CondensabLe AeRosol from non Ideal Stove Emissions (CLARISE)
非理想炉排放产生的冷凝气溶胶 (CLARISE)
基本信息
- 批准号:NE/X000923/1
- 负责人:
- 金额:$ 82.46万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Domestic wood burning is now the dominant direct source of airborne particulate matter less than 2.5 microns (PM2.5) in the UK (~38 % of the total in 2019 according to the National Atmospheric Emissions Inventory) and can account for a high fraction of the carcinogenic potential of particles even in urban areas. Current emission inventories underestimate the impact of residential wood burning, as they focus on optimum use conditions and exclude condensable material, which can contribute to both primary emissions and secondary aerosol production. Based on evidence from recent studies of wood combustion, we propose that 'non-ideal' operational conditions, including ignition, reloading, maloperation and use of unconventional fuels are a large and unaccounted for source of particulate pollution in the UK. The CLARISE project brings together unique expertise in biomass burning experiments, emissions monitoring, atmospheric complexity analysis and regional modelling. We will study emissions from domestic heating stoves, under a range of non-ideal conditions, providing high time resolution measurements of transient event emissions during operation. CLARISE will study wood burning in a dedicated stove test facility at the University of Manchester and will use a combination of state of the art online instruments that can capture the transient emissions with a high time resolution. An oxidation flow reactor (OFR) will be used to simulate the effect of atmospheric chemical ageing on the emissions and allow insight into the formation of secondary, or 'condensable' particulate. Gas and particulate samples will also be collected for subsequent analysis in the laboratory at the University of York. A novel suite of mass spectrometric methods will be used to generate volatility profiles of the emissions under both ideal and non-ideal conditions, using the popular Volatility Basis Set (VBS) approach. Where molecules are identified in the secondary particulate, these will be compared against the Master Chemical Mechanism (MCM), the gold standard explicit atmospheric organic chemistry model, in order to identify gaps in mechanistic understanding that should be targeted for future studies on reaction kinetics.The experimental data and parameterised outputs will then be used in regional atmospheric model simulations to predict the relative amounts of secondary particulate that can be expected from both the ideal and the non-ideal emissions relative to the ideal primary particulate that is already accounted for in the national inventory. This will allow us to assess not only the relative importance of non-ideal emissions but also their estimated contribution to PM2.5 in the UK and beyond. We will also produce a schedule of emission modes, fuels and emitted VOCs that will be of interest to the scientific community, stove manufacturers/installers, the third sector and policymakers, as many of the problem non-ideal areas can potentially be addressed by user education, engineering controls in the stoves and policy interventions.
