State Environmental Protection Key Laboratory of Cause and Prevention of Urban Air Pollution Complex , Shanghai Academy of Environmental Sciences , Shanghai , 200233 , China.
School of Resources and Environment Engineering , East China University of Science and Technology , Shanghai , 200237 , China.
Environ Sci Technol. 2018 Oct 2;52(19):11223-11231. doi: 10.1021/acs.est.8b03984. Epub 2018 Sep 11.
Motor vehicle ammonia (NH) emissions have attracted increasing attention for their potential to form secondary aerosols in urban atmospheres. However, vehicle NH emission factors (EFs) remain largely unknown due to a lack of measurements. Thus, we conducted detailed measurements of NH emissions from 18 Euro 2 to Euro 5 light-duty gasoline vehicles (LDGVs) in Shanghai, China. The distance- and fuel-based NH EFs average 29.2 ± 24.1 mg·km and 0.49 ± 0.41 g·kg, respectively. The average NH-to-CO ratio is 0.41 ± 0.34 ppbv·ppmv. The measurements reveal that NH emissions from LDGVs are strongly correlated with both vehicle specific power (VSP) and the modified combustion efficiency (MCE); these relationships were used to predict LDGV NH EFs via a newly developed model. The predicted LDGV NH EFs under urban and highway driving cycles are 23.3 mg·km and 84.5 mg·km, respectively, which are consistent with field measurements. The NH EF has decreased by 32% in average since the implementation of vehicle emission control policies in China five years ago. The model presented herein more accurately predicts LDGV NH emissions, contributing substantially to the compilation of NH emission inventories and prediction of future motor vehicle emissions in China.
机动车氨气（NH）排放因其在城市大气中形成二次气溶胶的潜力而引起了越来越多的关注。然而，由于缺乏测量，车辆 NH 排放因子（EF）仍然很大程度上未知。因此，我们在中国上海对 18 辆欧 2 至欧 5 轻型汽油车（LDGV）的 NH 排放进行了详细测量。基于距离和燃料的 NH EF 平均值分别为 29.2 ± 24.1 mg·km 和 0.49 ± 0.41 g·kg。NH 与 CO 的比值平均为 0.41 ± 0.34 ppbv·ppmv。测量结果表明，LDGV 的 NH 排放与车辆比功率（VSP）和改进燃烧效率（MCE）密切相关；这些关系被用于通过新开发的模型预测 LDGV NH EF。城市和高速公路行驶循环下预测的 LDGV NH EF 分别为 23.3 mg·km 和 84.5 mg·km，与现场测量结果一致。自五年前中国实施车辆排放控制政策以来，NH EF 平均降低了 32%。本文提出的模型更准确地预测了 LDGV 的 NH 排放，为 NH 排放清单的编制和中国未来机动车排放的预测做出了重要贡献。
