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Application of neural networks to the prediction of gas pollution of air

Pawul Małgorzata

New Trends in Production Engineering

2019

Vol. 2, Iss. 1

515--523

The issue of projecting the air pollution levels is quite essential from the viewpoint of the necessity to adopt specific prevention measures intended to reduce the pollution concentration in the air. One can apply certain machine learning methods, including neural networks, to build pollution concentration models. Neural networks are characterised by the fact that they can be used to solve the relevant problem when we face shortage of data, or we do not know the analytical relationship between input and output data. Consequently, neural networks can be applied in a number of problems. This paper discusses a possibility to apply neural networks to the prediction of selected gas concentrations in the air, based on the data originating from the measurement networks of the Polish State Environmental Monitoring System, combined with local meteorological data. Forecast results have been presented here for SO2, NO, NO2, and O3 in various locations. The author also discusses the accuracy of the respective forecasts and indicates the relevant contributing factors.

The concept of a mobile air quality monitoring system for Warsaw

Rogulski M.

Challenges of Modern Technology

2016

Vol. 7, no. 1

32--39

In Poland and in the world is conducted air monitoring in order to care for the atmospheric air. Thus, it is possible to develop of appropriate plans of improvement air quality in certain areas. Unfortunately, the number of stationary equipment in large cities is usually insufficient. For example, in Warsaw under the State Environmental Monitoring, information on the concentrations of pollutants in the air provide only 8 automatic stations and 3 manual stations, of which only 5 stations belong to the Mazovia Voivodship Inspectorate for Environmental Protection. 11 monitoring stations in the metropolitan area of 517 km2, is the number that is not able to provide an accurate measurement of air quality. In the article, on the example of Warsaw, is presented the concept of mobile network devices for air monitoring, from which data could complement to those from the fixed stations. The article sets out the measured substances, estimated cost of mobile network devices, and the choice of means of transport to move measuring devices.