Determination of the vertical profile of particle number concentration adjacent to a motorway using an unmanned aerial vehicle

Measurement of the vertical distributions of atmospheric pollutants using an uncrewed aerial vehicle platform in Xi'an, China

Vertical observations of atmospheric pollutants play crucial roles in a comprehensive understanding of the distribution characteristics and transport of atmospheric pollutants. A hexacopter uncrewed aerial vehicle equipped with miniature monitors was employed to measure the vertical distribution of atmospheric pollutants within a height of 1000 m at a rural site in Xi'an, China, in 2021. The concentrations of carbon monoxide (CO) and particulate matter (PM) showed generally decreasing trends with increasing height. The ozone (O3) concentration showed a general increasing trend with height followed by a gradual decreasing trend. Vertical decrements of PM2.5 and CO from 0 to 1000 m were significantly (p < 0.05) lower on observation days during summer (14.0 ± 8.1 μg m-3 and 8.7 ± 6.6 ppb, respectively), compared with those in winter (78.3 ± 14.1 μg m-3 and 34.8 ± 17.3 ppb, respectively). The horizontal transport of PM and CO mostly occurred in the morning and at night during winter observations at an altitude of 400-500 m. During the winter haze, the PM and CO profile concentrations below 500 m increased substantially with the decrease in the height of the thermal inversion layer. Vertical O3 transportation was observed in the afternoon and evening during summer, and a ∼37.7% (11.6 ppb) increase in ground-level O3 was observed in relation to vertical transport from the upper atmosphere. The results provide insights into the vertical distribution and transport of atmospheric pollutants in rural areas near cities.

Mitigating air and noise pollution through highway capping: The Bundang-Suseo Highway Cap Project case study

Highways, while vital for transportation, often lead to heightened air and noise pollution, adversely affecting nearby communities. This study delves into the effectiveness of highway capping, a sustainable urban development strategy, in addressing these environmental challenges, with a specific focus on the Bundang-Suseo Highway in South Korea. This study employed a multifaceted approach, incorporating on-road monitoring, in situ measurements, and vertical assessments using UAVs. Following the cap's installation, the area experienced more stable pollutant levels, marking a notable shift from the previously fluctuating conditions heavily influenced by the highway. In-depth in situ monitoring near the cap revealed significant reductions in noise and pollutants like UFP and BC. Furthermore, UAV monitoring captured these changes in pollutant levels at different altitudes. Notably, the installation of the highway cap led to increased PM2.5, PM10, and NO2 levels at ground level, but a decrease above the cap, emphasizing the critical importance of intentional highway cap design in enhancing urban air quality and reducing exposure to harmful pollutants. This research yields invaluable insights for urban planners, health authorities, and policymakers, aiding the precise identification of pollution-prone areas and advocating for improved highway cap design to enhance urban environments.

Characterizing nighttime vertical profiles of atmospheric particulate matter and ozone in a megacity of south China using unmanned aerial vehicle measurements

Daytime atmospheric pollution has received wide attention, while the vertical structures of atmospheric pollutants at night play a crucial role in the photochemical process on the following day, which is still less reported. Focusing on Guangzhou, a megacity of South China, we established an unmanned aerial vehicle (UAV) equipped with micro detectors to collect consecutive high-resolution samples of fine particle (PM2.5), submicron particle (PM1.0), black carbon (BC) and ozone (O3) concentrations in the atmosphere, as well as the air temperature (AT) and relative humidity (RH) within a 500 m altitude during nighttime from Oct. 24th to Nov. 6th, 2018. The measurements showed that PM2.5, PM1.0, and BC decreased with altitude and were influenced by the nighttime shallow planetary boundary layer (PBL) where BC was more accumulated and fluctuated. In contrast, O3 was positively correlated with altitude. Backward trajectory clustering and Pasquill stability classification showed that advection and convection significantly influenced the vertical distribution of all pollutants, particularly particulate matter. External air masses carrying high concentrations of pollutants increased PM1.0 and PM2.5 levels by 145% and 455%, respectively, compared to unaffected periods. The ratio of BC to PM2.5 indicated that local emissions had a minor role in nighttime particulate matter. Vertical transport caused by atmospheric instability reduced the differences in pollutant concentrations at various heights. Geodetector and generalized additive model showed that RH and BC accumulation in the PBL were significant factors influencing vertical changes of the secondary aerosol intensity as indicated by the ratio of PM1.0 to PM2.5. The joint explanation of RH and atmospheric stability with other variables such as BC is essential to understand the generation of secondary aerosols. These findings provide insights into regional and local measures to prevent and control night-time particulate matter pollution.

