This report discusses urban air quality measurements carried out in a park in Aigaleo (Athens), located adjacent to a busy road. The measurements were taken using the Sniffer4D Mini 2 sensor box with a drone to investigate how Urban Air Mobility can aid in measuring urban air quality. CO, NO₂, O₃, SO2, PM_2.5 and PM₁₀ concentrations were recorded through point measurements at varying locations, altitudes and times. Several validation measurements were carried out, showing that temperature heavily influenced the outcome of the recordings. Due to the high number of variables, no conclusion has been found on the wind effect. During rush hour, NO₂ and CO concentrations were highest close to the traffic; however, NO₂ concentration showed non-linear behaviour with increase in altitude when further from the traffic or out of rush hour. SO₂ concentration always decreased with an increase in altitude; highest concentrations were observed further from the busy road. Highest O₃ concentrations were obtained in the afternoon at higher altitudes, due to its reaction under sunlight. PM_2.5 and PM₁₀ concentrations had a high variability due to environmental conditions. Additionally, continuous measurements were carried out, in which the drone flew a path through several locations and altitudes. The results from these were interpolated to enable the detection of areas with higher concentrations of air pollutants.

Addressing the increasingly urgent need for sustainable aviation solutions, this study explores operational innovations as a quicker and more scalable addition to novel zero-emission propulsion systems. Through the use of regression-based causal inference methods, this study aims to understand the relationship between flight fuelburn inefficiency and the factors causing these inefficiencies. Such an approach allows for the attribution of inefficiencies to factors on an overall scale, requiring less specific domain knowledge for initial results. A case study, involving a sample of 100,000 flights, representative of European operations, reveals that airspace structure (3.2% increase in inefficiency) and turbulence along the flight plan (2.5% increase) are the leading causes, while variations in average airspeed, congestion, and crosswind contribute the least to flight inefficiency. A compilation of the results shows that the performed analysis leaves 61% of the observed flight inefficiency unaccounted for. Future work would include the exploration of different metrics even closer to actual climate and air quality effects, as well as detailed uncertainty quantification. The developed flight inefficiency prediction model allows experimentation with counterfactual scenarios, contributing to the global transition towards more sustainable air transport networks.

Ammonia shows great potential for decarbonizing the road transportation sector because it does not produce CO₂ emissions during combustion. On the other hand, ammonia-fueled engines emit gases such as (unburned) ammonia (NH₃), and nitrogen oxides (NO)_x, which contribute to air pollution and adversely impact human health, among other environmental effects. The aim of this work is to investigate the air quality impacts and human health trade-offs associated with potential emissions from an ammonia-fueled road transportation fleet of different vehicle categories. Specifically, we create a simplified emissions tool to quantify the NH₃ and NO_x spatial emissions from state-of-the-art ammonia engine developments. Next, the emissions are combined with spatial sensitivities, obtained from the adjoint of GEOS-Chem, to estimate the corresponding air quality impacts in terms of PM_2.5 formation and human health impacts with respect to premature mortalities.
The research findings indicate that the ammonia-fueled sector generally exhibits higher air quality and human health impacts compared to conventional transport. We estimate that the implementation of various ammonia engine configurations into the road transportation fleet in the USA in 2011 could lead to approximately 23 000 to 250 000 premature mortalities.
However, there is potential for mitigating air quality impacts of ammonia emissions through the use of post-combustion treatment methods or the adoption of ammonia-fueled heavy-duty vehicles. These approaches could help achieve air pollution levels comparable to those of fossil fuel vehicles while reducing the carbon footprint, offering future possibilities for an ammonia-fueled road transportation sector.

Aircraft noise is a significant problem for communities surrounding airports. Accurate prediction models are needed to estimate noise levels from aircraft operations. In this research, the accuracy of the sonAIR aircraft noise model is evaluated in predicting noise levels around Schiphol airport by comparison to measurement data from NOMOS and the current best-practice modelling approach Doc29. Results show a significant but consistent underestimation of noise levels by sonAIR, mainly due to a generalisation of emission models. The standard deviation of differences between model results and measurements is lower for sonAIR than for Doc29 by up to 1 dB. Differences between measurement and model results were found in the relation between N1 and noise levels, maximum noise levels and frequency spectra. These results demonstrate that sonAIR provides more reliable predictions of noise levels on the single flight event level than Doc29. Additionally, this study shows agreement with results from a previous validation study in Zürich, thereby confirming the applicability of sonAIR to another airport. This research contributes to better aircraft noise predictions, which will have implications ultimately leading to a better quality of life for communities affected by aircraft noise.

