forum in which citizens, policymakers, industrials and researchers exchanged ideas, ideas and experiences on odour management.
At the core of the one-day conference was the question on how to create collaborative ecosystems based on transparency of the information, reliability in the stakeholder's relationship and responsiveness in the management of the nuisances.
Leading experts presented their results of the project, particularly in the fields of odour modelling, e-nose sensors networks and odour information systems. Interesting discussion was also held on citizens’ involvement and participatory methodological frameworks.
List of Websites:
www.omniscientis.eu
CONTACT
Philippe Ledent - SPACEBEL
philippe.ledent@spacebel.be
+32 4361 81 11
