Not all brownfields are equal: a typological assessment reveals hidden green space in the city

While the role of urban green space in mitigating environmental hazards and enhancing urban resilience is widely recognised, the current or potential contribution of brownfield land to urban green infrastructure and ecosystem services has been largely overlooked by planning legislation. The perception of brownfield as low value spaces has instead driven a focus on brownfield-first redevelopment, and thus, this dynamic resource is quickly being lost. This research, based on GIS and remote sensing data, develops a novel hierarchical brownfield classification methodology to understand the nature and distribution of brownfield, using k-means clustering of several physical attributes, which can be used for a range of objectives and is widely applicable to post-industrial cities. Application of the methodology to the case study, Greater Manchester, UK, produced a typology of twenty-six brownfield types with distinct characteristics and differing spatial patterns across the city. Land cover analysis reveals that over half (51%) of brownfield land is vegetated (comprising 27% trees and shrubs, 24% grass and herbaceous vegetation), highlighting the significant ‘hidden’ green space present on brownfield. Brownfield sites traditionally perceived as difficult to develop (e.g. those with uneven topography, irregular shapes, or a water body), are particularly highly vegetated. Predominantly pervious types are widely distributed across the conurbation, including in built-up areas, which are a principal target for redevelopment, and thus highly vegetated brownfields are likely being lost undetected. Brownfield land is evidently a valuable dynamic resource in post-industrial cities and redevelopment should be planned at the city-scale to ensure careful strategic selection of sites for redevelopment, greening, or interim use based upon their characteristics and location

Mapping regulating ecosystem service deprivation in urban areas: A transferable high-spatial resolution uncertainty aware approach

Maps of regulating urban ecosystem services (UES) aid identification of priority areas for green–blue infrastructure investment to improve urban resilience to environmental hazards. Current mapping approaches however may present coarse spatial resolutions, and often fail to consider how UES flows serve resident demand at the appropriate micro-scale. In addition, prohibitive costs involved in collecting primary data to validate UES model parameters to local conditions may enforce the use of proxy methods, thereby inferring ambiguity in parameterisation and uncertainty in mapping outputs. This study examines both issues through the implementation of a high-spatial resolution approach to map multiple urban regulating ecosystem service (temperature regulation, stormwater absorption, and carbon storage) deprivation in Manchester, UK. Poorly performing UES areas are defined as the lowest 10% combined ecosystem service indicator values (‘coldspots’) at 100m grid resolution. Coldspots are compared to population demand levels, disaggregated from weighted population estimates, indicating neighbourhoods deprived of UES. Ambiguity in proxy method implementation is examined using combinations of UES parameter settings (n = 16) within various demand measures (n = 3) to measure changes in relationships between UES, and variation in final map outputs across the study area. Uncertainty is therefore quantified as an interactive process, whereby input parameter ambiguity affects local uncertainty in map outputs, due to varying landcover composition. As explicit sensitivity analysis in current UES mapping studies is limited, the study demonstrates how ambiguity in method parameterisation may impact UES mapping exercises. Complex interactions governing spatial variance in map uncertainty may therefore be addressed through identification of consistent areas of interest (e.g. hotspots, coldspots) by contrasting outputs realised from different parameterisations. As such, the study demonstrates the mapping approach as a transferable city-wide visualisation tool, using accessible data and methods, to investigate regulating UES deprivation at practical scales required to retrofit existing urban infrastructure with green-blue infrastructure investment

Spatiotemporal variability of nitrogen dioxide (NO2) pollution in Manchester (UK) city centre (2017-2018) using a fine spatial scale single-NOx diffusion tube network

