Effect of chemistry-transport model scale and resolution on population exposure to PM2.5 from aircraft emissions during landing and takeoff

Arunachalam, Saravanan; Wang, Binyu; Davis, Neil; Baek, Bok H.; Levy, Jonathan I.

doi:10.1016/j.atmosenv.2011.03.029

Cited by 99 publications

(78 citation statements)

References 19 publications

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“…PM 2.5 concentrations have also been found to be sensitive to the model horizontal resolution (Arunachalam et al, 2011;Punger and West, 2013;Markakis et al, 2015;Neal et al, 2017). In the US, Punger and West (2013) found populationweighted annual mean PM 2.5 concentrations to be 6 % higher at 36 km compared to 12 km, but 27 % lower when simulated at 408 km compared to 12 km.…”

Section: Introductionmentioning

confidence: 95%

“…Markakis et al, 2015;Schaap et al, 2015;Yu et al, 2016;Neal et al, 2017). Although the same model processes are represented at different model resolutions, simulated pollutant concentrations can vary due to differences in (i) the resolution of emissions, which may have a nonlinear effect on the chemical formation of pollutants, and (ii) the resolution of the driving meteorology (Valari and Menut, 2008;Tie et al, 2010;Arunachalam et al, 2011;Colette et al, 2013;Markakis et al, 2015;Schaap et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

et al. 2018

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Abstract. We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O 3 ) and particulate matter less than 2.5 µm in diameter (PM 2.5 ), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (∼ 140 km) and a finer (∼ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O 3 and annual-average PM 2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O 3 and PM 2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O 3 concentrations at the coarse resolution are higher on average in winter and spring (∼ 10 and ∼ 6 %, respectively). In contrast, simulated O 3 concentrations at the coarse resolution are lower in summer and autumn (∼ −1 and ∼ −4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO 2 ) concentrations simulated at the two resolutions. Compared to O 3 , we find the opposite seasonality in simulated PM 2.5 differences between the two resolutions. In winter and spring, simulated PM 2.5 concentrations are lower at the coarse compared to the finer resolution (∼ −8 and ∼ −6 %, respectively) but higher in summer and autumn (∼ 29 and ∼ 8 %, respectively). Simulated PM 2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O 3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM 2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O 3 range between −0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to populationweighted annual mean PM 2.5 range from −4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ∼ ±5 % of the total mortality across Europe.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

et al. 2018

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“…This method is routinely used to estimate the public health impacts of aircraft LTO PM emissions in the United States (Ratliff et al 2009;CSSI Inc. 2010;Arunachalam et al 2011;Levy et al 2011;Woody et al 2011). While several studies have measured the mass of emitted BC per unit fuel burned, known as EI(BC), the majority of engines in service have not been measured and for these the SN remains the only measure of their PM emissions (Timko et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Updated Correlation Between Aircraft Smoke Number and Black Carbon Concentration

Stettler

Swanson

Barrett

et al. 2013

Aerosol Science and Technology

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“…As submicron particles, gas turbine engine particle material (PM) emissions may potentially impact human health (Stettler et al 2011;Levy et al 2012), local air quality (Dodson et al 2009;Arunachalam et al 2011;Hsu et al 2011Hsu et al , 2012Zhu et al 2011), and global climate (Lee et al 2010;Dallara et al 2011;Dorbian et al 2011;Jacobson et al 2011;Unger 2011). Since aircraft use is predicted to increase in the coming decades (Lee et al 2009) and since post-treatment of aircraft engine exhaust is not feasible, better understanding of the combustion emissions is required so that the potential impacts can be properly accounted for in atmospheric models and to improve aircraft combustor designs.…”

Section: Introductionmentioning

confidence: 99%

Composition and Sources of the Organic Particle Emissions from Aircraft Engines

Timko

Albo

Onasch

et al. 2013

Aerosol Science and Technology

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We report a positive matrix factorization (PMF) analysis of organic particulate material (PM) emissions of aircraft engine exhaust that includes data from five different aircraft engines and two different fuels (petroleum jet fuel and a Fischer-Tropsch fuel) collected over three field missions. PMF of aerosol mass spectrometer (AMS) data was used to identify six distinct factors: two lubrication oil factors, two aliphatic factors, an aromatic factor, and a siloxane factor. Of these, the lubrication oil factors and the siloxane factor were noncombustion sources. The siloxane factor was attributed to silicone tubing used in the sampling system deployed in one of the three missions included in this study, but not the other two. The two lubrication oil factors correlate with the two different lubrication oils used by the aircraft engines evaluated in this study (Mobil II and Air BP) as well as minor differences presumably due to variation in the blend stocks, temperature history, and analytical factors. Overall, the sum of the aliphatic and aromatic factors decreased with increasing power, as expected based on known trends in VOC emissions. The aliphatic #1 factor correlated with soot emissions, especially at power conditions where EI m -soot was greater than Received 26 June 2013; accepted 11 October 2013. The authors thank NASA for leading the APEX-3 and AAFEX measurement activities and for supporting our participation in AAFEX-1 (NRA # NNC07CB57C). FAA (via Missouri University of Science and Technology) supported our participation in AAFEX-2. NASA DAOF and Cleveland Hopkins Airport were gracious hosts for the field measurement campaigns. Discussions with Kathy Tacina, Chris Heath, Bruce Anderson, and Andreas Beyersdorf helped guide our analysis and discussion of our results. Scott Herndon's efforts made sure that Aerodyne's involvement in the APEX-3 and AAFEX campaigns were successful. Berk Knighton generously shared his PTR-MS benzene measurement data. Ezra Wood (APEX-3 and AAFEX) and Jon Franklin (AAFEX-2) were valuable team members who contributed to preparation, execution, and analysis efforts. John Jayne developed AMS operating procedures used in this study and advised the team during the data analysis effort.Address correspondence to Richard C. . The aliphatic factor #2 mass spectrum shared some similarities with ambient aerosol organic PM present during the tests and correlated most strongly with dilution levels, two observations that suggest that aliphatic #2 contains components found in ambient aerosol. The aromatic factor correlated with benzene emissions, especially at low power conditions were EI m -benzene was greater than 0.03 mg kg ?1 . Our results improve the current understanding of aircraft PM composition.

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Effect of chemistry-transport model scale and resolution on population exposure to PM2.5 from aircraft emissions during landing and takeoff

Cited by 99 publications

References 19 publications

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

Updated Correlation Between Aircraft Smoke Number and Black Carbon Concentration

Composition and Sources of the Organic Particle Emissions from Aircraft Engines

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