Clean Regions Research Articles

Quantification of Ion-Implanted Single-Atom Dopants in Monolayer MoS2 via HAADF STEM Using the TEMUL Toolkit.

In recent years, atomic resolution imaging of two-dimensional (2D) materials using scanning transmission electron microscopy (STEM) has become routine. Individual dopant atoms in 2D materials can be located and identified using their contrast in annular dark-field (ADF) STEM. However, in order to understand the effect of these dopant atoms on the host material, there is now the need to locate and quantify them on a larger scale. In this work, we analyze STEM images of MoS2 monolayers that have been ion-implanted with chromium at ultra-low energies. We use functions from the open-source TEMUL Toolkit to create and refine an atomic model of an experimental image based on the positions and intensities of the atomic columns in the image. We then use the refined model to determine the likely composition of each atomic site. Surface contamination stemming from the sample preparation of 2D materials can prevent accurate quantitative identification of individual atoms. We disregard atomic sites from regions of the image with hydrocarbon surface contamination to demonstrate that images acquired using contaminated samples can give significant atom statistics from their clean regions, and can be used to calculate the retention rate of the implanted ions within the host lattice. We find that some of the implanted chromium ions have been successfully integrated into the MoS2 lattice, with 4.1% of molybdenum atoms in the transition metal sublattice replaced with chromium.

Impact of regional transport on high ozone episodes in southeast coastal regions of China

Severe ozone (O3) pollution can be harmful to human health and ecosystems. The O3 level in Fujian, a coast province in southeast China, is generally 30–60 μg m−3 lower than in highly polluted regions in China, including North China Plain (NCP), Yangtze River Delta (YRD), and Pearl River Delta (PRD). Yet, Fujian still experiences high O3 episodes that exceed the national standard. Here we investigate whether and how these high O3 episodes are impacted by regional O3 transport from polluted regions. A backward trajectory model, HYSPLIT, is combined with observational data to identify transport pathways and O3 source regions. The results show that the exceedance days (8 h O3 concentrations above 160 μg m−3), averaged over 2015–2020, range 12–34 days for coastal cities and 3–9 days for inland cities, with two peaks in late-spring and early-autumn. On average, O3 transport from non-Fujian regions can impact 29–38% of exceedance days in coastal cities, and 44–50% of exceedance days in inland cities. The dominant transport pathways are from YRD and NCP to the East China Sea near Fujian in the lower troposphere, and then to Fujian near the ground level. Regional transport from PRD, mainly in spring, also happens. Using synoptic weather pattern (SWP) classification, we identify three SWPs in spring and two SWPs in autumn that are favorable to regional O3 transport. In summer, such transport is mainly associated with typhoon activities. This study underscores the importance of regional O3 transport to a clean coastal region and helps predict regional air pollution.

Innovative solution using ion-electronic technology to purify the air from pathogenic microflora and create comfortable living conditions for humans

According to the Federal State Statistics Service regarding respiratory diseases in Krasnoyarsk Krai, the increase in this indicator was 6% over the five years, and the increase in oncologic diseases was 4% over the same period. Polluted air is one of the leading causes of the increased incidence. The paper aims to find ways to clean indoor air using ion-electronic technology and bring the microclimate parameters to optimal values in cold and warm seasons. Experimental and theoretical studies substantiated the possibility of developing a device capable of creating and maintaining an air environment in closed premises, close in terms of indicators to the healthy air of ecologically clean regions. The device can have different performance and can be used in domestic, industrial, and public premises. Depending on the mode of operation and purpose, this device can be both stationary and mobile. Fine dust cannot be removed from the room even if the air exchange rate is increased by 200 and 400 times. It has been experimentally proven that ion-electronic technology and volatile matter of woody plants remove dust to achieve a clean room. This concept formed the basis for developing a device using nanotechnology combined with the volatile matter of woody plants. The dependences of the influence of artificial ionization of air and volatile matter of woody plants on reducing the amount of fine dust and pathogenic microflora are theoretically substantiated. The air purified in this way maintains immunity and reduces the incidence of respiratory diseases, which has been proven experimentally based on a prototype of the developed device.