AirQuality Lab-on-a-Drone: A Low-Cost 3D-Printed Analytical IoT Platform for Vertical Monitoring of Gaseous H2S

The measurement of gaseous compounds in the atmosphere is a multichallenging task due to their low concentration range, long and latitudinal concentration variations, and the presence of sample interferents. Herein, we present a quadcopter drone deployed with a fully integrated 3D-printed analytical laboratory for H2S monitoring. Also, the analytical system makes part of the Internet of Things approach. The analytical method applied was based on the reaction between fluorescein mercuric acetate and H2S that led to fluorescence quenching. A 5 V micropump at a constant airflow of 50 mL min-1 was employed to deliver constant air into a flask containing 800 μL of the reagent. The analytical signal was obtained using a light-emitting diode and a miniaturized digital light detector. The method enabled the detection of H2S in the range from 15 to 200 ppbv, with a reproducibility of 5% for a sampling time of 10 min and an limit of detection of 9 ppbv. All devices were controlled using an Arduino powered by a small power bank, and the results were transmitted to a smartphone via Bluetooth. The proposed device resulted in a weight of 300 g and an overall cost of ∼50 USD. The platform was used to monitor the concentration of H2S in different intervals next to a wastewater treatment plant at ground and vertical levels. The ability to perform all analytical steps in the same device, the low-energy requirements, the low weight, and the attachment of data transmission modules offer new possibilities for drone-based analytical systems for air pollution monitoring.

Multidimensional spatial monitoring of open pit mine dust dispersion by unmanned aerial vehicle

Dust pollution is one of the most severe environmental issues in open pit mines, hindering green mining development. Open pit mine dust has characteristics of multiple dust-generating points, is irregular, influenced by climatic conditions, and has a high degree of distribution with a wide dispersion range in three dimensions. Consequently, evaluating the quantity of dust dispersion and controlling environmental pollution are crucial for supporting green mining. In this paper, dust monitoring above the open pit mine was carried out with an unmanned aerial vehicle (UAV) on board. The dust distribution patterns above the open pit mine were studied in different vertical and horizontal directions at different heights. The results show that the temperature changes less in the morning and more at noon in winter. At the same time, the isothermal layer becomes thinner and thinner as the temperature rises, which makes it easy for dust to spread. The horizontal dust is mainly concentrated at 1300 and 1550 elevations. The dust concentration is polarized at 1350-1450 elevation. The most serious exceedance is at 1400 elevation, with TSP (the concentration of total suspended particulate), PM10 (particulates with aerodynamic diameter < 10 μm), and PM2.5 (particulates with aerodynamic diameter < 2.5 μm) accounting for 188.8%, 139.5%, and 113.8%, respectively. The height is 1350-1450 elevation. Dust monitoring technology carried out by UAV can be applied to the study of dust distribution in the mining field, and the research results can provide reference for other open pit mines. It can also provide a basis for law enforcement part to carry out law enforcement, which has expanded and wide practical application value.

