Land use regression (LUR) models have been widely used in epidemiological studies and risk assessments related to air pollution. Although efforts have been made to improve the performance of LUR models so that they capture the spatial heterogeneity of fine particulate matter (PM₂.₅) in high-density cities, few studies have revealed the vertical differences in PM₂.₅ exposure. This study proposes a three-dimensional LUR (3-D LUR) assessment framework for PM₂.₅ exposure that combines a high-resolution LUR model with a vertical PM₂.₅ variation model to investigate the results of horizontal and vertical mobile PM₂.₅ monitoring campaigns. High-resolution LUR models that were developed independently for daytime and nighttime were found to explain 51% and 60% of the PM₂.₅ variation, respectively. Vertical measurements of PM₂.₅ from three regions were first parameterized to produce a coefficient of variation for the concentration (CVC) to define the rate at which PM₂.₅ changes at a certain height relative to the ground. The vertical variation model for PM₂.₅ was developed based on a spline smoothing function in a generalized additive model (GAM) framework with an adjusted R² of 0.91 and explained 92.8% of the variance. PM₂.₅ exposure levels for the population in the study area were estimated based on both the LUR models and the 3-D LUR framework. The 3-D LUR framework was found to improve the accuracy of exposure estimation in the vertical direction by avoiding exposure estimation errors of up to 5%. Although the 3-D LUR-based assessment did not indicate significant variation in estimates of premature mortality that could be attributed to PM₂.₅, exposure to this pollutant was found to differ in the vertical direction. The 3-D LUR framework has the potential to provide accurate exposure estimates for use in future epidemiological studies and health risk assessments.

Beach litter assessments rely on time inefficient and high human cost protocols, mining the attainment of global beach litter estimates. Here we show the application of an emerging technique, the use of drones for acquisition of high-resolution beach images coupled with machine learning for their automatic processing, aimed at achieving the first national-scale beach litter survey completed by only one operator. The aerial survey had a time efficiency of 570 ± 40 m² min⁻¹ and the machine learning reached a mean (±SE) detection sensitivity of 59 ± 3% with high resolution images. The resulting mean (±SE) litter density on Saudi Arabian shores of the Red Sea is of 0.12 ± 0.02 litter items m⁻², distributed independently of the population density in the area around the sampling station. Instead, accumulation of litter depended on the exposure of the beach to the prevailing wind and litter composition differed between islands and the main shore, where recreational activities are the major source of anthropogenic debris.

Unmanned aerial vehicles can collect high-resolution and real-time photos while emitting fewer greenhouse gases than ordinary airplanes and therefore are considered economic and environmentally friendly platforms. However, quantitative analyses of the sustainability of using unmanned aerial vehicles for aerial photography based on their performance and technical constraints compared to that of airplanes are lacking. The purpose of this study is to analyze the economically and environmentally appropriate monitoring coverage of unmanned aerial vehicle photogrammetry according to wing type (such as fixed-wing and rotary-wing types) and desired image resolution (such as 5 cm/pix and 20 cm/pix for the ground sample distance). To determine the sustainable monitoring coverage, the total photogrammetry costs must include the social cost to reduce the emitted greenhouse gases during operation, resulting in a feedback relation. As a result, the sustainable monitoring coverage of fixed-wing unmanned aerial vehicles should be less than 27.50 km² when the resolution is 5 cm/pix and 30.64 km² when the resolution is 20 cm/pix. Rotary-wing unmanned aerial vehicles are sustainable when their monitoring coverage is less than 23.98 km² at a resolution of 5 cm/pix and 26.75 km² at a resolution of 20 cm/pix. These results provide information on the number of unmanned aerial vehicles and the standing unmanned aerial vehicle deployment plans required to monitor the survey area.

