Xiaoyu Liang, Jianfei Peng, Yan Liu, Jinsheng Zhang, Lin Wu, Hongjun Mao
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引用次数: 0
Abstract
Tunnel experiments are widely used to determine fleet-average vehicle emission factors (EFs) under real-world conditions. However, limited sampling locations often lead to inaccuracies due to spatial heterogeneity in wind and pollutant dispersion. This study integrates CFD modeling with tunnel measurements to quantify and correct such errors. Simulations reveal that EFs derived from field measurements alone can be underestimated by up to 40 %, particularly under low traffic density and weak natural wind conditions. The estimated correction schemes for EFs were evaluated and validated using practical case studies. The results showed that the average EFs of NOx, CO, and PM2.5 for the tunnel fleet were underestimated by approximately 24.50, 161.66, and 3.33 mg km−1·veh−1, respectively. Although the corrected EFs for diesel vehicles remain significantly higher than those for petrol vehicles, their relative contribution to the fleet-average EFs is notably reduced. The CFD analysis also highlights that external atmospheric conditions strongly influence internal tunnel flows, especially within 200 m of the entrance, offering valuable guidance for tunnel siting and sampling strategies. This study enhances the reliability of tunnel-derived EFs and supports the standardization of tunnel experiment protocols, contributing to more accurate emission inventories and targeted air quality management policies.
期刊介绍:
Environmental Pollution is an international peer-reviewed journal that publishes high-quality research papers and review articles covering all aspects of environmental pollution and its impacts on ecosystems and human health.
Subject areas include, but are not limited to:
• Sources and occurrences of pollutants that are clearly defined and measured in environmental compartments, food and food-related items, and human bodies;
• Interlinks between contaminant exposure and biological, ecological, and human health effects, including those of climate change;
• Contaminants of emerging concerns (including but not limited to antibiotic resistant microorganisms or genes, microplastics/nanoplastics, electronic wastes, light, and noise) and/or their biological, ecological, or human health effects;
• Laboratory and field studies on the remediation/mitigation of environmental pollution via new techniques and with clear links to biological, ecological, or human health effects;
• Modeling of pollution processes, patterns, or trends that is of clear environmental and/or human health interest;
• New techniques that measure and examine environmental occurrences, transport, behavior, and effects of pollutants within the environment or the laboratory, provided that they can be clearly used to address problems within regional or global environmental compartments.