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At least 1,693 records · Page 94

Distribution of toenail selenium levels in young adult Caucasians and African Americans in the United States: The CARDIA Trace Element Study

Background: Data on selenium (Se) levels in American young adults, especially in African Americans, are lacking. Objective: This study presented toenail Se distributions in American young adults of both genders, including both Caucasians and African Americans; and explored potential predictors of toenail Se levels. Data and methods: Data from the Coronary Artery Risk Development in Young Adults study among 4252 American young adults, aged 20-32 in 1987 was used to examine toenail Se levels by instrumental neutron-activation analysis. The distribution of Se levels was described and multivariable linear regression was used to examine potential modifiers of toenail Se concentration within ethnicity-gender subgroups. Results: The geometric mean of toenail Se in this cohort was 0.844 {mu}g/g (95% CI, 0.840-0.849 {mu}g/g) and the median was 0.837 {mu}g/g (95% CI, 0.833-0.844 {mu}g/g). Median levels from lowest to highest quintile were 0.691, 0.774, 0.838, 0.913 and 1.037 {mu}g/g. Se levels varied geographically, and were generally in accordance with its concentrations in local soil. Males, African Americans, current smokers, heavy drinkers and less educated participants were more likely to have low Se levels. Conclusion: This study suggests that toenail Se levels vary geographically depending on soil Se concentrations. In addition to gender, ethnicity and education level, smoking status and alcohol consumption are two important indicators of Se status since they are modifiable lifestyle factors. Findings from this study might aid public health professionals in identifying people at relatively high or low Se levels, so that chronic disease prevention efforts can be directed toward these subgroups. - Research highlights: {yields} Average of toenail Se levels in this cohort was 0.844 {mu}g/g (95% CI, 0.840-0.849 {mu}g/g). {yields} Toenail Se levels vary geographically depending on soil Se concentrations. {yields} Males, African Americans and less educated participants have low Se levels. {yields} Smoking status and alcohol consumption are two important indicators of Se status.

54 ENVIRONMENTAL SCIENCES↗

Prediction of Stable and Active (Oxy-Hydro) Oxide Nanoislands on Noble-Metal Supports for Electrochemical Oxygen Reduction Reaction

Developing cost-effective oxygen electrocatalysts with high activity and stability is key to their commercialization. However, economical earth-abundant catalysts based on first-row transition-metal oxides suffer from low electrochemical stability, which is difficult to improve without compromising their activity. In this paper, using density functional theory calculations, we demonstrate that noble-metal supports lead to bifunctional enhancement of both the stability and the oxygen reduction reaction (ORR) activity of metal (oxy-hydro) oxide nanoislands. We observe a significant stabilization of supported nanoislands beyond the intrinsic stability limits of bulk phases, which originates from a favorable lattice mismatch and reductive charge transfer from oxophilic supports. Additionally, we discover that interfacial active sites (located between the nanoisland and the support) reinforce the binding strength of reaction intermediates, hence boosting ORR activity. Considering that both stability and activity lead to discovery of CoOOH|Pt, NiOOH|Ag, and FeO 2 |Ag as viable systems for alkaline ORR, we then use a multivariant linear regression method to identify elementary descriptors for efficient screening of promising cost-effective nanoisland|support catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The association between neighborhood obesogenic factors and prostate cancer risk and mortality: the Southern Community Cohort Study

