QuantAQ Cloud

MODULAIR

This page documents the QuantAQ MODULAIR air quality sensor.

KEY
VALUE

Product Name

MODULAIR

SKU(s)

MOD-XXX-NorAm

Pre-2025 version of the MODULAIR for use in North America.

MOD-XXX-Global

Pre-2025 version of the MODULAIR for use outside of North America.

Datasheet

XXX is a 3-digit number that indicates the gas sensors included in a specific sensor. The available options historically have been:

  1. 000: PM only

  2. 015: PM, CO, NO, NO2, O3

  3. 031: PM, CO, NO, NO2, O3, CO2

Only the 000 and 015 have been manufactured and sold since 2023.

1. Introduction and Specs

MODULAIR™ provides real-time estimates of particulate matter concentrations (PM1, PM2.5, PM10), the particle size distribution, and four gas-phase measurements. MODULAIR utilizes the same, patent-pending particle measurement technology found in the MODULAIR-PM, which combines nephelometry with single-particle scattering to accurately measure aerosol loadings across a variety of environments.

1.1. Specifications

1.1.1 Air Quality Measurements

PARAMETER
RANGE
ACCURACY

PM1, PM2.5, PM10

0 to 2,000 µg/m3

Please see the spec sheet.

Particle size distribution

0.35 to 40.0 µm (24 bins)

Not yet determined

Ozone (O3)

0 to 500 ppb

5 ppb or 20%

Carbon Monoxide (CO)

0 to 13,000 ppb

40 ppb or 20%

Nitrogen Oxide (NO)

0 to 5,000 ppb

5 ppb or 20%

Nitrogen Dioxide (NO2)

0 to 5,000 ppb

6 ppb or 35%

Temperature

-40º to 85º C

+/- 0.2ºC

Relative Humidity

0 to 100%

+/- 2%

For more information on the operating principle and performance of the MODULAIR, please refer to QAN-001, QAN-003, and QAN-004.

1.1.2 Power and Communications

PARAMETER
DETAILS

🔋 Power

5V, 2A (supply) 250 mA average consumption

🗼 Communication

LTE CAT-M1 (North America) LTE CAT-M1/3G/2G (Global)

📈 Data

Web interface (quant-aq.com) Programmatic access (QuantAQ API) Local storage (µSD Card)

1.1.3 Operating Specifications

PARAMETER
DETAILS

Weatherproof rating

IP68

Operating temperature

-20º to 45ºC

Operating humidity

5 to 95%, non-condensing

Dimensions

11.04" x 9.04" x 5.72"

Weight

6 lbs (2.72 kg)

1.2 Certifications

1.2.1 FCC 15(b)

The MODULAIR™ air quality sensor complies with part 15 of the FCC rules for class A devices. Operation is subject to the following two conditions: (1) this device may not cause harmful interference; (2) this device must accept any interference received, including interference that may cause undesired operation.

Model: MODULAIR

Contains FCC ID: 2AEMI-B404X

1.2.2 CE

The MODULAIR™ complies with European Union EMC Directive 2014/30/EU and conforms to the following technical standards (EN 55011, EN 61326).

Model: MODULAIR

Contains FCC ID: 2AEMI-B524

2. Installation and Hardware Setup

2.1 Unpacking

When you unpack your MODULAIR, you should have received the following:

  • MODULAIR Air Quality Sensor

  • Power supply and USB-C charging cable

  • Mounting hardware (flanges with 4, 10-32 screws)

  • 16 GB µSD card (pre-installed)

  • Device registration card

  • Sonic anemometer (if purchased)

  • Solar Power System (if purchased)

If any of these components are missing, please contact QuantAQ support via the in-app chat.

2.2.1 Device Overview

Upon opening your MODULAIR, it should appear as Figure 2.1 shows below, without the antenna attached. When attached, the antenna should be facing up to get the best service.

