Evaluation of biological markers for the risk assessment of carbon black in epidemiological studies.

Background/objectives: Engineered nanomaterials (ENMs) have been suggested as being capable of promoting inflammation, a key component in the pathways associated with carcinogenesis, cardiovascular disease, and other conditions. As a result, the risk assessment of biological markers as early-stage indicators has the potential to improve translation from experimental toxicologic findings to identifying evidence in human studies. The study aims to review the possible early biological changes in workers exposed to carbon black (CB), followed by an evidentiary quality evaluation to determine the predictive value of the biological markers. Methods: We conducted a literature search to identify epidemiological studies that assessed biological markers that were involved in the inflammatory process at early stages among workers with exposure to CB. We reviewed the studies with specific reference to the study design, statistical analyses, findings, and limitations. Results: We identified five Chinese studies that investigated the potential impact of exposure to CB on inflammatory markers, bronchial wall thickening, genomic instability, and lung function impairment in CB production workers. Of the five Chinese studies, four were cross-sectional; another study reported results at two-time points over six years of follow-up. The authors of all five studies concluded positive relationships between exposure and the inflammatory cytokine profiles. The weak to very weak correlations between biomarkers and early-stage endpoints were reported. Conclusion: Most inflammatory markers failed to satisfy the proposed evidentiary quality criteria. The significance of the results of the reviewed studies is limited by the cross-sectional study design, inconsistency in results, uncertain clinical relevance, and high occupational exposures. Based on this review, the risk assessment relying on inflammatory markers does not seem appropriate at this time. Nevertheless, the novel research warrants further exploration in assessing exposure to ENMs and corresponding potential health risks in occupational settings.

Mechanism of soot and particulate matter formation during high temperature pyrolysis and gasification of waste derived from MSW.

This research investigates the formation mechanism of soot and particulate matter during the pyrolysis and gasification of waste derived from Municipal Solid Waste (MSW) in a laboratory scale drop tube furnace. Compared with CO2 gasification atmosphere, more ultrafine particles (PM0.2, aerodynamic diameter less than 0.2 µm) were generated in N2 atmosphere at 1200℃, which were mainly composed of polycyclic aromatic hydrocarbons (PAHs), graphitic carbonaceous soot and volatile alkali salts. High reaction temperatures promote the formation of hydrocarbon gaseous products and their conversion to PAHs, which ultimately leads to the formation of soot particles. The soot particles generated by waste derived from MSW pyrolysis and gasification both have high specific surface area and well-developed pore structure. Compared with pyrolysis, the soot generated by gasification of waste derived from MSW had smaller size and higher proportion of inorganic components. The higher pyrolysis temperature led to the collapse of the mesoporous structure of submicron particles, resulting in a decrease in total pore volume and an increase in specific surface area. Innovatively, this research provides an explanation for the effect of reaction temperature/ CO2 on the formation pathways and physicochemical properties of soot and fine particulate matter.

Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations.

A reliable determination of equivalent black carbon (eBC) mass concentrations derived from filter absorption photometers (FAPs) measurements depends on the appropriate quantification of the mass absorption cross-section (MAC) for converting the absorption coefficient (babs) to eBC. This study investigates the spatial-temporal variability of the MAC obtained from simultaneous elemental carbon (EC) and babs measurements performed at 22 sites. We compared different methodologies for retrieving eBC integrating different options for calculating MAC including: locally derived, median value calculated from 22 sites, and site-specific rolling MAC. The eBC concentrations that underwent correction using these methods were identified as LeBC (local MAC), MeBC (median MAC), and ReBC (Rolling MAC) respectively. Pronounced differences (up to more than 50 %) were observed between eBC as directly provided by FAPs (NeBC; Nominal instrumental MAC) and ReBC due to the differences observed between the experimental and nominal MAC values. The median MAC was 7.8 ± 3.4 m2 g-1 from 12 aethalometers at 880 nm, and 10.6 ± 4.7 m2 g-1 from 10 MAAPs at 637 nm. The experimental MAC showed significant site and seasonal dependencies, with heterogeneous patterns between summer and winter in different regions. In addition, long-term trend analysis revealed statistically significant (s.s.) decreasing trends in EC. Interestingly, we showed that the corresponding corrected eBC trends are not independent of the way eBC is calculated due to the variability of MAC. NeBC and EC decreasing trends were consistent at sites with no significant trend in experimental MAC. Conversely, where MAC showed s.s. trend, the NeBC and EC trends were not consistent while ReBC concentration followed the same pattern as EC. These results underscore the importance of accounting for MAC variations when deriving eBC measurements from FAPs and emphasize the necessity of incorporating EC observations to constrain the uncertainty associated with eBC.

