Aerosol Model Research Articles

Bayesian predictive modeling of indoor ultrafine particles to enhance mid-cost monitoring

Monitoring airborne nanoparticles has a vital role in indoor air quality control due to their hazardous effects on human health. Detecting particles becomes more challenging as their sizes decrease. While research-grade instruments like the scanning mobility particle sizer (SMPS) can provide detailed and useful information, they are not practical for personal use due to their size and cost. This study aims to provide a comparable prediction of the temporal size distribution of ultrafine particles (UFPs, <100nm) using mid-cost measurements from a handheld particle sizer, which is more economical but has a narrower detectable size range. To achieve this, the study builds upon a computational modeling approach based on a mass-balance equation to estimate the time-varying particle size distribution, while accounting for particle evolution processes such as coagulation, deposition, and ventilation. The analytical model for indoor UFPs requires prior information regarding particle dynamic behavior, such as the size-resolved deposition rate and source emission rate. This study estimates, rather than pre-determines, the model parameters required for the temporal prediction of indoor UFP size distribution by applying Bayesian parameter inference with the analytical model of indoor aerosol. The results indicate that the present model reasonably predicts the temporal evolution of particle distributions, comparable to that of the SMPS. Furthermore, this study demonstrates the identifiability of model parameters, considering both the entire and detectable size ranges, through variance-based global sensitivity analysis.

Balloon Baseline Stratospheric Aerosol Profiles (B2SAP)—Perturbations in the Southern Hemisphere, 2019–2022

AbstractVolcanic and pyrocumulonimbus (pyroCB) injections into the stratosphere perturb the aerosol layer and can have important radiative and chemical impacts on timescales spanning from months to several years. Repeated in situ balloon‐borne measurements of aerosol size and number concentration (&gt;140 nm in diameter), ozone, water vapor, and atmospheric state variables made at midlatitudes in the southern hemisphere (SH) since 2019 enable us to better characterize such events. We use this record and coincident lidar extinction profiles to study several moderate to large stratospheric perturbations in the SH between 2019 and 2022 in detail, including the Australian New Year Super Outbreak (ANYSO) pyroCB in 2020. Median vertical profiles of aerosol number concentration, effective radius, and surface area in SH midlatitudes are also compared with those recorded in Northern Hemisphere midlatitudes under baseline conditions using an identical payload. These data depict the variability in stratospheric aerosol properties in the SH midlatitudes during this period and provide a benchmark for global sectional aerosol models. They reveal that sulfate particle size distributions under baseline conditions and in volcanic plumes are relatively well represented in the Community Earth System Model—Community Aerosol Radiation Model for Atmospheres (CESM‐CARMA), but more observations of biomass burning plumes are needed to improve model skill in simulating pyroCB. Comparisons between in situ and lidar observations also highlight a need for more observations of aerosol composition and refractive index in both fresh and aging biomass burning plumes.

Enhancing Fine Aerosol Simulations in the Remote Atmosphere with Machine Learning

Global aerosol models often underestimate the mass concentration of aerosols in the remote troposphere, as evidenced by aircraft measurements. This study leveraged data from the NASA Atmospheric Tomography Mission (ATom), which provides remote aerosol concentrations, to refine algorithms for simulating these concentrations. Using the GEOS-Chem model, we simulate five fine aerosol types and enhance the simulation results using five machine-learning algorithms: Random Forest, XGBoost, SVM, KNN, and LightGBM, and compare the performance of these algorithms. Additionally, we evaluate the refinement effect of algorithms based on decision trees on a validation dataset. The results demonstrate that GEOS-Chem generally underestimated aerosol mass concentration. Among the tested algorithms, algorithms based on decision trees, particularly the Random Forest algorithm and the LightGBM algorithm, exhibited a superior performance, significantly improving prediction accuracy and computational efficiency in both the training and testing phases, as well as on the validation dataset.

