Browsing by discipline "Forest Resource Science and Technology"

Euroopan Unioniin kuuluvien jäsenvaltioiden rakentamislainsäädännöt sisältävät yhdenmukaistettuja standardeja rakentamispuutuotteiden palonkestävyysvaatimuksiin, mutta rakentamista yksityiskohtaisesti ohjaavat lainsäädännöt ovat jokaisessa jäsenvaltiossa kansallisia. Tutkimuksen tavoitteena oli selvittää paloluokitukseltaan euroluokan B-s1, d0 (EN 13501-1) puisen ulkoverhousmateriaalin maakohtaiset paloluokitusvaatimukset, vaikuttavatko muut ulkoseinärakenteeseen kuuluvat rakenneosat siltä vaadittavaan paloluokitukseen ja kuinka eri kohdemaiden paloluokitusvaatimukset keskenään vaihtelevat. Tavoitteena oli selvittää myös kaikki muut rakentamislainsäädäntöjen edellyttämät tekijät, jotka voivat vaikuttaa ulkoverhousmateriaalilta vaadittaviin paloluokitusvaatimuksiin. Tutkimuksessa määritettiin euroluokitukseltaan B-s1, d0 puisen ulkoverhousmateriaalin maakohtaiset käyttömahdollisuudet erityyppisissä rakennuskohteissa. Tarkasteltuja maita olivat Tšekki, Saksa, Yhdistynyt kuningaskunta, Hollanti, Ranska ja Espanja. Tämän tutkimuksen tiedonkeruumenetelmänä oli systemaattinen kirjallisuuskatsaus ja analyysimenetelmänä induktiivinen sisällönanalyysi. Tutkimusaineisto perustuu tutkimukseen kuuluneiden maiden rakennuslainsäädäntöihin ja rakennusteknisiin ohjekirjoihin. Rakennuslainsäädäntöjen tulkinnat kohdistuivat ulkoseinärakenteita käsitteleviin paloturvallisuusosioihin ja edelleen ulkoverhousmateriaalin paloturvallisuusvaatimuksiin. Tulokset osoittivat, että puisen ulkoverhousmateriaalin paloluokitusvaatimukset ovat jokaisessa tutkimukseen kuuluneessa maassa erilaiset ja ne voivat vaihdella myös alueellisesti maiden sisällä. Rakentamismääräykset voivat olla ohjeistavia tai niitä on toteutettava täysin rakentamislainsäädäntöjen mukaisesti, jolloin rakentaminen tapahtuu niissä määriteltyjen reunaehtojen mukaisesti. Kansalliset rakentamislainsäädännöt määrittävät toteutettaville rakennusratkaisuille yleensä paloturvallisuutta koskevat minimivaatimukset. Paloluokitusvaatimuksiin vaikuttavat tekijät vaihtelevat laajasti ja niitä voivat olla rakennuksen korkeus, ulkoverhouksen sijainti julkisivuseinällä, etäisyys viereiseen rakennukseen, käyttötarkoitusluokka, vaadittava rakennejärjestelmä, rakennuskategoria ja rakennusluokka. Tutkimukseen kuuluneissa maissa yleisin ulkoverhousmateriaalin paloluokitusvaatimuksiin vaikuttava tekijä oli rakennuksen korkeus. Useimmissa maissa euroluokitukseltaan muita ulkoseinärakenteita huonompi ulkoverhousmateriaali asettaa tiukemmat vaatimukset muille ulkoseinärakenteille. Paloluokitukseltaan euroluokan B-s1, d0 (EN 13501-1) puisen ulkoverhousmateriaalin laajimmat käyttömahdollisuudet kohdistuivat Espanjan, Hollannin, Englannin, Walesin, Pohjois-Irlannin ja Saksan liittovaltio Nordrhein-Westfalenin markkinoille, joissa sitä on mahdollista käyttää kaikissa rakennuskohteissa. Seuraavaksi laajimmat käyttömahdollisuudet ovat Ranskassa, Skotlannissa ja Saksan muissa liittovaltioissa paitsi Nordrhein-Westfalenissa. Heikoimmat käyttömahdollisuudet kohdistuivat Tšekin markkinoille.

