Estimation of cloud condensation nuclei concentration from aerosol optical quantities: influential factors and uncertainties

Large-scale measurements of cloud condensation nuclei (CCN) are difficult to obtain on a routine basis, whereas aerosol optical quantities are more readily available. This study investigates the relationship between CCN and aerosol optical quantities for some distinct aerosol types using extensive observational data collected at multiple Atmospheric Radiation Measurement (ARM) Climate Research Facility (CRF) sites around the world. The influences of relative humidity (RH), aerosol hygroscopicity (<i>f</i>_RH) and single scattering albedo (SSA) on the relationship are analyzed. Better relationships are found between aerosol optical depth (AOD) and CCN at the Southern Great Plains (US), Ganges Valley (India) and Black Forest sites (Germany) than those at the Graciosa Island (the Azores) and Niamey (Niger) sites, where sea salt and dust aerosols dominate, respectively. In general, the correlation between AOD and CCN decreases as the wavelength of the AOD measurement increases, suggesting that AOD at a shorter wavelength is a better proxy for CCN. The correlation is significantly improved if aerosol index (AI) is used together with AOD. The highest correlation exists between CCN and aerosol scattering coefficients (&sigma;_sp) and scattering AI measured in situ. The CCN–AOD (AI) relationship deteriorates with increasing RH. If RH exceeds 75%, the relationship where AOD is used as a proxy for CCN becomes invalid, whereas a tight &sigma;_sp–CCN relationship exists for dry particles. Aerosol hygroscopicity has a weak impact on the &sigma;_sp–CCN relationship. Particles with low SSA are generally associated with higher CCN concentrations, suggesting that SSA affects the relationship between CCN concentration and aerosol optical quantities. It may thus be used as a constraint to reduce uncertainties in the relationship. A significant increase in &sigma;_sp and decrease in CCN with increasing SSA is observed, leading to a significant decrease in their ratio (CCN / &sigma;_sp) with increasing SSA. Parameterized relationships are developed for estimating CCN, which account for RH, particle size, and SSA

Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging

Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing Systems Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energys Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates

Theoretical understanding of the linear relationship between convective updrafts and cloud-base height for shallow cumulus clouds. Part II: Continental conditions

This is the Part II of a two-part study that seeks a theoretical understanding of an empirical relationship for shallow cumulus clouds: subcloud updraft velocity covaries linearly with the cloud-base height. This work focuses on continental cumulus clouds that are more strongly forced by surface fluxes and more deviated from equilibrium than those over oceans (Part I). We use a simple analytical model for shallow cumulus that is well tested against a high-resolution (25 m in the horizontal) large-eddy simulation model. Consistent with a conventional idea, we find that surface Bowen ratio is the key variable that regulates the covariability of both parameters: under the same solar insolation, a drier surface allows for stronger buoyancy flux, triggering stronger convection that deepens the subcloud layer. We find that the slope of the Bowen-ratio-regulated relationship between the two parameters (defined as l) is dependent on both the local time and the stability of the lower free atmosphere. The value of l decreases with time exponentially from sunrise to early afternoon and linearly from early afternoon to sunset. The value of l is larger in a more stable atmosphere. In addition, continental l in the early afternoon more than doubles the oceanic l. Validation of the theoretical results against ground observations over the Southern Great Plains shows a reasonable agreement. Physical mechanisms underlying the findings are explained from the perspective of different time scales at which updrafts and cloud-base height respond to a surface flux forcing

Simultaneous Biohydrogen and Bioethanol Production from Anaerobic Fermentation with Immobilized Sludge

