Black Carbon Research Articles

Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley – an integrated approach combining high-resolution dispersion modelling and micro-aethalometers

Abstract. Understanding black carbon (BC) levels and its sources in urban environments is of paramount importance due to the far-reaching health, climate, and air quality implications. While several recent studies have assessed BC concentrations at specific fixed urban locations, there is a notable lack of knowledge in the existing literature on spatially resolved data alongside source estimation methods. This study aims to fill this gap by conducting a comprehensive investigation of BC levels and sources in Modena (Po Valley, Italy), which serves as a representative example of a medium-sized urban area in Europe. Using a combination of multi-wavelength micro-aethalometer measurements and a hybrid Eulerian–Lagrangian modelling system, we studied two consecutive winter seasons (February–March 2020 and December 2020–January 2021). Leveraging the multi-wavelength absorption analyser (MWAA) model, we differentiate sources (fossil fuel combustion, FF, and biomass burning, BB) and components (BC vs. brown carbon, BrC) from micro-aethalometer measurements. The analysis reveals consistent, minimal diurnal variability in BrC absorption, in contrast to FF-related sources that exhibit distinctive diurnal peaks during rush hours, while BB sources show less diurnal variation. The city itself contributes significantly to BC concentrations (52 ± 16 %), with BB and FF playing a prominent role (35 ± 15 % and 9 ± 4 %, respectively). Long-distance transport also influences BC concentrations, especially in the case of BB and FF emissions, with 28 ± 1 % and 15 ± 2 %, respectively. When analysing the traffic-related concentrations, Euro 4 diesel passenger cars considerably contribute to the exhaust emissions. These results provide valuable insights for policy makers and urban planners to manage BC levels in medium-sized urban areas, taking into account local and long-distance sources.

Sectoral Size‐Resolved Particle Number Emissions With Speciation: Emission Profile‐Based Quantification and a Case Study in the Yangtze River Delta Region, China

AbstractSizes and number concentrations are critical parameters for the impact of atmospheric particles on climate and human health. However, comprehensive studies focusing on size‐resolved particle number (PN) emissions from various sectors are scarce. This study aims to fill this research gap by developing sectoral size‐resolved PN emissions for major species including sulfate, organic mass (OM), and black carbon (BC). The size‐resolved emission profiles derived from various measurements in the literature were integrated with a particle mass emission inventory (EI) for 13 major sectors in the Yangtze River Delta region of China as a case study. The particle number size distribution (PNSD) of emitted particles exhibited two distinct peaks: one at approximately 10 nm and the other in the range of 40–60 nm. The primary contributors to PN emissions in the region in 2017 were power plants, gasoline vehicles, diesel vehicles, and cooking sources. In terms of species, OM dominated PN emissions, followed by primary sulfate and then BC. A regional size‐resolved aerosol model employing the size‐resolved PN EI developed here (referred to as the BIN‐SPE experiment) provided reasonably accurate temporal variations of the total PN concentration and captured the PNSD within the size range of 10–300 nm. Uncertainty analysis of sectoral PN emissions across size ranges was carried out and the performance of the BIN‐SPE experiment was compared with those of three commonly used PN emission parameterizations. Our model evaluations highlight future needs for in‐depth investigations into more advanced size‐resolved emissions and secondary OM formation mechanisms.

Variation in Glacier Albedo on the Tibetan Plateau between 2001 and 2022 Based on MODIS Data

Albedo is a primary driver of the glacier surface energy balance and consequent melting. As glacier albedo decreases, it further accelerates glacier melting. Over the past 20 years, glaciers on the Tibetan Plateau have experienced significant melting. However, our understanding of the variations in glacier albedo and its driving factors in this region remains limited. This study used MOD10A1 data to examine the average characteristics and variations in glacier albedo on the Tibetan Plateau from 2001 to 2022; the MOD10A1 snow cover product, developed at the National Snow and Ice Data Center, was employed to analyze spatiotemporal variations in surface albedo. The results indicate that the albedo values of glaciers on the Tibetan Plateau predominantly range between 0.50 and 0.60, with distinctly higher albedo in spring and winter, and lower albedo in summer and autumn. Glacier albedo on the Tibetan Plateau decreased at an average linear regression rate of 0.06 × 10−2 yr−1 over the past two decades, with the fastest declines occurring in autumn at an average rate of 0.18 × 10−2 yr−1, contributing to the prolongation of the melting period. Furthermore, significant variations in albedo change rates with altitude were found near the snowline, which is attributed to the transformation of the snow and ice surface. The primary factors affecting glacier albedo on the Tibetan Plateau are temperature and snowfall, whereas in the Himalayas, black carbon and dust primarily influence glacier albedo. Our findings reveal a clear decrease in glacier albedo on the Tibetan Plateau and demonstrate that seasonal and spatial variations in albedo and temperature are the most important driving factors. These insights provide valuable information for further investigation into surface albedo and glacier melt.

