Dissertations / Theses on the topic 'Climatic change modelling'

The aim of this project is to investigate the influence of climate and topography on ice sheets in maritime environments. Numerical models are adapted to simulate the behaviour of the climate and ice sheets in southern Chile and Scotland during the last glaciation. The climate model relates climatic variables to snow accumulation and ablation using an energy balance model. The ice sheet model is based on the continuity equation for ice thickness and relates surface mass exchange to ice thickness and flow. Subsequently, a simple topography model is developed to examine the critical transition between glaciers and ice sheets. The net mass balance gradient in maritime regions is primarily sensitive to temperature and precipitation. Ice sheet initiation is strongly influenced by the adjacent ocean's temperature, which affects the delicate balance between decreasing precipitation and decreasing temperature. In Chile, expanded glaciation reflects an equatorward movement of the prevailing westerlies, though the postulated migration of precipitation belts implies that the maximum depression of the snowline is unlikely to have been contemporaneous at different latitudes. In Scotland, ice sheets appear to be triggered by the southward movement of the North Atlantic polar front. The configuration and latitude of upland topography determines the point of initiation and the threshold between stable upland glaciers and the growth of an ice sheet. The topography acts as a filter between climate and the response of a glacier, and topographic evolution leads to a powerful feedback between topography, climate and ice over Quaternary time scales.

A modelling approach focused on snow hydrology was developed and applied to project future changes in spring streamflow volumes in the St. Mary River headwaters basin, Montana. A spatially distributed, physically-based, hydrometeorological and snow mass balance model was refined and used to produce snow water equivalent (SWE) and rainfall surfaces for the study watershed. Snowmelt runoff (SR) and effective rainfall runoff (RR) volumes were compiled for the 1961-2004 historical period. A statistical regression model was developed linking spring streamflow volume (QS) at Babb, Montana to the SR and RR modelled data. The modelling results indicated that SR explained 70% of the variability in QS while RR explained another 9%. The model was applied to climate change scenarios representing the expected range of future change to produce annual QS for the period 2010-2099. Compared to the base period (1961-1990), average QS change ranged from -3% to -12% for the 2020s period. Percent changes increased to between -25% and -32% for the 2050s, and -38% and -55% for the 2080s. Decreases in QS also accompanied substantial advances in the onset of spring snowmelt. Whereas the spring pulse onset on average occurred on April 8 for the base period, it occurred 36 to 50 days earlier during the 2080s. The findings suggest that increasing precipitation will not compensate for the effects of increasing temperature in watershed SWE and associated spring runoff generation. There are implications for stakeholder interests related to ecosystems, the irrigation industry, and recreation.
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Thesis (PhD)--Stellenbosch University, 2014.
ENGLISH ABSTRACT: Numerous studies indicate that the agricultural sector is physically and economically vulnerable to climate change. In order to determine possible impacts of projected future climates on the financial vulnerability of selective farming systems in South Africa, a case study methodology was applied. The integrated modelling framework consists of four modules, viz.: climate change impact modelling, dynamic linear programming (DLP) modelling, modelling interphases and financial vulnerability assessment modelling. Empirically downscaled climate data from five global climate models (GCMs) served as base for the integrated modelling. The APSIM crop model was applied to determine the impact of projected climates on crop yield for certain crops in the study. In order to determine the impact of projected climates on crops for which there are no crop models available, a unique modelling technique, Critical Crop Climate Threshold (CCCT) modelling, was developed and applied to model the impact of projected climate change on yield and quality of agricultural produce. Climate change impact modelling also takes into account the projected changes in irrigation water availability (ACRU hydrological model) and crop irrigation requirements (SAPWAT3 model) as a result of projected climate change. The model produces a set of valuable results, viz. projected changes in crop yield and quality, projected changes in availability of irrigation water, projected changes in crop irrigation needs, optimal combination of farming activities to maximize net cash flow, and a set of financial criteria to determine economic viability and financial feasibility of the farming system. A set of financial criteria; i.e. internal rate of return (IRR), net present value (NPV), cash flow ratio, highest debt ratio, and highest debt have been employed to measure the impact of climate change on the financial vulnerability of farming systems. Adaptation strategies to lessen the impact of climate change were identified for each case study through expert group discussions, and included in the integrated modelling as alternative options in the DLP model. This aims at addressing the gap in climate change research, i.e. integrated economic modelling at farm level; thereby making a contribution to integrated climate change modelling.
AFRIKAANSE OPSOMMING: Die fisiese sowel as ekonomiese kwesbaarheid van die landbousektor as gevolg van klimaatverandering word deur verskeie studies beklemtoon. ‘n Gevallestudie-benadering is gebruik ten einde die potensiële impak van klimaatsverandering op die finansiële kwesbaarheid van verskillende boerderystelsels te bepaal. Die geïntegreerde klimaatsveranderingmodel bestaan uit vier modelleringsmodules, naamlik: klimaatsverandering, dinamiese liniêre programmering (DLP), interfases en finansiële-kwesbaarheidsontleding. Empiries afgeskaalde klimatologiese data van vyf verskillende klimaatmodelle dien as basis vir die geïntegreerde klimaatsveranderingmodel. Die APSIM gewas-model word aangewend om die impak van klimaatsverandering op gewasse-opbrengs te bepaal. Vir sekere gewasse is daar egter nie modelle beskikbaaar nie en het gevolglik die ontwikkeling van ‘n nuwe model genoodsaak. Die Kritiese Gewasse Klimaatsdrempelwaarde (KGKD) modelleringstegniek is ontwikkel ten einde die impak van klimaatsverandering op die opbrengs en kwaliteit van gewasse te kwantifiseer. Die geïntegreerde klimaatsveranderingmodel neem ook die verwagte verandering in besproeiingswaterbeskikbaarheid (ACRU-hidrologiemodel) en gewas-besproeiingsbehoeftes (SAPWAT3-model) as gevolg van klimaatsverandering in ag. Die model lewer waardevolle resultate op, naamlik: geprojekteerde veranderinge in gewasse-opbrengs en -kwaliteit, geprojekteerde verandering in beskikbaarheid van besproeiingswater en gewasse-besproeiingsbehoeftes, die optimale kombinering van boerdery-aktiwiteite om netto kontantvloei te maksimeer, asook ‘n stel finansiële resultate wat die impak van klimaatsverandering kwantifiseer. Die finansiële kriteria sluit in: interne opbrengskoers, netto huidige waarde, kontanvloeiverhouding, hoogste skuldverhouding en hoogste skuldvlak. Deur middel van deskundige-groepbesprekings is aanpassingstrategieë vir elk van die gevallestudies geïdentifiseer en by die geïntegreerde model ingesluit as alternatiewe opsies in die DLP-model. Die studie poog om die gaping in die huidige klimaatsveranderingnavorsing met betekking tot ‘n geïntegreerde ekonomiese model op plaasvlak aan te spreek en sodoende ‘n bydrae tot geïntegreerde klimaatveranderingmodellering te maak.

