Vertical and Horizontal Profiles of Particulate Matter and Black Carbon Near Elevated Highways Based on Unmanned Aerial Vehicle Monitoring

Particulate matter emissions from light-duty gasoline vehicles under different ambient temperatures: Physical properties and chemical compositions

Fine particulate matter (PM2.5) from vehicle exhaust is typically emitted at breathing height and thus imposes severe adverse effects on human health and air quality. However, there is currently limited knowledge on the characteristics of PM2.5 in exhaust, specifically its chemical components, at different ambient temperatures. Particulate emissions from typical light-duty gasoline vehicles (LDGVs) were investigated on a chassis dynamometer according to the Worldwide Harmonized Light-Duty Test Cycle at ambient temperatures of 38 °C, 28 °C, 15 °C, 5 °C and - 7 °C. The results showed a significant increase in particulate mass (PM) and particle number (PN) emissions with decreasing ambient temperature, particularly during cold starts below 5 °C. The particle size distributions exhibited distinct bimodal patterns, with accumulation-mode (AM) particles (60-125 nm) dominating the gasoline direct injection (GDI) distribution and nucleation-mode (NM) particles (8-12 nm) dominating the port fuel injection (PFI) distribution. AM particles were more temperature-sensitive than NM particles. Lower temperatures produced higher emissions of elements, carbonaceous components, and large-ring polycyclic aromatic hydrocarbons, while water-soluble ions showed an opposite trend. The total toxic equivalent, primarily influenced by benzo[a]pyrene, was significantly higher at -7 °C. The penalty distribution of LDGV PM and PN, defined by comparing the emissions at the various temperatures to those at regulated temperatures (23-30 °C), exhibited notable temporal heterogeneity (winter > autumn > spring > summer) and spatial heterogeneity (northern China > southern China). These findings are essential for establishing more stringent vehicle emission standards and improving emission models in cold environments.

Emerging Directions for Carbon Capture Technologies: A Synergy of High-Throughput Theoretical Calculations and Machine Learning

As the world grapples with the challenges of energy transition and industrial decarbonization, the development of carbon capture technologies presents a promising solution. The Scalable Modeling, Artificial Intelligence (AI), and Rapid Theoretical calculations, referred as SMART here, is an interdisciplinary approach that combines high-throughput calculation and data-driven modeling with expertise from chemical, materials, environmental, computer and data science and engineering, leading to the development of advanced capabilities in simulating and optimizing carbon capture processes. This perspective discusses the state-of-the-art material discovery research enabled by high-throughput calculation and data-driven modeling. Further, we propose a framework for material discovery, and illustrate the synergies among deep learning models, pretrained models, and comprehensive data sets, emerging as a robust framework for data-driven design and development in carbon capture. In essence, the adoption of the SMART approach promises a revolutionary impact on efforts in energy transition and industrial decarbonization.

Phytoremediation as a potential technique for vehicle hazardous pollutants around highways

With the synchronous development of highway construction and the urban economy, automobiles have entered thousands of households as essential means of transportation. This paper reviews the latest research progress in using phytoremediation technology to remediate the environmental pollution caused by automobile exhaust in recent years, including the prospects for stereoscopic forestry. Currently, most automobiles on the global market are internal combustion vehicles using fossil energy sources as the primary fuel, such as gasoline, diesel, and liquid or compressed natural gas. The composition of vehicle exhaust is relatively complex. When it enters the atmosphere, it is prone to a series of chemical reactions to generate various secondary pollutants, which are very harmful to human beings, plants, animals, and the eco-environment. Despite improving the automobile fuel quality and installing exhaust gas purification devices, helping to reduce air pollution, the treatment costs of these approaches are expensive and cannot achieve zero emissions of automobile exhaust pollutants. The purification of vehicle exhaust by plants is a crucial way to remediate the environmental pollution caused by automobile exhaust and improve the environment along the highway by utilizing the ecosystem's self-regulating ability. Therefore, it has become a global trend to use phytoremediation technology to restore the automobile exhaust pollution. Now, there is no scientific report or systematic review about how plants absorb vehicle pollutants. The screening and configuration of suitable plant species is the most crucial aspect of successful phytoremediation. The mechanisms of plant adsorption, metabolism, and detoxification are reviewed in this paper to address the problem of automobile exhaust pollution.

