- Abhijith, K. V., Kumar, P., 2020. Quantifying particulate matter reduction and their deposition on the leaves of green infrastructure. Environmental Pollution. Vol: 265, article: 114884.
- Arcucci, R. Effective Data Assimilation with Machine Learning - Data Science Book 2020, accepted.
- Arcucci, R., Mottet, L., Quilodran Casas, C. A., Guitton, F., Pain, C. and Guo, Y., 2020. Adaptive Domain Decomposition for Effective Data Assimilation - Lecture Notes in Computer Science book series (EuroPAR2019).
- Arcucci, R., Moutiq, L. and Guo, Y. Scalable Weak Constraint Gaussian Processes. Lecture Notes in Computer Science book series (ICCS 2020) , accepted.
- Arcucci, R., Quilodran Casas, C., Xiao, D., Mottet, L., Fang, F., Wu, P., Pain, C. and Guo, Y., 2020. A Domain Decomposition Reduced Order Model with Data Assimilation (DD-RODA). Advances in Parallel Computing. Vol: 36, pages: 189-198, DOI: 10.3233/APC200040.
- Barwise, Y., Kumar, P., 2020. Designing vegetation barriers for urban air pollution abatement: a practical review for appropriate plant species selection. npj Climate and Atmospheric Sciences. Vol: 3, article: 12.
- Cheng, M., Fang, F., Pain, C.C. and Navon, I. M., 2020. An advanced hybrid deep adversarial autoencoder for parameterized nonlinear fluid flow modelling. Computer Methods in Applied Mechanics and Engineering, Vol: 372, article: 113375.
- Cheng, M., Fang, F., Kinouchi, T., Navon, I. M. and Pain, C. C., 2020. Long lead-time daily and monthly streamflow forecasting using machine learning methods. Journal of Hydrology, Vol: 590, article: 125376.
- Cheng, M., Fang, F., Pain, C. C. and Navon, I. M., 2020. Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network. Computer Methods in Applied Mechanics and Engineering, Vol: 365, article: 113000.
- Dur, T. , Arcucci, R., Mottet, L., Molina Solana, M., Pain, C., Guo, Y., 2020. Weak Constraint Guassian Process for optimal sensor placement. Journal of Computational Science. Vol: 42, DOI: 10.1016/j.jocs.2020.101110.
- Hu, R., Fang, F., Pain, C. C., Navon, I. M., 2019. Rapid spatio-temporal flood prediction and uncertainty quantification using a deep learning method. Journal of Hydrology. Vol: 575, article: 911920.
- Kumar, P., Druckman, A., Gallagher, J., Gatersleben, B., Allison, S., Eisenman, T.S., Hoang, U., Hama, S., Tiwari, A., Sharma, A., Abhijith, KV, Adlakha, D., McNabola, A., Astell-Burt, T., Feng, X., Skeldon, A.C., de Lusignan, S., Morawska, L., 2019. The Nexus between Air Pollution, Green Infrastructure and Human Health. Environment International. Vol: 133, article: 105181.
- Kumar, P., Hama, S., Omidvarborna, H., Sharma, A., Sahani, J., Abhijith K.V., Debele, S. E., Zavala-Reyes, J. C., Barwise, Y., Tiwari, A., 2020. Temporary reduction in fine particulate matter due to ‘anthropogenic emissions switch-off’ during COVID-19 lockdown in Indian cities. Science Direct. Vol: 62, article: 102382.
- Kumar, P., Kalaiarasan, G., Porter, A. E., Pinna, A., Kłosowski, M. M., Demokritou, P., Chung K. F., Pain, C. C., Arvind, D. K., Arcucci, R., Adcock, I. M., Dilliway, C., 2020. An overview of methods of fine and ultrafine particle collection for physicochemical characterisation and toxicity assessments. Science of The Total Environment, Vol: TBC, article 143553.
- Kumar, P., Omidvarborna, H., Francesco, P., Lewin, N., 2020. A primary school driven initiative to influence commuting style for dropping-off and picking-up of pupils. Science of the Total Environment. Vol: 727, article: 138360.
- Kumar, P., Morawska, L., 2020. Could fighting airborne transmission be the next line of defence against COVID-19 spread? City and Environment Interactions. Vol: 4, article: 100033.
- Mack, J., Arcucci, R., Molina-Solana, M., Guo Y., 2020. Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation. Computer Methods in Applied Mechanics and Engineering. Vol: 372, article: 113291.
- Mortaz, E., Zadin, S. S., Shahir, M., Folkerts, G., Garssen, J., Mumby, S., Adcock, I. M., 2019. Does Neutrophil Phenotype Predict the Survival of Trauma Patients? Frontiers in Immunology. 10:2122. doi: 10.3389/fimmu.2019.02122
- Quilodrán Casas, C., Arcucci, R., Guo, Y., 2020. Reduced order deep Bayesian correction for urban air pollution physics and its healthcare applications. KDD 2020. Manuscript submitted to the Applied Data Science track of the KDD 2020 conference. (Under review)
- Quilodrán Casas, C., Arcucci, R., Guo, Y., 2020. Urban air pollution forecasts generated from latent space representation. International Conference on Learning Representation 2020; "Integration of Deep Neural Models and Differential Equations" workshop.
- Quilodrán Casas, C., Arcucci, R., Wu, P., Pain, C., Guo, Y., 2020. A reduced order deep data assimilation model. Physica D. Vol: 412, article: 132615.
