49 research outputs found
Chatbots onder de loep: onderzoek naar de gepercipieerde klantwaarde, gebruiksintentie en de invloed van antropomorfisme en demografische factoren
No full textChatbots onder de loep: onderzoek naar de gepercipieerde klantwaarde, gebruiksintentie en de invloed van antropomorfisme en demografische factoren
No full text
Tropospheric nitrogen dioxide inversions based on spectral measurements of scattered sunlight
No full textThis thesis describes the development of inversion methods for tropospheric nitrogen dioxide (NO2), based on ground based observations of scattered sunlight with themulti-axis differential optical absorption spectroscopy (MAX-DOAS) technique. NO2 is an atmospheric trace gas which, when present near the surface, is an important component of air pollution. On a global scale, fossil fuel combustion processes (power plants, automobiles) are the main source of NOx (=NO+NO2). NOx has a major impact on air quality, by its essential role in atmospheric photochemistry mechanisms: it influences tropospheric ozone formation as well as the levels of other oxidants (such as the hydroxyl and peroxy radicals), which catalyze the removal of species like carbonmonoxide, methane and other hydrocarbons from the atmosphere. In addition, NOx affects the formation of aerosols. Through the combination of these effects, tropospheric NOx reduces the radiative forcing, and therefore has a cooling effect on climate. A MAX-DOAS instrument measures wavelength spectra in the UV/Vis, with a resolution of less than one nanometer, in multiple viewing directions relative to the horizon. These measurements are analyzed with the differential optical absorption spectroscopy (DOAS) method, which can distinguish between the traces gases absorbing in a certain spectral window by making use of the fact that each gas has a unique spectral fingerprint. MAX-DOAS type of observations are complementary in two ways to other measuring techniques for NO2: Firstly in a temporal sense, relative to space-borne observations from the current generation of polar orbiting satellites, which frequently have no more than one observation per day. Secondly the MAX-DOAS observations are complementary in a spatial sense to in-situ monitors, which can only measure NO2 at the surface. MAX-DOAS instruments are especially suitable to measure tropospheric NO2 columns. This quantity is, more than NO2 concentrations measured at the surface, relevant for studies of transport and of trends in total amounts of tropospheric NO2. In this work it is investigated which information about the total amount and vertical distribution of tropospheric NO2 is contained in the MAX-DOAS measurements, and how this information can be extracted through inversemodeling (retrieval). What are the main error sources and which assumptions have to be made? Special attention is paid to aerosols, which have a large impact on the MAX-DOAS measurements. In addition, the developed retrieval methods are applied to a 14 month data set of MAXDOAS measurements performed in De Bilt. This data set was obtained as part of this research, and is unique for the Netherlands. The results are compared to satellite observations and to an air quality model. The first research described in this thesis (Chapter 3), focuses on the retrieval of tropospheric NO2 columns under clear sky conditions. A method was developed to derive differential air mass factors, by taking into account the effect of aerosols on the NO2 measurements. This was done in a new way: it was demonstrated that the aerosol optical thickness could be derived, for each elevation separately, by solely making use of MAX-DOAS measurements of relative intensity. It was assumed that all NO2 and aerosols were contained in a homogeneously mixed boundary layer of 1 km height. With this method, aerosol corrected air mass factors were derived for the elevations 4 degrees, 8 degrees and 16 degrees. Vertical columns could be derived for each elevation separately. Within this set of elevations, the 4 degrees elevation has the advantage of being most sensitive to trace gases in the boundary layer, but this viewing direction is also most sensitive to errors in the assumed aerosol and NO2 profile shape. With increasing elevation, the sensitivity to traces gases decreases, as well as errors due to wrong assumptions about the profile shapes. The retrieval method was applied to clear sky periods within the 14 month data set of MAX-DOAS observations performed in De Bilt. A comparison with AErosol RObotic NETwork (AERONET) observations of aerosol optical thickness showed good results: correlation of 0.85 was found, and a slope of the linear fit close to one. Comparison with space-borne retrievals of tropospheric NO2 columns retrieved by the OzoneMonitoring Instrument (OMI) shows on average reasonable results (correlations between 0.64 and 0.88 for different subsets), but individual comparisons can differ by more than a factor of two. This was attributed for the largest part to differences in spatial representativity, mostly in the horizontal direction, but also in the vertical. The second study (Chapter 4) focused on the question which information about the vertical distribution of aerosols and NO2 is contained in the MAX-DOAS observations. Vertical profile information