Clouds have a profound influence on weather and climate. Formation of cloud droplets by condensation of water vapour on particles has been studied for many decades. For inert involatile particles, this process and its impacts are relatively well understood. However, a substantial proportion of fine particle material can evaporate under some atmospheric conditions. Our recent Nature Geoscience Letter suggests that the role of this fraction on cloud droplet formation is large enough to be globally significant, is not normally considered in cloud parcel models and is completely untreated in large-scale models. This results from the co-condensation of partly volatile material along with the water vapour during droplet activation. Indirect evidence supports this effect, but direct measurements are unavailable. There has also been considerable interest in the potential role of amorphous "glassy" particles as seeds for ice crystals in cold and mixed-phase clouds. The Nature publication and subsequent work by project partner Virtanen identified that secondary organic aerosol from both biogenic and anthropogenic precursors could exist in an amorphous state dependent on relative humidity and temperature. The impact of glassy particles as ice nuclei is potentially very significant, but direct evidence is currently confused and realistic supporting measurements are sparse. It is proposed to quantify the impacts of organic components on warm and cold cloud formation by both processes through simulation chamber measurements, to use the measurements to evaluate a recently developed model treatment, to parameterise the model and use the parameterisation to quantify the regional impacts on cloud physical and radiative properties. We have conducted proof of concept laboratory work showing that we are able to study both processes. We have coupled the Manchester Aerosol Chamber (MAC), where we can make particles from the atmospheric chemistry of both natural plant emissions and man-made emissions, to the Manchester Ice Cloud Chamber (MICC), where we can form a cloud under reasonable atmospheric conditions. We have further measured the changes in the effectiveness of the particles to act as seeds for liquid cloud droplets, cloud condensation nuclei (CCN), along with the volatility, composition and phase behaviour. We propose to build on this proof-of-concept to systematically quantify the effects in a range of atmospherically-representative systems and quantify their impacts. The proposed work will be carried out in 4 parts. The first two are laboratory-based with numerical model interpretation and the second two solely use numerical modelling: i) quantification of the effect of organic vapours in two instruments that are used in the field and laboratory, one measuring particle water uptake below 100% RH and the other the ability to form a cloud droplet just above 100% RH. Particles will be exposed to controlled concentration of semi-volatile vapour and introduced into the instruments. Detailed flow modelling of the second instrument will be carried out, in collaboration with the author as project partner. ii) involves the coupling of the MAC and MICC chambers as in the proof-of-concept, but covering particles formed in a wide range of natural, manmade and mixed systems. We will measure all relevant parameters to quantify the formation of warm and cold clouds under a reasonable range of atmospheric conditions. iii) informed by the experiments, the effects of organic compounds on warm and cold clouds will be included in a numerical model and this will be used to develop physically-based parameterisations for use in large-scale models. iv) the parameterised process description will be used in large-scale models informed by our project partner Nenes to estimate the impact on cloud properties and radiation, hence quantifying the couplings between organic compounds and weather and climate under representative conditions.

As the global climate warms, thawing permafrost may lead to increased greenhouse gas release from Arctic and Boreal ecosystems. Scientists agree that this permafrost-climate feedback is important to the global climate system, but its magnitude and timing remains poorly understood. The overall aim of COUP is to use detailed understanding of landscape-scale processes to improve global scale climate models. Better predictions of how permafrost areas will respond to a warming climate can help us understand and plan for future global change. In recent years much scientific progress has been made towards understanding the complex responses of permafrost ecosystem to climate warming. Despite this, large challenges remain when it comes to including these processes in global climate models. Permafrost ecosystems are highly variable and studies show that very detailed field investigations are needed to understand complexities. Because global scale models cannot run at such high-resolutions, we propose an approach where local landscape-scale field studies and modelling are used to identify those key variables that should be improved in global models. We will carry out careful field studies and high-resolution modelling at field sites covering all pan-Eurasian environmental conditions. The system understanding gained from this will then be used to (1) scale key variables so they are useful for global models and (2) improve a new global climate model. In the final step, the improved global climate models will be run to quantify the impact of thawing permafrost on the global climate. Datasets produced in COUP will be freely available online so that they can be used by other scientists and help improvement of all global climate models. COUP is designed to maximise synergies with ongoing projects. Much of the needed data and system understanding was generated in other research programmes.