Vertical variation of atmospheric particulate matter under different pollution levels in the suburbs of Tianjin based on unmanned aerial vehicle

An unmanned aerial vehicle equipped with an isokinetic sampling device and a portable aerosol particle size spectrometer was used to detect atmospheric particles at different altitudes in the suburbs of Tianjin. In January 2017, four flight tests under different air conditions were conducted, and the Severe polluted and Excellent levels were classified according to the air quality index of the State-controlled site. Changes in mass concentration with altitude, and the vertical distribution of mass concentration and number concentration spectrum were analyzed. Results showed that under the Severe polluted condition, the concentration of particulate matter (PM) decreased significantly within 200 m, and became stable above 400 m. Two peaks at 260 m and 400 m were observed - they were attributed to local emissions and transportation of nearby areas. When the mass concentration significantly increased, the greatest contributor was particles with a size of 15-30 μm. As altitude increased, PM with the size of less than 1 μm accounted for the largest proportion. Regarding number concentration, the main particle size was less than 0.35 μm. Under the Excellent condition, particles less than 0.35 μm in size were the most important components in mass and number concentrations. Correlation analysis of meteorological factors and backward trajectory indicated that pollution was caused by particle concentration transport in several provinces and the particle accumulation due to temperature inversion.Implications: Study on the vertical structure of air pollutants was very important for understanding the occurrence and development of regional heavy pollution. Unmanned aerial vehicles (UAVs) was an efficient method for its easy operation, good stability, high flexibility and safety, and was introduced to observe the vertical distribution characteristics of particle concentration under different weather conditions. This study provided the number concentration spectra and the mass concentration spectra at different height, and would give some support for the precise control of air pollution.

Evaluation of vertical and horizontal distribution of particulate matter near an urban roadway using an unmanned aerial vehicle

Measurement of traffic emissions has gained a lot of interest in recent times due to its contribution to urban pollution. This paper reports the outcome from an unmanned aerial vehicle (UAV) based measurement of PM concentration near an urban roadway at Kolkata, India. A total of 54 flights were carried out for simultaneous measurements of PM₁, PM_2.5 and PM₁₀ mass concentration and meteorological parameters in vertical as well as in horizontal direction. Results for the vertical flight up to 100 m showed that the PM₁, PM_2.5 and PM₁₀ concentrations at higher altitudes are less (mean; 24.6, 39.9 and 103.8 μg m^-3) compared to the respective ground level concentrations (mean; 26.3, 50.4 and 201.9 μg m^-3). For all the three particle sizes, the majority of the cases of higher PM concentration at higher altitudes happened during the evening flight. Low mixing height and low wind speed are suggested to be the reasons for the poor dispersion of pollutants in the evening. While there was a 7-10% fall of fine particles (PM₁ and PM_2.5) mass concentrations up to 90 m away from the road, no trend could be seen for PM₁₀. The random forest model to predict the UAV/Ground concentration ratio showed high accuracy (R² = 0.82-0.95) for all three particle sizes. This is an important finding from this study, which shows how UAV measurement data can be used to generate models that can predict the higher altitude concentrations from the ground based measurements.

Direct Measuring Particulate Matters in Smoke Plumes from Chimneys in a Textile Dyeing Industrial Park by a Self-Developed PM Detector on an UAV in Yangtze River Delta of China

Directly measuring particulate matters (PM) from chimneys in an industrial park is difficult due to it being hard to reach the peak heights. A self-developed PM detector on an unmanned aerial vehicle (UAV) had been deployed to directly measure the PM emissions in smoke plumes from chimneys in a textile dyeing industrial park. Compared with a commercial PM device (LD-5R, SIBATA, Kyoto, Japan), the self-developed detector showed similar performance with a good correlation (R2 varying from 0.911 to 0.951) in simultaneously vertical PM measurements on UAV. The PM emissions from chimneys after different textile treating processes, including pigment printing, dyeing process, and digital printing, were investigated. PM mass concentrations and particle number concentrations (PNC) in different sizes were found to be significantly higher in pigment printing than those in dyeing process and digital printing by 2 or 3 times after electrostatic precipitation. The activated carbon adsorption and electrostatic precipitation were the major PM controlling techniques in the park. The PM mass concentrations and PNC were the highest in the process of dyeing after activated carbon adsorption with the concentrations of PM1 (1000 μg·m-3), PM2.5 (1600 μg·m-3), and PM10 (2000 μg·m-3), respectively. According to the results of PM and PNC, PM2.5 was found to be the dominant particles accounting for 99% of the PM emissions. It may be due to the high temperature in thermo-fixing machine, which is beneficial to the PM2.5 generation. This study revealed PM2.5 was the dominant particles to be reduced in textile dyeing enterprises to mitigate PM pollution.

