Sampling stations

The Aeroexplorer system: particulate and trace gas sampling measurements

AirPhoton has developed a set of filter stations instruments for retrospective analysis of particulate matter. The Aeroexplorer sampling station comes in single and dual inlet models which allow for sequential or simultaneous collection of particulates at two size cuts between PM2.5 and PM10. In conjunction with the real-time measurements from our nephelometers, users can get a complete picture of particulates for air quality.

Additionally, the Aeroexplorer sampling station is highly customizable, accommodating a wide range of research needs. The system components, such as controllers, pumps, inlet boxes, inlet heads, and cartridges, can be configured in various ways to suit specific sampling requirements. This flexibility ensures that users can optimize their setups for accurate and comprehensive particulate matter analysis.

Recently, we have enhanced its capabilities with a new station designed specifically for trace gas measurements. This advanced instrument can measure a variety of gases, including ammonia, nitrates, and volatile organic compounds, each of which play a crucial role in air quality analysis. The instrument is composed by four denuders, which allows us to sample by wind direction. This allows for analysis of source apportionment or fence-line monitoring. This instrument operates at low flow rates which can be supported by solar or battery power so that the instrument can be deployed in remote and or environmentally sensitive areas.

The Aeroexplorer sampling station: Single Inlet System

The Aeroexplorer sampling station is a versatile instrument for collecting particulate matter on filters for later analysis. Particulates can be collected in two sizes, typically PM2.5 and PM10 on up to 8 filters on a user programmable scheduled. The instrument has data ports which can be used to communicate with external instruments such as a weather station to enable collection by wind direction or coordination with our nephelometers. The instruments permits an autonomous particle sampling. Pump turns on/off and sampling advances to next filter slot, automatically, as function of minutes, hours or days. All is directed by operator-initiated programs, input with intuitive button controls or script command uploads.

Data sheet

Inlet-box specifications

  • Box dimensions: 12.5″ x 15″ x 9″
  • Weight: 6 kg
  • Installed height: 40″ but varies per configuration
  • Control box option: SS5e, SS5e7-1
  • Holds FC10, 8-slot filter cartridge
  • Flow rate: 1.5-7 lpm, set to control particle size
  • Inlet size cut-off options: PM10, PM4, P2.5, or PM1

Control-box specifications

  • Box dimensions: 12.5″ x 18″ x 9″
  • Weight: 5.3 kg
  • Compatible options: SS5i, SS5i-PMx
  • Max flow rate: around 7 lpm standard
  • Power inputs: 110/220 VAC 50/60Hz
  • Auxiliary power input: nominal 12VDC.
  • Solar power compatible.
  • User sets sampling protocols with intuitive button commands.
  • Controls on/off pump and advance to next filter slot as function of minutes, hours or days.
  • Data stored on removable memory cards with automatic backups.

The Aeroexplorer single inlet model can provide autonomous particle sampling. The pump turns on/off and sampling advances to next filter slot, automatically, as function of minutes, hours or days. All is  directed by operator-initiated programs, input with intuitive button controls or script command uploads.

Snider, Graydon;Weagle, Crystal L.;Murdymootoo, Kalaivani K.;Ring, Amanda;Ritchie, Yvonne;Stone, Emily;Walsh, Ainsley;Akoshile, Clement;Anh, Nguyen Xuan;Balasubramanian, Rajasekhar;Brook, Jeff;Qonitan, Fatimah D.;Dong, Jinlu;Griffith, Derek;He, Kebin;Holben, Brent N.;Kahn, Ralph;Lagrosas, Nofel;Lestari, Puji;Ma, Zongwei;Misra, Amit;Norford, Leslie K.;Quel, Eduardo J.;Salam, Abdus;Schichtel, Bret;Segev, Lior;Tripathi, Sachchida;Wang, Chien;Yu, Chao;Zhang, Qiang;Zhang, Yuxuan;Brauer, Michael;Cohen, Aaron;Gibson, Mark D.;Liu, Yang;Martins, J. Vanderlei;Rudich, Yinon;Martin, Randall V.; emerging results from SPARTAN. 2016. Atmospheric Chemistry and Physics, 16(15), 9629-9653. https://doi.org/10.5194/acp-16-9629-2016

