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Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter. 模型空间分辨率对全球地球物理卫星得出的细颗粒物的影响。
Pub Date : 2024-07-29 eCollection Date: 2024-09-13 DOI: 10.1021/acsestair.4c00084
Dandan Zhang, Randall V Martin, Aaron van Donkelaar, Chi Li, Haihui Zhu, Alexei Lyapustin

Global geophysical satellite-derived ambient fine particulate matter (PM2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R 2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM2.5 from columnar AOD.

全球地球物理卫星得出的环境细颗粒物(PM2.5)推断依赖于化学传输模型中的地球物理关系(η),将卫星获取的气溶胶光学深度(AOD)与地表 PM2.5 联系起来。模拟η与分辨率的关系值得进一步研究。在这项研究中,我们利用高性能配置(GCHP)下的 GEOS-Chem 模型模拟 η 计算了地球物理 PM2.5,其立方球分辨率为 C360(∼25 公里)和 C48(∼200 公里),卫星 AOD 为 0.01°(∼1 公里)。从卫星 AOD 和 GCHP 模拟推断出的年地球物理 PM2.5 浓度在 25 千米和 200 千米分辨率下表现出显著的相似性(R 2 = 0.96,斜率 = 1.03)。这种相似性在一定程度上反映了各成分对分辨率的相反反应,在更精细的分辨率下,初级物种的种群加权归一化平均差(PW-NMD)增加了 5%到 11%,而次级物种的种群加权归一化平均差(PW-NMD)则减少了-30%到-5%。尽管具有全球相似性,但我们的结果还发现,在孤立的污染源和山区,η 的分辨率敏感性更大,在这些地区,气溶胶浓度和组成的空间对比在精细分辨率下表现得更好。我们的结果凸显了近地表浓度和不同化学成分的垂直分布对分辨率的依赖性,这对从柱状 AOD 推断地面 PM2.5 有一定影响。
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引用次数: 0
Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter 模型空间分辨率对全球地球物理卫星得出的细颗粒物的影响
Pub Date : 2024-07-29 DOI: 10.1021/acsestair.4c0008410.1021/acsestair.4c00084
Dandan Zhang*, Randall V. Martin, Aaron van Donkelaar, Chi Li, Haihui Zhu and Alexei Lyapustin, 

Global geophysical satellite-derived ambient fine particulate matter (PM2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by −30% to −5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM2.5 from columnar AOD.

全球地球物理卫星得出的环境细颗粒物(PM2.5)推断依赖于化学传输模型中的地球物理关系(η),将卫星获取的气溶胶光学深度(AOD)与地表 PM2.5 联系起来。模拟η与分辨率的关系值得进一步研究。在这项研究中,我们利用高性能配置(GCHP)下的 GEOS-Chem 模型模拟 η 计算了地球物理 PM2.5,其立方球分辨率为 C360(∼25 公里)和 C48(∼200 公里),卫星 AOD 为 0.01°(∼1 公里)。从卫星 AOD 和 GCHP 模拟推断出的年地球物理 PM2.5 浓度在 25 千米和 200 千米分辨率下表现出显著的相似性(R2 = 0.96,斜率 = 1.03)。这种相似性在一定程度上反映了各成分的分辨率反应相反,在更精细的分辨率下,初级物种的种群加权归一化平均差(PW-NMD)增加了 5%到 11%,而次级物种则减少了-30%到-5%。尽管具有全球相似性,但我们的结果还发现,在孤立的污染源和山区,η 的分辨率敏感性更大,在这些地区,气溶胶浓度和组成的空间对比在精细分辨率下表现得更好。我们的结果凸显了近地表浓度和不同化学成分的垂直分布对分辨率的依赖性,这对从柱状 AOD 推断地面 PM2.5 有一定影响。
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引用次数: 0
Chemical Insights into the Molecular Composition of Organic Aerosols in the Urban Region of Houston, Texas 德克萨斯州休斯顿城市地区有机气溶胶分子组成的化学洞察力
Pub Date : 2024-07-27 DOI: 10.1021/acsestair.4c0014110.1021/acsestair.4c00141
Tania Gautam, Gregory W. Vandergrift, Nurun Nahar Lata, Zezhen Cheng, Ashfiqur Rahman, Annalisa Minke, Zhenli Lai, Darielle N. Dexheimer, Damao Zhang, Matthew A. Marcus, Maria A. Zawadowicz, Chongai Kuang, Ran Zhao, Allison L. Steiner and Swarup China*, 