Background: Prostate cancer is one of the leading causes of cancer-related mortality among men in the United States. We examined the role of neighborhood obesogenic attributes on prostate cancer risk and mortality in the Southern Community Cohort Study (SCCS). Methods: From the total of 34,166 SCCS male participants, 28,356 were included in the analysis. We assessed the relationship between neighborhood obesogenic factors [neighborhood socioeconomic status (nSES) and neighborhood obesogenic environment indices including the restaurant environment index, the retail food environment index, parks, recreational facilities, and businesses] and prostate cancer risk and mortality by controlling for individual-level factors using a multivariable Cox proportional hazards model. We further stratified prostate cancer risk analysis by race and body mass index (BMI). Results: Median follow-up time was 133 months [interquartile range (IQR): 103, 152], and the mean age was 51.62 (SD: ± 8.42) years. There were 1,524 (5.37%) prostate cancer diagnoses and 98 (6.43%) prostate cancer deaths during follow-up. Compared to participants residing in the wealthiest quintile, those residing in the poorest quintile had a higher risk of prostate cancer (aHR = 1.32, 95% CI 1.12–1.57, p = 0.001), particularly among non-obese men with a BMI < 30 (aHR = 1.46, 95% CI 1.07–1.98, p = 0.016). The restaurant environment index was associated with a higher prostate cancer risk in overweight (BMI ≥ 25) White men (aHR = 3.37, 95% CI 1.04–10.94, p = 0.043, quintile 1 vs. None). Obese Black individuals without any neighborhood recreational facilities had a 42% higher risk (aHR = 1.42, 95% CI 1.04–1.94, p = 0.026) compared to those with any access. Compared to residents in the wealthiest quintile and most walkable area, those residing within the poorest quintile (aHR = 3.43, 95% CI 1.54–7.64, p = 0.003) or the least walkable area (aHR = 3.45, 95% CI 1.22–9.78, p = 0.020) had a higher risk of prostate cancer death. Conclusion: Living in a lower-nSES area was associated with a higher prostate cancer risk, particularly among Black men. Restaurant and retail food environment indices were also associated with a higher prostate cancer risk, with stronger associations within overweight White individuals. Finally, residing in a low-SES neighborhood or the least walkable areas were associated with a higher risk of prostate cancer mortality.

60 APPLIED LIFE SCIENCES↗

Salvage Radiosurgery for Brain Metastases: Prognostic Factors to Consider in Patient Selection

Purpose: Stereotactic radiosurgery (SRS) is offered to patients for recurrent brain metastases after prior brain radiation therapy (RT), but few studies have evaluated the efficacy of salvage SRS or factors to consider in selecting patients for this treatment. This study reports overall survival (OS), intracranial progression-free survival (PFS), and local control (LC) after salvage SRS, and factors associated with outcomes. Methods and Materials: This is a retrospective review of patients treated from 2009 to 2011 with salvage SRS after prior brain RT for brain metastases. Survival from salvage SRS and from initial brain metastases diagnosis (IBMD) was calculated. Univariate and multivariable (MVA) analyses included age, performance status, recursive partitioning analysis (RPA) class, extracranial disease control, and time from initial RT to salvage SRS. Results: There were 106 patients included in the analysis with a median age of 56.9 years (range 32.5-82 years). A median of 2 metastases were treated per patient (range, 1-12) with a median dose of 21 Gy (range, 12-24) prescribed to the 50% isodose. With a median follow-up of 10.5 months (range, 0.1-68.2), LC was 82.8%, 60.1%, and 46.8% at 6 months, 1 year, and 3 years, respectively. Median PFS was 6.2 months (95% confidence interval [CI] = 4.9-7.6). Median OS was 11.7 months (95% CI = 8.1-13) from salvage SRS, and 22.1 months from IBMD (95% CI = 18.4-26.8). On MVA, age (P=.01; hazard ratio [HR] = 1.04; 95% CI = 1.01-1.07), extracranial disease control (P=.004; HR = 0.46; 95% CI = 0.27-0.78), and interval from initial RT to salvage SRS of at least 265 days (P=.001; HR = 2.46; 95% CI = 1.47-4.09) were predictive of OS. Conclusions: This study demonstrates that patients can have durable local control and survival after salvage SRS for recurrent brain metastases. In particular, younger patients with controlled extracranial disease and a durable response to initial brain RT are likely to benefit from salvage SRS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Conceptual Advances from Werner Complexes to Metal–Organic Frameworks

