Sources of Nitrous Acid in the Atmospheric Boundary Layer (SNAABL)

大气边界层中亚硝酸的来源 (SNAABL)

• 批准号: NE/M013405/1
• 负责人: Eiko Nemitz
• 金额: $ 41.42万
• 依托单位: NERC CEH (Up to 30.11.2019)
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FM013405%2F1
• 关键词: Sources; Nitrous; Acid; Atmospheric; Boundary

Atmospheric chemical processing drives the removal of emitted pollutants, and leads to the formation of ozone and secondary aerosol, which are harmful to human and environmental health, and contribute to climate forcing. Reaction with the OH radical is the primary driver of these oxidation processes; OH abundance must be quantitatively understood in order to accurately predict such effects. In the free troposphere, ozone photolysis is the principal net OH source (neglecting NO-driven HOx cycling); however in the boundary layer a large body of evidence shows that nitrous acid (HONO) is an important, and sometimes the dominant, net OH precursor.Well-understood gas-phase HONO chemistry is not able to explain observed levels of HONO in the boundary layer: large additional sources, forming up to an order of magnitude more HONO, are required - however their identity remains elusive. Recent laboratory work (Su et al., Science 2011; Oswald et al., Science 2013) has identified soils as a globally significant source of HONO - driven, in part, by microbial action (analogous to the well known NO, N2O production), alongside surface NO2-to-HONO conversion mechanisms - but this microbial source has not been explored in the real environment. In urban areas, there is also increasing evidence, from field and chamber studies, that vehicles dominate HONO production - yet no data on HONO production from the UK vehicle fleet exist. Past studies have attempted to constrain HONO production through steady-state approaches, applied to co-located point measurements of OH, NO and HONO. Such analyses are however potentially hampered by the very different atmospheric lifetimes of these species, which dictates that they may not be in equilibrium in complex (spatially heterogeneous) environments. There is an urgent need for robust quantification of HONO sources, in order to quantitatively predict boundary layer HONO and OH abundance, and atmospheric chemical processing affecting air quality.Within SNAABL, we will directly measure HONO production from (1) natural ground surfaces (including soil production), and (2) road traffic emissions. Our approach will focus upon real-world environmental behaviour, and will avoid the uncertainties associated with analyses of ambient HONO concentrations. (1) Natural Ground Surfaces. We will measure surface HONO fluxes from contrasting agricultural and unmanaged environments, and relate these to NOx and N2O fluxes and physical, chemical atmospheric and soil parameters. Fertiliser manipulation experiments will assess the impact of nutrient addition at a unique field location permitting simultaneous measurement of perturbed- and control systems. We will also perform laboratory studies of natural surface HONO production, using soil cores from our field sites and other UK locations. Through manipulation and selective sterilisation, we will isolate and characterise the potential abiotic and microbial HONO production mechanism(s), including surface processes. (2) Traffic Emissions. We will directly determine HONO production from traffic, through measurement of HONO, NOx and CO2 in a road tunnel, an approach which provides a single, well characterised (video monitoring) source term, and removes the confounding factors of multiple sources, dispersion and photochemistry found in the ambient atmosphere. This approach will reflect the real-world fleet emissions, rather than potentially artificial results from dynamometer driving cycles. We will use our data to parameterise the resulting HONO source terms, and assess their accuracy, and implications for boundary layer air quality, using photochemical box and regional chemistry-transport modelling. SNAABL will deliver quantitative understanding of HONO production from natural surfaces and vehicle traffic, and so substantially improve the accuracy of predictions of boundary layer atmospheric chemical processing.