Molecular functional groups, such as organosulfates (CHOS) and organonitrates (CHNO) are important tracers for field observations of secondary organic aerosols (SOA). While CHOS and CHNO are prevalent in the atmosphere, there is a lack of knowledge regarding daily and day- and night-time variations in these species in the urban atmosphere. Meteorological factors such as wind speed/direction, relative humidity (RH), and temperature can influence the formation of CHOS/CHNO. To investigate these trends, we utilized multimodal chemical imaging and advanced high resolution mass spectrometry techniques to acquire particle speciation and molecular formulas (MFs) associated with day and night sampling periods. Back trajectory analyses revealed the oceanic influence of southern wind airmasses in later June sampling periods with organic fractions <10%. Conversely, northern winds in early June sampling periods contributed to the episodic emergence of extremely low volatile organics (ELVOCs) and organic factions up to 41%. The observed unique MFs to June 3 (223 MFs) and to June 4 (144 MFs) were largely found to be of biogenic rather than anthropogenic origin. Our findings reveal episodic prevalence and temporal distribution of SOA constituents across the urban region of Houston, Texas.

有机硫酸盐(CHOS)和有机硝酸盐(CHNO)等分子官能团是实地观测二次有机气溶胶(SOA)的重要示踪剂。虽然 CHOS 和 CHNO 在大气中普遍存在,但人们对这些物种在城市大气中的日变化和昼夜变化缺乏了解。风速/风向、相对湿度(RH)和温度等气象因素会影响 CHOS/CHNO 的形成。为了研究这些趋势,我们利用多模态化学成像和先进的高分辨率质谱技术,获取了与白天和夜间采样时段相关的颗粒规格和分子式(MF)。回溯轨迹分析表明,在 6 月晚些时候的采样时段,南风气团受海洋影响,有机物含量为 10%。相反,6 月初采样时段的北风导致了极低挥发性有机物(ELVOCs)的偶发出现,有机物含量高达 41%。在 6 月 3 日(223 个 MFs)和 6 月 4 日(144 个 MFs)观测到的独特 MFs 大部分是生物源而非人为源。我们的研究结果揭示了得克萨斯州休斯顿城市地区 SOA 成分的偶发性流行和时间分布。
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引用次数: 0
Determination of Legacy and Emerging Per- and Polyfluoroalkyl Substances (PFAS) in Indoor and Outdoor Air 测定室内外空气中遗留的和新出现的全氟和多氟烷基物质 (PFAS)
Pub Date : 2024-07-25 DOI: 10.1021/acsestair.4c0009510.1021/acsestair.4c00095
Wen-Long Li,  and , Kurunthachalam Kannan*, 

Despite increasing awareness of health risks associated with exposure to per- and polyfluoroalkyl substances (PFAS), studies on analysis of these chemicals in air are limited. In this study, an extensive sampling of indoor and outdoor air (at a residential neighborhood) was performed to determine the occurrence, temporal variation, and gas/particle partitioning of PFAS. Among 58 PFAS analyzed in air (sum of gas and particulate phases), fluorotelomer alcohols (FTOHs) were found at the highest concentrations (1900 ± 2000 pg/m3). The concentrations of FTOHs and perfluorooctane sulfonamides (FOSA/E) were 4.9−5.9 times higher in indoor air than those in residential outdoor air (p < 0.05). Emerging PFAS such as hexafluoropropylene oxide dimer acid (HFPO-DA), chlorinated polyfluoroether sulfonate (Cl-PFESA), and ADONA were detected at average concentrations ranging from 0.10 to 4.4 pg/m3. We found significant temporal variations in PFAS concentrations, with concentrations higher in warmer than colder months. The majority of ionic PFAS (>50%) such as PFOS were detected in the particulate phase, whereas FTOHs partition predominantly to the vapor phase. This study establishes baseline indoor air concentrations of emerging PFAS and contributes to the understanding of gas−particle partitioning of PFAS.