Quantifying COVID-19's silver lining: Avoided deaths from air quality improvements in Bogotá

In cities around the world, COVID-19 lockdowns have significantly improved outdoor air quality. Even if only temporary, these improvements could have longer-lasting effects by making chronic air pollution more salient and boosting political pressure for change. To that end, it is important to develop objective estimates of both the air quality improvements associated with lockdowns and the benefits they generate. We use panel data econometric models to estimate the effect of Bogotá's 16-month lockdown on PM_2.5 and NO₂ pollution, epidemiological models to simulate the effect of reductions in these pollutants on long- and short-term mortality, and benefit transfer methods to value the avoided mortality. We find that on average, Bogotá's lockdown cut PM_2.5 pollution by 15% and NO₂ pollution by 21%. However, the magnitude of these effects varied considerably over time and across the city's neighborhoods. Equivalent permanent reductions in these pollutants would reduce long-term premature deaths from air pollution by 23% each year, a benefit valued at $1 billion annually. Finally, we estimate that if they occurred ceteris paribus, the temporary reductions in pollutant concentrations in 2020-2021 due to Bogotá's lockdown would have cut short-term deaths from air pollution by 19%, a benefit valued at $244 million.

Vertical distributions of atmospheric black carbon in dry and wet seasons observed at a 356-m meteorological tower in Shenzhen, South China

Black carbon (BC) is a vital climate forcer in the atmosphere, but measurements of BC vertical profiles near the surface remain limited. This study investigates time-resolved vertical profiling of BC in both dry (December 2017) and wet (August 2018) seasons in Shenzhen, China, at a 356-m meteorological tower. In the dry season, five micro-aethalometers were deployed at different heights (2, 50, 100, 200, and 350 m), while four heights (2, 100, 200, and 350 m) were measured in the wet season. The concentrations of equivalent BC (eBC) showed a decreasing trend with altitude in the dry season, while a weaker vertical gradient was observed in the wet season. The diurnal variability of eBC in the dry season is also more significant than in the wet season. Correlation analysis between eBC concentrations at the ground and those at the upper levels suggest a better vertical mixing of eBC in the wet season than in the dry season. In the wet season when south wind prevailed, eBC concentration at ground level was likely reduced by the large amount of vegetation cover south to the sampling site. In the dry season, eBC concentrations at 350 m show little dependence on wind speed, implying that local emissions have a limited effect on eBC concentrations at 350 m. In the wet season when brown carbon influence was weak, higher wind speed leads to a higher Ångström exponent (AAE) at 350 m, likely associated with more aged BC particles. Cluster analysis of backward trajectories suggests that high eBC concentration was associated with air masses from Central China in both seasons. This study provides a better understanding on the influencing factors that affect the vertical distributions of BC in the lower part of the boundary layer.

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.

The effect of COVID-19 on the distribution of PM10 pollution classes of vehicles: Comparison between 2020 and 2018

