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Urban air pollution can vary sharply in space and time. However, few monitoring strategies can concurrently resolve spatial and temporal variation at fine scales. Here, we present a new measurement-driven spatiotemporal modeling approach that transcends the individual limitations of two complementary sampling paradigms: mobile monitoring and fixed-site sensor networks. We develop, validate, and apply this model to predict black carbon (BC) using data from an intensive, 100-day field study in West Oakland, CA. Our spatiotemporal model exploits coherent spatial patterns derived from a multipollutant mobile monitoring campaign to fill spatial gaps in time-complete BC data from a low-cost sensor network. Our model performs well in reconstructing patterns at fine spatial and temporal resolution (30 m, 15 min), demonstrating strong out-of-sample correlations for both mobile (Pearson's R ∼ 0.77) and fixed-site measurements (R ∼ 0.95) while revealing features that are not effectively captured by a single monitoring approach in isolation. The model reveals sharp concentration gradients near major emission sources while capturing their temporal variability, offering valuable insights into pollution sources and dynamics.

The effects of global climate change have accelerated the melting of glaciers and the decline of sea ice coverage in the Arctic. In tandem with advancements in icebreaker and other shipping technologies, the navigability of Arctic shipping routes has dramatically improved. Given the geographical advantages of the Arctic region in terms of shipping routes and resource potential, various countries have implemented initiatives to secure a foothold in the Arctic shipping industry. However, the current shipping industry has not yet achieved the ideal state of netzero emissions, and the rapid increase in Arctic shipping has brought serious and even irreversible negative impacts on the Arctic environment. The study employs document and policy analyses to conduct an in-depth examination of legal and policy documents related to Arctic shipping, especially those from the past 5 years, systematically outlining the relevant legal and policy frameworks, as well as their historical context. At the same time, interdisciplinary research methods are utilized to comprehensively assess the new challenges. It is concluded that against the backdrop of the Arctic region's unique and fragile environment, the International Maritime Organization (IMO) and the Arctic Council are introducing increasingly stringent regulations for Arctic shipping, posing a complex array of challenges for the industry. Not only must it navigate the mounting pressure of emission reduction policies and intensifying public scrutiny but it must also overcome a multitude of complex technical and operational hurdles. Consequently, the joint efforts of the international community are essential to promote the sustainable development and emission reduction goals of the Arctic shipping industry. [ABSTRACT FROM AUTHOR]

In megacities, road traffic is a major source of particulate matter (PM), requiring a critical understanding of effective air pollution control. Despite existing methods to determine PM emission factors (EFs) of vehicles, accurate estimation of PM emissions under real driving conditions remains challenging. We aimed to assess the EFs of organic aerosol (OA) and equivalent black carbon (eBC) from vehicles through on-road measurements in Seoul, Korea, to understand real-world PM emissions. We used a mobile laboratory equipped with an aerosol mass spectrometer and an aethalometer to measure the composition of PM. On-road measurements were conducted in vehicle tunnels, urban roadways, and residential areas, and the characteristics of measurement points were compared and analyzed. Our results showed that concentrations of OA increased proportionally with the influence of vehicle exhaust, while oxidation states of the OA decreased. Mobile measurements revealed spatial heterogeneities in aerosols, highlighting distinct characteristics of fresh OA on vehicle roads and elevated oxidation state values in residential areas. Active nitrate formation near vehicles led to elevated NO3 concentrations on roads compared to residential areas. Our study shows that mobile PM measurements, including OA and eBC, are valuable for the direct evaluation of emission inventories. However, given that the calculated EFs may not be applicable to other cities due to differences in vehicle composition and traffic conditions, the development of city-specific EFs will be necessary in the future. Furthermore, it is recommended to integrate this methodology with conventional emission inventories to identify vehicle-type-specific emissions. [ABSTRACT FROM AUTHOR]

Black carbon (BC) is a highly persistent yet poorly understood component of forest soil carbon reservoirs, while its inventory, distribution, and determining factors in forest soils on a large geographic scale remain unclear. Here, we characterized soil BC across 68 Chinese forest sites using benzene polycarboxylic acid method and developed machine learning (ML) models to predict and interpret potential impacts of soil organic matter (SOM) properties, soil physiochemical properties, meteorological conditions, wildfire history, and microbial diversity on BC. Results revealed that SOM properties were the most critical in predicting BC, complemented by the negative impact of mean annual temperature and alkaline mineral composition. The superior prediction accuracy for BC with higher condensed aromaticity (more benzene hexa‐ and penta‐carboxylic acid monomers) likely results from its simpler sources and greater resistance to transformation. This study introduces an effective ML model for predicting and interpreting soil BC inventory to better understand BC cycling. Plain Language Summary: The black carbon (BC) derived from incomplete biomass combustion serves as a potential reservoir to store carbon in land ecosystems. Despite BC's significance in carbon sequestration, its inventory and distribution on a large geographic scale remains elusive. As such, we characterized both the quantity and quality of soil BC for forest sites across China. We find that soil BC content averaged 1.99 ± 1.94 mg C g−1 and constituted 8.8% ± 4.9% of soil organic carbon, without showing a clear geographic distribution pattern. Besides the well‐acknowledged predictive power of machine learning (ML) methodologies, they were introduced to determine the impacts of soil properties and environmental parameters in controlling the BC distribution. We discovered that soil organic matter properties were the most important parameters in predicting BC content, accounting for over 50% of the contribution in model construction based on mean absolute Shapley value. Alongside meteorological conditions, they were further extracted as the key parameters for predicting BC content to simplify the ML model. As a promising complement to traditional geochemical approaches, this research highlights the potential of leveraging ML to predict and interpret BC inventory on a global scale. Key Points: The black carbon (BC) inventory and distribution in Chinese forest soils on a large geographic scale were first determinedMachine learning (ML) models exhibited superior prediction accuracy for BC with higher condensed aromaticitySoil organic matter properties were the most critical in predicting BC content [ABSTRACT FROM AUTHOR]

Black carbon is a short-lived climate warming agent and serves as a crucial factor influencing the climate. Numerous models, observations, and laboratory studies have been conducted to quantify black carbon's direct or indirect impacts on the climate. Here, we applied bibliometric analysis to identify research trends and key topics on black carbon in the climate field. Based on the Web of Science (WOS) Core Collection database, a total of 4903 documents spanning the period from 2000 to 2023 were retrieved and screened, focusing on the topic of black carbon in the climate field, resulting in the Black-Carbon Climate Local (BCL) dataset. Our study examines the influence and trends of major countries, institutions, and authors in this field. The results show that China and the United States hold leading positions in terms of the number of publications. Based on keyword networks, the BCL dataset is segmented into six distinct research directions, and representative keywords of each direction include biomass burning, radiative forcing, air pollution, aerosol optical depth, optical properties, and biochar. This study helps to identify the current research status and trends of black carbon in the climate, highlighting main research directions and emerging topics. [ABSTRACT FROM AUTHOR]

Black carbon (BC) is a crucial air pollutant that contributes to short-lived climate forcing and adverse health impacts. BC emissions have rapidly declined over the past three decades and it is important to uncover the major factors behind this decline. Herein, the temporal trends in BC emissions were compiled from 146 detailed sources from 1960 to 2019. Results revealed that the major emission sources were residential solid fuel usage, coke production and brick production. Furthermore, 96.9% of the emission reduction from 3.03 Tg in 1995 to 1.02 Tg in 2019 was attributed to these three sources. It was determined that the transition in residential energy/stove usage, phasing-out of beehive coke ovens and brick kiln upgrading were the most important drivers leading to this reduction and will continue to play a key role in future emission mitigation. In addition, this study identified the need to address emissions from coal used in vegetable greenhouses and the commercial sector, and diesel consumption in on/off-road vehicles. [ABSTRACT FROM AUTHOR]