尽管人们越来越意识到接触全氟烷基和多氟烷基物质(PFAS)会对健康造成危害,但对这些化学物质在空气中的分析研究却十分有限。本研究对室内和室外空气(一个居民区)进行了广泛采样,以确定 PFAS 的出现、时间变化和气体/微粒分配情况。在空气中分析的 58 种 PFAS(气相和微粒相的总和)中,氟代醇(FTOHs)的浓度最高(1900 ± 2000 pg/m3)。室内空气中 FTOHs 和全氟辛烷磺酰胺 (FOSA/E) 的浓度是室外住宅空气中浓度的 4.9-5.9 倍(p < 0.05)。新出现的全氟烷烃类物质,如六氟环氧丙烷二聚酸 (HFPO-DA)、氯化聚氟醚磺酸盐 (Cl-PFESA) 和 ADONA 的平均检测浓度为 0.10 至 4.4 pg/m3。我们发现,PFAS 的浓度存在明显的时间差异,温暖月份的浓度高于寒冷月份。大多数离子型 PFAS(50%)(如全氟辛烷磺酸)是在颗粒物中检测到的,而 FTOHs 则主要分布在气相中。这项研究确定了室内空气中新出现的全氟辛烷磺酸的基准浓度,有助于人们了解全氟辛烷磺酸的气体-颗粒分配。
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引用次数: 0
Secondary Organic Aerosol Formation from Aqueous Ethylamine Oxidation Mediated by Particulate Nitrate Photolysis 由颗粒硝酸盐光解介导的乙胺水溶液氧化形成二次有机气溶胶
Pub Date : 2024-07-22 DOI: 10.1021/acsestair.3c0009510.1021/acsestair.3c00095
Xiaomeng Tian, Valeria YeeWan Chan and Chak K. Chan*, 

Atmospheric ethylamine (EA) is emitted by various primary sources and can be found abundantly in the gas and particle phases. Nitrate (NO3) is one of the most abundant inorganic compounds and has been found to coexist with amines in ambient particles. The photolysis of NO3 can produce oxidants such as the OH radical, NO2, O(3P), and N(III), which can lead to the decay of particulate EA. Moreover, the degradation of EA forms carbonyl species, which are precursors to brown carbon (BrC) formation. In this study, we investigated the aging of EA-containing particles mediated by NO3 photolysis under different relative humidity (RH) and initial pH conditions under 300 nm UV irradiation. The more acidic (pH 0.0, 0.2, and 0.6) particles (EA:H+ molar ratio = 4:4.25, 4:4.5, 4:5 at 70% RH) exhibited an increase in pH, while the less acidic (pH 5.0, 4.8, 4.7, and 5.1) particles (EA:H+ = 4:4 at 40%, 55%, 70%, and 85% RH) showed a decrease in pH as a result of photooxidation. We attributed these contrary pH changes to the combination of the HONO evaporation, which increases the pH, and the EA reactions, which decrease the pH. The decay rates of NO3 and EA appear not to be sensitive to RH and pH within experimental uncertainties. We proposed EA reaction pathways in the presence of oxidants produced from NO3 photolysis based on product speciation. We also observed the formation of water-soluble organics (BrC and an organic phase) as a potential secondary organic aerosol (SOA). This study sheds light on the particulate sink of EA and its potential in BrC and SOA formation mediated by NO3 photolysis in the atmosphere, providing new insights into the aging of amines in atmospheric aerosols.

This study shows particulate ethylamine decay during nitrate photolysis could form water-soluble secondary organics (BrC and an organic phase), providing insight into the atmospheric amine sink and aging.

