team Data Sauce at CTC15
Looking at tracing through what data is where, what the flow is for the sensors putting it there, and any other data sources that might be useful.
https://github.com/watty62/abdn_air_quality
https://seetheair.wordpress.com/2019/02/07/purpleair-ii-vs-luftdaten/
http://plumeplotter.com/news/LuftDEFRA.pdf
Luftdaten_ID (particulates) | luftdaten_ID (temp) | Madavi_ID | latitude | longitude |
---|---|---|---|---|
5331 | 5332 | 3654427 | 57.138 | -2.077 |
7789 | 7790 | tbc | 57.130 | -2.087 |
8554 | 8556 | 12017738 | 57.146 | -2.114 |
8733 | 8734? | 3654335 | 57.136 | -2.107 |
15462 | 15463 | xxx | xxx | xxx |
17079 | 17080 | xxx | xxx | xxx |
Sensor nodes submit readings to madavi which is then pulled to luftdaten
We have scrape of the historical data for these sensors (where ID is known).
https://github.com/watty62/abdn_air_quality/tree/master/data/luftdaten Folder for each sensor, then file for results for each day.
sensor_id;sensor_type;location;lat;lon;timestamp;P1;durP1;ratioP1;P2;durP2;ratioP2
Pearrson correlation between sensors:
8554 P1 | 8554 P2 | 5331 P1 | 5331 P2 | 7789 P1 | 7789 P2 | 8733 P1 | 8733 P2 | |
---|---|---|---|---|---|---|---|---|
8554 P1 | 1.000000 | 0.806795 | 0.840279 | 0.956321 | ||||
8554 P2 | 1.000000 | 0.908280 | 0.951232 | 0.970601 | ||||
5331 P1 | 0.806795 | 1.000000 | 0.842277 | 0.194654 | ||||
5331 P2 | 0.908280 | 1.000000 | 0.691692 | 0.375951 | ||||
7789 P1 | 0.840279 | 0.842277 | 1.000000 | 0.815039 | ||||
7789 P2 | 0.951232 | 0.691692 | 1.000000 | 0.929308 | ||||
8733 P1 | 0.956321 | 0.194654 | 0.815039 | 1.000000 | ||||
8733 P2 | 0.970601 | 0.375951 | 0.929308 | 1.000000 |
Spearman correlation between sensors (more valid since data is skewed and has outliers):
8554 P1 | 8554 P2 | 5331 P1 | 5331 P2 | 7789 P1 | 7789 P2 | 8733 P1 | 8733 P2 | |
---|---|---|---|---|---|---|---|---|
8554 P1 | 1.0 | 0.81091697049 | 0.896579489448 | 0.946524972808 | ||||
8554 P2 | 1.0 | 0.833924379799 | 0.906765734563 | 0.957153474657 | ||||
5331 P1 | 0.81091697049 | 1.0 | 0.833241977099 | 0.870656302456 | ||||
5331 P2 | 0.833924379799 | 1.0 | 0.874029415016 | 0.870762759225 | ||||
7789 P1 | 0.896579489448 | 0.833241977099 | 1.0 | 0.854244472158 | ||||
7789 P2 | 0.906765734563 | 0.874029415016 | 1.0 | 0.89751895235 | ||||
8733 P1 | 0.946524972808 | 0.870656302456 | 0.854244472158 | 1.0 | ||||
8733 P2 | 0.957153474657 | 0.870762759225 | 0.89751895235 | 1.0 |
Percentage of life of sensor 5331 P1 where particulate matter > 40 micro grams per cubic meter: 8.581590063270923 % Percentage of life of sensor 5331 P2 where particulate matter > 40 micro grams per cubic meter: 0.5372465843391006 % Percentage of life of sensor 7789 P1 where particulate matter > 40 micro grams per cubic meter: 6.69374880519977 % Percentage of life of sensor 7789 P2 where particulate matter > 40 micro grams per cubic meter: 0.24804052762378132 % Percentage of life of sensor 8554 P1 where particulate matter > 40 micro grams per cubic meter: 6.048349700648166 % Percentage of life of sensor 8554 P2 where particulate matter > 40 micro grams per cubic meter: 0.4771080861061591 % Percentage of life of sensor 8733 P1 where particulate matter > 40 micro grams per cubic meter: 11.28586575844231 % Percentage of life of sensor 8733 P2 where particulate matter > 40 micro grams per cubic meter: 0.7775600038556694 %