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As evidence for the devastating impacts of air pollution on human health continues to increase, improving urban air quality has become one of the most pressing tasks facing policy makers world-wide. Increasingly, and very often on the basis of conflicting and/or weak evidence, the introduction of green infrastructure (GI) is seen as a win–win solution to urban air pollution, reducing ground-level concentrations without imposing restrictions on traffic and other polluting activities. The impact of GI on air quality is highly context dependent, with models suggesting that GI can improve urban air quality in some situations, but be ineffective or even detrimental in others. Here we set out a novel conceptual framework explaining how and where GI can improve air quality, and offer six specific policy interventions, underpinned by research, that will always allow GI to improve air quality. We call GI with unambiguous benefits for air quality GI4AQ. However, GI4AQ will always be a third-order option for mitigating air pollution, after reducing emissions and extending the distance between sources and receptors.

Background The manual study of root dynamics using images requires huge investments of time and resources and is prone to previously poorly quantified annotator bias. Artificial intelligence (AI) image-processing tools have been successful in overcoming limitations of manual annotation in homogeneous soils, but their efficiency and accuracy is yet to be widely tested on less homogenous, non-agricultural soil profiles, e.g., that of forests, from which data on root dynamics are key to understanding the carbon cycle. Here, we quantify variance in root length measured by human annotators with varying experience levels. We evaluate the application of a convolutional neural network (CNN) model, trained on a software accessible to researchers without a machine learning background, on a heterogeneous minirhizotron image dataset taken in a multispecies, mature, deciduous temperate forest. Results Less experienced annotators consistently identified more root length than experienced annotators. Root length annotation also varied between experienced annotators. The CNN root length results were neither precise nor accurate, taking ~ 10% of the time but significantly overestimating root length compared to expert manual annotation ( p  = 0.01). The CNN net root length change results were closer to manual ( p  = 0.08) but there remained substantial variation. Conclusions Manual root length annotation is contingent on the individual annotator. The only accessible CNN model cannot yet produce root data of sufficient accuracy and precision for ecological applications when applied to a complex, heterogeneous forest image dataset. A continuing evaluation and development of accessible CNNs for natural ecosystems is required.

Diesel engine emissions are by far the largest source of nanoparticles in many urban atmospheres, in which they dominate the particle number count, and may present a significant threat to public health. This paper reviews knowledge of the composition and atmospheric properties of diesel exhaust particles, and exemplifies research in this field through a description of the FASTER project (Fundamental Studies of the Sources, Properties and Environmental Behaviour of Exhaust Nanoparticles from Road Vehicles) which studied the size distribution—and, in unprecedented detail, the chemical composition—of nanoparticles sampled from diesel engine exhaust. This information has been systematized and used to inform the development of computational modules that simulate the behaviour of the largely semi-volatile content of the nucleation mode particles, including consequent effects on the particle size distribution, under typical atmospheric conditions. Large-eddy model studies have informed a simpler characterization of flow around the urban built environment, and include aerosol processes. This modelling and engine-laboratory work have been complemented by laboratory measurements of vapour pressures, and the execution of two field measurement campaigns in London. The result is a more robust description of the dynamical behaviour on the sub-kilometre scale of diesel exhaust nanoparticles and their importance as an urban air pollutant.

The benefits of ‘green infrastructure’ are multi-faceted and well-documented, but estimating those of individual street-scale planting schemes at planning can be challenging. This is crucial to avoid undervaluing proposed schemes in cost–benefit analyses, and ensure they are resilient to ‘value engineering’ between planning and implementation. Here, we introduce prototype software enabling urban practitioners to estimate the site-specific air quality impacts of roadside vegetation barriers: highly localised changes in pollutant concentrations due to changes in the dispersion of vehicular emissions close to source. We summarise the recent shift in understanding regarding the impacts of vegetation on urban air pollution towards changes in pollutant dispersion (cf. deposition) and describe our prototype software, offering rapid estimates thereof. First tests of the underlying model’s performance are promising, reproducing: annual mean NO2 and PM2.5 concentrations in a street canyon (Marylebone Road, London, UK) to within 10% and 25%, respectively; and changes in pollutant concentrations of the right order of magnitude behind roadside barriers in a wind tunnel simulation of a street canyon and a real open-road environment. However, the model underestimates the benefits of a barrier in a simulated street canyon under perpendicular wind conditions. The prototype software is a first step towards informing practitioners of the site-specific impacts of vegetation barriers, which should always be additional to (i.e., no substitute for) essential emission reductions. The code is open-source to engage further researchers in its continued development.