The effects of organic loading rates (OLRs) on fermentative productions of hydrogen and ethanol were investigated in a continuous stirred tank reactor (CSTR) with attached sludge using molasses as substrate. The CSTR reactor with attached sludge was operated under different OLRs, ranging from 8 to 24 kg/m3·d. The H2 and ethanol production rate essentially increased with increasing OLR. The highest H2 production rate (10.74 mmol/h·L) and ethanol production rate (11.72 mmol/h·L) were obtained both operating at OLR = 24 kg/m3·d. Linear regression results show that ethanol production rate (y) and H2 production rate (x) were proportionately correlated and can be expressed as y = 1.5365x − 5.054 (r2 = 0.9751). The best energy generation rate was 19.08 kJ/h·L, which occurred at OLR = 24 kg/m3·d. In addition, the hydrogen yield was affected by the presence of ethanol and acetic acid in the liquid phase, and the maximum hydrogen production rate occurred while the ratio of ethanol to acetic acid was close to 1

Impact of Aerosols on Convective Clouds and Precipitation

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major reason for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. The central theme of this paper is to review past efforts and summarize our current understanding of the effect of aerosols on precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations will be presented. Specifically, this paper will address the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large-scale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions on aerosol - precipitation interactions are suggested

Enlarging rainfall area of tropical cyclones by atmospheric aerosols

The size of a tropical cyclone (TC), measured by the area of either rainfall or wind, is an important indicator for the potential damage by TC. Modeling studies suggested that aerosols tend to enhance rainfall in the outer rainbands, which enlarges the eyewall radius and expands the extent of rainfall area. However, no observational evidence has yet been reported. Using TC rainfall area and aerosol optical depth (AOD) data, we find that aerosols have a distinguishable footprint in the TC size. Other dynamical factors for TC size, such as relative SST and Coriolis parameter, are also quantified and discussed. We show that, on average, TC rainfall size increases 9–20 km for each 0.1 increase of AOD in the western North Pacific. This finding implies that anthropogenic aerosol pollution can increase not only TC rainfall rate, but also TC rainfall area, resulting in potentially more destructive flooding affecting larger areas

A Novel Separated Position and Orientation System Integrated with Inertially Stabilized Platform

Considering the application requirements of independent imaging payloads design, a novel scheme of separated position and orientation system (POS) is proposed, in which the high-precision inertial sensors of traditional centralized POS fixed on the imaging payloads are mounted on three gimbals of the inertially stabilized platform (ISP), respectively, and make them integrated. Then, the kinematics model of the ISP system is built to transmit the inertial information measured by separated inertial sensors mounted on ISP gimbals and flight body to the imaging payloads, calculating the position and attitude of the imaging payloads to achieve the function of separated POS. Based on the model, a series of simulations indicate that the precision difference between separated system and centralized system is ignorable under the condition of angular motion and variable velocity motion. Besides the effective function equal to traditional centralized system, the separated POS enhances the integration with the ISP. Moreover, it improves the design independence of the imaging payloads significantly

Cooperative simultaneous inversion of satellite-based real-time PM2.5 and ozone levels using an improved deep learning model with attention mechanism

Ground-level fine particulate matter (PM2.5) and ozone (O3) are air pollutants that can pose severe health risks. Surface PM2.5 and O3 concentrations can be monitored from satellites, but most retrieval methods retrieve PM2.5 or O3 separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China spanning 2014–2021, we found a strong relationship between PM2.5 and O3 with distinct spatiotemporal characteristics. Thus, in this study, we propose a new deep learning model called the Simultaneous Ozone and PM2.5 inversion deep neural Network (SOPiNet), which allows for daily real-time monitoring and full coverage of PM2.5 and O3 simultaneously at a spatial resolution of 5 km. SOPiNet employs the multi-head attention mechanism to better capture the temporal variations in PM2.5 and O3 based on previous days’ conditions. Applying SOPiNet to MODIS data over China in 2022, using 2019–2021 to construct the network, we found that simultaneous retrievals of PM2.5 and O3 improved the performance compared with retrieving them independently: the temporal R2 increased from 0.66 to 0.72 for PM2.5, and from 0.79 to 0.82 for O3. The results suggest that near-real time satellite-based air quality monitoring can be improved by simultaneous retrieval of different but related pollutants. The codes of SOPiNet and its user guide are freely available online at https://github.com/RegiusQuant/ESIDLM