Ultrafine particle size as a tracer for aircraft turbine emissions.

Ultrafine particle number (UFPN) and size distributions, black carbon, and nitrogen dioxide concentrations were measured downwind of two of the busiest airports in the world, Los Angeles International Airport (LAX) and Hartsfield-Jackson International Airport (ATL - Atlanta, GA) using a mobile monitoring platform. Transects were located between 5 km and 10 km from the ATL and LAX airports. In addition, measurements were taken at 43 additional urban neighborhood locations in each city and on freeways. We found a 3-5 fold increase in UFPN concentrations in transects under the landing approach path to both airports relative to surrounding urban areas with similar ground traffic characteristics. The latter UFPN concentrations measured were distinct in size distributional properties from both freeways and across urban neighborhoods, clearly indicating different sources. Elevated concentrations of Black Carbon (BC) and NO2 were also observed on airport transects, and the corresponding pattern of elevated BC was consistent with the observed excess UFPN concentrations relative to other urban locations.

Aerosol particle number concentration, ultrafine particle number fraction, and new particle formation measurements near the international airports in Berlin, Germany - First results from the BEAR study.

Studies revealed airports as a prominent source of ultrafine particles (UFP), which can disperse downwind to residential areas, raising health concerns. To expand our understanding of how air traffic-related emissions influence total particle number concentration (PNC) in the airport's surrounding areas, we conduct long-term assessment of airborne particulate exposure before and after relocation of air traffic from "Otto Lilienthal" Airport (TXL) to Berlin Brandenburg Airport "Willy Brandt" (BER) in Berlin, Germany. Here, we provide insights into the spatial-temporal variability of PNC measured in 16 schools recruited for Berlin-Brandenburg Air Study (BEAR). The results show that the average PNC in Berlin was 7900 ± 7000 cm-3, consistent with other European cities. The highest median PNC was recorded in spring (6700 cm-3) and the lowest in winter (5100 cm-3). PNC showed a bi-modal increase during morning and evening hours at most measurement sites due to road-traffic emissions. A comparison between measurements at the schools and fixed monitoring sites revealed good agreement at distances up to 5 km. A noticeable decline in this agreement occurred as the distance between measurement sites increased. After TXL was closed, PNC in surrounding areas decreased by 30 %. The opposite trend was not seen after BER was re-opened after the COVID-lock-down, as the air traffic has not reached the full capacity yet. The analysis of particle number size distribution data showed that UFP number fraction exhibit seasonal variations, with higher values in spring and autumn. This can be explained by nucleation events, which notably affected PNC. The presented findings will play a pivotal role in forthcoming source attribution and epidemiological investigations, offering a holistic understanding of airports' impact on airborne pollutant levels and their health implications. The study calls for further investigations of air-traffic-related physical-chemical pollutant properties in areas found further away (> 10 km) from airports.

Emissions from international airport and its impact on air quality: A case study of beijing daxing international airport (PKX), China.

The Beijing Daxing International Airport is a newly opened airport, and a comprehensive emission inventory of air pollution sources has not yet been established. The lack of basic inventory data will cause difficulties in controlling the air quality (AQ) in and around the airport. Based on actual flight data, we established a comprehensive emission inventory (carbon monoxide (CO), nitrogen oxides (NOX), hydrocarbons (HC), sulfur dioxide (SO2), particulate matter (PM), and carbon dioxide (CO2)) at Beijing Daxing International Airport. Furthermore, we evaluated the impact of airport emissions on the AQ of the surrounding areas using the ADMS-Airport model. The results showed that Beijing Daxing International Airport emitted 1.15 E+03, 1.76 E+03, 1.38 E+02, 1.16 E+02, 3.53 E+01, and 3.75 E+05 t of CO, NOX, HC, SO2, PM, and CO2, respectively, from July 1, 2020, to June 30, 2021. Engine exhaust emissions (landing and takeoff [LTO] cycles) dominated all airport pollutant emissions except for PM from the power plant. Among all aircraft types, B738 emitted the most CO2, as it accounted for almost half of all the flights. The AQ simulations showed that the air pollutant diffusion range was concentrated within 15 km of the airport and the surrounding areas. The contribution of airport emissions to NOX concentrations was most apparent under the most unfavorable meteorological conditions. Based on the average pollutant concentration during the study period, the Gu'an Li Hu Primary School station was the most affected. In particular, NOX concentrations at this station were approximately 50% higher in winter than in summer. Currently, the airport's contribution to pollution in the surrounding areas is insignificant. However, with the continuous increase in the number of flights at the airport, its impact on the AQ in the surrounding areas must be addressed in the future.

Sources of particle number concentration and noise near London Gatwick Airport.

