Noise and vibration from building-mounted micro wind turbines Part 2: Results of measurements and analysis

Description To research the quantification of vibration from a micro turbine, and to develop a method of prediction of vibration and structure borne noise in a wide variety of installations in the UK. Objective The objectives of the study are as follows: 1) Develop a methodology to quantify the amount of source vibration from a building mounted micro wind turbine installation, and to predict the level of vibration and structure-borne noise impact within such buildings in the UK. 2) Test and validate the hypothesis on a statically robust sample size 3) Report the developed methodology in a form suitable for widespread adoption by industry and regulators, and report back on the suitability of the method on which to base policy decisions for a future inclusion for building mounted turbines in the GPDO

The effect of microphone wind noise on the amplitude modulation of wind turbine noise and its mitigation

Microphone wind noise can corrupt outdoor recordings even when wind shields are used. When monitoring wind turbine noise, microphone wind noise is almost inevitable because measurements cannot be made in still conditions. The effect of microphone wind noise on two Amplitude Modulation (AM) metrics is quantified in a simulation, showing that even at low wind speeds of 2.5 m/s errors of over 4 dBA can result. As microphone wind noise is intermittent, a wind noise detection algorithm is used to automatically find uncorrupted sections of the recording, and so recover the true AM metrics to within ±2/±0.5 dBA

The sensitivity of the colour of dust in MSG-SEVIRI Desert Dust infrared composite imagery to surface and atmospheric conditions

Infrared "Desert Dust" composite imagery taken by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), onboard the Meteosat Second Generation (MSG) series of satellites above the equatorial East Atlantic, has been widely used for more than a decade to identify and track the presence of dust storms from and over the Sahara Desert, the Middle East, and southern Africa. Dust is characterised by distinctive pink colours in the Desert Dust false-colour imagery; however, the precise colour is influenced by numerous environmental properties, such as the surface thermal emissivity and skin temperature, the atmospheric water vapour content, the quantity and height of dust in the atmosphere, and the infrared optical properties of the dust itself. For this paper, simulations of SEVIRI infrared measurements and imagery have been performed using a modelling system, which combines dust concentrations simulated by the aerosol transport model COSMO-MUSCAT (COSMO: COnsortium for Small-scale MOdelling; MUSCAT: MUltiScale Chemistry Aerosol Transport Model) with radiative transfer simulations from the RTTOV (Radiative Transfer for TOVS) model. Investigating the sensitivity of the synthetic infrared imagery to the environmental properties over a 6-month summertime period from 2011 to 2013, it is confirmed that water vapour is a major control on the apparent colour of dust, obscuring its presence when the moisture content is high. Of the three SEVIRI channels used in the imagery (8.7, 10.8, and 12.0 μm), the channel at 10.8 μm has the highest atmospheric transmittance and is therefore the most sensitive to the surface skin temperature. A direct consequence of this sensitivity is that the background desert surface exhibits a strong diurnal cycle in colour, with light blue colours possible during the day and purple hues prevalent at night. In dusty scenes, the clearest pink colours arise from high-altitude dust in dry atmospheres. Elevated dust influences the dust colour primarily by reducing the contrast in atmospheric transmittance above the dust layer between the SEVIRI channels at 10.8 and 12.0 μm, thereby boosting red and pink colours in the imagery. Hence, the higher the dust altitude, the higher the threshold column moisture needed for dust to be obscured in the imagery: for a sample of dust simulated to have an aerosol optical depth (AOD) at 550 nm of 2-3 at an altitude of 3-4 km, the characteristic colour of the dust may only be impaired when the total column water vapour is particularly moist ('39 mm). Meanwhile, dust close to the surface (altitude < 1 km) is only likely to be apparent when the atmosphere is particularly dry and when the surface is particularly hot, requiring column moisture/13 mm and skin temperatures '314 K, and is highly unlikely to be apparent when the skin temperature is/300 K. Such low-altitude dust will regularly be almost invisible within the imagery, since it will usually be beneath much of the atmospheric water vapour column. It is clear that the interpretation of satellite-derived dust imagery is greatly aided by knowledge of the background environment