Indoor and ambient black carbon and fine particulate matter associations with blood biomarkers in COPD patients.

BACKGROUND: Systemic inflammation contributes to cardiovascular risk and chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between systemic inflammation and exposure to ambient fine particulate matter (PM ≤ 2.5 µm diameter; PM2.5), and black carbon (BC), a PM2.5 component attributable to traffic and other sources of combustion, infiltrating indoors are not well described. METHODS: Between 2012 and 2017, COPD patients completed in-home air sampling over one-week intervals, up to four times (seasonally), followed by measurement of plasma biomarkers of systemic inflammation, C-reactive protein (CRP) and interleukin-6 (IL-6), and endothelial activation, soluble vascular adhesion molecule-1 (sVCAM-1). Ambient PM2.5, BC and sulfur were measured at a central site. The ratio of indoor/ambient sulfur in PM2.5, a surrogate for fine particle infiltration, was used to estimate indoor BC and PM2.5 of ambient origin. Linear mixed effects regression with a random intercept for each participant was used to assess associations between indoor and indoor of ambient origin PM2.5 and BC with each biomarker. RESULTS: 144 participants resulting in 482 observations were included in the analysis. There were significant positive associations between indoor BC and indoor BC of ambient origin with CRP [%-increase per interquartile range (IQR);95 % CI (13.2 %;5.2-21.8 and 11.4 %;1.7-22.1, respectively)]. Associations with indoor PM2.5 and indoor PM2.5 of ambient origin were weaker. There were no associations with IL-6 or sVCAM-1. CONCLUSIONS: In homes of patients with COPD without major sources of combustion, indoor BC is mainly attributable to the infiltration of ambient sources of combustion indoors. Indoor BC of ambient origin is associated with increases in systemic inflammation in patients with COPD, even when staying indoors.

Application of graphite carbon black assisted-laser desorption ionization-mass spectrometry for soy sauce product discrimination.

In a previous study, we developed a novel analytical method to directly and simultaneously detect taste- and odor-active compounds using graphite carbon black (GCB)-assisted laser desorption ionization mass spectrometry (LDI-MS). In this study, we aimed to evaluate food quality using a variety of soy sauces using the method to discriminate each product. Graphite carbon black-laser desorption ionization-mass spectrometry allowed the provision of hundreds of MS peaks derived from soy sauces in both positive and negative modes without any tedious sample pretreatments. Principal component analysis using the obtained MS peaks clearly distinguished three soy sauce products based on the manufacturing countries (Japan, China, and India). Moreover, this method identified distinct MS peaks for discrimination, which significantly correlated with their quantitative amounts in the products. Thus, GCB-LDI-MS analysis was established as a simple and rapid technique for food analysis, illustrating the chemical patterns of food products.

Local and NON-LOCAL source apportionment of black carbon and combustion generated PM2.5.