Black carbon (BC) changes the radiative flux in the atmosphere by absorbing solar radiation, influencing photochemistry in the troposphere. To evaluate the seasonal direct radiative effects (DREs) of BC and its influence on surface atmospheric oxidants in China, the WRF-Chem model was utilized in this study. The simulation results suggested that the average annual mean values of the clear-sky DREs of BC at the top of the atmosphere, in the atmosphere and at the surface over China are +2.61, +6.27 and −3.66 W m−2, respectively. Corresponding to the seasonal variations of BC concentrations, the relative changes of the mean surface photolysis rates (J[O1D], J[NO2] and J[HCHO]) in the four seasons range between −3.47% and −6.18% after turning off the BC absorption, which further leads to relative changes from −4.27% to −6.82%, −2.14% to −4.40% and −0.47% to −2.73% in hydroxyl (OH) radicals, hydroperoxyl (HO2) radicals and ozone (O3), respectively. However, different from the relative changes, the absolute changes in OH and HO2 radicals and O3 after turning off BC absorption show discrepancies among the different seasons. In the North China Plain (NCP) region, O3 concentration decreases by 1.79 ppb in the summer, which is higher than the magnitudes of 0.24–0.88 ppb in the other seasons. In southern China, the concentrations of OH and HO2 radicals reach the maximum decreases in the spring and autumn, followed by those in the summer and winter, which is due to the enhancement of solar radiation and the summer monsoon. Thus, BC inhibits the formation of atmospheric oxidants, which further weakens the atmospheric oxidative capacity. [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosols have attracted wide attention over the world due to their significant climate effects on local and global scales. BC extinction aerosol optical thickness (AOT), scattering AOT, and single scattering albedo (SSA) over China are systematically studied based on the MERRA-2 satellite reanalysis data from 1983 to 2022 in terms of the spatial, yearly, seasonal, and monthly variations. The extinction and scattering AOTs of BC show similar spatial distribution, with high values in eastern and southern China, generally as opposed to BC SSA. A decrease in BC extinction and scattering AOTs has been documented over the last decade. The mean BC extinction AOT, scattering AOT, and SSA over China are 0.0054, 0.0014, and 0.26, respectively. The BC SSA showed small variations during 1983–2022, although a high BC extinction AOT and scattering AOT have been seen in the last two decades. During different decades, the seasonal patterns of BC extinction and scattering AOTs may differ, whereas the BC SSA shows seasonal consistency. Significant monthly variations in the BC SSA are seen over four decades, which are in agreement with their seasonal patterns. The mean BC extinction AOTs are 0.037, 0.033, 0.023, and 0.0054, whereas the average BC scattering AOTs are 0.0088, 0.0082, 0.0060, and 0.0014 in the Pearl River Delta (PRD), Yangtze River Delta (YRD), Beijing–Tianjin–Hebei (BTH) region, and Tarim Basin (TB), respectively. It is interesting to see that BC SSA values in the TB region are generally higher than those over the PRD, YRD and BTH areas, whereas the reverse is true for BC extinction and scattering AOTs. This study provides references for further research on black carbon aerosols and air pollution in China. [ABSTRACT FROM AUTHOR]

Black carbon (BC), primarily originating from fossil fuel and biomass combustion, holds significance for global carbon cycling, climate change, and human health. Despite a lake's role as a carbon sink, detailed information about BC sedimentary burial flux and sink in its sediment remains insufficiently explored. The current study investigates the distribution, sources, and burial flux of BC and its subtypes (char and soot) in the surface sediment of Daye Lake, the largest lake in Huangshi City, central China. BC concentrations in the sediment ranged from 0.10 to 3.60 mg/g, corresponding to 0.40%–17.02% of organic carbon (OC). Higher values of BC and BC/OC observed in the western region suggest direct terrestrial input via river discharge and surface runoff, influenced by anthropogenic activities. In contrast, variations in char/soot ratios reflect diverse combustion sources and hydrological dynamics in different regions. The indications from BC/OC and char/soot ratios imply that fossil fuel combustion is the predominant sources. The weak correlations between BC and OC suggest that they may come from different sources or undergo different processes that affect their distribution in the lake sediment. However, a stronger correlation was observed between BC and soot, as well as between char and soot, indicating potential similarities in their input pathways. The BC burial flux displays notable variations across the lake, ranging from 0.69 to 24.07 g/m2/yr, with elevated values observed in the western region. The BC sink in the sediments of Daye Lake was estimated to be 0.635 Gg/yr. Though locally small, it significantly contributes to the broader picture of BC burial in Chinese lakes and the global distribution of BC in lake ecosystems. [ABSTRACT FROM AUTHOR]

Light‐absorbing carbonaceous aerosols that dominate atmospheric aerosol warming over India remain poorly characterized. Here, we delve into UV‐visible‐IR spectral aerosol absorption properties at nine PAN‐India COALESCE network sites (Venkataraman et al., 2020, https://doi.org/10.1175/bams‐d‐19‐0030.1). Absorption properties were estimated from aerosol‐laden polytetrafluoroethylene filters using a well‐constrained technique incorporating filter‐to‐particle correction factors. The measurements revealed spatiotemporal heterogeneity in spectral intrinsic and extrinsic absorption properties. Absorption analysis at near‐UV wavelengths from carbonaceous aerosols at these regional sites revealed large near‐ultraviolet brown carbon absorption contributions from 21% to 68%—emphasizing the need to include these particles in climate models. Further, satellite‐retrieved column‐integrated absorption was dominated by surface absorption, which opens possibilities of using satellite measurements to model surface‐layer optical properties (limited to specific sites) at a higher spatial resolution. Both the satellite‐modeled and direct in‐situ absorption measurements can aid in validating and constraining climate modeling efforts that suffer from absorption underestimations and high uncertainties in radiative forcing estimates. Plain Language Summary: Particulate pollution in the atmosphere scatter and absorb incoming solar energy, thus cooling or warming Earth's atmosphere. In developing countries and especially in India, one of the most polluted regions of the world, the extent to which particles can absorb solar energy and warm the atmosphere is not well understood. Here, for the first time, we measure particle absorption simultaneously at nine ground sites across India, in diverse geographical regions with different levels and types of particulate pollution. We find that organic carbon particles exert large absorption at near‐ultraviolet wavelengths, which contain significant solar energy. These light absorbing organic carbon particles, called brown carbon, are emitted in large quantities from biomass burning (e.g., burning crop residue and cooking on wood‐fired stoves). Comparing ground measurements of absorption with satellite‐retrieved measurements that are representative of the entire atmospheric column, we find that near‐surface atmospheric particles can exert significant warming. This study highlights the need to improve climate model simulations of particulate pollution's impact on the climate by incorporating spatiotemporal surface‐level absorption measurements, including absorption by brown carbon particles. Key Points: Measurements at nine regional PAN‐India sites reveal several regions with large aerosol absorption strengthBrown carbon contributes significantly (21%–68%) to near‐ultraviolet absorption, indicating its importance in shortwave light absorptionStrong correlations observed between satellite data and surface absorption indicate future potential in modeling surface absorption [ABSTRACT FROM AUTHOR]

Indoor air quality can be affected by the presence of atmospheric pollutants, which impact severely in human health. The objectives were to show the characterization of particle number (PN0.3–PN2.5), particles mass (PM1.0, PM2.5, PM10), Black Carbon (BC), Brown Carbon (BrC) and bioaerosols (fungi and bacteria) in indoor environments of three pizzerias that have wood ovens as fuel at Londrina, Brazil. Mean Particle mass concentration varied amongst the pizzerias (28.9–42.4 µg m−3 for PM2.5) with the levels of BC and BrC reaching up to 42.9 µg m−3 and 29.4 µg m−3, respectively. These were correlated with the air ventilation of the place, the amount of wood burned, and service mode (e.g., all-can-eat). Furthermore, an average of 934 ± 404 CFU m−3 of bacteria was found in all places and Aspergillus, Penicillium, and Cladosphialophora were the most important fungal genera found. Inside kitchens, the concentrations of PM2.5, BC, BrC, bacteria and fungi were 29.6, 3.0, 2.8 µg m−3, 876, and 1261 CFU m−3, with a mean ratio of BrC/PM2.5 of 0.06, that indicates this as a significant source for BrC. Finally, the concentrations of PM and bioaerosols found inside kitchens demonstrate pollution levels much higher than those recommended by national and international guidelines. Consequently, problems associated with poor indoor air quality will only be solved when adequate kitchen designs are considered. From the results of this work is possible to conclude that the building characteristics of kitchen and the burning process carried out are important factors for the concentrations of pollutants analyzed in the indoor air of wood-burning kitchens. [ABSTRACT FROM AUTHOR]

