Susan E. Lee

Contrasting physiological and structural vegetation feedbacks in climate change simulations

Anthropogenic increases in the atmospheric concentration of carbon dioxide and other greenhouse gases are predicted to cause a warming of the global climate by modifying radiative forcing. Carbon dioxide concentration increases may make a further contribution to warming by inducing a physiological response of the global vegetation—a reduced stomatal conductance, which suppresses transpiration. Moreover, a CO2-enriched atmosphere and the corresponding change in climate may also alter the density of vegetation cover, thus modifying the physicalcharacteristics of the land surface to provide yet another climate feedback. But such feedbacks from changes in vegetation structure have not yet been incorporated into general circulation model predictions of future climate change. Here we use a general circulation model iteratively coupled to an equilibrium vegetation model to quantify the effects of both physiological and structural vegetation feedbacks on a doubled-CO2 climate. On a global scale, changes in vegetation structure are found to partially offset physiological vegetation–climate feedbacks in the long term, but overall vegetation feedbacks provide significant regional-scale effects.

Predicting the Future Productivity and Distribution of Global Terrestrial Vegetation

The climatological community of scientists has provided predictions of how the global climate will change in a future of increasing atmospheric concentrations of greenhouse gases. These predictions emerge from general circulation models (GCMs) that are now capable of providing predictions of the more realistic transient changes in climate that are expected as the concentrations of greenhouse gases steadily increase in the atmosphere. The ecological models that are necessary to interact with these transient climatic changes are those that can predict natural or dynamic changes in the distribution of vegetation. These dynamic global-vegetation models (DGVMs) must therefore be able to predict processes, such as vegetation disturbance and succession, in addition to processes that are now generally included in ecosystem models, such as biogeochemical cycling and carbon dioxide, and water fluxes. This chapter provides general detail and predictions from a DGVM, explains the Sheffield dynamic global-vegetation model (SDGVM) of terrestrial vegetation, and the responses to transient changes in climate over the next 100 years. Overall, net primary productivity (NPP) and net ecosystem productivity (NEP) are predicted to increase, with the most marked increases in NEP (increasing sink capacity) seen at high latitudes in the northern hemisphere.

Observed climate variations during the last 100 years in Lapland, northern Finland

Many general circulation models (GCMs) predict that high latitude environments will experience substantial warming over the next 100 years, which will be particularly pronounced during the winter months. Precipitation is also expected to increase but there is uncertainty as to the amount and spatial variation. The flora and fauna of the arctic and subarctic regions, together with indigenous people, such as the Saami, are particularly vunerable to rising temperatures and changing precipitation. Mean monthly temperature and precipitation data were examined for the last 100 years for northern Finland. These data were further analysed for the first and second half of the 20th century. There was no discernible warming trend between 1876 and 1993, but a significant annual warming (r=0.344, ρ<0.05) occurred in the period 1901–1945, together with a significant summer warming (r=0.381, ρ<0.05). Warming has occurred consistently in May and June over the last 100 years and there appears to be a current (i.e. post 1990) annual trend, mostly due to winter warming. The greatest temperature anomaly increase for the period 1901–1945 was in the winter months (+0.72°C). The degree of temperature variation in the winter is greater than in the summer and has risen from 3.98°C for December in the period 1901–1945 to 4.37°C in the period 1946–1990. This is attributed to the recent high variability in the North Atlantic Oscillation (NAO) Index. Annual precipitation has increased significantly during the period 1880–1993. The period 1946–1990 was wetter than 1901–1945, with greater variability particularly in the summer months, which contribute most to the annual precipitation in Lapland. Copyright

Simulating urban heat island effects with climate change on a Manchester house

This article presents a methodology for determining the internal temperatures of a post-1919 mid-terrace house for the present-day and a future (2050) climate. The Meteorological Office, Hadley Centre regional climate model has been run with urban parameterisation and an improved land-surface scheme with urban heat island forcing and a weather generator to quantify the effect of the urban heat island. Manchester city dry-bulb air temperatures are shown to be of the order of 4 K higher than those for the present-day under a UKCP09 medium emissions scenario. Extreme summer temperature data (99% percentile) are used to produce a cooling design day for use in a building simulation program.1 Loft and wall insulation decreases internal air temperatures by up to 17% and low e glazing with louvres by up to 8%. Internal temperatures for a 2050 climate will exceed existing Chartered Institution of Building Services Engineers thresholds. Practical application: Climate change is an important subject for both the building industry and local authorities. Climate change scenarios produced by the Hadley Centre General Circulation Models (GCM) have been downscaled to the local level for use in a building simulation model.1 This article demonstrates a technique that enables data from a GCM to be used within a building simulation program1 for an urban environment. It also examines the implications of the combined effect of the urban heat island and climate change on the adaptation options available to designers and planners for existing and future buildings.