Concurrent (Fe,Mo)2C carbides and Cu-rich clusters precipitation in ferritic steel containing copper during aging

ABSTRACT The concurrent (Fe,Mo)2C carbides and Cu-rich clusters precipitation in the ferritic steel containing copper after aging at 400°C for 4000 h have been investigated using transmission electron microscopy (TEM) and atom probe tomography (APT). The results show that spinodal decomposition and an atomic ordering reaction occur in the ferritic steel containing copper. After aging, the retained austenite decomposed by the spinodal mechanism into C-rich and C-lean regions. The C-rich phase transforms into the (Fe,Mo)2C carbides via the ordering reaction, while Cu-rich clusters formed in the C-lean regions. The experimental results can be interpreted on the basis of phase separation via spinodal decomposition followed by chemical ordering. The small size of Cu-rich clusters can be attributed to the lower diffusion coefficient of Cu in the retained austenite.

BREAST CANCER CAD SYSTEM BY USING TRANSFER LEARNING AND ENHANCED ROI

Computer systems are being employed in specialized professions such as medical diagnosis to alleviate some of the costs and to improve dependability and scalability. This paper implements a computer aided breast cancer diagnosis system. It utilizes the publicly available mini MIAS mammography image dataset. Images are preprocessed to clean isolate breast tissue region. Extracted regions are used to adjust and verify a pretrained convolutional deep neural network, the GoogLeNet. The implemented model shows good performance results compared to other published works with accuracy of 86.6%, sensitivity of 75% and specificity of 88.9%.

BREAST CANCER CAD SYSTEM BY USING TRANSFER LEARNING AND ENHANCED ROI

Computer systems are being employed in specialized professions such as medical diagnosis to alleviate some of the costs and to improve dependability and scalability. This paper implements a computer aided breast cancer diagnosis system. It utilizes the publicly available mini MIAS mammography image dataset. Images are preprocessed to clean isolate breast tissue region. Extracted regions are used to adjust and verify a pretrained convolutional deep neural network, the GoogLeNet. The implemented model shows good performance results compared to other published works with accuracy of 86.6%, sensitivity of 75% and specificity of 88.9%.

The age of hair matters – the incorporation of cortisol by external contamination is enhanced in distal hair segments of pigs and cattle

Hair cortisol concentration (HCC) is used as an indicator of long-term stress or pathologies in humans and increasingly in animals. Although the main mechanism for the incorporation of cortisol into the hair shaft is by diffusion from blood, cortisol may also be incorporated from external sources by contamination of the hair surface. In farm animals under conventional husbandry conditions and trapped animals, contamination of hair with cortisol-containing body fluids, especially with urine, was shown to be a considerable confounding factor when studying HCCs. We recently found that cattle and pigs exhibit elevated HCCs in distal hair segments and assume that the incorporation of external cortisol is facilitated in these older hair segments. Therefore, the aim of this study was to investigate the effects of urine contamination on HCC in different hair segments of pigs and cattle, and to determine whether different cleaning protocols can prevent contamination effects. In an in vivo experiment in pigs (n = 18) and an in vitro experiment in cattle (n = 12), hairs were repeatedly contaminated with urine of the respective species and then shaved or cut in segments. Cortisol concentrations in hair segments were analysed by enzyme immunoassay after washing with isopropanol and extraction with methanol. Results were compared with HCCs in untreated hairs or hairs treated with water. Moreover, additional bovine hair samples contaminated with urine were subjected to two further cleaning procedures. Contamination with urine generally increased HCCs, and it was demonstrated for the first time that this effect is more pronounced in distal compared to proximal hair segments in both species. The immersion of bovine hair in vitro in water caused a washout of cortisol, which was also more pronounced in distal hair segments. In general, the different cleaning protocols for cattle hair did not prevent contamination effects, so we assume that external cortisol not only adheres but is incorporated into the hair shaft. Structural damage of older, distal hair segments may facilitate permeability of the hair matrix and diffusion of cortisol from and into aqueous solutions. Thus, the validity of HCC as a marker of stress is compromised in animals where soiling of hair with body fluids is a risk factor. Therefore, hair samples should be collected from clean body regions and, if possible, using proximal hair segments.

Semantic Segmentation Dataset for AI-Based Quantification of Clean Mucosa in Capsule Endoscopy.