Noise quantification methods for helicopters are limited, this especially holds for military helicopters. This research assesses the suitability of an existing civil helicopter noise model for the military helicopters of the RNLAF. In order to achieve this noise modeling platform HELENA, which uses hemispheres created for the Apache in a previous project, has been integrated as input data in this research. HELENA has previously been used for civil helicopters. Surrounding the Gilze Rijen Airport, the noise measuring network Casper is installed. From Caspers Noise Measuring Terminals (NMT), noise levels 𝐿𝐴,𝑚𝑎𝑥 and 𝑆𝐸𝐿 are extracted for every helicopter that passes by. These values are compared with the calculations from HELENA.
For this research a set of flights has been selected, carefully keeping the limitations of both HELENA as well as Casper in mind. The most ideal flights would be steady, straight, symmetric and repeatable flights. Transit flights departing to or returning from a northeast positioned low-level flying area, encompass most of these requirements. These flights pass three NMTs. For a full year, all Apache flights passing these three NMTs were collected. The formation flights and flights with a maximum 𝐿𝐴,𝑚𝑎𝑥𝑑𝐵(𝐴) relatively close to the background 𝐿𝐴,𝑚𝑎𝑥 ≤ 70𝑑𝐵(𝐴) were removed. In total 108 noise events were selected for the model-calculation comparison. In general, the noise events were underestimated by HELENA. The error, measurement minus calculation, showed a large difference with a mean of𝜇 = 4.9𝑑𝐵(𝐴) and variance of 𝜎 = 2.9𝑑𝐵(𝐴). Upon closer inspection, the performance varied amongst the NMTs. One NMT (58) had the least noise events after selection but produced the largest difference between measurement and calculation (𝜇 = 8.8𝑑𝐵(𝐴) and variance 𝜎 = 3.3𝑑𝐵(𝐴)). The NMT with the most (70) noise events produced the smallest error with a mean (𝜇 = 4.2𝑑𝐵(𝐴)) and variance (𝜎 = 2.4𝑑𝐵(𝐴)). The underestimation could be due to certain circumstances that influence the measurement but are not included in the calculation. No correlation could be found for the presence of wind, deviation in speed relative to the speed of the corresponding hemisphere, distance or addition of ground effect.

Aircraft noise and its impact is one of the biggest challenges the aviation industry faces today. At airports, the number of operations and the flight routes are driven by the noise impact on the surrounding communities. To predict the expected aircraft noise levels around airports, noise models are used. The accuracy of these models is thus of great importance. This research aims to improve aircraft noise modelling by validation and calibration of the main input parameters using acoustic measurements. This research is focused on the Doc.29 aircraft noise model. This is an empirical model, based on Noise-Power-Distance (NPD) tables, which is convenient for fast computations of a large number of flight operations. The data set used consists of take-off measurements of the B737-800 gathered around Schiphol airport. To validate and calibrate the model with measurements, all input parameters should be correct to be able to identify where deviations come from. The power parameter thrust is an important input, but often not exactly known. The N1 rotational speed of the engines can be used to estimate the used thrust. An estimation of the N1% is performed by finding the fan tones from acoustic measurements. The found N1% is validated with Aircraft Condition and Monitoring System data (ACMS) from the measured flights. The estimation resulted in an average 4% root mean square error with the ACMS data. When using the estimated N1% as input for thrust, differences between model results and measurement are still found. These differences are assumed to be caused by errors in the NPD table. This allows altering the entries in the NPD table by adding the found differences from the measurements reduces the mean error to less than ±0.2 dBA and providing a 20-30% reduction in standard deviation. Another method of model improvement is done by looking at the measurements which have been standardised to reference conditions. The relation between thrust setting and sound level showed to be less dominant than originally expected from the NPD table. From these newfound thrust-noise relations, new NPD tables are created. This caused a 30-40% reduction in standard deviation, reducing the variation found between noise measurements and model results significantly. Next to an improvement in best-practice noise modelling, the methods described in this research give insight into the creation and validation of NPD values.

In recent years, there has been a rise of electric propeller aircraft in the field of general aviation. These propeller aircraft greatly reduce the emissions and engine noise compared to conventional aircraft, but noise coming from the propeller stays unchanged. Acoustic imaging, using beamforming, could help in the characterization of associated noise sources. In this research, the noise of a Cessna Skymaster 337F is recorded using a microphone array, and two beamforming algorithms are applied in the data analysis: conventional beamforming (CTDBF) and rotating beamforming (ROSI). The combination of these two algorithms adds a new dimension to acoustic analysis of propeller noise, namely a choice of reference frame, which allows the researcher to separate rotating noise sources from stationary noise sources. It has been shown that this is a very valuable tool for localizing the noise, making it easier to reduce the propeller noise in future research.