Current methods for measuring black carbon aerosol (BC) by optical methods apportion BC to fossil fuel and wood combustion. However, these results are aggregated: local and non-local combustion sources are lumped together. The spatial apportioning of carbonaceous aerosol sources is challenging in remote or suburban areas because non-local sources may be significant. Air quality modeling would require highly accurate emission inventories and unbiased dispersion models to quantify such apportionment. We propose FUSTA (FUzzy SpatioTemporal Apportionment) methodology for analyzing aethalometer results for equivalent black carbon coming from fossil fuel (eBCff) and wood combustion (eBCwb). We applied this methodology to ambient measurements at three suburban sites around Santiago, Chile, in the winter season 2021. FUSTA results showed that local sources contributed ∼80% to eBCff and eBCwb in all sites. By using PM2.5 - eBCff and PM2.5 - eBCwb scatterplots for each fuzzy cluster (or source) found by FUSTA, the estimated lower edge lines showed distinctive slopes in each measurement site. These slopes were larger for non-local sources (aged aerosols) than for local ones (fresh emissions) and were used to apportion combustion PM2.5 in each site. In sites Colina, Melipilla and San Jose de Maipo, fossil fuel combustion contributions to PM2.5 were 26 % (15.9 µg m-3), 22 % (9.9 µg m-3), and 22 % (7.8 µg m-3), respectively. Wood burning contributions to PM2.5 were 22 % (13.4 µg m-3), 19 % (8.9 µg m-3) and 22% (7.3 µg m-3), respectively. This methodology generates a joint source apportionment of eBC and PM2.5, which is consistent with available chemical speciation data for PM2.5 in Santiago.

A Long-Term Comparison between the AethLabs MA350 and Aerosol Magee Scientific AE33 Black Carbon Monitors in the Greater Salt Lake City Metropolitan Area.

Black carbon (BC) or soot contains ultrafine combustion particles that are associated with a wide range of health impacts, leading to respiratory and cardiovascular diseases. Both long-term and short-term health impacts of BC have been documented, with even low-level exposures to BC resulting in negative health outcomes for vulnerable groups. Two aethalometers-AethLabs MA350 and Aerosol Magee Scientific AE33-were co-located at a Utah Division of Air Quality site in Bountiful, Utah for just under a year. The aethalometer comparison showed a close relationship between instruments for IR BC, Blue BC, and fossil fuel source-specific BC estimates. The biomass source-specific BC estimates were markedly different between instruments at the minute and hour scale but became more similar and perhaps less-affected by high-leverage outliers at the daily time scale. The greater inter-device difference for biomass BC may have been confounded by very low biomass-specific BC concentrations during the study period. These findings at a mountainous, high-elevation, Greater Salt Lake City Area site support previous study results and broaden the body of evidence validating the performance of the MA350.

Potentially Massive and Global Non-Pyrogenic Production of Condensed "Black" Carbon through Biomass Oxidation.

With the increased occurrences of wildfires worldwide, there has been an increase in scientific interest surrounding the chemistry of fire-derived "black" carbon (BC). Traditionally, wildfire research has assumed that condensed aromatic carbon (ConAC) is exclusively produced via combustion, and thus, ConAC is equated to BC. However, the lack of correlations between ConAC in soils or rivers and wildfire history suggests that ConAC may be produced non-pyrogenically. Here, we show quantitative evidence that this occurs during the oxidation of biomass with environmentally ubiquitous hydroxyl radicals. Pine wood boards exposed to iron nails and natural weather conditions for 12 years yielded a charcoal-like ConAC-rich material. ConAC was also produced during laboratory oxidations of pine, maple, and brown-rotted oak woods, as well as algae, corn root, and tree bark. Back-of-the-envelope calculations suggest that biomass oxidation could be producing massive non-pyrogenic ConAC fluxes to terrestrial and aquatic environments. These estimates (e.g., 163-182 Tg-ConAC/year to soils) are much higher than the estimated pyrogenic "BC" fluxes (e.g., 128 Tg-ConAC/year to soils) implying that environmental ConAC is primarily non-pyrogenic. This novel perspective suggests that wildfire research trajectories should shift to assessing non-pyrogenic ConAC sources and fluxes, developing new methods for quantifying true BC, and establishing a new view of ConAC as an intermediate species in the biogeochemical processing of biomass during soil humification, aquatic photochemistry, microbial degradation, or mineral-organic matter interactions. We also advise against using BC or pyrogenic carbon (pyC) terminologies for ConAC measured in environmental matrices, unless a pyrogenic source can be confidently assigned.

Combustion conditions influence toxicity of flame-generated soot to ocular (ARPE-19) cells.

