To quantify the volatility of organic aerosols (OA), a comprehensive campaign was conducted in the Chinese megacity. Volatility distributions of OA and particle‐phase organic nitrate (pON) were estimated based on five methods: (a) empirical method and (b) kinetic model based on the measurement of a thermodenuder (TD) coupled with an aerosol mass spectrometer; (c) Formula‐based SIMPOL model‐driven method; (d) Element‐based estimations using molecular formula measurements of OA; and (e) gas/particle partitioning. Our results demonstrate that the ambient OA volatility distribution shows good agreement between the two heating methods and the formula‐based method when assuming ambient OA was mainly composed of organic nitrate (pON), organic sulfate and acid groups using the SIMPOL model. However, the element‐based method tends to overestimate the volatility of OA compared to the above three methods, suggesting large uncertainties in the parameterizations or in the representativeness of the molecular measurements that need further refinement. The volatility of ambient OA is generally lower than that of the laboratory‐derived secondary OA, emphasizing the impact of aging. A large fraction at the higher and lower volatility ranges (approximately log
- Award ID(s):
- 2045332
- PAR ID:
- 10542215
- Publisher / Repository:
- Zenodo
- Date Published:
- Subject(s) / Keyword(s):
- cheminformatics chemometrics metabolomics
- Format(s):
- Medium: X
- Right(s):
- MIT License
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract C* ≤ −9 and ≥2 μg m−3) was found for pON, implying the importance of both extremely low volatile and semi‐volatile species. Overall, this study evaluates different methods for volatility estimation and gives new insight into the volatility of OA and pON in urban areas. -
Volatility describes the tendency for a compound to partition into the gas phase and volatile metabolites facilitate unique biological interactions which have an influence on Earth's atmospheric physics and chemistry. Estimating which metabolites may be volatile is difficult, especially for those which do not have measured vapor pressures. Volcalc is a newly developed vapor pressure estimation tool which utilizes the SIMPOL.1 method, allowing users to rapidly identify plausible volatile metabolites within the Kyoto Encyclopedia for Genes and Genomes (KEGG) database. Here, we estimate the volatiles of all KEGG metabolites and associate them with KEGG reactions, enzymes, orthologs (KOs) and whole genomes within the KEGG database. This information may be used to identify which genes or species may be linked to particular forms of volatile metabolism, for the purpose hypothesis generation and integration into additional bioinformatics pipelines. This data is listed as a compliment to the publication "Automating methods for estimating metabolite volatility". The column "Paper" indicates whether the listed species is one from the subset analyzed within the data for Figure 3.more » « less
For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu -
The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called
volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate howvolcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. Withvolcalc , we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. Thevolcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems. -
Abstract In this paper we study the defocusing, cubic nonlinear wave equation in three dimensions with radial initial data. The critical space is $\dot{H}^{1/2} \times \dot{H}^{-1/2}$. We show that if the initial data is radial and lies in $\left (\dot{H}^{s} \times \dot{H}^{s - 1}\right ) \cap \left (\dot{H}^{1/2} \times \dot{H}^{-1/2}\right )$ for some $s> \frac{1}{2}$, then the cubic initial value problem is globally well-posed. The proof utilizes the I-method, long time Strichartz estimates, and local energy decay. This method is quite similar to the method used in [11].more » « less
-
We consider whether distributed subgradient methods can achieve a linear speedup over a centralized subgradient method. While it might be hoped that distributed network of n nodes that can compute n times more subgradients in parallel compared to a single node might, as a result, be n times faster, existing bounds for distributed optimization methods are often consistent with a slowdown rather than speedup compared to a single node. We show that a distributed subgradient method has this “linear speedup” property when using a class of square-summable-but-not-summable step-sizes which include 1/t^β when β ∈ (1/2,1); for such step-sizes, we show that after a transient period whose size depends on the spectral gap of the network, the method achieves a performance guarantee that does not depend on the network or the number of nodes. We also show that the same method can fail to have this “asymptotic network independence” property under the optimally decaying step-size 1/t^{1/2} and, as a consequence, can fail to provide a linear speedup compared to a single node with 1/t^{1/2} step-size.more » « less