Pollen are hygroscopic; therefore, they have the potential to act as cloud condensation nuclei (CCN) in the atmosphere. This could have uncertain implications for cloud processes and climate as well as plant biodiversity and human health. Previous studies have investigated the hygroscopic swelling of pollen, linked to CCN activity by the κ-Köhler theory, using methods that follow observed mass increase by electrodynamic balance (EDB) or vapour sorption analyser. This study uses an acoustic levitator to levitate pollen grains in the true aerosol phase and uses a macroscope to image the pollen to investigate hygroscopic behaviour when relative humidity (RH) is changed. Two pollen species were studied in this work: Lilium orientalis (oriental lily) and Populus deltoides (eastern cottonwood). Both species were successfully levitated; however, the smaller Populus deltoides showed greater instability throughout experiments. The quality of images taken by the macroscope, and thus calculations of pollen area and aspect ratio, varied significantly and were sensitive to lighting conditions as well as to levitated pollen grain movement and orientation. Experiments with surface-fixed pollen grains were also conducted. They showed evidence that pollen hygroscopic swelling could be observed by the macroscope. The produced results were comparable with previously reported mass increase values. Although less accurate than methods that measure mass changes, the acoustic levitator and macroscope set-up offer an attractive alternative by virtue of being commercial, off-the-shelf, low-cost, and versatile techniques. A key advantage of this method is that it is possible to visually observe particle shape dynamics under varying environmental conditions.

As part of an NERC-funded project investigating the southern methane anomaly, a team drawn from the Universities of Bristol, Birmingham and Royal Holloway flew small unmanned multirotors from Ascension Island for the purposes of atmospheric sampling. The objective of these flights was to collect air samples from below, within and above a persistent atmospheric feature, the Trade Wind Inversion, in order to characterise methane concentrations and their isotopic composition. These parameters allow the methane in the different air masses to be tied to different source locations, which can be further analysed using back trajectory atmospheric computer modelling. This paper describes the campaigns as a whole including the design of the bespoke eight rotor aircraft and the operational requirements that were needed in order to collect targeted multiple air samples up to 2.5 km above the ground level in under 20 min of flight time. Key features of the system described include real-time feedback of temperature and humidity, as well as system health data. This enabled detailed targeting of the air sampling design to be realised and planned during the flight mission on the downward leg, a capability that is invaluable in the presence of uncertainty in the pre-flight meteorological data. Environmental considerations are also outlined together with the flight plans that were created in order to rapidly fly vertical transects of the atmosphere whilst encountering changing wind conditions. Two sampling campaigns were carried out in September 2014 and July 2015 with over one hundred high altitude sampling missions. Lessons learned are given throughout, including those associated with operating in the testing environment encountered on Ascension Island.

The impact of urban morphology on air quality, particularly within deep canyons with longer residence times for complex chemical processes, remains insufficiently addressed. A flexible multi-box framework was used to simulate air quality at different canyon heights (3 m and 12 m). This approach incorporated essential parameters, including ventilation rates, background concentrations, photochemical schemes, and reaction coefficients. A field campaign within a deep canyon with an aspect ratio of 3.7, in Naples, Italy was conducted and used for the model evaluation. The model performance demonstrated good agreement, especially at the street level, when employing a realistic light intensity profile and incorporating volatile organic compound (VOC) chemistry. Our findings indicate that peroxyl radical production affects NO2 and O3 levels by up to 9.5% in deep canyons and underscore the significance of vertical distribution (approximately 5% variance) in health assessments and urban air quality strategy development. The model response was sensitive to changes in emissions as expected, but also, somewhat more surprisingly, to background conditions, emphasizing that policies to remove pollution hotspots must include local and broader citywide action. This work advances the understanding of air quality dynamics in deep urban canyons and presents a valuable tool for effective air quality management in intricate urban environments.