The newly reformed Forest Law in 2014 is going to expand the usage possibilities of uneven-aged forest management as it is no longer concerned to be a part of ”for special sites only” forest management. Nowadays, the number of forest owners, who are aiming towards multiattribute forest management, is increasing and uneven-aged forest management is probably going to increase its proportion. But there is a major problem of utilizing uneven-aged forest management, as there are basically neither significant practical models nor knowledge from the operational point of view. This research was completed as a part of Finnish Forest Research Institute’s research program in co-operation with Metsä Group Ltd. and Forest-Linna Ltd in Central Finland. The goals of the research were to analyze; the time-consumption of selection cutting and factors affecting it, the quality and quantity of the forest stand after cutting from the forest structure’s and tree damages’ point of view, and to research the need and possibilities of training for harvester operators. The effective time-consumption between Scots Pine and Norway Spruce didn’t statistically differ neither in clear cutting nor selection cutting, so a group of conifers was created for the comparison between them. The effective time-consumption was 15 – 17 % higher and the effective productivity 12 – 14 % lower in selection cutting, when the average stem volume was fixed between 0,700 m³ and 0,897 m³ in both methods. Processing of the stems located on the strip road was faster than those located on the sides. Out of the undergrowth saplings (h<2,5 m), which had growth-potential for future, 4,7% were injured and 42,5% destroyed or disappeared. The major factors causing either injury or destruction were slash and logs. Out of the remaining trees (h>2,5 m) 19,3% were injured, when all the recorded injuries were taken into account. According to the Finnish Forest Regulation, 7,7% of the remaining trees (dbh>7,0 cm) were injured. A prototype basal area chart was used for allowing the harvester operator to picture the remaining basal area at a single working location. The chart consisted of the basal area of different diameter classes at a half-circular location restricted by an 11-metre boom. The chart was designed for this research by Pentti Niemistö. By using the chart; oral information and a practice area, where trees were selected beforehand, the harvester operator was able to achieve different given basal area goals by fair means on the other parts of the research stumpage.

Nature has been said to have relaxing effects on human. In today’s world, people’s life takes place mostly indoors so it is essential to seek relaxing effects also indoors. Decorative wood surfaces may bring those relaxing effects of nature to an indoor environment. This research focuses on researching the restorative effect of wooden surfaces through people’s preferences and the abilities of wooden surfaces. In this research, people’s preferences between different wooden surfaces were compared with the use of haptic and visual sensations. All the surfaces were lightly sanded to minimize the effects of pro-cessing and to concentrate merely on the comparison of different materials. The selected surface materials were conifer glulam, birch glulam, birch plywood, conifer plywood, MDF-board (Medium Density Fibreboard) and OSB-board (Oriented Strand Board). The study was divided into three sec-tions: the first section concentrated on people’s preferences towards wooden surfaces only with haptic sensations, the second part included only visual sensations and the third part included both haptic and visual sensations. The third section also included an open question for participants about the potential use of each wood material. Some of the participants also took part in a stress test during the third section. The stress test aimed to examine whether the participants’ heart rate and blood pressure lowered as they experienced the haptic and visual effects of wood material and if there were differ-ences between different materials. In the preference study people were instructed to rate the descriptiveness of different adjectives with all the wooden samples on a scale of 1–7 (1 very little, 7 very much). The three sections of the study made it possible to compare participants’ haptic and visual sensations. The visual sensations were observed to have more dominant effect than haptic sensations on the participants’ preferences. The visually most preferred wood materials were also found the most potential use for. These materials were instructed to be used in places they were seen whereas the less preferred materials were instructed to be used in hidden structures and to remain unseen. Both the heart rate and blood pressure lowered from the start of the test with all the materials except with OSB-board that caused a little rise of heart rate and blood pressure.

There is need for information about stands and their future development in forest planning decision making. This information is collected by inventories. In general inventory is repeated with some before-hand set intervals, irrespective of the method. Between inventories information is updated with growth models. Both inventory and using of growth models causes errors in forest planning results, for example in management options. Erroneous predictions can lead to wrong conclusions and inoptimal decisions. If the optimal result is known, economical losses caused by wrong conclusions can be described with so called inoptimality losses. The aim of this study was to answer the question how long forest inventory information, updated with growth models, can be used in forest planning purposes. Study approach was economical, so evaluation of information`s usefulness was based on inoptimality losses which arise when development of the stand is predicted incorrectly with growth models. The study material included 99 stands. Their development was simulated with the SIMO software for 60 years from present. In the 60 years period influencies of growth prediction errors were studied with inventory periods which lengths were 5, 10, 15, 20, 30 and 60 years. It was assumed that new error-free forest inventory information was received in the beginning of each of the inventory periods. In order to study effects of different inventory periods, it was assumed that the growth models were able to predict the true development of stands. Erroneous developments were yielded with error model which was developed for this study and added to the growth models. Inoptimality losses were calculated with the information derived from the optimization of stands` true and erroneous developments. Inoptimality losses increased when the inventory period became longer. Absolute inoptimality loss was approximately 230 eur/ha when the inventory period was 5 years and approximately 860 eur/ha when the inventory period was 60 years. Relative inoptimality loss was 3,3 % when the inventory period was 5 years and 11,6 % when the inventory period was 60 years. The average inoptimality losses were different between different development classes, site classes and main tree species. Study results show that the length of the updating period has an effect on the developing economical losses. It seems also that the inventory period should be different for example in different development classes. However, it is difficult to specify the optimal updating period because total losses are a sum of losses of inventory errors, losses of growth prediction errors and losses caused by other uncertainty sources. The effects of both inventory errors and growth prediction errors are different in different kinds of stands. So estimation of total losses and estimation of inoptimality losses caused by different error sources requires more research.