In 2020, the COVID-19 outbreak led many countries across the globe to introduce lockdowns (LDs) that effectively caused most anthropic activities to either stop completely or be significantly reduced. In Europe, Italy played a pioneeristic role via the early introduction of a strict nationwide LD on March 9th. This study was aimed at evaluating, using both chemical and meteorological data, the environmental response to that occurrence as observed by the Lamezia Terme (LMT) GAW/WMO station in Calabria, Southern Italy. The first 2020 lockdown was therefore used as a "proving ground" to assess CO, CO2, CH4, BC, and NOx concentrations in a rather unique context by exploiting the location of LMT in the context of the Mediterranean Basin. In fact, its location on the Tyrrhenian coast of Calabria and local wind circulation both lead to daily cycles where western-seaside winds depleted in anthropogenic pollutants can be easily differentiated from northeastern-continental winds, enriched in anthropogenic outputs. In addition to this, the first Italian LD occurred during the seasonal transition from winter to spring and, consequently, summer, thus providing new insights on emission outputs correlated with seasons. The findings clearly indicated BC and, in particular, CO as strongly correlated with average daily temperatures, as well as possibly domestic heating. CO2's reduction during the lockdown and consequent increase in the post-lockdown period, combined with wind data, allowed us to constrain the local source of emissions located northeast from LMT. NOx reductions during specific circumstances were consistent with hypotheses from previous research, which linked them to rush hour traffic and other forms of transportation emissions. CH4's stable patterns were consistent with livestock, landfills, and other sources assumed to be nearly constant during LD periods. [ABSTRACT FROM AUTHOR]

The key to a sustainable future is the reduction in humankind's impact on natural systems via the development of new technologies and the improvement in source apportionment. Although days, years and seasons are arbitrarily set, their mechanisms are based on natural cycles driven by Earth's orbital periods. This is not the case for weeks, which are a pure anthropic category and are known from the literature to influence emission cycles and atmospheric chemistry. For the first time since it started data gathering operations, CO (carbon monoxide), CO2 (carbon dioxide), CH4 (methane) and eBC (equivalent black carbon) values detected by the Lamezia Terme WMO/GAW station in Calabria, Southern Italy, have been evaluated via a two-pronged approach accounting for weekly variations in absolute concentrations, as well as the number of hourly averages exceeding select thresholds. The analyses were performed on seven continuous years of measurements from 2016 to 2022. The results demonstrate that the analyzed GHGs (greenhouse gasses) and aerosols respond differently to weekly cycles throughout the seasons, and these findings provide completely new insights into source apportionment characterization. Moreover, the results have been combined into a new parameter: the hereby defined WDWO (Weighed Distribution of Weekly Outbreaks) normalizes weekly trends in CO, CO2, CH4 and eBC on an absolute scale, with the scope of providing regulators and researchers alike with a new tool meant to better evaluate anthropogenic pollution and mitigate its effects on the environment and human health. [ABSTRACT FROM AUTHOR]

This study compares the PM10 (particulate matter of diameter smaller than 10 μm) organic aerosol composition between urban and suburban stations in Heraklion, Crete, during winter 2024 in order to highlight the impact of local anthropogenic activities on urban atmospheric particulate matter pollution. Using an HPLC-ESI-MS Orbitrap analyzer (High Performance Liquid Chromatography-Electrospray Ionization-Mass Spectrometry) in full MS scan mode at a resolution of 140,000, 48 daily aerosol filter extracts were analyzed in both positive and negative modes, resulting in the detection of 2809 and 3823 features, respectively. Features with at least five times higher intensity in the urban environment compared to the suburban, and p < 0.05, were deemed significant. A correlation with black carbon (r > 0.6) was observed for 71% of significant urban features in positive mode. These features showed a predominance of low O:C ratios (<0.2) and the majority were classified as intermediate volatility organic compounds (IVOCs), indicating fresh primary emissions. A clear urban–suburban distinction was shown by PCA of positive mode features, unlike the negative mode features. Regarding the total intensity of the features, urban samples were on average 55% higher than suburban samples in positive mode and 39% higher in negative mode. This study reveals the molecular profile of locally emitted combustion related organics observed in positive mode in an urban environment. [ABSTRACT FROM AUTHOR]

This study explores the spatial patterns of particulate matter (PM) in the megacity of Delhi. A GRIMM aerosol spectrometer is used to analyze different aerodynamic diameters (PM10, PM2.5, PM1.0), inhalable, thoracic, and alveolic particles, and black carbon (BC) at six prominent locations in Delhi during summer and winter. Additionally, metals (Pb, Fe, Ca, Al, Zn), along with silicon and sulfur, are analyzed using an ED-XRF spectrometer over the sampling locations during the summer season. The sampling site data are interpolated using the Kriging method to generate spatial maps to explore the air pollution problem in Delhi. East Delhi is observed to be the most polluted site, while Guru Gobind Singh Indraprastha University (GGSIPU) is the least polluted site. We further observe a high correlation between Al-Fe, Al-Ca, Zn-Pb, Ca-Fe, and S-Zn, indicating their common source of emission. Aerosols are also found to be highly enriched with metals like Al, S, Fe, Zn, and Pb, suggesting strong anthropogenic sources of these metals. Construction activities, resuspended dust, an increased number of vehicles, faulty agricultural practices, and soil could be recognized as major sources of the particulate concentration in an urban area like Delhi. [ABSTRACT FROM AUTHOR]

Abstract In megacities, road traffic is a major source of particulate matter (PM), requiring a critical understanding of effective air pollution control. Despite existing methods to determine PM emission factors (EFs) of vehicles, accurate estimation of PM emissions under real driving conditions remains challenging. We aimed to assess the EFs of organic aerosol (OA) and equivalent black carbon (eBC) from vehicles through on-road measurements in Seoul, Korea, to understand real-world PM emissions. We used a mobile laboratory equipped with an aerosol mass spectrometer and an aethalometer to measure the composition of PM. On-road measurements were conducted in vehicle tunnels, urban roadways, and residential areas, and the characteristics of measurement points were compared and analyzed. Our results showed that concentrations of OA increased proportionally with the influence of vehicle exhaust, while oxidation states of the OA decreased. Mobile measurements revealed spatial heterogeneities in aerosols, highlighting distinct characteristics of fresh OA on vehicle roads and elevated oxidation state values in residential areas. Active nitrate formation near vehicles led to elevated NO3 concentrations on roads compared to residential areas. Our study shows that mobile PM measurements, including OA and eBC, are valuable for the direct evaluation of emission inventories. However, given that the calculated EFs may not be applicable to other cities due to differences in vehicle composition and traffic conditions, the development of city-specific EFs will be necessary in the future. Furthermore, it is recommended to integrate this methodology with conventional emission inventories to identify vehicle-type-specific emissions. Graphical Abstract

Abstract Indoor air quality can be affected by the presence of atmospheric pollutants, which impact severely in human health. The objectives were to show the characterization of particle number (PN0.3–PN2.5), particles mass (PM1.0, PM2.5, PM10), Black Carbon (BC), Brown Carbon (BrC) and bioaerosols (fungi and bacteria) in indoor environments of three pizzerias that have wood ovens as fuel at Londrina, Brazil. Mean Particle mass concentration varied amongst the pizzerias (28.9–42.4 µg m−3 for PM2.5) with the levels of BC and BrC reaching up to 42.9 µg m−3 and 29.4 µg m−3, respectively. These were correlated with the air ventilation of the place, the amount of wood burned, and service mode (e.g., all-can-eat). Furthermore, an average of 934 ± 404 CFU m−3 of bacteria was found in all places and Aspergillus, Penicillium, and Cladosphialophora were the most important fungal genera found. Inside kitchens, the concentrations of PM2.5, BC, BrC, bacteria and fungi were 29.6, 3.0, 2.8 µg m−3, 876, and 1261 CFU m−3, with a mean ratio of BrC/PM2.5 of 0.06, that indicates this as a significant source for BrC. Finally, the concentrations of PM and bioaerosols found inside kitchens demonstrate pollution levels much higher than those recommended by national and international guidelines. Consequently, problems associated with poor indoor air quality will only be solved when adequate kitchen designs are considered. From the results of this work is possible to conclude that the building characteristics of kitchen and the burning process carried out are important factors for the concentrations of pollutants analyzed in the indoor air of wood-burning kitchens.

