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In this study, we explore an innovative approach to calculate Lidar ratios, an important element of atmospheric science that is generally assumed to be constant. By integrating 532nm laser lidar with camera data, we can derive extinction coefficients from Lidar and backscatter signals from laser images captured by the camera to calculate relative Lidar ratios under different atmospheric conditions. The relative Lidar ratio here is not the actual Lidar ratio because it is obtained from the backscatter signal and not the backscatter coefficient. Our method also overcomes the near-field limitation of Lidar by using camera-derived pixel values to restore the near-field extinction coefficient. These advances present more accurate techniques for determining atmospheric properties and demonstrate the potential of combining Lidar and camera data in environmental monitoring.

Rapid industrialization and the influx of human resources have led to the establishment of industrial complexes near urban areas, exposing residents to various air pollutants. This has led to a decline in air quality, impacting neighboring residential areas adversely, which highlights the urgent need to monitor air pollution in these areas. Recent advancements in technology, such as Solar Occultation Flux (SOF) and Sky Differential Optical Absorption Spectroscopy (SkyDOAS) used as remote sensing techniques and mobile extraction Fourier Transform Infrared Spectrometry (MeFTIR) used as an in situ technique, now offer enhanced precision in estimating the pollutant emission flux and identifying primary sources. In a comprehensive study conducted in 2020 in the Sinpyeong Jangrim Industrial Complex in Busan City, South Korea, a mobile laboratory equipped with SOF, SkyDOAS, and MeFTIR technologies was employed to approximate the emission flux of total alkanes, sulfur dioxide (SO2), nitrogen dioxide (NO2), formaldehyde (HCHO), and methane (CH4). Using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) diffusion model, pollutant dispersion to residential areas was simulated. The highest average daily emission flux was observed for total alkanes, with values of 69.9 ± 71.6 kg/h and 84.1 ± 85.8 kg/h in zones S1 and S2 of the Sinpyeong Jangrim Industrial Complex, respectively. This is primarily due to the prevalence of metal manufacturing and mechanical equipment industries in the area. The HYSPLIT diffusion model confirmed elevated pollution levels in residential areas located southeast of the industrial complex, underscoring the influence of the dominant northwesterly wind direction and wind speed on pollutant dispersion. This highlights the urgent need for targeted interventions to address and mitigate air pollution in downwind residential areas. The total annual emission fluxes were estimated at 399,984 kg/yr and 398,944 kg/yr for zones S1 and S2, respectively. A comparison with the Pollutant Release and Transfer Registers (PRTRs) survey system revealed that the total annual emission fluxes in this study were approximately 24.3 and 4.9 times higher than those reported by PRTRs. This indicates a significant underestimation of the impact of small businesses on local air quality, which was not accounted for in the PRTR survey system.

This study focuses on the technology for real-time water droplets removal using two-wavelength scanning LiDAR monitoring. The LiDAR measures the Ångström exponent, using extinction coefficients at 1064 nm and 532 nm wavelengths, to assess particle size, and calculates depolarization ratio from backscatter signals at 532 nm to determine particle shape. This technology allowed for the identification and classification of particle types, focusing on fine particles while excluding water droplets. The aim of this study is to use scanning LiDAR to distinguish fine particles and water droplets across a wide area and to identify their movement and origin when pollutant concentrations are high.

Black carbon (BC) absorption aerosol optical depth (AAODBC) defines the contribution of BC in light absorption and is retrievable using sun/sky radiometer measurements provided by Aerosol Robotic Network (AERONET) inversion products. In this study, we utilized AERONET-retrieved depolarization ratio (DPR, δp), single scattering albedo (SSA, ω), and Ångström Exponent (AE, å) of version 3 level 2.0 products as indicators to estimate the contribution of BC to the absorbing fractions of AOD. We applied our methodology to the AERONET sites, including North and South America, Europe, East Asia, Africa, India, and the Middle East, during 2000–2018. The long-term AAODBC showed a downward tendency over Sao Paulo (−0.001 year−1), Thessaloniki (−0.0004 year−1), Beijing (−0.001 year−1), Seoul (−0.0015 year−1), and Cape Verde (−0.0009 year−1) with the highest values over the populous sites. This declining tendency in AAODBC can be attributable to the successful emission control policies over these sites, particularly in Europe, America, and China. The AAODBC at the Beijing, Sao Paulo, Mexico City, and the Indian sites showed a clear seasonality indicating the notable role of residential heating in BC emissions over these sites during winter. We found a higher correlation between AAODBC and fine mode AOD at 440 nm at all sites except for Beijing. High pollution episodes, BC emission from different sources, and aggregation properties seem to be the main drivers of higher AAODBC correlation with coarse particles over Beijing.

