Big Data and analytical systems. OpenWeatherMap data on air pollution for exact forecasts

Big Data and analytical systems. OpenWeatherMap data on air pollution for exact forecasts

Posted on 26 Mar 2016

In recent years, the situation with air pollution is becoming more alarming and attracted the attention of leading media and politicians at the highest level. This is especially true of large cities such as Beijing, Los Angeles, Mexico City, Tehran, Johannesburg and other densely populated settlements, which are under the influence of various risk factors, such as dense traffic, the presence of air polluting enterprises located poorly in terms of ecology, where pollution levels sometimes exceed all standards many times.

Depending on the degree of interest of the authorities in cities, pollution control is more or less in place, but, unfortunately, the monitoring systems which are in use now, are ineffective. Technologies that allow to build forecasts already exist, but they do not provide the necessary level of accuracy and do not allow to predict rises to a dangerous levels of pollution. The basis for the creation of accurate predictions certainly are accurate data on key parameters in an amount, that is sufficient for analysis.

OpenWeatherMap provides unencrypted API data on basic parameters such as carbon CO2, ozone O3, nitrogen dioxide NO2 and sulfur dioxide S02, as well as data on the contents in the air of fine particles AOD (Aerosol optical depth), which are extremely dangerous for human health. OpenWeatherMap processes massive amounts of accurate data that can be processed for any geo point in the world. This data is obtained from tens of thousands of sensors worldwide from satellites and monitoring systems. On the basis of such data, using modern technology, such as the Internet of Things (IoT) and Big Data has now become possible to build the analytical system, capable of delivering high-precision forecasts for maximum contaminant levels for a few days in advance. With these forecasts, experts can formulate recommendations, and local authorities are able to take measures to reduce pollution, such as the optimization of the traffic, movement of industrial facilities outside the city, planting of forests and the creating green parks at key locations in major cities, the use of alternative sources energy. Similar measures have already been shown to be effective in some countries - in the UK (London) and in Japan (Tokyo).

OpenWeatherMap provides API to the historical data, as long as to the data obtained as a result of monitoring in real time, which allows a visual comparison, including the virtualized format and helps to identify the sources and periods of maximum and minimum levels of pollution, their possible recurrence, estimate the effectiveness of measures taken to combat the pollution and to understand the weaknesses of the monitoring infrastructure in the big cities.

With the help of a joint analysis of pollution data, historical and current weather and satellite data provided by OpenWeatherMap, one can find the cause of environmental degradation in any region or a particular village - to find out the location of the sources of pollution, to assess the impact of, for example, the formation and dispersion of smog, important factors such as temperature and humidity, wind direction, the level of ultraviolet radiation (UV index), to evaluate the pros and cons of geographic location.

Currently, OpenWeatherMap, together with its partners, develops innovative solutions and models, which allow not only to deliver data and API to different data in the clear mode, as is the case now, but also to visualize all this global information clearly presenting it in the form of graphs and interactive maps which makes the work with data suitable for analysis.