Concept of Using an Unmanned Aerial Vehicle (UAV) for 3D Investigation of Air Quality in the Atmosphere—Example of Measurements near a Roadside

A substantial amount of air pollution is emitted from urban sources. Hence, investigating air pollutant dispersion from urban sources is of great importance. The mechanisms influencing air pollutant dispersion also need to be studied thoroughly. Unmanned Aerial Vehicle (UAV)-based systems offer great potential for mobile exploration of air pollutants in the lower atmosphere due to the high maneuverability of multi-rotor UAVs. The aim of this study was to develop an effective UAV system that can perform high-resolution three-dimensional profiling of pollutants, such as particulate matter (PM), ultrafine particles (UFP), black carbon (BC), as well as meteorological parameters, including air temperature, relative humidity, pressure, wind speed, and wind direction. Different experiments were performed to finalize the positioning of the instruments on the UAV platform so as not to destabilize the drone during flight, even when the wind speed is high and during turbulent flight conditions. Another very crucial question is where to place the air inlet of the measurement devices. In addition, field tests were conducted to evaluate the stability of the UAV platform and the in-flight performance of the sensors. This UAV platform was deployed to perform vertical profiles at the University campus in Stuttgart-Vaihingen and in an area near the campus, close to the federal highway B14. The measurement campaign was performed on three days in February 2021, with a maximum flight height of 120 m above ground. The vertical profiles showed that concentrations were higher on the ground due to the proximity to the source and that high wind speeds assisted pollutant dispersion. The horizontal profiles showed that the pollutant concentrations were higher at the roadside and decreased with increasing distance from the road. In conclusion, this UAV platform represented a low-cost, practical, and reliable method for studying the three-dimensional distribution of pollutants near the source.

Urban Traffic Monitoring and Analysis Using Unmanned Aerial Vehicles (UAVs): A Systematic Literature Review

Unmanned aerial vehicles (UAVs) are gaining considerable interest in transportation engineering in order to monitor and analyze traffic. This systematic review surveys the scientific contributions in the application of UAVs for civil engineering, especially those related to traffic monitoring. Following the PRISMA framework, 34 papers were identified in five scientific databases. First, this paper introduces previous works in this field. In addition, the selected papers were analyzed, and some conclusions were drawn to complement the findings. It can be stated that this is still a field in its infancy and that progress in advanced image processing techniques and technologies used in the construction of UAVs will lead to an explosion in the number of applications, which will result in increased benefits for society, reducing unpleasant situations, such as congestion and collisions in major urban centers of the world.

Ultra-Light Airborne Measurement System for Investigation of Urban Boundary Layer Dynamics

Winter smog episodes are a severe problem in many cities around the world. The following two mechanisms are responsible for influencing the level of pollutant concentrations: emission of pollutants from different sources and associated processes leading to formation of secondary aerosols in the atmosphere and meteorology, including advection, which is stimulated by horizontal wind, and convection, which depends on vertical air mass movements associated with boundary layer stability that are determined by vertical temperature and humidity gradients. The aim of the present study was to evaluate the performance of an unmanned aerial vehicle (UAV)-based measurement system developed for investigation of urban boundary layer dynamics. The evaluation was done by comparing the results of temperature, relative humidity, wind speed and particulate matter fraction with aerodynamic diameter below 10 μm (PM₁₀) concentration vertical profiles obtained using this system with two reference meteorological stations: Jagiellonian University Campus (JUC) and radio transmission tower (RTCN), located in the urban area of Krakow city, Southern Poland. The secondary aim of the study was to optimize data processing algorithms improving the response time of UAV sensor measurements during the ascent and descent parts of the flight mission.

