Identification of industrial sources of airborne heavy metal pollution in urban areas

The research examines the deposition of airborne particles which contain heavy metals and investigates the methods that can be used to identify their sources. The research focuses on lead and cadmium because these two metals are of growing public and scientific concern on environmental health grounds. The research consists of three distinct parts. The first is the development and evaluation of a new deposition measurement instrument - the deposit cannister - designed specifically for large-scale surveys in urban areas. The deposit cannister is specifically designed to be cheap, robust, and versatile and therefore to permit comprehensive high-density urban surveys. The siting policy reduces contamination from locally resuspended surface-dust. The second part of the research has involved detailed surveys of heavy metal deposition in Walsall, West Midlands, using the new high-density measurement method. The main survey, conducted over a six-week period in November - December 1982, provided 30-day samples of deposition at 250 different sites. The results have been used to examine the magnitude and spatial variability of deposition rates in the case-study area, and to evaluate the performance of the measurement method. The third part of the research has been to conduct a 'source-identification' exercise. The methods used have been Receptor Models - Factor Analysis and Cluster Analysis - and a predictive source-based deposition model. The results indicate that there are six main source processes contributing to deposition of metals in the Walsall area: coal combustion, vehicle emissions, ironfounding, copper refining and two general industrial/urban processes. |A source-based deposition model has been calibrated using facctorscores for one source factor as the dependent variable, rather than metal deposition rates, thus avoiding problems traditionally encountered in calibrating models in complex multi-source areas. Empirical evidence supports the hypothesised associatlon of this factor with emissions of metals from the ironfoundry industry.

Geometric spectral accuracy of airborne remote sensing

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A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^

Airborne laser quantification of Florida shoreline and beach volume change caused by hurricanes

This dissertation combines three separate studies that measure coastal change using airborne laser data. The initial study develops a method for measuring subaerial and subaqueous volume change incrementally alongshore, and compares those measurements to shoreline change in order to quantify their relationship in Palm Beach County, Florida. A poor correlation (R2 = 0.39) was found between shoreline and volume change before the hurricane season in the northern section of Palm Beach County because of beach nourishment and inlet dynamics. However, a relatively high R2 value of 0.78 in the southern section of Palm Beach County was found due to little disturbance from tidal inlets and coastal engineering projects. The shoreline and volume change caused by the 2004 hurricane season was poorly correlated with R 2 values of 0.02 and 0.42 for the north and south sections, respectively. The second study uses airborne laser data to investigate if there is a significant relationship between shoreline migration before and after Hurricane Ivan near Panama City, Florida. In addition, the relationship between shoreline change and subaerial volume was quantified and a new method for quantifying subaqueous sediment change was developed. No significant spatial relationship was found between shoreline migration before and after the hurricane. Utilization of a single coefficient to represent all relationships between shoreline and subaerial volume change was found to be problematic due to the spatial variability in the linear relationship. Differences in bathymetric data show only a small portion of sediment was transported beyond the active zone and most sediment remained within the active zone despite the occurrence of a hurricane. The third study uses airborne laser bathymetry to measure the offshore limit of change, and compares that location with calculated depth of closures and subaqueous geomorphology. There appears to be strong geologic control of the depth of closure in Broward and Miami-Dade Counties. North of Hillsboro Inlet, hydrodynamics control the geomorphology which in turn indicates the location of the depth of closure.

Airborne Laser Quantification of Florida Shoreline and Beach Volume Change Caused by Hurricanes

This dissertation combines three separate studies that measure coastal change using airborne laser data. The initial study develops a method for measuring subaerial and subaqueous volume change incrementally alongshore, and compares those measurements to shoreline change in order to quantify their relationship in Palm Beach County, Florida. A poor correlation (R2 = 0.39) was found between shoreline and volume change before the hurricane season in the northern section of Palm Beach County because of beach nourishment and inlet dynamics. However, a relatively high R2 value of 0.78 in the southern section of Palm Beach County was found due to little disturbance from tidal inlets and coastal engineering projects. The shoreline and volume change caused by the 2004 hurricane season was poorly correlated with R2 values of 0.02 and 0.42 for the north and south sections, respectively. The second study uses airborne laser data to investigate if there is a significant relationship between shoreline migration before and after Hurricane Ivan near Panama City, Florida. In addition, the relationship between shoreline change and subaerial volume was quantified and a new method for quantifying subaqueous sediment change was developed. No significant spatial relationship was found between shoreline migration before and after the hurricane. Utilization of a single coefficient to represent all relationships between shoreline and subaerial volume change was found to be problematic due to the spatial variability in the linear relationship. Differences in bathymetric data show only a small portion of sediment was transported beyond the active zone and most sediment remained within the active zone despite the occurrence of a hurricane. The third study uses airborne laser bathymetry to measure the offshore limit of change, and compares that location with calculated depth of closures and subaqueous geomorphology. There appears to be strong geologic control of the depth of closure in Broward and Miami-Dade Counties. North of Hillsboro Inlet, hydrodynamics control the geomorphology which in turn indicates the location of the depth of closure.