Bio-inspired spreadable multi-signal self-sensing covering composite material for intelligent devices

The spreadable materials with multi-sensing capabilities offer a wide range of application possibilities. They can be applied directly to the surface of intelligent devices, facilitating the creation of self-sensing shells. Despite significant progress in the development of such materials, expanding their diverse sensing capabilities remains a critical focus in this field. Here, we present a spreadable material endowed with multiple signal self-sensing capabilities. The material, which can be easily applied to the surface of devices, offers real-time monitoring of temperature, humidity, and device damage. This material comprised carbon black nanoparticles, carbon nanotubes, and sodium carboxymethyl cellulose, exhibiting excellent electrical conductivity. It exhibited a temperature coefficient of resistivity (TCR) of approximately 0.35%per°C, a humidity sensing sensitivity ranging from 3.57 to 4.31 Ω/RH%, and a strain sensing sensitivity gauge factor value of approximately 2.3. We anticipate that the proposed strategy utilizing spreadable multi-signal sensing materials will be extensively applied to the surfaces of various intelligent equipment, thereby furnishing a diverse range of signal data crucial for both safeguarding intelligent systems and enhancing environmental monitoring capabilities.

New Analytical Paradigm to Determine Concentration of Brown Carbon and Its Sample-by-Sample Mass Absorption Efficiency.

Brown carbon (BrC) has a substantial direct radiative effect, but current estimates of its impact on radiative balance are highly uncertain due to a lack of measurements of its light-absorbing properties, such as mass absorption efficiency (MAE). Here, we present a new analytical paradigm based on a Bayesian inference (BI) model that takes multiwavelength aethalometer measurements and total carbon data to resolve the concentrations of black carbon and BrC, and MAEs of BrC on a sample-by-sample basis. Hourly MAEs, unattainable in previous studies, can now be calculated, enabling the first-time observation of the darkening-bleaching dynamics of BrC in response to photochemical transformation. We demonstrate the application of this BI model to analyze measurements collected over one year (2021-2022) in Hong Kong. Diel variations in MAE370nm of BrC reveal a darkening-to-bleaching transition occurring between 8 and 10 O'clock when the solar irradiance ranges from 30 to 400 W m-2. Furthermore, we consistently observe an increase in MAE370nm of BrC with nitrogen oxide concentrations, suggesting the enhanced formation of nitrogenous organics. This BI model-based data analysis would bring forth a breakthrough in amassing observation data of BrC and its MAEs in diverse ambient environments and with high time resolution.

Anthropic-Induced Variability of Greenhouse Gasses and Aerosols at the WMO/GAW Coastal Site of Lamezia Terme (Calabria, Southern Italy): Towards a New Method to Assess the Weekly Distribution of Gathered Data

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.

Ambient fine particulate matter and its constituents may exacerbate the acceleration of aging in adults