Vertical Structures of Meteorological Elements and Black Carbon at Mt. Tianshan Using an Unmanned Aerial Vehicle System

As the largest independent east–west-trending mountain in the world, Mt. Tianshan exerts crucial impacts on climate and pollutant distributions in central Asia. Here, the vertical structures of meteorological elements and black carbon (BC) were first derived at Mt. Tianshan using an unmanned aerial vehicle system (UAVS). Vertical changes in meteorological elements can directly affect the structure of the planet boundary layer (PBL). As such, the influences of topography and meteorological elements’ vertical structure on aerosol distributions were explored from observations and model simulations. The mass concentrations of BC changed slightly with the increasing height below 2300 m above sea level (a.s.l.), which significantly increased with the height between 2300–3500 m a.s.l. and contrarily decreased with ascending altitude higher than 3500 m. Topography and mountain–valley winds were found to play important roles in the distributions of aerosols and BC. The prevailing valley winds in the daytime were conducive to pollutant transport from surrounding cities to Mt. Tianshan, where the aerosol number concentration and BC mass concentration increased rapidly, whereas the opposite transport pattern dominated during nighttime.

In Situ, Rotor-Based Drone Measurement of Wind Vector and Aerosol Concentration in Volcanic Areas

Unmanned aerial vehicles (UAVs), represented by rotor-based drones, are suitable for volcanic observations owing to the advantages of mobility and safety. In this study, vertical profiles of wind and aerosol concentrations at altitudes up to 1000 m around Mt. Sakurajima, one of the most active volcanoes in Japan, were measured in situ using a drone equipped with an ultrasonic anemometer and aerosol sensor. The drone-measured wind profiles were compared with Doppler LiDAR data and analysis values derived from a meteorological model. Drone-measured vertical profiles collected at a vertical speed of 1 m·s−1 (upward and downward) showed strong agreement with the LiDAR observations, as did the averaged values of hovering drone measurements. Obvious vertical wind shear was found by the drone in the vicinity of Mt. Sakurajima. An aerosol sensor was installed on the drone with the capability to measure fine (PM2.5) and coarse particles (PM10) simultaneously; in this manner, volcanic ash and aerosol pollutants around the volcano could be distinguished. Thus, it was proven that drones could be applied to investigate wind conditions and aerosols in situ, even at dangerous locations near active volcanoes.

Post-movement stabilization time for the downwash region of a 6-rotor UAV for remote gas monitoring

Unmanned aerial vehicles (UAV) have been used to monitor gas emissions for research projects, though downwash, the airflow produced by the UAV rotors, is potentially capable of artificially altering gas concentration measurements. Anemometers, placed at ten different distances below a 6-rotor UAV, measured air speeds in the downwash region. The collected data was used in combination with UAV rotor speed data to determine the stabilization time of the downwash region after the UAV has returned to a stable hovering position. The stabilization time will determine the amount of time after UAV movement until reliable concentration readings can be obtained within the downwash region. This paper presents stabilization times after vertical upward and rotational UAV movement.

