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Published on: December 4, 2016
Intermediate-Volatility Organic Compound Emissions from Nonroad Construction Machinery under Different Operation
Lijuan Qi1,2, Huan Liu1,2, Xiu'e Shen3
1State Key Joint Laboratory of ESPC, School of Environment , Tsinghua University , Beijing 100084 , China.
Intermediate-volatility organic compounds (IVOCs) from nonroad construction machineries are significant contributors to secondary organic aerosol (SOA) formation. Idling modes produced substantially higher IVOC emissions, impacting urban air quality.
Area of Science:
- Atmospheric Chemistry
- Environmental Science
- Combustion Emissions
Background:
- Intermediate-volatility organic compounds (IVOCs) are key precursors to secondary organic aerosol (SOA).
- Nonroad construction machineries (NRCMs) are prevalent in urban environments, but their IVOC emissions are not well quantified.
- Understanding IVOC emissions is crucial for accurate SOA formation modeling.
Purpose of the Study:
- To characterize IVOC emissions from NRCMs.
- To compare IVOC emission factors across different operation modes.
- To assess the SOA production potential of NRCM-emitted IVOCs.
Main Methods:
- Utilized an improved portable emission measurement system to quantify IVOCs from road rollers and motor graders.
- Analyzed IVOC composition, identifying unspeciated b-alkanes and cyclic compounds as major components.
- Performed SOA production potential analysis.
Main Results:
- Fuel-based IVOC emission factors (EFs) ranged from 245.85 to 1802.19 mg/kg·fuel, comparable to other diesel sources.
- Idling mode exhibited 1.24–3.28 times higher IVOC EFs than moving/working modes.
- Unspeciated compounds constituted approximately 91% of total IVOCs, and IVOCs dominated SOA formation potential.
Conclusions:
- NRCMs are a significant, previously underestimated source of IVOC emissions.
- IVOC emissions from NRCMs, particularly during idling, substantially contribute to SOA formation in urban atmospheres.
- Accurate assessment of NRCM IVOC emissions is vital for urban air quality management and SOA modeling.
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