Both ambient fine particulate matter (PM2.5) and aging are important urban concerns. However, the associations between PM2.5 constituents and the acceleration of aging (AA) remain unclear. We included 16,051 adults (aged 25–80 years) with 19,252 medical observations in Taiwan during 2008−2017. 2-year average PM2.5 and its five major constituents were assessed using a two-stage machine learning model at a resolution of 1 km2. AA was determined by the difference between the Klemera–Doubal biological age and chronological age. A linear mixed model (LMM) with inverse probability weights was used to examine the associations between AA and air pollution. In a semi-randomized study design, we applied a post-matching LMM to assess the impacts of changes in air pollution exposure on AA. Each interquartile range increase in ambient PM2.5, SO4-2, NO3–, NH4+, organic matters (OM), and black carbon (BC) was associated with a 0.20 (95 %confidence interval [CI]: 0.17–0.24), 0.19 (0.15–0.23), 0.14 (0.11–0.18), 0.21 (0.17–0.24), 0.22 (0.19–0.26) and 0.25 (0.21–0.28) year increase in AA, respectively. BC was generally associated with the greatest increase in AA as compared to other constituents. We did not find evident thresholds in their concentration–response associations. Participants exposed to increased levels of PM2.5, SO4-2, NO3–, NH4+, OM, and BC experienced an increase in AA of 0.11 (−0.07–0.29), 0.20 (0.02–0.39), 0.15 (−0.02–0.33), 0.12 (−0.07–0.31), 0.24 (0.07–0.41), and 0.30 (0.07–0.52) years, respectively, compared to those exposed to decreased/unchanged levels. Long-term exposure to ambient PM2.5 and its constituents may accelerate biological aging among Chinese adults. Exposed to increased levels may further aggregate the aging process. This study suggests that reducing exposure to air pollution is beneficial, even for residents within moderately-to-highly polluted regions, such as Taiwan. Rigorous regulation of PM2.5 and its constituents may prevent the acceleration of biological age.

Characterization of indoor airborne particulate matter and bioaerosols in wood-fired pizzeria kitchens

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.

Spatial variation, sources, and trajectory of black carbon in the South Sumatra Region of Indonesia using MERRA-2 reanalysis data

Spatial variation, sources, and trajectory of black carbon in the South Sumatra Region of Indonesia using MERRA-2 reanalysis data

The behaviour of charged particles (ions) during new particle formation events in urban Leipzig, Germany

Abstract. Air ions are electrically charged particles in air. They are ubiquitous in the natural environment and affect the Earth's radiation budget by accelerating the formation and growth of new aerosol particles. Despite this, few datasets exist exploring these effects in the urban environment. A neutral cluster and air ion spectrometer was deployed in Leipzig, Germany, to measure the number size distribution of charged particles from 0.8 to 42 nm, between 27 July and 25 August 2022. Following previous analyses, charged particles were classified into small (0.8–1.6 nm), intermediate (1.6–7.5 nm), and large (7.5–22 nm) fractions by mass diameter, and their mean concentrations (sum of positive and negative polarities) during the campaign were 405, 71.6, and 415 cm−3, respectively. The largest peaks in intermediate and large ions were explained by new particle formation (NPF), with intermediate ions correlating well with sulfuric acid dimer. Smaller morning and evening peaks were coincident with black carbon concentrations and attributed to primary emissions. NPF events, observed on 30 % of days, coincided with intense solar radiation and elevated sulfuric acid dimer. Small charged particles were primarily associated with radioactive decay and highest during the early hours, and they are unrelated to primary emissions or NPF. The apparent contributions of charged particles to 3 and 7.5 nm particle formation rates were 5.7 % and 12.7 %, respectively, with mean growth rates of 4.0 nm h−1 between 3–7.5 nm and 5.2 nm h−1 between 7.5 and 22 nm. The ratio of charged to total particle formation rates at 3 nm suggests a minor role for charged particles in NPF. We conclude that NPF is a primary source of > 3 nm ions in our data, with primary emissions being the major source in the absence of NPF.

Long-term biochar and soil organic carbon stability – Evidence from field experiments in Germany

Organic soil amendments (OSA) with long residence times, such as biochar, have a high potential for soil organic carbon (SOC) sequestration. The highly aromatic structure of biochar reduces microbial decomposition and explains the slow turnover of biochar, indicating long persistence in soils and thus potential SOC sequestration. However, there is a lack of data on biochar-induced SOC sequestration in the long-term and under field conditions. We sampled two long-term field experiments in Germany, where biochar was applied 12 and 14 years ago. Both locations differ in soil characteristics and in the types and amounts of biochar and other OSA. Amendments containing compost and 31.5 Mg ha−1 of biochar on a loamy soil led to a SOC stock increase of 38 Mg ha−1 after OSA addition. The additional increase is due to non-biochar co-amendments such as compost or biogas digestate. After eleven years, this SOC stock increase was still stable. High biochar amount additions of 40 Mg ha−1 combined with biogas digestate, compost or synthetic fertilizer on a sandy soil led to an increase of SOC stocks of 61 Mg ha−1; 38 Mg ha−1 dissipated in the following four years most likely due to lacking physical protection of the coarse soil material, and after nine years the biochar-amended soils showed only slightly higher SOC stocks (+7 Mg ha−1) than the control. Black carbon stocks on the same soil increased in the short- and mid-term and decreased almost to the original stock levels after nine years. Our results indicate that in most cases the long-term effect on SOC and black carbon stocks is controlled by biochar quality and amount, while non-biochar co-amendments can be neglected. This study proves that SOC sequestration through the use of biochar is possible, especially in loamy soils, while non-biochar OSA cannot sequester SOC in the long term.

