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Air pollution, characterized by high levels of particulate matter (PM), poses the greatest environmental threat to human health, causing an estimated 7 million deaths annually and accounting for 5 % of the global gross domestic product (GDP). While the health impacts of PM are influenced by the toxicity of its individual chemical constituents, the mortality burden of PM is solely based on its total mass concentration. This is because of a lack of large-scale, high-resolution data on PM chemical composition, needed for epidemiological assessments. Identifying which PM constituents are harmful to health has been the "holy grail" of atmospheric science since the landmark 1993 study on six US cities established a definitive link between PM and mortality. Ever since, atmospheric scientists have focused on understanding aerosol composition, emission sources, and formation pathways, while longitudinal epidemiological studies have required individual-level exposure data, employing land use regression models for the prediction of exposures at fine resolutions. In this opinion article, we argue that the time has come to shift the focus towards incorporating PM chemical composition into epidemiological health assessments, laying the foundation for the development of new regulatory metrics. This shift will enable the creation of targeted guidelines and subsequent regulations, prioritizing mitigation efforts against the most harmful anthropogenic emissions. Central to this shift is the availability of global, long-term, high-resolution data on PM chemical composition that are obtained through field observations and modelling outputs. In the article, we underscore key milestones within aerosol science that have been integral for advancing this foundational shift. Specifically, we examine emerging modelling tools for estimating exposure to individual PM components, present the type of ambient observations needed for model developments, identify key gaps in our fundamental understanding of emissions and their atmospheric transformation, and propose advancing cross-disciplinary collaboration between aerosol scientists and epidemiologists to understand the health impacts of individual PM components. We contend that aerosol science has now reached a pivotal moment in elucidating the differential health impacts of PM components, representing a first step towards their incorporation into air quality guidelines. [ABSTRACT FROM AUTHOR]

As national air quality networks and international research infrastructures, such as ACTRIS (EU) and ASCENT (US), continue to expand, the deployment of online aerosol chemistry measurements increases worldwide. These research infrastructures are focused on the ability to compare atmospheric properties from one region to another, making it crucial to understand instrument operation in various settings. This paper is part of a series of publications dedicated to better understanding the operation of these instruments using a series of laboratory tests. A particular focus was made on evaluating the organic aerosol (OA) measurement performance of six Aerosol Chemical Speciation Monitors (ACSMs) when sampling known mixtures of organic and inorganic aerosols and in ambient air. The study focuses on assessing the impact of instrument-to-instrument variability on ACSM data processing as well as identifying and quantifying the previously identified m/z44/NO3 artifacts that can affect the accuracy of the measurements. A high degree of variability was observed in instrument measurements of the m/z44/NO3 artifact when compared to results obtained two years earlier (e.g., an increase from ∼0 in 2016 to 0.16 in 2018 or a decrease from 0.12 in 2016 to 0.05 in 2018), confirming the need for frequent evaluation and quantification during calibration. This study underlines that the product between organic aerosol relative ionization efficiency and the instrument collection efficiency value is instrument dependent and that the variability in these values (1.78 ± 0.35) should be considered when estimating the measurement uncertainties. Using a range of specific compounds, an average RIEOA for levoglucosan (1.29 ± 0.23) close to the default value commonly used in ACSM was determined, obtaining a value more specific to each instrument. This study provides valuable information for the calibration and operation of ACSM instruments, ensuring that future studies can build on this work to evaluate and improve instrument performance. [ABSTRACT FROM AUTHOR]

Solid fuel (SF) combustions, including coal and biomass, are important sources of pollutants in the particle and gas phase and therefore have significant implications for air quality, climate, and human health. In this study, we systematically examined real-time gas-phase emissions using the Vocus proton20 transfer-reaction time-of-flight mass spectrometer, from a variety of solid fuels, including beech logs, spruce and pine logs, spruce and pine branches and needles, straw, cow dung, and coal. The average emission factors (EFs) for organic gases ranged from 6.7 to 74.2 g kg-1, depending on the combustion phases and fuel types. Despite slight differences in modified combustion efficiency (MCE) for some experiments, increasing EFs for primary organic gases were observed with lower MCE. The CxHyOz family is the most abundant group, but a greater contribution of nitrogen-containing species and CxHy families (related to polycyclic aromatic hydrocarbons) could be found in cow dung burning and coal burning, respectively. Intermediate volatility organic compounds (IVOCs) also constituted a considerable fraction in solid-fuel combustions (from 12.6% to 39.3%), especially for spruce and pine branches and needles (39.3%), and coal (31.1%). Despite the large variability of EFs in the organic gas emissions, the relative contribution of different classes showed large similarities between the combustion phases in beech stove burning. The product from pyrolysis of coniferyl-type lignin and the extract of cedar pine needle were identified as characteristic compounds in the spruce and pine branches and needles open burning (e.g., C10H14O2, C11H14O2, C10H10O2). The characteristic product (C9H12O) from the pyrolysis of beech lignin was identified as the characteristic compound for beech log stove burning. Many series of nitrogen-containing homologues (e.g., C10H11-21NO, C12H11-21N, C11H11-23NO and C15H15-31N) and nitrogen-containing species (e.g., acetonitrile, acrylonitrile, propanenitrile, methylpentanenitrile) were specifically identified in cow dung burning emissions. Polycyclic aromatic hydrocarbons (PAHs) with 9-12 carbons were identified with significantly higher abundance from coal burning compared to emissions from other studied fuels. The composition of these characteristic organic vapors reflects the burned fuel types and can help constrain emissions of solid fuel burning in regional models. [ABSTRACT FROM AUTHOR]