Soot is a prevalent aerosol found both indoors and outdoors that has several sources, such as natural (e.g., wildfires), civilian (e.g., cooking), or military (e.g., burn pit operation). Additionally, within the sources, factors that influence the physicochemical properties of the soot include combustion temperature, oxygen availability, and fuel type. Being able to reproduce soot in the laboratory and systematically assess its toxicity is important in the pursuit of elucidating pathologies associated with its exposure. Of the organs of interest, we targeted the eye given the scant attention received. Yet, air pollution constituents such as soot have been linked to diseases such as age-related macular degeneration and proliferative vitreoretinopathy. We developed a bench-scale system to synthesize different types of soot, that is, soot with a systematically varied physical attributes or chemical composition. We used common analytical techniques to probe such properties, and used statistical analyses to correlate them with toxicity in vitro using ARPE-19 cells. Within the range of flame conditions studied, we find that soot toxicity increases with increasing oxygen concentration in fuel-rich premixed flames, and weakly increases with decreasing flame temperature. Additionally, soot particles produced in premixed flames are generally smaller in size, exhibit a lesser fractal structure, and are considerably more toxic to ARPE-19 cells than soot particles produced in non-premixed flames.

Constructing transferable and interpretable machine learning models for black carbon concentrations.

Black carbon (BC) has received increasing attention from researchers due to its adverse health effects. However, in-situ BC measurements are often not included as a regulated variable in air quality monitoring networks. Machine learning (ML) models have been studied extensively to serve as virtual sensors to complement the reference instruments. This study evaluates and compares three white-box (WB) and four black-box (BB) ML models to estimate BC concentrations, with the focus to show their transferability and interpretability. We train the models with the long-term air pollutant and weather measurements in Barcelona urban background site, and test them in other European urban and traffic sites. Despite the difference in geographical locations and measurement sites, BC correlates the strongest with particle number concentration of accumulation mode (PNacc, r = 0.73-0.85) and nitrogen dioxide (NO2, r = 0.68-0.85) and the weakest with meteorological parameters. Due to its similarity of correlation behaviour, the ML models trained in Barcelona performs prominently at the traffic site in Helsinki (R2 = 0.80-0.86; mean absolute error MAE = 3.90-4.73 %) and at the urban background site in Dresden (R2 = 0.79-0.84; MAE = 4.23-4.82 %). WB models appear to explain less variability of BC than BB models, long short-term memory (LSTM) model of which outperforms the rest of the models. In terms of interpretability, we adopt several methods for individual model to quantify and normalize the relative importance of each input feature. The overall static relative importance commonly used for WB models demonstrate varying results from the dynamic values utilized to show local contribution used for BB models. PNacc and NO2 on average have the strongest absolute static contribution; however, they simultaneously impact the estimation positively and negatively at different sites. This comprehensive analysis demonstrates that the possibility of these interpretable air pollutant ML models to be transfered across space and time.

Photo-Reactivity of dissolved black carbon unveiled by combination of optical spectroscopy and FT-ICR MS analysis: Effects of pyrolysis temperature.

Dissolved black carbon (DBC) has high photoactivity, which plays an important role in contaminants photodegradation. However, it is unclear how pyrolysis temperatures would affect the composition and photo-reactivity of DBC at the molecular level. Herein, we combined complementary techniques to study the characteristics of DBC pyrolyzed at 200 - 500 ℃, as well as the photoproduction of reactive species and the photodegradation of tetracycline (TC). Bulk composition characterization found that condensed aromatic carbonyl compounds (ConAC) with narrow molecular weights in DBC experienced an increase from 200 to 500 °C, which enhanced the photoproduction of 3DBC*,1O2, and ·OH. Molecular-level data suggested that 3DBC* and 1O2 were both related to the same DBC compounds. Comparatively, the patterns for ·OH were less pronounced, implying its precursor was not 3DBC* and had more complexity. Plentiful CHOx species of ConAC in DBC400 and DBC500 (DBCT, where T = pyrolysis temperature) accelerated the generation of 3DBC* and 1O2, enhancing the photodegradation of TC, and mainly triplet states of quinones reacted with TC. In contrast, DBC200 and DBC300 exhibited inhibition since massive CHOx species in lignin-like reduced 3TC* to TC. Our data revealed the diverse photochemical behavior mechanisms of DBC pyrolyzed at 200 - 500 ℃ at the molecular level and the implications for aquatic contaminants photochemistry.

