Key Takeaways & Executive Findings
- •• • Photochemical loss correction increased TVOCs from 12.49×10⁻⁹ to 14.93×10⁻⁹ (16.4% loss), with alkenes losing 53.2%—critical for accurate emission inventory and control strategy design. • • OFP loss rate reached 45.0% (from 21.31×10⁻⁹ to 38.75×10⁻⁹), with alkenes contributing 56.4% of the loss—underscoring the need to account for reactivity in ozone mitigation. • • During ozone pollution, TVOCs chemical loss was 1.9× higher and OFP loss 1.2× higher than non-pollution periods, with alkenes accounting for 88.4% of TVOCs loss—highlighting the role of alkenes in episodic ozone formation. • • PMF source apportionment based on initial concentrations shifted the dominant OFP source from motor vehicles (42.5% by observed) to petrochemical enterprises (42.5% by initial), demonstrating that ignoring photochemical losses misidentifies key ozone precursors.
Abstract
This study estimated initial volume mixing ratios of volatile organic compounds (VOCs) in Dalian from June 1 to August 31, 2024, using a photochemical age-based parameterization method, and performed source apportionment with positive matrix factorization (PMF). Observed average TVOCs concentration was 12.49×10⁻⁹, comprising alkanes (84.2%), alkenes (10.4%), and aromatics (5.4%). Corrected initial TVOCs was 14.93×10⁻⁹, indicating a loss rate of 16.4%. Loss rates were highest for alkenes (53.2%), followed by aromatics (23.3%) and alkanes (6.8%). Ozone formation potential (OFP) averaged 21.31×10⁻⁹ (observed) and 38.75×10⁻⁹ (initial), with an OFP loss rate of 45.0%, distributed as alkenes (56.4%), aromatics (32.7%), and alkanes (10.3%). During ozone pollution episodes, TVOCs chemical loss was 1.9 times that of non-pollution periods, with alkene loss reaching 61.6%; OFP loss was 1.2 times higher, with alkenes contributing 88.4% to TVOCs loss. Secondary organic aerosol (SOA) formation potential from 08:00–17:00 was 1.51×10⁻¹ μg·m⁻³, with 99.4% from aromatics and toluene contributing 68.3%. PMF identified five sources: motor vehicles (49.6%), oil and gas volatilization (20.7%), petrochemical enterprises (12.6%), industrial processes (11.2%), and solvent use (5.9%). OFP modeling indicated motor vehicles contributed most to ozone formation (41.1%), followed by petrochemical enterprises (35.8%). During ozone pollution, PMF based on initial concentrations showed petrochemical sources had the highest OFP contribution (42.5%), whereas observed concentrations indicated motor vehicles as the top contributor (42.5%). This discrepancy underscores the necessity of correcting for photochemical losses in source apportionment studies.
1. Introduction
Urban air quality management critically depends on accurate source apportionment of volatile organic compounds (VOCs), which are key precursors to tropospheric ozone and secondary organic aerosols. However, conventional monitoring measures ambient concentrations that have already undergone photochemical degradation, leading to underestimation of reactive species and distortion of source contributions. This is particularly problematic in summer when photochemical activity is intense, as seen in coastal cities like Dalian, where industrial and vehicular emissions intersect. Existing studies often neglect this chemical aging, resulting in misallocation of emission sources and ineffective control measures.
This study addresses this bottleneck by applying a photochemical age-based parameterization to estimate initial VOCs concentrations from online monitoring data, followed by PMF source apportionment. The approach corrects for losses of alkanes, alkenes, and aromatics, providing a more realistic basis for identifying sources and assessing ozone formation potential. By comparing results from observed versus initial concentrations, the study quantifies the impact of photochemical losses on source apportionment, offering a methodological improvement that can refine emission reduction strategies in ozone-polluted regions.
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CAO Shanshan, YAN Shouzheng, MIAO Shuyi, JIA Dezhou, WANG Xiaohuan, CHEN Xin, LIU Jiajun (2026). Photochemical Reaction Characteristics and Source Apportionment of VOCs Based on Estimation of Initial Volume Mixing Ratios during Summer in Dalian. Environmental Chemistry. https://doi.org/10.7524/j.issn.0254-6108.2025042702
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Frequently Asked Questions
How does the photochemical age-based parameterization method correct for VOC losses, and what are its limitations in coastal urban environments?
The method uses the ratio of reactive to inert VOC species (e.g., m/p-xylene to ethylbenzene) to estimate photochemical age, then calculates initial concentrations via a pseudo-first-order kinetics model. In Dalian, this yielded a TVOCs loss rate of 16.4%, with alkenes losing 53.2%. Limitations include assumptions of constant OH exposure and well-mixed air masses, which may not hold under varying meteorological conditions or near strong local sources, potentially introducing uncertainties in the correction factors.
What are the implications of the observed shift in dominant OFP source from motor vehicles to petrochemical enterprises when using initial concentrations?
Using observed concentrations, motor vehicles appeared to contribute 42.5% to OFP, but after correcting for photochemical losses, petrochemical enterprises emerged as the top contributor (42.5%). This indicates that reactive alkenes from petrochemical sources are rapidly consumed, masking their true impact. For policymakers, this means that control measures targeting motor vehicles alone may be insufficient; instead, petrochemical emission reductions could be more effective in reducing ozone formation, as evidenced by the 35.8% contribution from petrochemical sources to total OFP over the entire period.
How does the SOA formation potential vary with photochemical processing, and what is the role of toluene?
SOA formation potential was estimated for 08:00–17:00, yielding 1.51×10⁻¹ μg·m⁻³, with 99.4% from aromatics. Toluene alone contributed 68.3%, indicating its dominance. Photochemical processing increases the fraction of oxygenated products that partition into the particle phase, but the study did not explicitly correct SOA for losses. However, given that aromatics have moderate loss rates (23.3%), the actual SOA potential from fresh emissions could be higher, emphasizing the need to control aromatic solvents and traffic emissions.
What are the key uncertainties in PMF source apportionment when using initial concentrations, and how do they affect source contribution estimates?
PMF on initial concentrations reduces the bias from photochemical losses, but uncertainties arise from the accuracy of the photochemical age estimation and the assumption that the OH exposure is uniform. In this study, source contributions changed notably: motor vehicles decreased from 49.6% (observed) to a lower share in initial-based PMF, while oil and gas volatilization and petrochemical sources increased. The OFP contribution from petrochemical sources rose to 42.5% during ozone pollution, compared to 35.8% overall, indicating that these sources are more reactive and their impact is underestimated without correction.
How can these findings be applied to design effective ozone mitigation strategies in Dalian?
The results suggest that reducing emissions from petrochemical enterprises and oil/gas volatilization would be more effective in lowering ozone formation than focusing solely on motor vehicles, especially during pollution episodes. For instance, during ozone pollution, petrochemical sources contributed 42.5% to OFP based on initial concentrations, while motor vehicles contributed less. Therefore, targeted controls on petrochemical processes, storage, and transport, along with solvent use, could yield significant ozone reductions. Additionally, the high alkene loss rates (61.6% during pollution) indicate that alkenes are rapidly consumed, so controlling them at the source is critical.
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