Yendle Barwise

Yendle Barwise

Postgraduate Researcher
MSc Conservation and Land Management; BA (Hons) English Studies


My research project


EDWARD YENDLE BARWISE, PRASHANT KUMAR (2021)Designing green infrastructure for urban air pollution mitigation

Green infrastructure (GI) includes trees, hedges, individual shrubs, green walls, and green roofs. GI offers many different benefits or services, including flood risk mitigation, microclimate regulation, carbon sequestration, improved health and wellbeing and – the focus of this document – air pollution abatement. Air pollution comprises variable quantities of many different types of pollutants, including gaseous pollutants, such as nitrous oxides (NOx) and particulate matter (PM), which is composed of particles such as black carbon (BC). Road traffic is a dominant source of air pollution in urban areas globally. In near-road environments, vegetation can act as a barrier between traffic emissions and pedestrians (figure below), by collecting pollutants and/or redirecting the flow of polluted air. This document summarises best practice regarding GI implementation for improved urban air quality and reduced pedestrian exposure to air pollution. Generic (i.e. not site-specific) recommendations are offered for typical urban environments. These recommendations are based upon contemporary scientific evidence and knowledge, and may therefore be subject to modification as the evidence base develops. This guidance document consolidates major findings from relevant publications, including a detailed report on the relationship between vegetation and urban air quality, review articles and other guidance documents.

Prashant Kumar, Sarkawt Hama, Hamid Omidvarborna, Ashish Sharma, Jeetendra Sahani, K.V Abhijith, Sisay E. Debele, Juan C. Zavala-Reyes, Yendle Barwise, Arvind Tiwari (2020)Temporary reduction in fine particulate matter due to ‘anthropogenic emissions switch-off’ during COVID-19 lockdown in Indian cities, In: Sustainable Cities and Society102382 Elsevier

The COVID-19 pandemic elicited a global response to limit associated mortality, with social distancing and lockdowns being imposed. In India, human activities were restricted from late March 2020. This ‘anthropogenic emissions switch-off’ presented an opportunity to investigate impacts of COVID-19 mitigation measures on ambient air quality in five Indian cities (Chennai, Delhi, Hyderabad, Kolkata, and Mumbai), using in-situ measurements from 2015 to 2020. For each year, we isolated, analysed and compared fine particulate matter (PM2.5) concentration data from 25 March to 11 May, to elucidate the effects of the lockdown. Like other global cities, we observed substantial reductions in PM2.5 concentrations, from 19 to 43% (Chennai), 41–53 % (Delhi), 26–54 % (Hyderabad), 24–36 % (Kolkata), and 10–39 % (Mumbai). Generally, cities with larger traffic volumes showed greater reductions. Aerosol loading decreased by 29 % (Chennai), 11 % (Delhi), 4% (Kolkata), and 1% (Mumbai) against 2019 data. Health and related economic impact assessments indicated 630 prevented premature deaths during lockdown across all five cities, valued at 0.69 billion USD. Improvements in air quality may be considered a temporary lockdown benefit as revitalising the economy could reverse this trend. Regulatory bodies must closely monitor air quality levels, which currently offer a baseline for future mitigation plans.

Yendle Barwise, Prashant Kumar (2020)Designing vegetation barriers for urban air pollution abatement: a practical review for appropriate plant species selection, In: npj Climate and Atmospheric Science Nature Research

Vegetation can form a barrier between traffic emissions and adjacent areas, but the optimal configuration and plant composition of such green infrastructure (GI) are currently unclear. We examined the literature on aspects of GI that influence ambient air quality, with a particular focus on vegetation barriers in open-road environments. Findings were critically evaluated in order to identify principles for effective barrier design, and recommendations regarding plant selection were established with reference to relevant spatial scales. As an initial investigation into viable species for UK urban GI, we compiled data on 12 influential traits for 61 tree species, and created a supplementary plant selection framework. We found that if the scale of the intervention, the context and conditions of the site, and the target air pollutant type are appreciated, the selection of plants that exhibit certain biophysical traits can enhance air pollution mitigation. For super-micrometre particles, advantageous leaf micromorphological traits include the presence of trichomes and ridges or grooves. Stomatal characteristics are more significant for sub-micrometre particle and gaseous pollutant uptake, although we found a comparative dearth of studies into such pollutants. Generally advantageous macromorphological traits include small leaf size and high leaf complexity, but optimal vegetation height, form and density depend on planting configuration with respect to the immediate physical environment. Biogenic volatile organic compound and pollen emissions can be minimised by appropriate species selection, although their significance varies with scale and context. While this review assembled evidence-based recommendations for practitioners, several important areas for future research were identified.