Weakened black carbon trans-boundary transport to the Tibetan Plateau during the COVID-19 pandemic.

The lockdowns implemented during the coronavirus disease 2019 (COVID-19) pandemic provide a unique opportunity to investigate the impact of emission sources and meteorological conditions on the trans-boundary transportation of black carbon (BC) aerosols to the Tibetan Plateau (TP). In this study, we conducted an integrative analysis, including in-situ observational data, reanalysis datasets, and numerical simulations, and found a significant reduction in the trans-boundary transport of BC to the TP during the 2020 pre-monsoon season as a result of the lockdowns and restrictive measures. Specifically, we observed a decrease of 0.0211 µgm-3 in surface BC concentration over the TP compared to the 2016 pre-monsoon period. Of this reduction, approximately 6.04 % can be attributed to the decrease in emissions during the COVID-19 pandemic, surpassing the 4.47 % decrease caused by changes in meteorological conditions. Additionally, the emission reductions have weakened the trans-boundary transport of South Asia BC to the TP by 0.0179 µgm-2s-1; indicating that the recurring spring atmospheric pollution from South Asia to the TP will be alleviated through the reduction of anthropogenic emissions. Moreover, it is important to note that BC deposition on glaciers contributes significantly to glacier melting due to its enrichment, posing a threat to the water sustainability of the TP. Therefore, urgent measures are needed to reduce emissions from adjacent regions to preserve the TP as the "Asian Water Tower."

Evaluation of MERRA-2 and CAMS reanalysis for black carbon aerosol in China.

Black carbon (BC) constitutes a pivotal component of atmospheric aerosols, significantly impacting regional and global radiation balance, climate, and human health. In this study, we evaluated BC data in two prominent atmospheric composition reanalysis datasets: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and the Copernicus Atmosphere Monitoring Service (CAMS), and analyzed the causes of their deviations. This assessment is based on observational data collected from 34 monitoring stations across China from 2006 to 2022. Our research reveals a significant and consistent decline in BC concentrations within China, amounting to a reduction exceeding 67.33%. However, both MERRA-2 and CAMS reanalysis data fail to capture this declining trend. The average annual decrease of BC in MERRA-2 from 2006 to 2022 is only 0.06 µg/m3 per year, while the BC concentration in CAMS even increased with an average annual value of 0.014 µg/m3 per year. In 2022, MERRA-2 had overestimated BC concentration by 20% compared to observational data, while CAMS had overestimated it by approximately 66%. In the regional BC concentration analysis, the data quality of the reanalysis data is better in the South China (RM = 0.59, RC = 0.53), followed by the North China (RM = 0.50, RC = 0.42). Reanalysis BC data in Northwest China and the Tibetan Plateau are difficult to use for practical analysis due to their big difference with observation. In a comparison of the anthropogenic BC emissions inventory used in the two atmospheric composition reanalysis datasets with the Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) emissions inventory, we found that: Despite the significant decline in China's BC emissions, MERRA-2 still relies on the 2006 emissions inventory, while CAMS utilizes emission inventories that even show an increasing trend. These factors will undoubtedly lead to greater deviations between reanalysis and observational data.

A comprehensive exploration of characteristics and source attribution of carbonaceous aerosols in PM2.5 in an East China megacity.