The clean-up effort that is occurring across the region affected by the 2011 Fukushima Daiichi Nuclear Power Plant accident is unprecedented in its magnitude as well as the financial cost that will eventually result. A major component of this remediation is the stripping of large volumes of material from the land surface, depositing this into large waste storage bags before placing these 1 cubic meter bags into specially constructed stores across Fukushima Prefecture.In this work, using an unmanned aerial vehicle to perform radiological surveys of a site, the time-resolved distribution of contamination during the construction of one of these waste storage sites was assessed. The results indicated that radioactive material was progressively leaching from the store into the surrounding environment. A subsequent survey of the site conducted eight months later revealed that in response to this survey and remedial actions, the contamination issue once existing on this site had been successfully resolved. Such results highlight the potential of low-altitude unmanned aerial systems to easily and rapidly assess site-wide changes over time – providing highly-visual results; therefore, permitting for prompt remedial actions to be undertaken as required.Use of UAV radiation mapping and airborne photogrammetry to produce a time-resolved assessment of remediation efforts within a Fukushima temporary storage facility.

Potential utilities of instrumented lightweight unmanned aerial vehicles (UAVs) to quickly characterize tropospheric ozone pollution and meteorological factors including air temperature and relative humidity at three-dimensional scales are highlighted in this study. Both vertical and horizontal variations of ozone within the 1000 m lower troposphere at a local area of 4 × 4 km² are investigated during summer and autumn times. Results from field measurements show that the UAV platform has a sufficient reliability and precision in capturing spatiotemporal variations of ozone and meteorological factors. The results also reveal that ozone vertical variation is mainly linked to the vertical distribution patterns of air temperature and the horizontal transport of air masses from other regions. In addition, significant horizontal variations of ozone are also observed at different levels. Without major exhaust sources, ozone horizontal variation has a strong correlation with the vertical convection intensity of air masses within the lower troposphere. Higher air temperatures are usually related to lower ozone horizontal variations at the localized area, whereas underlying surface diversity has a week influence. Three-dimensional ozone maps are obtained using an interpolation method based on UAV collected samples, which are capable of clearly demonstrating the diurnal evolution processes of ozone within the 1000 m lower troposphere.

Unmanned aerial vehicles (UAVs) offer new opportunities to monitor pollution and provide valuable information to support remediation. Their low-cost, ease of use, and rapid deployment capability make them ideal for environmental emergency response. Here we present a UAV-based study of the third largest coal ash spill in the United States. Coal ash from coal combustion is a toxic industrial waste material present worldwide. Typically stored in settling ponds in close proximity to waterways, coal ash poses significant risk to the environment and drinking water supplies from both chronic contamination of surface and ground water and catastrophic pond failure. We sought to provide an independent estimate of the volume of coal ash and contaminated water lost during the rupture of the primary coal ash pond at the Dan River Steam Station in Eden, NC, USA and to demonstrate the feasibility of using UAVs to rapidly respond to and measure the volume of spills from ponds or containers that are open to the air. Using structure-from-motion (SfM) imagery analysis techniques, we reconstructed the 3D structure of the pond bottom after the spill, used historical imagery to estimate the pre-spill waterline, and calculated the volume of material lost. We estimated a loss of 66,245 ± 5678 m3 of ash and contaminated water. The technique used here allows rapid response to environmental emergencies and quantification of their impacts at low cost, and these capabilities will make UAVs a central tool in environmental planning, monitoring, and disaster response.

The effects of dike construction on the geomorphology and sedimentary processes of tidal flats were investigated using high-precision topographic profiling, short cores, and unmanned aviation vehicle (UAV)-assisted photogrammetry to understand their adverse consequences on the benthic ecosystem. Tidal flats at the south of Shinsi Island near one of the two sluice gates of the Saemangeum dike, display prominent morphologic features known as shelly sand ridges or cheniers (sensu Otvos, 2000) that have migrated landward about 5 m in a year. The tidal flats were dominated by erosion from winter to spring and by deposition during the remainder of the year except for the periods of heavy precipitation when tidal drainage channels became larger and deeper by headward erosion. With overall coarser-grained surface sediments, the presence of actively migrating wave-built cheniers are in stark contrast to muddy tidal flats with a monotonous morphology before the completion of the Saemangeum dike in 2006. Southeasterly waves reflected from the dike during winter to spring when north to northwesterly winds prevail account for the wave-induced onshore sediment transport and rapid morphologic changes in the tidal flats despite their location protected from offshore waves. The diversity and biomass of major macrofauna species tend to increase during rapid erosion and decrease during rapid deposition, highlighting the anthropogenic effect of dike-induced physical disturbance on the benthic ecosystem in the otherwise sheltered tidal flats.