2.2.2 Device Front Panel

The front panel of the MODULAIR can be accessed by opening the lid of the enclosure. The panel provides access to the ON/OFF switch, the µSD card for local data logging, the internal battery status indicator (Battery Charge Status), and the device status LED (Device Status Indicator), all of which are shown in Figure 2.2.

Front Panel Screw

The front panel can be opened by unscrewing the Front Panel Screw, though should not be necessary under normal use. If it is opened, make sure that when re-closing, you do not "pop" out the µSD card. If so, you can simply push it back into place.

2.2.3 Device Base

Viewing the bottom of the MODULAIR, you can see the air intake covered by an insect-screen, the RJ11 jack for connecting the optional sonic anemometer, and the USB-C power in.

2.2.4 Device Circuit Board

The device circuit board is located under the front panel (Figure 2.2). To access, un-screw the Front Panel Screw and you will see the Core Board toward the lower left, as shown in Figure 2.4. The micro-USB cable is used exclusively for streaming logs directly from the device. While it does output some data, it is not designed to be used to connect to a data logger (this behavior is not supported). When used to collect logs, the MODULAIR must still be powered by the normal Power In USB-C connector shown in Figure 2.3.

2.3 Connections and Device Registration

The MODULAIR is shipped completely assembled, aside from the mounting hardware. Once the device is mounted and you have verified the power switch is in the OFF position, plug in the power supply and connect the USB-C cable to the bottom of the device. Once the power cable is connected, flip the power switch to the ON position. Upon receiving power, the Device Status LED (Figure 2.2) will flash green and eventually begin a sequence of slowly breathing cyan; this indicates the cellular connection is active and a session with the cloud server has begun.

If the device is being powered on in a new location or has been powered off for an extended period of time, this may take some time to complete.

The device will log data locally during the period where it is searching for cellular service and push the data to the server once a connection is established. If the LED indicator does not eventually begin breathing cyan, this indicates a cloud connectivity problem. Common errors and next steps can be found in Section 6.2.

To register your device, scan the QR code on the device registration card you received with your device. It is easiest to complete this step using a cellphone or tablet with a working internet connection. A laptop with a functioning camera will also work, though may be more difficult. It is also suggested that you first log in to the website (quant-aq.com) on the device you will use to complete this process. To register your device:

  1. Use your camera to scan the QR code. This will open a tab in your default browser and will direct you to the device registration page.

  2. Enter the fields for the information that the form asks for and click "Continue"

  3. Enter the claim code found on the same QR code card → it should be a 6-character alphanumeric code.

  4. Follow the instructions on the form and enter in data for the device location and other meta data. All of these can be changed in the future through the dashboard, so don't worry if you can't answer all questions at this time.

2.4 Installation

The MODULAIR can be mounted in several ways depending on your exact use and available mounting options available to you. The device is shipped with mounting flanges which can be used to easily mount the device to several surfaces. Each flange is secured to the back of the device with two 1/4-20 x 0.5" stainless steel screws (included). Each flange includes three slots with the following dimensions:

Common installation approaches include:

  • using high-strength zip ties to secure the device to a fence or post (not recommended)

  • using screws to mount the device to a wall using the provided flanges

  • Using u-bolts or similar to attach to a fence post, fence, or rail

  • Purchase a pole mount kit from Polycase (the box supplier). Polycase part number PK-087.

The complete box dimensions are:

11.04" x 9.04" x 5.72" (280.42 x 229.62 x 145.29 mm)

3. Software Setup and Data

3.1 Data Structure and Outputs

There are three primary ways in which data can be accessed for the MODULAIR:

  1. Raw data is stored locally on the µSD card

  2. Data can be downloaded from the QuantAQ Cloud Console

  3. Data can be downloaded from the QuantAQ API

The data formats are slightly different depending on which method you’ve used to access the data, each of which is documented below.

