Assessment of NAAPS-RA performance in Maritime Southeast Asia during CAMP²Ex

Monitoring and modeling aerosol particle lifecycle in Southeast Asia (SEA) is challenged by high cloud cover, complex meteorology, and the wide range of aerosol species, sources, and transformations found throughout the region. Satellite observations are limited, and there are few in situ observations of aerosol extinction profiles, aerosol properties, and environmental conditions. Therefore, accurate aerosol model outputs are crucial for the region. This work evaluates the Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA) aerosol optical thickness (AOT) and light extinction products using airborne aerosol and meteorological measurements from the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) in SEA. Modeled AOTs and extinction coefficients were compared to those retrieved with a High Spectral Resolution Lidar (HSRL-2). Correlations were highest for AOT in the mixed layer (AOTML; R2 = 0.83, bias = 0.00, root mean square error [RMSE] = 0.03) compared to total AOT (R2 = 0.68, bias = 0.01, RMSE = 0.14), although the correlations between the observations and 1° × 1° degree NAAPS-RA outputs were weaker in regions with strong gradients in aerosol properties, such as near areas of active convection. Correlations between simulated and retrieved aerosol extinction coefficients were highest from 145–500 m (R2 = 0.75, bias = 0.01 km−1, RMSE = 0.08 km−1) and decreased with increasing altitude (R2 = 0.69 and 0.26, bias = 0.00 and 0.00 km−1, RMSE = 0.09 and 0.00 km−1 for 500–1500 m and > 1500 m, respectively), which was likely a result of the use of bulk cloud mixing parameterizations. We also investigated the role of possible relative humidity (RH) errors in extinction simulations. Despite negative biases in modeled RH (−4.9, −7.7, and −2.3 % for altitudes < 500 m, 500–1500 m, and > 1500 m, respectively), AOT and extinction agreement with the HSRL-2 did not change significantly at any altitude when RHs from dropsondes were substituted into the model. Improvements may have been stunted due to errors in how NAAPS-RA modeled physics of particle hygroscopic growth, dry particle mass concentrations, and/or dry mass extinction efficiencies, especially when combined with AOT corrections from data assimilation. Specifically, the model overestimated the hygroscopicity of (i) smoke particles from biomass burning in the Maritime Continent (MC), and (ii) anthropogenic emissions transported from East Asia. This work provides insight into how certain environmental and microphysical properties influence AOT and extinction simulations, which can then be interpreted in the context of modeling global concentrations of particle mass and cloud condensation nuclei (CCN).

Exploring the Change in PM2.5 and Ozone Concentrations Caused by Aerosol–Radiation Interactions and Aerosol–Cloud Interactions and the Relationship with Meteorological Factors

Aerosols can interact with other meteorological variables in the air via aerosol–radiation or aerosol–cloud interactions (ARIs/ACIs), thus affecting the concentrations of particle pollutants and ozone. The online-coupled model WRF-Chem was applied to simulate the changes in the PM2.5 (particulate matter less than 2.5 μm in aerodynamic diameter) and ozone concentrations that are caused by these mechanisms in China by conducting three parallel sensitivity tests. In each case, availabilities of aerosol–radiation interactions and aerosol–cloud interactions were set differently in order to distinguish each pathway. Partial correlation coefficients were also analyzed using statistical tools. As suggested by the results, the ARIs reduced ground air temperature, wind speed, and planetary boundary height while increasing relative humidity in most places. Consequently, the ozone concentration in the corresponding region declined by 4%, with a rise in the local annual mean PM2.5 concentration by approximately 12 μm/m3. The positive feedback of the PM2.5 concentration via ACIs was also found in some city clusters across China, despite the overall enhancement value via ACIs being merely around a quarter to half that via ARIs. The change in ozone concentration via ACIs exhibited different trends. The ozone concentration level increased via ACIs, which can be attributed to the drier air in the south and the diminished solar radiation that is received in central and northern China. The correlation coefficient suggests that the suppression in the planetary boundary layer is the most significant factor for the increase in PM2.5 followed by the rise in moisture required for hygroscopic growth. Ozone showed a significant correlation with NO2, while oxidation rates and radiation variance were also shown to be vitally important.