大气中的乙胺(EA)由各种主要来源排放,在气相和颗粒相中含量丰富。硝酸盐(NO3-)是最丰富的无机化合物之一,已被发现与胺共存于环境颗粒物中。NO3- 的光解可产生氧化剂,如 OH 自由基、NO2、O(3P) 和 N(III),从而导致颗粒 EA 的衰变。此外,EA 降解会形成羰基物种,而羰基物种是褐碳(BrC)形成的前体。在本研究中,我们研究了在 300 纳米紫外线照射下,不同相对湿度(RH)和初始 pH 值条件下,NO3- 光解介导的含 EA 颗粒老化过程。酸性较强(pH 值为 0.0、0.2 和 0.6)的颗粒(EA:H+ 摩尔比 = 4:4.25、4:4.5、4:5,相对湿度为 70%)的 pH 值升高,而酸性较弱(pH 值为 5.0、4.8、4.7 和 5.1)的颗粒(EA:H+ = 4:4,相对湿度为 40%、55%、70% 和 85%)的 pH 值因光氧化作用而降低。我们将这些相反的 pH 值变化归因于 HONO 蒸发(增加了 pH 值)和 EA 反应(降低了 pH 值)的共同作用。在实验的不确定性范围内,NO3- 和 EA 的衰减率似乎对相对湿度和 pH 值并不敏感。我们根据产物种类提出了在 NO3- 光解产生的氧化剂存在下的 EA 反应途径。我们还观察到水溶性有机物(BrC 和有机相)作为潜在的二次有机气溶胶(SOA)的形成。这项研究揭示了EA的微粒汇及其在大气中由NO3-光解介导的BrC和SOA形成中的潜力,为大气气溶胶中胺的老化提供了新的见解。
{"title":"Secondary Organic Aerosol Formation from Aqueous Ethylamine Oxidation Mediated by Particulate Nitrate Photolysis","authors":"Xiaomeng Tian,&nbsp;Valeria YeeWan Chan and Chak K. Chan*,&nbsp;","doi":"10.1021/acsestair.3c0009510.1021/acsestair.3c00095","DOIUrl":"https://doi.org/10.1021/acsestair.3c00095https://doi.org/10.1021/acsestair.3c00095","url":null,"abstract":"<p >Atmospheric ethylamine (EA) is emitted by various primary sources and can be found abundantly in the gas and particle phases. Nitrate (NO<sub>3</sub><sup>–</sup>) is one of the most abundant inorganic compounds and has been found to coexist with amines in ambient particles. The photolysis of NO<sub>3</sub><sup>–</sup> can produce oxidants such as the OH radical, NO<sub>2</sub>, O(<sup>3</sup>P), and N(III), which can lead to the decay of particulate EA. Moreover, the degradation of EA forms carbonyl species, which are precursors to brown carbon (BrC) formation. In this study, we investigated the aging of EA-containing particles mediated by NO<sub>3</sub><sup>–</sup> photolysis under different relative humidity (RH) and initial pH conditions under 300 nm UV irradiation. The more acidic (pH 0.0, 0.2, and 0.6) particles (EA:H<sup>+</sup> molar ratio = 4:4.25, 4:4.5, 4:5 at 70% RH) exhibited an increase in pH, while the less acidic (pH 5.0, 4.8, 4.7, and 5.1) particles (EA:H<sup>+</sup> = 4:4 at 40%, 55%, 70%, and 85% RH) showed a decrease in pH as a result of photooxidation. We attributed these contrary pH changes to the combination of the HONO evaporation, which increases the pH, and the EA reactions, which decrease the pH. The decay rates of NO<sub>3</sub><sup>–</sup> and EA appear not to be sensitive to RH and pH within experimental uncertainties. We proposed EA reaction pathways in the presence of oxidants produced from NO<sub>3</sub><sup>–</sup> photolysis based on product speciation. We also observed the formation of water-soluble organics (BrC and an organic phase) as a potential secondary organic aerosol (SOA). This study sheds light on the particulate sink of EA and its potential in BrC and SOA formation mediated by NO<sub>3</sub><sup>–</sup> photolysis in the atmosphere, providing new insights into the aging of amines in atmospheric aerosols.</p><p >This study shows particulate ethylamine decay during nitrate photolysis could form water-soluble secondary organics (BrC and an organic phase), providing insight into the atmospheric amine sink and aging.</p>","PeriodicalId":100014,"journal":{"name":"ACS ES&T Air","volume":"1 9","pages":"951–959 951–959"},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acsestair.3c00095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Machine Learning Model to Predict Saturation Vapor Pressures of Atmospheric Aerosol Constituents 预测大气气溶胶成分饱和蒸气压的机器学习模型
Pub Date : 2024-07-22 DOI: 10.1021/acsestair.4c0011310.1021/acsestair.4c00113
Noora Hyttinen*, Linjie Li, Mattias Hallquist and Cheng Wu, 