A recent study by Pini et al. (2021), focusing on year 2018, demonstrated that different strategies should be considered in different Italian cities to mitigate the effects of PM10 pollution produced by circulating cars and commercial vehicles. The current study focuses on year 2020, considering the same ten Italian cities. This new study relies on the estimation of specific indices used to assess the size of the different circulating vehicle fleets (vehicle yearly mileage, diesel-fuel car and LCV fleet dimension, etc.) and their impact on PM10 pollution (Strength of Pollution). Results for 2020, severely affected by vehicular restrictions associated with COVID-19, indicate the need to adopt PM10 pollution reduction strategies for the various cities partially different from those identified earlier. For example, Euro 4 cars is the fleet having the highest impact on PM10 pollution in Rome (emitting 3,3 times more than Euro 6 vehicles), while in Milan the most polluting vehicles are Euro 0 cars (emitting 2 times more than Euro 6 vehicles). In Naples, Euro 0 cars emit 12,5 times more than Euro 6 vehicles. A careful look into the results also reveals that, for all considered cities, the three top fleets in terms of PM10 pollution always include Euro 4 or a higher Euro category fleet and a lower Euro category fleet (Euro 0 or Euro 3). These values were validated based on the use of pollution data from ground monitoring stations, which also allowed estimating the atmospheric mixing layer height. Results from the paper suggest that different incentivization policies have to be considered for the different considered cities. For example, in Naples the allocation of incentives should be ~60% towards new vehicles and ~40% towards recent used (i.e. second-hand) non-diesel vehicles, while in Florence it should be ~90% towards ECVs and ~10% towards recent used non-diesel vehicles.

Vertical profiling of black carbon and ozone using a multicopter unmanned aerial vehicle (UAV) in urban Shenzhen of South China

Existing studies on vertical profiling of black carbon (BC) and ozone (O₃) were mainly conducted in the rural areas, leading to limited knowledge of their vertical distributions in the urban area. To fill this knowledge gap, vertical profiling (0-500 m and 0-900 m, AGL) of BC and O₃ was conducted in a highly urbanized area of Shenzhen in subtropical South China using a multicopter unmanned aerial vehicle (UAV) platform. In total 32 flights were conducted from the 10th to 15th, December 2017 (winter campaign) and 42 flights from the 19th to 28th, August 2018 (summer campaign) with 4 time slots per day, including morning, afternoon, evening, and midnight. In general, equivalent BC (eBC) concentration decreased as the height increased with an overall slope of -0.13 μg m^-3 per 100 m in the winter campaign and -0.08 μg m^-3 per 100 m in the summer campaign. On the contrary, an increase of O₃ level with altitude was observed (7.8 ppb per 100 m). Absorption Ångström exponent (AAE) exhibits a slightly increasing trend with height. Seasonality of eBC vertical profiles was observed in morning, afternoon and midnight flights, but not for evening flights. The analysis showed the shape of vertical profiles of eBC and O₃ can be affected by planetary boundary layer height (PBLH) and air mass origin. Calculated heating rates due to BC show distinct seasonal variability for morning but not for afternoon, because of the counteracting effects by solar irradiance in the subtropical afternoon and eBC concentration in urban South China influenced by the monsoon climate.

The Unmanned Systems Research Laboratory (USRL): A New Facility for UAV-Based Atmospheric Observations

The Unmanned Systems Research Laboratory (USRL) of the Cyprus Institute is a new mobile exploratory platform of the EU Research Infrastructure Aerosol, Clouds and Trace Gases Research InfraStructure (ACTRIS). USRL offers exclusive Unmanned Aerial Vehicle (UAV)-sensor solutions that can be deployed anywhere in Europe and beyond, e.g., during intensive field campaigns through a transnational access scheme in compliance with the drone regulation set by the European Union Aviation Safety Agency (EASA) for the research, innovation, and training. UAV sensor systems play a growing role in the portfolio of Earth observation systems. They can provide cost-effective, spatial in-situ atmospheric observations which are complementary to stationary observation networks. They also have strong potential for calibrating and validating remote-sensing sensors and retrieval algorithms, mapping close-to-the-ground emission point sources and dispersion plumes, and evaluating the performance of atmospheric models. They can provide unique information relevant to the short- and long-range transport of gas and aerosol pollutants, radiative forcing, cloud properties, emission factors and a variety of atmospheric parameters. Since its establishment in 2015, USRL is participating in major international research projects dedicated to (1) the better understanding of aerosol-cloud interactions, (2) the profiling of aerosol optical properties in different atmospheric environments, (3) the vertical distribution of air pollutants in and above the planetary boundary layer, (4) the validation of Aeolus satellite dust products by utilizing novel UAV-balloon-sensor systems, and (5) the chemical characterization of ship and stack emissions. A comprehensive overview of the new UAV-sensor systems developed by USRL and their field deployments is presented here. This paper aims to illustrate the strong scientific potential of UAV-borne measurements in the atmospheric sciences and the need for their integration in Earth observation networks.