There is increasing evidence of potential health impacts from both aircraft noise and aircraft-associated ultrafine particles (UFP). Measurements of noise and UFP are however scarce near airports and so their variability and relationship are not well understood. Particle number size distributions and noise levels were measured at two locations near Gatwick airport (UK) in 2018-19 with the aim to characterize particle number concentrations (PNC) and link PNC sources, especially UFP, with noise. Positive Matrix Factorization was used on particle number size distribution to identify these sources. Mean PNC (7500-12,000 p cm-3) were similar to those measured close to a highly trafficked road in central London. Peak PNC (94,000 p cm-3) were highest at the site closer to the runway. The airport source factor contributed 17% to the PNC at both sites and the concentrations were greatest when the respective sites were downwind of the runway. However, the main source of PNC was associated with traffic emissions. At both sites noise levels were above the recommendations by the WHO (World Health Organisation). Regression models of identified UFP sources and noise suggested that the largest source of noise (LAeq-1hr) above background was associated with sources of fresh traffic and urban UFP depending on the site. Noise and UFP correlations were moderate to low suggesting that UFP are unlikely to be an important confounder in epidemiological studies of aircraft noise and health. Correlations between UFP and noise were affected by meteorological factors, which need to be considered in studies of short-term associations between aircraft noise and health.

Source apportionment of particle number size distribution in urban background and traffic stations in four European cities.

Ultrafine particles (UFP) are suspected of having significant impacts on health. However, there have only been a limited number of studies on sources of UFP compared to larger particles. In this work, we identified and quantified the sources and processes contributing to particle number size distributions (PNSD) using Positive Matrix Factorization (PMF) at six monitoring stations (four urban background and two street canyon) from four European cities: Barcelona, Helsinki, London, and Zurich. These cities are characterised by different meteorological conditions and emissions. The common sources across all stations were Photonucleation, traffic emissions (3 sources, from fresh to aged emissions: Traffic nucleation, Fresh traffic - mode diameter between 13 and 37 nm, and Urban - mode diameter between 44 and 81 nm, mainly traffic but influenced by other sources in some cities), and Secondary particles. The Photonucleation factor was only directly identified by PMF for Barcelona, while an additional split of the Nucleation factor (into Photonucleation and Traffic nucleation) by using NOx concentrations as a proxy for traffic emissions was performed for all other stations. The sum of all traffic sources resulted in a maximum relative contributions ranging from 71 to 94% (annual average) thereby being the main contributor at all stations. In London and Zurich, the relative contribution of the sources did not vary significantly between seasons. In contrast, the high levels of solar radiation in Barcelona led to an important contribution of Photonucleation particles (ranging from 14% during the winter period to 35% during summer). Biogenic emissions were a source identified only in Helsinki (both in the urban background and street canyon stations), that contributed importantly during summer (23% in urban background). Airport emissions contributed to Nucleation particles at urban background sites, as the highest concentrations of this source took place when the wind was blowing from the airport direction in all cities.

Relative contributions of a major international airport activities and other urban sources to the particle number concentrations (PNCs) at a nearby monitoring site.

In this study, the positive matrix factorization (PMF) source apportionment model was employed to quantify the contributions of airport activities to particle number concentrations (PNCs) at Amsterdam Schiphol. Time-resolved particle number size distributions in parallel with the concentrations of auxiliary variables, including gaseous pollutants (NOx and CO), black carbon, PM2.5 mass, and number of arrivals/departures were measured for 32 sampling days over a 6-month period near Schiphol airport to be used in the model. PMF results revealed that airport activities, cumulatively, accounted for around 79.3% of PNCs and our model segregated them into three major groups: (i) aircraft departures, (ii) aircraft arrivals, and (iii) ground service equipment (GSE) (with some contributions of local road traffic, mostly from airport parking lots). Aircraft departures and aircraft arrivals showed mode diameters <20 nm and contributed, respectively, to 46.1% and 26.7% of PNCs. The factor GSE/local road traffic, with a mode diameter of around 60-80 nm, accounted for 6.5% of the PNCs. Road traffic related mainly to the surrounding freeways was characterized with a mode diameter of 30-40 nm; this factor contributed to 18.0% of PNCs although its absolute PNCs was comparable with that of areas heavily impacted by traffic emissions. Lastly, urban background with a mode diameter at 150-225 nm, had a minimal contribution (2.7%) to PNCs while dominating the particle volume/mass concentrations with a contribution of 58.2%. These findings illustrate the dominant role of the airport activities in ambient PNCs in the surrounding areas. More importantly, the quantification of the contributions of different airport activities to PNCs is a useful tool to better control and limit the increased PNCs near the airports that could adversely impact the health of the adjacent urban communities.