Publications

                                                       2018                                                    

Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model

Weagle, C. L., Snider, G., Li, C., van Donkelaar, A., Philip, S., Bissonnette, P., et al. (2018). Global Sources of Fine Particulate Matter: Interpretation of PM 2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model. Environmental Science & Technology, acs.est.8b01658. https://doi.org/10.1021/acs.est.8b01658

Summary

 

A global chemical transport model (GEOS-Chem) constrained by satellite-based estimates of PM2.5 is used to interpret the globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Interpretation of these measurements yields insight into the dominant sources contributing to PM2.5 at each site. Global population-weighted PM2.5 concentrations are driven by the residential energy sector with industrial activity tailing close behind. Insight is gained into the sources and process that influence the global spatial variation in PM2.5.

                                                       2017                                                    

Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models

Philip, S., Martin, R. V., Snider, G., Weagle, C. L., van Donkelaar, A., Brauer, M., Henze, D. K., Klimont, Z., Venkataraman, C., Guttikunda, S. K. and Zhang, Q.: Environ. Res. Lett. 12 (2017) 044018 doi:https://doi.org/10.1088/1748-9326/aa65a4 [Full Text (PDF)].

Summary

 

Global measurements of the elemental composition of fine particulate matter (PM2.5) across several urban locations by the Surface PARTiculate mAtter Network (SPARTAN) reveal an enhanced fraction of anthropogenic dust compared to natural dust sources, especially over Asia. We develop a global simulation of anthropogenic fugitive, combustion, and industrial dust which, to our knowledge, is partially missing or strongly underrepresented in global models. We estimate a 2-16 μg/m3 increase in PM2.5 concentrations across East and South Asia by including anthropogenic fugitive, combustion, and industrial dust emissions. A simulation including anthropogenic fugitive, combustion, and industrial dust emissions increases the correlation from 0.06 to 0.66 of simulated fine dust in comparison with SPARTAN measurements at 13 globally dispersed locations and reduces the low bias by 10% in total fine particulate mass in comparison with global in situ observations. Global population-weighted PM2.5 increases by 2.9 μg/m3 (10%). Our assessment ascertains the urgent need of including this underrepresented fine anthropogenic dust source into global bottom-up emission inventories and global models.

Figure:  Annual mean concentration of PM2.5 total dust (top panel), natural mineral dust (middle panel), and anthropogenic fugitive dust (bottom panel) simulated with the GEOS-Chem model. Coloured concentric circles in the bottom panel denote SPARTAN-measured campaign-mean PM2.5 dust concentration (inner circle) and the coincident simulated value (outer circle).

                                                       2016                                                    

Variation in Global Chemical Composition of PM2.5: Emerging Results from SPARTAN

Snider, G., Weagle, C. L., Murdymootoo, K. K., Ring, A., Ritchie, Y., Walsh, A., Akoshile, C., Anh, N. X., Brook, J., Qonitan, F. D., Dong, J., Griffith, D., He, K., Holben, B. N., Kahn, R., Lagrosas, N., Lestari, P., Ma, Z., Misra, A., Quel, E. J., Salam, A., Schichtel, B., Segev, L., Tripathi, S. N., Wang, C., Yu, C., Zhang, Q., Zhang, Y., Brauer, M., Cohen, A., Gibson, M. D., Liu, Y., Martins, J. V., Rudich, Y., and Martin, R. V.: Atmos. Chem. Phys. 16, 9629-9653, 2016 doi:10.5194/acp-16-9629-2016, .[Full Text (PDF)].

Summary

 

We examine the chemical composition of fine particulate matter (PM2.5) collected on filters at traditionally under-sampled, globally dispersed urban locations. Several PM2.5 chemical components (e.g. ammonium sulfate, ammonium nitrate, and black carbon) vary by more than an order of magnitude between sites while water uptake values vary by a factor of two. We also observe enhanced anthropogenic dust fractions are apparent from high Zn:Al ratios.

                                                       2015                                                    

SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

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, 2015 , doi:10.5194/amt-8-505-2015 [Full Text (PDF)].

Summary

 

We have initiated a global network of ground-level monitoring stations to measure concentrations of fine aerosols in urban environments. Our findings include major ions species, total mass, and total scatter at three wavelengths. Results will be used to further evaluate and enhance satellite remote sensing estimate.

                                                       2012                                                    

SPARTAN White Paper

Summary

 

Satellite remote sensing offers a promising approach to provide PM2.5 exposure information at regional-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and columnar aerosol optical depth (AOD), sampled at specific overpass times during cloud-free conditions. We are developing 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.

The complete original network white paper is available. [PDF].

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