Global warming in tandem with surface albedo reduction caused by black carbon (BC) deposition on glaciers accelerated glacier melting; however, their respective contributions remain unclear. Glaciers in the Qilian Mountains are crucial for the development of oases in the Hexi Corridor; however, their area has decreased by more than 20% over the past half-century. Thus, this study developed a dynamic deposition model for light-absorbing particles (LAPs), coupled with a surface energy and mass balance model. We comprehensively assessed the effects of BC and warming on the melting of a typical glacier in the Qilian Mountains based on the coupled model. BC on the glacier surface caused 13.1% of annual glacier-wide melting, of which directly deposited atmospheric BC reduced the surface albedo by 0.02 and accounted for 9.1% of glacier melting. The air temperature during 2000–2010 has increased by 1.5 °C relative to that during the 1950s, accounting for 51.9% of current glacier melting. Meanwhile, BC emission have increased by 4.6 times compared to those of the early Industrial Revolution recorded in an ice core, accounting conservatively for 6.3% of current glacier melting. Mitigating BC emissions has a limited influence on current glacier melting; however, in the long-term, mitigation should exert a noteworthy impact on glacier melting through the self-purification of glaciers.

Abstract Background There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited. Methods A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. Results After adjustment for confounders, exposure to PM2.5 and its constituents (NO3 −, NH4 +, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3 − and NH4 + occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118–1.293) and 18.2% (95% CI. 1.107–1.263), respectively. The lowest inflection points between PM2.5, SO4 2−, NO3 −, NH4 +, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO4 2−, OM, and BC and the risk of GDM was observed. Conclusions This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3 −, NH4 +, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM.

Certification standards for non-volatile particulate matter (nvPM) emissions from aircraft engines have recently been adopted by ICAO as the CAEP10 standard in 2016 and the CAEP11 standard in 2019. The measurements of the nvPM levels are prescribed in ICAO (2019) and SAE documents (2021). The measurement system specifications are designed to minimize the volatile contributions to the measured nvPM quantities. In a series of “certification-like” measurement campaigns that were used to collect data for developing the ICAO nvPM standards, the volatile particulate matter (vPM) contributions to the measured nvPM were quantified. An Aerosol Mass Spectrometer (AMS) in concert with a Cavity Attenuation Phase Shift (CAPS) monitor were used to measure the vPM and nvPM levels, respectively. These vPM contributions are primarily representative of coatings on the nvPM soot particles. Data from a range of engine designs were collected and the relative amounts of vPM to nvPM were ascertained to determine how much the vPM component could affect the nvPM quantification. For the engines evaluated, which span a variety of in‑service engines in the commercial fleet, the vPM contributions are small, averaging 3 % of the nvPM mass value, and were usually relatively independent of engine power condition.

Background: There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited. Methods: A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. Results: After adjustment for confounders, exposure to PM2.5 and its constituents (NO3−, NH4+, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3− and NH4+ occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118–1.293) and 18.2% (95% CI. 1.107–1.263), respectively. The lowest inflection points between PM2.5, SO42−, NO3−, NH4+, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO42−, OM, and BC and the risk of GDM was observed. Conclusions: This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3−, NH4+, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM. [ABSTRACT FROM AUTHOR]

In recent years, the role of the atmosphere in the formation of the chemical composition of water in Lake Baikal and its tributaries has been increasing. In this regard, the study of equivalent black carbon (eBC) in the air above the lake and its coast has an important practical application. This paper presents the results of the mass concentration of eBC and submicron aerosol in the air above the water area of Lake Baikal, which were obtained during expeditions onboard research vessels in the summer of 2019 and 2023. We analyzed the data from the coastal monitoring station Listvyanka. To measure eBC, an MDA-02 aethalometer was used in the water area of the lake, and a BAC-10 aethalometer at the Listvyanka station. The background level of the eBC concentration in the air at different areas of the lake ranged between 0.15 and 0.3 µg m−3. The results of the two expeditions revealed the influence of the coastal settlements and the air mass transport along the valleys of the lake's large tributaries on the five- to twentyfold growth of the eBC concentration in the near-water atmosphere. In the diurnal dynamics of eBC near settlements, we recorded high values in the evening and at night. In background areas, the diurnal dynamics were poorly manifested. In the summer of 2019, there were smoke plumes in the water area of Lake Baikal from distant wildfires and a local fire site on the east coast of the lake. The eBC concentration increased to 5–6 µg m−3, which was 10 to 40 times higher than the background. The long-range transport of plumes from coal-fired thermal power plants in large cities of the region made the major contribution to the eBC concentration at «Listvyanka» in winter, which data on aerosol, gas impurities, and meteorological parameters confirmed. [ABSTRACT FROM AUTHOR]

Over the years, the Cape Peninsula has seen a rise in the number of fires that occur seasonally. This study aimed to investigate the extent of fire spread and associated damages during the 2023/2024 Cape Peninsula fire events. Remote sensing datasets from Sentinel-5P, Sentinel-2, Moderate Resolution Imaging Spectroradiometer (MODIS), and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) were used. Most of the fires on the northern side of the Cape Peninsula had a short burning span of between 6 and 12 h, but fires with a duration of 12–24 h were minimal. The northern area is composed of low forests and thickets as well as fynbos species, which were the primary fuel sources. Excessive amounts of carbon monoxide (CO) and black carbon (BC) emissions were observed. High speeds were observed during the period of the fires. This is one of the factors that led to the spread of the fire. Relative humidity at 60% was observed, indicating slightly dry conditions. Additionally, the Leaf Water Content Index (LWCI) indicated drier vegetation, enhancing fire susceptibility. High temperatures, low moisture and strong winds were the main drivers of the fire. The Normalized Burn Ratio (NBR) values for the targeted fires showed values close to −1, which signifies presence of a fire scar. The study can be of use to those in the fire management agencies and biodiversity conservation in the region. [ABSTRACT FROM AUTHOR]

This study aims to delineate the characteristics of black carbon (BC) in the atmosphere over the urban background environment in Vilnius (Lithuania) from 1 June 2021 to 31 May 2022 using aethalometer (Magee Scientific) measurements. The annual mean concentrations of BC originating from fossil fuels (BCff) and from biomass burning (BCbb) were found to be 0.63 μg m−3 with a standard deviation (SD) of 0.67 μg m−3 and 0.27 µg m−3 (0.35 μg m−3). The further findings highlight the dominance of fossil-fuel-related BC throughout the study period (71%) and the seasonal variability of BC pollution, with biomass-burning-related BC making the largest contribution during the summer season (41%) and the smallest contribution during autumn (23%). This information provides valuable insights into the sources and dynamics of BC pollution in the region. The sources and composition of BC on the days with the highest pollution levels were influenced by a combination of local and regional factors in every season. Additionally, this study employs an advanced approach to understanding urban BC pollution by focusing on high-pollution days (18), identified based on a daily mean BC mass concentration exceeding the 95th percentile, alongside an analysis of overall seasonal and diurnal variations. This methodology surpasses many those of previous urban BC studies, offering a comprehensive examination of the sources and composition of BC pollution. [ABSTRACT FROM AUTHOR]

Residential wood combustion (RWC) is a significant source of gaseous and particulate emissions causing adverse health and environmental effects. Several factors affect emissions, but the effects of the fuel wood species on emissions are currently not well understood. In this study, the Nordic wood species (named BirchA, BirchB, Spruce, SpruceDry, Pine and Alder) were combusted in a modern stove, and the emissions were studied. The lowest emissions were obtained from the combustion of BirchA and the highest from Spruce and Alder. The fine particle mass (PM2.5) was mainly composed of elemental carbon (50–70% of PM2.5), which is typical in modern appliances. The lowest PAH concentrations were measured from BirchA (total PAH 107 µg/m3) and Pine (250 µg/m3). In the ignition batch, the PAH concentration was about 4-fold (416 µg/m3). The PAHs did not correlate with other organic compounds, and thus, volatile organic compounds (VOCs) or organic carbon (OC) concentrations cannot be used as an indicator of PAH emissions. Two birch species from different origins with a similar chemical composition but different density produced partially different emission profiles. This study indicates that emission differences may be due more to the physical properties of the wood and the combustion conditions than to the wood species themselves. [ABSTRACT FROM AUTHOR]