Climate change poses significant threats to mountain ecosystems in North America (Barnett et al., 2005) and will subsequently impact water supply for human and ecosystem use. To assess these threats, we must have an understanding of the local variability in hydrometeorological conditions over the mountains. This thesis describes the continued development and application of a fine scale spatial hydrometeorological model, GENESYS (GENerate Earth SYstems Science input). The GENESYS model successfully simulated daily snowpack values for a 10 year trial period and annual runoff volumes for a thirty year period. Based on the results of these simulations the model was applied to estimate potential changes in snowpack over the St. Mary River watershed, Montana. GCM derived future climate scenarios were applied, representing a range of emissions controls and applied to perturb the 1961-90 climate record using the “delta” downscaling technique. The effects of these changes in climate were assessed for thirty year time slices centered on 2020s, 2050s, and 2080s. The GENESYS simulations of future climate showed that mountain snowpack was highly vulnerable to changes in temperature and to a lesser degree precipitation. A seasonal shift to an earlier onset of spring melt and an increase in the ratio of rain to snow occurred under all climate change scenarios. Results of mean and maximum snowpack were more variable and appeared to be highly dependent on scenario selection. The results demonstrated that although annual volume of available water from snowpack may increase, the seasonal distribution of available water may be significantly altered.
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Climate change is affecting several environmental factors and together with socio-economic changes put high pressure on water resources. Climate change manifest itself through increasing temperatures and changes in precipitation patterns and intensities, with knock-on effects on hydrologically-relevant parameters such as water flows, evapotranspiration rates, glacial melt etcetera, all of which have already been observed in the recent past and are predicted to continue in the future. India has the world’s second largest population. The majority of the population live in rural areas and are dependent on climate sensitive sectors such as agriculture, forestry and fishery. The Indian-Himalayan region supplies 600 million people with water, thus future climate change impacts on the hydrological cycle in the area are of great interest and concern. In order to cope with these predicted impacts, there is a need to adapt to the changing climate. This study combines data analyses from a hydro-climatic modelling campaign (carried out externally to this thesis), a literature review on climate change effects on agriculture and opportunities to adapt to these effects and participatory methods bringing stakeholders and scientists together in order to co-create adaptation options that are suitable to minimise short- and long-term climate change impacts on the water flows of the Ganges and hence agriculture in the region. The study concentrates on two districts in the Indo-Gangetic Plain that are characterised by their high dependency on the farming sector: Uttarkashi (upstream Ganges, Uttarakhand) and Patna (downstream Ganges, Bihar). The analysis of hydro-climatic data based on a modelling campaign focussed on three climate variables that are of significance for agriculture: precipitation, temperature, and evapotranspiration. To characterise future climates, four climate change projections based on IPCC’s representative concentrations pathways (RCPs) have been chosen: RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5. The impacts of these scenarios on the above listed three climate variables are analysed over three time periods: 2011-2040, 2041-2070, and 2071-2100, with a special focus on the monsoon months from June to October, as this is the main crop (rice) growing season. The results from the hydro-climatic modelling indicate that the maximum, minimum, and average temperature will be increasing over the next century in both districts. An increase in evapotranspiration can be seen for both districts, with a few exceptions for RCP scenarios 2.6, 6.0 and 8.5 in April and May in Patna, and for all RCP scenarios in April, May and June in Uttarkashi. An increase in maximum and average precipitation can be seen for most RCP scenarios and future time periods (e.g. of exceptions in average precipitation: RCP 4.5 and 8.5 in June and July in the period 2011-2040) during the monsoon period in Patna. Similarly, in Uttarkashi maximum and average precipitation increases for all three time periods and RCP scenarios during the monsoon months of September and August (only for RCP scenarios 2.6 and 8.5). For the remaining months, the precipitation patterns show great variability for all scenarios and both regions. The literature review resulted in a table of adaptation options, where nine out of 63 were considered as transformational adaptation, and enabled identification of possible climate change impacts on agriculture in the two districts. The minimum temperature could result in more severe and intense hailstorms in the future for both districts. The increase in temperature could lead to a prolonged growing season in Uttarkashi, whilst the increase in average and maximum temperature in Patna could lead to heat-stress for the crops. Furthermore, the increase in average and maximum precipitation could lead to more severe and intense natural disasters e.g. landslides in Uttarkashi and floods in Patna. Moreover, the increase in average evapotranspiration combined with the decrease in average precipitation during some months could lead to an increasing need of irrigation. Two workshops were held in the region with the aim to bring together researchers and stakeholders (e.g. famers) in order to jointly discuss 1) the suitability of hydrological modelling data for preparing the agriculture sector to a changing climate, and 2) suggest suitable adaptation options based on researchers’ and stakeholders’ knowledge and experience. Information from the first workshop was obtained by a workshop report, whilst information from the second workshop was obtained from the author’s own participation. The result from the workshop showed that the farmers had several suggestions of suitable adaptation options e.g. implementation of irrigation system and improved access to credit. It also showed that the farmers already adapted to climate change e.g. usage of short- and long duration variations of rice and sowing date adjustment. The combination of these results informed the suggestions for adaptation options for the two districts, namely the development of disaster reduction plans and early warning systems for weather extremes, as well as a diversification of agriculture and more generally livelihoods. In addition, indirect adaptation measures suggested for both districts included insurance schemes against yield failure, improved access to credit schemes, and right/fair market prices. Specific measures for each district were also suggested e.g. heat-tolerant crops in Patna and implementation or irrigation systems in Uttarkashi.
Klimatförändringarna påverkar åtskilliga miljöfaktorer och tillsammans med socioekonomiska förändringar sätter de stort tryck på vattenresurser. Klimatförändringar manifesterar sig i stigande temperaturer och ändrade nederbördsmönster och nederbördsintensitet, med påföljande effekter på hydrologiskt relevanta parametrar så som vattenflöden, evapotranspirationsvärden, smältande glaciärer etcetera, vilka alla är effekter som redan observerats och är förutspådda att fortsätta under innevarande århundrande. Befolkningen i Indien är näst störst i världen. Större delen av befolkningen i Indien bor på landsbygden och är beroende av klimatkänsliga sektorer så som jordbruk, fiske och skogsbruk. Indiska Himalaya förser 600 miljoner människor med vatten, framtida effekter på den hydrologiska cykeln, orsakade av klimatförändringarna i området, är därför av största intresse. För att kunna hantera de framtida effekterna orsakade av klimatförändringarna är det viktigt att implementera klimatanpassningsstrategier. Den här studien kombinerar data analyser från en hydro-klimatisk modelleringskampanj (som är genomförd externt till det här arbetet), litteraturstudie över effekter på jordbruk orsakade av klimatförändringar och möjligheter att anpassa sig till dessa förändringar, samt involverar preferenser och kunskaper från intressenter inom det aktuella området för att kunna identifiera lämpliga klimatanpassningsstrategier. Studien har ett huvudfokus på klimatanpassning för jordbruksområden i två distrikt i Indien: Uttarkashi (uppströms Ganges, Uttarakhand) och Patna (nedströms Ganges, Bihar). Analysen av hydro-klimatisk data, baserad på en modelleringskampanj, fokuserar på tre klimatvariabler som är av betydelse för jordbrukssektor: nederbörd, temperatur, och evapotranspiration. För att kunna karakterisera framtida klimat har IPCCs fyra representativa koncentrationsvägar (RCPs) tagits hänsyn till: RCP 2.6, RCP 4.5, RCP 6.0, och RCP 8.5. Effekterna av dessa scenarier på de tre ovan listade klimatvariablerna är analyserade över tre framtida tidsperioder: 2011-2040, 2041-2070, 2071-2100, med ett speciellt fokus på monsunperioden från juni till oktober. Resultatet från analysen av hydro-klimatisk data indikerar en ökning under århundrandet i minimal, maximal, och genomsnittlig temperatur i båda distrikten. En ökning i evapotranspiration för båda distrikten kunde också identifieras, med några få undantag för RCP 2.6, 6.0 och 8.5 i april och maj i Patna, samt för alla RCP scenarier i april, maj och juni för Uttarkashi. Trender i nederbörd visar en ökning i maximal och genomsnittlig nederbörd för nästan alla scenarier under monsunperioden i Patna (exempel på scenarier där den genomsnittliga nederbörden inte ökar är RCP 4.5 och 8.5 i juni och juli under perioden 2011-2040). En ökning i maximal och genomsnittlig nederbörd identifierades i september för alla RCP scenarier och framtidsperioder, samt i augusti för RCP 2.6 och 8.5 i Uttarkashi. Kvarvarande månader visar på stor variabilitet i nederbörd för alla scenarier i båda distrikten. Litteraturstudien resulterade i en tabell med klimatanpassningsstrategier, där nio av 63 ansågs vara transformerande, samt identifierade möjliga effekter på jordbruket i de två distrikten orsakade av klimatförändringar. Ökningen i minimal temperatur kan leda till mer allvarliga och intensifierade hagelstormar i framtiden. Temperaturökningen kan i Uttarkashi leda till förlängd odlingssäsong medan ökningen i genomsnittlig och maximal temperatur kan leda till värmestress på grödorna i Patna. Vidare gäller att ökningen i maximal och genomsnittlig nederbörd kan leda till mer allvarliga naturkatastrofer i framtiden som exempelvis jordskred i Uttarkashi och översvämningar i Patna. Ökningen i evapotranspiration kombinerat med minskningen i genomsnittlig nederbörd under vissa månader skulle kunna leda till ett ökat bevattningsbehov. Två ”worskhops” anordnades i regionen med målet att sammanföra forskare och intressenter (exempelvis bönder) för att gemensamt diskutera 1) lämpligheten av användandet av hydrologiskt modellerad data för att förbereda jordbruket på klimatförändringar, och 2) föreslå lämpliga klimatanpassningsstrategier baserat på forskarnas och intressenternas kunskap och erfarenheter. Informationen från den första workshopen erhölls genom en workshoprapport, medan informationen i den andra workshopen erhölls genom författarens eget deltagande i workshopen. Resultatet från workshopen visade på att bönderna hade flertalet egna föreslag vad gäller lämpliga klimatanpassningsstrategier så som exempelvis implementerande av bevattningssystem och ökade kreditmöjligheter. Bönderna hade även börjat anpassa sig till klimatförändringar genom exempelvis ha lång- och korttids variationer av ris samt att de hade flyttat på datumet för sådden. Kombinationen av hydro-klimatisk data, litteratur och intressentpreferenser och kunskap möjliggjorde förslag på klimatanpassningsstrategier i de två distrikten. Strategier för att reducera skador på grödor och jordbruksmark orsakade av extrema händelser, varningssystem som varnar i ett tidigt skede, och diversifiering av försörjning är direkta klimatanpassningsstrategier som identifierades för båda distrikten. Försäkringslösningar, ökade kreditmöjligheter, och ett rättvist marknadspris var indirekta anpassningsstrategier som identifierats för båda distrikten. Även specifika anpassningsstrategier för respektive distrikt har identifierats, där exempelvis värme-tåliga grödor identifierades som viktigt för Patna och implementering av bevattningssystem identifierades som extra viktigt för Uttarkashi.

>Magister Scientiae - MSc
The occurrence and spread of Invasive Alien Plants (IAPs) is a threat to global water resources and natural ecosystems due to high water use rates. With the current climate change projections and their ability to survive extreme environmental conditions, these species pose a huge threat to grazing resources, water availability and ecosystems in general. Routine monitoring and understanding their distribution and potential vulnerable areas is fundamental as it provides the requisite baseline information to guide clearing efforts and other related management and rehabilitation initiatives.

