Profiling Dust Mass Concentration in Northwest China Using a Joint Lidar and Sun-Photometer Setting

The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (<6 km), with the average mass loading of 905 ± 635 µg m−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.

Assessing the accuracy of low-cost optical particle sensors using a physics-based approach

Low-cost sensors for measuring particulate matter (PM) offer the ability to understand human exposure to air pollution at spatiotemporal scales that have previously been impractical. However, such low-cost PM sensors tend to be poorly characterized, and their measurements of mass concentration can be subject to considerable error. Recent studies have investigated how individual factors can contribute to this error, but these studies are largely based on empirical comparisons and generally do not examine the role of multiple factors simultaneously. Here, we present a new physics-based framework and open-source software package (opcsim) for evaluating the ability of low-cost optical particle sensors (optical particle counters and nephelometers) to accurately characterize the size distribution and/or mass loading of aerosol particles. This framework, which uses Mie theory to calculate the response of a given sensor to a given particle population, is used to estimate the fractional error in mass loading for different sensor types given variations in relative humidity, aerosol optical properties, and the underlying particle size distribution. Results indicate that such error, which can be substantial, is dependent on the sensor technology (nephelometer vs. optical particle counter), the specific parameters of the individual sensor, and differences between the aerosol used to calibrate the sensor and the aerosol being measured. We conclude with a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer general recommendations for the choice of calibrant under different measurement scenarios.

Aerosol Absorption: Progress Towards Global and Regional Constraints

PURPOSE OF REVIEW

Some aerosols absorb solar radiation, altering cloud properties, atmospheric stability and circulation dynamics, and the water cycle. Here we review recent progress towards global and regional constraints on aerosol absorption from observations and modeling, considering physical properties and combined approaches crucial for understanding the total (natural and anthropogenic) influences of aerosols on the climate.

RECENT FINDINGS

We emphasize developments in black carbon absorption alteration due to coating and ageing, brown carbon characterization, dust composition, absorbing aerosol above cloud, source modeling and size distributions, and validation of high-resolution modeling against a range of observations.

SUMMARY

Both observations and modeling of total aerosol absorption, absorbing aerosol optical depths and single scattering albedo, as well as the vertical distribution of atmospheric absorption, still suffer from uncertainties and unknowns significant for climate applications. We offer a roadmap of developments needed to bring the field substantially forward.

Modeling the scattering properties of mineral aerosols using concave fractal polyhedra

The single-scattering properties of concave fractal polyhedra are investigated, with particle size parameters ranging from the Rayleigh to geometric-optics regimes. Two fractal shape parameters, irregularity and aspect ratio, are used to iteratively construct "generations" of irregular fractal particles. The pseudospectral time-domain (PSTD) method and the improved geometric-optics method (IGOM) are combined to compute the single-scattering properties of fractal particles over the range of size parameters. The effects of fractal generation, irregularity, and aspect ratio on the single-scattering properties of fractals are investigated. The extinction efficiency, absorption efficiency, and asymmetry factor, calculated by the PSTD method for fractal particles, with small-to-moderate size parameters, smoothly bridges the gap between those size parameters and size parameters for which solutions given by the IGOM may be used. Somewhat surprisingly, excellent agreement between values of the phase function of randomly oriented fractal particles calculated by the two numerical methods is found, not only for large particles, but in fact extends as far down in equivalent-projected-area size parameters as 25. The agreement in the case of other nonzero phase matrix elements is not as good at so small a size. Furthermore, the numerical results of ensemble-averaged phase matrix elements of a single fractal realization are compared with dust particle measurements, and good agreement is found by using the fractal particle model to represent data from a study of feldspar aerosols.