derived from MAX-DOAS observations is not only relevant to improve the accuracy of the column retrieval, but it is needed as well in comparisons with other measurement techniques, such as satellite and lidar, and to derive NO2 surface concentrations, which are more directly related to air quality than vertical columns. Profile retrieval is challenging, since the profile information contained in MAX-DOAS measurements is known to be quite low. The topic is currently an active area of research in the MAXDOAS community: a range of approaches is being investigated, and no approach has yet emerged that can be considered a proven concept in all respects, partly because validation is a challenge as well. One of the main research questions addressed in this study, was the question if MAX-DOAS measurements can be used to distinguish between NO2 in the boundary layer and in the free troposphere. The basic retrieval model for tropospheric columns of the first study was expanded with two parameters for NO2, and one for aerosols: the height of the aerosol and NO2 layer above the surface was not longer assumed �fixed, and a second elevated NO2 layer was introduced at a fixed altitude in the free troposphere. In addition O4 measurements were used instead of relative intensity measurements, in order to better characterize the aerosol extinction profile in the boundary layer. Sensitivity studies were performed to investigate the retrieval accuracy for different noise levels, and for aerosol and NO2 profile shapes that were different from those assumed in the retrieval model. This led to the following conclusions: Firstly, if (in reality) NO2 is present above the boundary layer, and if the retrieval model allows an elevated NO2 layer at the same altitude as the real layer, then the amount of elevated NO2 can in principle be retrieved with reasonable accuracy. Secondly, for retrieval models which allow an elevated NO2 layer, tropospheric NO2 may also be retrieved when it is not present in reality. This may be the case for example when the aerosol andNO2 profiles shapes in the boundary layer are not well described by the retrieval model, or when the signal to noise level is low. Finally, despite the fact that MAX-DOAS measurements frequently do not contain more than two or three pieces of information to describe the NO2 profile, a retrieval model with only three free parameters will frequently be too rigid to perform accurate retrievals. In Chapter 6 of this thesis a more flexible approach is proposed. The profile retrieval approach was applied to MAX-DOAS measurements taken at the Cabauw Intercomparison campaign for NItrogen Dioxide measuring Instruments (CINDI). Comparison with independent observations of tropospheric NO2 columns from a lidar and NO2 surface concentrations from an in-situ monitor, showed on average good agreement (an average difference below 5 percent for both), but significant differences for individual cases. The third part of the research (Chapter 5) consisted of a comparison of tropospheric NO2 columns derived from the 14 month data set (that was also used in the first study) with tropospheric columns from the regional air quality model Lotos-Euros, which was run on a resolution of approximately 7x7 km. Whereas the comparison with satellite observations (Chapter 3) could only be performed under cloud free conditions, and at most two times per day, the comparison with the air quality model could be performed by making use of all MAX-DOAS observations. The total data volume therefore increased by a factor of 30, which improved the statistical significance, and allowed more detailed case studies. In order to analyze MAX-DOAS measurements under cloudy conditions, it was required to develop a third retrieval approach. This was based on MAX-DOAS observations at 30 degrees elevation (and the zenith reference), in order to be least sensitive to errors in the assumed NO2 profile shape, and to aerosols (the retrieval of which is difficult under cloudy conditions). Air mass factors were derived using information about the boundary layer height from a meteorological model. In addition, lidar observations of cloud bottom height were used. The comparison between Lotos-Euros and MAX-DOAS showed on average a good agreement (an average difference below 1 percent, and for daily averages over cloud free days a correlation of 0.8). The agreement found was surprising, especially when considering the fact that a bottom-up approach (the model) is compared to a top-down approach (the measurements). Furthermore, a remarkably good agreement was found for the tropospheric NO2 column averaged per sector of the wind direction. This indicates that the average tropospheric NO2 column that is measured in De Bilt, is not dominated by local sources, such as nearby highways with frequent traffic jams (such emissions are difficult to capture in the model), but rather by emissions in densely populated and industrial areas further away, e.g. the cities of Rotterdam, Amsterdam, Antwerp, Brussels and the German Ruhr area. It appears that tropospheric NO2 columns measured with MAX-DOAS can be used for validation of (high resolution) chemistry transport models in urban regions, and the same may be expected for satellite observations with a sufficiently small resolution. This is especially