Vision 360

Vision 360 platform is a Suez registered trademark. Vision 360 is an environmental data management system, focused on air quality, odors, emissions and meteorology, all based on Web technology.

Vision 360 Advantages

The comparative advantages with other systems are its flexibility to integrate new developments "ad hoc", the ability to consult data from any place and device with Internet access, as well as the possibility of outsourcing environmental information, so that the technician or operator of a monitoring network in charge of data management tasks disregards the exploitation, but he can control it at any time and carry out all the necessary tasks.


Into its modular system concept, the platform is made up of three systems: Supervision, Hypervision and Manage.

Supervision

Supervision integrates all those tools in charge of managing and exploiting data from environmental observations, as air quality control cabinets, mobile immission units, nanosensors, meteorological stations, LIDAR, emission monitors, etc.

It is introduced as a modular, intuitive and powerful application. It is possible to integrate in the application new functionalities to customer demand. The basic functionalities are the following:

  • Visualization of data in real-time (last data received, air quality indices, etc). Alarms of exceeding thresholds and critical values on screen and by e-mail.
  • Generation of systematic reports (daily summaries and notification of exceedances).
  • Data advanced analysis module based in IA.
  • Data graphs and reports. Data export and WEB-API

Hypervision

Hypervision integrates, into the VISION 360 interface, information generated by advanced mathematical meteorological, air quality and emissions models. The spatial resolutions of the models are generated to customer demand, being able to cover the local scale (from 4 meters of spatial resolution in Street canyon models) to regional or mesoscale resolutions. It is composed of the following modules, depending on the function of generating retro-trajectories, operational predictions, or dispersions in diagnostic mode:

Hypervision Backtrajectory

As a complement to predictive modeling, and with the aim of confirming the origin of air masses (pollution sources) during detected pollution episodes, VISION 360 allows to generate back-trajectory analysis from the locations of the stations where non-compliance has occurred or any other. point located in the domain, such as specific observations, citizen complaints, etc.


This function becomes a support tool for the identification of potential sources of pollutant emissions, determining the possible origins.

Hypervision Forecasting

HYPERVISION FORECASTING air quality prediction system is a tool that forecasts the impact on air quality up to 24/48/72 hours in advance. This prediction capacity becomes a perfect decision support tool that allows correcting or taking measures on the susceptible processes to generate the emissions that will cause the impact.


Forecasting is based on a complex system of mathematical models. It is possible to chain high resolution Street Canyon models with regional photochemical models. As a weather model, Hypervision Forecasting uses the WRF model. The Weather Research and Forecasting - WRF (Skamarock et al. 2008) model is a last generation limited area numerical model designed for research and numerical prediction of meteorological weather.


To achieve even higher resolutions, Forecasting can use other downscaling models to increase spatial resolution.


On a local scale, Hypervision uses micro-scale flow models.

Technical specifications for HYPERVISION dispersion models

  • Street Canyon (Gral / PMSS), for primary compounds (1-50 m resolution)
  • Gaussians / Lagrangians (Calpuff / Aermod / Lapmod) (50 m - 1 km resolution).
  • Eulerian, photochemical (Chimere, CAMx), from 1 km resolution.
  • Update frequency: 4 times a day / Daily Prediction time scale: 24/48/72/96 hours.
  • Meteorological variables: temperature, rain, wind speed and direction, solar radiation, cloud cover, boundary layer height, humidity, atmospheric pressure, among others.
  • Data at ground level (surface) and height.
As an example of the functionalities, two images corresponding to a regional ozone prediction (O3) with a photochemical model (top) and a nitrogen dioxide prediction with a Street Canyon model at 10 m resolution (bottom) are shown below.