Surface albedo, which is the fraction of reflected radiant energy by earth’s surface to incoming solar energy, plays an important role in earth energy budget and energy equilibrium. Different features of the earth’s surface have different reflectivity rates which affect albedo. Vegetation land-covers covering vast areas of earth’s surface such as agricultural land, forest, grassland and so on, have great impact on land surface albedo. The species composition, geographical distribution, and seasonal phenology of different vegetation land-covers have an impact on surface albedo and earth’s energy budget and, consequently, on climate change. The boreal zone covering latitudes between 60º – 70º N is one of the largest vegetation biomes on earth and has a significant impact on surface albedo. The boreal region is mostly covered by coniferous forests which are optically very dark and absorb most of the incoming solar energy. This low reflectivity is very influential during the times that earth’s surface is snow covered by masking the high reflectivity of the snow covered land surface. This has caused most studies to focus on the boreal vegetation land-cover albedo during the snow covered periods of the year. In this study, the effects of five different vegetation classes (agricultural, deciduous, coniferous, mixed forest and shrubland), three different latitudinal gradients (northern, middle and southern Finland), and the vegetation phenology during the growing season on surface albedo of vegetated areas of Finland for the year 2009 has been investigated. The results of the study showed that there is a significant difference between the albedo of different vegetation land-cover classes. The albedo of agricultural lands tends to be systematically the highest in all conditions while coniferous are the lowest. The vegetation land-cover albedo is generally lower in northern Finland compared to middle and south. There is a gradual increase in vegetation albedo until mid-July and after reaching a maximum level it starts to decrease towards the end of the growing season. The peak in albedo is reached about two weeks earlier in the north compared to the south possibly due to and longer days during its shorter growing season.

Carbonization is thermochemical conversion, where biomass is thermally degraded in the absence of oxygen. Solid char, pyrolysis oil and non-condensable gases are produced from the biomass. Torrefaction is early phase of the carbonization in temperatures of 220–300 °C. Torrefied wood is promising as a renewable fuel for industrial use in coal co-combustion and gasification-combustion. Torrefaction and carbonization increase the higher heating value and fuel properties of wood compared to untreated wood. There’s a lack of knowledge in torrefaction and carbonization effects to higher heating value, carbon content and turn from endothermic to exothermic reaction of conifer zone wood species. Raw material was stemwood of birch (Betula pubescens) and pine (Pinus sylvestris) including bark. Trees were harvested from the Helsinki district and chipped, particle size 16 ? 8 mm. Samples were torrefied and carbonized at 250, 300, 350, 400 and 450 ?C without nitrogen flow. Carbon content (%), higher heating value (MJ/kg), mass yield (%) and turn of endothermic to exothermic reaction were inspected. Carbon content of untreated birch and pine increased from 47 % to 82 % (at 450 ?C). Higher heating value exceeded 26 MJ/kg at 300 ?C and 28 MJ/kg at 400 ?C, reaching bituminous coal’s values. Mass yield declined to 45–54 % of the initial mass at 300 °C. In low temperature, gradual exothermic peak was observable. In higher temperatures peak was evident. Carbonization and torrefaction improved the higher heating value and carbon content of wood but decreased the solid char yield.

The use of forest chips has increased rapidly in the past 15 years and the usage must be increased even more in order to achieve the renewable energy usage goals. Forest chips are produced mainly from logging residues and stumps collected from clear cutting areas. One source is also small sized trees harvested from thinning areas. Increasing the use of forest chips could be possible, but the problem are the long transportation distances of the raw material. Most of the wood chip potential is located in Eastern and Central Finland and Kainuu, but the heat and power plants and demand are located by the sea. Transportation costs must be reduced to make usage possible. This was a pioneer study to develop working models for loading energy wood trucks. The aim of this study was to create systematic working models for loading logging residuals and stumps to bioenergy trucks to increase payload. The optimal load weight and its relation to transportation distance was also the point of interest. Twelve operators participated the study and the data was collected in Southern and Eastern Finland between April and September. The data set included 12 stump loads and 11 logging residual loads. The work researcher sat next to the driver, interviewed him about loading techniques and collected information about the loads. The loading events were also recorded by video camera for later performed time and observation studies. To compare the drivers the payloads were weighted. Drivers’ loadings where observed and analyzed with the payload weights and the loading times and as a result four different working models were developed. For stump material two different working models were described by the size of the stump: for small sized stump and normal sized stump. The working model for normal sized stumps was divided into two working models to achieve a large payload and an average payload with minimal loading time. For logging residues only one working model was necessary to describe. Working models consisted of systematic ways of work and different types of compressing methods and tricks. The average loading time towards one ton for stumps was 2.7 minutes and for logging residuals 2.2 minutes. Aiming for large payload is not always the most cost-efficient choice. The operator should consider the transportation distance as well as loading time along with the payload. The longer the driving distance the larger the payload should be. With shorter distances it is optimal to use less time for the loading even tough large payloads will not be achieved and use the spared time for driving of extra loads.