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

In this study, we have assessed the three-dimensional (3-D) spatial extent of near-road air pollution around a signalized intersection in a densely populated area using collaborating methodologies of stationary measurements, drone monitoring, and atmospheric dispersion modeling. Stationary measurement data collected in the roadside apartment building showed a substantial effect of emitted pollutants, such as nitrogen oxides (NO_x), black carbon (BC), and ultrafine particles (UFPs), especially during the morning rush hours. Vertical drone monitoring near the road intersection exhibited a steeper decreasing trend with increasing altitude for BC concentration rather than for fine particulate matter (PM_2.5) concentration below the apartment building height. Atmospheric NO_x dispersion was simulated using the weather research and forecasting (WRF) and computational fluid dynamics (CFD) models for the drone measurement periods. Based on the agreement between the measured BC and simulated NO_x concentrations, we concluded that the air pollution around the road intersection has adverse effects on the health of residents living within the 3-D spatial extent within at least 120 m horizontally and a half of building height vertically during the morning rush hours. The comparability between drone monitoring and WRF-CFD modeling can further guarantee the identification of air pollution hotspots using the methods.

Measuring Regional Atmospheric CO2 Concentrations in the Lower Troposphere with a Non-Dispersive Infrared Analyzer Mounted on a UAV, Ogata Village, Akita, Japan

We have developed a simple measuring system prototype that uses an unmanned aerial vehicle (UAV) and a non-dispersive infrared (NDIR) analyzer to detect regional carbon dioxide (CO2) concentrations and obtain vertical CO2 distributions. Here, we report CO2 measurement results for the lower troposphere above Ogata Village, Akita Prefecture, Japan (about 40° N, 140° E, approximately −1 m amsl), obtained with this UAV system. The actual flight observations were conducted at 500, 400, 300, 200, 100, and 10 m above the ground, at least once a month during the daytime from February 2018 to February 2019. The raw CO2 values from the NDIR were calibrated by two different CO2 standard gases and high-purity nitrogen (N2) gas (as a CO2 zero gas; 0 ppm). During the observation period, the maximum CO2 concentration was measured in February 2019 and the minimum in August 2018. In all seasons, CO2 concentrations became higher as the flight altitude was increased. The monthly pattern of observed CO2 changes is similar to that generally observed in the Northern Hemisphere as well as to surface CO2 changes simulated by an atmospheric transport model of the Japan Meteorological Agency. It is highly probable that these changes reflect the vegetation distribution around the study area.

Four-band Thermal Mosaicking: A New Method to Process Infrared Thermal Imagery of Urban Landscapes from UAV Flights

Unmanned aerial vehicles (UAVs) support a large array of technological applications and scientific studies due to their ability to collect high-resolution image data. The processing of UAV data requires the use of mosaicking technology, such as structure-from-motion, which combines multiple photos to form a single image mosaic and to construct a 3-D digital model of the measurement target. However, the mosaicking of thermal images is challenging due to low lens resolution and weak contrast in the single thermal band. In this study, a novel method, referred to as four-band thermal mosaicking (FTM), was developed in order to process thermal images. The method stacks the thermal band obtained by a thermal camera onto the RGB bands acquired on the same flight by an RGB camera and mosaics the four bands simultaneously. An object-based calibration method is then used to eliminate inter-band positional errors. A UAV flight over a natural park was carried out in order to test the method. The results demonstrated that with the assistance of the high-resolution RGB bands, the method enabled successful and efficient thermal mosaicking. Transect analysis revealed an inter-band accuracy of 0.39 m or 0.68 times the ground pixel size of the thermal camera. A cluster analysis validated that the thermal mosaic captured the expected contrast of thermal properties between different surfaces within the scene.

Fine-resolution mapping of particulate matter concentration in urban areas and population exposure analysis via dispersion modeling: a study in Daejeon, South Korea

To deliver accurate particulate matter information to citizens, a detailed particulate matter dispersion model including factors such as land use and meteorological information was developed and used to create particulate matter concentration distribution maps for Daejeon Metropolitan City (South Korea). The results showed differences from existing particulate matter concentration distribution maps created using established methods. For PM2.5, approximately 3600 concentration maps were constructed. Taking a map as an example, according to existing methods, the PM2.5 concentration was "good" in 56% and "moderate" in 44% of areas. However, according to our modeling, the PM2.5 concentration was good in 31%, moderate in 26%, "unhealthy" in 28%, and "very unhealthy" in 15% of areas. Furthermore, the existing methods indicated that no portion of the population was exposed to poor particulate matter concentrations, while the proposed model found that over 170,000 people were exposed to such concentrations. These results will contribute to sustainable urban and environmental planning.