Globally fish production has continued to increase during recent years at a rate exceeding that of human population growth. However the contribution from capture fisheries has remained largely static since the late 1980s with the increase in production being accounted for by dramatic growth in the aquaculture sector. As of 2012 aquaculture accounted for approximately 42% of total fisheries production and 78% of inland fish production. In view of these figures it is unsurprising that for a number of regions aquaculture represents an important source of both food security and income. The use of Geographical Information Systems (GIS) and spatial data have seen substantial developments in recent years with the help of increasingly affordable computing capacity. From an aquaculture perspective the use of GIS has shown significant potential as a means of combining varied data sources, including those acquired via remote sensing, into models to provide decision support in relation to site selection. A common theme amongst site suitability assessments is the incorporation of climate variables relating to temperature and water availability. These factors in turn can have a significant influence on aquaculture in terms of water availability and quality, and temperature modulated growth performance. There is now a strong consensus that during the 20th century, and especially during recent decades, the earth has experienced a significant warming trend. There is also strong agreement that this warming trend is at least partially a consequence of anthropogenic greenhouse gas emissions and that some degree of further warming is inevitable. While global warming is typically discussed in terms of degrees centigrade of average global temperature increase the full effects in terms of climate changes will be varied both in terms of location and season. The current project focuses on site suitability for aquaculture in relation to changing climate conditions. Significant use is made of GIS and a range of spatial data including remotely sensed data and output from a series of climate models. The project consists of a number of key components: 1. Vulnerability of aquaculture related livelihoods to climate change was assessed at the global scale based on the concept of vulnerability to climate related impacts as a function of sensitivity to climate change, exposure to climate change, and adaptive capacity. Use was made of national level statistics along with gridded climate and population data. Climate change scenarios were supplied using the MAGICC/SCENGEN climate modelling tools. Analysis was conducted for aquaculture in freshwater, brackish, and marine environments with outputs represented as a series of raster images. A number of Asian countries (Vietnam, Bangladesh, Laos, and China) were indicated as most vulnerable to impacts on freshwater production. Vietnam, Thailand, Egypt and Ecuador stood out in terms of brackish water production. Norway and Chile were considered most vulnerable to impacts on Marine production while a number of Asian countries (China, Vietnam, and the Philippines) also ranked highly. 2. Site suitability for pond-based aquaculture was modelled at the global scale using a 10 arcsecond grid. Data from an ensemble of 13 climate models was used to model pond temperature and water availability for rain fed ponds under late 20th century conditions and for a 2°C global warming scenario. Two methods are demonstrated for combining data with a focus on the culture of warm water species. Results suggest both positive and negative impacts in relation to the 2°C warming scenario depending on location and season. Some areas are projected to see negative effects from maximum temperatures during the warmest parts of the year while for many regions there are likely to be potential increases in growth performance during colder months with possible expansion into previously unsuitable areas. 3. Methods for detecting surface water using remotely sensed data were investigated for Bangladesh. Use was made of data from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat ETM+ instruments with accuracy assessed against ground truth data collected in the field. A time series was constructed using all available MODIS data (approximately 13 years with an 8 day temporal resolution) to show areas of: surface water, land, and mixed land and water. The time series was then analysed to produce a layer showing the percentage of the total time series where surface water is indicated thus providing a spatial representation of flood prevalence. 4. A land cover data set was produced using 9 Landsat ETM+ scenes to cover the majority of Bangladesh. 10 different classification routines were evaluated including a decision tree approach unique to the current study. Classification results were assessed against two sets of ground control points produced: one based on field collected ground truth data and the other using a stratified random sampling procedure in association with visual analysis of high resolution true colour satellite images and ETM+ composites. The most accurate classifications were provided by the decision tree method developed for the current study and a Multi-Layer Perceptron (MLP) neural network based classifier. 5. Site suitability for pond-based aquaculture within Bangladesh was assessed using a GIS in combination with the ETM+ based land cover data, the MODIS based surface water time series, and components of the global site suitability assessment including modelled pond temperature data. Assessments were made based on late 20th century conditions and a 2°C global warming scenario. The MODIS surface water time series was also used to show the effects of storm surge flooding in relation to cyclone Aila that struck Bangladesh on 25th May 2009. The south and east of the country were considered most suitable for aquaculture due to more favourable cold season temperatures and higher water balance values. The north west of the country was considered least favourable due to higher maximum modelled pond temperatures and lower water balance values. The effect of the 2°C warming scenario was to enhance these trends. To date the potential spatial implications of changing climate for aquaculture has been significantly under researched. In this respect the current study provides a highly useful indication of where aquaculture related livelihoods may be vulnerable. In addition valuable and unique insights are provided into the distribution of areas of both potential increased, as well as decreased, suitability for existing aquaculture and further aquaculture development.

Ticks are of global interest as the pathogens they spread can cause diseases that are of importance to both human health and economies. In Scotland, the most populous tick species is the sheep tick Ixodes ricinus, which is the vector of pathogens causing diseases such as Lyme borreliosis and Louping-ill. Recently, both the density and spread of I. ricinus ticks have grown across much of Europe, including Scotland, increasing disease risk. Due to the nature of the tick lifecycle they are particularly dependent on environmental factors, including temperature and habitat type. Because of this, the recent increase in tick-borne disease risk is believed to be linked to climate change. Many mathematical models have been used to explore the interactions between ticks and factors within their environments; this thesis begins by presenting a thorough review of previous modelling of tick and tick-borne pathogen dynamics, identifying current knowledge gaps. The main body of this thesis introduces an original mathematical modelling framework with the aim to further our understanding of the impact of climate change on tick-borne disease risk. This modelling framework takes into account how key environmental factors influence the I. ricinus lifecycle, and is used to create predictions of how I. ricinus density and disease risk will change across Scotland under future climate warming scenarios. These predictions are mapped using Geographical Information System software to give a clear spatial representation of the model predictions. It was found that as temperatures increase, so to do I. ricinus densities, as well as Louping-ill and Lyme borreliosis risk. These results give a strong indication of the disease risk implications of any changes to the Scottish environment, and so have the potential to inform policy-making. Additionally, the models identify areas of possible future research.

There is a consensus of scientific thought that humana ctivities are altering the gaseous composition of the atmosphere and leading to global climate change. This thesis addresses the question of how this global climate change will manifest itself at the regional level. In particular, a dynamic simulation model integrating both climate change and climatically sensitives ocio-economic activities will be developed. This model will explore the regional variations in both climate change and socio-economic activity. Three Local Authorities in Scotland were chosen for this study, Argyll on the west coast, Stirling inland and Fife on the east coast. This provides a west-east transect across central Scotland. Meteorological data, covering the period 1970-1998, was collected from twelve sites spread across these regions. These data were analysed in order to provide a climatic profile of each of the regions, and to identify any evidence of climate change in the form of trends in the data. Data relating to socio-economic factors was taken from a variety of sources. Mere possible this covered the same period in time as the climate data. Both sets of data were examined to determine evidence of climate sensitivity in the socioeconomic data using suitable statistical techniques. A simple, yet thermodynamically sound, dynamic climate model was developed and calibrated for each region using the data from the previous analysis. This model allowed increasing levels of atmospheric carbon dioxide (C02) to directly affect the mean surface temperature of the three regions. Precipitation changes from the UKCIP02 regional climate model were included This allowed seasonal temperature and precipitation totals to be simulated, on a regional basis, under different climate change scenarios. Simulations, calibrated on datafrom 1970-1998, were run forward to 2100. The climate results were similar to the outputfrom the UKCIP02 model. Six sectors of a socio-economic model were constructed population, employment, land use, water resources, housing and emissions. Where statistically significant relationships, between climatic and the local socio-economic variables were found, these were included in the model. Simulations for the period 1970-2100, were run under four different climate change scenarios, and that of constant climate, in order to assessth eir impact on the six sectors at the regional scale. The results indicate considerable regional variations in the impacts both of climate change and the associated climatically sensitive activities. Argyll in the west, for example, could benefit from increased tourism and the potential for agricultural expansion. If in-migration is allowed to offset labour shortages, then the west sees a reversal of the population decline of previous decades. Climate change has little impact on the economy of the inland and eastern regions. However, a problem does emerge with water resources in the east. Summer droughts are seen to increase in frequency, suggesting that both the costs and benefits of climate change will be unevenly distributed. The implications of these results for the management of change are then discussed along with future research needs.

Altitudinal treeline advance represents a sensitive and well-studied example of species response to climate warming. Although a great deal of work has been conducted globally, few studies have considered subtropical alpine treelines and little is known about their structure and function. This research aims to investigate the response of high altitude forests in Taiwan to climate variation by characterising treeline advance in the area, exploring the mechanisms driving the advance, and considering the consequences of advance for the wider community. The thesis consists of a general introduction to the topic followed by a series of papers, exploring: (1) Possible consequences of treeline shifts for biodiversity and ecosystem function. (2) The advance of the Abies kawakamii treeline through aerial photograph analysis. (3) The changes in growth rate of Abies kawakamii at treeline and the influence of altitude and temperature on growth. (4) Regeneration patterns at treeline and the importance of microclimate and topographic sheltering. (5) Consequences of the range shift for the wider forest community. The work is then concluded with a general discussion and synthesis. The main aims of this work are therefore to characterise and understand the pattern and pace of treeline advance and forest structural change throughout the Central Mountain Range of Taiwan. Treeline advance is characterised through the study of repeat aerial photographs and the mechanisms behind the observed shift are explored through the study of two key responses associated with forest advance: tree growth at treeline and seedling establishment beyond treeline. The consequences of treeline advance for the wider subalpine community are investigated through the study of epiphytic lichen communities at treeline sites. This investigation of an understudied region will allow for improved understanding of treeline response at a global scale.

L'objectif général de cette thèse est axé sur l’amélioration de modèles agro-hydrologique spatialement distribués pour l’analyse d'agro-hydrosystèmes, sous contrainte de changements climatiques et anthropiques. Cette thèse est structurée autour de trois questions de recherche liées à : i) la représentation de la dynamique spatio-temporelle des systèmes de cultures pour leur utilisation en entrée de modèles agro-hydrologiques distribués ; ii) la représentation du niveau exploitation agricole et des décisions des agriculteurs dans les modèles agro-hydrologiques distribués ; iii) la capacité de ces modèles à simuler des changements climatiques et anthropiquesDes éléments de réponse à ces questions sont apportés par des approches de modélisation réalisées dans différents contextes et à différentes échelles d’espace et de temps. Ces différentes approches sont discutées en les comparant notamment avec d’autres travaux réalisés. Ces différentes études soulèvent la nécessité de développer des méthodologies permettant i) d’une part l’acquisition de données et leur intégration dans les modèles agro-hydrologiques distribués ii) et d’autre part l’amélioration de l’exploitation des simulations, notamment pour les transformer en informations pertinentes et accessibles pour les parties prenantes au niveau d’un territoire. Des perspectives, portant à la fois sur la prise en compte des incertitudes des simulations des modèles agro-hydrologiques et l’analyse de la robustesse de ces modèles, sont également considérées
The general objective of this thesis is to improve spatially distributed agro-hydrological models for agro-hydrosystems analysis, under climatic and anthropogenic changes, in order to contribute to the identification of levers of action to mitigate effects of non-point source agricultural pollution. This thesis is structured around three research questions related to: i) the representation of spatio-temporal dynamics of cropping systems for their use as input in distributed agro-hydrological models; ii) the representation of farm level and decisions of farmers in distributed agro-hydrological models; and iii) the ability of these models to simulate climate and anthropogenic changes.Elements of response to these questions are provided by modeling approaches carried out in different contexts and at different scales of space and time. These approaches are discussed by comparing them with other works carried out. These different studies raise the need to develop methodologies allowing (i) the acquisition of data and their integration in distributed agro-hydrological models (ii) and, the improvement of the use of simulations results, in particular to transform them into relevant and accessible information for stakeholders at territorial level. Perspectives, covering both uncertainties of the simulations of the agro-hydrological models and the analysis of the robustness of these models, are also considered