Alfred Werner's work on the geometric aspects of how ligands bind to metal ions at the end of the 19th century has given rise, in the molecular realm, to organometallic, bioinorganic, and cluster chemistries. By stitching together organic and inorganic units into crystalline porous metal-organic frameworks (MOFs), the connectivity, spatial arrangement, and geometry of those molecular complexes can now be fixed in space and become directly addressable. The fact that MOFs are porous provides additional space within which molecules can further be transformed and their chemistry controlled. Finally, an aspect not available in molecular chemistry but a direct consequence of Werner's analysis of coordination complexes is the ability to have multivariable functionality in MOFs to bring about a continuum of chemical environments, within the repeating order of the framework, from which a substrate can sample and be transformed in ways not possible in molecular complex chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

A new diagnostic tool is developed for examining relationships between the synoptic scale circulation and regional temperature distributions in GCMs. The 4 x 5 deg GISS GCM is shown to produce accurate simulations of the variance in the synoptic scale sea level pressure distribution over the U.S. An analysis of the observational data set from the National Meteorological Center (NMC) also shows a strong relationship between the synoptic circulation and grid point temperatures. This relationship is demonstrated by deriving transfer functions between a time-series of circulation parameters and temperatures at individual grid points. The circulation parameters are derived using rotated principal components analysis, and the temperature transfer functions are based on multivariate polynomial regression models. The application of these transfer functions to the GCM circulation indicates that there is considerable spatial bias present in the GCM temperature distributions. The transfer functions are also used to indicate the possible changes in U.S. regional temperatures that could result from differences in synoptic scale circulation between a 1XCO2 and a 2xCO2 climate, using a doubled CO2 version of the same GISS GCM.

Crane, Robert G.↗

A Step Beyond Simple Keyword Searches: Services Enabled by a Full Content Digital Journal Archive

The problems of managing and searching large archives of scientific journal articles can potentially be addressed through data mining and statistical techniques matured primarily for quantitative scientific data analysis. A journal paper could be represented by a multivariate descriptor, e.g., the occurrence counts of a number key technical terms or phrases (keywords), perhaps derived from a controlled vocabulary ( e . g . , the American Meteorological Society's Glossary of Meteorology) or bootstrapped from the journal archive itself. With this technique, conventional statistical classification tools can be leveraged to address challenges faced by both scientists and professional societies in knowledge management. For example, cluster analyses can be used to find bundles of "most-related" papers, and address the issue of journal bifurcation (when is a new journal necessary, and what topics should it encompass). Similarly, neural networks can be trained to predict the optimal journal (within a society's collection) in which a newly submitted paper should be published. Comparable techniques could enable very powerful end-user tools for journal searches, all premised on the view of a paper as a data point in a multidimensional descriptor space, e.g.: "find papers most similar to the one I am reading", "build a personalized subscription service, based on the content of the papers I am interested in, rather than preselected keywords", "find suitable reviewers, based on the content of their own published works", etc. Such services may represent the next "quantum leap" beyond the rudimentary search interfaces currently provided to end-users, as well as a compelling value-added component needed to bridge the print-to-digital-medium gap, and help stabilize professional societies' revenue stream during the print-to-digital transition.

Boccippio, Dennis J.↗

Automated Framework for Groundwater Monitoring Using DWT with LSTM and Transformers