An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation

Abstract. Aerosols constitute important substance components of the Earth's atmosphere and have a profound influence on climate dynamics, radiative properties, and biogeochemical processes. Here we introduce updated emission schemes for dust, sea-salt, and marine primary organic aerosols (MPOA), as well as augmented secondary organic aerosol (SOA) formation pathways within the Community Earth System Model (CESM; version 2.1.3). The modified dust emission scheme shifts the original hotspot-like dust emission to a more continuous distribution, improving the dust aerosol optical depth (DAOD) simulations at stations in north Africa and central Asia. This update also reduces dust residence time from 4.1 to 1.6 d, enhancing concentration simulations downwind of dust source regions. For sea-salt emissions, we incorporate an updated sea surface temperature (SST) modulation and introduce a relative-humidity-dependent correction factor for sea-salt particle size, with SST having a significantly larger impact on sea-salt emissions (16.1 %) compared to the minor effect of humidity (−0.3 %). We then extend our modelling to incorporate emissions of marine primary organic aerosols (MPOA) as mixed externally with sea-salt aerosols, coupled offline with the ocean component Parallel Ocean Program (POP2). The results underscore the substantial influence of phytoplankton diversity on MPOA emissions, with 148 % variability simulated among different phytoplankton types, highlighting the role of biological variability in aerosol modelling. Furthermore, we refine the model's chemical mechanisms by including the irreversible aqueous uptake of dicarbonyl compounds as a new pathway for SOA formation, contributing an additional 37 % to surface SOA concentrations. These improvements enrich the ability of the CESM to use intricate linkages between different components of the Earth system, thereby enabling a more comprehensive description of natural aerosol emissions, chemical processes, and their impacts.

Characterization of a Mycoplasma hyopneumoniae aerosol infection model in pigs

The purpose of the present study was to develop and characterize an experimental aerosol model for Mycoplasma hyopneumoniae (M. hyopneumoniae) infection and respiratory disease in pigs. The experiment was carried out to determine the pathogenicity, colonization, mucosal immune response, and clinical course of disease of dose-controlled aerosols of M. hyopneumoniae. Four groups of three M. hyopneumoniae-free gilts each were individually exposed to aerosols of diluted lung homogenate containing M. hyopneumoniae strain 232 in a chamber. Each group was exposed to different doses of viable organisms (105 to 106 color changing units/mL during 15-20 or 30-35min in two consecutive days). Nasal, laryngeal, and deep-tracheal secretions were collected from each gilt at 0, 7, 14, 21, and 28 days post-exposure (dpe). Blood samples were collected at 0 and 28 dpe. At necropsy, lung lesions were assessed, and bronchial secretions and bronchoalveolar lavage fluid (BALF) were collected from each lung set. Blood was used to assess seroconversion by means of an indirect ELISA, while BALF, deep-tracheal and nasal secretions were tested by modifying the ELISA to evaluate mucosal IgG and IgA production. Nasal, laryngeal, deep-tracheal, and bronchial secretions were tested by real-time PCR to evaluate bacterial load. Gilts became infected irrespective of the infectious dose, as determined by M. hyopneumoniae detection in deep-tracheal secretions from all gilts at 7 dpe. A specific local humoral immune response starting at 14 dpe was detected in all gilts. While all experimental groups presented gilts with some extent of mycoplasmal pneumonia, only the exposure of gilts to high-dose aerosols consistently reproduced typical clinical signs and severe lung lesions. These results showed that the reproduction of mycoplasmal pneumonia by means of infectious aerosols can be successfully achieved at experimental level, making this model a valuable alternative to evaluate preventive and treatment measures against M. hyopneumoniae.

Determination of optimal solar-viewing geometry for in-flight polarization calibration using sun glint over ocean