McNeill, J., Snider, G., Weagle, C.L. et al. Large global variations in measured airborne metal concentrations driven by anthropogenic sources. Sci Rep 10, 21817 (2020). https://doi.org/10.1038/s41598-020-78789-y

Bluvshtein, Nir. The Weizmann Institute of Science (Israel) ProQuest Dissertations & Theses,  2017. 28465231. https://doi.org/10.34933/wis.000157

Shuaibo Wang, Wentao Xu, Sijie Chen, Chengkang Xu, Weize Li, Chonghui Cheng, Jiesong Deng, and Dong Liu, “Synergistic monitoring of PM2.5 and CO2 based on active and passive remote sensing fusion during the 2022 Beijing Winter Olympics,” Appl. Opt. 63, 1231-1240 (2024)
https://opg.optica.org/ao/abstract.cfm?URI=ao-63-5-1231

Asfaw, A., Isaxon, C., Malmqvist, E., Hasheminassab, S., Diner, D.J. (2024). Air Quality Monitoring Assists Meeting the Sustainable Development Goals in Ethiopia. In: Fomba, K.W., Tchanche Fankam, B., Mellouki, A., Westervelt, D.M., Giordano, M.R. (eds) Advances in Air Quality Research in Africa. ICAQ-Africa 2022. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-53525-3_20

Hasheminassab, Sina ; Diner, David J. ; Asfaw, Araya ; Blair, Jeffrey ; Dillner, Ann M. ; Isaxon, Christina ; Liu, Yang search by orcid ; L’Orange, Christian ; Mamo, Tesfaye ; Martin, Randall ; Oxford, Christopher Ray ; Sarnat, Jeremy ; Walsh, Brenna. In-Situ Air Quality Monitoring in Ethiopia for the Multi-Angle Imager for Aerosols (MAIA) Investigation: Spatial and Temporal Trends in Levels and Composition of Ambient PM2.5. AGU Fall Meeting 2022, held in Chicago, IL, 12-16 December 2022, id. A42O-1908. https://ui.adsabs.harvard.edu/abs/2022AGUFM.A42O1908H/abstract

Zhu, H., Martin, R., van Donkelaar, A., Hammer, M., Li, C., Meng, J., Oxford, C., Liu, X., Li, Y., Zhang, D., Singh, I., and Lyapustin, A.: Global Spatial Variation in the PM2.5 to AOD Relationship Strongly Influenced by Aerosol Composition, EGUsphere. 2024, https://doi.org/10.5194/egusphere-2024-950

Snider, G., Weagle, C. L., Martin, R. V., van Donkelaar, A., Conrad, K., Cunningham, D., Gordon, C., Zwicker, M., Akoshile, C., Artaxo, P., Anh, N. X., Brook, J., Dong, J., Garland, R. M., Greenwald, R., Griffith, D., He, K., Holben, B. N., Kahn, R., Koren, I., Lagrosas, N., Lestari, P., Ma, Z., Vanderlei Martins, J., Quel, E. J., Rudich, Y., Salam, A., Tripathi, S. N., Yu, C., Zhang, Q., Zhang, Y., Brauer, M., Cohen, A., Gibson, M. D., and Liu, Y.: SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications, Atmos. Meas. Tech., 8, 505–521, https://doi.org/10.5194/amt-8-505-2015

Crystal L. Weagle, Graydon Snider, Chi Li, Aaron van Donkelaar, Sajeev Philip, Paul Bissonnette, Jaqueline Burke, John Jackson, Robyn Latimer, Emily Stone, Ihab Abboud, Clement Akoshile, Nguyen Xuan Anh, Jeffrey Robert Brook, Aaron Cohen, Jinlu Dong, Mark D. Gibson, Derek Griffith, Kebin B. He, Brent N. Holben, Ralph Kahn, Christoph A. Keller, Jong Sung Kim, Nofel Lagrosas, Puji Lestari, Yeo Lik Khian, Yang Liu, Eloise A. Marais, J. Vanderlei Martins, Amit Misra, Ulfi Muliane, Rizki Pratiwi, Eduardo J. Quel, Abdus Salam, Lior Segev, Sachchida N. Tripathi, Chien Wang, Qiang Zhang, Michael Brauer, Yinon Rudich, and Randall V. Martin. Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model. Environmental Science & Technology 2018 52 (20), 11670-11681. https://doi.org/10.1021/acs.est.8b01658

