Novel informatic software for automated aerosol component property predictions and ensemble predictions for direct model - measurement comparison

Lead Research Organisation: University of Manchester
Department Name: Earth Atmospheric and Env Sciences

Abstract

Atmospheric aerosol particles, or particulate matter suspended in the atmosphere, are highly important yet highly uncertain components of the earths climate system and key determinants of air quality. Properties which determine these highly uncertain impacts are linked at the most fundamental level to the chemical components which may reside in the particle. Both inorganic and organic material can transfer between the gas and particle phase. Inorganic material is restricted to a few well-understood compounds. However, organic material can comprise many thousands, as yet largely unidentified, compounds with a vast range of properties. Owing to the complexity and diversity of atmospheric aerosol components, quantification of the properties that determine their highly uncertain climatic and human health impacts requires the development and application of novel technological applications such as the informatic software proposed here. Firstly, we must be able to predict how ever many thousands of components can exist in particulate matter. Specifically, predicting the evolution of aerosol requires calculation of the distribution of all components between the gas and particle phases which in turn requires knowledge of all component vapour pressures and other thermodynamic properties. Furthermore, the physical properties of the aerosol determining their climatic impacts require detailed knowledge of fundamental properties of all components. The many thousands of individual aerosol components ensure that explicit manual calculation of these properties is laborious, time-consuming and often impossible. Thus, automation is necessary. Secondly, to identify key components and resolve their environmental impacts we must be able to replicate chemical characteristics measured in real/simulated atmospheres. A comprehensive experimental determination of individual organic components of atmospheric aerosols is not available, leading to indirect measurements on 'chemical signatures' of mixtures. Through automation of component property estimation, combined with a gas/aerosol transfer model, these 'chemical sigmatures' as determined by state-of-the-science atmospheric sampling instrumentation will be predicted. This will be achieved by calculating instrument response functions with the predicted abundance of all components. Again, the prediction (and combination) of instrument response functions for each individual component lends itself to automation due to the vast numbers involved. The informatics suite will be built using a flexible high-level portable programming language and an open source chemical informatics package that is designed to allow extraction of appropriate sub-molecular information relevant for each property estimation method.

Publications

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O'Meara S (2014) An assessment of vapour pressure estimation methods. in Physical chemistry chemical physics : PCCP

 
Description The impacts of aerosol on climate are still credited with the largest uncertainty in climate forcing and a large part of the radiatively active boundary layer sub-micron aerosol burden is organic. In this project we developed new informatics software for predicting the properties of complex organic molecules and ensemble aerosol mixtures. The software has now been made available to the research community via an online portal. The tools developed have allowed us to evaluated our current predictive capability in this area and has identified the need for additional research programs including both laboratory and field studies. It has also served as a great example of how developments in other fields can be leveraged in order to meet objectives in an efficient and cost effective manner.
Exploitation Route The automated software tools we have developed can be used to predict the properties of any number of chemical components. Similarly, the algorithms now implemented in these automated tools have the potential to model complex systems within process engineering. We are already exploring funding mechanisms to take this forward. Developing the skillset within universities to perform the research for which this software is designed can take many years and much expense. The software developed has now been made available to the research community via an online portal. This ensures maximum outreach and provides the community with the tools to tackle this complex problem of understanding the role aerosol particles have on the environment. The tools developed are also now being fed into existing NERC funded programes to develop methods for better understanding the role aerosol particles have in the atmosphere.
Sectors Chemicals,Digital/Communication/Information Technologies (including Software),Environment

 
Description We have engaged with a broad range of researchers from across multiple disciplines. Aside from using the tools developed in new research papers, we hope that this will enable a broad range of new research avenues. We have already been given notifcation that our tools are now used across multiple areas, with automatic links to the new web facility.
First Year Of Impact 2015
Sector Chemicals,Environment,Manufacturing, including Industrial Biotechology
 
Title UManSysProp 
Description UManSysProp is an online facility for calculating the properties of individual organic molecules, ensemble mixtures and aerosol particles. Built using open source chemical informatics, and currently hosted at the University of Manchester, the facilities are provided via: a browser-friendly web-interface. a programmer friendly JSON API that enables you to call our suite of tools from your own code. access to the source code GitHub respository for all predictive techniques provided on the site. 
Type Of Material Computer model/algorithm 
Year Produced 2015 
Provided To Others? Yes  
Impact The facility is too new for assessing any impact, through appropriate reference to our description paper. Nonetheless, we receive roughly 800 users per month on the site already and is being used as a focal point for a NERC international network grant starting this year [2016]. 
URL http://umansysprop.seaes.manchester.ac.uk/
 
Description Collaborations with international research institutes 
Organisation California Institute of Technology
Country United States 
Sector Academic/University 
PI Contribution In the first instance, the academic community has openly welcomed the facilities we have developed during this grant. Specifically we are in the process of incorporating additional predictive techniques with the California Institute of Technology and the Belgian Institute for Space Aeronomy. This arose through advertisements and presentations at international conferences. We are currently exploring potential routes for future commercial exploitation.
Start Year 2011
 
Title New online and open source facility for predicting the properties of organic molecules and mixtures. 
Description UManSysProp is an online facility for calculating the properties of individual organic molecules, ensemble mixtures and aerosol particles. Built using open source chemical informatics, and currently hosted at the University of Manchester, the facilities are provided here via: a browser-friendly web-interface. a programmer friendly JSON API that enables you to call our suite of tools from your own code. access to the source code behind all predictive techniques provided on the site. 
Type Of Technology Webtool/Application 
Year Produced 2016 
Impact There have been 1800 unique users within its first 9 months of deployment, including 4 references since the paper release. 
URL http://umansysprop.seaes.manchester.ac.uk/
 
Title PyBox is a Python based box-model generator and simulator designed for atmospheric chemistry and aerosol studies. 
Description PyBox is a Python based box-model generator and simulator designed for atmospheric chemistry and aerosol studies. The first phase of the PyBox project is to develop a gas phase model, using the reaction information within the Master Chemical Mechanism (MCM) as the basis, coupled with an idealised sectional aerosol model. PyBox also relates component properties, using molecular structural information, through the UManSysProp informatics suite. Any public release will occur according to new processes added, agreement from any partner contributions and/or associated peer-review papers. 
Type Of Technology Software 
Year Produced 2018 
Open Source License? Yes  
Impact N/A srtill in adoption phase 
URL http://joss.theoj.org/papers/10.21105/joss.00755