Environmental monitoring is critical for safeguarding public health and ecological well-being. Traditional data structuring and workflow monitoring methods consume significant time and effort, hindering timely insights and effective decision-making. Our study addresses this challenge by presenting an AI framework that automates data cleaning, structuring, and modeling processes, specifically targeting applications in groundwater monitoring. By leveraging automation for data processing and model training, our framework establishes a novel and efficient paradigm for environmental monitoring, with its potential application to the vast network of over a hundred Department of Energy Environmental Management (DoE-EM) cleanup sites across the country. It analyzes data streams from a network of groundwater Internet-of-Things (IoT) sensors deployed at the Savannah River Site (SRS) for prediction modeling. This allows human experts to focus on analysis and decision-making, ultimately leading to better environmental outcomes.The framework employs multivariate time-series forecasting methods to study and model the behavior of varying chemical analytes. The continuous learning process is enabled by utilizing deep learning techniques. It allows the framework to become more nuanced in its analysis over time, adapting to the specific characteristics of the environmental site and the evolving nature of contaminant behavior. Deep learning models known for sequence modeling, LSTM, and Transformers are employed for time series forecasting. Data processing and structuring are essential components significantly impacting the final model's performance. This hypothesis was proven by presenting a comparative analysis of model performance with processed and unprocessed data. The feature engineering approach utilized was the Discrete Wavelet Transform, which works well with time series data.

Discrete Wavelet Transform (DWT)↗

Multiple burn fuel-optimal orbit transfers: Numerical trajectory computation and neighboring optimal feedback guidance

This report describes current work in the numerical computation of multiple burn, fuel-optimal orbit transfers and presents an analysis of the second variation for extremal multiple burn orbital transfers as well as a discussion of a guidance scheme which may be implemented for such transfers. The discussion of numerical computation focuses on the use of multivariate interpolation to aid the computation in the numerical optimization. The second variation analysis includes the development of the conditions for the examination of both fixed and free final time transfers. Evaluations for fixed final time are presented for extremal one, two, and three burn solutions of the first variation. The free final time problem is considered for an extremal two burn solution. In addition, corresponding changes of the second variation formulation over thrust arcs and coast arcs are included. The guidance scheme discussed is an implicit scheme which implements a neighboring optimal feedback guidance strategy to calculate both thrust direction and thrust on-off times.

Chuang, C.-H.↗

Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics

A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear model structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence.

Morelli, Eugene A.↗

Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics

A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear model structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence.

Morelli, Eugene A.↗

Statistical Analysis of Factors Riving Surface Ozone Variability over Continental South Africa

Statistical relationships between surface ozone (O3) concentration, precursor species and meteorological conditions in continental South Africa were examined from data obtained from measurement stations in north-eastern South Africa. Three multivariate statistical methods were applied in the investigation, i.e. multiple linear regression (MLR), principal component analysis (PCA) and –regression (PCR), and generalised additive model (GAM) analysis. The daily maximum 8-h moving average O3 concentrations were considered in these statistical models (dependent variable). MLR models indicated that meteorology and precursor species concentrations are able to explain ~50% of the variability in daily maximum O3 levels. MLR analysis revealed that atmospheric carbon monoxide (CO), temperature and relative humidity were the strongest factors affecting the daily O3 variability. In summer, daily O3 variances were mostly associated with relative humidity, while winter O3 levels were mostly linked to temperature and CO. PCA indicated that CO, temperature and relative humidity were not strongly collinear. GAM also identified CO, temperature and relative humidity as the strongest factors affecting the daily variation of O3. Partial residual plots found that temperature, radiation and nitrogen oxides most likely have a non-linear relationship with O3,while the relationship with relative humidity and CO is probably linear. An inter-comparison between O3 levels modelled with the three statistical models compared to measured O3 concentrations showed that the GAM model offered a slight improvement over the MLR model. These findings emphasise the critical role of regional-scale O3 precursors coupled with meteorological conditions in daily variances of O3 levels in continental South Africa.

multiple linear regression (MLR)↗

Search for the associated production of a Higgs boson with a single top quark in proton-proton collisions at $ \sqrt{s}=8 $ TeV

