Public Lab Wiki documentation

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

Questions

[questions:optical-pm]

How optical particle sensors work

A sensor and a beam of light sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Read more in-depth in this illustrated post by @DonBlair.

The sensor registers a pulse for as long as the particle reflects light to the sensor:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Issues with optical particulate data

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an ‘impactor’, which has a less sharp cutoff.

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014, Purple Air. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

[questions:dylos]

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

[questions:speck]

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

[questions:airbeam]

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

[questions:dustduino]

Other platforms

ManyLabs

clAIRity

Pickle Jr.

Also see

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

Questions

[questions:optical-pm]

How optical particle sensors work

A sensor and a beam of light sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Read more in-depth in this illustrated post by @DonBlair.

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014, Purple Air. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

Questions

[questions:optical-pm]

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014, Purple Air. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

Questions

[questions:optical-pm]

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

Comparative tests

A number of comparison tests of commercially available sensors have been performed or are underway. Please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD's Air Quality Sensor Performance Evaluation Center
• AQICN: Air Quality sensors experiments on the World Air Quality Index project
• EPA Evaluation of Field Deployed Low Cost PM Sensors

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

A number of comparison tests of commercially available sensors have been performed or are underway. please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD
• AQICN
• EPA Evaluation of Field Deployed Low Cost PM Sensors

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

A number of comparison tests of commercially available sensors have been performed or are underway. please add to this list if you know of other comparative evaluations.

• SouthCoast AQMD
• AQICN

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech, Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

Humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

Accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

Humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

Emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

humidity and optical PM measurements

Optical monitors detect droplets and dust, and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

humidity and optical PM measurements

Optical monitors detect droplets and (dust)(/wiki/pm#Dust), and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Further information

links to EPA lit from /research/dust

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair:

A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

humidity and optical PM measurements

Optical monitors detect droplets and (dust)(/wiki/pm#Dust), and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Further information

do a review of the literature, link to EPA docs.

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

Optical PM monitoring of Particulate Matter (PM) is an attempt to measure the diameter of particles in flight. Optical monitors are a low-cost way to get real-time data about particles in the air. They are an automated, electronic version of the effect seen in a darkened room by light glinting off of dust in a sunbeam.

How optical particle sensors work

A sensor and a focused light (sometimes a laser) sit at an angle to each other. As a particle passes in front of the light, some light is reflected towards the sensor. The sensor registers a pulse for as long as the particle reflects light to the sensor. If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter.

Stepping through the process with these Illustrations by @DonBlair: A sensor and a focused light (sometimes a laser) sit at an angle to each other:

As a particle passes in front of the light, some light is reflected towards the sensor:

The sensor registers a pulse for as long as the particle reflects light to the sensor:

If the air is moving at a consistent speed, the length of this pulse can be used to estimate the particle’s diameter:

With an estimate of particle diameter and an estimate of average particle density, airborne concentrations of PM can be extrapolated. These estimates are somewhat imperfect, as accounting for particle density and the estimating and accounting for the quantity of water in droplet mode particles is not straightforward. Both of these issues complicate the process of correlating optical PM measurements to regulatory monitoring.

Correcting and correlating optical data

accounting for variable particle density

Most low-cost optical monitors assume a standard particle density based on a ‘test dust,’ such as the standard “Arizona Road Dust,” now ISO 12103-1:1997. Read more on the history of test dust in this article from Powder Technology.

Some more expensive optical monitors combine and optical monitor with a filter-based PM monitor. The filter is weighed (‘gravimetric analysis’) before and after sampling to create a calibration factor for particle density.

humidity and optical PM measurements

Optical monitors detect droplets and (dust)(/wiki/pm#Dust), and droplets are often ‘wet,’ having absorbed water in the humidity.

[illustration of ‘wet’ mode from /pm]

humidity measurements are frequently used to correct for the expected effects of humidity on droplets. These corrections are based on assumptions about the percentage of dust that is in a droplet mode and succeptable to wetting, and the percentage that is dust.

emulating PM2.5 & PM10 impactors with correction equations

PM regulatory standards are technology-based, meaning that measurements of PM10 must be related back to the results from a specific PM10 monitor. While optical monitors can set a ‘sharp’ cutoff of particles, filter-based Federal Regulatory Methods depend on the mechanical sorting of an [‘impactor’](link, which has a less sharp cutoff.

