Datathon Sofia Air Solution – Air station measurement bias correction using Pearson correlation coefficient

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This article aims to improve the estimation of the measured PM10 pollutants. In Sofia, there are several air pollution measurement stations. They measure PM10 particles, which are particles found in the air with a diameter between 2.5 and 10 micrometers.

The measurement stations fall into two categories, official stations and citizen stations. The official stations provide reliable measurements, they are better monitored and documented. The down-side is that they are only 5 and they are all concentrated in a single region. The citizen stations represent devices mounted on people homes or properties which measure PM10 particles. There is a whole network of such devices. They are many in number and provide a good coverage of the city. The problem with those measurements is that they are biased because of many local factors. Therefore the measurements form the citizen stations are not as reliable as those from the official stations, but on the up-side they are many in numbers.

In this article we define a method to reduce the bias of the measurements from the citizen stations.

Datathon Air Sofia Solution – Team Teljapenosss

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— Team Teljapenosss Team Members — Jalapeno (Nasiba Zokirova) Team Mentor: petya-par   Business Understanding The levels of air pollution allegedly caused by solid fuel heating and motor vehicle traffic are ever growing in the City of Sofia. The primary economical impact for the City of Sofia was a ruling by the European Court of […]

Datathon Sofia Air Solution – The Telelink Case handled by the Urban air quality Gurus!

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  1. Business Understanding Particulate matter is considered the air pollutant of greatest concern to the health of the urban population. Researches have shown that exposure to PM can lead to increased days lost from work or school, emergency room visits, hospital stays, and deaths. Both short and long-term exposures to PM can lead to […]

Datathon Sofia Air Solution – Telelink Case Solution

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Telelink Case Solution Team Dimas The Team Members – apetkov – desinik – rdimitrov – melania-berbatova – vrategov Github Repo: https://github.com/Bugzey/Team-Midas Workflow The main workflow happens over at our github page. You can read the latest version of this article here: https://github.com/Bugzey/Team-Midas/blob/master/7.%20Documentation/Doc_010%20Documentation.md ## Content 0. Data We were given the following 4 datasets: Air Tube-20180928T185037Z-001.zip […]

Datathon Air Sofia Solution – Telelink Televised by Teleloonies

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Techonnology and methods used: R – plyr, dplyr, tidyverse, stringr, data.table, geohash, ggmap, maps, robustbase, geosphere, pracma, Hmisc, ggplot2, tidyquant, reshape2, pastecs Python – s3fs, pandas, numpy, matplotlib, plotly, geohash2, folium, geopy OLS Regression, Ridge Regression, Decision Trees Introduction Air pollution beyond the norms is a common problem in many locations. Examining the causes behind and being able to predict […]