Surface elevation and ice thickness measurements of an airborne radar survey made in the Sør Rondane Mountains, Antarctica

We present surface elevations and ice thicknesses along an airborne radar survey made in Eastern Dronning Maud Land. The survey was carried out above 4 major outlet glaciers which flows around Sør Rondane Mountains with AWI's radar mounted on Polar 5 plane. The data were collected between the 21st and the 23th of January 2011. A full description of the data can be found in Callens et al. (see further detatils).

Airborne Laser Scanning and the Archaeological Interpretation of Ireland’s First World War Landscape”:The Case Study of Randalstown Training Camp

The training of Irish soldiers for service in the British Army during the First World War required the establishment of training camps across the island, such as at Shane’s Castle Estate, close to Randalstown in County Antrim, Northern Ireland. The camp saw active use from 1914 to 1918 but after the war it was demilitarised and returned to use as farmland. Archaeological investigations have revealed that earthwork traces of the camp can still be identified in the modern landscape. Comparison of a map of the camp from 1915, Airborne Laser Scanning data and aerial photographs has enabled the footprint of the camp to be re-established, while also helping to identify the location of specific elements such as the remains of barrack huts, stores, mess halls and officers’ quarters.

Grain size, morphometry and mineralogy of airborne input in the Canary basin: evidence of iron particle retention in the mixed layer

[EN]Aeolian dust plays an important role in climate and ocean processes. Particularly, Saharan dust deposition is of importance in the Canary Current due to its content of iron minerals, which are fertilizers of the ocean. In this work, dust particles are characterized mainly by granulometry, morphometry and mineralogy, using image processing and scanning northern Mauritania and the Western Sahara. The concentration of terrigenous material was measured in three environments: the atmosphere (300 m above sea level), the mixed layer at 10 m depth, and 150 m depth. Samples were collected before and during the dust events, thus allowing the effect of Saharan dust inputs in the water column to be assessed. The dominant grain size was coarse silt

Grain size, morphometry and mineralogy of airborne input in the Canary basin: evidence of iron particle retention in the mixed layer

[EN] Aeolian dust plays an important role in climate and ocean processes. Particularly, Saharan dust deposition is of importance in the Canary Current due to its content of iron minerals, which are fertilizers of the ocean. In this work, dust particles are characterized mainly by granulometry, morphometry and mineralogy, using image processing and scanning northern Mauritania and the Western Sahara. The concentration of terrigenous material was measured in three environments: the atmosphere (300 m above sea level), the mixed layer at 10 m depth, and 150 m depth. Samples were collected before and during the dust events, thus allowing the effect of Saharan dust inputs in the water column to be assessed.

Spatial and Temporal Variations in Airborne Ambrosia Pollen in Europe

Aim: The European Commission Cooperation in Science and Technology (COST) Action FA1203 “SMARTER” aims to make recommendations for the sustainable management of Ambrosia across Europe and for monitoring its efficiency and cost effectiveness. The goal of the present study is to provide a baseline for spatial and temporal variations in airborne Ambrosia pollen in Europe that can be used for the management and evaluation of this noxious plant . Location: The full range of Ambrosia artemisiifolia L. distribution over Europe (39oN-60oN; 2oW-45oE). Methods: Airborne Ambrosia pollen data for the principal flowering period of Ambrosia (August-September) recorded during a 10-year period (2004-2013) were obtained from 242 monitoring sites. The mean sum of daily average airborne Ambrosia pollen and the number of days that Ambrosia pollen was recorded in the air were analysed. The mean and Standard Deviation (SD) were calculated regardless of the number of years included in the study period, while trends are based on those time series with 8 or more years of data. Trends were considered significant at p < 0.05. Results: There were few significant trends in the magnitude and frequency of atmospheric Ambrosia pollen (only 8% for the mean sum of daily average Ambrosia pollen concentrations and 14% for the mean number of days Ambrosia pollen was recorded in the air). Main conclusions: The direction of any trends varied locally and reflect changes in sources of the pollen, either in size or in distance from the monitoring station. Pollen monitoring is important for providing an early warning of the expansion of this invasive and noxious plant.

Airborne remote sensing of ocean wave directional wavenumber spectra in the marginal ice zone

Interactions between surface waves and sea ice are thought to be an important, but poorly understood, physical process in the atmosphere-ice-ocean system. In this work, airborne scanning lidar was used to observe ocean waves propagating into the marginal ice zone (MIZ). These represent the first direct spatial measurements of the surface wave field in the polar MIZ. Data were compared against two attenuation models, one based on viscous dissipation and one based on scattering. Both models were capable of reproducing the measured wave energy. The observed wavenumber dependence of attenuation was found to be consistent with viscous processes, while the spectral spreading of higher wavenumbers suggested a scattering mechanism. Both models reproduced a change in peak direction due to preferential directional filtering. Floe sizes were recorded using co-located visible imagery, and their distribution was found to be consistent with ice breakup by the wave field.

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.