[illustration of sharpness from /pm]

The sharpness of regulatory impactors can be simulated by calculations detailed by Hinds 1999 page 255:

The average mass concentration is discrete integral of the individual particle’s contribution to mass concentration, multiplied by a curve for respirable PM10 and PM2.5.

E for PM 2.5:

PM2. 5 = [1 + exp((3.233 x projectedDiameter) - 9.495)^-3.368

Available Optical PM monitors & sensors

Further information

do a review of the literature, link to EPA docs.

Filter-calibrated Optical Monitors

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration.

Currently there are only proprietary commercial services available for reading commercial sensors, such as Netronix, which costs around $100/month.

Low cost and open source Optical Monitors

Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

Current efforts to correlate low-cost sensors with commercial reference sensors, and each other are available. AQICN’s effort appears the most comprehensive Others include: AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

Other platforms:

ManyLabs

clAIRity

Pickle Jr.

Also see:

Public Lab Development of PM Monitors

Open Pipe Kit for connecting optical monitors and setting up alerts

We are in the midst of a boom of low-cost air sensing devices, and open source particulate sensing projects have really taken off in the past year. Here we will examine four in-development projects using almost identical sensors (Shinyei PPD42NS, Syhitech DSM501A, Shinyei PPD60PV ) and a low-cost commercial competitor with a similar design, the Dylos.

I'll also lay out a plan for comparing and calibrating these sensors to each other and to commercial reference equipment. Current efforts have correlated low-cost sensors with commercial reference sensors, but never to each other. AQICN, AirBeam, Sonoma Tech Gao et al. 2015, Holstus et al 2014. Thanks to @Willie for many of those links.

Here is a little background information from the EPA on their take of some of these technologies:

How the Sensors Work

All these dust sensors are optical sensors. @DonBlair explains how optical dust sensors work:

There are issues calibrating optical sensors for not just water particles (humidity), but also for the albedo (or brightness) of the particles themselves, as Tim Dye succinctly documents. That said, the biggest differences between different devices is the way they control airflow. Passive monitors rely on convection to draw in air, while active monitors blow a controlled stream of air across the sensor’s path. Which of these strategies is best? I don't know, so I propose co-locating all of these sensors and testing them against benchmark equipment.

Airflow strategies comparison:

Passive airflow: a system that doesn't actively control for airflow, either using natural or thermal convection to drive particulates through.

Active airflow: The use of a fan or pump to control and/or meter airflow through a sensor.

Dylos DC1100

by Dylos my previous notes

The Dylos uses a small fan. A great teardown is here:

Speck

by Carnegie Mellon’s CREATELab, my previous notes.

the Speck uses a small fan:

hooked up to their open source fluxtream platform and designed for home use, it's being used by the Southwest Pennsylvania Environmental Health Project.

Airbeam

developed by the HabitatMap, it is designed to hook to an android device. It is open source hardware and uses a small fan.

Dustduino

in development by @schroyer and @willie passive airflow via a convection current, it sends data to xively

There are a few more systems using these sensors too, see “other platforms” below.

Benchmark systems

The idea is to use a single Raspberry Pi to read all the sensors in their enclosures simultaneously, along with the reference system.

Optical Benchmark

Currently there are only proprietary commercial services available for commercial sensors, such as Netronix, which costs around $100/month.

I'll connect to a TSI Dusttrak I or II or Thermo Scientific pDR 1500, as per @rjstatic's directions, updated for the Open Pipe Kit.

Filter system benchmark?

Both Dusttrak and pDR-1500 have a filter for "gravimetric analysis" (weighing the quantity of dust collected) as an additional calibration. There are extra questions about characterizing an optical sensors' response to local dust via fingerprinting the different dust particles. That may require an extra system, and I'm looking to source some low cost passive monitors as well.

[image of turtle pump + tube]

Other platforms:

ManyLabs

clAIRity

Pickle Jr.