Background and Objectives: Capsule endoscopy (CE) for bowel cleanliness evaluation primarily depends on subjective methods. To objectively evaluate bowel cleanliness, we focused on artificial intelligence (AI)-based assessments. We aimed to generate a large segmentation dataset from CE images and verify its quality using a convolutional neural network (CNN)-based algorithm. Materials and Methods: Images were extracted and divided into 10 stages according to the clean regions in a CE video. Each image was classified into three classes (clean, dark, and floats/bubbles) or two classes (clean and non-clean). Using this semantic segmentation dataset, a CNN training was performed with 169 videos, and a clean region (visualization scale (VS)) formula was developed. Then, measuring mean intersection over union (mIoU), Dice index, and clean mucosal predictions were performed. The VS performance was tested using 10 videos. Results: A total of 10,033 frames of the semantic segmentation dataset were constructed from 179 patients. The 3-class and 2-class semantic segmentation’s testing performance was 0.7716 mIoU (range: 0.7031–0.8071), 0.8627 Dice index (range: 0.7846–0.8891), and 0.8927 mIoU (range: 0.8562–0.9330), 0.9457 Dice index (range: 0.9225–0.9654), respectively. In addition, the 3-class and 2-class clean mucosal prediction accuracy was 94.4% and 95.7%, respectively. The VS prediction performance for both 3-class and 2-class segmentation was almost identical to the ground truth. Conclusions: We established a semantic segmentation dataset spanning 10 stages uniformly from 179 patients. The prediction accuracy for clean mucosa was significantly high (above 94%). Our VS equation can approximately measure the region of clean mucosa. These results confirmed our dataset to be ideal for an accurate and quantitative assessment of AI-based bowel cleanliness.

Investigating the Understanding of Oxidation Chemistry Using 20 Years of Airborne OH and HO2 Observations

AbstractHydroxyl (OH) and hydroperoxyl (HO2) strongly influence the atmosphere's oxidation of gases emitted from Earth's surface and the formation and aging of aerosol particles. Thus, understanding OH and HO2 chemistry is essential for examining the impact of human activity on future atmospheric composition and climate. Using the OH and HO2 data set collected with the Penn State Airborne Tropospheric Hydrogen Oxides Sensor (ATHOS) during nine aircraft missions over the past 20 years, we compare observed OH and HO2 to that modeled using the same near‐explicit photochemical box model. In general, the agreement is well within the combined uncertainties of the observations and models, even when the model is constrained only with a common data set of simultaneous measurements. However, in environments such as cities, forests, and pollution plumes, the model chemical mechanism and size of the data set of constraining measurements do matter. The model constrained by the full set of measurements better simulates OH loss and OH in these regions than the model constrained by the common set of measurements. In cleaner regions, the differences between observed and modeled OH and HO2 found in previous studies generally remain and do not appear to be systematic, indicating that the differences are driven by measurement issues for ATHOS and/or other instruments. Thus, these comparisons indicate that the oxidation chemistry in most of the free troposphere is understood to as well as current measurements can determine. The focus of future research needs to be on regions rich in volatile organic compounds, where observed‐to‐modeled differences are more persistent, and on improving measurement consistency.

Boundary Effects for EMD-Based Algorithms

Empirical mode decomposition (EMD) and its improved EMD-based algorithms are adaptive and nonlinear methods that decompose a nonstationary signal into several intrinsic mode functions (IMFs) through the sifting process. When the EMD-based algorithms are applied to decompose a signal polluted with noise in some regions, the noise will spread into the clean region and introduce errors in the IMFs. During the real-time computation of an EMD-based algorithm, the signal is partitioned into a series of overlapping time windows. Points outside the window are discarded, they act as an error source and the error will spread into the window. We will prove that the above two problems are mathematically identical. Due to the complex nature of the sifting iteration, a mathematical theory for the error analysis of the boundary effect is still lacking. Previous studies mainly rely on simulations, and the results show that the error seems to be confined locally near the boundary. Beginning with one sifting iteration, which is the kernel of an EMD-based method, we will theoretically analyze the boundary effects completely based on the sifting process without any approximations, and prove that the error will propagate into the interior domain and may be amplified and thus obscure the meaning of an IMF. Then, we will prove a sufficient condition for the exponential decay of the error. When the error is amplified, we propose a method to resolve this problem. Finally, numerical experiments are conducted to analyze multiple siftings and IMFs.

PUFA-GAN: A Frequency-Aware Generative Adversarial Network for 3D Point Cloud Upsampling.