Fine particulate matter (PM) release is regulated by environmental policies in most countries. This study investigated long–term trends in the mass extinction efficiency (Qe) of aerosols in Northeast Asia. For this purpose, the Qe was calculated using visibility, PM2.5 recorded between 2015 and 2020, and PM10 recorded between 2001 and 2020 at eight Korean sites. The Qe of PM10 (Qe,10) showed an increasing trend with 0.06~0.22 (m2/g)/yr in seven cities except for Jeju. The Qe of PM2.5 (Qe,2.5) also showed an increasing trend with 0.28–2.47 (m2/g)/yr in all cities. In this study, PM10 and PM2.5, were divided into low, moderate, and high concentrations, and the Qe value change by year was examined. Qe,10 showed a tendency to decrease at low concentrations (19–21 μg/m3). However, at moderate (69–71 μg/m3) and high concentrations (139–141 μg/m3), Qe,10 increased in most regions. Qe,2.5 showed an increasing trend at low concentration (9–11 μg/m3), moderate concentration (29–31 μg/m3), and high concentration (69–71 μg/m3), except for Suwon and Pohang, where data were insufficient for analysis. Both Qe,10 and Qe,2.5 showed an increasing trend. The increase in Qe indicated that the visibility-impairing effect of PM can increase even if the same concentration of PM is present. The visibility-impairing effects of PM vary based on the composition, size and other characteristics of the particles in the atmosphere at a given point in time and not simply the quantity of particles. This means that reducing the quantity of particles does not reliably produce a proportionate improvement in visibility. Air quality policies must take the variable nature of PM particles and their effect on visibility into account so that more consistent improvements in air quality can be achieved.

Hygroscopic growth of aerosols significantly affects radiative forcing and visibility, yet remains challenging due to the interplay among size, composition, and humidity. This study integrates in-situ PM and lidar data to address discrepancies between dry mass concentrations and wet optical measurements. Using machine learning inversion (XGBoost, R 2  = 0.98), dry-state size distributions were retrieved from PM data. Mie theory was applied to derive the dry extinction coefficient, and the lidar-based wet extinction coefficient yielded the hygroscopic growth. Aerosol types were classified using Random Forest (accuracy 83.4%), revealing dominance of coarse hygroscopic aerosols in this coastal urban region. Optical response varied with hygroscopicity: wet extinction coefficient increased with RH for hydrophilic types but remained low for hydrophobic aerosols. Notably, clean conditions occasionally showed a sharp increase in wet extinction coefficient despite low PM, highlighting limitations of mass-only assessments. This approach suggests improved aerosol characterization algorithms considering size and hygroscopicity, supporting advanced air quality and climate modeling studies.

To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (τD) and coarse-(τPC) and fine-pollution particles (τPF) depending on emission sources and size. Ångström exponent values are also identified separately as total and fine-mode particles (αT and αPF). We checked these trends in various ways; (1) first-order linear regression analysis of the annual average values, (2) percent variation using the slope of linear regression method, and (3) a reliability analysis using the Mann–Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. Although there were regional differences, τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of τPC and τPF, show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular, τPF considerably decreased in Europe and Northeast Asia (95% confidential levels in MK-test), and τPC decreased in Northeast Asia (Z-values for Seoul and Osaka are −2.955 and −2.306, respectively, statistically significant if |z| ≥ 1.96). The decrease in τPC seems to be because of the reduction of primary and anthropogenic emissions from regulation by air quality policies. The meaningful result in this paper is that the particle size became smaller, as seen by values of αT that decreased by −3.30 to −30.47% in Europe, North Africa, and the Middle East because αT provides information on the particle size. Particle size on average became smaller over India and Asian regions considered in our study due to the decrease in coarse particles. In particular, an increase of αPF in most areas shows the probability that the average particle size of fine-mode aerosols became smaller in recent years. We presumed the cause of the increase in αT is because relatively large-sized fine-mode particles were eliminated due to air quality policies.

Accumulating evidence reveals the oncogenic role of methyltransferase-like 3 (METTL3) in a variety of cancer types, either dependent or independent of its m6A methyl transferase activity. We have designed proteolysis-targeting chimeras (PROTACs) targeting METTL3 and identified KH12 as a potent METTL3 degrader. Treatment of KH12 on MOLM-13 cells causes more than 80% degradation of METTL3 with a half-maximal degradation concentration (DC50) of 220 nM in a dose-, time- and ubiquitin-dependent fashion. In addition, KH12 reverses differentiation and possesses anti proliferative effects surpassing the reported inhibitors in MOLM-13 cells. Furthermore, KH12 significantly suppresses the growth of various gastric cancer (GC) cells, where the m6A-independent activity of METTL3 plays a crucial role in tumorigenesis. The anti-GC effect of KH12 was further confirmed in patient-derived organoids (PDOs). This study highlights the therapeutic potential of targeted degradation of epitranscriptomic writer METTL3 as an anti-cancer strategy.Competing Interest StatementTaebo Sim is a shareholder of Magicbullet therapeutics Inc.