The focus on particulate matter (PM2.5) mass reductions in UK air quality policy reflects the metrics measured for regulatory compliance. Epidemiological approaches have struggled to untangle the relative hazard of PM constituents within this mass, as well as co-pollutant gases, such as NO2, leading to the contention that all PM2.5 components must be treated as being equally harmful to human health. This makes little toxicological sense. The lack of a relative hazard ranking of PM constituents and co-emitted gases means that policy focuses on blunt strategies based on overall reductions in pollutant concentrations, rather than a refined focus on health relevant sources and components. This poses risks of unintended consequences, e.g. focusing on the largest contributors to PM2.5 for regulatory compliance, rather than the most harmful fractions, may fail to deliver predicted health benefits to the most vulnerable members of our society. In outdoor air this has remained unresolved for over 20-years, but further complexity is introduced by the heterogeneous indoor environment which must be considered in a complete picture of exposure. To address this major knowledge gap, the UK requires integration and focus of toxicological resource methodologies to identify the most hazardous fractions of indoor and outdoor PM and to elucidate the causal pathways contributing to disease development and exacerbation. Our proposed consortium brings together recognised UK expertise in atmospheric sciences, toxicology and biomedical sciences in a world-leading interdisciplinary collaboration to build an Air Pollution Hazard Identification Platform. This platform will deliver the capability to conduct controlled and characterised exposures to defined pollutant mixtures from different sources for in vitro, in vivo animal and human toxicological studies. We will use the large atmospheric simulation chamber at the University of Manchester to conduct experiments exposing human volunteers to diesel exhaust, woodsmoke, cooking emissions, secondary organic aerosol and NOx-enhanced mixtures, all at ambient atmospheric levels. These have been selected for their recognised substantial contributions to indoor and outdoor air pollution. The chamber exposures will be used as a reference and these experiments will be used to provide filtered samples of the PM for in vitro and transgenic animal exposures at the partner Institutions. Referenceable portable source units for all primary and secondary pollutant mixtures will be developed, characterised and deployed for in vitro and animal exposures to the full gas and particle mixture. Within the proposal, we will demonstrate the capability of the platform to elucidate the toxicological mechanisms involved in the neurological impacts of air pollution, though any health outcomes are accessible to the platform. The in vitro studies will be used to explore possible direct and indirect mechanisms for neuroinflammation and injury, identifying the molecular pathways associated with cellular activation. Using a unique panel of transgenic stress-reporter mouse lines, the stress response on exposure to the various pollutants will be tracked in a tissue and cell specific manner in vivo and provide a hazard ranking of the pollutants that can be related back to the in vitro molecular signatures. Repeat experiments with mouse lines susceptible to Alzheimer's disease will examine changes in these stress responses. Epigenetic DNA signatures will be examined in target tissues. A panel of healthy aged human subjects with a family history of increased dementia risk will provide biosamples and be subjected to cognitive tests on exposure to the different mixtures, further enabling their hazard ranking for correlation with the in vitro and animal studies. The mechanistic linkages between the animal and human exposure responses will be explored using candidate driven biomarker and untargeted metabolomic and epigenetic studies.