3.1.1 Data Stored Locally on the µSD Card

Data is collected and saved to an onboard µSD card every five seconds; each minute, these values are averaged and pushed to the cloud where they are available on the QuantAQ Cloud. It is unlikely you will ever need to use the locally saved data; however, you are more than welcome to use it if you would like. This section covers the locally stored data and how to understand it. When removing the µSD card to pull the data, make sure your device is turned OFF.

On the µSD card, you will find data files (with a prefix of DATA_YYYYMMDD.csv) and log files which are located in the logs directory. Log files contain debugging information about the onboard sensors and the cellular communication module. It is unlikely these logs will be useful to most users, though they are available to you if you would like to use them. It is highly recommended that you use the QuantAQ CLI (discussed below) to analyze them, as it will vastly reduce the amount of time needed.

Data files are written each day and can be read or analyzed using any programming language or spreadsheet program (e.g., Microsoft Excel). Each file begins with three meta-data rows describing the device model (row 1), device ID (row 2), and device serial number (row 3). See Figure 3.1A below. If you are automating your data analysis, you can skip these three rows. The fourth row contains the header information with the names of all columns. The remaining rows contain the data, where each row corresponds to a new 5-second sampling interval. The table below summarizes the columns.

The data outputs will change depending on the SKU (or model) of your MODULAIR. Most columns are constant except for the gas-phase columns.

COLUMN
SKU
UNIT
DESCRIPTION

timestamp_iso

all

The sample timestamp in ISO format

sku

all

The device SKU number

fw

all

The current firmware version

flag

all

The status flag corresponding to this data row

sample_temp

all

°C

The sample temperature

sample_rh

all

%

The sample relative humidity

bin0

all

p/cm3

Number of particles per cubic cm in bin0 (0.35 - 0.46 µm)

bin1

all

p/cm3

Number of particles per cubic cm in bin1 (0.46 - 0.66 µm)

bin2

all

p/cm3

Number of particles per cubic cm in bin2 (0.66 - 1.0 µm)

bin3

all

p/cm3

Number of particles per cubic cm in bin3 (1.0 - 1.3 µm)

bin4

all

p/cm3

Number of particles per cubic cm in bin4 (1.3 - 1.7 µm)

bin5

all

p/cm3

Number of particles per cubic cm in bin5 (1.7 - 2.3 µm)

bin6

all

p/cm3

Number of particles per cubic cm in bin6 (2.3 - 3.0 µm)

bin7

all

p/cm3

Number of particles per cubic cm in bin7 (3.0 - 4.0 µm)

bin8

all

p/cm3

Number of particles per cubic cm in bin8 (4.0 - 5.2 µm)

bin9

all

p/cm3

Number of particles per cubic cm in bin9 (5.2 - 6.5 µm)

bin10

all

p/cm3

Number of particles per cubic cm in bin10 (6.5 - 8.0 µm)

bin11

all

p/cm3

Number of particles per cubic cm in bin11 (8.0 - 10.0 µm)

bin12

all

p/cm3

Number of particles per cubic cm in bin12 (10.0 - 12.0 µm)

bin13

all

p/cm3

Number of particles per cubic cm in bin13 (12.0 - 14.0 µm)

bin14

all

p/cm3

Number of particles per cubic cm in bin14 (14.0 - 16.0 µm)

bin15

all

p/cm3

Number of particles per cubic cm in bin15 (16.0 - 18.0 µm)

bin16

all

p/cm3

Number of particles per cubic cm in bin16 (18.0 - 20.0 µm)

bin17

all

p/cm3

Number of particles per cubic cm in bin17 (20.0 - 22.0 µm)

bin18

all

p/cm3

Number of particles per cubic cm in bin18 (22.0 - 25.0 µm)

bin19

all

p/cm3

Number of particles per cubic cm in bin19 (25.0 - 28.0 µm)

bin20

all

p/cm3

Number of particles per cubic cm in bin20 (28.0 - 31.0 µm)

bin21

all

p/cm3

Number of particles per cubic cm in bin21 (31.0 - 34.0 µm)

bin22

all

p/cm3

Number of particles per cubic cm in bin22 (34.0 - 37.0 µm)

bin23

all

p/cm3

Number of particles per cubic cm in bin23 (37.0 - 40.0 µm)

bin1MToF

all

ml/s

Time of flight for particles in bin1

bin3MToF

all

ml/s

Time of flight for particles in bin3

bin5MToF

all

ml/s

Time of flight for particles in bin5

bin7MToF

all

ml/s

Time of flight for particles in bin7

sample_period

all

s

The sample period in seconds.

