Local Atmospheric Ozone Production Perturbation Instrument - Proof of Concept

当地大气臭氧产生扰动仪器 - 概念验证

• 批准号: NE/I000674/1
• 负责人: William Bloss
• 金额: $ 17.83万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI000674%2F1
• 关键词: Local; Atmospheric; Ozone; Production; Perturbation

Ozone is a major pollutant in the lower atmosphere, known to be harmful to human health, ecosystems, vegetation and certain materials. Ozone is produced as a consequence of the atmospheric degradation of VOCs (Volatile Organic Compounds) in the presence of oxides of nitrogen (NOx). As ozone is a secondary pollutant, control of ozone levels is not straightforward, with ozone production rate showing a highly non-linear dependence upon NOx and VOC levels. Detailed atmospheric chemistry models may be used to inform air quality strategies for ozone abatement, however the link between model predictions, emission controls and ozone production rates is hard to evaluate, as a combination of in situ ozone production, local chemical effects and transport all contribute to variations in ozone levels at a given site. Moreover, even the most detailed models (or measurements) cannot incorporate all atmospheric processes (or species), and model mechanisms are subject to ongoing development. The aim of this project is to test a new approach to directly measure the local atmospheric ozone production rate, and its dependence upon chemical and physical conditions. By perturbing the ambient chemical conditions (for example, through addition of NOx or VOCs), and measuring the effect of the perturbation upon the local ozone production rate, this technology will allow the efficacy of air quality strategies to be directly evaluated (and the importance of local production vs. transport determined). By comparing the measured (and perturbed) ozone production rate with that predicted using atmospheric models, our understanding of the underlying chemical processes may be tested. The fundamental approach will be to sample ambient air into reactors with residence times of a few minutes, exposed to either ambient light or ambient light with the UV component removed. In the former, ozone production continues as in the ambient atmosphere, while in the latter, the ozone production chemistry is switched off by excluding UV light, allowing an ozone baseline to be determined. By comparing the ozone levels exiting each reactor (strictly, O3 + NO2), the in situ ozone production rate may be deduced. By adding reagents to the sampled airstream, the effects of perturbations to the ambient conditions may be investigated and the extent of VOC vs. NOx control may be established. By illuminating the chambers artificially with a controlled spectral distribution, the importance of different chemical mechanisms driving ozone production may be tested. The project will deliver proof-of concept data for a new approach to perform perturbed ozone production rate measurements. Future development of this technology will enable atmospheric measurements which will improve our understanding of the rate of, and most efficient controls upon, atmospheric ozone production. Such measurements will be of considerable use to atmospheric scientists, policy makers and air quality practitioners.

臭氧是低大气中的主要污染物，已知对人类健康，生态系统，植被和某些材料有害。在存在氮氧化物（NOX）的情况下，VOC（挥发性有机化合物）的大气降解而产生的臭氧。由于臭氧是一种次要污染物，因此对臭氧水平的控制并不直接，臭氧的生产率显示出高度非线性的依赖性对NOX和VOC水平。详细的大气化学模型可用于为消除臭氧的空气质量策略提供信息，但是，很难评估模型预测，排放控制与臭氧生产率之间的联系，因为原位臭氧的产生，局部化学效应和运输都在给定位点在臭氧水平上有助于变化。此外，即使是最详细的模型（或测量）也无法纳入所有大气过程（或物种），并且模型机制也会持续发展。该项目的目的是测试一种新方法，以直接测量当地大气臭氧的生产率及其对化学和物理状况的依赖。通过扰动环境化学条件（例如，通过添加NOX或VOC），测量扰动对本地臭氧生产率的影响，该技术将允许直接评估空气质量策略的功效（以及本地生产与确定的本地生产的重要性）。通过将测得的（和干扰）臭氧的生产率与使用大气模型的预测进行比较，我们可以测试我们对基本化学过程的理解。基本方法是将环境空气采样到停留时间为几分钟的反应堆，暴露于环境光或环境光中，并取出了紫外线分量。在前者中，臭氧的产量像在环境大气中一样继续，而在后者中，臭氧产量化学反应是通过排除紫外光来关闭的，从而可以确定臭氧基线。通过比较退出每个反应器的臭氧水平（严格，O3 + NO2），可以推导原位臭氧的产量。通过将试剂添加到采样的气流中，可以研究扰动对环境条件的影响，并且可以建立VOC与NOX控制的程度。通过用受控的光谱分布人为地照亮钱伯斯，可以测试驱动臭氧产生的不同化学机制的重要性。该项目将提供概念验证数据的新方法，以执行扰动的臭氧生产率测量。这项技术的未来开发将实现大气测量，这将提高我们对大气臭氧生产的速度，最有效控制的理解。这种测量将对大气科学家，政策制定者和空中质量从业人员有很大的用途。