For a hub airport, capturing transfer passengers and offering better connections are key elements that largely influence its future growth and profitability. This research aims to develop a strategic stand planning model capable of selecting profitable turnarounds that will expand the network of a hub, integrating those turnarounds into the pre-existing schedule and efficiently capturing transfer passengers. The model includes 2 main goals, namely i) the maximization of the number of captured transfer passengers and the ii) minimization of connection times, which are integrated with 2 other objectives, iii) the minimization of unassigned turnarounds and iv) the minimization of tow moves. The 4 objectives are solved hierarchically in the order: iii)-i)-ii)-iv). In an attempt to tackle the inherent complexity of models that include transfer passengers, the problem is split into two less complex levels. One solves the multi-objective function and the other delivers a specific stand assignment. This approach significantly reduced the computational load for large input sets. The results show that an efficient stand planning can maximize the transfer passenger throughput by up to 38.66\% and reduce the average connection by 17.86\%. It was also possible to conclude that objectives i) and ii) conflict with each other. Further results confirmed that the time slot to which each new turnaround is allocated is the best slot for the airport, but it is not necessarily the most profitable for the airlines. This research could lead to the development of tools used by rapidly expanding airports to assess the connection potential of new routes. It can also be utilized by busy airports to optimize the current schedule and to make important time slot decisions.

As poor air quality poses a risk to human health, this study aims to estimate the impact of Schiphol airport on local concentrations of various air pollutants from January 2014 to August 2020. The pollutants of interest are nitrogen monoxide, nitrogen dioxide, ozone and particulate matter. Three separate methods were applied: a comparison of air quality measurements from different locations, an analysis about the effect of wind on ambient concentrations and finally meteorology and road and air traffic activity-based regression modelling. Based on these methods it was estimated that the airport is responsible for between 24 to 31% of local concentrations of nitrogen dioxide. During the COVID-19 situation these effects decreased by ~ 4 - 5 µg/m3, which is 17 - 21% of the average concentrations measured in the years before. For the other pollutants the results were less robust and quantitative estimates include large uncertainties.

The past years there has been a significant increase in the popularity and commercial availability of consumer drones.

In order to reduce aircraft emissions during on-ground operations, electric taxiing systems (ETS) have been intensively researched to take over or assist in part of the taxiing phase of a flight. One of these ETS is the TaxiBot, deployed by Smart Airport Systems (SAS). While a number of papers have been researching this vehicle routing problem (VRP) in order to minimise costs, fuel consumption or another metric, most research uses deterministic input data. However, sudden changes are inevitable, disrupting the resulting schedule. In this paper, we propose both a strategic model and a tactical model for airport surface movement, taking into account stochastic delays to the flight schedule. The subsequent tactical schedule can be produced with only little deviations from the strategic schedule. The tactical model can be generated in the order of seconds, making it useful for real-life traffic management decision support systems. We found that the tactical schedule does not worsen remarkably. Still 47.9% of the flights can be towed by a TaxiBot, which was 48.5% in the strategic schedule. Different case studies have been performed in order to determine the effect of e.g. the size of the flight schedule and the number of TaxiBots used, on the aircraft taxiing coverage and TaxiBot efficiency. With this, both busy and calm days, now and in the near future are assessed and the optimum number of TaxiBots necessary can be determined. An upper limit is reached at an asymptote starting from 34 TaxiBots, while a lower limit is dependent on a trade-off between flight coverage and spare TaxiBot capacity.

Permeable trailing edges are experimentally investigated in this thesis as a mean tomitigate aeroacoustic noise. The first part of the study is devoted to deciphering themechanisms of noise generation involved in these devices. To this aim, trailing-edge inserts are manufactured employing commercially-produced open-cell metallic foams with different material properties, i.e., permeability and pore size.@en

As the number of aircraft movements increases around Schiphol, and other airports alike, questions are being raised about the environmental impact of the aircraft movements. One of the questions about the environmental impact of aircraft operations is the validity of aircraft noise prediction models. This research focuses on the validation of the input parameters for the ECAC Doc.29 aircraft noise model by combining flight data with aircraft noise measurements.

Over the past years, noise nuisance around airports strongly increased resulting in the need for aircraft noise reduction. Therefore, the noise sources should be known. This thesis assesses a new acoustic imaging method to identify sources on aircraft fly-over measurements. The proposed Global Optimisation (GO) algorithm is based on the theory behind Conventional Beamforming, but can identify sources in 3-dimensions and potentially overcomes the spatial resolution limit. This imaging method was applied to simulations, an anechoic room set-up, and two fly-over measurements (landing and take-off) performed with a 64-microphone array. The simulations and anechoic room test showed that GO can overcome the spatial resolution limit, but has difficulty finding the correct distance between the array and the source. The fly-over cases showed that the aircraft height was not found by GO. For the landing case, the engines and landing gear were found as sources. For the take-off case, GO did not find sources at low frequencies. The method is promising, but to increase the performance on fly-over measurements, it is advised to use the knowledge of the aircraft geometry when applying the GO algorithm.