The sun glint has been proven to be a valuable natural polarization calibration target because it is strongly polarized, and its polarization characteristics can be accurately simulated with models. It is convenient to calibrate the satellite’s in-flight polarimetry by comparing the polarization simulations with actual measurements. Meanwhile, the accuracy of polarization simulation at the top of the atmosphere (TOA) over sun glint is affected by several atmospheric and oceanic surface factors and depends on the specific solar-viewing geometry. In this paper, the sensitivity of the degree of linear polarization (DOLP) at the TOA to the uncertainties of the aerosol optical depth, aerosol model, absorption gas content (CWV, O3), sea surface instantaneous wind speed (WS), and chlorophyll concentration (Chl) under different solar-viewing geometries is analyzed via radiative transfer simulation. The error budgets indicate that aerosols and WS are the main error factors for polarization calibration, while the uncertainties of Chl and absorbing gases can be disregarded. The total DOLP error increases with the solar zenith angle and viewing zenith angle (i.e., the increase of atmospheric optical path) and the sun glint angle (SGA, the angle between the viewing and the specular directions of the sun) (i.e., the decrease of sun glint brightness). The dependence of the total DOLP error on SGA decreases with the WS (i.e., the increase of sun glint spot area and the decrease of the sun glint intensity) and increases with the wavelength (i.e., the decrease of atmospheric scattering contribution). Based on the error budgets, an optimized solar-viewing geometry screening strategy is proposed to ensure that the simulated DOLP error is limited to 0.02. The in-flight DOLP calibration result of POLDER/PARASOL shows that the proposed screening strategy obtained more calibration samples and covered a wider range of DOLP, especially for the samples with DOLP of less than 0.2, compared with the screening strategies of Toubbe et al. [IEEE Trans. Geosci. Remote Sens. 37, 513 (1999)IGRSD20196-289210.1109/36.739104]and Hagolle et al. [IEEE Trans. Geosci. Remote Sens. 42, 1472 (2004)IGRSD20196-289210.1109/TGRS.2004.826805] in previous work. The smaller standard error (SE) of the samples indicates more stable calibration results obtained for the optimized strategy. This research presents an optimized strategy for screening the solar-viewing geometry of the samples to calibrate satellite in-flight polarization measurements using the sun glint.

Can satellite products monitor solar brightening in Europe?

Satellite products provide the best way to monitor the solar radiation reaching the Earth’s surface on a global scale. However, their capability to monitor solar radiation trends needs to be constantly evaluated. This depends on their temporal stability and the accurate representation of all processes driving solar radiation. This study evaluates these aspects by comparing and cross-comparing different solar radiation products (ERA5, CAMS-RAD 4.6, SARAH-3, CLARA-A3, CERES-EBAF 4.2) against in-situ measurements over Europe.All products show a moderate positive bias over Europe but strong differences in their root mean squared deviation (RMSD) related to their different cloud transmittance models. Geostationary-based products (SARAH-3, CAMS-RAD 4.6) provide the smallest RMSD closely followed by CLARA-A3, whereas ERA5 shows a large RMSD due to random errors in cloud transmittance.All products show an increase in surface solar radiation, or brightening, over the last 40 years over Europe, but the magnitude of the trends and their spatiotemporal variability differ between products. Despite finding temporal inhomogeneities in some products, the different trends are mostly due to different aerosol modeling approaches implemented by each product. Both SARAH-3 (+2.3 W/m2/decade, 2001–22) and CERES-EBAF 4.2 (+2.2 W/m2/decade, 2001–22) provide the most consistent trends compared to in-situ data, showing that after stabilizing in the late 2000s, brightening is particularly recovering in Western Europe. In-situ measurements show a reduction of aerosol optical depth from 2001 to 2022 that has been accentuated in the last 10 years, particularly in Western Europe. This would be consistent with the hypothesis that brightening recovery is driven by an aerosol reduction, though other analyses suggest that clouds also play a role in this recovery. More work is needed to understand the contribution of aerosols to solar radiation trends and the exact aerosol effects represented by each solar radiation product.

A comparative analysis of an aerosol dry deposition microscale model for overhead powerlines insulators

Aerosol particles deposition on overhead power line insulators may significantly threaten electric systems, affecting dielectric properties and potentially causing surface discharges and service interruptions, leading to economic consequences. This study addresses this challenge by evaluating a dedicated microscale deposition model that integrated into an advanced air quality (AQ) modeling system. The microscale model integration into the AQ system aims to improve predictions of equivalent salt deposit density (ESDD), a key measure of insulator contamination. This enhancement is crucial for improving system resilience and reliability. The microscale model’s performance in reconstructing particulate matter (PM) deposition fluxes onto XP-70 porcelain-disk electrical insulator is assessed against measured ESDD data collected across various regions in Italy during several experimental campaigns. In order to better understand the specific phenomena impacting PM deposition, the microscale model is compared to the state-of-the-art Zhang deposition model used in CAMx. The analysis reveals that the microscale model tends to overestimate measured ESDD values and predicts higher deposition velocities than the Zhang model. These results suggest potential modelling differences between the two models, including variations in obstacle parameterizations, influence of particle aerodynamics, and dispersion modelling in the near-wall region.