Cheng, J., Su, J., Cui, T., Li, X., Dong, X., Sun, F., Yang, Y., Tong, D., Zheng, Y., Li, Y., Li, J., Zhang, Q., and He, K.: Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis, Atmos. Chem. Phys., 19, 6125–6146, 2019. https://doi.org/10.5194/acp-19-6125-2019

Sajeev Philip, Randall V Martin, Graydon Snider, Crystal L Weagle, Aaron van Donkelaar, Michael Brauer, Daven K Henze, Zbigniew Klimont, Chandra Venkataraman, Sarath K Guttikunda, Qiang Zhang. Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models. Environ. Res. Lett. 12 044018. 2017. https://doi.org/10.1088/1748-9326/aa65a4

Weagle, Crystal. “Interpretation of Ground-Based Measurements from the Surface Particulate Matter Network to Understand the Global Distribution of Fine Particulate Matter.” 2020. Dalhousie University, https://dalspace.library.dal.ca//handle/10222/79617

MacInnis, J., Chaubey, J. P., Weagle, C., Atkinson, D., & Chang, R. Y.-W. (2021). Measurement report: The chemical composition of and temporal variability in aerosol particles at Tuktoyaktuk, Canada, during the Year of Polar Prediction Second Special Observing Period. Atmospheric Chemistry and Physics, 21, 14199-14220. https://doi.org/10.5194/acp-21-14199-2021

Bluvshtein, N., Lin, P., Flores, J. M., Segev, L., Mazar, Y., Tas, E., Snider, G., Weagle, C., Brown, S. S., Laskin, A., & Rudich, Y. (2016). The magnitude and sources of uncertainty in North American climate projections: A comprehensive analysis. Journal of Geophysical Research: Atmospheres, 121(19), 11481-11503. https://doi.org/10.1002/2016JD026230

Jacob A. McNeill. Chemical Analysis of Fine Particulate Matter Measured Worldwide through Global Air Sampling Network. Dalhousie University. 2021. https://dalspace.library.dal.ca/handle/10222/80442

Heald, C. L., Ridley, D. A., Kroll, J. H., Sayer, A. M., Colarco, P. R., Massie, S., … & Salam, A. (2016). Variation in global chemical composition of PM2.5: emerging results from SPARTAN. Atmospheric Chemistry and Physics Discussions, 16(13), 8351-8386. https://doi.org/10.5194/acp-16-8351-2016

The Aeroexplorer sampling station: Dual Inlet System

The Dual Inlet configuration of the sampling station allows for simultaneous collection of particles at two different sizes depending on the choice of inlet size. Shown at right is the instrument configured with two cyclone inlets. The system can also be configured to use mini-impactors for the collection of larger-sized particles. This adaptability ensures precise sampling tailored to diverse research requirements.

Data sheet

Inlet-box specifications

  • Box dimensions: 12.5″ x 15″ x 9″
  • Weight: 6 kg
  • Installed height: 40″ but varies per configuration
  • Control box option: SS5e, SS5e7-1
  • Holds FC10, 8-slot filter cartridge
  • Flow rate: 1.5-7 lpm, set to control particle size
  • Inlet size cut-off options: PM10, PM4, P2.5, or PM1

Control-box specifications

  • Box dimensions: 12.5″ x 18″ x 9″
  • Weight: 5.3 kg
  • Compatible options: SS5i, SS5i-PMx
  • Max flow rate: around 7 lpm standard
  • Power inputs: 110/220 VAC 50/60Hz
  • Auxiliary power input: nominal 12VDC.
  • Solar power compatible.
  • User sets sampling protocols with intuitive button commands.
  • Controls on/off pump and advance to next filter slot as function of minutes, hours or days.
  • Data stored on removable memory cards with automatic backups.

The Aeroexplorer dual inlet model can provide autonomous particle sampling. The pump turns on/off and sampling advances to next filter slot, automatically, as function of minutes, hours or days. All is  directed by operator-initiated programs, input with intuitive button controls or script command uploads.