sample_flow

all

ml/s

The OPC sample flow rate.

opc_temp

all

°C

The internal temperature of the OPC

opc_rh

all

%

The internal relative humidity of the OPC

opc_pm1

all

µg/m3

The factory computed value for PM1 from the OPC

opc_pm25

all

µg/m3

The factory computed value for PM2.5 from the OPC

opc_pm10

all

µg/m3

The factory computed value for PM10 from the OPC

laser_status

all

The status of the OPC laser.

pm1_std

all

µg/m3

The factory computed value for PM1 from the Nephelometer

pm25_std

all

µg/m3

The factory computed value for PM2.5 from the Nephelometer

pm10_std

all

µg/m3

The factory computed value for PM10 from the Nephelometer

pm1_env

all

µg/m3

The factory computed value for PM1 from the Nephelometer

pm25_env

all

µg/m3

The factory computed value for PM2.5 from the Nephelometer

pm10_env

all

µg/m3

The factory computed value for PM10 from the Nephelometer

neph_bin0

all

p

Number of particles in bin0 for the nephelometer

neph_bin1

all

p

Number of particles in bin1 for the nephelometer

neph_bin2

all

p

Number of particles in bin2 for the nephelometer

neph_bin3

all

p

Number of particles in bin3 for the nephelometer

neph_bin4

all

p

Number of particles in bin4 for the nephelometer

neph_bin5

all

p

Number of particles in bin5 for the nephelometer

ws

all

mph

The wind speed from the sonic anemometer.

wd

all

deg

The wind direction from the sonic anemometer.

co_we

015, 031, 033

mV

The working electrode signal for the CO sensor.

co_ae

015, 031, 033

mV

The auxiliary electrode signal for the CO sensor.

no_we

015, 031

mV

The working electrode signal for the NO sensor.

no_ae

015, 031

mV

The auxiliary electrode signal for the NO sensor.

so2_we

033

mV

The working electrode signal for the SO2 sensor.

so2_ae

033

mV

The auxiliary electrode signal for the SO2 sensor.

no2_we

015, 031

mV

The working electrode signal for the NO2 sensor.

no2_ae

015, 031

mV

The auxiliary electrode signal for the NO2 sensor.

ox_we

015, 031

mV

The working electrode signal for the OX sensor.

ox_ae

015, 031

mV

The auxiliary electrode signal for the OX sensor.

co2_raw

031

mV

The raw signal for the CO2 sensor.

3.1.2 Data Downloaded from the QuantAQ Cloud Console

Data are pushed to the QuantAQ Cloud with 1-minute time resolution and can be downloaded via the QuantAQ Cloud Console. When downloading data, you can select whether you would like to download the raw data, the final data, or both the raw+final data. Generally, the final data is what is desired, as it contains the final, cleaned data that is ready for analysis. The raw data is well-suited for researchers trying to investigate specific questions. When downloaded, the data is exported as a csv and contains the following columns:

COLUMN
FILE LOCATION
UNITS
DESCRIPTION

timestamp

rawfinal

The sample timestamp in ISO format

id

rawfinal

A unique id the corresponds to the record shown

timestamp_local

rawfinal

The sample timestamp in ISO format, corrected for the timezone as defined in the device settings

sn

rawfinal

The device serial number

rh

rawfinal

%

The sample relative humidity

temp

rawfinal

°C

The sample temperature

bin0

raw

p/cm3

Number of particles per cubic cm in bin0 (0.35 - 0.46 µm)

bin1

raw

p/cm3

Number of particles per cubic cm in bin1 (0.46 - 0.66 µm)

bin2

raw

p/cm3

Number of particles per cubic cm in bin2 (0.66 - 1.0 µm)

bin3

raw

p/cm3

Number of particles per cubic cm in bin3 (1.0 - 1.3 µm)

bin4

raw

p/cm3

Number of particles per cubic cm in bin4 (1.3 - 1.7 µm)

bin5

raw

p/cm3

Number of particles per cubic cm in bin5 (1.7 - 2.3 µm)

bin6

raw

p/cm3

Number of particles per cubic cm in bin6 (2.3 - 3.0 µm)

bin7

raw

p/cm3

Number of particles per cubic cm in bin7 (3.0 - 4.0 µm)

bin8

raw

p/cm3

Number of particles per cubic cm in bin8 (4.0 - 5.2 µm)

bin9

raw

p/cm3

Number of particles per cubic cm in bin9 (5.2 - 6.5 µm)

bin10

raw

p/cm3

Number of particles per cubic cm in bin10 (6.5 - 8.0 µm)

bin11

raw

p/cm3

Number of particles per cubic cm in bin11 (8.0 - 10.0 µm)

bin12

raw

p/cm3

Number of particles per cubic cm in bin12 (10.0 - 12.0 µm)

bin13

raw

p/cm3

Number of particles per cubic cm in bin13 (12.0 - 14.0 µm)

bin14

raw

p/cm3

Number of particles per cubic cm in bin14 (14.0 - 16.0 µm)

bin15

raw

p/cm3

Number of particles per cubic cm in bin15 (16.0 - 18.0 µm)

bin16

raw

p/cm3

Number of particles per cubic cm in bin16 (18.0 - 20.0 µm)

bin17

raw

p/cm3

Number of particles per cubic cm in bin17 (20.0 - 22.0 µm)

bin18

raw

p/cm3

Number of particles per cubic cm in bin18 (22.0 - 25.0 µm)

bin19

raw

p/cm3

Number of particles per cubic cm in bin19 (25.0 - 28.0 µm)

bin20

raw

p/cm3

Number of particles per cubic cm in bin20 (28.0 - 31.0 µm)

bin21

raw

p/cm3

Number of particles per cubic cm in bin21 (31.0 - 34.0 µm)

bin22

raw

p/cm3

Number of particles per cubic cm in bin22 (34.0 - 37.0 µm)

bin23

raw

p/cm3

Number of particles per cubic cm in bin23 (37.0 - 40.0 µm)

opcn3_pm1

raw

µg/m3

Factory computed value of PM1 from the OPC

opcn3_pm25

raw

µg/m3

Factory computed value of PM2.5 from the OPC

opcn3_pm10

raw

µg/m3

Factory computed value of PM10 from the OPC

pm1_env

raw

µg/m3

Factory computed value of PM1 from the nephelometer

pm25_env

raw

µg/m3

Factory computed value of PM2.5 from the nephelometer

pm10_env

raw

µg/m3

Factory computed value of PM10 from the nephelometer

neph_bin0

raw

p

The number of particles in bin0 from the nephelometer

wd

rawfinal

deg

Wind direction from the sonic anemometer

ws

rawfinal

mph

Wind speed from the sonic anemometer

co_we

raw

mV

The working electrode signal for the CO sensor.

co_ae

raw

mV

The auxiliary electrode signal for the CO sensor.

no_we

raw

mV

The working electrode signal for the NO sensor.

no_ae

raw

mV

The auxiliary electrode signal for the NO sensor.

no2_we

raw

mV

The working electrode signal for the NO2 sensor.

no2_ae

raw

mV

The auxiliary electrode signal for the NO2 sensor.

o3_we

raw

mV

The working electrode signal for the O3 sensor.

o3_ae

raw

mV

The auxiliary electrode signal for the O3 sensor.