relevant because it is known that comparison between satellite and in-situ is problematic in urban regions (due to the large difference in spatial representativity). No observations were performed in summer months. It may however be expected that because of the shorter lifetime of NO2 in summer, nearby sources would have a larger relative impact on the MAX-DOAS observations, and therefore lead to less agreement with the model than as found in this study. For individual comparisons on an hourly and day-to-day basis, observed differences could be substantial. This is mainly attributed to the fact that within the model actual emissions cannot be described on a high enough spatial and temporal resolution. In addition, differences could be large for example when the observed wind direction or wind speed was different from that in the model, or in the weekend: Observations showed on average a clear decrease in the weekend, compared to the rest of the week, whereas the model showed a less pronounced weekly cycle. The three studies described in this work lead to the following general conclusions about MAX-DOAS observations of NO2: Firstly, it has been demonstrated that long-term MAX-DOAS observations of tropospheric columns are particularly suitable for validation of space-borne observations and air quality models. When averaged over long-enough periods, patterns show up (e.g. as a function of time, wind direction, or another quantity) that would not be seen for individual comparisons, or not even for a few months of observations, due to differences in representativity and limited accuracy. Thorough satellite and model validation therefore requires a large network of MAX-DOAS sites, on locations with a variety of conditions with respect to NO2 and aerosols. There is currently no other ground based method that can provide automated tropospheric NO2 column observations for such a low cost per observation. Secondly, it is concluded that with a simple algorithm, based on a high viewing elevation (e.g. 30 degrees), tropospheric NO2 columns can be retrieved with reasonable accuracy, for a large number of different aerosol and NO2 scenarios, and without strong dependence on a-priori assumptions. With respect to NO2 profile retrieval, the situation is different: due to the many aspects that influence the measurements, the required accuracy, and the relatively low information content, the accuracy of individual retrievals is generally not very high (especially for the free troposphere), and depends strongly on a-priori assumptions, as well as on the atmospheric conditions at the time of measurement. To make optimal use of the information content, it is important that the profile shape parametrization is highly flexible for the lowest 1-2 kilometers of the atmosphere. Profile retrieval accuracy is highest and depends least on a-priori assumptions for cloud free situations, when the aerosol optical thickness is low, when the NO2 is located in a boundary layer of which the top lies between approximately 400 m and 1.5 km altitude, and when in addition the MAX-DOAS instrument is aimed away from the sun. Finally, it is concluded that more validation of MAX-DOAS retrieval methods is needed. This requires long-term observations in the presence of other instruments that can be used for comparisons, such as those present at the CINDI campaign. Such comparisons should be performed in various seasons and under various conditions with respect to the abundance of aerosols and NO2
The Retrieval of Tropospheric NO2 Vertical Column Density from Spectrolite Measurements over Berlin
No full textAir pollution has become one of the most serious problems societies worldwide are facing, thus there is an emergent need for air quality monitoring to quantify pollution level and supervise pollution sources. One of the main pollutants, nitrogen dioxide, mostly comes from human activities such as the burning of fossil fuels, vehicle exhaust and electricity generation by power stations. In recent years, methods have been successfully developed and widely applied to monitor trace gases by measuring the vertical column density from space-borne satellites or ground-base stations. Recently, airborne observation for tropospheric trace gases column densities has become more and more popular, providing unique high spatial resolution observations that can be used for emission monitoring and for validation of satellite or ground-based observations. The Netherlands Organization for Applied Scientific Research (TNO) has developed Spectrolite, a compact, low cost hyperspectral imaging spectrometer based on the technological heritage fromTROPOsphericMonitoring Instrument (TROPOMI). In this project, an algorithm was developed to retrieve tropospheric NO2 vertical column densities from Spectrolite spectral observations during the AROMAPEX campaign in Berlin on 21 April, 2016. We applyDifferentialOptical Absorption Spectroscopy (DOAS) approach to obtain differential slant column densities (dSCDs) from spectral measurements. Afterwards, a look-up table which contains radiances output as function of various parameters was derived from radiative transfer model to compute air mass factors (AMFs). However, since we do not know the surface reflectance during the measurements, Landsat observations over a