@article{petters_pujiastuti_satheesh_kasparoglu_sutherland_meskhidze_2024, title={Wind-driven emissions of coarse-mode particles in an urban environment}, volume={24}, ISSN={["1680-7324"]}, DOI={10.5194/acp-24-745-2024}, abstractNote={Abstract. Quantifying surface–atmosphere exchange rates of particles is important for understanding the role of suspended particulate matter in radiative transfer, clouds, precipitation, and climate change. Emissions of coarse-mode particles with a diameter greater than 0.5 µm provide giant cloud condensation nuclei and ice nuclei. These emissions are critical for understanding the evolution of cloud microphysical properties yet remain poorly understood. Here we introduce a new method that uses lidar retrievals of the elastic backscatter and Doppler velocity to obtain surface number emissions of particles with a diameter greater than 0.53 µm. The technique is applied to study particle number fluxes over a 2-month period from 1 June to 10 August 2022 during the TRACER campaign at an urban site near Houston, TX, USA. We found that all the observed fluxes were positive (upwards), indicating particle emission from the surface. The fluxes followed a diurnal pattern and peaked near noon local time. Flux intensity varied through the 2 months with multi-day periods of strong fluxes and multi-day periods of weak fluxes. Emission particle number fluxes peaked near ∼ 100 cm−2 s−1. The daily averaged emission fluxes correlated with friction velocity and were anticorrelated with surface relative humidity. The emission flux can be parameterized as F= 3000 u*4, where u* is the friction velocity in m s−1 and the emission flux F is in cm−2 s−1. The u* dependence is consistent with emission from wind-driven erosion. Estimated values for the mass flux are in the lower range of literature values from non-urban sites. These results demonstrate that urban environments may play an important role in supplying coarse-mode particles to the boundary layer. We anticipate that quantification of these emissions will help constrain aerosol–cloud interaction models that use prognostic aerosol schemes.
                    }, number={1}, journal={ATMOSPHERIC CHEMISTRY AND PHYSICS}, author={Petters, Markus D. and Pujiastuti, Tyas and Satheesh, Ajmal Rasheeda and Kasparoglu, Sabin and Sutherland, Bethany and Meskhidze, Nicholas}, year={2024}, month={Jan}, pages={745–762} }
 @article{sutherland_burton_hostetler_ferrare_hair_park_oak_meskhidze_2023, title={Application of DIAL/HSRL and CATCH algorithm-based methodologies for surface PM2.5 concentrations during the KORUS-AQ campaign}, volume={301}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2023.119719}, abstractNote={Particulate matter with an aerodynamic diameter of equal to or less than 2.5 μm (PM2.5) has been found to have a serious adverse effect on human health and the environment. While the importance of measuring PM2.5 has been demonstrated, doing so remotely remains challenging. In this study, methodologies for the assessment of aerosol PM2.5 and chemical composition based on a combination of regional and global models and active remote sensing were evaluated against surface observations from the KORUS-AQ campaign. The model outputs from the Community Multiscale Air Quality (CMAQ) and GEOS-Chem were used and were available at the KORUS-AQ campaign data archive. For remote sensing, aerosol extinction and derived aerosol types available from NASA Langley Airborne Differential Absorption Lidar (DIAL)/High Spectral Resolution Lidar (HSRL) flying onboard DC-8 aircraft were used. A revised version of the algorithm, which incorporates size-specific aerosol dry mass extinction efficiencies for sulfate, nitrate, and ammonia as well as organic matter, is also presented. The PM2.5 concentration estimates were compared with measurements taken at the ground stations. The estimated mean absolute error between the ground station measurements and the remote-sensing-based methodologies was significantly lower compared to the models. The data analysis has shown that uncertainties in relative humidity values, the presence of particles larger than 2.5 μm in diameter, and the abundance of black carbon and organic matter in Asian aerosol were unlikely to explain the differences between measured and predicted surface PM2.5. Local meteorology was found to play a key role influencing the spatiotemporal variability of aerosols and the most important factor determining the agreement between the estimated and ground site-measured PM2.5. The lowest mean absolute error was found for the May 1–16 period, when aerosols were well mixed within the mixing layer and homogeneous across the temporal (1 h) and spatial (8 km) scales used in this study. Under these conditions, the methodologies presented here could give reasonable estimates of PM2.5 concentration and derived chemical composition over South Korea when HSRL data are available.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Sutherland, Bethany and Burton, Sharon and Hostetler, Chris A. and Ferrare, Richard A. and Hair, Johnathan and Park, Rokjin J. and Oak, Yujin J. and Meskhidze, Nicholas}, year={2023}, month={May} }