A New Method Proposed for the Estimation of Exposure to Atmospheric Pollution through the Analysis of Black Pigments on the Lung Surface

Megacities can be considered excellent laboratories for studying the effects of the urban environment on human health. Typically, exposure to pollution is estimated according to daily or annual averages of pollutant concentrations, collected at monitoring stations, using satellite data for remote sensing of pollutant levels, considering proximity to major roads, or through personal exposure monitoring with portable sensors. However, these approaches fall short in identifying individual exposure values over a lifetime. It is well established that individuals living in large urban areas inhale atmospheric particles containing carbonaceous components, resulting in the deposition of black pigments in lung tissue, known as black carbon or anthracosis. This study aims to detail the procedures for assessing the deposition of such pigments, which serve as an estimate of an individual’s exposure to atmospheric pollution particles. Data collection involves administering detailed questionnaires and capturing lung images in the autopsy room. The analysis is based on macroscopic quantification of black pigments, supplemented by an evaluation of personal habits and the clinical histories of the individuals. This method of estimating lifetime exposure to inhaled particles provides a valuable tool for understanding the correlation between urban living and its potential health effects.

Large‐Scale Climate Features Control Fire Emissions and Transport in Africa

AbstractRecent increase in extreme wildfire events has led to major health and environmental consequences across the globe. These adverse impacts underlined the need for better understanding of this phenomenon and to formulate mitigating actions. While previous research has focused on local weather drivers of wildfires, our knowledge about their large‐scale climatic controls remains limited, especially in tropical Africa, which stands out as a global hotspot for fire emissions. Here, we show that interannual variability of carbon emission due to fires in the southern Congo Basin is strongly linked to low‐level winds that are controlled by the Indian Ocean subtropical high. The interhemispheric transport of these emissions to West Africa relies on the intensity and position of both Indian and South Atlantic subtropical highs. Combined effects of this transport mechanism and carbon production in the source region explain a majority of the interannual variability of black carbon in West Africa.

Urban road BC emissions of LDGVs: Machine learning models using OBD/PEMS data

Urban Black Carbon (BC) emissions from light-duty gasoline vehicles (LDGVs) are challenging to quantify in real-world settings. This study employed a Portable Emission Measurement System (PEMS) to assess BC emissions from five LDGVs on urban roads. We also developed five machine learning (ML) models based on On-Board Diagnostics (OBD) data to predict BC emissions. Among these, the Random Forest (RF) model consistently demonstrates the best ability to predict BC emissions across all tested LDGVs, with R2 values exceeding 0.6. Integrating OBD-based ML models within vehicles could enable real-time BC monitoring and aid emission reduction strategies. We observed a strong correlation between BC emissions and engine parameters, such as engine speed and load (R2 values between 0.5 and 0.9). Furthermore, China VI standard-compliant LDGVs showed minor differences in BC emissions across urban road types. Vehicles equipped with gasoline direct injection (GDI) engines registered BC emission factors (EFs) of 0.141 ± 0.038 mg/km, an increase of 23.7% compared to their port fuel injection (PFI) counterparts, which averaged 0.114 ± 0.049 mg/km.

Air pollution and risk of 32 health conditions: outcome-wide analyses in a population-based prospective cohort in Southwest China

BackgroundUncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions.MethodsA total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD.ResultsPer interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62–1.89), hypertensive diseases (1.49, 1.38–1.62), cardiac arrests (1.52, 1.30–1.77), arrhythmia (1.76, 1.44–2.15), cerebrovascular diseases (1.86, 1.65–2.10), stroke (1.77, 1.54–2.03), ischemic stroke (1.85, 1.61–2.12), atherosclerosis (1.77, 1.57–1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15–1.51), pneumonia (1.37, 1.16–1.61), inflammatory bowel diseases (1.34, 1.16–1.55), liver diseases (1.59, 1.43–1.77), type 2 diabetes (1.48, 1.26–1.73), lipoprotein metabolism disorders (2.20, 1.96–2.47), purine metabolism disorders (1.61, 1.38–1.88), anemia (1.29, 1.15–1.45), sleep disorders (1.54, 1.33–1.78), renal failure (1.44, 1.21–1.72), kidney stone (1.27, 1.13–1.43), osteoarthritis (2.18, 2.00–2.39), osteoporosis (1.36, 1.14–1.61). OM had max weights for joint effects of AP on many conditions.ConclusionsLong-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

