Fine particulate matter (PM2.5) is a leading risk factor for premature mortality. Additional attention is needed to improve global estimates of PM2.5 exposure.
Satellite remote sensing, when combined with aerosol vertical profiles from chemical transport models, has emerged as a promising solution to this need. However there are outstanding questions about the accuracy and precision with which ground-level long-term PM2.5 mass concentrations can be inferred from discontinuous aerosol optical depth (AOD) observations. Measurements of ground-level PM2.5 collocated with AOD measurements in diverse settings with different PM sources are needed to evaluate model calculations of PM2.5/AOD ratios and, in turn, improve estimates of surface PM2.5 from satellite AOD retrievals. Composition information is also needed to understand processes.
We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN; Snider et al., 2015; 2016) includes a global federation of ground-level PM2.5 monitors situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. We welcome expressions of interest to join this grass-roots network.
For more information, please see the SPARTAN website.
Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models (2017). Philip, S., R. V. Martin, G. Snider, C. Weagle, A. van Donkelaar, M. Brauer, D. Henze, Z. Klimont, C. Venkataraman, S. Guttikunda and Q. Zhang,, Environ. Res. Lett., doi:10.1088/1748-9326/aa65a4.
Variation in Global Chemical Composition of PM2.5: Emerging Results from SPARTAN. (2016) Snider, G, C. L. Weagle, K. K. Murdymootoo, A. Ring, Y. Ritchie, A. Walsh, C. Akoshile, N. X. Anh, J. Brook, F D. Qonitan, J. Dong, D. Griffith, K. He, B. N. Holben, R. Kahn, N. Lagrosas, P. Lestari, Z. Ma, A. Misra, E. J. Quel, A. Salam, B. Schichtel, L. Segev, S. N. Tripathi, C. Wang, C. Yu, Q. Zhang, Y. Zhang, M. Brauer, A. Cohen, M. D. Gibson, Y. Liu, J. V. Martins, Y. Rudich, and R. V. Martin. Atmos. Chem. Phys., 16, 9629–9653, doi:10.5194/acp-16-9629-2016.
SPARTAN: A Global Network to Evaluate and Enhance Satellite-Based Estimates of Ground-level Particulate Matter for Global Health Applications. (2015)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. Atmos. Meas. Tech., 8, 505-521, doi:10.5194/amt-8-505-2015.