Multichannel analysis of correlation length of SEVIRI images around ground- based cloud observatories to determine their representativeness

Images of measured radiance in different channels of the geostationary Meteosat-9 SEVIRI instrument are analysed with respect to the representativeness of the observations of eight cloud observatories in Europe (e.g. measurements from cloud radars or microwave radiometers). Cloudy situations are selected to get a time series for every pixel in a 300 km × 300 km area centred around each ground station. Then a cross correlation of each time series to the pixel nearest to the corresponding ground site is calculated. In the end a correlation length is calculated to define the representativeness

Noise and vibration from building-mounted micro wind turbines part 3 : prediction methodology

This brief report describes a simplified method for estimation of levels of structure-borne sound in buildings to which a micro-wind turbine (MWT) is attached. The method is applicable to two specific designs of MWT, each for three lengths of mounting pole and for masonry buildings. The output gives expected noise level for given rotational speed of the MWT. Applicability and limitations of the method are described. A more general methodology is provided in companion reports but requires specialist knowledge to implement. Structure-borne sound is notoriously difficult to predict and several assumptions have been necessary in order to produce a sufficiently simple estimation method. Therefore, caution is required in relying on the predictions until sufficient confidence has been built up through experience of real installations

Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products

The EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol–cloud–radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150 km swath and a pixel sampling at 500 m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.</p

Perception of noise from large wind turbines(EFP-06 Project)

Is noise from large wind turbines more annoying than noise from small wind turbines? This is a question that is discussed widely in the context of a new generation of large wind turbines replacing the traditional smaller ones. To date legislation takes noise levels and the tonality of noise sources into account. However, many more influencing factors are known from the psychoacoustic literature. Examples are the nature of the listening environment, spectral and temporal characteristics of the sound, and the influence of masking noise. An earlier part of the EFP-06 project established the measurable differences between large and small wind turbines. It concluded that spectral characteristics are generally very similar apart from a slight increase in the low frequency content of large turbines. In this study on the perception of wind turbine noise, audibility thresholds and equal annoyance contours have been established for idealised wind turbine sounds containing low frequency tones. The listening test simulated an indoor scenario and an outdoor scenario with and without masking garden noise. The focus has been on the question whether annoyance changes with the frequency of a tone. The test sounds consisted of a broadband spectrum with a specific tone at one of the frequencies 32, 44, 72, 115, 180 and 400 Hz. Idealised sounds with features broadly representative of wind turbine sounds were used. The participant were asked to imagine being in different scenarios. The outdoor scenario presented sounds broadly representative of a wind turbine at three A-weighted sound pressure levels, each with and without garden noise, whereas the indoor scenario omitted the garden noise since the facade attenuation rendered it inaudible. A comparative adaptive method was used to establish relative equal annoyance levels in the form of equal annoyance contours. The results enable comparisons between different scenarios, broadband levels, tone frequencies, masked and unmasked ‘wind turbine’ sound, and two different prominence levels for the reference tone. Temporal variation like “swishing” was avoided to keep the research questions well focused. In a second part of the study wind turbine recordings from a large and a small wind turbine were compared in annoyance with steady traffic noise. The recordings were manipulated to include the effect of sound propagation and façade attenuation. They were also normalised to equal A-weighted levels.The study concludes:Tones in quiet were heard at levels that agree well with hearing thresholds published elsewhere. As the broadband noise level increases the tones were heard at levels that were determined by the masking level. Masking thresholds predicted by the ISO 1996-2 standard have been shown to agree well with the measured tonal audibility thresholds as long as the masking noise clearly exceeds the hearing threshold of the tones. As low levels can frequently occur indoors in the neighbourhood of wind turbines when the Danish noise regulations are observed it would be useful to extend the standard to include a method to evaluate the hearing threshold. One possible method published by Pedersen (2008) to establish the audibility of broadband spectra has been successfully tested for two examples: a broadband spectrum of room background noise and the broadband spectra of wind turbine noise at levels close to the hearing threshold. The calculated critical band levels agree to within 2 dB with perceived audibility. Theoretical considerations support the conclusion that the method should be adequate for use in standard applications. Low frequency tones had to be adjusted to higher tone levels above the masking threshold to be equally annoying as higher frequency tones. Garden noise was not shown to reduce annoyance because different scenarios could not be compared easily. It was shown that increasing the tone level by 5 dB increases the equal annoyance level by a smaller value both for tone frequencies lower than 180 Hz and at 400 Hz. This casts doubt on the appropriateness of the adjustment used in the ISO 1996-2 standard which adds penalty adjustments which are increasing linearly with sound pressure level above masking. Relative sensation levels were calculated from equal annoyance contours to determine whether low frequency tones are relatively more annoying than high frequency tones. The frequency dependence was not shown to be significant. The main influence on these levels is the tone level above masking level: Tones at higher levels are more annoying than tones at lower levels above masking. Both findings are common for the indoor and outdoor scenarios. To compare real recordings of a large and a small wind turbine a test protocol was developed. This method was successfully trialled. The comparison between normalised recordings showed the spectral characteristics of the small turbine to be more annoying outdoors than those of the large turbine recording. This has been attributed to the different spectral characteristics of the two turbines. These differences are effectively masked by garden noise and the equal annoyance ratings change accordingly. The indoor scenario does also not find the turbines to be differently annoying. If these results can be reproduced in other listening experiments then it follows that the specific differences in spectral content will determine the annoyance levels from a wind turbine more than whether it is a small or a large turbine. It would also mean that the differences in annoyance between wind turbines get smaller when sufficient masking noise is present. Presently, the finding that the small turbine is more annoying cannot be generalised to large and small wind turbines or to a wider range of wind and terrain conditions than were used in the test. The listener responses were however consistent and therefore demonstrate the potential of the comparison method. Another significant achievement of this project was of technical nature: It was the design of an immersive sound reproduction system that is calibrated to high precision over the largest part of the audible frequency range including low frequencies down to 30 Hz. It has been shown that this design is possible and that the stimuli sound realistic. Future listening test with similar requirements will therefore be easy to design and fast to perform.In answer to the initial question whether large turbines are more annoying than small wind turbines, the results of this study find no evidence for a significant difference in annoyance between small and large wind turbines as long as total noise levels and tonal characteristics are taken into account in the assessment. Temporal variations of wind turbine noise such as the level of swishing might also have to be evaluated in the future