Concentrations of dissolved organic carbon (DOC) measured within water bodies have been increasing on a global scale over the last two decades. Changes in temperature and rainfall have been shown to increase the production and export of DOC from catchments with peat soils in the UK (Freeman et al., 2001). However it is not clear whether increases in DOC concentrations are caused by production increases induced by temperature changes or by a greater incidence of high flows induced by rainfall changes. Increases in both temperature and rainfall have been predicted in Scotland over the next few decades (Kerr et al., 1999) which may further increase current DOC concentrations and exports. The implications of this include both a decrease in water quality and an increase in mobility of metals in upland water bodies. The overall aim of the thesis is to determine if the relationship between dissolved organic carbon (DOC) concentrations and discharge has changed over a 20 year period in small stream catchments in Scotland, in order to better understand the role of hydrology, in driving changes in DOC concentration. To achieve this streams draining two coniferous forest sites and one moorland site were monitored intensively between June 2004 and February 2006. Analysis of the relationship between DOC and discharge, within the catchments, identified the importance of the amount of precipitation falling on the catchment, antecedent precipitation and season, on the concentration of DOC that was measured within the stream. Models were then developed using variables to represent these drivers in terms of both the production (seasonal sine values and 14 day average temperatures) and movement (log of discharge (log Q), days since previous storm event and rising or falling stage) of DOC. In the Ochil Hills catchment, the best predictive model, used 4 hour average discharge and 1 day average 30cm soil temperatures (R2= 0.88). In the Duchray and Elrig catchments, the best predictive models produced used discharge and seasonal sine values; the strength of the model was greater in the Elrig (R2= 0.80) than the Duchray (R2= 0.48) catchment. The strength of the regression models produced highlighted the importance of precipitation in the movement of DOC to the stream and temperature variables representing production in the surrounding catchment. To determine if dissolved organic carbon (DOC) concentrations had changed within the three study catchments, since previous research was conducted at the same sites in the early 1980s and 1990s (Grieve, 1984a; Grieve, 1994), then regression analysis conducted in the previous research was repeated, so changes in the DOC and discharge relationship could be identified. Analysis of the Ochil Hills regression equations identified higher log of discharge and lower temperature and seasonal sine values in the present study (2004-06), when compared to the previous study (1982-83). This suggests that more DOC is now available for movement from the soil, and that the difference between winter and summer DOC production has decreased, potentially because of increasing temperatures. This would explain the limited increase in DOC concentration within the Ochil Hills stream. In the Duchray and Elrig streams, a large increase in DOC was identified at all discharges when all the models produced were compared between the two sampling periods (1989-90 and 2004-06). The increasing trend in DOC concentrations is too large to have been produced by change in temperature alone and it is suggested that the measured reduction in acidic deposition has resulted in the increased DOC concentrations measured in the Duchray and Elrig. The results from this research have identified that concentrations of DOC have increased in Scottish streams over the last 20 years and that the increases in DOC have been induced, potentially by temperature changes in climate. However, changes in temperature are not the only driver of this change as the reduction in acidic deposition is potentially more important, specifically in areas with base poor geology such as the Duchray and Elrig catchments.

Permafrost is an important component in Arctic environments and has been hypothesized to be diminishing due to global warming. A growing concern is that large quantities of stored organic carbon will be mobilized and released to the atmosphere as the potent greenhouse gas methane if the ground thaws. This could result in a massive positive feedback on the global climate change. To quantify this effect, the permafrost extent as well as carbon storages must be mapped. In this study, a Basal Temperature of Snow (BTS) survey is conducted in the Tarfala Valley in Northern Sweden and a model of the current permafrost extent in the region is produced. Additionally, the model explores how the permafrost extent will change under three climate change scenarios at +1°C, +2°C and +4°C. According to a statistical analysis, elevation is the only significant variable for permafrost occurrence in the Tarfala Valley. Currently, continuous permafrost (>0.8 probability) is present at elevations exceeding 1523 m a.s.l. and sporadic or patchy permafrost (<0.5 probability) dominates below 1108 m a.s.l. The permafrost in Northern Sweden is near the boundary of favorable conditions for permafrost, and the greatest decline in permafrost extent occurs during the initial warming. In the +1°C scenario, which will be reached in 20 years if current warming rate is sustained, 97.6% of the continuous permafrost in the Abisko and Tarfala area degrades. The areal extent of the zone with the lowest probability of permafrost occurrence increases from 59% to 90% in the same scenario. Under continued warming to +4°C compared to current ground temperatures, 98% of the study area will be covered by sporadic or patchy occurrences of permafrost.
Permafrost är en viktig komponent i arktiska miljöer och befaras minska i utbredning på grund av den globala uppvärmningen. En farhåga är att stora mängder bundet organiskt kol ska mobiliseras och släppas ut till atmosfären som den potenta växthusgasen metan om marken värms. Detta skulle kunna innebära stor positiv återkoppling på de globalt stigande temperaturerna. För att kvantifiera den effekten är det viktigt att kartlägga permafrostens utbredning såväl som mängde bundet kol i permafrostmarker. I den här studien utförs en undersökning av bastemperaturen av snötäcket (BTS) i Tarfaladalen i norra Sverige och en modellering av permafrostens nuvarande utbredning i regionen. Vidare modelleras hur permafrostens utbredning kommer att påverkas i framtiden under tre olika klimatförändringsscenarior vid +1°C, +2°C och +4°C. Enligt en statistisk analys är altitud den enda signifikanta variabeln för permafrostförekomst i Tarfaladalen. Vid nuvarande marktemperaturer är kontinuerlig permafrost (>0.8 probabilitet) utbredd på höjder över 1523 m ö.h. och sporadisk permafrost (0.5 - 0 probabilitet) dominerar under 1108. Permafrosten i norra Sverige är nära gränsen för dess gynnsamma förhållanden och den huvudsakliga förlusten av permafrost sker redan vid en blygsam markuppvärmning. I scenariot +1°C, som inträffar redan om 20 år om nuvarande uppvärmningstakt fortsätter, degraderas 97.6% av den kontinuerliga permafrosten i Abisko och Tarfalaområdet. Utbredningen av sporadisk permafrost, det vill säga zonen med lägst sannolikhet för permafrostförekomst, ökar i det scenariot från 59% till 90%. Vid fortsatt uppvärmning till +4°C jämfört med nuvarande marktemperaturer så kommer 98% av det studerade området endast innehålla sporadiska förekomster av permafrost.

The climate of the Neoproterozoic Snowball Earth is tested in the UKMO Unified Model, specifically the HadCM3 climate model. The model is largely left unchanged, but the boundary conditions, both external and initial, are adjusted to create experiments based on the Snowball Earth hypothesis. The model can reproduce multiple equilibrium climates, as have been seen in energy balance models of the Earth's climate. The modelled present day and Neoproterozoic versions of Earth can both reproduce both ice capped and ice covered climate states. Neither can reproduce a climate which remains ice free throughout the year, even with an equilibrated ocean or elevated levels of C02. In all cases the ice free climate reverts toward the ice capped climate after the first polar winter. The modelled Neoproterozoic ice covered climate, that is the climate of Snowball Earth, has a climate very different from the present day. These changes are mostly driven by the lower thermal inertia, latitudinal temperature differences and the changed meridional circulation that results. The weather of the modelled Snowball Earth climate is also very different, dom- inated by a strong diurnal variation due to solar heating, as opposed to the more varied weather in the present day. The model responds well to the conditions of the Snowball Earth climate, with temperatures similar to those predicted by a simple physical model. The model responds less well to high levels of C02 in the Snowball Earth climate. The ice model also allows excessive heat and moisture to escape from the ocean into the atmosphere compared to that that would be predicted from solid ice coverage of the ocean. The exit from a Snowball Earth state was also tested within the model. Neither an decrease in albedo nor an increase in CO2 is unable to increase the temperature of the climate system sufficiently to exit the Snowball Earth state.

The main objective of this thesis is to develop a robust statistical model by accounting the non-linear relationships between hospital admissions due to lower respiratory (LR) disease and factors of climate and pollution, and their delayed effects on hospital admissions. This study also evaluates whether the model fits can be improved by considering the non-linearity of the data, delayed effect of the significant factors, and thus calculate threshold levels of the significant climate and pollution factors for emergency LR hospital admissions. For the first time three unique administrative datasets were merged: Hospital Episode Statistics, Met office observational data for climate factors, and data from London Air Quality Network. The results of the final GLM, showed that daily temperature, rain, wind speed, sun hours, relative humidity, and PM10 significantly affected the LR emergency hospital admissions. Then, we developed a Distributed lag non-linear model (DLNM) model considering the significant climate and pollution factors. Time and ‘day of the week’ was incorporated as linear terms in the final model. Higher temperatures around ≥270C a quicker effect of 0-2 days lag but lower temperatures (≤00C) had delayed effects of 5-25 days lag. Humidity showed a strong immediate effect (0-3 days) of the low relative humidity at around ≤40% and a moderate effect for higher humidity (≥80%) with lag period of 0-2 days. Higher PM10 around ≥70-μg/m3 has both shorter (0-3 days) and longer lag effects (15-20 days) but the latter one is stronger comparatively. A strong effect of wind speed around ≥25 knots showed longer lag period of 8-15 days. There is a moderate effect for a shorter lag period of 0-3 days for lower wind speed (approximately 2 knots). We also notice a stronger effect of sun hours around ≥14 hours having a longer lag period of 15-20 days and moderate effect between 1-2 hours of 5-12 days lag. Similarly, higher amount of rain (≥30mm) has stronger effects, especially for the shorter lag of 0-2 days and longer lag of 7- 10 days. So far, very little research has been carried out on DLNM model in such research area and setting. This PhD research will contribute to the quantitative assessment of delayed and non-linear lag effects of climate and pollutants for the Greater London region. The methodology could easily be replicated on other disease categories and regions and not limited to LR admissions. The findings may provide useful information for the development and implementation of public health policies to reduce and prevent the impact of climate change on health problems.