homogeneous region are utilized for vicarious calibration of radiances and this allows us to retrieve surface reflectance needed for AMF calculations. Subsequently, OMI data is used in order to determine tropospheric background and to correct for effects related to stratospheric NO2. Results of the dSCD retrieval show a pronounced NO2 plume over Berlin stretching out from West to East over the city. Several hot spots can be observed and related to emission sources on the ground. They also acquire a good correspondence with the dSCDs retrieved by other instruments (AirMap, SWING) at the same time during the campaign and therefore give much confidence for the future development at TNO. In order to obtain VCDs, AMFs were derived using complementary observations for some parameters (e.g. aerosol optical). Sensitivity studies were performed to assess the impact on the retrieval accuracy of other parameters. It can come to a conclusion that aerosol and NO2 vertical profiles are very essential to the VCD retrieval and need to be more well-defined in order to provide precise VCD results in absolutemagnitude.Civil Engineering and GeosciencesGeoscience and Remote Sensin
Develop a LES-based air quality model by nesting DALES in LOTOS-EUROS
No full textNitrogen dioxide (NO2) is one of the nitrogen oxides (NOx) pollutants. Not only the NO2 itself is toxic to human health, but also the precursors of a number of hazardous secondary air pollutants, such as nitric acid, tropospheric ozone and nitrate component of particulate matters. Besides, NO2 is also an essential substances involving in ozone destruction in the stratosphere. The main source of NO2 over urban is combustion processes from traffic. Jeopardized by the severe situation, the monitoring and observation to this harmful trace gas is important. For urban regions, the in-situ and remote sensing techniques are combined. However, these measurements can be problematic due to the meteorological conditions or atmospheric processes, such as clouds. Besides, the retrieval of the measurements provides limited information on concentration fields under various a-priori assumptions. Alternatively, the atmospheric dispersion modeling is in use to study the air quality, which provides a more complete deterministic description of pollutants dispersion problem. Currently, the dominating atmospheric dispersion models are based on the parameterization. These models are efficient to simulate meso-scale or macro-scale atmospheric dispersion, with spatial resolution of magnitude of kilometers. Considering on urban scale, however, this resolution is too coarse to resolve the air pollutants, where the emission sources are close to receptors. Instead, a more effective technique is large eddy simulation (LES). It applies a low-pass filter that effective removes small-scale turbulences from numerical calculation. By nesting DALES (Dutch Atmospheric Large Eddy Simulation) into LOTOS-EUROS (LOng Term Ozone Simulation-EURopean Operational Smog model), an air quality module is developed to evaluate the LES-based air quality model by comparing with LOTOS-EUROS. The conclusion of this thesis consists of two parts. The first one is the sensitivity study, where the properties of DALES original chemical module are explored. These properties includes the sensitivity of NO2 concentration to background ozone level, reaction rate coefficient, clouds perturbation and turbulent control. In the second part, simulation over Rotterdam is operated on a relative coarse resolution, as the consequence of the limitation of restore space and process capability. The slab averaged profiles are not significantly different because of the strongly constrained concentration boundary condition by LOTOS-EUROS. Although attempt to study the difference of concentration field due to the dynamics scheme is not achieved, DALES still has much higher resolution compared with LOTOS-EUROS. Hence, the spatial variability in DALES is more detailed. Conclusively, the DALES air quality module performs consistently with LOTOS-EUROS. The improvement in terms of chemical mechanism, the emission inventory, the capability of processing. etc. will complete this module in future.Civil Engineering and GeosciencesGeoscience and Remote Sensin
The impact of high resolution surface reflectance data on the accuracy of the TROPOMI tropospheric NO2 product over the greater Rotterdam region
No full textThe Sentinel-5 Precursor satellite has a payload of the TROPOspheric Monitoring Instrument, TROPOMI.The satellite was launched in 2017 by ESA with the intended goal of measuring trace gases in the atmosphere.One of the products of TROPOMI is the Tropospheric NO2 column. This product is based on thespectral measurements to obtain the column abundance of NO2 in the troposphere. This product alsorelies on a-priori data and one of these a-priori datasets is the albedo dataset.The currently used dataset has a resolution of 0.5°x 0.5°, which corresponds to approximately 55 kmx 34 km at mid-latitudes. The TROPOMI pixel size is significantly smaller, 3.5 km x 7 km. Due to this large difference in resolution the discussion arises if this used dataset is sufficient for accurate results. This researchmakes a comparison between the current a-priori dataset and possible replacements.This paper makes this