Technical Note: Real-Time Diagnosis of the Hygroscopic Growth Micro-Dynamics of Nanoparticles with Two-Dimensional Correlation Infrared Spectroscopy

Nanoparticles can absorb water to grow up and this will affect the light scattering behavior, cloud condensation nuclei properties, lifetime, and chemical reactivity of these particles. Current techniques usually assume the shapes of nanoparticles to be spherical in calculation of aerosol liquid water content (ALWC), which may result in large uncertainties when the shapes of nanoparticles show large deviations to the spherical assumptions. Furthermore, current techniques are also difficult to identify the intermolecular chemical interactions of phase transition micro-dynamics during nanoparticle deliquescence process because their limited temporal resolutions are unable to capture the complex femtosecond-level intermediate states. In this study, the hygroscopic growth properties of nanoparticles with electrical mobility diameter of approximately 100 nm and their phase transition interaction dynamics on molecular scale are characterized on real time by using the Fourier transform infrared (FTIR) and the two-dimensional correlation infrared (2D-IR) spectroscopic techniques. With the FTIR spectroscopy, we develop a novel real-time method for ALWC by constructing the absorption spectra of liquid water, and realized real-time measurements of water content and dry nanoparticle mass to characterize the hygroscopic growth factors (GF) which show discrepancies to the extended aerosol inorganics model (E-AIM). We further explore the difference that the deliquescence points of sodium nitrate (SN) and oxalic acid (OA) compounds are lower than that of AS by using the 2D-IR spectroscopic analysis technique. We also identify the occurrence sequential order of the hydration interactions and investigate the dynamic deliquescence process of the functional groups for AS and its mixture compounds. Both SN and OA compounds lower the deliquescence point of AS, but only AN can change the hydrolysis reaction mechanism for AS in AS/AN and AS/OA mixtures. This study can not only provide important information with respect to the difference in phase transition point under different conditions, but also improve current understanding of the chemical interaction mechanism between nanoparticles (particularly for organic particles) and medium, which is of great significance for haze control across China.

Computer Mathematical Statistics and Comparative Analysis of Meteorological Conditions in the Bohai Rim Region through Big Data Digitization

Based on the data of environmental monitoring stations and meteorological stations in typical city in the Bohai Rim region in June 2021 and June 2020. The air quality in June 2021 was better than that in the same period in 2020. Ozone (O3) was the primary pollutant in June 2021 and June 2020. The overall meteorological conditions in May 2021 were relatively favorable. In June 2021, the number of light wind days and wind speed had no significant impact on air quality compared with the same period last year. The dominant wind direction in June 2021 was southeast wind, which was not conducive to the increase of ozone concentration compared with the southwest wind frequency in the same period in 2020; the relative humidity in June 2021 was slightly higher year-on-year, which was slightly conducive to the hygroscopic growth of pollution; the static stability index in June 2021 was lower year-on-year, and the weather conditions for comprehensive pollution diffusion were preferred year-on-year; the height of the mixed layer in June 2021 was lower year-on-year, the vertical diffusion weather conditions were deviated year-on-year; the average temperature, sunshine hours and total radiation in June 2021 were all low, which was not conducive to the generation of ozone.

Regularized inversion of aerosol hygroscopic growth factor probability density function: Application to humidity-controlled fast integrated mobility spectrometer measurements

Aerosol hygroscopic growth plays an important role in atmospheric particle chemistry and the effects of aerosol on radiation and hence climate. The hygroscopic growth is often characterized by a growth factor probability density function (GF-PDF), where the growth factor is defined as the ratio of the particle size at a specified relative humidity to its dry size. Parametric, least-square methods are the most widely used algorithms for inverting the GF-PDF from measurements of humidified tandem differential mobility analyzers (HTDMA) and have been recently applied to the GF-PDF inversion from measurements of the humidity-controlled fast integrated mobility spectrometer (HFIMS). However, these least square methods suffer from noise amplification due to the lack of regularization in solving the ill-posed problem, resulting in significant fluctuations in the retrieved GF-PDF and even occasional failures of convergence. In this study, we introduce nonparametric, regularized methods to invert aerosol GF-PDF and apply them to HFIMS measurements. Based on the HFIMS kernel function, the forward convolution is transformed into a matrix-based form, which facilitates the application of the nonparametric inversion methods with regularizations, including Tikhonov regularization and Twomey’s iterative regularization. Inversions of the GF-PDF using the nonparameteric methods with regularization are demonstrated using HFIMS measurements simulated from representative GF-PDFs of ambient aerosols. The characteristics of reconstructed GF-PDFs resulting from different inversion methods, including previously developed least-square methods, are quantitively compared. The result shows that Twomey’s method generally outperforms other inversion methods. The capabilities of the Twomey’s method in reconstructing the pre-defined GF-PDFs and recovering the mode parameters are validated.