Mobile monitoring is used as an additional tool to collect air quality data at a high spatial resolution and to complement data from fixed air quality stations. Citizens are interested in contributing to air quality monitoring, and while the availability of low-cost air quality sensors can create opportunities to measure the air quality at a high spatial resolution, the data are often of lower quality, and sensors that measure combustion-related aerosols (like black carbon) are not commonly available. Mobile monitoring using a mid-range instrument can fill this gap. We present the results of a mobile BC (black carbon) monitoring campaign performed by citizens in Mechelen as part of a local citizen observatory (CO), Meet Mee Mechelen, initiated as part of the European H2020 project, Ground Truth 2.0. The goal of the study was two-fold: (1) to propose and evaluate a mobile monitoring method (data collection and data processing) to construct pollution maps of BC concentrations and (2) to demonstrate how to organize community-based air quality monitoring to measure both the spatial and temporal variations in air pollution levels. Measurements were taken during peak hours in four campaigns characterized by different meteorological conditions: October–November 2017, February–March 2018, June–July 2018 and September 2018. The results show large spatial and temporal variabilities. Spatial variability is influenced by traffic volume, stop-and-go traffic and also the building environment and the distance of biking paths from road traffic. The four different campaigns show similar spatial patterns, but due to background and meteorological influences, the absolute concentrations differ between seasons. A rescaling method using data from fixed stations in the air quality monitoring network (AQMN) was presented to construct maps representative of longer periods. This paper shows that mobile measurements can be used by CO to assess the spatial variability of air quality in a city. The data can be used to evaluate mobility plans, carry out hot spot detection, evaluate the exposure of cyclists as a function of cycling infrastructure and perform model validation. However, it is important to use high-quality instruments and apply the correct measurement methodology (number of repetitions, season) to obtain meaningful data. [ABSTRACT FROM AUTHOR]

Urban air pollution has been long understood as a critical threat to human health worldwide. Worsening urban air quality can cause increased rates of asthma, respiratory illnesses, and mortality. Air pollution is also an important environmental justice issue as it disproportionately burdens populations made vulnerable by their socioeconomic and health status. Using spatially continuous fine-scale air quality data for the city of Philadelphia, this study analyzed the relationship between two air pollutants: particulate matter (PM2.5, black carbon (BC), and three dimensions of vulnerability: social (non-White population), economic (poverty), and health outcomes (asthma prevalence). Spatial autoregressive models outperformed Ordinary Least Squares (OLS) regression, indicating the importance of considering spatial autocorrelation in air pollution-related environmental-justice modeling efforts. Positive relationships were observed between PM2.5 concentrations and the socioeconomic variables and asthma prevalence. Percent non-White population was a significant predictor of BC for all models, while percent poverty was shown to not be a significant predictor of BC in the best fitting model. Our findings underscore the presence of distributive environmental injustices, where marginalized communities may bear a disproportionate burden of air pollution within Philadelphia. [ABSTRACT FROM AUTHOR]

The Italian Interministerial Decree of February 11, 2021, introduces the diesel engine exhaust (DDE) among the carcinogenic occupational compounds, also establishing an occupational exposure limit. Elemental carbon (EC), improperly called black carbon, has been proposed as a tracer of DDE exposure; EC is the carbon that is quantified in the ambient matrixes after all the organic carbon has been removed; traditionally, EC is measured with a thermo-optical analytical technique. EC determination and relative interpretation are challenging for the following reasons: (i) the scarce availability of equipped laboratories hampers EC analysis, (ii) EC interpretation is not easy due to the lack of reference values. Finally, (iii) the limit value of 0.050 mg/m³ of EC in the workplace appears too high compared to recently published exposure data. All these aspects stimulate a reflection on the significance of EC data in the context of both occupational hygiene and occupational medicine. [ABSTRACT FROM AUTHOR]

Air pollution, particularly from particulate matter (PM2.5) and black carbon (eBC), has been implicated in airway pathologies. This study aims to assess the relationship between exposure to these pollutants and respiratory function in various populations, including healthy individuals, while seeking an accurate assessment method. A cross-sectional study was conducted in Bogotá, evaluating respiratory function in the users of bicycles, minivans, and buses through spirometry and impulse oscillometry. Measurements were taken along two main avenues, assessing the PM2.5 and eBC concentrations. The results reveal higher pollutant levels on AVE KR 9, correlating with changes in oscillometry values post-travel. Cyclists exhibited differing pre- and post-travel values compared to bus and minivan users, suggesting aerobic exercise mitigates pollutant impacts. However, no statistically significant spirometry or impulse oscillometry variations were observed among routes or modes. Public transport and minivan users showed greater PM2.5 and eBC exposure, yet no significant changes associated with environmental contaminants were found in respiratory function values. These findings underscore the importance of further research on pollutant effects and respiratory health in urban environments, particularly concerning different transport modes. [ABSTRACT FROM AUTHOR]

Coastal estuaries and adjacent continental shelf seas constitute vital global carbon reservoirs, and the sources and transformations of organic carbon in these regions are crucial to global biogeochemical cycles and climate change. This study investigated the total organic carbon (TOC), total nitrogen (TN), black carbon (BC), and their stable carbon and nitrogen isotopes (δ15NTN, δ13CTOC, δ13CBC) in the surface sediments of the Pearl River Estuary (PRE) and its adjacent northern South China Sea (NSCS) aiming to assess the impact of human activities on organic carbon dynamics in these areas. Results showed that the highest TOC concentrations occurred in the inner PRE due to intense human activities, and decreased seaward. The west side of the PRE exhibited higher TOC levels than the east side, which was attributed to differences in hydrodynamic processes and human activities. The westward flow of the Pearl River diluted water, which carried terrestrial organic matter inputs due to the influence of the Coriolis effect and intense local human activities, was a primary contributor to higher TOC levels on the west side (terrestrial source). In contrast, increased productivity and intensive mariculture activities on the east side predominated as sources of organic matter (marine source). Similar to the TOC, BC and TN sources were mainly influenced by human activities. δ15NTN distribution shows that TN in the east side of PRE mainly originated from industrial wastewater input from the Pearl River, while in the east side TN was mainly from domestic sewage discharge. Additionally, BC sources have shifted from primarily biomass combustion in the 1990s to fossil fuel emissions presently. Isotopic analysis revealed that over 70% of BC originated from fossil fuel inputs and C3 plant combustion, highlighting the significant influence of human activities in the PRE and adjacent NSCS, and underscoring the need for effective management and protection of the eco-environment in these regions.

The rapid expansion of the aviation sector raises concerns about air quality impacts within and around airports. Ultrafine particles (UFP, diameter 2-fold) of Fe, Al, Cr, Cu, Mo, Mn, Pb, Ti, and Sb at the airport compared to the UB, with Al exhibiting the most pronounced disparity. Generally, PAH levels were low at both sites, although concentrations were higher at the airport relative to the UB. Overall, this study provides a comprehensive understanding of UFP within a major European airport, identifying the different sources contributing to PNC and PNSD.

Abstract Black carbon (BC) is a highly persistent yet poorly understood component of forest soil carbon reservoirs, while its inventory, distribution, and determining factors in forest soils on a large geographic scale remain unclear. Here, we characterized soil BC across 68 Chinese forest sites using benzene polycarboxylic acid method and developed machine learning (ML) models to predict and interpret potential impacts of soil organic matter (SOM) properties, soil physiochemical properties, meteorological conditions, wildfire history, and microbial diversity on BC. Results revealed that SOM properties were the most critical in predicting BC, complemented by the negative impact of mean annual temperature and alkaline mineral composition. The superior prediction accuracy for BC with higher condensed aromaticity (more benzene hexa‐ and penta‐carboxylic acid monomers) likely results from its simpler sources and greater resistance to transformation. This study introduces an effective ML model for predicting and interpreting soil BC inventory to better understand BC cycling.