Spatiotemporal Variation in Absorption Aerosol Optical Depth over China

Absorbing aerosols can absorb solar radiation, affect the atmospheric radiation balance, and further have a profound influence on the global and regional climates. The absorption aerosol optical depth (AAOD) as well as the absorption Angstrom exponent (AAE) across China over 2005–2018 were systematically studied through the Ozone Monitoring Instrument (OMI) dataset. The monthly AAOD samples from the OMI generally showed a good correlation (~0.55) compared to the monthly data from AERONET at four typical sites (North: Xianghe, East: Taihu, South: Hongkong Polytechnic Univ; Northwest: Sacol) across China. The ensemble annual average of the OMI AAOD at 388 and 500 nm is 0.046 and 0.022, with minor changes during 2005–2015, and a relatively fast increase after that. The winter and spring seasons depict the maximum mean AAODs, followed by autumn, whereas summer shows minimum levels. On the contrary, the high AAE values appear in summer and low values in winter. The order of the annual average AAOD500 from 2005 to 2018 is the Tarim Basin (TB, 0.041) > the Yellow River Basin (YRB, 0.023) > Beijing and Tianjin (BT, 0.026) > the Sichuan Basin (SB, 0.023) > Nanjing and Shanghai (NS, 0.021) > the Pearl River Delta (PRD, 0.017), whereas the AAE388–500 exhibits the opposite trend except for the TB (3.058). From 2005 to 2018, the AAOD rises by nearly 1.5–2.0 fold in the six typical regions, implying a severe situation of dust and/or BC aerosol pollution in the last several years. The monthly mean AAOD388 over the TB, the SB, the YRB, BT, the PRD, and NS is estimated to be smallest at 0.072, 0.024, 0.026, and 0.027 in July, 0.024 in June, and 0.025 in September, respectively, whilst largest in January for NS, the YRB and BT, April for the TB, February for the SB, and March for the PRD with 0.055, 0.077 and 0.067, 0.123, and 0.073 and 0.075, respectively. The monthly averaged AAOD500 in each region is consistently about half of the AAOD388. The highest AAE appears in June while the lowest values are in December and January, and the daily AAE values in episode days slightly decrease as compared to non-episode days. Our study indicates that northwestern China plays an important role in the overall AAOD as a result of dust aerosols stemming from desert areas. Moreover, the meteorological conditions in winter and early spring are associated with more energy consumption conducive to the accumulation of high black carbon (BC) aerosol pollution, causing high alert levels of AAOD from November to the following March.

Prenatal exposure to PM2.5 and its composition on child growth trajectories in the first two years: A prospective birth cohort study

The findings on the relationship between prenatal exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and its constituent and children's growth trajectories are inconsistent. This association's sensitive exposure time window and possible gender differences remain unclear. Our aim was to determine the association between prenatal exposure to PM2.5 and its component and children's growth trajectories by the age of two. From 2015 to 2021, 6407 mother-infant pairs were enrolled in the study. The PM2.5 include sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), organic matter (OM), and black carbon (BC), from the ChinaHighAirPollutants (CHAP) datasets. Children were followed at birth, 1, 3, 6, 9, 12, 18, and 24 months. Population-based and individual-based methods were used to simulate child growth trajectories: slow growth, normal growth, and rapid growth. The distributed lags modeling was used to identify sensitive time windows for the effects of prenatal exposure to PM2.5 and its components on child growth. Sex-stratified analyses estimated sex differences. Median concentrations [interquartile ranges (IQRs)] were 57.46(17.3), 10.59(3.8), 14.26(4.4), 8.69(2.8), 13.05(3.4), and 2.53(0.7) μg/m3 for PM2.5, SO42−, NO3−, NH4+, OM, and BC, respectively. Compared with the normal growth trajectory group, exposure to PM2.5 was significantly associated with a higher risk of rapid growth trajectory in boys (ORs with 95% CI for the entire, first trimester, and second trimester of pregnancy, respectively: 1.016[1.006,1.025], 1.007[1.002,1.011], 1.007[1.002,1.011]). Exposure to PM2.5 was significantly associated with a higher risk of slow growth trajectory in girls (ORs with 95% CI for the entire, second trimester, and third trimester of pregnancy, respectively: 1.010 [1.001,1.018], 1.006 [1.001,1.011], 1.007 [1.002,1.012]). Prenatal PM2.5 and its composition exposure was positively associated with BMI peak in boys (βs with 95% CI for PM2.5, SO42−, NO3−, NH4+, OM, BC: 0.004[0.000,0.007], 0.025[0.006,0.044], 0.012[0.002,0.023], 0.022[0.004,0.039], 0.016[0.001,0.031], 0.082[0.005,0.159]), and not statistically significant in girls. We observed a more pronounced BC effect in our cohort. Prenatal exposure to PM2.5 and its component, especially at 10–22 weeks of gestation, is associated with a higher risk of rapid growth in boys and a risk of slow growth in girls.