We propose a generative adversarial network for point cloud upsampling, which can not only make the upsampled points evenly distributed on the underlying surface but also efficiently generate clean high frequency regions. The generator of our network includes a dynamic graph hierarchical residual aggregation unit and a hierarchical residual aggregation unit for point feature extraction and upsampling, respectively. The former extracts multiscale point-wise descriptive features, while the latter captures rich feature details with hierarchical residuals. To generate neat edges, our discriminator uses a graph filter to extract and retain high frequency points. The generated high resolution point cloud and corresponding high frequency points help the discriminator learn the global and high frequency properties of the point cloud. We also propose an identity distribution loss function to make sure that the upsampled points remain on the underlying surface of the input low resolution point cloud. To assess the regularity of the upsampled points in high frequency regions, we introduce two evaluation metrics. Objective and subjective results demonstrate that the visual quality of the upsampled point clouds generated by our method is better than that of the state-of-the-art methods.

The GALAH Survey: chemical tagging and chrono-chemodynamics of accreted halo stars with GALAH+ DR3 and Gaia eDR3

ABSTRACT Since the advent of Gaia astrometry, it is possible to identify massive accreted systems within the Galaxy through their unique dynamical signatures. One such system, Gaia-Sausage-Enceladus (GSE), appears to be an early ‘building block’ given its virial mass $\gt 10^{10}\, \mathrm{M_\odot }$ at infall (z ∼ 1−3). In order to separate the progenitor population from the background stars, we investigate its chemical properties with up to 30 element abundances from the GALAH+ Survey Data Release 3 (DR3). To inform our choice of elements for purely chemically selecting accreted stars, we analyse 4164 stars with low-α abundances and halo kinematics. These are most different to the Milky Way stars for abundances of Mg, Si, Na, Al, Mn, Fe, Ni, and Cu. Based on the significance of abundance differences and detection rates, we apply Gaussian mixture models to various element abundance combinations. We find the most populated and least contaminated component, which we confirm to represent GSE, contains 1049 stars selected via [Na/Fe] versus [Mg/Mn] in GALAH+ DR3. We provide tables of our selections and report the chrono-chemodynamical properties (age, chemistry, and dynamics). Through a previously reported clean dynamical selection of GSE stars, including $30 \lt \sqrt{J_R / \, \mathrm{kpc\, km\, s^{-1}}} \lt 55$, we can characterize an unprecedented 24 abundances of this structure with GALAH+ DR3. With our chemical selection we characterize the dynamical properties of the GSE, for example mean $\sqrt{J_R / \, \mathrm{kpc\, km\, s^{-1}}} =$$26_{-14}^{+9}$. We find only $(29\pm 1){{\ \rm per\ cent}}$ of the GSE stars within the clean dynamical selection region. Our methodology will improve future studies of accreted structures and their importance for the formation of the Milky Way.

TOTAL PHENOLIC AND FLAVONOID CONTENT, ANTIOXIDANT ACTIVITY OF FICARIA VERNA

The objective of the present study was to determine the total content of phenolics and flavonoids in ethanol extracts of a plant from the family of Ranunculaceae – Ficaria verna. Harvesting of medicinal plant was carried out in ecologically clean regions of west Ukraine in spring 2020. The extracts were obtained by maceration of grass, leaves,and flowers to compare the content of active substances in different types of raw materials. The total phenolic content was estimated spectrophotometrically using Folin Ciocalteu method. The total flavonoid content was measured by aluminium chloride colorimetric assay. The maximum content of phenolic and flavonoids compounds was observed in the grass Ficaria verna. The antioxidant effects of the extracts were investigated. The Ficaria verna can be regarded as a promising natural plant source of antioxidant effects with a high potential for phytopreparations.

Ablation Patterns of the Debris Covered Tongue of Halong Glacier Revealed by Short Term Unmanned Aerial Vehicle Surveys