Background: Epidemiological evidence on the association between wildfire-specific fine particulate matter (PM2.5) and its carbonaceous components with perinatal outcomes is limited.We aimed to examine the short-term effects of wildfire-specific PM2.5 and its carbonaceous components on perinatal outcomes. Methods: A multicentre cohort of 9743 singleton births during the wildfire seasons from 1 September 2009 to 31 December 2015 across six cities in New South Wales, Australia were linked with daily wildfire-specific PM2.5 and carbonaceous components (organic carbon and black carbon). Adjusted distributed lag Cox regression models with spatial clustering were performed to estimate daily and cumulative adjusted hazard ratios (aHRs) during the last four gestational weeks for preterm birth, stillbirth, nonvertex presentation, low 5-min Apgar score, special care nursery/neonatal intensive care unit (SCN/NICU) admission, and caesarean section. Results: Daily aHRs per 10 µg/m3 PM2.5 showed nearly inverted ‘U’-shaped positive associations and daily cumulative aHRs that increased with increasing duration of the exposures. The aHRs for lag 0–6 days were 1.17 (95 % CI: 1.04, 1.32) for preterm birth, 1.40 (95 % CI: 1.11, 1.78) for stillbirth, 1.20 (95 % CI: 1.08, 1.33) for nonvertex presentation, 1.12 (95 % CI: 0.93, 1.35) for low 5-min Apgar score, 0.99 (95 % CI: 0.83, 1.19) for SNC/NICU admission, and 1.01 (95 % CI: 0.94, 1.08) for caesarean section. Organic carbon and black carbon components for lag 0–6 days showed positive associations. The highest component-specific aHRs were 1.09 (95 % CI: 1.03, 1.15) and 4.57 (95 % CI: 1.96, 10.68) for stillbirth per 1 µg/m3 organic carbon and black carbon, respectively. The subgroups identified as most vulnerable were female births, births to mothers with low socioeconomic status, and births to mothers with high biothermal exposure. Conclusions: Positive associations of short-term wildfire-specific PM2.5 exposure and its carbonaceous components with adverse perinatal outcomes suggest that policies to reduce exposure would benefit public health.

Summary: Background: Nephron number variability may hold significance in the Developmental Origins of Health and Disease hypothesis. We explore the impact of gestational particulate pollution exposure on cord blood cystatin C, a marker for glomerular function, as an indicator for glomerular health at birth. Methods: From February 2010 onwards, the ENVIRONAGE cohort includes over 2200 mothers giving birth at the East-Limburg hospital in Genk, Belgium. Mothers without planned caesarean section who are able to fill out a Dutch questionnaire are eligible. Here, we evaluated cord blood cystatin C levels from 1484 mother–child pairs participating in the ENVIRONAGE cohort. We employed multiple linear regression models and distributed lag models to assess the association between cord blood cystatin C and gestational particulate air pollution exposure. Findings: Average ± SD levels of cord blood cystatin C levels amounted to 2.16 ± 0.35 mg/L. Adjusting for covariates, every 0.5 μg/m³ and 5 μg/m³ increment in gestational exposure to black carbon (BC) and fine particulate matter (PM2.5) corresponded to increases of 0.04 mg/L (95% CI 0.01–0.07) and 0.07 mg/L (95% CI 0.03–0.11) in cord blood cystatin C levels (p

Black carbon is a product of the incomplete combustion of carbonaceous fuels and has significant adverse effects on climate change, air quality, and human health. China has been a major contributor to global anthropogenic black carbon emissions. This study develops a black carbon inventory in China, using 2015 as the base year, and projects annual black carbon emissions in China for the period 2016-2050, under two scenarios: a Reference scenario and an Accelerated Reduction scenario. The study estimates that the total black carbon emissions in China in 2015 were 1100 thousand tons (kt), with residential use being the biggest contributor, accounting for more than half of the total black carbon emissions, followed by coke production, industry, agricultural waste burning, and transportation. This study then projects the total black carbon emissions in China in 2050 to be 278 kt in the Reference scenario and 86 kt in the Accelerated Reduction Scenario. Compared to the Reference scenario, the Accelerated Reduction scenario will achieve much faster and deeper black carbon reductions in all the sectors. The dramatic reductions can be attributed to the fuel switching in the residential sector, faster implementation of high-efficiency emission control measures in the industry, transportation, and coke production sectors, and faster phase-out of agricultural waste open burning. This analysis reveals the high potential of black carbon emission reductions across multiple sectors in China through the next thirty years.

Air pollution around industrial area has become a serious concern for both the public and local government. Thus, research on PM2.5 characterization is urgently needed. This study identifies the concentration and chemical characteristics of PM2.5 to provide an in-depth understanding of the composition of these particles around the largest industrial complex in North Jakarta. Sixty samples of PM2.5 were collected from residential sites around industrial areas in North Jakarta. Samples were collected on Teflon filters using a SuperSASS instrument during the period from February to July 2023, representing the wet and dry seasons. Mass concentrations of PM2.5, black carbon, and 19 chemical elements were determined. The average mass concentration of PM2.5 in the wet and dry seasons was 27.81±11.82 µg/m3 and 46.63±14.37 µg/m3, respectively. Although the concentration of PM2.5 was lower during the wet season, the concentrations of black carbon and certain elements did not decrease significantly. This shows that pollutants play an important role in both seasons in the study location. Sulfur is the most abundant element with the average concentration in the dry season (2,727.89 ng/m3) higher than in the wet season (1,983.18 ng/m3). The PM2.5 mass reconstruction results show that ammonium sulfate and black carbon have the largest portion of PM2.5 mass. The results are expected to be used as a scientific reference in studying air pollution problems in this region and assist in formulating air protection policies to reduce PM2.5 emissions.

Objective Black carbon is a carbonaceous mixture formed by the incomplete combustion of biomass and fossil fuels. Since black carbon has a high carbon content and an aromatized molecular structure, it can persist in the natural environment, suggesting that black carbon is an important component of the global carbon cycle. Although pioneering studies have advanced the understanding of nature, circulation fluxes, and reserves of black carbon in the geosphere, it is still necessary to further clarify the source-sink processes of black carbon and explore the importance of black carbon in the global carbon cycle. Methods Here, this study reviews the available data on pathways, fluxes, and time scales of the global black carbon cycle and analyses and summarizes the migration mechanisms and constraints in the source-sink process of marine black carbon. Results This paper concludes that marine sediments serve as a large reservoir for black carbon, with a reserve of 569-1 380 Pg. Black carbon can persist over millennia in marine sediments, which is associated with a long turnover time as an "effective carbon sink" in the context of "carbon neutrality". Moreover, black carbon exerts a negative feedback effect on global warming due to its longer turnover cycle time than biomass carbon. The deposition of black carbon into the sea is an effective means to enhance carbon sequestration in the ocean and could be an effective way to implement the carbon capture, utilization, and storage (CCUS) strategy. Conclusion In this paper, we propose that human-induced production of black carbon from biogenic combustion may be actively regulated and that the deposition pathways and burial areas of black carbon into the sea should also be optimized given the premise of ecological and environmental friendliness based on a summary and assessment of the strategic value and climate significance of black carbon in marine sediments in the context of "carbon neutrality". Therefore, the positive role of black carbon in "negative ocean carbon emissions" can provide a basic theoretical framework for achieving the goals of "carbon neutrality".

The effects of heavy fuel oil and biodiesel blends on engine combustion and emissions were studied in a marine two-stroke diesel engine. The engine was operated under propeller conditions using five different fuels with biodiesel blends of 10% (B10), 30% (B30), 50% (B50), and sulphur contents of 0.467% low sulphur fuel oil (LSFO) and 2.9% high sulphur fuel oil (HSFO). Tests have shown that using a biodiesel blend increases the engine fuel consumption due to its lower calorific value. Heavy fuel oil has a high Polycyclic aromatic hydrocarbons (PAH) content, which leads to higher exhaust temperatures due to severe afterburning in the engine. A comparison of engine soot emissions under different fuel conditions was carried out, and it was found that the oxygen content in biodiesel promoted the oxidation of soot particles during the combustion process, which reduced the soot emissions of biodiesel. Compared to HSFO, B10, B30, B50 and LSFO, the soot emission concentrations were reduced by 50.2%, 56.4%, 61% and 37.4%, respectively. In our experiments, the soot particles in the engine exhaust were sampled with a thermal float probe. Using Raman spectroscopy analysis, it was found that as the biodiesel ratio increased, the degree of carbonisation of the soot particles in the exhaust became less than that in the oxygenation process, resulting in a decrease in the degree of graphitisation.

