34 resultados para Air sampling apparatus.


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Tiivistelmä: Havaintotiheyden vaikutus valumavesien laatuarvioihin

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We present a laser-based system to measure the refractive index of air over a long path length. In optical distance measurements it is essential to know the refractive index of air with high accuracy. Commonly, the refractive index of air is calculated from the properties of the ambient air using either Ciddor or Edlén equations, where the dominant uncertainty component is in most cases the air temperature. The method developed in this work utilises direct absorption spectroscopy of oxygen to measure the average temperature of air and of water vapor to measure relative humidity. The method allows measurement of temperature and humidity over the same beam path as in optical distance measurement, providing spatially well matching data. Indoor and outdoor measurements demonstrate the effectiveness of the method. In particular, we demonstrate an effective compensation of the refractive index of air in an interferometric length measurement at a time-variant and spatially non-homogenous temperature over a long time period. Further, we were able to demonstrate 7 mK RMS noise over a 67 m path length using 120 s sample time. To our knowledge, this is the best temperature precision reported for a spectroscopic temperature measurement.

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In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.

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The urban heat island phenomenon is the most well-known all-year-round urban climate phenomenon. It occurs in summer during the daytime due to the short-wave radiation from the sun and in wintertime, through anthropogenic heat production. In summertime, the properties of the fabric of city buildings determine how much energy is stored, conducted and transmitted through the material. During night-time, when there is no incoming short-wave radiation, all fabrics of the city release the energy in form of heat back to the urban atmosphere. In wintertime anthropogenic heating of buildings and traffic deliver energy into the urban atmosphere. The initial focus of Helsinki urban heat island was on the description of the intensity of the urban heat island (Fogelberg 1973, Alestalo 1975). In this project our goal was to carry out as many measurements as possible over a large area of Helsinki to give a long term estimate of the Helsinki urban heat island. Helsinki is a city with 550 000 inhabitants and located on the north shore of Finnish Bay of the Baltic Sea. Initially, comparison studies against long-term weather station records showed that our regular, but weekly, sampling of observations adequately describe the Helsinki urban heat island. The project covered an entire seasonal cycle over the 12 months from July 2009 to June 2010. The measurements were conducted using a moving platform following microclimatological traditions. Tuesday was selected as the measuring day because it was the only weekday during the one year time span without any public holidays. Once a week, two set of measurements, in total 104, were conducted in the heterogeneous temperature conditions of Helsinki city centre. In the more homogeneous suburban areas, one set of measurements was taken every second week, to give a total of 52.The first set of measurements took place before noon, and the second 12 hours, just prior to midnight. Helsinki Kaisaniemi weather station was chosen as the reference station. This weather station is located in a large park in the city centre of Helsinki. Along the measurement route, 336 fixed points were established, and the monthly air temperature differences to Kaisaniemi were calculated to produce monthly and annual maps. The monthly air temperature differences were interpolated 21.1 km by 18.1 km horizontal grid with 100 metre resolution residual kriging method. The following independent variables for the kriging interpolation method were used: topographical height, portion of sea area, portion of trees, fraction of built-up and not built-up area, volumes of buildings, and population density. The annual mean air temperature difference gives the best representation of the Helsinki urban heat island effect- Due to natural variability of weather conditions during the measurement campaign care must be taken when interpretation the results for the monthly values. The main results of this urban heat island research project are: a) The city centre of Helsinki is warmer than its surroundings, both on a monthly main basis, and for the annual mean, however, there are only a few grid points, 46 out of 38 191, which display a temperature difference of more than 1K. b) If the monthly spatial variation is air temperature differences is small, then usually the temperature difference between the city and the surroundings is also small. c) Isolated large buildings and suburban centres create their own individual heat island. d) The topographical influence on air temperature can generally be neglected for the monthly mean, but can be strong under certain weather conditions.