We present a novel machine learning (ML) model for predicting saturation vapor pressures (psat), a physical property of use to describe transport, distribution, mass transfer, and fate of environmental toxins and contaminants. The ML model uses σ-profiles from the conductor-like screening model (COSMO) as molecular descriptors. The main advantages in using σ-profiles instead of other types of molecular representations are the relatively small size of the descriptor and the fact that the addition of new elements does not affect the size of the descriptor. The ML model was trained separately for liquid and solid compounds using experimental vapor pressures at various temperatures. The 95% confidence intervals of the error in the liquid- and solid-phase log10(psat/Pa) are 1.02 and 1.4, respectively. Especially our solid-phase model outperforms all group-contribution models in predicting experimental sublimation pressures of solid compounds. To demonstrate its applicability, the model was used to predict psat of atmospherically relevant species, and the values were compared with those obtained from a new experimental method. Here, our model provided a tool for a better description of this critical property and gave a higher confidence in the measurements.

Accurate saturation vapor pressure estimates of environmental contaminants are lacking in the low volatility range. Our quantum chemistry-based machine learning model provides a novel tool for predicting vapor pressure.

我们提出了一种新的机器学习(ML)模型,用于预测饱和蒸汽压(psat),这是一种用于描述环境毒素和污染物的迁移、分布、传质和归宿的物理特性。该 ML 模型使用类导体筛选模型 (COSMO) 中的σ-profiles 作为分子描述符。使用 σ-profiles 而不是其他类型的分子描述符的主要优点是描述符的大小相对较小,而且添加新元素不会影响描述符的大小。利用不同温度下的实验蒸汽压,分别对液态和固态化合物进行了 ML 模型训练。液相和固相 log10(psat/Pa) 误差的 95% 置信区间分别为 1.02 和 1.4。在预测固体化合物的实验升华压力方面,我们的固相模型尤其优于所有的基团贡献模型。为了证明该模型的适用性,我们使用该模型预测了大气中相关物种的 psat 值,并将其与一种新的实验方法得出的值进行了比较。在此,我们的模型为更好地描述这一关键特性提供了工具,并提高了测量结果的可信度。我们基于量子化学的机器学习模型为预测蒸气压提供了一种新工具。
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引用次数: 0
Estimation and Applications of Uncertainty in Methane Emissions Quantification Technologies: A Bayesian Approach 甲烷排放定量技术中不确定性的估计与应用:贝叶斯方法
Pub Date : 2024-07-22 DOI: 10.1021/acsestair.4c0003010.1021/acsestair.4c00030
Augustine Wigle*, Audrey Béliveau, Daniel Blackmore, Paule Lapeyre, Kirk Osadetz, Christiane Lemieux and Kyle J. Daun, 

An accurate understanding of uncertainty is needed to properly interpret methane emission estimates from upstream oil and gas sources in a variety of contexts, from component-level measurements to yearly jurisdiction-wide inventories. To characterize measurement uncertainty, we examine controlled release (CR) data from five different technology providers including quantitative gas imaging (QOGI), tunable diode laser-absorption spectroscopy (TDLAS); and airborne near-infrared hyperspectral (NIR HS) imaging. We introduce a novel empirical method to develop probability distributions of measurements given a true emission rate using the CR data. The approach includes flexible likelihoods which capture complex relationships in the data. An algorithm which provides the distribution of the true emission rate given a measurement is also developed, which synthesizes the measurement with the CR data and external information about the possible true emission rate. The results show that flexible models that accommodate complex nonlinear behavior are needed to adequately model measurement error. We also show that measurement error can vary under different conditions. We demonstrate that measurement uncertainty can be reduced by performing repeated measurements. A limitation of the study is that the collected CR data is collected under controlled conditions that may differ from those in industrial settings. As new CR data become available, the models presented in this paper can be refit to consider more diverse scenarios. The methodology can be extended to explicitly model different conditions to improve performance.