This study focuses on the impact of potential changes in the wind-wave climate on shoreline change. The 'one-line' model for medium to long-term prediction of coastline evolution is employed. New analytical and numerical solutions of this important model are described. Specifically: 1) original semi-analytical solutions are derived that relax the unrealistic assumption of existing analytical work that a constant wave condition drives shoreline change and, 2) a more general form of the one-line model is solved with a novel application of the 'Method of Lines'. Model input consists of 30-year nearshore wave climate scenarios, corresponding to the 'present' (1961-1990) and the future (2071-2100). Winds from a high resolution, (12km x 12km), regional climate model, obtained offshore of the south-central coast of England at a dense temporal resolution of 3 hours, are used to develop the aforementioned wave climate scenarios, through hindcast and inshore wave transformation. A hypothetical shoreline segment is adopted as a 'benchmark' case for comparisons. Monthly and seasonal statistics of output shoreline positions are generated and assessedfo r relative changeso f 'significance' between 'present' and future. Different degrees of evidence that such changes do exist are found. This study is the first application of such high resolution climate model output to investigate climate change impact on shoreline response. Major findings include: 1) shoreline changes of 'significance' are strongly linked to 'significant' changes in future wave direction, 2) future changes appear smaller for entire seasons than for individual months, 3) shoreline position variability is often smaller in the future, 4) different climate model experiments produce diverging results; however, general trends are largely similar. The present study, at a fundamental level, offers analytical solutions of the 'oneline' model that are closer to reality and a numerical solution that is of increased effciency. At a practical level, it contributes to better understanding of the patterns of shoreline response to changing offshore wave climate through: 1) the use of fast and straightforward methods that can accommodate numerous climate scenarios without need for data reduction, and 2) the development of a methodology for using climate model output for coastal climate change impact assessment studies.

Scour of bridge piers and abutments has been identified as the main cause of bridge collapse around the world. Undermining of bridge foundations occurs by river sediment removal which may lead to loss of their load bearing capacity. Long-term climate change arising from global warming has the potential to further exacerbate bridge scour due to increased river flooding resulting from increased precipitation. It is important for bridge owners and managers to understand how the risk of their bridge is likely to change due to the potential effects of climate change as this will assist towards their long-term management so that the consequences arising from bridge failures/damage can be minimised as far as possible. In the UK, climate change is expected to increase the magnitude and/or frequency of precipitation, leading to increased and/or more frequent river flooding. Several recent studies on high river flows in various British rivers predict future peak discharges that capture climate change effects. These predictions supersede the older 20% and 25% allowances that have been used in the UK in the past for climate change analyses. In this research, selected climate change allowances for the UK (Environment Agency, 2016) were applied to two common bridge assessment methodologies. As part of this study, the UK highway and railway scour assessment codes were reviewed to assess their capability in capturing climate change effects on bridge scour and identify potential limitations. The main limitation of the railway code was identified as being its inability to account for changes in river discharge. The Highway Agency (2012) (BD97/12), which has been developed more recently, was suitable for adaptation to capture climate change effects on bridge scour and, as a result, has been the focus of this study. A large number of analyses were carried out as part of this study to quantify the effects of climate change on bridge scour. The generated scour data consisted of 27,000 scour depths for bridges on wide river channels, 18,000 on intermediate and 9,000 on narrow channels, each accounting for different median sediment sizes, foundation depth, pier width and angle of attack. The aim was to simulate a large number of scenarios of bridge-river configurations to identify which situations are more susceptible to climate change effects. It was found that, in some situations, climate change has the potential of shifting the scour risk ranking of bridges to a higher risk level, potentially leading to changes in their long-term risk management. The angle of attack effect on scour risk was found to be the factor that has the most significant effect on scour risk irrespective of bridge location/river channel type. Other key findings of this research are that Highway Agency (2012) the BD97/12, the scour assessment method for highway bridges over predicted scour depth. Sediment sizes and foundation depths have significant effect on bridge scour alongside the opening ratio of a bridge The availability of a large database with scour field measurements in the USA offered the opportunity to assess the accuracy of the scour model predictions in the Highway Agency (2012) BD97/12. The majority of bridge scour equations have been derived from idealised laboratory studies which may not necessarily be representative of realistic river conditions. Statistical analyses were used to quantify the deviations between code predictions and real measurements. The former were found to lead to conservative predictions. Probabilistic distributions were fitted to the data and suggested as modelling uncertainty factors to be used with the existing scour models in the codes to update their predictions to more realistic levels.

Climate change is a complex problem. Approaches to understanding climate change risk and preparing for its management include assessments of biophysical changes, the influence of public risk perceptions on support for policies aimed at adapting to these changes, and analysis of the governance structures charged with developing and implementing climate action plans. Climate change issues, however, are often approached from a disciplinary perspective and there are few studies examining how climate risk is viewed from multiple perspectives in a particular locale. This thesis takes a bottom-up approach to understanding climate change by focusing on how climate risk is understood on the Sunshine Coast, British Columbia, as a biophysical, social, and governance issue. It begins by surveying the available biophysical information of climate change and presents a sea level rise impact model for the Sunshine Coast. Next, it explores how public perceptions of climate risk (as distinct from climate change knowledge as scientific literacy) develop and how these affect support for climate change policies. It then examines the perspective of a local government, the Town of Gibsons, in planning for climate change adaptation. Here, it focuses on how decision- makers plan for climate change by examining their perspectives on biophysical risks and the social context within which climate issues are located. Throughout the thesis, I argue that the process of adapting to climate change (a risk management strategy) has strongly social roots and that understanding how climate change fits within the context of individual communities is, along with knowledge of biophysical hazards, an essential component of adaptation.
Science, Faculty of
Resources, Environment and Sustainability (IRES), Institute for
Graduate

It is thought that climate change will have a major impact on species distributions by changing the habitat suitability for species. Species distribution modelling is a modern approach to assess the potential effect of climate change on biodiversity. We used 11 environmental variables with the MaxEnt algorithm to model the distributions of 114 Egyptian medicinal plant species under current conditions, then projecting them into three different future times (2020, 2050, and 2080) under two different climate-change emission scenarios (A2a and B2a), under two hypotheses about the capability of the species for dispersal (unlimited and no dispersal). Species richness maps for current and future times were produced. We tested the value of Egypt’s Protected Areas under climate change by estimating the species richness inside and outside under each scenario. We assessed Egyptian medicinal plants based on IUCN Red List categories and criteria, and then used the SDMs for conservation planning with and without consideration of socioeconomic factors using Zonation software. The A2 emission scenario was more harmful than B2 under all assumptions. Species richness inside Protected Areas was significantly higher than outside for all models. Based just on the records, between 75% and 90% of species could be classified as Least Concern, according to the assumptions made. Similarly, based on SDMs all species could be classified as LC at the current time, whilst in the future under climate change, up to 18% of species face the risk of extinction, depending on assumptions and based on the absolute time gap between the two future times. Based on 10 years, most species were assigned as Least Concern. Areas within PAs were no better in conservation prioritization value than area outside when socioeconomic costs (especially the Human Influence Index) were taken into account. Species distribution models appear to be extremely useful for conservation planning under climate change, particularly when only sparse data are available. Socioeconomic information adds a new dimension to conservation planning, which is actually misleading and incomplete without it.

Climate change associated with increasing concentrations of the greenhouse gas, carbon dioxide(CO2), is expected to lead to an increase in global mean temperature of between 1 and 3.5 deg C by the end of the 21st century, with regional changes in rainfall and humidity. This thesis is concerned with modelling the effects of a changing climate and atmospheric C02 concentration on global vegetation. The process-based model, DOLY (Dynamic glObal phtogeographY), is used. It is able to operate using three climate variables, two soil variables and an atmospheric CO2 concentration. Its outputs are leaf area index (LAI), and net primary productivity (NPP). The LAI and NPP values predicted by DOLY were used to run a life-form model with a climate change scenario. It was found that warming led to the spread of trees into the tundra region. The DOLY model was also coupled with the Hadley Centre general circulation model to determine the feedbacks of vegetation on climate. With a global warming of 2◦C, the global feedback of vegetation on temperature was a decrease of 0.1 deg C. However at the regional scale the feedback was +/-2 ◦C, of similar magnitude to the driving temperature change. Finally, the DOLY model was run with transient climate data from the Hadley Centre. The boreal forest moved north, and the Gobi desert and the southern steppes in the former Soviet Union shrank in area. The sensitivity of the model to its soil and climate inputs have also been analysed over a range of environments and the model has been validated with reference to satellite data and experimental data. It was found to perform well. This thesis has shown that it is possible to predict current and possible future distributions of vegetation with climate change using a vegetation model.

Particulate matter suspended in air (i.e. aerosol particles) exerts a substantial influence on the climate of our planet and is responsible for causing severe public health problems in many regions across the globe. Human activities have altered the natural and anthropogenic emissions of aerosol particles through direct emissions or indirectly by modifying natural sources. The climate effects of the latter have been largely overlooked. Humans have dramatically altered the land surface of the planet causing changes in natural aerosol emissions from vegetated areas. Regulation on anthropogenic and natural aerosol emissions have the potential to affect the climate on regional to global scales. Furthermore, the regional climate effects of aerosol particles could potentially be very different than the ones caused by other climate forcers (e.g. well mixed greenhouse gases). The main objective of this work was to investigate the climatic effects of land use and air pollution via aerosol changes. Using numerical model simulations it was found that land use changes in the past millennium have likely caused a positive radiative forcing via aerosol climate interactions. The forcing is an order of magnitude smaller and has an opposite sign than the radiative forcing caused by direct aerosol emissions changes from other human activities. The results also indicate that future reductions of fossil fuel aerosols via air quality regulations may lead to an additional warming of the planet by mid-21st century and could also cause an important Arctic amplification of the warming. In addition, the mean position of the intertropical convergence zone and the Asian monsoon appear to be sensitive to aerosol emission reductions from air quality regulations. For these reasons, climate mitigation policies should take into consideration aerosol air pollution, which has not received sufficient attention in the past.

