receptor model
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2022 ◽  
Vol 423 ◽  
pp. 127030
Author(s):  
Ram Proshad ◽  
Tapos Kormoker ◽  
Mamun Abdullah Al ◽  
Md. Saiful Islam ◽  
Sujan Khadka ◽  
...  

Author(s):  
Aleksandra Jachimowicz ◽  
Aleksandra Jachimowicz ◽  
He Zhang ◽  
Leslie Y. Chen
Keyword(s):  

2021 ◽  
Vol 14 (12) ◽  
pp. 7573-7604
Author(s):  
Qian Ye ◽  
Jie Li ◽  
Xueshun Chen ◽  
Huansheng Chen ◽  
Wenyi Yang ◽  
...  

Abstract. Many efforts have been devoted to quantifying the impact of intercontinental transport on global air quality by using global chemical transport models with horizontal resolutions of hundreds of kilometers in recent decades. In this study, a global online air quality source–receptor model (GNAQPMS-SM) is designed to effectively compute the contributions of various regions to ambient pollutant concentrations. The newly developed model is able to quantify source–receptor (S-R) relationships in one simulation without introducing errors by nonlinear chemistry. We calculate the surface and planetary boundary layer (PBL) S-R relationships in 19 regions over the whole globe for ozone (O3), black carbon (BC), and non-sea-salt sulfate (nss-sulfate) by conducting a high-resolution (0.5&deg &times 0.5&deg) simulation for the year 2018. The model exhibits a realistic capacity in reproducing the spatial distributions and seasonal variations of tropospheric O3, carbon monoxide, and aerosols at global and regional scales – Europe (EUR), North America (NAM), and East Asia (EA). The correlation coefficient (R) and normalized mean bias (NMB) for seasonal O3 at global background and urban–rural sites ranged from 0.49 to 0.87 and −2 % to 14.97 %, respectively. For aerosols, the R and NMB in EUR, NAM, and EA mostly exceed 0.6 and are within ±15 %. These statistical parameters based on this global simulation can match those of regional models in key regions. The simulated tropospheric nitrogen dioxide and aerosol optical depths are generally in agreement with satellite observations. The model overestimates ozone concentrations in the upper troposphere and stratosphere in the tropics, midlatitude, and polar regions of the Southern Hemisphere due to the use of a simplified stratospheric ozone scheme and/or biases in estimated stratosphere–troposphere exchange dynamics. We find that surface O3 can travel a long distance and contributes a non-negligible fraction to downwind regions. Non-local source transport explains approximately 35 %–60 % of surface O3 in EA, South Asia (SAS), EUR, and NAM. The O3 exported from EUR can also be transported across the Arctic Ocean to the North Pacific and contributes nearly 5 %–7.5 % to the North Pacific. BC is directly linked to local emissions, and each BC source region mainly contributes to itself and surrounding regions. For nss-sulfate, contributions of long-range transport account for 15 %–30 % within the PBL in EA, SAS, EUR, and NAM. Our estimated international transport of BC and nss-sulfate is lower than that from the Hemispheric Transport of Air Pollution (HTAP) assessment report in 2010, but most surface O3 results are within the range. This difference may be related to the different simulation years, emission inventories, vertical and horizontal resolutions, and S-R revealing methods. Additional emission sensitivity simulation shows a negative O3 response in receptor region EA in January from EA. The difference between two methods in estimated S-R relationships of nss-sulfate and O3 are mainly due to ignoring the nonlinearity of pollutants during chemical processes. The S-R relationship of aerosols within EA subcontinent is also assessed. The model that we developed creates a link between the scientific community and policymakers. Finally, the results are discussed in the context of future model development and analysis opportunities.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Prince Chapman Agyeman ◽  
Kingsley JOHN ◽  
Ndiye Michael Kebonye ◽  
Luboš Borůvka ◽  
Radim Vašát ◽  
...  

AbstractUnhealthy soils in peri-urban and urban areas expose individuals to potentially toxic elements (PTEs), which have a significant influence on the health of children and adults. Hundred and fifteen (n = 115) soil samples were collected from the district of Frydek Mistek at a depth of 0–20 cm and measured for PTEs content using Inductively coupled plasma—optical emission spectroscopy. The Pearson correlation matrix of the eleven relevant cross-correlations suggested that the interaction between the metal(loids) ranged from moderate (0.541) correlation to high correlation (0.91). PTEs sources were calculated using parent receptor model positive matrix factorization (PMF) and hybridized geostatistical based receptor model such as ordinary kriging-positive matrix factorization (OK-PMF) and empirical Bayesian kriging-positive matrix factorization (EBK-PMF). Based on the source apportionment, geogenic, vehicular traffic, phosphate fertilizer, steel industry, atmospheric deposits, metal works, and waste disposal are the primary sources that contribute to soil pollution in peri-urban and urban areas. The receptor models employed in the study complemented each other. Comparatively, OK-PMF identified more PTEs in the factor loadings than EBK-PMF and PMF. The receptor models performance via support vector machine regression (SVMR) and multiple linear regression (MLR) using root mean square error (RMSE), R square (R2) and mean square error (MAE) suggested that EBK-PMF was optimal. The hybridized receptor model increased prediction efficiency and reduced error significantly. EBK-PMF is a robust receptor model that can assess environmental risks and controls to mitigate ecological performance.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Diane N. H. Kim ◽  
Alexander A. Lim ◽  
Michael A. Teitell

