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Volatile organic compounds (VOCs) during non-haze and haze days in Shanghai: characterization and secondary organic aerosol (SOA) formation

机译:上海非雾度和阴霾天期间挥发性有机化合物(VOC):表征和二次有机气溶胶(SOA)形成

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To better understand the characterization and secondary organic aerosol (SOA) formation of volatile organic compounds (VOCs) during non-haze and haze days, ambient VOCs were continuously measured by a vehicle-mounted online thermal desorption system coupled with a gas chromatography-mass spectrometry (TD-GC/MS) system in Shanghai, China. The average concentrations of VOCs in haze episodes (193.2 mu g m(-3)) were almost 50% higher than in non-haze periods (130.8 mu g m(-3)). VOC concentrations exhibited a bi-modal pattern in the morning and evening rush hour periods on both non-haze and haze days. The ratios of toluene to benzene (T/B) and m,p-xylene to ethylbenzene (X/E) indicated that VOCs were aged air mass transported from nearby areas. The estimated SOA yields were 12.6 +/- 5.3 and 16.7 +/- 6.7 mu g m(-3) for non-haze and haze days, respectively, accounting for 9.6 and 8.7% of the corresponding PM2.5 concentrations, which were slightly underestimated. VOCs-sensitivity (VOCs-S) based on a PM2.5-dependent model was used to investigate the variation between VOCs and PM2.5 concentrations in the morning rush hour. It was found that VOCs were more sensitive to PM2.5 on clean days than during periods of heavy particulate pollution. VOCs-sensitivity was significantly correlated with the ratio of specific PM2.5 to background PM2.5, with a simulated equation of y = 0.84x(-0.62) (r (2) = 0.93, p < 0.001). Our findings suggest that strategies to mitigate VOC emissions and further alleviate haze episodes in Shanghai based on reducing gasoline vehicle-related sources would be very efficient.
机译:为了更好地了解在非雾度和雾度期间形成挥发性有机化合物(VOC)的表征和次级有机气溶胶(SOA),通过与气相色谱 - 质谱法耦合的车载的在线热解吸系统连续测量环境VOC (TD-GC / MS)系统在中国上海,中国。雾度发作的VOC的平均浓度(193.2μgm(-3))比在非雾度周期(130.8μgm(-3)中)高近50%。 VOC浓度在早晨和晚间高峰时段在非阴霾和阴霾天展出了双模模式。甲苯与苯(T / B)和M,对二甲苯至乙基苯(X / E)的比例表明VOC值老化空气质量从附近的区域运输。估计的SOA产量为12.6 +/- 5.3和16.7 +/-6.7μmg(-3),分别用于非雾度和阴霾天,占相应PM2.5浓度的9.6%和8.7%,这略微低估了。基于PM2.5依赖模型的VOCS-敏感度(VOCS-S)用于探讨早晨高峰时段的VOC和PM2.5浓度之间的变化。发现VOC对PM2.5更敏感的清洁日,而不是重质颗粒污染期间。 VOCS-敏感性与特定PM2.5与背景PM2.5的比率显着相关,y = 0.84x(-0.62)(R(2)= 0.93,p <0.001)的模拟方程。我们的调查结果表明,基于减少汽油车辆相关来源的上海减排和进一步缓解阴霾剧集的战略将是非常有效的。

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