Salt Supersaturation as an Accelerator of Influenza A Virus Inactivation in 1 μL Droplets.

Influenza A virus (IAV) spreads through exhaled aerosol particles and larger droplets. Estimating the stability of IAV is challenging and depends on factors such as the respiratory matrix and drying kinetics. Here, we combine kinetic experiments on millimeter-sized saline droplets with a biophysical aerosol model to quantify the impact of NaCl on IAV stability. We show that IAV inactivation is determined by NaCl concentration, which increases during water evaporation and then decreases again when efflorescence occurs. When drying in air with relative humidity RH = 30%, inactivation follows an inverted sigmoidal curve, with inactivation occurring most rapidly when the NaCl concentration exceeds 20 mol/(kg H2O) immediately prior to efflorescence. Efflorescence reduces the NaCl molality to saturated conditions, resulting in a significantly reduced inactivation rate. We demonstrate that the inactivation rate k depends exponentially on NaCl molality, and after the solution reaches equilibrium, the inactivation proceeds at a first-order rate. Introducing sucrose, an organic cosolute, attenuates IAV inactivation via two mechanisms: first by decreasing the NaCl molality during the drying phase and second by a protective effect against the NaCl-induced inactivation. For both pure saline and sucrose-containing droplets, our biophysical model ResAM accurately simulates the inactivation when NaCl molality is used as the only inactivating factor. This study highlights the role of NaCl molality in IAV inactivation and provides a mechanistic basis for the observed inactivation rates.

Evaluating the Importance of Nitrate‐Containing Aerosols for the Asian Tropopause Aerosol Layer

AbstractThe Asian Summer Monsoon (ASM) convection transports aerosols and their precursors from the boundary layer to the upper troposphere and lower stratosphere (UTLS). This process forms an annually recurring aerosol layer near the tropopause. Recent observations have revealed a distinct property of the aerosol layer over the ASM region, it is nitrate‐rich. We present a newly implemented aerosol formation algorithm that enhances the representation of nitrate aerosol in the Community Aerosol and Radiation Model for Atmospheres (CARMA) coupled with the Community Earth System Model (CESM). The simulated aerosol chemical composition, as well as vertical distributions of aerosol size and mass, are evaluated using in situ and remote sensing observations. The simulated concentrations (ammonium, nitrate, and sulfate) and size distributions are generally within the error bars of data. We find nitrate, organics, and sulfate contribute significantly to the UTLS aerosol concentration between 15°–45°N and 0°–160°E. The two key formation mechanisms of nitrate‐containing aerosols in the ATAL are ammonium neutralization to form ammonium nitrate in regions where convection is active, and condensation of nitric acid in regions of cold temperature. Furthermore, including nitrate formation in the model doubles the surface area density in the tropical tropopause region between 15°–45°N and 0°–160°E, which alters the chlorine partitioning and subsequently impacts the rate of ozone depletion.

Microphysical Prescriptions for Parameterized Water Cloud Formation on Ultra-cool Substellar Objects

Water must condense into ice clouds in the coldest brown dwarfs and exoplanets. When they form, these icy clouds change the emergent spectra, temperature structure, and albedo of the substellar atmosphere. The properties of clouds are governed by complex microphysics but these complexities are often not captured by the simpler parameterized cloud models used in climate models or retrieval models. Here, we combine microphysical cloud modeling and 1D climate modeling to incorporate insights from microphysical models into a self-consistent, parameterized cloud model. Using the 1D Community Aerosol and Radiation Model for Atmospheres (CARMA), we generate microphysical water clouds and compare their properties with those from the widely used EddySed cloud model for a grid of Y dwarfs. We find that the mass of water condensate in our CARMA water clouds is significantly limited by available condensation nuclei; in models without additional seed particles for clouds added, the atmosphere becomes supersaturated. We incorporate water latent heat release in the convective and radiative parts of the atmosphere and find no significant impact on water-ice cloud formation for typical gas giant compositions. Our analysis reveals the CARMA cloud profiles have a gradual decrease in opacity of approximately 4% per bar below the cloud base. Incorporating this gradual cloud base falloff and a variable f sed parameter allows spectra generated from the parameterized Eddysed model to better match those of the microphysical CARMA model. This work provides recommendations for efficiently generating microphysically informed water clouds for future models of cold substellar objects with H/He atmospheres.

Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application

Abstract Aerosols affect Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60–0.85 for BC; R = 0.75–0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing.

Efficacy of mefloquine and its enantiomers in a murine model of Mycobacterium avium infection.

The treatment of Mycobacterium avium infections is still long, complex, and often poorly tolerated, besides emergence of resistances. New active molecules that are more effective and better tolerated are deeply needed. Mefloquine and its enantiomers ((+) Erythro-mefloquine ((+)-EMQ) and (-)-Erythro-mefloquine ((-)-EMQ)) have shown efficacy in both in vitro and in vivo, in a mouse model of M. avium intraveinous infection. However, no study reports aerosol model of infection or combination with gold standard treatment. That was the aim of our study. In an aerosol model of M. avium infection in BALB/c mice, we used five treatment groups as followed: Clarithromycin-Ethambutol-Rifampicin (CLR-EMB-RIF, standard of care, n = 15), CLR-EMB-MFQ (n = 15), CLR-EMB-(+)-EMQ (n = 15), CLR-EMB-(-)-EMQ (n = 15) and an untreated group (n = 25). To evaluate drug efficacy, we sacrificed each month over 3 months, 5 mice from each group. Lung homogenates were diluted and plated for colony forming unit count (CFU) expressed in Log10. At each time point, we found a significant difference between the untreated group and each of the treatment groups (p<0.005). The (+)-EMQ-CLR-EMB group was the group with the lowest CFU count at each time point but never reached statistical significance. The results of each group 3 months after treatment are: (+)-EMQ-CLR-EMB (4.43 ± 0.26), RIF-CLR-EMB (4.83 ± 0.37), (-)-EMQ-CLR-EMB (4.82 ± 0.18), MFQ-CLR-EMB (4.70 ± 0.21). In conclusion, MFQ and its enantiomers appear to be as effective as rifampicin in combination therapy. Further studies are needed to evaluate the ability of these drugs to prevent selection of clarithromycin resistant strains and potential for lung sterilization.

Extreme wildfires over northern Greece during summer 2023 – Part A: Effects on aerosol optical properties and solar UV radiation

In Mediterranean countries, such as Greece, the frequency of forest fires has increased in recent years, primarily due to the widespread impacts of climate change. At the end of August 2023, Greece experienced a record-breaking heatwave that triggered severe wildfire incidents, significantly impacting the atmospheric conditions of several cities, among them Thessaloniki. A significant number of wildfires occurred in northern Greece (Evros), burning thousands of hectares of the protected Dadia forest (Natura 2000) and releasing a significant load of smoke into the atmosphere. According to the European Strategy Forum on Research Infrastructures (ESFRI) a total area of 90,000ha was burnt collectively by the Evros extreme wildfires during August 2023. The emissions led to severely adverse air pollution conditions, causing reduced visibility across an extended eastern Mediterranean region for several days. In this work, we analyze the influence of the transported biomass burning particles on the aerosol properties in the free troposphere, as well as on the surface UV radiation levels over Thessaloniki during the last week of August 2023. The transported smoke plume was detected over the Laboratory of Atmospheric Physics (LAP) in Thessaloniki, approximately 240 km away from the burning area, from August 22nd to the 25th. During this period, the presence of smoke led to exceptionally increased levels of aerosol optical depth (AOD), reaching up to 3.4 at 340nm (the highest ever recorded in Thessaloniki), as well as high Ångström exponent (AE) values, peaking at 2.4 for the 440–870nm range, followed by high Fine Mode Fractions (FMFs), indicating the prevalence of fine-mode smoke aerosol particle. Moreover, during the event, the presence of the biomass burning aerosols led to a strong attenuation of the solar UV irradiance by up to 90 %, reaching unprecedented levels, similar of a solar eclipse. The primary goal of this study is to highlight the extensive impacts that wildfires have, which are anticipated to increase in frequency in the near future, due to the predicted rise in the rate of occurrence of summer heatwaves especially for Mediterranean areas and specifically for Greece. Furthermore, the great value of the synergistic monitoring of the event with ground-based remote sensing instrumentation, along with satellite aerosol observations and modeling tools, is made prominent.

