Urban energy fluxes in Helsinki and their high frequency spectral corrections

Inadvertent climate modification has led to an increase in urban temperatures compared to the surrounding rural area. The main reason for the temperature rise is the altered energy portioning of input net radiation to heat storage and sensible and latent heat fluxes in addition to the anthropogenic heat flux. The heat storage flux and anthropogenic heat flux have not yet been determined for Helsinki and they are not directly measurable. To the contrary, turbulent fluxes of sensible and latent heat in addition to net radiation can be measured, and the anthropogenic heat flux together with the heat storage flux can be solved as a residual. As a result, all inaccuracies in the determination of the energy balance components propagate to the residual term and special attention must be paid to the accurate determination of the components. One cause of error in the turbulent fluxes is the fluctuation attenuation at high frequencies which can be accounted for by high frequency spectral corrections. The aim of this study is twofold: to assess the relevance of high frequency corrections to water vapor fluxes and to assess the temporal variation of the energy fluxes. Turbulent fluxes of sensible and latent heat have been measured at SMEAR III station, Helsinki, since December 2005 using the eddy covariance technique. In addition, net radiation measurements have been ongoing since July 2007. The used calculation methods in this study consist of widely accepted eddy covariance data post processing methods in addition to Fourier and wavelet analysis. The high frequency spectral correction using the traditional transfer function method is highly dependent on relative humidity and has an 11% effect on the latent heat flux. This method is based on an assumption of spectral similarity which is shown not to be valid. A new correction method using wavelet analysis is thus initialized and it seems to account for the high frequency variation deficit. Anyhow, the resulting wavelet correction remains minimal in contrast to the traditional transfer function correction. The energy fluxes exhibit a behavior characteristic for urban environments: the energy input is channeled to sensible heat as latent heat flux is restricted by water availability. The monthly mean residual of the energy balance ranges from 30 Wm-2 in summer to -35 Wm-2 in winter meaning a heat storage to the ground during summer. Furthermore, the anthropogenic heat flux is approximated to be 50 Wm-2 during winter when residential heating is important.

Factors controlling the surface energy budget over snow and ice

Polar Regions are an energy sink of the Earth system, as the Sun rays do not reach the Poles for half of the year, and hit them only at very low angles for the other half of the year. In summer, solar radiation is the dominant energy source for the Polar areas, therefore even small changes in the surface albedo strongly affect the surface energy balance and, thus, the speed and amount of snow and ice melting. In winter, the main heat sources for the atmosphere are the cyclones approaching from lower latitudes, and the atmosphere-surface heat transfer takes place through turbulent mixing and longwave radiation, the latter dominated by clouds. The aim of this thesis is to improve the knowledge about the surface and atmospheric processes that control the surface energy budget over snow and ice, with particular focus on albedo during the spring and summer seasons, on horizontal advection of heat, cloud longwave forcing, and turbulent mixing during the winter season. The critical importance of a correct albedo representation in models is illustrated through the analysis of the causes for the errors in the surface and near-surface air temperature produced in a short-range numerical weather forecast by the HIRLAM model. Then, the daily and seasonal variability of snow and ice albedo have been examined by analysing field measurements of albedo, carried out in different environments. On the basis of the data analysis, simple albedo parameterizations have been derived, which can be implemented into thermodynamic sea ice models, as well as numerical weather prediction and climate models. Field measurements of radiation and turbulent fluxes over the Bay of Bothnia (Baltic Sea) also allowed examining the impact of a large albedo change during the melting season on surface energy and ice mass budgets. When high contrasts in surface albedo are present, as in the case of snow covered areas next to open water, the effect of the surface albedo heterogeneity on the downwelling solar irradiance under overcast condition is very significant, although it is usually not accounted for in single column radiative transfer calculations. To account for this effect, an effective albedo parameterization based on three-dimensional Monte Carlo radiative transfer calculations has been developed. To test a potentially relevant application of the effective albedo parameterization, its performance in the ground-based retrieval of cloud optical depth was illustrated. Finally, the factors causing the large variations of the surface and near-surface temperatures over the Central Arctic during winter were examined. The relative importance of cloud radiative forcing, turbulent mixing, and lateral heat advection on the Arctic surface temperature were quantified through the analysis of direct observations from Russian drifting ice stations, with the lateral heat advection calculated from reanalysis products.