Understanding of climate change and policy responses thereto rely on accurate measurements as well as models of both socio-economic and physical processes. However, data to assess impacts and establish historical climate records are non-stationary: distributions shift over time due to shocks, measurement changes, and stochastic trends - all of which invalidate standard statistical inference. This thesis establishes econometric methods to model non-stationary climate data consistent with known physical laws, enabling joint estimation and testing, develops techniques for the automatic detection of structural breaks, and evaluates socio-economic scenarios used in long-run climate projections. Econometric cointegration analysis can be used to overcome inferential difficulties stemming from stochastic trends in time series, however, cointegration has been criticised in climate research for lacking a physical justification for its use. I show that physical two-component energy balance models of global mean climate can be mapped to a cointegrated system, making them directly testable, and thereby provide a physical justification for econometric methods in climate research. Automatic model selection with more variables than observations is introduced in modelling concentrations of atmospheric CO₂, while controlling for outliers and breaks at any point in the sample using impulse indicator saturation. Without imposing the inclusion of variables a-priori, model selection results find that vegetation, temperature and other natural factors alone cannot explain the trend or the variation in CO₂ growth. Industrial production components, driven by business cycles and economic shocks, are highly significant contributors. Generalizing the principle of indicator saturation, I present a methodology to detect structural breaks at any point in a time series using designed functions. Selecting over these break functions at every point in time using a general-to-specific algorithm, yields unbiased estimates of the break date and magnitude. Analytical derivations for the split-sample approach are provided under the null of no breaks and the alternative of one or more breaks. The methodology is demonstrated by detecting volcanic eruptions in a time series of Northern Hemisphere mean temperature derived from a coupled climate simulation spanning close to 1200 years. All climate models require socio-economic projections to make statements about future climate change. The large span of projected temperature changes then originates predominantly from the wide range of scenarios, rather than uncertainty in climate models themselves. For the first time, observations over two decades are available against which the first sets of socio-economic scenarios used in the Intergovernmental Panel on Climate Change reports can be assessed. The results show that the growth rate in fossil fuel CO₂ emission intensity (fossil fuel CO2 emissions per GDP) over the 2000s exceeds all main scenario values, with the discrepancy being driven by underprediction of high growth rates in Asia. This underestimation of emission intensity raises concerns about achieving a world of economic prosperity in an environmentally sustainable fashion.

The Earth's middle atmosphere at about 10-100 km has shown a substantial sensitivity to human activities. First, the ozone layer has been reduced since the the early 1980s due to man-made emissions of halogenated hydrocarbons. Second, the middle atmosphere has been identified as a region showing clear evidence of climate change due to increased emissions of greenhouse gases. While increased CO₂ abundances are expected to lead to a warmer climate near the Earth's surface, observations show that the middle atmosphere has been cooling by up to 2-3 degrees per decade over the past few decades. This is partly due to CO₂ increases and partly due to ozone depletion.

Predicting the future development of the middle atmosphere is problematic because of strong feedbacks between temperature and ozone. Ozone absorbs solar ultraviolet radiation and thus warms middle atmosphere, and also, ozone chemistry is temperature dependent, so that temperature changes are modulated by ozone changes.

This thesis examines the middle atmospheric response to a doubling of the atmospheric CO₂ content using a coupled chemistry-climate model. The effects can be separated in the intrinsic CO₂-induced radiative response, the radiative feedback through ozone changes and the response due to changes in the climate of the underlying atmosphere and surface. The results show, as expected, a substantial cooling throughout the middle atmosphere, mainly due to the radiative impact of the CO₂ increase. Model simulations with and without coupled chemistry show that the ozone feedback reduces the temperature response by up to 40%. Further analyses show that the ozone changes are caused primarily by the temperature dependency of the reaction O+O₂+M->O₃+M. The impact of changes in the surface climate on the middle atmosphere is generally small. In particular, no noticeable change in upward propagating planetary wave flux from the lower atmosphere is found. The temperature response in the polar regions is non-robust and thus, for the model used here, polar ozone loss does not appear to be sensitive to climate change in the lower atmosphere as has been suggested recently. The large interannual variability in the polar regions suggests that simulations longer than 30 years will be necessary for further analysis of the effects in this region.

The thesis also addresses the long-standing dilemma that models tend to underestimate the ozone concentration at altitudes 40-75 km, which has important implications for climate change studies in this region. A photochemical box model is used to examine the photochemical aspects of this problem. At 40-55 km, the model reproduces satellite observations to within 10%, thus showing a substantial reduction in the ozone deficit problem. At 60-75 km, however, the model underestimates the observations by up to 35%, suggesting a significant lack of understanding of the chemistry and radiation in this region.

Oxygen production due to phytoplankton photosynthesis is an important phenomenon keeping in mind the underlying dynamics of marine ecosystems. However, despite its crucial importance, not only for marine but also for terrestrial ecosystems, the coupled oxygen-plankton dynamics have been overlooked. This dissertation aims to provide insight into an oxygen-plankton system using mathematical modelling. We firstly develop a ‘baseline’ oxygen-phytoplankton model which is then further developed through the addition of biologically relevant factors such as plankton respiration and the predator effect of zooplankton. The properties of the model have been studied both in the nonspatial case, which corresponds to a well mixed system with a spatially uniform distribution of species, and in the spatially explicit extension, by taking into account the transport of oxygen and movement of plankton by turbulent diffusion. Since the purpose of this work is to reveal the oxygen dynamics, the effect of global warming is considered taken into consideration and modelled by various oxygen production rates and phytoplankton growth functions in Chapters 5 and 6. It is shown that sustainable oxygen production is only possible in an intermediate range of the production rate. If the oxygen production rate becomes sufficiently low or high, in the course of time, the system’s dynamics shows abrupt changes resulting in plankton extinction and oxygen depletion. We show that the spatial system’s sustainability range is larger that of the corresponding nonspatial system. We show that oxygen production by phytoplankton can stop suddenly if the water temperature exceeds a certain critical threshold. Correspondingly, this dissertation reveals the scenarios of extinction which can potentially lead to an ecological disaster.

Global climate change is an important threat to biodiversity and is predicted to be a major driver of wildlife population extinctions throughout the current century. Across a wide range of taxa, a well-documented response to climate change has been changes in species distributions, often towards higher latitudes and altitudes. Species distribution models (SDMs) have been widely used to predict further range changes in future but their use has often focused on discrete geographical areas. Moreover, SDMs have typically been correlative, ignoring biological traits. Here, I use SDMs to project future ranges for the world’s terrestrial birds under climate change. To improve the realism of projected range changes, I incorporate biological traits, including species’ age at first breeding and natal dispersal range. I use these projections to predict large-scale patterns in the responses of terrestrial birds to climate change, and to explore the implications of these models for avian conservation. There is little consensus on the most useful predictors for SDMs, so I begin by exploring how this varies geographically. With this knowledge, I develop SDMs for the world’s terrestrial birds and project future species ranges using three different global climate models (CCSM4, GFDL-CM3, HadGEM2-ES) under a low (rcp26), a medium (rcp45) and a high (rcp85) representative concentration pathway. The projected ranges are used to identify species most at risk from climate change and to highlight global hotspots where species are projected to experience the highest range losses. I explore how the projected range changes affect global species communities and I identify areas where species communities are projected to change or novel communities will emerge. I assess how projected changes will affect the ability of the global Important Bird and Biodiversity Areas (IBAs) network to confer protection on the world’s terrestrial bird species. Additionally, I highlight - based on projected range loss and suitable habitat and climate space beyond the dispersal range - species that will be unable to track climate change and that could be candidates for Assisted Colonization (AC). Finally, I explore the divergence between global species richness (SR) patterns and phylogenetic diversity (PD) for the world’s terrestrial birds, to assess if measuring biodiversity and setting conservation targets based on SR can be expected to cover their PD as well. Identifying the global consequences of projected range changes can inform future conservation efforts and research priorities. Changes in range extent and overlap were projected for the vast majority of the world’s terrestrial birds, with one-fifth projected to experience major range losses (>75% decline in range extent projected). This has far reaching consequences for the IBA network, with an overall trend of species moving out of the IBA coverage. Furthermore 13% of the world’s terrestrial birds are projected to have severe range losses that, combined with an inability to follow suitable habitat and climate space, mean they could benefit from AC as a conservation tool. Overall, PD was found to be highly correlated to SR on a global scale; however, there are localized differences where PD is higher or lower than could be expected from SR alone. These differences suggest that considering PD could enhance conservation planning. The results demonstrate the major threat that climate change poses for the world’s terrestrial bird species across all areas of the globe, and highlight the importance of considering climate change impacts to enhance their protection.

This work has contributed to the understanding of dominant runoff generation at the large catchment scale and to the understanding of the relationships between landscape properties and hydrological behaviour. The developed models were used to estimate the climate change impact on the hydrology in the study catchment. A multivariate geochemical tracer survey was carried out in North Esk catchment in north east Scotland. A generic typology was developed using multivariate statistical methods to characterise the hydrochemical tracer response. Upland headwater runoff was dominant downstream in winter and provided significant flows during base flow periods in summer. These insights were complemented by a conjunctive analysis of long-term river flow data and a one year stable isotope survey. Integrative metrics of transit times, hydrometric responses, and catchment characteristics were explored for relationships at the large catchment scale. The evaluation that the associated soils and bedrocks, themselves controlling the flow path distribution, have a strong influence on the integrated hydrological catchment response. The empirically-based understanding of dominant runoff generation processes in the North Esk uplands and lowlands were used in a stepwise rainfall-runoff model development. Tracers were directly incorporated to reduce structural and parameter uncertainty. The integration of tracers helped reduce parameter uncertainty. These tracer-aided models increased confidence for using them to explore the effects of environmental change. Climate change impacts in the catchment where explored by forcing the models with projected climate change forcing from the UK Climate Projections 2009. The results revealed landscape-specific changes in the hydrological response with increased summer drought risk in the lowlands and diminishing snow influence and increased winter floods in the uplands. The spatial integration mediated the extremes observed in the subcatchments.