Yendle Barwise, Prashant Kumar, Arvind Tiwari, Fahad Rafi-Butt, Aonghus McNabola, Stuart Cole, Benjamin C.T Field, Justine Fuller, Jeewaka Mendis, Kayleigh J Wyles (2021)The co-development of HedgeDATE, a public engagement and decision support tool for air pollution exposure mitigation by green infrastructure, In: Sustainable Cities and Society Elsevier

There is a lack of clear guidance regarding the optimal configuration and plant composition of green infrastructure (GI) for improved air quality at local scale. This study aimed to co-develop (i.e. with feedback from end-users) a public engagement and decision support tool, to facilitate effective GI design and management for air pollution abatement. The underlying model uses user-directed input data (e.g. road type) to generate output recommendations (e.g. plant species) and pollution reduction projections. This model was computerised as a user-friendly tool named HedgeDATE (Hedge Design for Abatement of Traffic Emissions). A workshop generated feedback on HedgeDATE, which we also discuss. We found that data from the literature can be synthesised to predict air pollutant exposure and abatement in open road environments. However, further research is required to describe pollutant decay profiles under more diverse roadside scenarios (e.g. split-level terrain) and to strengthen projections. Workshop findings validated the HedgeDATE concept and indicated scope for uptake. End-user feedback was generally positive, although potential improvements were identified. For HedgeDATE to be made relevant for practitioners and decision-makers, future iterations will require enhanced applicability and functionality. This work sets the foundation for the development of advanced GI design tools for reduced pollution exposure.

EDWARD YENDLE BARWISE, Abhijith Kooloth Valappil, ARVIND TIWARI, GOPINATH KALAIARASAN, HAMID OMIDVARBORNA, Thor-Bjørn Ottosen, SARKAWT MUHAMMAD LATEEF HAMA, SISAY ESHETU DEBELE, Sachit Mahajan, Aakash Rai, PRASHANT KUMAR Green infrastructure and air quality: impacts from research in open road environments
Mamatha Tomson, PRASHANT KUMAR, Yendle Barwise, Pascal Perez, Hugh Forehead, Kristine French, Lidia Morawska, John F Watts (2021)Green infrastructure for air quality improvement in street canyons, In: Environment International146pp. 106288-106288 Elsevier Ltd

Street canyons are generally highly polluted urban environments due to high traffic emissions and impeded dispersion. Green infrastructure (GI) is one potential passive control system for air pollution in street canyons, yet optimum GI design is currently unclear. This review consolidates findings from previous research on GI in street canyons and assesses the suitability of different GI forms in terms of local air quality improvement. Studies on the effects of various GI options (trees, hedges, green walls, green screens and green roofs) are critically evaluated, findings are synthesised, and possible recommendations are summarised. In addition, various measurement methods used for quantifying the effectiveness of street greening for air pollution reduction are analysed. Finally, we explore the findings of studies that have compared plant species for pollution mitigation. We conclude that the influences of different GI options on air quality in street canyons depend on street canyon geometry, meteorological conditions and vegetation characteristics. Green walls, green screens and green roofs are potentially viable GI options in existing street canyons, where there is typically a lack of available planting space. Particle deposition to leaves is usually quantified by leaf washing experiments or by microscopy imaging techniques, the latter of which indicates size distribution and is more accurate. The pollutant reduction capacity of a plant species largely depends on its macromorphology in relation to the physical environment. Certain micromorphological leaf traits also positively correlate with deposition, including grooves, ridges, trichomes, stomatal density and epicuticular wax amount. The complexity of street canyon environments and the limited number of previous studies on novel forms of GI in street canyons mean that offering specific recommendations is currently unfeasible. This review highlights a need for further research, particularly on green walls and green screens, to substantiate their efficacy and investigate technical considerations.