Molecular Genetic Studies of Melanocortin Receptors in Morbid Obesity

The prevalence of obesity is increasing at an alarming rate in all age groups worldwide. Obesity is a serious health problem due to increased risk of morbidity and mortality. Although environmental factors play a major role in the development of obesity, the identification of rare monogenic defects in human genes have confirmed that obesity has a strong genetic component. Mutations have been identified in genes encoding proteins of the leptin-melanocortin signaling system, which has an important role in the regulation of appetite and energy balance. The present study aimed at identifying mutations and genetic variations in the melanocortin receptors 2-5 and other genes active on the same signaling pathway accounting for severe early-onset obesity in children and morbid obesity in adults. The main achievement of this thesis was the identification of melanocortin-4 receptor (MC4R) mutations in Finnish patients. Six pathogenic MC4R mutations (308delT, P299H, two S127L and two -439delGC mutations) were identified, corresponding to a prevalence of 3% in severe early-onset obesity. No obesity causing MC4R mutations were found among patients with adult-onset morbid obesity. The MC4R 308delT deletion is predicted to result in a grossly truncated nonfunctional receptor of only 107 amino acids. The C-terminal residues, which are important in MC4R cell surface targeting, are totally absent from the mutant 308delT receptor. In vitro functional studies supported a pathogenic role for the S127L mutation since agonist induced signaling of the receptor was impaired. Cell membrane localization of the S127L receptor did not differ from that of the wild-type receptor, confirming that impaired function of the S127L receptor was due to reduced signaling properties. The P299H mutation leads to intracellular retention of the receptor. The -439delGC deletion is situated at a potential nescient helix-loop-helix 2 (NHLH2) -binding site in the MC4R promoter. It was demonstrated that the transcription factor NHLH2 binds to the consensus sequence at the -439delGC site in vitro, possibly resulting in altered promoter activity. Several genetic variants were identified in the melanocortin-3 receptor (MC3R) and pro-opiomelanocortin (POMC) genes. These polymorphisms do not explain morbid obesity, but the results indicate that some of these genetic variations may be modifying factors in obesity, resulting in subtle changes in obesity-related traits. A risk haplotype for obesity was identified in the ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) gene through a candidate gene single nucleotide polymorphism (SNP) genotyping approach. An ENPP1 haplotype, composed of SNPs rs1800949 and rs943003, was shown to be significantly associated with morbid obesity in adults. Accordingly, the MC3R, POMC and ENPP1 genes represent examples of susceptibility genes in which genetic variants predispose to obesity. In conclusion, pathogenic mutations in the MC4R gene were shown to account for 3% of cases with severe early-onset obesity in Finland. This is in line with results from other populations demonstrating that mutations in the MC4R gene underlie 1-6% of morbid obesity worldwide. MC4R deficiency thus represents the most common monogenic defect causing human obesity reported so far. The severity of the MC4-receptor defect appears to be associated with time of onset and the degree of obesity. Classification of MC4R mutations may provide a useful tool when predicting the outcome of the disease. In addition, several other genetic variants conferring susceptibility to obesity were detected in the MC3R, MC4R, POMC and ENPP1 genes.

Lypsylehmän energiataseen mallintaminen tuotoskauden alkuvaiheessa

Energiataseen mallinnus on osa KarjaKompassi-hankkeeseen liittyvää kehitystyötä. Tutkielman tavoitteena oli kehittää lypsylehmän energiatasetta etukäteen ennustavia ja tuotoskauden aikana saatavia tietoja hyödyntäviä matemaattisia malleja. Selittävinä muuttujina olivat dieetti-, rehu-, maitotuotos-, koelypsy-, elopaino- ja kuntoluokkatiedot. Tutkimuksen aineisto kerättiin 12 Suomessa tehdyistä 8 – 28 laktaatioviikon pituisesta ruokintakokeesta, jotka alkoivat heti poikimisen jälkeen. Mukana olleista 344 lypsylehmästä yksi neljäsosa oli friisiläis- ja loput ayshire-rotuisia. Vanhempien lehmien päätiedosto sisälsi 2647 havaintoa (koe * lehmä * laktaatioviikko) ja ensikoiden 1070. Aineisto käsiteltiin SAS-ohjelmiston Mixed-proseduuria käyttäen ja poikkeavat havainnot poistettiin Tukeyn menetelmällä. Korrelaatioanalyysillä tarkasteltiin energiataseen ja selittävien muuttujien välisiä yhteyksiä. Energiatase mallinnettiin regressioanalyysillä. Laktaatiopäivän vaikutusta energiataseeseen selitettiin viiden eri funktion avulla. Satunnaisena tekijänä mallissa oli lehmä kokeen sisällä. Mallin sopivuutta aineistoon tarkasteltiin jäännösvirheen, selitysasteen ja Bayesin informaatiokriteerin avulla. Parhaat mallit testattiin riippumattomassa aineistossa. Laktaatiopäivän vaikutusta energiataseeseen selitti hyvin Ali-Schaefferin funktio, jota käytettiin perusmallina. Kaikissa energiatasemalleissa vaihtelu kasvoi laktaatioviikosta 12. alkaen, kun havaintojen määrä väheni ja energiatase muuttui positiiviseksi. Ennen poikimista käytettävissä olevista muuttujista dieetin väkirehuosuus ja väkirehun syönti-indeksi paransivat selitysastetta ja pienensivät jäännösvirhettä. Ruokinnan onnistumista voidaan seurata maitotuotoksen, maidon rasvapitoisuuden ja rasva-valkuaissuhteen tai EKM:n sisältävillä malleilla. EKM:n vakiointi pienensi mallin jäännösvirhettä. Elopaino ja kuntoluokka olivat heikkoja selittäjiä. Malleja voidaan hyödyntää karjatason ruokinnan suunnittelussa ja seurannassa, mutta yksittäisen lehmän energiataseen ennustamiseen ne eivät sovellu.