大气中的化学处理推动了排放污染物的清除，并导致臭氧和二次气溶胶的形成，这对人类和环境健康有害，并导致气候强迫。与OH自由基的反应是这些氧化过程的主要驱动力;为了准确预测这些影响，必须定量地了解OH丰度。在自由对流层中，臭氧光解是主要的净OH源（忽略NO驱动的HOx循环）;然而，在边界层中，大量证据表明亚硝酸（HONO）是一种重要的，有时是主要的净OH前体。众所周知的气相HONO化学不能解释边界层中观察到的HONO水平：需要形成高达一个数量级的HONO的大量额外的源-然而它们的身份仍然难以捉摸。最近的实验室工作（Su et al.，Science 2011; Oswald等人，Science 2013）已经将土壤确定为HONO的全球重要来源-部分由微生物作用（类似于众所周知的NO、N2 O产生）驱动，以及表面NO2-至-HONO转化机制-但这种微生物来源尚未在真实的环境中探索。在城市地区，也有越来越多的证据表明，从现场和室内研究，车辆占主导地位的HONO生产-但没有数据的HONO生产从英国车队存在。过去的研究试图通过稳态方法来限制HONO的产生，应用于OH，NO和HONO的同位点测量。然而，这些物种在大气中的寿命差异很大，这就意味着它们在复杂（空间异质性）环境中可能不会处于平衡状态，这可能会妨碍这种分析。为了定量预测边界层HONO和OH丰度以及影响空气质量的大气化学过程，迫切需要对HONO来源进行可靠的量化。在SNAABL中，我们将直接测量（1）自然地表（包括土壤产生）和（2）道路交通排放的HONO产生。我们的方法将侧重于现实世界的环境行为，并将避免与环境HONO浓度分析相关的不确定性。(1)自然地面。我们将测量对比农业和非管理环境的表面HONO通量，并将其与NOx和N2 O通量以及物理，化学大气和土壤参数联系起来。肥料操作实验将评估在一个独特的田间位置，允许同时测量扰动和控制系统的养分添加的影响。我们还将使用我们的现场和其他英国地点的土芯对自然表面HONO生产进行实验室研究。通过操作和选择性灭菌，我们将分离和鉴定潜在的非生物和微生物HONO生产机制，包括表面过程。(2)交通排放。我们将通过测量公路隧道中的HONO、NOx和CO2来直接确定交通中的HONO产生量，这种方法提供了一个单一的、表征良好的（视频监控）源项，并消除了环境大气中发现的多个源、分散和光化学的混杂因素。这种方法将反映真实世界的车队排放，而不是潜在的人工结果，从测功机驾驶循环。我们将使用我们的数据参数化的HONO源项，并评估其准确性，边界层空气质量的影响，使用光化学箱和区域化学传输模型。SNAABL将提供对自然表面和车辆交通产生的HONO的定量了解，从而大大提高边界层大气化学过程预测的准确性。

项目成果

Quantification of within-vehicle exposure to NOx and particles: Variation with outside air quality, route choice and ventilation options

车内氮氧化物和颗粒物暴露的量化：随外部空气质量、路线选择和通风选项的变化

• DOI: 10.1016/j.atmosenv.2020.117810
• 发表时间: 2020
• 期刊: Atmospheric Environment
• 影响因子: 5
• 作者: Matthaios V

Intercomparison of nitrous acid (HONO) measurement techniques in a megacity (Beijing)

• DOI: 10.5194/amt-12-6449-2019
• 发表时间: 2019-12-09
• 期刊: ATMOSPHERIC MEASUREMENT TECHNIQUES
• 影响因子: 3.8
• 作者: Crilley, Leigh R.;Kramer, Louisa J.;Bloss, William J.
• 通讯作者: Bloss, William J.

Insights into air pollution chemistry and sulphate formation from nitrous acid (HONO) measurements during haze events in Beijing.

• DOI: 10.1039/d0fd00100g
• 发表时间: 2020-12
• 期刊: Faraday discussions
• 影响因子: 3.4
• 作者: W. Bloss;L. Kramer;L. Crilley;T. Vu;R. Harrison;Zongbo Shi;James D. Lee;F. Squires;L. Whalley;Eloise J. Slater;Robert Woodward-Massey;C. Ye;D. Heard;Shengrui Tong;S. Hou;Yele Sun;Jingsha Xu;Lianfang Wei;P. Fu

Predicting real-time within-vehicle air pollution exposure with mass-balance and machine learning approaches using on-road and air quality data

• DOI: 10.1016/j.atmosenv.2023.120233
• 发表时间: 2023-11
• 期刊: Atmospheric Environment
• 影响因子: 5
• 作者: V. Matthaios;Luke D. Knibbs;L. Kramer;L. Crilley;W. Bloss

Concentrations and biosphere-atmosphere fluxes of inorganic trace gases and associated ionic aerosol counterparts over the Amazon rainforest

亚马逊雨林上空无机微量气体和相关离子气溶胶对应物的浓度和生物圈-大气通量

• DOI: 10.5194/acp-20-15551-2020
• 发表时间: 2020
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: Ramsay R