Aerial drone as a carrier for miniaturized air sampling systems

The applicability of an aerial drone as a carrier for new passive and active miniaturized air sampling systems, including solid phase microextration Arrow (SPME Arrow) and in-tube extraction (ITEX), was studied in this research. Thermal desorption, gas chromatography and mass spectrometry were used for the determination of volatile organic compounds (VOCs) collected by the sampling systems. The direct comparison of the profiles of VOCs, simultaneously sampled in air by SPME Arrow system including four different coatings, allowed the elucidation of their adsorption selectivity. A more complex experimental design, involving 20 samples (10 flights) and non-supervised pattern recognition techniques, was needed for the clarification of the same sampling parameters in the case of five ITEX sorbent materials. In addition, ITEX sampling accessories, such as particle, water and ozone traps, were evaluated by comparing the results obtained for air samples simultaneously collected by two ITEX systems, packed with the same sorbent and furnished or not with sampling accessories. The effect of the aerial drone horizontal displacement (HD) on the sampling efficiency was clear in the case of SPME Arrow. The number of detected compounds and their relative peak area values (RPA) revealed a clear increase (4 and 43%, respectively) in comparison with samples collected without drone HD. However, just minor differences were observed in the case of ITEX (2 compounds and 9% of the ∑RPA). In addition, the system was able to provide almost simultaneous passive (SPME Arrow) and active (ITEX) samplings at different altitudes (5 and 50 m), being a good tool for low cost vertical profiling studies (∑RPA decreased over 35% for the samples collected at 50 m). Finally, the successful simultaneous air sampling by SPME Arrow and ITEX systems in two difficult access places, such as boreal forest and wetlands, was demonstrated, resulting in 21 and 31 detected compounds in forest and wetlands by SPME Arrow, and 27 and 39 compounds by ITEX.

Determination of the vertical profile of aerosol chemical species in the microscale urban environment

This study developed a lightweight air composition measuring equipment (ACME) mounted in unmanned aerial vehicles (UAVs) to measure the vertical distribution characteristics of PM_2.5 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 PM_2.5 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 SO₄^2- 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.

Vertical profiles of lung deposited surface area concentration of particulate matter measured with a drone in a street canyon

The vertical profiles of lung deposited surface area (LDSA) concentration were measured in an urban street canyon in Helsinki, Finland, by using an unmanned aerial system (UAS) as a moving measurement platform. The street canyon can be classified as an avenue canyon with an aspect ratio of 0.45 and the UAS was a multirotor drone especially modified for emission measurements. In the experiments of this study, the drone was equipped with a small diffusion charge sensor capable of measuring the alveolar LDSA concentration of particles. The drone measurements were conducted during two days on the same spatial location at the kerbside of the street canyon by flying vertically from the ground level up to an altitude of 50 m clearly above the rooftop level (19 m) of the nearest buildings. The drone data were supported by simultaneous measurements and by a two-week period of measurements at nearby locations with various instruments. The results showed that the averaged LDSA concentrations decreased approximately from 60 μm²/cm³ measured close to the ground level to 36-40 μm²/cm³ measured close to the rooftop level of the street canyon, and further to 16-26 μm²/cm³ measured at 50 m. The high-resolution measurement data enabled an accurate analysis of the functional form of vertical profiles both in the street canyon and above the rooftop level. In both of these regions, exponential fits were used and the parameters obtained from the fits were thoroughly compared to the values found in literature. The results of this study indicated that the role of turbulent mixing caused by traffic was emphasized compared to the street canyon vortex as a driving force of the dispersion. In addition, the vertical profiles above the rooftop level showed a similar exponential decay compared to the profiles measured inside the street canyon.