Snider, Graydon;Weagle, Crystal L.;Murdymootoo, Kalaivani K.;Ring, Amanda;Ritchie, Yvonne;Stone, Emily;Walsh, Ainsley;Akoshile, Clement;Anh, Nguyen Xuan;Balasubramanian, Rajasekhar;Brook, Jeff;Qonitan, Fatimah D.;Dong, Jinlu;Griffith, Derek;He, Kebin;Holben, Brent N.;Kahn, Ralph;Lagrosas, Nofel;Lestari, Puji;Ma, Zongwei;Misra, Amit;Norford, Leslie K.;Quel, Eduardo J.;Salam, Abdus;Schichtel, Bret;Segev, Lior;Tripathi, Sachchida;Wang, Chien;Yu, Chao;Zhang, Qiang;Zhang, Yuxuan;Brauer, Michael;Cohen, Aaron;Gibson, Mark D.;Liu, Yang;Martins, J. Vanderlei;Rudich, Yinon;Martin, Randall V.; emerging results from SPARTAN. 2016. Atmospheric Chemistry and Physics, 16(15), 9629-9653. https://doi.org/10.5194/acp-16-9629-2016

McNeill, J., Snider, G., Weagle, C.L. et al. Large global variations in measured airborne metal concentrations driven by anthropogenic sources. Sci Rep 10, 21817 (2020). https://doi.org/10.1038/s41598-020-78789-y

Bluvshtein, Nir. The Weizmann Institute of Science (Israel) ProQuest Dissertations & Theses,  2017. 28465231. https://doi.org/10.34933/wis.000157

Shuaibo Wang, Wentao Xu, Sijie Chen, Chengkang Xu, Weize Li, Chonghui Cheng, Jiesong Deng, and Dong Liu, “Synergistic monitoring of PM2.5 and CO2 based on active and passive remote sensing fusion during the 2022 Beijing Winter Olympics,” Appl. Opt. 63, 1231-1240 (2024)
https://opg.optica.org/ao/abstract.cfm?URI=ao-63-5-1231

Asfaw, A., Isaxon, C., Malmqvist, E., Hasheminassab, S., Diner, D.J. (2024). Air Quality Monitoring Assists Meeting the Sustainable Development Goals in Ethiopia. In: Fomba, K.W., Tchanche Fankam, B., Mellouki, A., Westervelt, D.M., Giordano, M.R. (eds) Advances in Air Quality Research in Africa. ICAQ-Africa 2022. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-53525-3_20

Hasheminassab, Sina ; Diner, David J. ; Asfaw, Araya ; Blair, Jeffrey ; Dillner, Ann M. ; Isaxon, Christina ; Liu, Yang search by orcid ; L’Orange, Christian ; Mamo, Tesfaye ; Martin, Randall ; Oxford, Christopher Ray ; Sarnat, Jeremy ; Walsh, Brenna. In-Situ Air Quality Monitoring in Ethiopia for the Multi-Angle Imager for Aerosols (MAIA) Investigation: Spatial and Temporal Trends in Levels and Composition of Ambient PM2.5. AGU Fall Meeting 2022, held in Chicago, IL, 12-16 December 2022, id. A42O-1908. https://ui.adsabs.harvard.edu/abs/2022AGUFM.A42O1908H/abstract

Zhu, H., Martin, R., van Donkelaar, A., Hammer, M., Li, C., Meng, J., Oxford, C., Liu, X., Li, Y., Zhang, D., Singh, I., and Lyapustin, A.: Global Spatial Variation in the PM2.5 to AOD Relationship Strongly Influenced by Aerosol Composition, EGUsphere. 2024, https://doi.org/10.5194/egusphere-2024-950

Snider, G., Weagle, C. L., Martin, R. V., van Donkelaar, A., Conrad, K., Cunningham, D., Gordon, C., Zwicker, M., Akoshile, C., Artaxo, P., Anh, N. X., Brook, J., Dong, J., Garland, R. M., Greenwald, R., Griffith, D., He, K., Holben, B. N., Kahn, R., Koren, I., Lagrosas, N., Lestari, P., Ma, Z., Vanderlei Martins, J., Quel, E. J., Rudich, Y., Salam, A., Tripathi, S. N., Yu, C., Zhang, Q., Zhang, Y., Brauer, M., Cohen, A., Gibson, M. D., and Liu, Y.: SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications, Atmos. Meas. Tech., 8, 505–521, https://doi.org/10.5194/amt-8-505-2015