Air pollution poses the greatest environmental threat to human health, causing an estimated nine million premature deaths annually and accounting for 5 % of the global GDP. This opinion paper explores how advances in aerosol science inform our understanding of the health impacts of outdoor particulate pollution. In the article, we advocate for a shift from solely considering total particulate matter (PM) mass to utilizing specific PM components as metrics for health assessments. This will allow targeted evidence-based interventions, limiting the most harmful anthropogenic emissions, while exempting uncontrollable or non-detrimental components. Central to this shift is the availability of global long-term PM chemical composition data obtained through field observations and modelling outputs. These data will serve as the new foundation for identifying the most harmful chemical components in different regions. We discuss emerging modelling tools for personalized exposure estimation to these components, present the type of ambient observations needed for model evaluation and highlight key gaps in our fundamental understanding of emissions and their health effects. Through global PM chemical composition data, advancements in modelling tools, and collaboration between aerosol scientists and epidemiologists, we can gain a deeper understanding of how different PM components influence disease development. The reevaluation of air quality guidelines with a focus on specific PM components will be essential for fostering healthier environments, preventing diseases and building resilient communities. [ABSTRACT FROM AUTHOR]

Air pollution poses the greatest environmental threat to human health, causing an 11 estimated nine million premature deaths annually and accounting for 5% of the global GDP. This 12 opinion paper explores how advances in aerosol science inform our understanding of the health impacts 13 of outdoor particulate pollution. In the article, we advocate for a shift from solely considering total 14 particulate matter (PM) mass to utilizing specific PM components as metrics for health assessments. 15 This will allow targeted evidence-based interventions, limiting the most harmful anthropogenic 16 emissions, while exempting uncontrollable or non-detrimental components from guidelines. Central to 17 this shift is the availability of global long-term PM chemical composition data obtained through field 18 observations and modelling outputs. These data will serve as the new foundation for identifying the 19 most harmful chemical components in different regions. We discuss emerging modelling tools for 20 personalized exposure estimation to these components, present the type of ambient observations needed 21 for model evaluation and highlight key gaps in our fundamental understanding of emissions and their 22 health effects. Through global PM chemical composition data, advancements in modelling tools, and 23 collaboration between aerosol scientists and epidemiologists, we can gain a causal understanding of 24 how different PM components influence disease development. The reevaluation of air quality guidelines 25 with a focus on specific PM components will be essential for fostering healthier environments, 26 preventing diseases and building resilient communities. [ABSTRACT FROM AUTHOR]

During the past decades, the source apportionment of organic aerosol (OA) in the ambient air has been improving substantially. The database of source retrieval model resolved mass spectral profiles for different sources has been built with the aerosol mass spectrometer (AMS). However, distinguishing similar sources (such as wildfires and residential wood burning) remains challenging, as the hard ionization of AMS mostly fragments compounds and therefore cannot capture the detailed molecular information. Recent mass spectrometer technologies of soft ionization and high mass resolution have allowed for aerosol characterization at the molecular formula level. In this study, we systematically estimated the emission factors and characterized the primary OA (POA) chemical composition with the AMS and the extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) for the first time from a variety of solid fuels, including beech logs, spruce and pine logs, spruce and pine branches and needles, straw, cow dung, and plastic bags. The emission factors of organic matter and hydrocarbon gases are 16.2 ± 10.8 g kg-1 and 30.3 ± 8.5 g kg-1 for cow dung burning, which is generally higher than that of wood (beech, spruce, and pine), straw, and plastic bags burning (in the range from 1.3 to 6.2 g kg-1 and 2.8 to 9.4 g kg-1). The POA measured by the AMS shows that the f60 (mass fraction of m/z 60) varies from 0.003 to 0.04 based on fuel types and combustion efficiency for wood (beech, spruce, and pine) and cow dung burning. The contribution of some polycyclic aromatic hydrocarbons is linked to burning fuels. On molecular level, the dominant compound of POA from wood, straw, and cow dung is C6H10O5 (mainly levoglucosan), contributing ~7% to ~30% of the total intensity, followed by C8H12O6 with fractions of ~2% to ~9%. However, as they are prevalent in all burns of biomass material, they cannot act as tracers for the specific sources. By using the Mann-Whitney U test among the studied fuels, we find specific potential new markers for these fuels from the measurement of the AMS and EESI-TOF. Markers from spruce and pine burning could be resin and conifer needle-related. The product from pyrolysis of hardwood lignins is found especially in beech logs burning. Nitrogen-containing species are selected markers primarily for cow dung open burning. These markers provide important support for the source apportionment. [ABSTRACT FROM AUTHOR]

Lucknow is the capital of India's largest state, Uttar Pradesh, one of South Asia's most polluted urban cities. Tropospheric photochemistry relies on non-methane volatile organic compounds (NMVOCs), which are ozone and secondary organic aerosol precursors. Using the proton-transfer reaction time of flight mass spectrometer (PTR-ToF-MS) at an urban background site in Lucknow, the chemical characterisation of NMVOCs was performed in real-time from Dec-2020–May 2021. The campaign mean concentrations of the NMVOCs were 125.5 ±37.5 ppbv. The average concentrations of NMVOCs are relatively high during winter. An advanced multi-linear engine (ME-2) model was used to perform the NMVOCs source apportionment using positive matrix factorisation (PMF). It resolves the five main sources contributing to these organic compounds in the atmosphere. They include traffic, two solid fuel combustion factors, secondary volatile organic compounds and volatile chemical products. Biomass burning contributes most to the NMVOCs and SOA formation, while interestingly, traffic sources most influence ozone formation. Significant differences in the composition of the two solid fuel combustion indicate the influence of local emissions and transport of regional pollution to the city. The high temperature during summer leads to more volatilisation of oxygenated VOCs. [ABSTRACT FROM AUTHOR]