Acorn production in oak ( Quercus spp.) shows considerable inter-annual variation, known as masting, which provides a natural defence against seed predators but a highly-variable supply of acorns for uses such as in commercial tree planting each year. Anthropogenic emissions of greenhouse gases have been very widely reported to influence plant growth and seed or fruit size and quantity via the ‘fertilisation effect’ that leads to enhanced photosynthesis. To examine if acorn production in mature woodland communities will be affected by further increase in CO 2 , the contents of litter traps from a Free Air Carbon Enrichment (FACE) experiment in deciduous woodland in central England were analysed for numbers of flowers and acorns of pedunculate oak ( Quercus robur L.) at different stages of development and their predation levels under ambient and elevated CO 2 concentrations. Inter-annual variation in acorn numbers was considerable and cyclical between 2015 and 2021, with the greatest numbers of mature acorns in 2015, 2017 and 2020 but almost none in 2018. The numbers of flowers, enlarged cups, immature acorns, empty acorn cups, and galls in the litter traps also varied amongst years; comparatively high numbers of enlarged cups were recorded in 2018, suggesting Q. robur at this site is a fruit maturation masting species (i.e., the extent of abortion of pollinated flowers during acorn development affects mature acorn numbers greatly). Raising the atmospheric CO 2 concentration by 150 μL L −1 , from early 2017, increased the numbers of immature acorns, and all acorn evidence (empty cups + immature acorns + mature acorns) detected in the litter traps compared to ambient controls by 2021, but did not consistently affect the numbers of flowers, enlarged cups, empty cups, or mature acorns. The number of flowers in the elevated CO 2 plots’ litter traps was greater in 2018 than 2017, one year after CO 2 enrichment began, whereas numbers declined in ambient plots. Enrichment with CO 2 also increased the number of oak knopper galls ( Andricus quercuscalicis Burgsdorf). We conclude that elevated CO 2 increased the occurrence of acorns developing from flowers, but the putative benefit to mature acorn numbers may have been hidden by excessive pre- and/or post-dispersal predation. There was no evidence that elevated CO 2 altered masting behaviour.

The increasing miniaturization of accurate, reliable meteorological sensors and logging systems allows the deployment of sensor packages on lightweight airborne platforms. Here, we demonstrate the safe and humane use of avian species (white-tailed and Spanish imperial eagles) to carry a prototype miniature sensor package to measure temperature with a 5-Hz response and ±0.2°C resolution. This technique could allow sensor deployment above complex urban terrain, where such data are urgently required. Recent meteorological work has been facilitated by using unmanned aerial vehicles (UAVs), but their use within, and adjacent to, urban areas is heavily controlled. The package contains a wind speed sensor, a GPS, a pressure altimeter, and accelerometers. Four flight tests were conducted in a steep valley (glen) at a remote Scottish location that provided contrasting vertical temperature profiles. The glen was instrumented with additional meteorological equipment at the bird launch and landing sites. Vertical temperature profile data from the raptors indicated the success of this approach with absolute temperatures and lapse rates consistent with those measured by the weather stations. Movement and airspeed data aided the interpretation of finescale temperature profiles in complex terrain. As well as the potential for meteorological sensing, this work is of interest to the avian ecology and behavior communities and to aerodynamicists interested in developing airborne robotics to mimic aspects of bird f light. These sensors are being miniaturized further for deployment on other bird species in urban areas for rapid, repeatable, and reliable measurements, with the potential to fulfill a measurement niche above the urban canopy.

Future scenarios provide challenging, plausible and relevant stories about how the future could unfold. Urban Futures (UF) research has identified a substantial set (>450) of seemingly disparate scenarios published over the period 1997–2011 and within this research, a sub-set of >160 scenarios has been identified (and categorized) based on their narratives according to the structure first proposed by the Global Scenario Group (GSG) in 1997; three world types (Business as Usual, Barbarization, and Great Transitions) and six scenarios, two for each world type (Policy Reform—PR, Market Forces—MF, Breakdown—B, Fortress World—FW, Eco-Communalism—EC and New Sustainability Paradigm—NSP). It is suggested that four of these scenario archetypes (MF, PR, NSP and FW) are sufficiently distinct to facilitate active stakeholder engagement in futures thinking. Moreover they are accompanied by a well-established, internally consistent set of narratives that provide a deeper understanding of the key fundamental drivers (e.g., STEEP—Social, Technological, Economic, Environmental and Political) that could bring about realistic world changes through a push or a pull effect. This is testament to the original concept of the GSG scenarios and their development and refinement over a 16 year period.