There are currently inadequacies in our representations of physical processes in indoor air chemistry models. We need to understand and parameterise these processes better if we want our model predictions to improve. This is important as models give us additional information in situations where measurements cannot be made and provide additional insight into chemical processing indoors. Having confidence in models also means that we can use them to explore the impacts of emerging pollutants or predict future IAQ problems. 

Although there are many differences between indoor and outdoor air chemistry, there are also many similarities. Deposition to and emissions from surfaces, particle formation and photolysis processes happen indoors and outdoors, although the rates may be different. Working more closely with outdoor air modellers should be of benefit to both communities (WG2 report). 

There are several good sources of information around indoor air chemistry models and what we still need to understand (e.g. our editorial, or Section 3 of the Summary Report that resulted from our WG1 activities). Section 2 of the Final report from WG2, also summarises what we can learn from outdoor air models that could potentially be useful for indoor environments. Morrison et al. (2017) discussed what a framework for indoor air chemistry modelling might look like, whilst Shiraiwa et al. (2019) reported on the development of a new modelling consortium for indoor environments called MOCCIE (MOdelling Consortium for the Chemistry of Indoor Environments): MOCCIE aims to connect models over a range of temporal (from seconds to days) and spatial (from molecular to room) scales. Recent studies have shown that large gains in our understanding are made when modellers are fully integrated into measurement campaigns (e.g. HOMEChem). Measured data can be used to evaluate models, whilst the improved models inform future measurements.

There are a number of models/model systems in use by the outdoor air pollution community. Many of them are open source community models built on cores developed by organisations such as e.g. NOAA, NCAR or the European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West (EMEP MSC-W), which then coordinate further model developments though open fora of developers and users. Thanks to this overarching organisation of model development, outdoor air models often consist of modules which can be exchanged and implemented across many models. 

Extensive effort has also been spent on integration of the knowledge, benchmarking of the models, and development of air quality monitoring and modelling infrastructures. Indoor air modelling is at a much less advanced stage, and developing such protocols and procedures based on the knowledge from the outdoor air community would be very valuable.

The following outputs from outdoor air modellers could inform indoor air models:

• Outdoor pollution levels in European regions and cities (CAMS, EMEP, national met-offices, FAIRMODE & HARMO, EIONET, Nordic Welfare) where indoor air models need this information to drive the indoor chemistry.

• For urban/local studies, prognostics of meteorological variables, including data from at the least meso-meteorological scales, such as wind velocity and direction, temperature and relative humidity fields. For microscale studies, 3D wind, temperature and pressure fields, namely around buildings (CFD models)

• Development and evaluation of indoor air intervention strategies that consider outdoor pollution as an important chemical driver and/or health impact.

• Identify existing outdoor air models and the modules/information within them that could be integrated within indoor models. This might include information on processes such as deposition to surfaces, particle formation and other issues as highlighted in our WG2 report.

• Develop a standard protocol to evaluate results, ensure transparency, and offer proper documentation for each model. This could be done through learning from outdoor air modelling communities (e.g. HARMO and FAIRMODE) through common workshops, working groups and networks. 

• Integrate the models fully into future measurement campaigns and carry out thorough evaluations. Note where there are discrepancies and use these to drive the next set of measurements.

A starting place would be urban environments, perhaps with a theme of investigating ozone and/or ozone-initiated chemistry as a pollutant relevant for both indoors and outdoors, for large-scale exposure assessment studies (and in the context of climate-change).