Our paper presents the search for the production of a Higgs boson in association with a single top quark, using data collected in proton-proton collisions at a center-of-mass energy of 8 TeV corresponding to an integrated luminosity of 19.7 fb -1 . The search exploits a variety of Higgs boson decay modes resulting in final states with photons, bottom quarks, and multiple charged leptons, including tau leptons, and employs a variety of multivariate techniques to maximize sensitivity to the signal. Furthermore, our analysis is optimized for the opposite sign of the Yukawa coupling to that in the standard model and corresponding to a large enhancement of the signal cross section. In the absence of an excess of candidate signal events over the background predictions, 95% confidence level observed (expected) upper limits on anomalous tHq production are set, ranging between 600 (450) fb and 1000 (700) fb depending on the assumed diphoton branching fraction of the Higgs boson. This is the first time that results on anomalous tHq production have been reported.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Postoperative Chemoradiation Therapy in High-Risk Cervical Cancer: Re-evaluating the Findings of Gynecologic Oncology Group Study 109 in a Large, Population-Based Cohort

Purpose: To review the National Cancer Database (NCDB) to evaluate postoperative high-risk cervical cancer patients for factors associated with a benefit from chemoradiation therapy (CRT) over external beam radiation therapy alone (EBRT). Methods and Materials: The National Cancer Database was queried for women with cervical cancer treated with hysterectomy and adjuvant EBRT from 2002 to 2012. Only patients with pathologic lymph node involvement (LN+), positive surgical margins, and/or parametrial invasion were included in our analysis (on the basis of Peter's criteria). Univariable and multivariable analyses (MVA) were performed, and hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to investigate for factors associated with of CRT utilization and overall survival (OS). Results: A total of 3053 patients met inclusion criteria, and 2479 received adjuvant CRT (81%), whereas 574 (19%) received EBRT alone. Factors associated with increased CRT utilization on MVA included age <69 years, year of diagnosis ≥2008, non-adenocarcinoma histology, and LN+. Use of CRT improved OS among the entire cohort on MVA (HR 0.76, CI 0.601-0.962; P=.022). On MVA, CRT improved OS in patients with LN+ as their sole Peter's criteria (HR 0.58, CI 0.413-0.814; P=.002). Chemoradiation therapy did not improve OS in patients with only positive margins (P=.73), only parametrial invasion (P=.95), or any combination of these 2 factors without LN+ (P=.63). Conclusions: The use of adjuvant CRT after hysterectomy improves OS in patients with high-risk cervical cancer compared with EBRT alone, but this benefit seems to be restricted to patients with LN+. The benefits of adjuvant CRT over EBRT alone in patients with parametrial invasion and/or positive margins (without nodal involvement) are unknown.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Operando structural and chemical evolutions of TiS 2 in Na-ion batteries

Titanium disulfide (TiS 2 ) with high electric conductivity, fast rate capability, and good cycling performance is a promising candidate for electrode material in sodium (Na)-ion batteries. Despite the well-studied electrochemical behaviors of TiS 2 in Li-ion batteries, the detailed reaction mechanism of TiS 2 in Na-ion batteries is not yet fully understood due to a more complex multi-phase conversion process. In this work, reactions of TiS 2 in Na-ion batteries are investigated via a multi-modal synchrotron approach: operando X-ray Absorption Spectroscopy (XAS) – including X-ray Absorption Near-Edge Structure (XANES) and Extended X-ray Absorption Fine Structure (EXAFS) – and ex situ X-ray Powder Diffraction (XPD), coupled with computational modeling. Operando XANES spectra indicate that the redox reactions occur in both Ti and S during the electrochemically driven phase transformation. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) analysis of XAS suggests that different numbers of components are involved in the lithiation and sodiation of TiS 2 , with the sodiation including at least one intermediate phase in addition to the starting material and the final sodiation product. Ex situ XPD and Rietveld refinement further determined and quantified the unknown phases, showing that three phases, TiS 2 , Na 0.55 TiS 2 , and NaTiS 2 , participate in the sodiation of TiS 2 . Operando EXAFS results show the changes in the Ti–Ti coordination number and interatomic distance. This explains the coulombic efficiency decay due to the incomplete recovery of the coordination number of Ti after cycling. Overall, this work reveals the reaction mechanism occurring in Na–TiS 2 batteries with a greater quantitative understanding of the structural evolution. By combining the multi-modal synchrotron approach and computational work, this study provides a framework for studying a broader range of electrochemically driven phase-transformation systems towards advanced energy storage and conversion applications.

