Influence of semi- and intermediate-volatile organic compounds (S/IVOC) parameterizations, volatility distributions and aging schemes on organic aerosol modelling in winter conditions

Giani, Paolo; Balzarini, Alessandra; Pirovano, Guido; Gilardoni, Stefania; Paglione, Marco; Colombi, Cristina; Gianelle, V.; Belis, Claudio A.; Poluzzi, Vanes; Lonati, Giovanni

doi:10.1016/j.atmosenv.2019.05.061

Cited by 26 publications

(28 citation statements)

References 82 publications

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“…emissions estimates (Zheng et al 2017a)), uncertain initial and boundary conditions (Georgiou et al 2018), and incomplete understanding of some physical-chemical processes (e.g. formation of secondary organic aerosol (Giani et al 2019)). These issues can lead to potentially large biases in mortality estimates and thus we stress the importance of data assimilation techniques in calculating the mortality burden.…”

Section: Discussionmentioning

confidence: 99%

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Giani

Anav

Marco

et al. 2020

Environ. Res. Lett.

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Atmospheric pollution from fine particulate matter (PM 2.5 ) is one of the major concerns in China because of its widespread and harmful impacts on human health. In recent years, multiple studies have sought to estimate the premature mortality burden from exposure to PM 2.5 to inform policy decisions. However, different modeling choices have led to a wide array of results, with significant discrepancies both in the total mortality burden and in the confidence intervals. Here, we present a new comprehensive assessment of PM 2.5 -related mortality for China, which includes quantification of the main sources of variability, as well as of age and province-specific premature mortality trends during 2015-2018. Our approach integrates PM 2.5 observations from more than 1600 monitoring stations with the output of a high-resolution (8 km) regional simulation, to accurately estimate PM 2.5 fields along with their uncertainty, which is generally neglected. We discuss the sensitivity of mortality estimates to the choice of the exposure-response functions (ERFs), by comparing the widely used integrated exposure response functions (IERs) to the recently developed Global Exposure Mortality Models (GEMMs). By propagating the uncertainty in baseline mortalities, PM 2.5 and ERFs under a Monte Carlo framework, we show that the 95% confidence intervals of mortality estimates are considerably wider than previously reported. We thus highlight the need for more epidemiological studies to constrain ERFs and we argue that uncertainty related to PM 2.5 estimate should be also incorporated in health impact assessment studies. Although the overall mortality burden remains vast in China (~1.6 million premature deaths, according to GEMMs), our results suggest that 200 000 premature deaths were avoided and 195 billion US dollars were saved in 2018 compared to 2015, bolstering the mounting evidence about the effectiveness of China's air quality policies.

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Section: Discussionmentioning

confidence: 99%

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Giani

Anav

Marco

et al. 2020

Environ. Res. Lett.

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“…For this study, only the portion of the domain covering Lombardy is analyzed and shown. The overall configuration of the modeling chain follows the one presented in Meroni et al [36] and Giani et al [37], the main difference being the use of the traditional Secondary Organic Aerosol Processor (SOAP) [38] aerosol scheme for organic matter modeling. The meteorological input derives from a customized configuration of the numerical weather prediction (NWP) model Weather Regional Forecast (WRF) [39].…”

Section: Camx Configuration and Input Datamentioning

confidence: 99%

Modeling the Effect of COVID-19 Lockdown on Mobility and NO2 Concentration in the Lombardy Region

et al. 2020

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Recent observation and modeling-based studies have shown how air quality has been positively affected by the containment measures enforced due to the COVID-19 outbreak. This work aims to analyze Lombardy’s NO2 atmospheric concentration during the spring lockdown. The region of Lombardy is known for having the largest number of residents in Italy and high levels of pollution. It is also the region where the first European confinement measures were imposed by the Italian government. The modeling suite composed of CAMx (Comprehensive Air Quality Model with Extensions) and WRF (Weather Research and Forecasting model) provides the setting to compare the atmospheric NO2 concentration from mid-February to the end of March with a business as usual situation. The main interest in this work is to investigate the response of NO2 atmospheric concentration to increasingly reduced road traffic. We can simulate, for the first time, a real circumstance of progressively reduced mobility, as well as validating it with measured air quality data. Focusing on the city of Milan, we found that the decrease in NO2 concentration reflects progressively reduced traffic contraction. In the case of a large traffic abatement (71%), the concentration level is reduced by one third. We also find that industrial activities have a relevant impact on NO2 atmospheric concentration, especially in the provinces of Brescia and Bergamo. This study provides an overview of how incisive policies must be implemented to achieve the set environmental targets and protect human health.