Urinary Amino-Polycyclic Aromatic Hydrocarbons in Urban Residents: Finding a Biomarker for Residential Exposure to Diesel Traffic

Despite substantial evidence of marked exposure to and ill-health effects from diesel exhaust (DE) emissions among occupational population (e.g., miners, truck drivers, and taxi drivers), it is less understood to what extent non-occupational population was exposed to DE among various combustion sources, largely due to the lack of biomarkers that would indicate specific exposure to DE. We evaluated whether urinary amino-polycyclic aromatic hydrocarbons (APAHs), such as major metabolites of DE-specific nitrated PAHs, can be used as DE exposure biomarkers in residential settings. We measured five urinary APAHs in 177 urine samples from 98 UK residents, 89 (91%) of them were London residents, and estimated their residential proximity to various traffic indicators (e.g., the road type, road length, traffic flow, and traffic volume). Participants living within 100 m of major roads exhibited increased levels of all five APAHs, among which 2-amino-fluorene (2-AFLU) reached statistical significance (p < 0.05). We estimated that a 10 m increase in the length of nearby major roads (<100 m) was associated with a 4.4% (95% CI of 1.1 to 7.6%) increase in 2-AFLU levels. Levels of 2-AFLU were significantly associated with the traffic flow of nearby buses and heavy-duty vehicles but not motorbikes, taxis, or coaches. We did not observe a significant association between distance to major roads or the sum of the major road length within 100 m with the other four biomarker concentrations. These results suggest the use of urinary 2-AFLU as a biomarker of DE exposure in urban residents.

Impact of the different vehicle fleets on PM10 pollution: Comparison between the ten most populous Italian metropolitan cities for the year 2018

The main aim of this research effort is to assess the impact of the different circulating vehicle fleets on PM10 pollution, comparing the results from the ten most populated metropolitan cities in Italy. Circulating diesel vehicles have been categorized in different groups depending on the vehicle type (car or Light Commercial Vehicle - LCV) and European emission standard. The annual mileage and the total PM10 emission for each category has been determined based on several data sources. Estimated overall annual emissions of PM10 particles have been compared with PM10 concentration measurements from distributed ground monitoring stations. A new index, named SoP (Strength of Pollution), has been defined in order to quantify the contribution of each fleet category to the overall PM10 pollution. The index has been computed for the ten most populated Italian metropolitan cities, i.e. all cities with more than 300.000 inhabits: Rome, Milan, Naples, Turin, Palermo, Genoa, Bologna, Florence, Bari and Catania. Results in terms of SoP estimates for year 2018 reveal the presence in these Italian cities of emission clusters with heterogeneous characteristics, which impose the adoption of different PM10 pollution mitigation approaches in the different cities. For example, in Naples, Catania and Palermo, Euro 0 car fleets emit a total PM10 mass which is respectively 19, 10 and 5 times the mass emitted by Euro 6 vehicles, and consequently a reduction of this fleet is desirable for pollution mitigation purposes. Conversely, in Rome, Genoa and Bari, Euro 3 and 4 car fleets emit a total PM10 mass which is 3-6 times the one emitted by Euro 6 vehicles, which calls for a reduction of these fleets. Thus, the extension to the entire national territory of the results obtained in a specific metropolitan city may be strongly misleading and produce limited effects in terms of pollution mitigation.