25 ENERGY STORAGE↗

Concurrent determination of nanocrystal shape and amorphous phases in complex materials by diffraction scattering computed tomography

Advanced functional materials often contain multiple phases which are (nano)crystalline and/or amorphous. The spatial distribution of these phases and their properties, including nanocrystallite size and shape, often drives material function yet is difficult to obtain with current experimental techniques. This article describes the use of diffraction scattering computed tomography, which maps wide-angle scattering information onto sample space, to address this challenge. The wide-angle scattering signal contains information on both (nano)crystalline and amorphous phases. Rietveld refinement of reconstructed diffraction patterns is employed to determine anisotropic nanocrystal shapes. The background signal from refinements is used to identify contributing amorphous phases through multivariate curve resolution. Thus it is demonstrated that reciprocal space analysis in combination with diffraction scattering computed tomography is a very powerful tool for the complete analysis of complex multiphase materials such as energy devices.

Birkbak, Mie Elholm↗

CCN activity and organic hygroscopicity of aerosols downwind of an urban region in central Amazonia: seasonal and diel variations and impact of anthropogenic emissions

Abstract. During the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign, size-resolved cloud condensation nuclei (CCN) spectra were characterized at a research site (T3) 60 km downwind of the city of Manaus, Brazil, in central Amazonia for 1 year (12 March 2014 to 3 March 2015). Particle hygroscopicity (κCCN) and mixing state were derived from the size-resolved CCN spectra, and the hygroscopicity of the organic component of the aerosol (κorg) was then calculated from κCCN and concurrent chemical composition measurements. The annual average κCCN increased from 0.13 at 75 nm to 0.17 at 171 nm, and the increase was largely due to an increase in sulfate volume fraction. During both wet and dry seasons, κCCN, κorg, and particle composition under background conditions exhibited essentially no diel variations. The constant κorg of ∼ 0. 15 is consistent with the largely uniform and high O : C value (∼ 0. 8), indicating that the aerosols under background conditions are dominated by the aged regional aerosol particles consisting of highly oxygenated organic compounds. For air masses strongly influenced by urban pollution and/or local biomass burning, lower values of κorg and organic O : C atomic ratio were observed during night, due to accumulation of freshly emitted particles, dominated by primary organic aerosol (POA) with low hygroscopicity, within a shallow nocturnal boundary layer. The O : C, κorg, and κCCN increased from the early morning hours and peaked around noon, driven by the formation and aging of secondary organic aerosol (SOA) and dilution of POA emissions into a deeper boundary layer, while the development of the boundary layer, which leads to mixing with aged particles from the residual layer aloft, likely also contributed to the increases. The hygroscopicities associated with individual organic factors, derived from PMF (positive matrix factorization) analysis of AMS (aerosol mass spectrometry) spectra, were estimated through multivariable linear regression. For the SOA factors, the variation of the κ value with O : C agrees well with the linear relationship reported from earlier laboratory studies of SOA hygroscopicity. On the other hand, the variation in O : C of ambient aerosol organics is largely driven by the variation in the volume fractions of POA and SOA factors, which have very different O : C values. As POA factors have hygroscopicity values well below the linear relationship between SOA hygroscopicity and O : C, mixtures with different POA and SOA fractions exhibit a steeper slope for the increase in κorg with O : C, as observed during this and earlier field studies. This finding helps better understand and reconcile the differences in the relationships between κorg and O : C observed in laboratory and field studies, therefore providing a basis for improved parameterization in global models, especially in a tropical context.

Thalman, Ryan↗