Many particle sensors are useless in foggy/hazy conditions, which ruins many citizen science projects in terms of data quality. Currently, the best solution is to calculate the dew point and then switching them off once you hit a specified limit.

How does this model deal with this?

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pppone 4 days ago | parent | next [-]

I don't think it would. Data in these instances would have to be ignored.

You can detrend for high humidities, but once water condenses, the only way round this would be to add a drying instrument.

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HPsquared 4 days ago | parent [-]

I wonder if a radiant heat source beside the sensor, maybe also somehow focused in the same area, could get rid of the condensed water.

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Catbert59 4 days ago | parent [-]

The problem is not condensed water. This can be solved with heating.

It's that fog is being detected as a particle. This distorts the measured values.

	▲	HPsquared 4 days ago \| parent [-]
		Fog is condensed water droplets suspended in the air. Radiant heat , especially if it's optically focused, could remove them in the area where the PM sensor is looking.

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TimByte 4 days ago | parent | prev [-]

I didn't see anything in the article about humidity compensation