AbstractQuantitative phase microscopy (QPM) enables studies of living biological systems without exogenous labels. To increase the utility of QPM, machine-learning methods have been adapted to extract additional information from the quantitative phase data. Previous QPM approaches focused on fluid flow systems or time-lapse images that provide high throughput data for cells at single time points, or of time-lapse images that require delayed post-experiment analyses, respectively. To date, QPM studies have not imaged specific cells over time with rapid, concurrent analyses during image acquisition. In order to study biological phenomena or cellular interactions over time, efficient time-dependent methods that automatically and rapidly identify events of interest are desirable. Here, we present an approach that combines QPM and machine learning to identify tumor-reactive T cell killing of adherent cancer cells rapidly, which could be used for identifying and isolating novel T cells and/or their T cell receptors for studies in cancer immunotherapy. We demonstrate the utility of this method by machine learning model training and validation studies using one melanoma-cognate T cell receptor model system, followed by high classification accuracy in identifying T cell killing in an additional, independent melanoma-cognate T cell receptor model system. This general approach could be useful for studying additional biological systems under label-free conditions over extended periods of examination.


2021 ◽  
Author(s):  
Qian Ye ◽  
Jie Li ◽  
Xueshun Chen ◽  
Huansheng Chen ◽  
Wenyi Yang ◽  
...  

Abstract. Many efforts have been devoted to quantifying the impact of intercontinental transport on global air quality by using global chemical transport models with horizontal resolutions of hundreds of kilometers in recent decades. In this study, a global online air quality source-receptor model (GNAQPMS-SM) is designed to effectively compute the contributions of various regions to ambient pollutant concentrations. The newly developed model is able to quantify source-receptor (S-R) relationships in one simulation without introducing errors by nonlinear chemistry, which largely reduces the computation costs compared to the brute force method. We calculate the surface and planetary boundary layer (PBL) S-R relationships in 19 regions over the whole globe for ozone, black carbon (BC) and non-sea-salt sulphate (nss-sulphate) by conducting a high-resolution (0.5° × 0.5°) simulation for the year 2018. The model exhibits a realistic capacity in reproducing the spatial distributions and seasonal variations of tropospheric ozone, carbon monoxide, and aerosols at global and regional scales (Europe, North America and East Asia). The correlation coefficient (R) and normalized mean bias (NMB) for seasonal ozone at global background and urban-rural sites ranged from 0.49 to 0.87 and −2 % to 14.97 %, respectively. For aerosols, the R and NMB in Europe, North America and East Asia mostly exceed 0.6 and are within ±15 %. These statistical parameters based on this global simulation can match those of regional models in key regions. The simulated tropospheric nitrogen dioxide and aerosol optical depths are generally in agreement with satellite observations. The model overestimates ozone mixing ratios in the upper troposphere and stratosphere in the tropics, mid-latitude and polar regions of the Southern Hemisphere due to the use of a simplified stratospheric ozone scheme and/or biases in estimated stratosphere-troposphere exchange dynamics. We find that O3 in the surface layer can travel a long distance and contributes a nonnegligible fraction to downwind regions. Nonlocal source transport explains approximately 35–60 % of surface O3 in East Asia, South Asia, Europe and North America. The O3 exported from Europe can also be transported across the Arctic Ocean to the North Pacific and contributes nearly 5–7.5 % to the North Pacific. BC, as a primary aerosol, is directly linked to local emissions, and each BC source region mainly contributes to itself and surrounding regions. For nss-sulphate, contributions of long-range transport account for 15–30 % within the PBL in East Asia, South Asia, Europe and North America. Our estimated international transport is lower than that from the Hemispheric Transport of Air Pollution (HTAP) assessment report in 2010. In this study, local contributions to surface nss-sulphate and BC exceed the ranges given in the HTAP model, while local contributions to nss-sulphate and BC within the PBL are mainly within the ranges. This difference may be related to the different simulation years, emission inventories, horizontal resolutions and S-R revealing methods. The S-R relationship of aerosols within the East Asia subcontinent is also assessed. The model that we developed creates a link between the scientific community and policymakers. Finally, the results are discussed in the context of future model development and analysis opportunities.


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