The uncertainty in measurements from methane emissions quantification technologies has important implications for emissions monitoring and reduction efforts. We show how a novel flexible model can be used to quantify measurement uncertainty.

需要准确了解不确定性,才能在各种情况下正确解释上游石油和天然气源的甲烷排放估计值,从组件级测量到年度全辖区清单。为了描述测量的不确定性,我们检查了来自五个不同技术提供商的控制释放 (CR) 数据,包括定量气体成像 (QOGI)、可调谐二极管激光吸收光谱 (TDLAS) 和机载近红外高光谱 (NIR HS) 成像。我们引入了一种新颖的经验方法,利用 CR 数据在给定真实发射率的情况下开发测量概率分布。该方法包括灵活的似然,可捕捉数据中的复杂关系。此外,还开发了一种算法,可根据测量结果提供真实发射率的分布情况,该算法将测量结果与 CR 数据以及有关可能的真实发射率的外部信息进行综合。研究结果表明,要对测量误差进行充分建模,就必须建立能适应复杂非线性行为的灵活模型。我们还表明,测量误差会在不同条件下发生变化。我们证明,通过重复测量可以减少测量误差。这项研究的局限性在于,所收集的 CR 数据是在受控条件下收集的,可能与工业环境下的数据不同。随着新的 CR 数据的出现,本文中介绍的模型可以进行改装,以考虑更多不同的情况。甲烷排放量化技术测量结果的不确定性对排放监控和减排工作具有重要影响。我们展示了如何使用新颖灵活的模型来量化测量的不确定性。
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引用次数: 0
Atmospheric Aerosol Sulfur Distribution and Speciation in Mexico City: Sulfate, Organosulfates, and Isoprene-Derived Secondary Organic Aerosol from Low NO Pathways 墨西哥城大气气溶胶硫的分布和种类:低氮途径产生的硫酸盐、有机硫酸盐和异戊二烯二次有机气溶胶
Pub Date : 2024-07-18 DOI: 10.1021/acsestair.4c0004810.1021/acsestair.4c00048
Madeline E. Cooke, Cara M. Waters, Joel Y. Asare, Jessica A. Mirrielees, Andrew L. Holen, Molly P. Frauenheim, Zhenfa Zhang, Avram Gold, Kerri A. Pratt, Jason D. Surratt, Luis A. Ladino and Andrew P. Ault*, 

Poor air quality is a persistent challenge in Mexico City, and addressing this issue requires an understanding of the chemical composition of PM2.5 (particulate matter less than 2.5 μm in diameter). Sulfate and secondary organic aerosol (SOA) are two of the largest contributors to PM2.5 in Mexico City, but uncertainties exist regarding their sources, distribution across individual particles, and ability to form organosulfates. Herein, we show using electron dispersive x-ray spectroscopy that only 41 ± 1% and 25 ± 1% of particles (aerodynamic diameter, 0.32–0.56 μm) by number at two sites in Mexico City, respectively, contain sulfur. Vibrational spectroscopy (Optical-Photothermal Infrared + Raman Microspectroscopy) shows that these sulfur-containing particles consist of inorganic sulfate (SO42–) and organosulfates (ROSO3). In addition, we unexpectedly measured abundant isoprene-derived SOA from low nitric oxide reaction pathways, specifically organosulfates (methyltetrol sulfates = avg. 50 ng/m3, max. 150 ng/m3) and polyols (methyltetrols = avg. 70 ng/m3, max. 190 ng/m3) using liquid chromatography with high-resolution mass spectrometry. Differences in SO2 and NOx concentrations between sites likely contribute to these spatial differences in sulfate, organosulfate, and SOA formation. These findings improve understanding of sulfur distribution and sources of SOA in Mexico City, which can inform efforts to improve air quality.