家庭木材燃烧现在是英国小于2.5微米的空气颗粒物(PM2.5)的主要直接来源(根据国家大气排放清单,2019年约占总量的38%),即使在城市地区,也可能占颗粒物致癌潜力的很大一部分。目前的排放清单低估了住宅木材燃烧的影响,因为它们侧重于最佳使用条件,并排除了可冷凝材料,而可冷凝材料可能有助于一次排放和二次气溶胶的产生。根据最近的木材燃烧研究的证据,我们建议,“非理想”的操作条件,包括点火,重装,误操作和使用非常规燃料是一个大的和不明来源的颗粒物污染在英国。该项目汇集了生物质燃烧实验,排放监测,大气复杂性分析和区域建模方面的独特专业知识。我们将研究在一系列非理想条件下家用采暖炉的排放,提供运行过程中瞬态事件排放的高时间分辨率测量。EQUISE将在曼彻斯特大学的专用炉灶测试设施中研究木材燃烧,并将使用最先进的在线仪器组合,这些仪器可以以高时间分辨率捕获瞬态排放。氧化流动反应器(OFR)将用于模拟大气化学老化对排放物的影响,并允许深入了解二次或“可冷凝”颗粒的形成。还将收集气体和微粒样本,供随后在约克大学的实验室进行分析。一套新的质谱方法将被用来生成在理想和非理想条件下的排放的挥发性配置文件,使用流行的挥发性基集(VBS)的方法。在二次颗粒物中识别出分子的情况下,这些分子将与主化学机理(MCM)进行比较,MCM是黄金标准明确的大气有机化学模型,为了确定在机理理解方面的差距,应针对未来的反应动力学研究。实验数据和参数化的输出将用于区域大气模型模拟,以预测二次污染的相对数量。相对于国家清单中已经考虑的理想主要颗粒物,可以从理想和非理想排放中预期的颗粒物。这将使我们不仅能够评估非理想排放的相对重要性,还可以评估它们对英国及其他地区PM2.5的估计贡献。我们还将制定一份排放模式、燃料和挥发性有机化合物排放时间表,这将引起科学界、炉灶制造商/安装商、第三部门和政策制定者的兴趣,因为许多问题非理想领域可以通过用户教育、炉灶工程控制和政策干预来解决。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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James Allan其他文献
A Single Nucleotide Resolution Model for Large-Scale Simulations of Double Stranded DNA
用于大规模模拟双链 DNA 的单核苷酸分辨率模型
- DOI:
10.1101/069310 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Y. G. Fosado;D. Michieletto;James Allan;C. Brackley;O. Henrich;D. Marenduzzo - 通讯作者:
D. Marenduzzo
Introduction to topic detection and tracking
- DOI:
10.1007/978-1-4615-0933-2_1 - 发表时间:
2002 - 期刊:
- 影响因子:0
- 作者:
James Allan - 通讯作者:
James Allan
A semantic data framework to support data-driven demand forecasting
支持数据驱动的需求预测的语义数据框架
- DOI:
10.1088/1742-6596/2600/2/022001 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
James Allan;Francesca Mangili;Marco Derboni;Luis Gisler;A. Hainoun;A. Rizzoli;Luca Ventriglia;M. Sulzer - 通讯作者:
M. Sulzer
Using CrowdLogger for in situ information retrieval system evaluation
使用CrowdLogger进行现场信息检索系统评估
- DOI:
10.1145/2513150.2513164 - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
H. Feild;James Allan - 通讯作者:
James Allan
Reranking search results for sparse queries
对稀疏查询的搜索结果重新排序
- DOI:
10.1145/2063576.2063606 - 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Elif Aktolga;James Allan - 通讯作者:
James Allan
James Allan的其他文献
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{{ truncateString('James Allan', 18)}}的其他基金
III: Medium: Collaborative Research: Athena: Learning-oriented Search with Personalized Learning Flows
III:媒介:协作研究:Athena:具有个性化学习流程的面向学习的搜索
- 批准号:
2106282 - 财政年份:2021
- 资助金额:
$ 82.46万 - 项目类别:
Continuing Grant
EAGER: Dynamic Contextual Explanation of Search Results
EAGER:搜索结果的动态上下文解释
- 批准号:
2039449 - 财政年份:2020
- 资助金额:
$ 82.46万 - 项目类别:
Standard Grant
CRI: CI-SUSTAIN: Collaborative Research: Sustaining Lemur Project Resources for the Long-Term
CRI:CI-SUSTAIN:合作研究:长期维持狐猴项目资源
- 批准号:
1822986 - 财政年份:2018
- 资助金额:
$ 82.46万 - 项目类别:
Standard Grant
Soot Aerodynamic Size Selection for Optical properties (SASSO)
光学特性烟灰空气动力学尺寸选择 (SASSO)
- 批准号:
NE/S00212X/1 - 财政年份:2018
- 资助金额:
$ 82.46万 - 项目类别:
Research Grant
III: Small: Mirador: Explainable Computational Models for Recognizing and Understanding Controversial Topics Encountered Online
III:小:Mirador:用于识别和理解网上遇到的有争议话题的可解释计算模型
- 批准号:
1813662 - 财政年份:2018
- 资助金额:
$ 82.46万 - 项目类别:
Standard Grant
I-Corps: Probabilistically Detecting Controversy
I-Corps:概率性检测争议
- 批准号:
1721069 - 财政年份:2017
- 资助金额:
$ 82.46万 - 项目类别:
Standard Grant
Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux) - Manchester
大城市德里大气排放量化、评估和影响 (DelhiFlux) - 曼彻斯特
- 批准号:
NE/P016472/1 - 财政年份:2016
- 资助金额:
$ 82.46万 - 项目类别:
Research Grant
Sources and Emissions of Air Pollutants in Beijing (Manchester)
北京(曼彻斯特)空气污染物来源及排放
- 批准号:
NE/N007123/1 - 财政年份:2016
- 资助金额:
$ 82.46万 - 项目类别:
Research Grant
III: Small: Interactive Construction of Complex Query Models
III:小:复杂查询模型的交互构建
- 批准号:
1617408 - 财政年份:2016
- 资助金额:
$ 82.46万 - 项目类别:
Standard Grant
III: Small: Topical Positioning System (TPS) for Informed Reading of Web Pages
III:小:网页知情阅读的主题定位系统(TPS)
- 批准号:
1217281 - 财政年份:2012
- 资助金额:
$ 82.46万 - 项目类别:
Standard Grant
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