co2_raw

raw

mV

The raw CO2 signal

co_diff

raw

mV

The difference between co_we and co_ae

no_diff

raw

mV

The difference between no_we and no_ae

no2_diff

raw

mV

The difference between no2_we and no2_ae

ox_diff

raw

mV

The difference between o3_we and o3_ae

flag

raw

The status flag corresponding to this record

lat

rawfinal

deg

The latitude of the device

lon

rawfinal

deg

The longitude of the device

device_state

rawfinal

The current state of the device

pm1

final

µg/m3

The PM1 value

pm25

final

µg/m3

The PM2.5 value

pm10

final

µg/m3

The PM10 value

co

final

ppb

The CO concentration

no

final

ppb

The NO concentration

no2

final

ppb

The NO2 concentration

o3

final

ppb

The O3 concentration

co2

final

ppm

The CO2 concentration

pm1_model_id

final

The id corresponding to the model used to compute PM1

pm25_model_id

final

The id corresponding to the model used to compute PM2.5

pm10_model_id

final

The id corresponding to the model used to compute PM10

co_model_id

final

The id corresponding to the model used to compute CO

no_model_id

final

The id corresponding to the model used to compute NO

no2_model_id

final

The id corresponding to the model used to compute NO2

o3_model_id

final

The id corresponding to the model used to compute O3

co2_model_id

final

The id corresponding to the model used to compute CO2

3.1.3 Data Downloaded via the QuantAQ API

Data are available via the QuantAQ API at a 1-minute recording interval → the data available are the same as those available via the QuantAQ Cloud Console discussed above. The API is designed to allow engineers to build applications and map layers powered by the QuantAQ platform; however, it can also be a good way to automate data downloads, especially for large teams or lengthy download intervals. The data format is slightly different, as outlined below.

Each API call will return a paginated list of json objects with two keys: data and metaand will look something like the following:

"meta": {
    "first_url": "https://api.quant-aq.com/device-api/v1/devices/MOD-00001/data/?page=1&per_page=50&limit=3",
    "last_url": "https://api.quant-aq.com/device-api/v1/devices/MOD-00001/data/?page=1&per_page=50&limit=3",
    "next_url": null,
    "page": 1,
    "pages": 1,
    "per_page": 50,
    "prev_url": null,
    "total": 3
  }

The key definitions can be described as:

first_url: The unique url for the first page of data in the query

last_url: The unique url for the last page of data in the query

next_url: The unique url for the next page of data in the query

prev_url: The unique url for the previous page of data in the query

page: The current page number

pages: The total number of pages available for the query

per_page: The number of data objects per page

total: The total number of data objects in the query

The data object contains a list of all individual data objects for that page of data. You can query either the raw or the final data, both of which have different data values available. The final endpoint will return the following and will be different depending on the product SKU:

"data": [
    {
      "co": 132.63,
      "geo": {
        "lat": 19.451,
        "lon": -155.879
      },
      "met": {
        "rh": 69.6,
        "temp": 20,
        "wd": 15.1,
        "ws": 5.25
      },
      "model": {
        "gas": {},
        "pm": {
          "pm1": 4692,
          "pm10": 4694,
          "pm25": 4693
        }
      },
      "pm1": 0.53,
      "pm10": 24.59,
      "pm25": 3.64,
      "rh": 69.6,
      "sn": "MOD-00001",
      "so2": 6.35,
      "temp": 20,
      "timestamp": "2022-12-20T17:54:57",
      "timestamp_local": "2022-12-20T07:54:57",
      "url": "https://api.quant-aq.com/device-api/v1/devices/MOD-00001/data/23523900",
      "wd": 15.1,
      "ws": 5.25
    },
		{...},
		{...},
]

It contains several objects including the geo, met, and model objects. The descriptions of the individual data points are mapped to their respective columns in Section 3.1.2 above.