Rapsista tuotetun biodieselin ja vehnästä tuotetun bioetanolin energiavirrat ja ympäristövaikutukset Euroopan unionissa

The aim of this thesis was to study the crops currently used for biofuel production from the following aspects: 1. what should be the average yield/ ha to reach an energy balance at least 0 or positive 2. what are the shares of the primary and secondary energy flows in agriculture, transport, processing and usage, and 3. overall effects of biofuel crop cultivation, transport, processing and usage. This thesis concentrated on oilseed rape biodiesel and wheat bioethanol in the European Union, comparing them with competing biofuels, such as corn and sugarcane-based ethanol, and the second generation biofuels. The study was executed by comparing Life Cycle Assessment-studies from the EU-region and by analyzing them thoroughly from the differences viewpoint. The variables were the following: energy ratio, hectare yield (l/ha), impact on greenhouse gas emissions (particularly CO2), energy consumption in crop growing and processing one hectare of a particular crop to biofuel, distribution of energy in processing and effects of the secondary energy flows, like e.g. wheat straw. Processing was found to be the most energy consuming part in the production of biofuels. So if the raw materials will remain the same, the development will happen in processing. First generation biodiesel requires esterification, which consumes approximately one third of the process energy. Around 75% of the energy consumed in manufacturing the first generation wheat-based ethanol is spent in steam and electricity generation. No breakthroughs are in sight in the agricultural sector to achieve significantly higher energy ratios. It was found out that even in ideal conditions the energy ratio of first generation wheat-based ethanol will remain slightly under 2. For oilseed rape-based biodiesel the energy ratios are better, and energy consumption per hectare is lower compared to wheat-based ethanol. But both of these are lower compared to e.g. sugarcane-based ethanol. Also the hectare yield of wheat-based ethanol is significantly lower. Biofuels are in a key position when considering the future of the world’s transport sector. Uncertainties concerning biofuels are, however, several, like the schedule of large scale introduction to consumer markets, technologies used, raw materials and their availability and - maybe the biggest - the real production capacity in relation to the fuel consumption. First generation biofuels have not been the expected answer to environmental problems. Comparisons made show that sugarcane-based ethanol is the most prominent first generation biofuel at the moment, both from energy and environment point of view. Also palmoil-based biodiesel looks promising, although it involves environmental concerns as well. From this point of view the biofuels in this study - wheat-based ethanol and oilseed rape-based biodiesel - are not very competitive options. On the other hand, crops currently used for fuel production in different countries are selected based on several factors, not only based on thier relative general superiority. It is challenging to make long-term forecasts for the biofuel sector, but it can be said that satisfying the world's current and near future traffic fuel consumption with biofuels can only be regarded impossible. This does not mean that biofuels shoud be rejected and their positive aspects ignored, but maybe this reality helps us to put them in perspective. To achieve true environmental benefits through the usage of biofuels there must first be a significant drop both in traffic volumes and overall fuel consumption. Second generation biofuels are coming, but serious questions about their availability and production capacities remain open. Therefore nothing can be taken for granted in this issue, expect the need for development.

Soil carbon modelling as a tool for carbon balance studies in forestry

Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.