Evaluation of a self-monitoring protocol for assessing soot and polycyclic aromatic hydrocarbon exposure among chimney sweeps.

Traditional methods for measuring chemical exposure have challenges in terms of obtaining sufficient data; therefore, improved methods for better assessing occupational exposure are needed. One possible approach to mitigate these challenges is to use self-monitoring methods such as sensors, diaries, or biomarkers. In the present study, a self-monitored method for measuring soot exposure, which included real-time air monitoring, a work diary, and the collection of urine samples, was evaluated. To validate the method, exposure measurements during the workday and diary entries were compared with velocities calculated from GPS tracking and the expected polycyclic aromatic hydrocarbon (PAH) metabolite patterns in urine. The method was applied with chimney sweeps, an occupational group at a high risk of many severe health outcomes and for whom effective control measures for reducing exposure are needed. In the study, 20 chimney sweeps followed a self-monitoring protocol for 8 consecutive workdays. Personal exposure to soot was measured as black carbon (BC) using micro-aethalometers. A diary was used to record the work tasks performed, and urine samples were collected and analysed for PAH metabolites. From the expected 160 full day measurements, 146 (91%) BC measurements and 149 (93%) diaries were collected. From the expected 320 urine samples, 304 (95%) were collected. The tasks noted in the diaries overlapped with information obtained from the GPS tracking of the chimney sweeps, which covered 96% of the measurement time. The PAH metabolites in urine increased during the work week. Factors believed to have positively influenced the sample collection and task documentation were the highly motivated participants and the continuous presence of trained occupational hygiene professionals during the planning of the study and throughout the measurement stage, during which they were available to inform, instruct, and address questions. In conclusion, the self-monitored protocol used in this study with chimney sweeps is a valuable and valid method that can be used to collect larger numbers of samples. This is especially valuable for occupations in which the employees are working independently and the exposure is difficult to monitor with traditional occupational hygiene methods.

Characterizing hydrogen-diesel dual-fuel performance and emissions in a commercial heavy-duty diesel truck

This study investigates hydrogen (H2) as a supplementary fuel in heavy-duty diesel engines using pre-manifold injection. A H2-diesel dual-fuel (H2DF) system was implemented on a commercial class-8 heavy-duty diesel truck without modifying the original diesel injection system and engine control unit (ECU). Tests were conducted on a chassis dynamometer at engine speeds between 1000 and 1400 rpm with driver-demanded torques from 10 to 75%. The hydrogen energy fraction (HEF) was strategically controlled in the range between 10 and 30%. Overall, CO2 reduction (comparable to the HEF level) was achieved with similar brake-specific energy consumption (BSEC) at all loads and speeds. To maintain the same shaft torque, the driver-demanded torque was reduced in H2DF operation, which resulted in a lower boost pressure. At higher loads, engine-out BSNOx slightly decreased, while BSCO and black carbon (BC) increased significantly due to lower oxygen concentration resulting from the lower boost pressure. At lower loads, engine-out BSCO and BSBC decreased moderately, while NO2/NO ratio increased substantially in H2DF operation. Deliberate air path and diesel injection control are expected to enable higher HEF and GHG reductions.

PM10 Organic Aerosol Fingerprints by Using Liquid Chromatography Orbitrap Mass Spectrometry: Urban vs. Suburban in an Eastern Mediterranean Medium-Sized Coastal City

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.