Ground-level climate at a peatland wind farm in Scotland is affected by wind turbine operation

The global drive to produce low-carbon energy has resulted in an unprecedented deployment of onshore wind turbines, representing a significant land use change for wind energy generation with uncertain consequences for local climatic conditions and the regulation of ecosystem processes. Here, we present high-resolution data from a wind farm collected during operational and idle periods that shows the wind farm affected several measures of ground-level climate. Specifically, we discovered that operational wind turbines raised air temperature by 0.18 °C and absolute humidity (AH) by 0.03 g m−3 during the night, and increased the variability in air, surface and soil temperature throughout the diurnal cycle. Further, the microclimatic influence of turbines on air temperature and AH decreased logarithmically with distance from the nearest turbine. These effects on ground-level microclimate, including soil temperature, have uncertain implications for biogeochemical processes and ecosystem carbon cycling, including soil carbon stocks. Consequently, understanding needs to be improved to determine the overall carbon balance of wind energy.

Dataset of the livability performance of the City of Birmingham, UK, as measured by its citizen wellbeing, resource security, resource efficiency and carbon emissions

This data article presents the UK City LIFE1 data set for the city of Birmingham, UK. UK City LIFE1 is a new, comprehensive and holistic method for measuring the livable sustainability performance of UK cities. The Birmingham data set comprises 346 indicators structured simultaneously (1) within a four-tier, outcome-based framework in order to aid in their interpretation (e.g., promote healthy living and healthy long lives, minimize energy use, uncouple economic vitality from CO2 emissions) and (2) thematically in order to complement government and disciplinary siloes (e.g., health, energy, economy, climate change). Birmingham data for the indicators are presented within an Excel spreadsheet with their type, units, geographic area, year, source, link to secondary data files, data collection method, data availability and any relevant calculations and notes. This paper provides a detailed description of UK city LIFE1 in order to enable comparable data sets to be produced for other UK cities. The Birmingham data set is made publically available at http://epapers.bham.ac.uk/3040/ to facilitate this and to enable further analyses. The UK City LIFE1 Birmingham data set has been used to understand what is known and what is not known about the livable sustainability performance of the city and to inform how Birmingham City Council can take action now to improve its understanding and its performance into the future (see “Improving city-scale measures of livable sustainability: A study of urban measurement and assessment through application to the city of Birmingham, UK” Leach et al. [2]).

EATS: a life cycle-based decision support tool for local authorities and school caterers

PurposeThis paper describes the research that underpins the development of EATS (the Environmental Assessment Tool for School meals), a life cycle-based decision support tool for local authorities and their contractors responsible for providing catering services to schools. The purpose of this tool is to quantify the carbon footprint (CF) and water footprint (WF) of the meals served in order to identify hotspot meals and ingredients, and suggest simple, yet transformative, reduction measures. A case study is used to test the tool, comparing the impacts of 34 school meal recipes.MethodsThe tool utilises secondary data to calculate values of CF and WF for a school meal from cradle to plate. This includes three phases: (1) food production, (2) transport of each ingredient to a generic school kitchen in the UK, and (3) meal preparation. Considerations for waste along the supply chain are included. After testing the tool against a set of nutritionally compliant meals, a sensitivity analysis was performed to investigate the influence of the origin and seasonality of the ingredients, transport mode and cooking appliances used on the final results.Results and discussionThe results of the case study show the predominance of the production phase in the overall carbon footprint and that there is a strong tendency towards lower impacts for meat-free meals; however, this is not always the case, for instance some of the chicken-based meals present lower impacts than vegetarian meals rich in dairy ingredients. The sensitivity analysis performed on one of the meals shows that the highest value of CF is obtained when the horticultural products are out of season and produced in heated greenhouses, whilst the highest value of WF is obtained when the origin of the ingredients is unknown and the global average values of WF are used in the analysis; this defines a crucial data need if accurate analyses are to be uniformly possible.ConclusionsThis article focuses on the potential offered by the public food sector for a transformative reduction in the environmental impact of urban food consumption. The results presented prove that careful menu planning and procurement choices can considerably reduce the overall environmental impact of the service provided without compromising quality or variety. This research thus supports those responsible for making these decisions via a user-friendly tool based on robust scientific evidence.