Debris-covered glaciers are an important glacier type and have attracted more and more attention. This study presents the results of ablation patterns of debris-covered tongue of the Halong Glacier in the northeastern Tibetan Plateau, by using two repeated unmanned aerial vehicle (UAV) surveys performed on August 11 and September 15, 2019. The results show that the tongue of Halong Glacier has experienced strong ablation during the surveyed period, with an overall ice loss amount to 4.17 × 105 metric tons. Among all the briefly classified surface types, supraglacial debris has the largest area (80.9%) and also mass losses (58.6%) comparing to others. However, ice cliffs show the strongest and the most significant ablation rates (averagely 1.36 and 1.22 m w.e. for supraglacial and lateral ice cliffs, respectively), followed by clean ice regions (1.01 m w.e.). The backwastes of ice cliffs also resulted in up to 7.8 m horizontal back-off at different parts of Halong Glacier, lead to fast terminal retreat and narrowing down of the glacier tongue, and may result in the break off of Halong Glacier tongue into separated parts in the future. The surface ablation rates show a clear negative exponential relationship with the measured debris thicknesses, well in accordance with previous studies. Regions in cutting and flushing by supraglacial and lateral rivers have the largest surface elevation decreases but are not significant due to their limited area and the relatively lower quality of UAV digital surface models (DSMs) in those covered regions.

Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty.

Annual global satellite-based estimates of fine particulate matter (PM2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998-2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5-3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM2.5 concentrations exceed 90 μg/m3, with local concentrations of approximately 200 μg/m3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 μg/m3/year, with decreases beginning 2-3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM2.5. The evaluation of uncertainty for agglomerated values indicates that hybrid PM2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.

Declining dry deposition of NO2 and SO2 with diverse spatiotemporal patterns in China from 2013 to 2018

The nitrogen and sulfur deposition results in damages on ecosystems, while the lack of direct observation on dry deposition limits our understanding of the total deposition. This study aimed to improve the methodology and estimates of NO2 and SO2 dry deposition in China and to explore the efficacy of China's recent emission control measures on dry deposition at the national and regional scales. We combined the random forest algorithm and the GEOS-Chem chemical transport model to predict the dry deposition fluxes of NO2 and SO2 and their inter-annual variabilities during 2013–2018 in mainland China. The annual NO2 dry deposition ranged between 2.1 and 3.1 kg N ha−1 yr−1, with an annual reduction rate of 0.21 kg N ha−1 yr−1 over this period. The areas with large deposition were located in the east, while the biggest reduction existed in the relatively clean Tibet Plateau region. The annual SO2 dry deposition ranged between 7.5 and 18.4 kg S ha−1 yr−1, with the annual reduction rate at 2.4 kg S ha−1 yr−1. Both the magnitude and relative reduction in the north were generally larger than the south. Regarding the four typical economically developed regions, the NO2 deposition declined slower than the national average, while SO2 generally declined faster than or equivalently to the national average, except for Pearl River Delta. The reduced emissions attributed to the national action on air pollution control were identified as an important reason for the declining deposition. However, the increased traffic and industrial capacity in the east weakened its benefit on NO2.

Data-Driven Reduced-Order Modeling of Convective Heat Transfer in Porous Media

This work presents a data-driven Reduced-Order Model (ROM) for parametric convective heat transfer problems in porous media. The intrusive Proper Orthogonal Decomposition aided Reduced-Basis (POD-RB) technique is employed to reduce the porous medium formulation of the incompressible Reynolds-Averaged Navier–Stokes (RANS) equations coupled with heat transfer. Instead of resolving the exact flow configuration with high fidelity, the porous medium formulation solves a homogenized flow in which the fluid-structure interactions are captured via volumetric flow resistances with nonlinear, semi-empirical friction correlations. A supremizer approach is implemented for the stabilization of the reduced fluid dynamics equations. The reduced nonlinear flow resistances are treated using the Discrete Empirical Interpolation Method (DEIM), while the turbulent eddy viscosity and diffusivity are approximated by adopting a Radial Basis Function (RBF) interpolation-based approach. The proposed method is tested using a 2D numerical model of the Molten Salt Fast Reactor (MSFR), which involves the simulation of both clean and porous medium regions in the same domain. For the steady-state example, five model parameters are considered to be uncertain: the magnitude of the pumping force, the external coolant temperature, the heat transfer coefficient, the thermal expansion coefficient, and the Prandtl number. For transient scenarios, on the other hand, the coastdown-time of the pump is the only uncertain parameter. The results indicate that the POD-RB-ROMs are suitable for the reduction of similar problems. The relative L2 errors are below 3.34% for every field of interest for all cases analyzed, while the speedup factors vary between 54 (transient) and 40,000 (steady-state).