Black carbon (BC) is a critical environmental pollutant with significant implications for human health. This study aims to quantify personal exposure to BC by focusing on the influence of microenvironments and time-activity patterns in the Rio Grande Valley (RGV) region of South Texas, USA. Over eight days in March and April 2023, a portable aethalometer and GPS tracking instruments were used to measure BC exposure among a study participant, alongside recording the time spent in various microenvironments. The BC measurements were correlated to the time activity patterns to calculate BC inhaled dosage values thereby elucidating its impact on human health. The mean values for different hours ranged from the lowest,0.26 µg/m³ ± 0.29 at 02:00, to the highest, 1.07 µg/m³ ± 1.40 at 17:00. The study also identified peak BC levels in areas near major roadways and airports. Outdoor activities accounted for 31% - 33% of the BC inhaled dosage on weekends, which was much higher than the 0.10% - 1.42% contribution observed on weekdays. The results also reflect a negative impact of Mexican wildfire activities on black carbon in this border region. This research provides insights into one of the first black carbon measurement studies conducted in the South Texas, U.S.– Tamaulipas State, Mexico border region.

Understanding the impact of various climate forcing agents, such as aerosols, on extreme precipitation is socially and scientifically vital. While anthropogenic absorbing aerosols influence Earth's energy balance and atmospheric convection, their role in extreme events remains unclear. This paper uses convective‐resolving radiative‐convective‐equilibrium simulations, with fixed solar radiation, to investigate the influence of absorbing aerosols on extreme precipitation comprehensively. Our findings reveal an underappreciated mechanism through which absorbing aerosols can, under certain conditions, strongly intensify extreme precipitation. Notably, we demonstrate that a mechanism previously reported for much warmer (hothouse) climates, where intense rainfall alternates with multi‐day dry spells, can operate under current realistic conditions due to absorbing aerosol influence. This mechanism operates when an aerosol perturbation shifts the lower tropospheric radiative heating rate to positive values, generating a strong inhibition layer. Our work highlights an additional potential effect of absorbing aerosols, with implications for climate change mitigation and disaster risk management. Plain Language Summary: Aerosols, particles suspended in the atmosphere, can interact with the incoming solar radiation by scattering or absorbing it. Aerosol species that absorb solar radiation generate local warming of the atmosphere. This local warming changes the vertical profile of temperature and by that affects cloud and precipitation development. In this paper we use idealized computer simulations to investigate the effect of absorbing aerosols on precipitation, and specifically on extreme precipitation events in the tropics. We demonstrate that under certain conditions, absorbing aerosols can strongly enhance extreme precipitation even despite reducing the mean. We show that this trend can be explained by a mechanism previously reported for much warmer climate conditions than currently found on Earth, involving heating by radiation of the lower part of the troposphere. These results have implications for climate change mitigation and disaster risk management. Key Points: The effect of absorbing aerosol on extreme precipitation is examined in idealized convective‐resolving radiative‐convective‐equilibrium simulationsAerosol perturbation that shifts the lower tropospheric radiative heating rate to positive values strongly enhances extreme precipitationThis trend is explained by a mechanism reported before for hothouse climate conditions involving a shift into an "episodic deluge" regime [ABSTRACT FROM AUTHOR]

Black carbon (BC) has emerged as an integral part of the global carbon (C) cycle, constituting 12% ± 5% of the organic C pool in rivers and soils, with the potential to generate negative climate feedback. However, its ability to sequester C depends on the recalcitrant nature of BC in the environment, which is under debate. Using CTO‐375 method and by measuring concentrations and isotopic compositions of particulate BC (δ13CPBC), we explore the transformation of particulate black carbon (PBC) along the atmosphere‐river‐ocean continuum. Significantly high δ13CPBC in the ocean compared to rivers and atmospheric particulate matter indicates (a) degradation of PBC, potentially through photodegradation and leaching, and/or (b) availability of an enriched source other than fluvial or aeolian inputs. This evidence for degradation of PBC in aquatic systems warrants rethinking on its C sequestration potential and role in aquatic C biogeochemistry and further raises concerns regarding the use of sedimentary BC as a paleoenvironmental proxy. Plain Language Summary: Particulate black carbon (PBC) forms ∼12% ± 5% of the particulate organic carbon pool in aquatic systems. Black carbon has been considered highly recalcitrant and therefore a potent sink for carbon. Paleo‐environmental and biogeochemical studies have been conducted assuming BC as highly stable and its isotopic composition to remain unaltered after formation. This study explores the variability in stable isotopic composition of PBC in the riverine, atmospheric, and oceanic systems and provides evidence contrary to the general belief of the refractory nature of BC, which warrants revisiting and rethinking of the BC dynamics in aquatic systems. Key Points: Particulate black carbon (PBC) concentration decreases along the river ocean continuumStable carbon isotopic composition of the oceanic PBC pool is higher compared to the riverine and atmospheric poolsIsotopic evidence suggests degradation of PBC with the preferential loss of lighter carbon [ABSTRACT FROM AUTHOR]

This study investigated the aerosol particle properties and light absorption properties of brown carbon (BrC) by utilizing a seven-wavelength aethalometer, and analyzed NH4+, NO3−, SO42−, K+, K, organic carbon, elemental carbon, levoglucosan, and mannosan in PM2.5. The research was conducted in a rural area of Jeonnam, South Korea, during the winter season. In addition, the dithiothreitol assay-oxidative potential normalized to 9,10-phenanthrenequinone (QDTT-OP) was investigated throughout the study period. The absorption coefficient was found to be 2.6 to 5.6 times higher at 370 nm compared to 880 nm, suggesting the presence of light-absorbing substances in addition to black carbon (BC) particles. The estimated absorption coefficient of BrC370 was 29.9% of the total light absorption coefficient at 370 nm. Furthermore, BrC370 exhibited a strong affinity with levoglucosan while showing a weak correlation with K+, confirming the suitability of levoglucosan as a tracer for biomass burning. The QDTT-OP was 5.3 nM m−3, and highly correlated with the carbonaceous components levoglucosan and mannosan, suggesting a relatively high contribution of biomass combustion emissions to oxidative potential. Further research should be conducted to assess the health risks associated with future PM2.5 exposure related to biomass burning in the atmosphere. [ABSTRACT FROM AUTHOR]

Air pollution around industrial area has become a serious concern for both the public and local government. Thus, research on PM2.5 characterization is urgently needed. This study identifies the concentration and chemical characteristics of PM2.5 to provide an in-depth understanding of the composition of these particles around the largest industrial complex in North Jakarta. Sixty samples of PM2.5 were collected from residential sites around industrial areas in North Jakarta. Samples were collected on Teflon filters using a SuperSASS instrument during the period from February to July 2023, representing the wet and dry seasons. Mass concentrations of PM2.5, black carbon, and 19 chemical elements were determined. The average mass concentration of PM2.5 in the wet and dry seasons was 27.81±11.82 µg/m³ and 46.63±14.37 µg/m³, respectively. Although the concentration of PM2.5 was lower during the wet season, the concentrations of black carbon and certain elements did not decrease significantly. This shows that pollutants play an important role in both seasons in the study location. Sulfur is the most abundant element with the average concentration in the dry season (2,727.89 ng/m³ ) higher than in the wet season (1,983.18 ng/m³ ). The PM2.5 mass reconstruction results show that ammonium sulfate and black carbon have the largest portion of PM2.5 mass. The results are expected to be used as a scientific reference in studying air pollution problems in this region and assist in formulating air protection policies to reduce PM2.5 emissions. [ABSTRACT FROM AUTHOR]

Wildfires frequently occur in Ukraine during agricultural open-burning seasons in spring and autumn. High aerosol concentrations from fire emissions can significantly affect meteorological processes via direct and indirect aerosol effects. To study these impacts, we selected a severe wildfire episode from April 2020 in the Chornobyl Exclusion Zone (CEZ) and its surrounding area as a case study. We employed the Enviro-HIRLAM modeling system to simulate reference (REF) meteorological conditions, along with direct (DAE), indirect (IDAE), and combined (COMB) aerosol effects. In our simulations, black carbon (BC) and organic carbon (OC) comprised 70–80% of all aerosol mass in the region, represented in two layers of higher concentrations: one near the surface and the other 3–4 km above the surface. Our simulations showed that the inclusion of aerosol effects into the modeling framework led to colder (up to −3 °C) and drier (relative humidity drop up to −20%) conditions near the surface. We also observed localized changes in cloudiness, precipitation (mainly redistribution), and wind speed (up to ±4 m/s), particularly during the movement of atmospheric cold fronts. Larger uncertainties were observed in coarser model simulations when direct aerosol effects were considered. Quantifying the aerosol effects is crucial for predicting and promptly detecting changes that could exacerbate unfavorable weather conditions and wildfires. Such knowledge is essential for improving the effectiveness of emergency response measures. [ABSTRACT FROM AUTHOR]