The amount of air traffic worldwide is increasing, with an adverse effect on aircraft noise in the vicinity of airports as a result. Measurements and calculations have complementary benefits and limitations for the assessment of aircraft noise. A common method for the calculation of aircraft noise is ECAC Doc. 29. Various improvements of this method have been developed and studied in the past. However, research often lacks large numbers of measurements to validate these findings. The current study examined the effect of ECAC Doc. 29 model improvements on the differences between measured and calculated aircraft noise levels. The two improvements addressed in this research are: (1) The use of actual instead of standard meteorological conditions and (2) the use of derived flight performance instead of standard flight performance profiles. The calculated results have been compared with NOMOS measurements, the network of unattended microphones around Amsterdam Airport Schiphol. Using 151,108 flights and 385,001 NOMOS measurements, it was found that the difference between measurement and calculation depends on type of operation, aircraft type, and position of the microphone. The use of actual meteorological conditions showed the ability to reduce variability due to temperature, relative humidity, and pressure. The use of derived flight performance showed the ability to reduce variability due to wind up to 8 m/s. However, the absolute difference between measurements and calculations did not decrease for both improvements. Additionally, the aircraft substitution corrections were assessed. The substitution corrections based on ICAO type code showed smaller differences between measurements and calculations compared to the corrections based on aircraft configuration. It is suggested to study the substitution corrections further in the future. Moreover, it is advised to make use of the advancements in air traffic operations research for noise calculations based on derived flight performance.

With the increasing human activities in the marine environment, such as fisheries, dredging, coastal protection or construction of marine infrastructure, seabed sediment and habitat mapping have become highly relevant for the development of sustainable marine management strategies. Compared to traditional mapping methods, primarily based on bed sampling, multibeam echosounding belongs to the cutting-edge technology to time-efficiently acquire high-resolution bathymetric and backscatter (BS) data over large areas. Using classification methods to combine the acoustic data with ground-truthing, large-scale maps can be automatically and objectively produced, that enables to describe the distribution of benthic habitats or quantify marine resources. However, acoustic sediment classification still does not allow to discriminate between the entire heterogeneity of the seabed and is generally applied to a single multibeam echosounder dataset by means of revealing the seabed state only at a given time instant. Two challenging issues addressed within the scope of this thesis are summarized as: (1) Investigation on the applicability of repetitive multibeam (single-frequency) BS measurements for monitoring the seabed; and (2) Evaluation of the potential of multispectral BS to increase the acoustic discrimination between different seabed environments.@en

Turboprop engines are known for their high fuel efficiency on short-range missions compared to turbofan engines. A disadvantage of turboprop engines is the noise they produce. The dominant noise source of the turboprop engine is the propeller. The goal of this research is to develop a propeller source noise model which has the future goal to extend already existing noise prediction tools like the VCNS (Virtual Community Noise Simulator). In this research the Helicoidal Surface theory is coupled with two external aerodynamic tools, XFoil and XRotor, for the computation of the harmonic noise sources of the propeller. The developed tool is called the HeliX-tool. The harmonic noise sources that are implemented for the computation of the propeller noise are the steady loading noise and the thickness noise. The HeliX-tool is successfully implemented in Matlab and the tool is validated using literature data and two NLR-tools (one for the propeller aerodynamics and one for the propeller acoustics). From the validation some limitations came to light. For operating conditions that result in high local Mach numbers (>0.7 Mach), the HeliX-tool shows bad agreement with the literature data. For lower local Mach numbers the HeliX-tool shows good agreement with literature data and the NLR-tools. Additional comparisons are made using the HeliX-tool and NLR-tools for operating conditions that are not considered in the literature data. The agreement with the NLR-tools is shown by these comparisons. However, for harmonic numbers higher than 1 the difference between the HeliX-tool and NLR-tools becomes more noticeable as the harmonic decay of the HeliX-tool is larger. More research into the higher harmonic numbers can possibly improve the agreement for the higher harmonic numbers. The ultimate aim of the HeliX-tool is to be able to perform a noise simulation of a propeller. Therefore an auralization of a propeller fly-over is performed. Several propagation effects are taken into account. These are the ground reflection, spherical spreading, atmospheric absorption and the Doppler frequency shift. As a result an audible simulation of a propeller fly-over is obtained.