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“…The SOA particle mass is usually predicted based on the extrapolation of the SOA yields from single SOA precursor laboratory studies (Kanakidou et al, 2005). Recently, the volatility basis set (VBS; Donahue et al, 2006Donahue et al, , 2012 under the assumption of equilibrium absorptive partitioning has been developed and implemented in such models to predict the formation and evolution of SOA (Shrivastava et al, 2011;Giani et al, 2019;Koo et al, 2014;Tsimpidi et al, 2018). The SOA volatility distribution used in such models is obtained directly or indirectly from laboratory/field studies (Zhao et al, 2016;Giani et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the volatility basis set (VBS; Donahue et al, 2006Donahue et al, , 2012 under the assumption of equilibrium absorptive partitioning has been developed and implemented in such models to predict the formation and evolution of SOA (Shrivastava et al, 2011;Giani et al, 2019;Koo et al, 2014;Tsimpidi et al, 2018). The SOA volatility distribution used in such models is obtained directly or indirectly from laboratory/field studies (Zhao et al, 2016;Giani et al, 2019). Additivity is implicitly assumed, as the coexistence of multiple reacting VOCs does not affect the volatility distribution of the SOA formed from each precursor.…”

Section: Introductionmentioning

confidence: 99%

The influence of the addition of isoprene on the volatility of particles formed from the photo-oxidation of anthropogenic–biogenic mixtures

Voliotis

Du²,

Wang³

et al. 2022

Atmos. Chem. Phys.

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Abstract. In this study, we investigate the influence of isoprene on the volatility of secondary organic aerosol (SOA) formed during the photo-oxidation of mixtures of anthropogenic and biogenic precursors. The SOA particle volatility was quantified using two independent experimental techniques (using a thermal denuder and the Filter Inlet for Gas and Aerosols iodide high-resolution time-of-flight Chemical Ionisation Mass Spectrometer – FIGAERO-CIMS) in mixtures of α-pinene/isoprene, o-cresol/isoprene, and α-pinene/o-cresol/isoprene. Single-precursor experiments at various initial concentrations and results from previous α-pinene/o-cresol experiments were used as a reference. The oxidation of isoprene did not result in the formation of detectable SOA particle mass in single-precursor experiments. However, isoprene-derived products were identified in the mixed systems, likely due to the increase in the total absorptive mass. The addition of isoprene resulted in mixture-dependent influence on the SOA particle volatility. Isoprene made no major change to the volatility of α-pinene SOA particles, though changes in the SOA particle composition were observed and the volatility was reasonably predicted based on the additivity. Isoprene addition increased o-cresol SOA particle volatility by ∼5/15 % of the total mass/signal, respectively, indicating a potential to increase the overall volatility that cannot be predicted based on the additivity. The addition of isoprene to the α-pinene/o-cresol system (i.e. α-pinene/o-cresol/isoprene) resulted in slightly fewer volatile particles than those measured in the α-pinene/o-cresol systems. The measured volatility in the α-pinene/o-cresol/isoprene system had an ∼6 % higher low volatile organic compound (LVOC) mass/signal compared to that predicted assuming additivity with a correspondingly lower semi-volatile organic compound (SVOC) fraction. This suggests that any effects that could increase the SOA volatility from the addition of isoprene are likely outweighed by the formation of lower-volatility compounds in more complex anthropogenic–biogenic precursor mixtures. Detailed chemical composition measurements support the measured volatility distribution changes and showed an abundance of unique-to-the-mixture products appearing in all the mixed systems accounting for around 30 %–40 % of the total particle-phase signal. Our results demonstrate that the SOA particle volatility and its prediction can be affected by the interactions of the oxidized products in mixed-precursor systems, and further mechanistic understanding is required to improve their representation in chemical transport models.

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Influence of semi- and intermediate-volatile organic compounds (S/IVOC) parameterizations, volatility distributions and aging schemes on organic aerosol modelling in winter conditions

Cited by 26 publications

References 82 publications

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Modeling the Effect of COVID-19 Lockdown on Mobility and NO2 Concentration in the Lombardy Region

The influence of the addition of isoprene on the volatility of particles formed from the photo-oxidation of anthropogenic–biogenic mixtures

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