Sectoral Size‐Resolved Particle Number Emissions With Speciation: Emission Profile‐Based Quantification and a Case Study in the Yangtze River Delta Region, China

AbstractSizes and number concentrations are critical parameters for the impact of atmospheric particles on climate and human health. However, comprehensive studies focusing on size‐resolved particle number (PN) emissions from various sectors are scarce. This study aims to fill this research gap by developing sectoral size‐resolved PN emissions for major species including sulfate, organic mass (OM), and black carbon (BC). The size‐resolved emission profiles derived from various measurements in the literature were integrated with a particle mass emission inventory (EI) for 13 major sectors in the Yangtze River Delta region of China as a case study. The particle number size distribution (PNSD) of emitted particles exhibited two distinct peaks: one at approximately 10 nm and the other in the range of 40–60 nm. The primary contributors to PN emissions in the region in 2017 were power plants, gasoline vehicles, diesel vehicles, and cooking sources. In terms of species, OM dominated PN emissions, followed by primary sulfate and then BC. A regional size‐resolved aerosol model employing the size‐resolved PN EI developed here (referred to as the BIN‐SPE experiment) provided reasonably accurate temporal variations of the total PN concentration and captured the PNSD within the size range of 10–300 nm. Uncertainty analysis of sectoral PN emissions across size ranges was carried out and the performance of the BIN‐SPE experiment was compared with those of three commonly used PN emission parameterizations. Our model evaluations highlight future needs for in‐depth investigations into more advanced size‐resolved emissions and secondary OM formation mechanisms.

Characterization of the aerosol contribution to the top-of-atmosphere radiance for satellite ocean color retrievals

A method is proposed for characterization of the aerosol contribution to the top-of-atmosphere (TOA) radiance. The method is based on solving the problem of radiative transfer in the atmosphere-ocean system and expanding the solution in powers of the aerosol optical thickness τ a . We show that the linear term of the expansion is analytically expressed in terms of the bidirectional transmittance/reflectance of the aerosol-free Rayleigh atmosphere. A procedure is also proposed for successively extracting the terms of higher order in τ a from the data of the TOA radiance computation with the DISORT code. As analysis shows, the radiance expansion in τ a is not purely polynomial. Beginning from the quadratic term, the coefficients of the series expansion in powers of τ a become dependent logarithmically on τ a . The approach proposed enables us to reproduce analytically the τ a -dependence of the TOA radiance with controlled accuracy. We determine the expansion coefficients up to the cubic term inclusive and validate our results on the aerosol model embedded in NASA’s SeaDAS algorithm for aerosol loadings, representative for the Barents and Kara seas. In the visible and near-infrared spectral ranges, accounting for the terms up to a quadratic one is found to be sufficient for the atmospheric correction of satellite ocean color data typical for the Arctic region.

Optimizing indoor air models through k-means clustering of nanoparticle size distribution data

Sectional physics-based aerosol models imply a computational effort that hinders their use in building digital twins, real-time predictive control, and computer-based iterative optimization versus black-box approaches. The innovation of this paper lies in the proposal of a novel systematic methodology to optimize the number of size bins in sectional reduced-order models for particle concentration simulations. This allows its application in indoor air quality management and overcomes generalizability and data-dependency issues of black-box models. This method, based on k-means clustering, aims to ensure precision when tackling relatively fast fine and ultrafine particle simulations targeting the reduction of time and resource consumption from experimentally-determined aerosol size distribution time series. Consequently, three tests were carried out using combustion aerosols inside a custom-designed emission chamber to simulate emission hotspots in non-commercial and occupational settings. 2-, 3-, 4-, and 5-cluster classifications were evaluated for data coming from 13 particle size bins through silhouette analysis and the study of their temporal profiles. Results show that the 4-cluster classification summarizes the behavior of data in the 10–420 nm range, ensuing up to a 77 % improvement in the model's computational demand. Moreover, this method allows an accurate definition of the necessary size ranges to calculate nanoparticle concentrations inside the chamber and facilitates the interpretation of aerosol behavior and processes through the resulting clusters' temporal profiles.

