the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 May 2026
Molecular-Level Characterization of Urban Aerosol Analogues in Controlled Atmospheric Simulations
Abstract. Urban air pollution involves complex mixtures of gases and particulate matter whose molecular-level composition and gas-particle partitioning remain poorly characterized, limiting our understanding of secondary organic aerosol (SOA) formation. We address this gap using controlled atmospheric simulations combined with detailed molecular characterization.
Two distinct urban atmospheric scenarios were simulated in the CESAM smog chamber: a standard urban (traffic emissions and biogenic precursors) and a biomass burning enhanced. Both scenarios were aged under controlled irradiation with NOx to simulate tropospheric photochemistry.
PM1 concentrations reached 15 ± 7 µg.m-3 for the standard scenario and 63 ± 24 µg.m-3 for the biomass burning scenario, with organic aerosol fractions of approximately 17 % and 40 %, respectively. Gas-phase analysis via proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) identified 23 volatile organic compounds (VOCs), dominated by oxygenated species (74–77 %). Particle-phase molecular analysis using ultrahigh-performance liquid chromatography electrospray ionization ion mobility quadrupole time-of-flight mass spectrometry (UPLC/ESI-IMS-QTOFMS) revealed 32 distinct compounds. The biomass burning scenario showed elevated source-specific tracers, including a levoglucosan isomer, nitrophenolic compounds (e.g., 3-methyl-4-nitrocatechol, 4-nitroguaiacol), and oxidized aromatics. Volatility distributions estimated via group contribution methods placed most compounds in the semi-volatile, low-volatility, and extremely low-volatility organic compound ranges (C* < 300 µg m-3), indicating substantial functionalization and partitioning.
These results demonstrate the capacity of simulation chambers to generate reproducible urban aerosol analogues with distinct source-specific molecular signatures and well-characterized volatility distributions. This detailed molecular speciation provides a robust basis for process-oriented model evaluation and opens perspectives for systematic investigations of SOA formation pathways under controlled urban photochemical conditions.
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Status: open (until 23 Jun 2026)
- RC1: 'Comment on egusphere-2026-1743', Anonymous Referee #1, 02 Jun 2026 reply
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Mass spectrometry data for molecular-level characterization of urban aerosol analogues in controlled atmospheric simulations. E. Al Marj et al. https://doi.org/10.5281/zenodo.19546628
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- 1
In this manuscript, the authors simulated two urban atmospheric scenarios, namely a standard urban pollution scenario and a biomass-burning-enhanced scenario, using the CESAM smog chamber and the PolluRisk exposure platform. They showed that PM1 and organic aerosol concentrations increased markedly under the biomass-burning-enhanced scenario, with characteristic molecular markers detected, including a levoglucosan isomer, nitrophenolic compounds, and oxidized aromatic products. However, this manuscript has major flaws and is not suitable for publication in ACP.
The conclusion “atmospheric simulation chambers as complementary tools to field studies for urban air quality assessment” has long been recognized by the atmospheric chemistry community, so I did not find any real novelty in this work.
The second paragraph of the Introduction is very brief and states in a single sentence that the molecular composition of PM1 particles may play a role in toxicological responses. In addition, this paragraph should be expanded to more clearly explain why molecular-level characterization of PM1 is important for understanding aerosol toxicity and health effects. More importantly, the authors did not report any toxicity or health effects, so the paper did not answer this scientific question.
The authors argue that the focus of this work was the molecular-level chemical composition. However, the chemical analysis results were too simplified to show insights into any new findings. Specifically, the author primarily reported qualitative results in the component analysis, with very few quantitative or semi-quantitative discussions.
Have the potential effects of wall loss and photolysis of reaction products in the chamber been considered? These processes may influence the measured concentrations and chemical composition of the oxidation products, and should be discussed.
The authors state that compounds in the SVOC-LVOC-ELVOC ranges were predominant based on Fig. 5. However, Fig. 5 does not show the relative signal intensities or abundances of individual compounds. Therefore, concluding predominance solely based on the number of detected compounds may be biased.