Globally, there is increasing concern about the potential risks of air pollution to human health and the environment. Whilst many people consider air pollution predominantly an urban issue, rural areas are also regularly exposed to a range of air pollutants. Growing evidence suggests that common air pollutants such as ozone and nitrogen oxides (NOx) may indirectly impair the fitness of plants and insects, by reacting with and chemically altering the odour compounds that plants and insects use for communication. Whilst the dominant sense used by humans is vision, many insects and plants use odours to perceive and interact with their environment. These odours can be a vital part of many everyday tasks that are critical to their survival. Insects commonly use odours to locate food (e.g. a flower's scent) or find a mate (i.e. pheromones), and plants also detect and respond to odours from other nearby plants (e.g. they can increase production of defence chemicals in their leaves if they detect odours released from neighbouring plants being fed upon by insects). Many insects provide vital ecosystem services which benefit society, e.g. the pollination of food crops, and therefore disruption of the odour cues that insects use to carry out such tasks could result in significant negative consequences. Increasing numbers of studies are demonstrating how air pollutants can chemically alter different odour cues used by plants and insects, e.g. our previous research showed that diesel exhaust reacts with and alters the unique blend of chemicals that make up a flower's scent, making it no longer recognizable to honey bees. However, most of the evidence for these effects is from laboratory studies and simulation models, the outcomes of which do not always translate accurately to effects in nature. Field-based experiments are rare because in open air conditions it is practically very challenging to elevate pollutants in a controlled manner. Recently, we designed a novel temporary prototype facility which successfully allowed us to investigate how air pollution can impact upon important ecological processes in the field. Our initial unpublished results indicate that these impacts may be significantly greater than predicted by laboratory studies and simulation models. Moderate increases in NOx and ozone levels resulted in a 90% reduction in flower visitation by pollinators, indicating an unexpectedly severe negative impact upon insect-provided pollination. This result substantiates the urgent need for a dedicated permanent field-based research platform to investigate: 1) which ecological process and interactions are affected and what are the potential consequences; 2) what are the mechanisms of such changes; 3) are there interventions that can be put in place to mitigate these changes? Therefore, this project will fund the construction of a globally unique state-of-the-art bespoke research facility at the University of Reading's Sonning Farm to provide a research platform for academics across the globe to conduct cutting edge research in this scientific field. This new, Free-Air Diesel and Ozone Enrichment research platform, will consist of a series of 12 independently controllable 8-meter diameter rings. Within each ring it will be possible to accurately elevate and maintain ozone and diesel exhaust, both separately and in combination, to ecologically realistic values. Researchers will be able to alter the plant/insect communities within these rings to permit them to study the ecological impacts of these air pollutants on a range of odour-mediated interactions and, using advanced field-based chemical techniques, study the chemical mechanisms behind any changes. The facility will provide researchers with the tools to address key questions in the field and make a step change in our knowledge of how air pollution impacts upon biodiversity and the key insect-mediated ecosystem services upon which we rely for sustainable food production.

Until recently, awareness of the importance of winter carbon dioxide emissions from arctic soils was highly limited, resulting from incorrect assumptions that emissions from frozen soils beneath snow were insignificant compared to other sources. Consequently, carbon dioxide emissions during arctic winter months are frequently omitted from global carbon cycling budgets and our capacity to measure atmosphere-snow-soil processes controlling carbon dioxide emission and simulate them in climate models are under-developed. This limits our ability to make future climate projections, especially in arctic tundra and forested regions, which characterise about 27% of the Earth's land surface and are warming more than twice as fast as the global average since the late twentieth century. Carbon dioxide, a gas which causes the Earth's atmosphere to trap heat causing the planet to warm, is emitted by microbes decomposing organic material in soil. Decomposition can occur when the soil is frozen, but rates of carbon dioxide emission decrease as soil temperatures decrease, down to -20 degrees Celsius when carbon dioxide emissions become negligible. Winter snow cover has an important impact on arctic soil temperatures, acting like a duvet covering a bed. A thick duvet with lots of air trapped between the feathers provides insulation. Air trapped between the snow crystals within a snowpack acts in a similar manner, limiting the loss of heat from soils warmed in the summer to the cold atmosphere during long arctic winters. As the ground is often snow covered for at least half of the year in Arctic regions, it is vital that we understand processes that control the impact of snow cover on soil temperatures and carbon dioxide emissions, and accurately represent these processes in climate models. Here we ask, how sensitive are measured carbon dioxide concentrations within arctic snowpacks to the variability of snowpack physical properties (e.g. size of the snow crystals)? Can more realistic simulations of snowpack density and thermal conductivity in climate models reduce the underprediction in carbon dioxide emissions from arctic snowpacks? And, how may future changes in winter soil temperatures and snow cover affect future carbon dioxide emissions? In order to answer these questions, we will create a new field measurement database of arctic meteorology, soil and snow properties, and carbon dioxide concentrations. We will use this database to develop more realistic representations of processes controlling winter carbon dioxide emissions in climate models, which will lead to confident model projections of future winter carbon dioxide emissions from the wider Arctic region. By combining field and laboratory measurements with climate modelling, this partnership between Canadian, Finnish and UK scientists will increase our predictive understanding of Arctic environmental change resulting from, and contributing to, our warming planet.