Methodologies across the dispersion preparation, characterization, and cellular dosimetry of hydrophilic nanoparticles (NPs) have been developed and used extensively in the field of nanotoxicology. However, hydrophobic NPs pose a challenge for dispersion in aqueous culture media using conventional methods that include sonication followed by mixing in the culture medium of interest and cellular dosimetry. In this study, a robust methodology for the preparation of stable dispersions of hydrophobic NPs for cellular studies is developed by introducing continuous energy over time via stirring in the culture medium followed by dispersion characterization and cellular dosimetry. The stirring energy and the presence of proteins in the culture medium result in the formation of a protein corona around the NPs, stabilizing their dispersion, which can be used for in vitro cellular studies. The identification of the optimal stirring time is crucial for achieving dispersion and stability. This is assessed through a comprehensive stability testing protocol employing dynamic light scattering to evaluate the particle size distribution stability and polydispersity. Additionally, the effective density of the NPs is obtained for the stable NP dispersions using the volumetric centrifugation method, while cellular dosimetry calculations are done using available cellular computational modeling, mirroring approaches used for hydrophilic NPs. The robustness of the proposed dispersion approach is showcased using a highly hydrophobic NP model (black carbon NPs) and two culture media, RPMI medium and SABM, that are widely used in cellular studies. The proposed approach for the dispersion of hydrophobic NPs results in stable dispersions in both culture media used here. The NP effective density of 1.03–1.07 g/cm3 measured here for black carbon NPs is close to the culture media density, resulting in slow deposition on the cells over time. So, the present methodology for dispersion and dosimetry of hydrophobic NPs is essential for the design of dose–response studies and overcoming the challenges imposed by slow particle deposition. [ABSTRACT FROM AUTHOR]

Tremendous efforts have been made to construct large-scale estimates of aerosol components. However, Black Carbon (BC) estimates over large spatiotemporal scales are still limited. We proposed a novel approach utilizing machine-learning techniques to estimate BC on a large scale. We leveraged a comprehensive gridded BC emission database and auxiliary variables as inputs to train various machine learning (ML) models, specifically a Random Forest (RF) algorithm, to estimate high spatiotemporal BC concentration over China. Different ML algorithms have been applied to a large number of potential datasets and detailed variable importance and sensitivity analysis have also been carried out to explore the physical relevance of variables on the BC estimation model. RF algorithm showed the best performance compared with other ML models. Good predictive performance was observed for the training cases (R2 = 0.78, RMSE = 1.37 μgm−3) and test case databases (R2 = 0.77, RMSE = 1.35 μgm−3) on a daily time scale, illustrating a significant improvement compared to previous studies with remote sensing and chemical transport models. The seasonal variation of BC distributions was also evaluated, with the best performance observed in spring and summer (R2 ≈ 0.7–0.76, RMSE ≈ 0.98–1.26 μgm−3), followed by autumn and winter (R2 ≈ 0.7–0.72, RMSE ≈ 1.37–1.63 μgm−3). Variable importance and sensitivity analysis illustrated that the BC emission inventories and meteorology showed the highest importance in estimating BC concentration (R2 = 0.73, RMSE = 1.88 μgm−3). At the same time, albedo data and some land cover type variables were also helpful in improving the model performance. We demonstrated that the emission-based ML model with an appropriate auxiliary database (e.g., satellite and reanalysis datasets) could effectively estimate the spatiotemporal BC concentrations at a large scale. In addition, the promising results obtained through this approach highlight its potential to be utilized for the assessment of other primary pollutants in the future. [ABSTRACT FROM AUTHOR]

Short-term exposure to ultra-fine Black Carbon (BC) particles produced during incomplete fuel combustion of wood and fossil fuel has been linked to respiratory and cardiovascular diseases, hospitalizations and premature deaths. The goal of this research was to assess traffic-related BC in a cold climate along an urban highway and 300 m into an adjacent residential neighborhood. BC was measured with an aethalometer (MA350, Aethlabs) along the main traffic artery in geothermally heated Reykjavík, the capital of Iceland (64.135° N–21.895° W, 230,000 inhabitants). Stationary monitoring confirmed that traffic was the dominant source of roadside BC in winter, averaging 1.0 ± 1.1 µg/m3 (0.6 and 1.1 µg/m3 median and interquartile range; 28,000 vehicles/day). Inter-day variations in BC were primarily correlated to the atmospheric lapse rate and wind speed, both during stationary and mobile campaigns. During winter stills, BC levels surpassed 10 µg/m3 at intersections and built up to 5 µg/m3 during the afternoon in the residential neighborhood (adjacent to the highway with 43,000 vehicles/day). The BC penetrated deeply into the neighborhood, where the lowest concentration was 1.8 µg/m3 within 300 m. BC concentration was highly correlated to nitrogen dioxide (r > 0.8) monitored at the local Urban Traffic Monitoring site. [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosols are important for absorbing aerosols, affecting global climate change and regional air quality, and potentially harming human health. From March to May 2023, we investigated black carbon aerosol levels and air pollution in Beijing. Employing methods such as linear regression, Potential Source Contribution Function (PSCF) and Concentration-Weighted Trajectory (CWT), we analyzed the characteristics and sources of black carbon aerosols in the region. Results indicate that the light absorption coefficients of BC and BrC decrease with increasing wavelength, with BrC accounting for less than 40% at 370 nm. Daily variations in BC and PM2.5 concentrations exhibit similar trends, peaking in March, and BC displays a distinct bimodal hourly concentration structure during this period. Aethalometer model results suggest that liquid fuel combustion contributes significantly to black carbon (1.08 ± 0.71 μg·m−3), surpassing the contribution from solid fuel combustion (0.31 ± 0.2 μg·m−3). Furthermore, the significant positive correlation between BC and CO suggests that BC emissions in Beijing predominantly result from liquid fuel combustion. Potential source area analysis indicates that air masses of spring in Beijing mainly originate from the northwest (40.93%), while potential source areas for BC are predominantly distributed in the Beijing–Tianjin–Hebei region, as well as parts of the Shandong, Shanxi and Henan provinces. Moreover, this study reveals that dust processes during spring in Beijing have a limited impact on black carbon concentrations. This study's findings support controlling pollution in Beijing and improving regional air quality. [ABSTRACT FROM AUTHOR]

Globalization and industrialization have increased the shipping activities in Metro Manila. This increase in economic activity has contributed to the exacerbation of atmospheric particle pollution, particularly black carbon (BC) and particulate matter (PM). In this study, PM0.49 and BC were characterized in North Harbour in Metro Manila, Philippines. Using a multiple-split high-volume cascade impactor, PM0.49 and PM2.5 were collected from December 2019 to January 2020. Equivalent BC (eBC) mass concentrations were measured using an aethalometer (AE33, Magee Scientific) while chemical analysis was also performed using ion chromatography. The PM0.49 was tested for its morphological and mineralogical characteristics. Daily analysis showed no significant difference between the weekday and weekend pollution concentration in the port, although mean concentration (70 ± 21 μg/m3) exceeds that of the 24-hr Philippine air quality guideline value of 50 μg/m3 for PM2.5 concentrations. The particle compositions of PM0.49 are mostly from Si-rich particles and Pb-rich particles. High variability was observed for Mg, Si, Ca, Fe, Cd, Zn, Mn, S, Cl, V, and Cr heavy metals. The carbonaceous species with the highest concentration was organic carbon (OC) (33 ± 9 μg/m3) followed by BC (16 ± 3 μg/m3) and eBC (12 ± 3 μg/m3). An analysis of the ionic species showed SOX and NOX emissions as the primary ions, which are mostly related to ship emissions while the mineralogical analysis showed that soot particles are the main composition of the particles. Overall, the pollution assessment showed that North Harbour is polluted with heavy metals but within the Philippine air quality pollutant standard. In brief, the results of this study suggest that atmospheric pollution in the study site was mostly caused by local anthropogenic sources, particularly vessel emissions. The researchers suggest that a longer study period be conducted to further assess the seasonal variation of atmospheric particle pollution in North Harbour, Metro Manila.