This thesis tests and applies a new, physically based snow distribution and melt model at spatial scales of tens of metres and temporal scales of days across sub-arctic landscapes, in order to assess the significance of snow variability in sub-arctic human ecodynamics at resolutions relevant to human activities. A wider goal is to contribute to planning in the face of future climate change. Model tests are undertaken based on original field data collected in Sweden and Norway, and secondary data from Idaho, France and Greenland. Model applications focus on the ‘completed experiment’ of the medieval Norse in Greenland, a comparatively isolated population that relied on a combination of pastoralism and hunting for survival. A combination of local calibration based on contemporary meteorological data, customised climate reconstructions based on GCM data, new archaeological survey and new DEM are used in order to apply the model. This thesis shows, for the first time, the likely range of snow depth and duration experienced across the medieval Norse Greenland landscape as a result of climate and vegetation change. Results show that increases in snow cover could have been significant drivers of transformative change in Norse Greenland, and are therefore likely to be key in understanding the potential impact of future climate changes on similar sub-arctic and relatively marginal communities. Selected model analyses simulate the total spring (April-June) snow cover at the homefields to range from 32% cover lasting 6 days in the most favourable climate to 100% cover lasting 45 days in the most unfavourable climate at key elite inner fjord farms. At the more isolated outer fjord farms, total spring snow cover ranges from 33% cover lasting 10 days in the most favourable climate to 100% cover lasting 60 days in the most unfavourable climate. Increased climate variance and recovery times, as experienced by the Norse, are potential early warning signals of threshold-crossing change. Model results show that these signals could have been masked for the Norse decision making elite because they were located in the most favourable and least snow covered locations. Masking could have been further increased through the intensified seal hunting implemented by the Norse as an adaption strategy, and these actions could have developed into a rigidity trap. When the conjunctures of the 15th century developed in terms of increased sea ice, snow cover, storminess, culture contact, changing trade and sea level rise, it was too late to develop different responses. Whilst current populations have improved technology and knowledge relative to the Norse Greenlanders, there is a risk that adaptations will lack long-term utility, spatially restricted indications of change may be ignored, and rigidity traps develop. This thesis provides an additional tool for understanding a key element of both the past and possible futures of subarctic human ecodynamics.

Over the last three decades, concern about food safety and the management of natural resources has increased. Instigated by the previous EU pesticide review, (EU 91/414) carrot growers in particular have been hit by the revocation of several post-emergence herbicides. There is real concern among growers that this may impair profits. To identify alternative weed control strategies, a modelling framework capable of simulating the impact of alternative weed management strategies on long-term weed population dynamics, was proposed. Scentless mayweed (Tripleurospermum inodorum) was chosen as model weed species. The system represented in ECOSEDYN (Effects of Cultural control and climate On SEedbank DYN For each component model in ECOSEDYN the literature was reviewed to identify the best mathematical representation and then the model was parameterised. To improve accuracy of model projections and address gaps in knowledge, field experiments were conducted in two areas: soil cultivation, and plant growth and reproduction. The results of the cultivation experiments revealed that key assumptions in models for weed seed re-distribution are incorrect. The experiments focusing on plant growth and reproduction resulted in a novel approach to the modeling of biomass increase, flowering and seed shedding where the different processes were quantitatively and temporally linked using Beta functions. amics), comprises a six-year crop rotation: one year of carrot and five years winter wheat and repeated four times. The weed management strategies consist of combinations of cultural control measures (sowing time and crop maturity time). In addition, the interaction of climate with the cultural control measures was assessed by implementing two future climate scenarios, (‘No change’ vs ‘Heating up’) based on weather data over the last 18 years. The results of the ECOSEDYN simulations showed that, regardless of the prevailing climate, choosing a fast maturing carrot cultivar is by far the most important factor in maintaining the weed seedbank low. In addition, the risk for higher seedbank levels in the long-term under ‘Heating up’ climate is largest if carrot is continuously sown late.

Soil organic matter (SOM) models simplify the complex turnover dynamics of organic matter in soils. Stabilization mechanisms are currently thought to play a dominant role in SOM turnover but they are not explicitly accounted for in most SOM models. One study addresses the implementation of an approach to account for the stabilization mechanism of physical protection in the SOC model RothC using 13C abundance measurements in conjunction with soil size fractionation data. SOM models are increasingly used to support policy decisions on carbon (C) mitigation and credibility of model predictions move into the focus of research. A site scale, Monte Carlo based model uncertainty analysis of a SOM model was carried out. One of the major results was that uncertainty and factor importance depend on the combination of external drivers. A different approach was used with the SOM ECOSSE model to estimate uncertainties in soil organic carbon (SOC) stock changes of mineral and organic soils in Scotland. The average statistical model error from site scale evaluation was transferred to regional scale uncertainty to give an indication of the uncertainty in national scale predictions. National scale simulations were carried out subsequently to quantify SOC stock changes differentiating between organic and mineral soils and land use change types. Organic soils turned out to be most vulnerable to SOC losses in the last decades. The final study of this thesis emplyed the RothC model to simulate possible futures of global SOC stock changes under land use change and ten different climate scenarios. Land use change turned out to be of minor importance. The regionally balance between soil C inputs and decomposition leads to a diverse map of regional C gains and losses with different degrees of certainty.

Adaptation is necessary to cope with, or take advantage of, the effects of climate change on socio-ecological systems. This is especially important in the forestry sector, which is sensitive to the ecological and economic impacts of climate change, and where the adaptive decisions of owners play out over long periods of time. These decisions are subject to experienced and expected impacts, and depend upon the temporal interactions of a range of individual and institutional actors. Knowledge of, and responses to, climate change are therefore very important if forestry is to cope with, or take advantage of, the effects of climate change over longer timescales. It is important to understand the role of human behaviour and decision-making processes in the study of complex socio-ecological systems and modelling is a method that can support experiments to advance this understanding. This study is based on the development of CRAFTY-Sweden; an agent-based model that allows the exploration of Swedish land-use dynamics and adaptation to climate change through scenario analysis. In CRAFTY-Sweden, forest and farmland owners make land use and management decisions according to their objectives, management preferences and capabilities. As a result of their management and location characteristics they are able to provide ecosystem services. To explore future change, quantitative scenarios were used that considered both socio-economic development pathways and climatic change. Simulations were run under the different scenarios for the period 2010-2100, for the whole of Sweden. Furthermore, because institutions (i.e. organisations) also influence socio-ecological systems through their actions and interactions between them and with land owners and the environment, a conceptual model of institutional actions applied to socio-ecological systems was developed. The application of this conceptual model was explored through a model of institutions that can act, interact and adapt to environmental change in attempting to affect ecosystem service provision within a simple forestry governance system. I found that forestry in the future will likely be unable to meet societal demands for forest services solely on the basis of autonomous adaptation. A northward expansion of agriculture and especially of forestry proved positive for both sectors to adapt to changing conditions, under several scenarios, given the substantial land availability and the improved environmental conditions for plant growth. Legacy effects of past land-use change can have a great impact on future land-use change and adaptation processes, especially in forestry. Also, greater competition for land may lead to shorter forest rotation times. Socio-economic change and land owner behavioural differences may have a larger impact on owner competitiveness, land-use change and ecosystem service provision than climate-driven changes in land productivity. Different owner objectives and behaviour resulted in different levels of ecosystem service provision. Also, particular forest types were differently suitable for adaptation depending on the sets of objectives under which they were managed. Owners implementing particular management strategies can be differently competitive under different future scenarios, and the suitability of such strategies for adaptation is not a static, inherent characteristic of a system. Instead, it evolves in response to changing contexts that include both the external global change drivers and the internal dynamics of agent interactions. Additionally, institutional conceptual models as presented here can support better understanding of the key institutional decision-making dynamics and their consequences, endogenously, flexibly across different socio-ecological systems. Finally, study limitations, future research and the policy relevance of findings are discussed.

Climate and the environment are key determinants impacting various aspects of disease transmission, including lifecycle, survivability and prevalence. Recent changes in both the long-term climatology, and short term El Niño events are impacting the spatial distribution of disease, increasing the number of people being at higher risk of contracting fatal diseases. These changes are particularly detrimental in developing countries, where socioeconomic conditions hinder access to disease prevention and treatment. This thesis explores climate, environment and disease interactions using multiple epidemiological modelling methodologies to develop an informative framework within which disease risk can be assessed, to aid decision-making. Statistical analysis of the impact of extreme events indicate that El Niño has a significant impact on the Tanzanian climate, which differs by location. Spatial modelling results demonstrate that by 2050 under RCP 8.5 mean malaria risk will initially reduce by 4.7%, which then reverses to an increase of 8.9% in 2070. Overall, analysis indicates increases in mean malaria risk. Biological modelling indicates that the predicted increases in malaria risk are likely a result of the reduction in time taken to complete the sporogonic and gonotrophic cycles due to increasingly optimum environmental conditions. The novel approach applied here contributes the development of a new model in environmental epidemiology. This thesis concludes that epidemiological modelling results could be beneficial in aiding decision makers to prepare for the impact of climate and environmental change, with a recommendation to continue research in this area with a particular focus on understudied and developing countries.

