Transforming urban life: Particulate matter emission and dispersion analysis

Owing to the rapid industrialization, extensive vehicular emission and various other combustion activities there has been an upshot in the amount of air pollutants such as particulate matter (PM_x), being added to the atmosphere. Depending upon the size of the emitted pollutant in micro-meters these particles are classified as PM₁₀, PM_2.5, PM₁. Notoriously these particulate matter (PM_x) are a major cause of various respiratory diseases, along with visibility impairment, environmental and material damage. Thus a genuine case crops up to monitor the emission and the dispersal of these particulate matter in order to identify the sources of pollutants, demarcate the pollution hotspots, help to develop a data based formulation of mitigation measures and provide the general public with reliable data on the extent of exposure to these pollutants. Though there is an evident requirement for wide scale monitoring the implementation of the system has not succeeded on a large scale especially in the developing economies owing to huge installation and maintenance cost, complicated installation procedure of the pre-existing atmospheric parameters monitoring systems. For this purpose the use of cost effective monitoring systems, Internet of Things (IoT) based network development and end user data availability is gaining in importance. This study analyses various aspects of a cost effective particulate matter monitoring system for wide scale implementation in cities and adjoining industrial hubs to monitor the ambient air quality. It involves the deployment of an IOT based sensor model with a view to develop a network of monitoring devices that can provide highly accurate, feasible and reliable field data on particulate matter. It investigates calibration techniques such as neural network models to improve the quality of data acquisition, post processing and finally giving an output using techniques of geo spatial analysis such as geometric kriging. The aim would be to provide reliable data, capture the trends in the change in concentration of particulate matter emission, validate the models, reduce the inter model variability and finally provide the data to the end user through data visualisation. This data is to be used by the government as well as the general public. This will form the basis of formulation of pollution guidelines, monitoring the actions of polluters and provide a way out for the general public to tweak their routine chores to have minimum adverse health impact. Through this study we aim to bring down the hidden cost to support the urban population i.e. through expenditure in health, unscientific development of green belt, many unplanned construction activities etc. The ultimate aim of this study is to provide a basis for sustainable development of urban settlement and protect the urban population from harmful effects of high particulate matter concentration.