空气质量差是墨西哥城长期面临的挑战,要解决这一问题,就必须了解 PM2.5(直径小于 2.5 μm 的颗粒物)的化学成分。硫酸盐和二次有机气溶胶(SOA)是墨西哥城 PM2.5 的两大来源,但它们的来源、在单个颗粒中的分布以及形成有机硫酸盐的能力还存在不确定性。在此,我们使用电子色散 X 射线光谱法表明,在墨西哥城的两个地点,按数量计算,分别只有 41±1% 和 25± 1% 的颗粒(空气动力学直径,0.32-0.56 μm)含有硫。振动光谱(光学-光热红外光谱 + 拉曼微光谱)显示,这些含硫颗粒由无机硫酸盐(SO42-)和有机硫酸盐(ROSO3-)组成。此外,我们还利用液相色谱-高分辨率质谱法意外地测量到了来自低一氧化氮反应途径的大量异戊二烯衍生 SOA,特别是有机硫酸盐(甲基四醇硫酸盐 = 平均 50 纳克/立方米,最大 150 纳克/立方米)和多元醇(甲基四醇 = 平均 70 纳克/立方米,最大 190 纳克/立方米)。不同地点之间二氧化硫和氮氧化物浓度的差异很可能导致了硫酸盐、有机硫酸盐和 SOA 形成的空间差异。这些发现加深了人们对墨西哥城硫分布和 SOA 来源的了解,为改善空气质量提供了参考。
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引用次数: 0
The Role of Indoor Surface pH in Controlling the Fate of Acids and Bases in an Unoccupied Residence 室内表面 pH 值在控制无人居住住宅中酸碱命运中的作用
Pub Date : 2024-07-18 DOI: 10.1021/acsestair.4c0004410.1021/acsestair.4c00044
Jenna C. Ditto*, Marc Webb, Han N. Huynh, Jie Yu, Glenn C. Morrison, Barbara J. Turpin, Michael R. Alves, Kathryn Mayer, Michael F. Link, Allen H. Goldstein, Dustin Poppendieck, Marina E. Vance, Delphine K. Farmer, Arthur W. H. Chan and Jonathan P. D. Abbatt, 

The chemical composition of indoor air is strongly driven by the composition and properties of indoor surfaces. At the Chemical Assessments of Surfaces and Air (CASA) campaign, we performed controlled additions of ammonia (reaching up to 297 ppb to 662 ppb) to investigate the impacts of changing surface basicity on the fate of gaseous and particulate acids and bases in an unoccupied house. In response to ammonia injections, nitrogen-containing compounds (C2–7H3–11N1O0–3) were emitted from surfaces to the gas phase with signals increasing 101% to 104% compared to their signals prior to ammonia addition. At the same time, oxygen-containing compounds (C1–7H2–6O2–3) were removed from the gas phase by indoor surface partitioning. Indoor surface pH and aerosol pH likely increased during these controlled ammonia injections relative to their baseline conditions. We estimate indoor surface pH to be nearly 5 and indoor aerosol pH to range from 2 to 4 during this experiment. At each ammonia injection, we observed ammonium and nitrate concentrations in the aerosol phase to increase due to gas-particle partitioning of ammonia and nitric acid. This gas-particle-surface exchange showed strong dependence on relative humidity; evaporation of gaseous bases was more pronounced at lower relative humidity when surface-associated water volume was reduced, while gas-to-particle partitioning of inorganic species was greater in the presence of more aerosol liquid water at higher relative humidity. From cooking experiments, which represent realistic sources of acids and bases to the indoor environment but which emit 10 times less ammonia than was introduced to the house via pure ammonia injection experiments, we predict that surfaces may still be important sources of these basic gases to indoor air.