Modeling Indoor Inorganic Aerosol Concentrations During the ATHLETIC Campaign with IMAGES.

In 2018, the ATHLETIC campaign was conducted at the University of Colorado Dal Ward Athletic Center and characterized dynamic indoor air composition in a gym environment. Among other parameters, inorganic particle and gas-phase species were alternatingly measured in the gym's supply duct and weight room. The Indoor Model of Aerosols, Gases, Emissions, and Surfaces (IMAGES) uses the inorganic aerosol thermodynamic equilibrium model, ISORROPIA, to estimate the partitioning of inorganic aerosols and corresponding gases. In this study herein, measurements from the ATHLETIC campaign were used to evaluate IMAGES' performance. Ammonia emission rates, nitric acid deposition, and particle deposition velocities were related to observed occupancy, which informed these rates in IMAGES runs. Initially, modeled indoor inorganic aerosol concentrations were not in good agreement with measurements. A parametric investigation revealed that lowering the temperature or raising the relative humidity used in the ISORROPIA model drove the semivolatile species more toward the particle phase, substantially improving modeled-measured agreement. One speculated reason for these solutions is that aerosol water was enhanced by increasing the RH or decreasing the temperature. Another is that thermodynamic equilibrium was not established in this indoor setting or that the thermodynamic parametrizations in ISORROPIA are less accurate for typical indoor settings. This result suggests that applying ISORROPIA indoors requires further careful experimental validation.

Aerosol effects during heat waves in summer 2022 and responses to emission change over China

This study explores aerosol direct, indirect, and feedback effects on meteorology and fine particulate matter during heat waves of August 2022 over eastern China by using an online coupled regional climate–chemistry–aerosol model. In this period, aerosols exerted mean direct (DRE) and indirect (IRE) radiative effects of −3.9 Wm−2 and −2.4 Wm−2 at TOA, which totally caused a decrease in average surface air temperature by 0.3 °C over east China, accompanied by decreases in PBLH (planetary boundary layer height) and precipitation and an increase in PM2.5 concentration. With the anthropogenic emission reduction from 2013 to 2022, DRE apparently decreased while IRE changed little, leading to a decrease in total aerosol radiative effect (TRE) by 27% at TOA. The weakened TRE resulted in increases in surface air temperature and precipitation by 0.14 °C and 2.7 mm, respectively, on average over east China, with the maximum warming exceeding 0.5 °C in BTH (Beijing–Tianjin–Hebei province). This study highlights a warming trend due to weakened TRE, which may exacerbate heat wave, and an increasing importance of aerosol IRE relative to DRE due to weak sensitivity of cloud properties to aerosol change during the emission reduction.

Quality Assessment and Application Scenario Analysis of AGRI Land Aerosol Product from the Geostationary Satellite Fengyun-4B in China.

The Advanced Geostationary Radiation Imager (AGRI) sensor on board the geostationary satellite Fengyun-4B (FY-4B) is capable of capturing particles in different phases in the atmospheric environment and acquiring aerosol observation data with high spatial and temporal resolution. To understand the quality of the Land Aerosol (LDA) product of AGRI and its application prospects, we conducted a comprehensive evaluation of the AGRI LDA AOD. Using the 550 nm AGRI LDA AOD (550 nm) of nearly 1 year (1 October 2022 to 30 September 2023) to compare with the Aerosol Robotic Network (AERONET), MODIS MAIAC, and Himawari-9/AHI AODs. Results show the erratic algorithmic performance of AGRI LDA AOD, the correlation coefficient (R), mean error (Bias), root mean square error (RMSE), and the percentage of data with errors falling within the expected error envelope of ±(0.05+0.15×AODAERONET) (within EE15) of the LDA AOD dataset are 0.55, 0.328, 0.533, and 34%, respectively. The LDA AOD appears to be overestimated easily in the southern and western regions of China and performs poorly in the offshore areas, with an R of 0.43, a Bias of 0.334, a larger RMSE of 0.597, and a global climate observing system fraction (GCOSF) percentage of 15% compared to the inland areas (R = 0.60, Bias = 0.163, RMSE = 0.509, GCOSF = 17%). Future improvements should focus on surface reflectance calculation, water vapor attenuation, and more suitable aerosol model selection to improve the algorithm's accuracy.