Crystal L. Weagle, Graydon Snider, Chi Li, Aaron van Donkelaar, Sajeev Philip, Paul Bissonnette, Jaqueline Burke, John Jackson, Robyn Latimer, Emily Stone, Ihab Abboud, Clement Akoshile, Nguyen Xuan Anh, Jeffrey Robert Brook, Aaron Cohen, Jinlu Dong, Mark D. Gibson, Derek Griffith, Kebin B. He, Brent N. Holben, Ralph Kahn, Christoph A. Keller, Jong Sung Kim, Nofel Lagrosas, Puji Lestari, Yeo Lik Khian, Yang Liu, Eloise A. Marais, J. Vanderlei Martins, Amit Misra, Ulfi Muliane, Rizki Pratiwi, Eduardo J. Quel, Abdus Salam, Lior Segev, Sachchida N. Tripathi, Chien Wang, Qiang Zhang, Michael Brauer, Yinon Rudich, and Randall V. Martin. Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model. Environmental Science & Technology 2018 52 (20), 11670-11681. https://doi.org/10.1021/acs.est.8b01658

Cheng, J., Su, J., Cui, T., Li, X., Dong, X., Sun, F., Yang, Y., Tong, D., Zheng, Y., Li, Y., Li, J., Zhang, Q., and He, K.: Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis, Atmos. Chem. Phys., 19, 6125–6146, 2019. https://doi.org/10.5194/acp-19-6125-2019

Sajeev Philip, Randall V Martin, Graydon Snider, Crystal L Weagle, Aaron van Donkelaar, Michael Brauer, Daven K Henze, Zbigniew Klimont, Chandra Venkataraman, Sarath K Guttikunda, Qiang Zhang. Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models. Environ. Res. Lett. 12 044018. 2017. https://doi.org/10.1088/1748-9326/aa65a4

Weagle, Crystal. “Interpretation of Ground-Based Measurements from the Surface Particulate Matter Network to Understand the Global Distribution of Fine Particulate Matter.” 2020. Dalhousie University, https://dalspace.library.dal.ca//handle/10222/79617

MacInnis, J., Chaubey, J. P., Weagle, C., Atkinson, D., & Chang, R. Y.-W. (2021). Measurement report: The chemical composition of and temporal variability in aerosol particles at Tuktoyaktuk, Canada, during the Year of Polar Prediction Second Special Observing Period. Atmospheric Chemistry and Physics, 21, 14199-14220. https://doi.org/10.5194/acp-21-14199-2021

Bluvshtein, N., Lin, P., Flores, J. M., Segev, L., Mazar, Y., Tas, E., Snider, G., Weagle, C., Brown, S. S., Laskin, A., & Rudich, Y. (2016). The magnitude and sources of uncertainty in North American climate projections: A comprehensive analysis. Journal of Geophysical Research: Atmospheres, 121(19), 11481-11503. https://doi.org/10.1002/2016JD026230

Jacob A. McNeill. Chemical Analysis of Fine Particulate Matter Measured Worldwide through Global Air Sampling Network. Dalhousie University. 2021. https://dalspace.library.dal.ca/handle/10222/80442

Heald, C. L., Ridley, D. A., Kroll, J. H., Sayer, A. M., Colarco, P. R., Massie, S., … & Salam, A. (2016). Variation in global chemical composition of PM2.5: emerging results from SPARTAN. Atmospheric Chemistry and Physics Discussions, 16(13), 8351-8386. https://doi.org/10.5194/acp-16-8351-2016

Programable sampling: Filter Cartridge Model FC10

The AirPhoton 8-slot filter cartridge is a unique design that holds and protects 8 particle sampling filters. This design minimizes the handling of the filters in the field and reduces the frequency of site visits by technicians. Used in conjunction with the AirPhoton Explorer Automated Filter Sampling Station, the cartridge can be deployed through 8 sampling cycles (one of which can be a blank for reference) before exchange with a fresh cartridge is necessary. Each of the 8 slots can hold either 1 filter for straightforward measurements of particles of one size, or 2 sequential filters of different pore sizes for separation of particles by size. When used with the dual inlet system and control box each inlet can be used separately for four sampling cycles. One filter location for each flow can be used as a reference blank.

Data sheet

  • Dimensions: 3″ x 6″ x 1.25″
  • Single or dual stage filtering
  • Filter Diameter: 1″
  • Weight: ~ 0.6 kg

The Filter Cartridge Model FC10 programmable capability allows flexibility when designing sampling cycles, moving collection from filter slot to filter slot or turning collection on and off at specified times.