HETEAC – the Hybrid End-To-End Aerosol Classification model for EarthCARE

The Hybrid End-To-End Aerosol Classification (HETEAC) model for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is introduced. The model serves as the common baseline for the development, evaluation, and implementation of EarthCARE algorithms. It guarantees the consistency of different aerosol products from the multi-instrument platform and facilitates the conformity of broad-band optical properties needed for EarthCARE radiative-closure assessments. While the hybrid approach ensures that the theoretical description of aerosol microphysical properties is consistent with the optical properties of the measured aerosol types, the end-to-end model permits the uniform representation of aerosol types in terms of microphysical, optical, and radiative properties. Four basic aerosol components with prescribed microphysical properties are used to compose various natural and anthropogenic aerosols of the troposphere. The components contain weakly and strongly absorbing fine-mode and spherical and non-spherical coarse-mode particles and thus are representative for pollution, smoke, sea salt, and dust, respectively. Their microphysical properties are selected such that good coverage of the observational phase space of intensive, i.e., concentration-independent, optical aerosol properties derived from EarthCARE measurements is obtained. Mixing rules to calculate optical and radiative properties of any aerosol blend composed of the four basic components are provided. Applications of HETEAC in the generation of test scenes, the development of retrieval algorithms for stand-alone and synergistic aerosol products from EarthCARE's atmospheric lidar (ATLID) and multi-spectral imager (MSI), and for radiative-closure assessments are introduced. Finally, the implications of simplifying model assumptions and possible improvements are discussed, and conclusions for future validation and development work are drawn.</p