A total of 84 PM2.5 (fine particulate matter) aerosol samples were collected between October 2020 and August 2021 within an urban site in Hangzhou, an East China megacity. Chemical species, such as organic carbon (OC), elemental carbon (EC), as well as char, soot, and n-alkanes, were analyzed to determine their pollution characteristics and source contributions. The mean yearly concentrations of OC, EC, char, soot, and total n-alkanes (∑n-alkane) were 8.76 ± 3.61 µg/m3, 1.44 ± 0.76 µg/m3, 1.21 ± 0.69 µg/m3, 0.3 ± 0.1 µg/m3, and 24.2 ± 10.6 ng/m3. The OC, EC, and ∑n-alkanes were found in the highest levels during winter and lowest during summer. There were strong correlations between OC and EC in both winter and spring, suggesting similar potential sources for these carbonaceous components in both seasons. There were poor correlations among the target pollutants due to summertime secondary organic carbon formation. Potential source contribution functions analysis showed that local pollution levels in winter and autumn were likely influenced by long-range transportation from the Plain of North China. Source index and positive matrix factorization models provided insights into the complex sources of n-alkanes in Hangzhou. Their major contributors were identified as terrestrial plant releases (32.7%), traffic emissions (28.8%), coal combustion (27.3%), and microbial activity (11.2%). Thus, controlling vehicular emissions and coal burning could be key measures to alleviate n-alkane concentrations in the atmosphere of Hangzhou, as well as other Chinese urban centers.

Evaluating the performance and influencing factors of three portable black carbon monitors for field measurement.

Black carbon (BC) is associated with adverse human health and climate change. Mapping BC spatial distribution imperatively requires low-cost and portable devices. Several portable BC monitors are commercially available, but their accuracy and reliability are not always satisfactory during continuous field observation. This study evaluated three models of portable black carbon monitors, C12, MA350 and DST, and investigates the factors that affect their performance. The monitors were tested in urban Beijing, where portable devices running for one month alongside a regular-size reference aethalometer AE33. The study considers several factors that could influence the monitors' performance, including ambient weather, aerosol composition, loading artifacts, and built-in algorithms. The results show that MA350 and DST present considerable discrepancies to the reference instrument, mainly occurring at lower concentrations (0-500 ng/m3) and higher concentrations (2500-8000 ng/m3), respectively. These discrepancies were likely caused by the anomalous noise of MA350 and the loading artifacts of DST. The study also suggests that the ambient environment has limited influence on the monitors' performance, but loading artifacts and accompanying compensation algorithms can result in unrealistic data. Based on the evaluation, the study suggests that C12 is the best choice for unsupervised field measurement, DST should be used in scenarios where frequent maintenance is available, and MA350 is suitable for research purposes with post-processing applicable. The study highlights the importance of assigning portable BC monitors to appropriate applications and the need for optimized real-time compensation algorithms.

Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study.

BACKGROUND: Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate trends in black carbon and PM2·5 concentrations and their attributable mortality burden across the USA. METHODS: In this study, we derived daily concentrations of PM2·5 and its highly toxic black carbon component at a 1-km resolution in the USA from 2000 to 2020 via deep learning that integrated big data from satellites, models, and surface observations. We estimated the annual PM2·5-attributable and black carbon-attributable mortality burden at each 1-km2 grid using concentration-response functions collected from a national cohort study and a meta-analysis study, respectively. We investigated the spatiotemporal linear-regressed trends in PM2·5 and black carbon pollution and their associated premature deaths from 2000 to 2020, and the impact of wildfires on air quality and public health. FINDINGS: Our results showed that PM2·5 and black carbon estimates are reliable, with sample-based cross-validated coefficients of determination of 0·82 and 0·80, respectively, for daily estimates (0·97 and 0·95 for monthly estimates). Both PM2·5 and black carbon in the USA showed significantly decreasing trends overall during 2000 to 2020 (22% decrease for PM2·5 and 11% decrease for black carbon), leading to a reduction of around 4200 premature deaths per year (95% CI 2960-5050). However, since 2010, the decreasing trends of fine particles and premature deaths have reversed to increase in the western USA (55% increase in PM2·5, 86% increase in black carbon, and increase of 670 premature deaths [460-810]), while remaining mostly unchanged in the eastern USA. The western USA showed large interannual fluctuations that were attributable to the increasing incidence of wildfires. Furthermore, the black carbon-to-PM2·5 mass ratio increased annually by 2·4% across the USA, mainly due to increasing wildfire emissions in the western USA and more rapid reductions of other components in the eastern USA, suggesting a potential increase in the relative toxicity of PM2·5. 100% of populated areas in the USA have experienced at least one day of PM2·5 pollution exceeding the daily air quality guideline level of 15 µg/m3 during 2000-2020, with 99% experiencing at least 7 days and 85% experiencing at least 30 days. The recent widespread wildfires have greatly increased the daily exposure risks in the western USA, and have also impacted the midwestern USA due to the long-range transport of smoke. INTERPRETATION: Wildfires have become increasingly intensive and frequent in the western USA, resulting in a significant increase in smoke-related emissions in populated areas. This increase is likely to have contributed to a decline in air quality and an increase in attributable mortality. Reducing fire risk via effective policies besides mitigation of climate warming, such as wildfire prevention and management, forest restoration, and new revenue generation, could substantially improve air quality and public health in the coming decades. FUNDING: National Aeronautics and Space Administration (NASA) Applied Science programme, NASA MODIS maintenance programme, NASA MAIA satellite mission programme, NASA GMAO core fund, National Oceanic and Atmospheric Administration (NOAA) GEO-XO project, NOAA Atmospheric Chemistry, Carbon Cycle, and Climate (AC4) programme, and NOAA Educational Partnership Program with Minority Serving Institutions.