Fast growing hybrids of Salix and Populus can be grown in a short rotation coppice (SRC) system to produce renewable energy. This PhD investigates the interactions between the environment and productivity, with a view to finding the key limiting factors to yield and the potential of these crops to fulfil UK renewable energy obligations, now and in the future. An empirical modelling technique, using partial least squares regression was developed to extrapolate actual field observations to a national scale. Genotype x age x environment interactions were studied to examine the key limiting factors to productivity. Modelled yields differed between genotypes, with mean annual aboveground biomass ranging from 4.9 to 10.7 oven dry tonnes (odt) per hectare for Populus trichocarpa x P. deltoides genotype ‘Beaupré’ and Salix triandra x S. viminalis genotype ‘Q83’, respectively. Variation in yield was primarily described by spring and summer precipitation, suggesting water availability is the key limiting factor to yield. Output from the model was up-scaled across the UK using a geographic information system (GIS), and scenarios were developed to better understand the role and impact of land use management and policy development on potential crop distribution. For example, to meet UK biomass and biofuel targets without compromising food security or ecosystem services, would require 5 % of grade 3 land, 56 % grade 4 land and 47 % of grade 5 land. This quantity of biomass would produce 7.5 M tonnes of biomass per annum and would theoretically generate 15.5 TWh yr-1 of electrical energy, displacing 3.3 M tonnes of oil – approximately 4% of current UK electricity demand. The South West and North West alone producing over a third of this figure (5.2 TWh yr-1). These results suggest that SRC has the potential to become a significant component of a mixed portfolio of renewables. Furthermore, climate change is predicted to have far reaching consequences on crop growth. Process-based models can help quantify these interactions and predict future productivity. Here we use ForestGrowth-SRC, a process-based model originally designed for high-forest species and parameterised for a coppice system. Climate change scenarios (UK Climate Projections) were run with the model to assess the impact of a changing climate on the growth and spatial distribution of SRC poplar. Results suggest ForestGrowth-SRC is capable of accurately simulating growth over a large spatial and temporal scale. However, pests and disease were found to significantly affect yield. In the absence of pests and disease, productivity could increase by 20 % nationwide by 2080 (under a medium emissions scenario), suggesting we will see a future increase in the value and production of these crops as feedstocks for heat, power and liquid transportation fuels

Doutoramento em Ciências e Engenharia do Ambiente
The better understanding of the interactions between climate change and air quality is an emerging priority for research and policy. Climate change will bring changes in the climate system, which will affect the concentration and dispersion of air pollutants. The main objective of the current study is to assess the impacts of climate change on air quality in 2050 over Portugal and Porto urban area. First, an evaluation and characterization of the air quality over mainland Portugal was performed for the period between 2002 and 2012. The results show that NO2, PM10 and O3 are the critical pollutants in Portugal. Also, the influence of meteorology on O3, NO2 and PM10 levels was investigate in the national main urban areas (Porto and Lisboa) and was verified that O3 has a statistically significant relationship with temperature in most of the components. The results also indicate that emission control strategies are primary regulators for NO2 and PM10 levels. After, understanding the national air quality problems and the influence that meteorology had in the historical air quality levels, the air quality modelling system WRF-CAMx was tested and the required inputs for the simulations were prepared to fulfil the main goal of this work. For the required air quality modelling inputs, an Emission Projections under RCP scenarios (EmiPro-RCP) model was developed to assist the estimation of future emission inventories for GHG and common air pollutants. Also, the current emissions were estimated for Portugal with a higher detailed disaggregation to improve the performance of the air quality simulations. The air quality modelling system WRF/CAMx was tested and evaluated over Portugal and Porto urban area and the results point out that is an adequate tool for the analysis of air quality under climate change. For this purpose, regional simulations of air quality during historical period and future (2045-2050) were conducted with CAMx version 6.0 to evaluate the impacts of simulated future climate and anthropogenic emission projections on air quality over the study area. The climate and the emission projections were produced under the RCP8.5 scenario. The results from the simulations point out, that if the anthropogenic emissions keep the same in 2050, the concentrations of NO2, PM10 and O3 will increase in Portugal. When, besides the climate change effects, is consider the projected anthropogenic emissions the annual mean concentrations of NO2 decrease significantly in Portugal and Porto urban area, and on the contrary the annual mean PM10 concentrations increases in Portugal and decrease in Porto urban area. The O3 results are mainly caused by the reduction of ozone precursors, getting the higher reductions in urban areas and increases in the surrounding areas. All the analysis performed for both simulations for Porto urban area support that, for PM10 and O3, there will be an increase in the occurrence of extreme values, surpassing the annual legislated parameters and having more daily exceedances. This study constitutes an innovative scientific tool to help in future air quality management in order to mitigate future climate change impacts on air quality.
A interação entre as alterações climáticas e a qualidade do ar é neste momento um assunto emergente em termos de implementação de políticas e de investigação. As alterações climáticas causarão mudanças no clima, o que irá afetar a concentração e dispersão dos poluentes atmosféricos. Assim, o principal objetivo deste trabalho é avaliar os impactos das alterações climáticas na qualidade do ar em 2050 em Portugal e na área urbana do Porto. Numa primeira fase, realizou-se uma caracterização da qualidade do ar em Portugal para o período de 2002 a 2012, na qual se identificou que os poluentes NO2, PM10 e O3 são os mais críticos em termos de qualidade do ar. Adicionalmente, foi analisada a influência da meteorologia na qualidade do ar para esses três poluentes nas duas maiores áreas urbanas nacionais (Porto e Lisboa), sendo que o O3 é estatisticamente dependente da temperatura na maioria das suas componentes. Após o entendimento dos problemas de qualidade do ar nacionais e da influência da meteorologia nos mesmos, o sistema de modelos WRF-CAMx foi testado e todos os seus dados de entrada foram preparados. As emissões nacionais atuais foram estimadas com maior detalhe de desagregação para melhorar as simulações de qualidade do ar; o modelo de emissões, EmiPro-RCP, foi desenvolvido para estimar as emissões de 2050 tendo em conta os cenários de emissão RCPs. O sistema de modelos WRF-CAMx foi testado e avaliado para Portugal e para a área urbana do Porto, verificando-se que é uma ferramenta adequada para realizar as simulações de qualidade do ar em cenário climático. Realizaram-se simulações regionais com o modelo CAMx versão 6.0, para dois períodos: histórico e futuro (2045-2050), de forma a simular os impactos do clima futuro e das futuras emissões antropogénicas na qualidade do ar para a região de estudo. O cenário climático, bem como as emissões, foram projetadas tendo como base o cenário RCP8.5. Os resultados provenientes das simulações demonstram que, se as emissões antropogénicas se mantiverem constantes em 2050, as concentrações de NO2, PM10 e O3 irão aumentar em Portugal. Quando, aos efeitos das alterações climáticas se juntaram as futuras emissões antropogénicas, verifica-se que as concentrações médias anuais de NO2 irão diminuir e as concentrações médias anuais de PM10 aumentam em Portugal e diminuem na área urbana do Porto. Os resultados de O3 estão relacionados com as variações de concentração dos seus precursores, verificando-se as maiores reduções nas áreas urbanas e os aumentos nas áreas suburbanas. Toda a análise realizada aos dados das simulações para a área urbana do Porto indica que, no caso de PM10 e O3, irá existir um aumento de ocorrência de valores extremos de concentração, ultrapassando os valores legislados de cada poluente. Este estudo constitui uma ferramenta científica inovadora que pode ser relevante para uma futura e cuidada gestão da qualidade do ar, de forma a mitigar os impactes das alterações climáticas na qualidade do ar.

Mestrado em Ciências do Mar e das Zonas Costeiras
Estuaries are highly dynamic systems which may be modified in a climate change context. These changes can affect the biogeochemical cycles. Among the major impacts of climate change, the increasing rainfall events and sea level rise can be considered. This study aims to research the impact of those events in biogeochemical dynamics in the Tagus Estuary, which is the largest and most important estuary along the Portuguese coast. In this context a 2D biophysical model (MOHID) was implemented, validated and explored, through comparison with in-situ data. In order to study the impact of extreme rainfall events, which can be characterized by an high increase in freshwater inflow, three scenarios were set by changing the inputs from the main tributaries, Tagus and Sorraia Rivers. A realistic scenario considering one day of Tagus and Sorraia River extreme discharge, a scenario considering one day of single extreme discharge of the Tagus River and finally one considering the extreme runoff just from Sorraia River. For the mean sea level rise, two scenarios were also established. The first with the actual mean sea level value and the second considering an increase of 0.42 m. For the extreme rainfall events simulations, the results suggest that the biogeochemical characteristics of the Tagus Estuary are mainly influenced by Tagus River discharge. For sea level rise scenario, the results suggest a dilution in nutrient concentrations and an increase in Chl-a in specific areas.For both scenarios, the suggested increase in Chl-a concentration for specific estuarine areas, under the tested scenarios, can lead to events that promote an abnormal growth of phytoplankton (blooms) causing the water quality to drop and the estuary to face severe quality issues risking all the activities that depend on it.
Os estuários são sistemas altamente dinâmicos que se encontram em risco devido a eventos relacionados com as alterações climáticas. Estas alterações podem ter impactos nos ciclos biogeoquímicos. Entre esses efeitos podem considerar-se o aumento de períodos de chuvas torrenciais e o aumento do nível médio do mar. Assim, o objetivo deste trabalho é o estudo do impacto destes eventos na dinâmica biogeoquímica do Estuário do Tejo, que se trata do maior sistema estuarino da Península Ibérica. Neste contexto, foi implementado, validado e explorado através de comparação com dados in-situ, um modelo biofísico 2D (MOHID). De forma a avaliar a resposta biogeoquímica do estuário a períodos de chuvas torrenciais, caracterizadas por variações abruptas nas descargas fluviais dos principais tributários, Tejo e Sorraia, foram considerados três cenários. O primeiro considerando um dia de descarga extrema para os rios Tejo e Sorraia. O segundo, considerando uma descarga extrema apenas para o Rio Tejo e por último, considerando uma descarga apenas para o Rio Sorraia. Relativamente ao aumento do nível médio do mar, foram estabelecidos dois cenários, o primeiro com o nível médio do mar atual e o segundo considerando um aumento de 0.42 m, conforme estimado em estudos anteriores. Os resultados para a simulação das chuvas torrenciais indicam que as modificações previstas para os padrões biogeoquímicos dependem essencialmente da descarga do Rio Tejo. Para o cenário de aumento do nível médio do mar os resultados sugerem uma diminuição da concentração de nutrientes e um aumento de clorofila em áreas específicas. Em ambos os cenários, o aumento de clorofila em determinadas zonas do estuário, sugerido pelos resultados, pode levar a eventos que promovam um crescimento anormal de fitoplâncton fazendo com que a qualidade da água diminua e colocando em risco todas as atividades que dependem no Estuário do Tejo.