comparison by calculating Air Mass Factors (AMFs) using the OMI LERalbedo climatology as a reference and the two alternative high resolution surface reflectance datasets,Sentinel-2 and Landsat-8. These surface reflectance datasets were regridded and averaged on the corresponding TROPOMI grid. The focus area of this paper is the Greater Rotterdam region in the Nether-lands.Before these AMF calculations were done, a comparison between Sentinel-2 and Landsat-8 surfacereflectance datasets is made. This is done both on their own high resolution and regridded onto theTROPOMI grid. Above water surfaces and land covered by vegetation a bias of approximately 0.01 was present between the two high resolution surface reflectance datasets. These differences are relatively small. The differences calculated for the datasets regridded to the TROPOMI grid were also relatively small, with a bias of 0.01 above the water and vegetation surfaces.Two cases were studied during this research: the 21st of April 2018 and the 6th/7th of May 2018. Theresults show that significant improvements can be made by using a higher resolution surface reflectancedataset. A median bias of -10.4% (-15.6%) was calculated for the 21st of April for Sentinel-2 (Landsat-8)compared to the AMFs based on the OMI albedo dataset. For May this was -3.9% (-9.3%). Furthermorethis study showed extreme AMF-biases of 68.0% overestimation and 39.8% underestimation by the OMIalbedo dataset compared to Sentinel-2, where the overestimation was observed over the greenhouses inthe Westland region and the underestimation in the rural region to the East of the domain in April.For May the underestimation was mostly observed to the West (North Sea), indicating that over regionswith a low surface reflectance the atmospheric correction greatly influences the AMF. The comparisonbetween Landsat-8 and OMI showed similar results in the AMF differences.These findings are supported further by a recent Sentinel-5P validation study, which comparedground based observations to the TROPOMI observations. This project found an NO2 underestimationof approximately 20% for many different stations. This research suggest that, at least partly, this difference can be explained by the coarse resolution of the a-priori albedo dataset used. Civil Engineerin
Acoustic Array Design: The design of a reconfigurable phased microphone array for aeroacoustic wind tunnel measurements
No full textSince both the aircraft and wind energy sectors are experiencing rapid growth, improvements must be made in terms of noise reduction as to enable growth whilst fulfilling the restrictions on noise pollution. An open-section vertical wind tunnel with an anechoic test chamber has recently been constructed at the Delft University of Technology, in part to facilitate research into this subject.The purpose of this thesis project is the design, creation, testing and evaluation of a reconfigurable phased microphone array for this wind tunnel. Tests were performed with a calibrated sound source, and using conventional (delay-and-sum) beamforming, CLEAN-PSF and CLEAN-SC, performance was assessed in terms of sound power level and sound source location estimation.The result of this iterative process is a practical, reconfigurable phased microphone array for acoustic analysis using beamforming, which is calibrated in third octave bands between 500 and 5000 Hz.Aerospace Engineering | Aerodynamics and Wind Energ
Separation of NOx emissions from Drilling, and Oil and Gas Extraction in the U.S. using Monthly Data from the Ozone Monitoring Instrument
No full textHorizontal drilling and hydraulic fracturing have increased unconventional oil and gas extraction from shale reserves in the U.S. in the last decade, making up more than half of total U.S. oil and gas production at present. This activity results in NOx emissions in the extraction regions that are measurable from space using the Ozone Monitoring Instrument (OMI) on the NASA Aura satellite. The NOx emissions are a result of two different activities: (1) the drilling and hydraulic fracturing of new wells, and (2) the extraction of oil and gas after the well is completed. To separate the NOx emissions from drilling and extraction, a multiple linear regression to the NO2 columns as a function of time is calculated for 9 extraction regions using the number of drilling rigs and the oil and gas extraction data from 2007 until 2018. In 3 regions (Permian, Bakken, Eagle Ford) a significant correlation between measured and modeled NO2 columns is found, of which the Permian region shows the highest correlation. The analysis shows that half of the total NOx emissions in the Permian region can be attributed to emissions from oil and gas activities, and that both the drilling and extraction activities have an equal share in the emissions. A fuel-based oil and gas emission inventory shows a different split for NOx emissions from drilling and extraction in the Permian region, indicating drilling as the larger source. In other extraction regions, NO2 columns show poor correlation with the oil and gas activities due to the proximity of urban areas (Barnett, Denver-Julesburg, Haynesville regions), power plants (San Juan) or variations in the drilling and extraction activity over time that are too small (Uintah, Upper Green River)