Influence of Polycyclic Aromatic Compounds and Oxidation States of Soot Organics on the Metabolome of Human-Lung Cells (A549): Implications for Vehicle Fuel Selection.

Decades of research have established the toxicity of soot particles resulting from incomplete combustion. However, the unique chemical compounds responsible for adverse health effects have remained uncertain. This study utilized mass spectrometry to analyze the chemical composition of extracted soot organics at three oxidation states, aiming to establish quantitative relationships between potentially toxic chemicals and their impact on human alveolar basal epithelial cells (A549) through metabolomics-based evaluations. Targeted analysis using MS/MS indicated that particles with a medium oxidation state contained the highest total abundance of compounds, particularly oxygen-containing polycyclic aromatic hydrocarbons (OPAHs) composed of fused benzene rings and unsaturated carbonyls, which may cause oxidative stress, characterized by the upregulation of three specific metabolites. Further investigation focused on three specific OPAH standards: 1,4-naphthoquinone, 9-fluorenone, and anthranone. Pathway analysis indicated that exposure to these compounds affected transcriptional functions, the tricarboxylic acid cycle, cell proliferation, and the oxidative stress response. Biodiesel combustion emissions had higher concentrations of PAHs, OPAHs, and nitrogen-containing PAHs (NPAHs) compared with other fuels. Quinones and 9,10-anthraquinone were identified as the dominant compounds within the OPAH category. This knowledge enhances our understanding of the compounds contributing to adverse health effects observed in epidemiological studies and highlights the role of aerosol composition in toxicity.

Source apportionment, health risk assessment, and trajectory analysis of black carbon and light absorption properties of black and brown carbon in Delhi, India.

Black Carbon (BC) is an important atmospheric pollutant, well recognized for adverse health and climatic effects. The present work discusses the monthly and seasonal variations of BC sources, health risks, and light absorption properties. The measurement was done from January to December 2021 using a seven wavelength aethalometer. Annual average BC concentration during the study period was 12.2 ± 8.8 µg/m3 (ranged from 1.9 - 52.2 µg/m3). Results represent highest BC concentration during winter (W), followed by post-monsoon (P-M), summer (S), and monsoon (M) seasons where the fossil fuel (FF) combustion is the major source during W, S, and M seasons and biomass burning (BB) during the P-M season. The health risk assessment revealed that individuals in Delhi are exposed to BC levels equivalent to inhaling the smoke from 36 passively smoked cigarettes (PSC) everyday. The risk is highest during W reaching upto 71 PSC and minimum during M i.e., 9 PSC. The light absorption properties were calculated for BC (AbsBC) and Brown carbon (AbsBrC). AbsBC and varied from 229-89 Mm-1 between 370-950 nm and AbsBrC varied from 87-12 Mm-1 between 370-660 nm. AbsBC contributed substantially to total absorption at all wavelengths, while AbsBrC contribution is quite significant in the UV region only. Trajectory analysis confirmed significant influence of regional sources (e.g., biomass-burning aerosols from northwest and east direction) on air quality, health risks, and light absorption properties of BC over Delhi especially during the P-M season. The BB events of Punjab, Haryana, Uttar Pradesh, and eastern Pakistan seems to have significant influence on Delhi's air quality predominantly during P-M season.