Note: If nothing appears in the right-hand column, the variable definition/name is the same

geo.lat

lat

geo.lon

lon

met.wd

wd

met.ws

ws

met.rh

rh

met.temp

temp

model.pm.pm1

pm1_model_id

model.pm.pm25

pm25_model_id

model.pm.pm10

pm10_model_id

pm1

pm25

pm10

co, no, no2, o3, so2, co2

Pending SKU, you may have one or more of these columns

sn

timestamp

timestamp_local

url

The unique url for this data point.

3.2 Understanding the Status Flag

Each row of data contains a single-byte data flag that describes the current state of the device. Flags are stored as unsigned integers and contain encoded information about each of the sensors on board. They are generated via a bitmask and can be decoded by reversing the procedure. To determine whether a specific flag is set, you can use the bitwise AND operation. If the flag's value is returned, then it is set. If a zero is returned, it is not set. This can seem complicated, so let's clear it up with a simple example.

Let's assume the value of the flag column is set to 4. We can perform a bitwise AND operation to check the result to see if FLAG_STARTUP was set (it wasn't). Below, we will check to see if the flag for the nephelometer is set (it is!).

# bit AND - is FLAG_STARTUP set?
>>> 4 & 1
0

# bit AND - is FLAG_NEPH set?
>>> 4 & 4
4

The following table describes the flags, their value, and what they mean.

The following table describes the flags, their value, and what they mean.

FLAG
VALUE
WHY IS IT SET?
WHAT TO DO?

FLAG_STARTUP

1

This flag is set when the device powers on.

Remove any rows where this flag is set.

FLAG_OPC

2

This flag is set when the OPC has indicated the data failed to transfer correctly. This can be caused by the fan being off, the laser being off, or the checksum not validating properly.

Remove any rows where this flag is set.

FLAG_NEPH

4

This flag is set when the nephelometer has indicated the data failed to transfer correctly.

Remove any rows where this flag is set.

FLAG_RHTP

8

This flag is set when the relative humidity and temperature sensor has failed.

Remove any rows where this flag is set.

FLAG_CO

16

This flag is set when the CO sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_NO

32

This flag is set when the NO sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_NO2

64

This flag is set when the NO2 sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_O3

128

This flag is set when the O3 sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_CO2

256

This flag is set when the CO2 sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_SO2

512

This flag is set when the SO2 sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_H2S

1024

This flag is set when the H2S sensor has failed or data does not meet initial on-board QA/QC.

Remove any rows where this flag is set.

FLAG_BAT

2048

This flag is set when the internal LiPo battery is low or dead.

None.

FLAG_OVERHEAT

4096

This flag is set when the OPC has overheated.

Contact QuantAQ.

FLAG_SD

8192

This flag is set when the SD card has failed.

Replace the SD card.

3.3 Leveraging QuantAQ's Software Tools

To make data analysis easier, QuantAQ maintains several software programs designed to reduce the time you spend munging and cleaning your data. The most relevant piece of software is going to be the QuantAQ CLI (command line interface). The CLI can be used to easily concatenate files, merge files together, and de-code the flag and NaN bad data. It is quite simple to go from a large folder full of files to a clean, munged data file in less than a few commands. Full documentation and use cases can be found on the QuantAQ CLI website.

4. Maintenance and Service

There are no consumable or user-replaceable components to the MODULAIR-PM. If you believe a component is broken or not functioning correctly, please contact support via the in-app chat.

4.1 Reporting Issues

As a new product, issues will likely arise with the hardware, firmware, software, or all three! We do our best to prevent issues from arising and will be timely in fixing any that do arise. If you experience an issue or have a suggestion related to the MODULAIR hardware, please check the knowledge base. If you do not find the answer you're looking for in the knowledge base, you can open a ticket via the in-app chat.

5. Changelog

5.1 Hardware Changes

DATE
VERSION
CHANGES

October 2021

0.1.0

First production release. No changes at this time.

5.2 Firmware Changes

Please see our public changelog for a full history of all firmware support changes.

6. Appendix

6.1 Wiring Diagrams

Coming soon!

6.2 LED Indicator Status and Meaning

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