Interpreting data

I am trying to get a better sense of how to interpret data from the sensors in my state area(South Carolina). I was curious if there were examples of users being able to figure out patterns of point sources of man-made pollution as contrasted with non-man-made natural phenomenon (weather,etc). For example, in the below screenshot I can see a general correlation between air quality points that are about 90 miles apart between Charleston and Myrtle Beach during the previous month of May, which would make me think this is more of a natural wider area weather pattern that a point source of man-made pollution which I would think would be more localized.

I am thinking there should be some way of analyzing the data from all sensors with a given local or regional density of monitors to differentiate maybe between natural/wide patterns and man-made/local patterns and their locations.


Right, after years of watching these meters, I have seen there are both regional and local contributions. Regional are often related to weather fronts and wind direction - where I am typically bad from the south, and better with cold front out of canada. Then there are local sources … if you live close to congestion, wild fires, manufacturing, or in my case, some of those, plus a neighbor that heats his house with wood, or local burning of yard waste, over zealous barbecuing, lawn mowers and machines, etc. But even if moving away from the local issues, say 10 or 20 miles, I’d still be subject to the regional air quality (and possible other, different local issues). I can make out patterns of better regional locations.

Of course, this is just analysis by sight. You may be after more mechanized, automated.


Thanks for the feedback, I work with some low-income communities near interstates and industry and thus far with the smaller number of sensors I haven’t seen issues with air quality that I could readily point towards a more localized point source of man-made pollution. Wildfires and their broader scale effect on air quality on the west coast seem to be a better application so far for this type of sensor with regards to being able to more easily associate and follow a cause and effect tracked by the sensors. Or to restate, most local sources of air pollution don’t contribute enough individually(unless monitored very close to the source) to make much difference when measured from several hundred yards away. The sensors are probably a better indicator of larger regional(between 50 and 150 miles) aggregate air quality or similarly large regional contributors to poor air quality such as forest fires.

In general, I understand your point. But my experience is counter to it. My neighbor, who is about 100 yards away and burns wood exclusively to heat his house, will send my meter well into the upper 100’s when he cranks up his fireplace, when other meters one to a couple of miles away are in the 20s or 30s. This is particularly the case when winds are “light and variable” at night. I can also tell when some habitual yard waste burners are at it several streets over, just by looking at my meter (when the wind is out of their direction).

Thanks again for the input and your experience with the air monitor use. We used to live at a house across from some good retired neighbors whose only fault was burning their leaves during the fall and it made the air smoky, acrid and unpleasant so sorry having to deal with that and can better understand the utility of the monitor in understanding and documenting issues in that case. Currently we live probably a mile from the interstate and I think the combination of the high-speed traffic dispersing any particulate matter and geography and wind patterns I don’t know that we would pick up much signal from that source. Ideally would be nice to have inexpensive consumer sensors for ozone or other air pollutants other than PM2.5 to PM10, but haven’t researched those.