Nitrogen dioxide (NO2) is linked to poor air quality and severe human health impacts, including respiratory and cardiovascular diseases and being responsible annually for approximately 23,500 premature deaths in the UK. Automated air quality monitoring stations continuously record pollutants in urban environments but are restricted in number (need for electricity, maintenance and trained operators), only record air quality proximal to their location and cannot document variability of airborne pollutants at finer spatial scales. As an alternative, passive sampling devices such as Palmes-type diffusion tubes can be used to assess the spatial variability of air quality in greater detail, due to their simplicity (e.g. small, light material, no electricity required) and suitability for long-term studies (e.g. deployable in large numbers, useful for screening studies). Accordingly, a one passive diffusion tube sampling approach has been adapted to investigate spatial and temporal variability of NO2 concentrations across the City of Manchester (UK). Spatial and temporal detail was obtained by sampling 45 locations over a 12-month period (361 days, to include seasonal variability), resulting in 1080 individual NO2 measurements. Elevated NO2 concentrations, exceeding the EU/UK limit value of 40 µg m−3, were recorded throughout the study period (N = 278; 26% of individual measurements), particularly during colder months and across a wide area including residential locations. Of 45 sampling locations, 24% (N = 11) showed annual average NO2 above the EU/UK limit value, whereas 16% (N = 7) showed elevated NO2 (> 40 µg m−3) for at least 6 months of deployment. Highest NO2 was recorded in proximity of highly trafficked major roads, with urban factors such as surrounding building heights also influencing NO2 dispersion and distribution. This study demonstrates the importance of high spatial coverage to monitor atmospheric NO2 concentrations across urban environments, to aid identification of areas of human health concern, especially in areas that are not covered by automated monitoring stations. This simple, reasonably cheap, quick and easy method, using a single-NOx diffusion tube approach, can aid identification of NO2 hotspots and provides fine spatial detail of deteriorated air quality. Such an approach can be easily transferred to comparable urban environments to provide an initial screening tool for air quality and air pollution, particularly where local automated air quality monitoring stations are limited. Additionally, such an approach can support air quality assessment studies, e.g. lichen or moss biomonitoring studies

High spatial resolution assessment of air quality in urban centres using lichen carbon, nitrogen and sulfur contents and stable-isotope-ratio signatures

Air pollution and poor air quality is impacting human health globally and is a major cause of respiratory and cardiovascular disease and damage to human organ systems. Automated air quality monitoring stations continuously record airborne pollutant concentrations, but are restricted in number, costly to maintain and cannot document all spatial variability of airborne pollutants. Biomonitors, such as lichens, are commonly used as an inexpensive alternative to assess the degree of pollution and monitor air quality. However, only a few studies combined lichen carbon, nitrogen and sulfur contents, with their stable-isotope-ratio signatures (δ13C, δ15N and δ34S values) to assess spatial variability of air quality and to ‘fingerprint’ potential pollution sources. In this study, a high-spatial resolution lichen biomonitoring approach (using Xanthoria parietina and Physcia spp.) was applied to the City of Manchester (UK), the centre of the urban conurbation Greater Manchester, including considerations of its urban characteristics (e.g., building heights and traffic statistics), to investigate finer spatial detail urban air quality. Lichen wt% N and δ15N signatures, combined with lichen nitrate (NO3−) and ammonium (NH4+) concentrations, suggest a complex mixture of airborne NOx and NHx compounds across Manchester. In contrast, lichen S wt%, combined with δ34S strongly suggest anthropogenic sulfur sources, whereas C wt% and δ13C signatures were not considered reliable indicators of atmospheric carbon emissions. Manchester’s urban attributes were found to influence lichen pollutant loadings, suggesting deteriorated air quality in proximity to highly trafficked roads and densely built-up areas. Lichen elemental contents and stable-isotope-ratio signatures can be used to identify areas of poor air quality, particularly at locations not covered by automated air quality measurement stations. Therefore, lichen biomonitoring approaches provide a beneficial method to supplement automated monitoring stations and also to assess finer spatial variability of urban air quality

Climate change and the city: Building capacity for urban adaptation

The significant shifts in climate variables projected for the 21st century, coupled with the observed impacts of ongoing extreme weather and climate events, ensures that adaptation to climate change is set to remain a pressing issue for urban areas over the coming decades. This volume of Progress in Planning seeks to contribute to the widening debate about how the transformation of cities to respond to the changing climate is being understood, managed and achieved. We focus particularly on spatial planning, and building the capacity of this key mechanism for responding to the adaptation imperative in urban areas. The core focus is the outcomes of a collaborative research project, EcoCities, undertaken at the University of Manchester's School of Environment and Development. EcoCities drew upon inter-disciplinary research on climate science, environmental planning and urban design working within a socio-technical framework to investigate climate change hazards, vulnerabilities and adaptation responses in the conurbation of Greater Manchester, UK. Emerging transferable learning with potential relevance for adaptation planning in other cities and urban areas is drawn out to inform this rapidly emerging international agenda. Approaches to build adaptive capacity challenge traditional approaches to environmental and spatial planning, and the role of researchers in this process, raising questions over whether appropriate governance structures are in place to develop effective responses. The cross-cutting nature of the adaptation agenda exposes the silo based approaches that drive many organisations. The development of a collaborative, sociotechnical agenda is vital if we are to meet the climate change adaptation challenge in cities