The automatic identification (location, segmentation, and classification) by UAV- based optical imaging of spills of transparent floating Hazardous and Noxious Substances (HNS) benefits the on-site response to spill incidents, but it is also challenging. With a focus on the on-site optical imaging of HNS, this study explores the potential of single spectral imaging for HNS identification using the Faster R-CNN architecture. Images at 365 nm (narrow UV band), blue channel images (visible broadband of ∼400–600 nm), and RGB images of typical HNS (benzene, xylene, and palm oil) in different scenarios were studied with and without Faster R-CNN. Faster R-CNN was applied to locate and classify the HNS spills. The segmentation using Faster R-CNN-based methods and the original masking methods, including Otsu, Max entropy, and the local fuzzy thresholding method (LFTM), were investigated to explore the optimal wavelength and corresponding image processing method for the optical imaging of HNS. We also compared the classification and segmentation results of this study with our previously published studies on multispectral and whole spectral images. The results demonstrated that single spectral UV imaging at 365 nm combined with Faster R-CNN has great potential for the automatic identification of transparent HNS floating on the surface of the water. RGB images and images using Faster R-CNN in the blue channel are capable of HNS segmentation.

This study developed a lightweight air composition measuring equipment (ACME) mounted in unmanned aerial vehicles (UAVs) to measure the vertical distribution characteristics of PM₂.₅ chemical species in the micro-scale urban environment for the first time. 212 samples collected from 0 to 350 m above ground level were analyzed for water-soluble ions. The concentrations of most ions on the above ground level were higher than that on the ground surface during the sampling period. The measurements of the total ion concentrations were approximately 54 to 26% of the PM₂.₅ mass concentrations on the ground surface. The concentrations of NH₄⁺ and NO₃⁻ decreased with increases in the height from the ground, which may be related to the influence of the vehicle emissions and human activities. NO₂⁻ and SO₄²⁻ both had a peak concentration on the higher vertical altitude at night in the sea-land wind system. In the southern wind system, the emissions of sea salts, dust, and stationary pollution, might be transported by the regional prevailing airflow from the southern coastal area, were the major pollutant sources above the boundary layer. The vertical distribution of ionic concentrations and wind field provided information concerning changes in pollutant transport and source regions that affect the local air quality. The ACME mounted in UAVs is the feasible and convenient method to fast understand the vertical distributions of aerosol chemical species. It provides important information about the accumulation and diffusion effects by the boundary layer variation to aerosol characteristics, which is difficulty observed from the conventional ground-based measurements. In future, this technology is the useful application for investigating the pollutant species emitted from the smokestack and the sudden pollution accident.

Airborne systems such as lightweight and highly portable unmanned aerial vehicles (UAVs) are becoming increasingly widespread in both academia and industry - with an ever-increasing range of applications, including (but not limited to), air quality sampling, wildlife monitoring and land-use mapping.In this work, high-resolution airborne photogrammetry obtained using a multi-rotor system operating at low survey altitudes, is combined with ground-based radiation mapping data acquired at an interim storage facility for wastes removed as part of the large-scale Fukushima clean-up program. The investigation aimed to assess the extent to which the remediation program at a specific site has contained the stored contaminants, as well as present a new methodology for rapidly surveying radiological sites globally. From the three-dimensional rendering of the site of interest, it was possible to not only generate a powerful graphic confirming the elevated radiological intensity existing at the location of the waste bags, but also to also illustrate the downslope movement of contamination due to species leakage from the large 1m³ storage bags. The entire survey took less than 1 h to perform, and was subsequently post-processed using graphical information software to obtain the renderings. The conclusions within this study not only highlight the usefulness of incorporating three-dimensional renderings within radiation mapping protocols, but also conclude that current methods of monitoring these storage facilities in the long term could be improved through the integration of UAVs within the standard protocol.