- Tajnafoi, G., Arcucci R., Mottet, L. Vouriot, C., Molina Solana, M., Pain, C., Guo, Y. Variational Gaussian Processes for optimal sensor placement. Journal of Applied Mathematics, under review.
- Tiwari, A., Kumar, P., 2020. Integrated dispersion-deposition modelling for air pollutant reduction via green infrastructure at an urban scale. Science of the Total Environment. Vol: 723, article: 138078.
- Tiwari, A., Kumar, P., Kalaiarasan, G., Ottosen, T-B., 2020. The impacts of existing and hypothetical green infrastructure scenarios on urban heat island formation. Environmental Pollution, accepted.
- Wu, P., Sun, J., Chang, X., Zhang, W., Arcucci, R., Guo, Y., Pain, C.C., 2020. Data-driven reduced order model with temporal convolutional neural network. Computer Methods in Applied Mechanics and Engineering. Vol: 360, article: 112766.
- Xiao, D., Fang, F., Zheng, J., Pain, C. C., Navon, I. M., 2019. Machine learning-based rapid response tools for regional air pollution modelling. Atmospheric Environment. Vol: 199, article: 463473.
- Zheng, J., Fang, F., Wang, Z., Zhu, J., Li, J., Li, J., Xiao, H., Pain, C.C., 2020. A new anisotropic adaptive mesh photochemical model for ozone formation in power plant plumes. Atmospheric Environment, Vol: 229, article: 117431, ISSN: 1352-2310.
Presentations, conferences and workshops
- Fang. F., Multiscale physical green and thermal dynamical modelling in urban environment, the international conference on Sustainable Development in Building and Environment and International Forum of Green Buildings and Healthy Buildings, SuDBE2020, China, 26, August 2020.
- Dr Xiaofei Wu presented a talk entitled ‘Processes in the development of the Fluidity-Urban model’ to a MAGIC consortium meeting on 13 October 2020.
- Professor Kian Fan Chung gave a plenary talk on “Exposomes and Gene Interaction in Asthma” at the European Academy of Allergy and Immunology Digital Congress on 6 June 2020, describing the INHALE project amongst several Exposome projects.
- Dr Rossella Arcucci organised the second edition of the Workshop on Machine Learning and Data Assimilation for Dynamical Systems (MLDADS) 2020 - ICCS 3-5 June 2020.
- Dr Rossella Arcucci was a Keynote speaker at SIAM-IMA (Institute of Mathematics and its applications) with a talk entitled "Artificial Neural Network at the service of Data Assimilation" on 1 June 2020, online.
- Dr Rossella Arcucci presented a talk entitled "Data Assimilation and Machine Learning" to the Leverhulme Wildfires workshop ‘Approaches to Data Analysis’ on 19 May 2020, online.
- Dr Rossella Arcucci presented a talk entitled "Data Learning: Data Assimilation with Machine Learning" at the University of Reading on 11 March 2020.
- Professor Chris Pain and Professor Alex Porter presented the INHALE project at the 2019 Physics of Life Town Meeting at the Royal Society on 3rd December 2019.
- Professor Arvind presented a ticketed invited talk entitled “Every breath you take” at the 2019 Edinburgh International Science Festival, which was reviewed in Lancet Respiratory Medicine (pdf).
- Professor Arvind was invited to participate on an expert panel in BodyNets 2019, Florence, Italy on 2-3 Oct 2019 on the topic "Smart IoT and big data for intelligent health management”, and present at The Royal Society Science+ meeting on Air Quality, past, present and future on 11-12 Nov 2019.
- Further to the aforementioned publication of ‘Temporary reduction in fine particulate matter due to ‘anthropogenic emissions switch-off’ during COVID-19 lockdown in Indian cities’, a press article was published by the University of Surrey.
- Imperial College London published an article ‘Air pollution during lockdown and beyond’ reporting that air pollution monitors had been installed near South Kensington campus to measure pollution during and after the COVID-19 Lockdown.
- Further to the aforementioned publication of ‘Could fighting airborne transmission be the next line of defence against COVID-19 spread?’, a press article was published by the University of Surrey.
- INHALE research is being disseminated via @ImperialRSM, @AirPollSurrey & @GuildfordLivingLab Twitter accounts as well as investigators account @pk_shishodia – usually linked with programme Twitter @PhysicsofLifeUK.
- Further to the aforementioned publication of ‘The Nexus between Air Pollution, Green Infrastructure and Human Health’, the associated press release was widely published by many media outlets including Science Daily, EnvironTech and DovMed.
- Imperial College London published an article ‘Study to provide new insights into health impact of urban pollution’.
- Further to the aforementioned publication of ‘Designing vegetation barriers for urban air pollution abatement: a practical review for appropriate plant species selection’ the associated press release generated media interest, for example in the DailyMail, BBC and the Times.
- Further to the aforementioned publication of ‘A primary school driven initiative to influence commuting style for dropping-off and picking-up of pupils’, the associated press release generated media interest, for example in the Times.
Summarising various pieces of work
- Kumar, P., Omidvarborna, H., Barwise, Y., Tiwari, A. Mitigating Exposure to Traffic Pollution in and around Schools: Guidance for Children Schools and Local Communities, accepted.
- Prashant, K., Abhijith, K. V., Barwise, Y. (2019). Implementing Green Infrastructure for Air Pollution Abatement: General Recommendations for Management and Plant Species Selection. 10.6084/m9.figshare.8198261.v1.