室内空气的化学成分深受室内表面成分和特性的影响。在 "表面和空气化学评估(CASA)"活动中,我们进行了氨的受控添加(达到 297 ppb 至 662 ppb),以研究表面碱性的变化对无人居住的房屋中气态和颗粒酸碱的归宿的影响。在注入氨气后,含氮化合物(C2-7H3-11N1O0-3)从表面释放到气相中,其信号比加入氨气前增加了 101% 至 104%。同时,含氧化合物(C1-7H2-6O2-3)通过室内表面分区从气相中移除。与基线条件相比,室内表面 pH 值和气溶胶 pH 值在这些受控氨气注入过程中可能会升高。我们估计,在这次实验中,室内表面 pH 值接近 5,室内气溶胶 pH 值介于 2 到 4 之间。在每次注入氨气时,我们都观察到气溶胶相中的氨和硝酸盐浓度由于氨和硝酸的气体颗粒分配而增加。这种气体-颗粒-表面交换与相对湿度有很大关系;在相对湿度较低时,气态碱的蒸发更明显,因为表面相关水量减少了;而在相对湿度较高时,气溶胶液态水较多,无机物的气体-颗粒分配更多。烹饪实验代表了室内环境中酸碱的真实来源,但其释放的氨气比通过纯氨注射实验引入室内的氨气少 10 倍,因此我们预测表面可能仍然是室内空气中这些基本气体的重要来源。
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引用次数: 0
Composition and Sources of Organic Aerosol in Two Megacities in Western China Using Complementary Mass Spectrometric and Statistical Techniques 利用质谱和统计互补技术研究中国西部两个特大城市有机气溶胶的组成和来源
Pub Date : 2024-07-16 DOI: 10.1021/acsestair.4c0005110.1021/acsestair.4c00051
Tianqu Cui*, Manousos I. Manousakas, Qiyuan Wang, Gaëlle Uzu, Yufang Hao, Peeyush Khare, Lu Qi, Yang Chen, Yuemei Han, Jay G. Slowik, Jean-Luc Jaffrezo, Junji Cao, André S. H. Prévôt* and Kaspar R. Daellenbach*, 

Over 300 daily PM2.5 filter samples were collected in two western Chinese megacities, Xi’an and Chongqing, from October 2019 to May 2020. Their aqueous extracts were nebulized simultaneously to an aerosol mass spectrometer (AMS) and a recently developed extractive electrospray ionization (EESI) mass spectrometer, for bulk and near-molecular organic aerosol (OA) composition, respectively. Carbonate was quantified using EESI and a total organic carbon analyzer to separate inorganic carbon from dust. Via isotopically-labelled internal standards and positive matrix factorization, seven water-soluble sources were quantified separately using the AMS- and EESI-based analyses, with consistent types, concentrations, and correlations. These include dust, solid fuel combustion (SFC)-related, nitrogen- (and sulfur-) containing, summer/winter oxygenated OAs, and a cigarette-related OA only in EESI. When accounting for water-solubility, SFC-related OAs were the largest (53%) sources in Chongqing, while dust (consisting of 77% OA and 23% carbonates) was the largest (30%) source in Xi’an. Overall, this study presents one of the first times that complementary mass spectrometric techniques independently resolved consistent OA sources─with added chemical information─over multiple seasons and locations of complex pollution. The methods and quantified sources are essential for subsequent chemical, modelling, and health studies, and policy making for air pollution mitigation.

This study used complementary state-of-the-art mass spectrometric and statistical techniques to characterize bulk and near-molecular organic aerosol composition in two western Chinese megacities, resolving consistent source types and concentrations.

从2019年10月至2020年5月,在中国西部的两个特大城市--西安和重庆,每天采集300多个PM2.5过滤样品。它们的水提取物被同时雾化到气溶胶质谱仪(AMS)和最近开发的萃取电喷雾离子化质谱仪(EESI)上,分别检测块状和近分子有机气溶胶(OA)成分。使用萃取电喷雾离子化质谱仪和总有机碳分析仪对碳酸盐进行定量,以从尘埃中分离出无机碳。通过同位素标记的内部标准和正矩阵因式分解,利用基于 AMS 和 EESI 的分析分别量化了七种水溶源,其类型、浓度和相关性都是一致的。这些来源包括灰尘、与固体燃料燃烧 (SFC) 有关的、含氮(和硫)的、夏季/冬季含氧 OA,以及仅在 EESI 中与香烟有关的 OA。考虑到水溶性,与 SFC 相关的 OA 是重庆最大的来源(53%),而粉尘(由 77% 的 OA 和 23% 的碳酸盐组成)则是西安最大的来源(30%)。总之,这项研究首次展示了互补质谱技术在多季节、多地点的复杂污染中独立解析出一致的 OA 来源,并提供了更多的化学信息。这些方法和量化的来源对于后续的化学、建模和健康研究以及缓解空气污染的政策制定至关重要。这项研究使用了互补的先进质谱和统计技术来表征中国西部两个特大城市的大量和近分子有机气溶胶成分,解析了一致的来源类型和浓度。
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引用次数: 0
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