CUMULATIVE INCIDENCE OF LYMPHOID AND MYELOID LEUKEMIAS IN DIFFERENT REGIONS OF THE CHERKASSY REGION IN 2001 AND 2014

The purpose - to carry out comparison of the cumulative morbidity on the lymphoid and myeloid leukemia on relatively clean and contaminated regions of the Cherkassy region for 2001 and 2014.
 Materials and methods. The incidence was determined in regions A (relatively clean), B (radioactive contaminated), C (chemically contaminated) and D (radioactive and chemical contaminated) per 100 thousand population, which was registered during the All-Ukrainian census conducted in 2001, and in 2014 according to the published data of the State Statistical Service of Ukraine.
 Results. In 2001, in the radioactive contaminated region of Cherkassy oblast, there was a 2.46-fold (p = 0.024) higher incidence of myeloid leukemias alone (5.30; 3.03-8.33 vs. 2.15; 0.66-3.64 per 100 thousand population, respectively). Instead, in the area contaminated with chemical factors, the prevalence of lymphoid (acute and chronic) was determined (7.12; 1.84 - 12.39 vs. 2.69; 1.02 - 4.35 per 100 thousand population, respectively) and myeloid (6.10; 1.22 - 10.99 vs. 2.15; 0.66 - 3.64 per 100 thousand population, respectively) leukemia, compared with relatively clean regions. According to 2001 data, who living in a chemical contaminated region, the risk of cumulative morbidity for acute and chronic lymphoid and myeloid leukemias is 3.30 (p = 0.014) and 2.83 (p = 0.043), respectively.
 In 2014, no increase in the level of cumulative incidence of these hematological neoplasms was detected between the clean and contaminated regions of Cherkassy oblast.
 Conclusions. It was proved that the radiation factor in 2001 increased the probability of growth the cumulative incidence only for myeloid leukemias, and chemical contamination - for both myeloid and lymphoid leukemias. In 2014, there was no increase in the level of cumulative incidence of certain hematological diseases between clean and contaminated regions of Cherkasy oblast.

Microstructure and mechanical properties of two Al alloys welded by linear friction weld

Two high strength Al alloys AA2050 and AA7010 have been joined using linear friction welding (LFW) in this study. Microstructural evolution across the weld line developed during linear friction welding has been examined. Their effects on mechanical properties have also been evaluated. A clean weld region where there is free of microcracking, microporosity, and oxides, was obtained. Dynamic recrystallization (nearly full and partial) took place on the weldment. Dissolution of ‘parent’ precipitates in centre weld zone (CWZ) and thermomechanical affected zone (TMAZ) was observed, thus leading to lower hardness and strength compared with the parent materials.

Optimisation of CO2 absorption and liquid scintillation counting method for carbon-14 specific activity measurement in atmospheric air

A method for the determination of 14C activity in the ambient air was optimised with the development of a simple setup for the regeneration of CO2 from carbonate sample and saturating the absorber in <45 min for direct determination of activity by liquid scintillation counting (LSC). Atmospheric CO2 was trapped in NaOH solution and precipitated as BaCO3 by adding BaCl2. The carbonate sample was taken in a newly designed regeneration system, subjected to acid hydrolysis, and the absorber (CarboSorb-E) was saturated with the CO2 regenerated from carbonate sample. This allowed optimisation of CO2 absorption by the absorber (up to ~ 2.3941 g of CO2/10 mL with an average of 2.1688 g) and a minimum detectable activity value of 14 Bq kg−1C for a counting time of 300 min (8 Bq kg−1C for 1000 min) was achieved with Quantulus - 1220 LSC system. The necessity of (i) the measurement of the total volume of air sampled, (ii) the determination of trapping efficiency for CO2 in the NaOH, recovery of 14C in chemical processing of BaCO3, and subsequent regeneration and absorption processes, and (iii) independent determination of carbon content in the air for expressing the results in terms of 14C specific activity (Bq kg−1C), are avoided in this method. The method is capable of yielding accurate results, in a considerably shorter time when compared to previously reported methods, with a deviation of <2.2% from the target value (with a relative standard deviation of 1.1%, and a relative error of 0.53%) when ambient air samples from clean air region (region not affected by local anthropogenic sources of 14C) are analysed. Validation of the method was performed by (i) analysing BaCO3 sample derived from ambient air by accelerator mass spectrometry, and (ii) analysing the CO2 produced from the combustion of IAEA C3 reference material. Upon validation, the suitability of the method for determining small excess 14C specific activity in the vicinity of a nuclear power plant was demonstrated.