The connection between six common air pollution particles and adult brain tumors: a meta-analysis of 26,217,930 individuals.

Environmental air pollutants (black carbon (BC), nitrogen oxides (NOx), particulate matter with diameter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), particulate matter with diameter <10 µm (PM10), and ozone (O3)) are one of the major menaces to mankind's health globally. This analysis reviews the association between exposure to these air pollutants and the chance of developing brain tumors in adults (total brain tumors, malignant brain tumors, and benign brain tumors). Studies published by April 2022 were searched. Raw effect sizes were converted to standardized effect sizes per 10 µg/m3 increase. Random effect models were applied to calculate combined effect size and 95% confidence intervals (CIs) were computed. A total of 8 articles were included for meta-analysis. The pooled effect size (ES) for per 10 µg/m3 BC intake was 1.67 (95% CI: 1.25, 2.22), P = 0.449. For every 10 µg/m3 rise in NO2 concentration, ES was 1.03 (95% CI: 1.01, 1.05), P = 0.319. Meanwhile, there was a boundary association between NOx and adult brain tumors (ES and 95% CI: 1.01; 1.00, 1.01/10 µg/m3; P = 0.716). While there was no conjunction between PM2.5, PM10, O3 (PM2.5: ES and 95% CI: 1.04; 0.99, 1.08/10 µg/m3; P = 0.834; PM10: ES and 95% CI: 1.01; 0.97, 1.04/10 µg/m3; P = 0.627; O3: ES and 95% CI: 0.97; 0.94, 1.00/10 µg/m3; P = 0.253). This research shows testimony of a significant link between air pollutants and brain tumors in adults, especially when exposed to BC, NO2, and NOx. This evidence emphasizes the importance of improving air quality as part of a comprehensive approach to prevent the occurrence and deterioration of brain tumors.

Early-life exposure to residential black carbon and childhood cardiometabolic health.

BACKGROUND: Early life exposure to air pollution, such as particulate matter ≤2.5 µm (PM2.5), may be associated with obesity and adverse cardiometabolic health outcomes in childhood. However, the toxicity of PM2.5 varies according to its chemical composition. Black carbon (BC) is a constituent of PM2.5, but few studies have examined its impact on childhood cardiometabolic health. Therefore, we examined relationships between prenatal and early childhood exposure to BC and markers of adiposity and cardiometabolic health in early childhood. METHODS: This study included 578 mother-child pairs enrolled in the Healthy Start study (2009-2014) living in the Denver-metro area. Using a spatiotemporal prediction model, we assessed average residential black carbon levels during pregnancy and in the year prior to the early childhood follow-up visit at approximately 5 years old. We estimated associations between prenatal and early childhood BC and indicators of adiposity and cardiometabolic biomarkers in early childhood (mean 4.8 years; range, 4.0, 8.3), using linear regression. RESULTS: We found higher early childhood BC was associated with higher percent fat mass, fat mass index, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and lower leptin and waist circumference at approximately 5 years old, after adjusting for covariates. For example, per interquartile range (IQR) increase in early childhood BC (IQR, 0.49 µg/m3) there was 3.32% higher fat mass (95% CI; 2.05, 4.49). Generally, we did not find consistent evidence of associations between prenatal BC and cardiometabolic health outcomes in early childhood, except for an inverse association between prenatal BC and adiponectin, an adipocyte-secreted hormone typically inversely associated with adiposity. CONCLUSIONS: Higher early childhood, but not in utero, ambient concentrations of black carbon, a component of air pollution, were associated with greater adiposity and altered insulin homeostasis at approximately 5 years old. Future studies should examine whether these changes persist later in life.