High Black Carbon Concentrations Research Articles

Atmospheric black carbon observations and its valley-mountain dynamics: Eastern cordillera of the central Andes of Peru

Glacial bodies in the Peruvian Andes Mountains store and supply freshwater to hundreds of thousands of people in central Peru. Atmospheric black carbon (BC) is known to accelerate melting of snow and ice, in addition to contributing to air pollution and the health of people. Currently there is limited understanding on the sources and temporal variability of BC in valley and mountain environments in Peru. To address this problem, this study combined surface observations of BC collected during 2022–2023 with WRF model simulations and HYSPLIT trajectories to analyze the dispersion and sources of BC in valley and high elevation environments and the associated local atmospheric circulations. Results show high BC concentrations are associated with the valley-mountain wind system that occurs on both sides of the Huaytapallana mountain range. A pronounced circulation occurs on the western slopes of Huaytapallana when concentrations of BC increase during daylight hours, which transports atmospheric pollutants from cities in the Mantaro River Valley to the Huaytapallana mountain range. Low concentrations of BC are associated with circulations from the east that are channeled by the pronounced ravines of the Andes-Amazon transition. On average, during the season of highest BC concentrations (July–November), the relative contributions of fossil fuels are dominant to biomass burning at the valley observatory and are slightly lower at the Huaytapallana observatory. These results demonstrate the need to promote mitigation actions to reduce emissions of BC and air pollution associated with forest fires and local anthropogenic activity.

Source-specified atmospheric age distribution of black carbon and its impact on optical properties over the Yangtze River Delta

Black carbon (BC) exerts a profound and intricate impact on both air quality and climate due to its high light absorption. However, the uncertainty in representing the absorption enhancement of BC in climate models leads to an increased range in the modeled aerosol climate effects. Changes in BC optical properties could result either from atmospheric aging processes or from variations in its sources. In this study, a source-age model for identifying emission sources and aging states presented by University of California at Davis/California Institute of Technology (UCD/CIT) was used to simulate the atmospheric age distribution of BC from different sources and to quantify its impact on the optical properties of BC-containing particles. The results indicate that regions with greater aged BC concentrations do not correspond to regions with higher BC emissions due to atmospheric transport. High concentrations of aged BC are found in northern Yangtze River Delta (YRD) regions during summer. The chemical compositions of particles from different sources and with different atmospheric ages differ significantly. BC and primary organic aerosols (POA) are dominating in Traffic-dominated source while other components dominate in Industry-dominated source. As the atmospheric age increases, the mass fraction of secondary inorganic aerosols rises. Compared to the original model, the simulated mass absorption cross section of BC particles in the source-age model decreases while the single scattering albedo increases. This compensates for ~11 % of the overestimation of the simulated BC direct radiative forcing. Our study highlights that incorporating atmospheric age and source information into models can greatly improve the estimation of optical properties of BC-containing particles and deepen our understanding of their climate effects.

Emission-Based Machine Learning Approach for Large-Scale Estimates of Black Carbon in China

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.

Black carbon instrument responses to laboratory generated particles

Accurate measurement of black carbon (BC) particles is vital for climate models as well as air quality assessments. While the need for BC particle measurement has been recognized, standardization of instruments and procedures for ambient measurement is still underway. In this study, we used laboratory generated soot particles to assess nine instruments targeting BC mass concentration measurement. The measurement matrix included different BC concentrations (ranging from atmospheric levels to combustion emission levels), different particle coatings, two particle sources (gas burner and spark generator) and two dilution methods. The nine instruments included six different models: aethalometers AE33 and MA200, thermo-optical OC-EC analysis, multi-angle absorption photometer MAAP 5012, photoacoustic instrument MSS, and soot particle aerosol mass spectrometer SP-AMS. The main discrepancy we observed was that the SP-AMS results were systematically lower, approximately only half of the BC measured by other instruments. A portion of this is explained by particle losses in the aerodynamic lens of the SP-AMS and the parameters used in the data analysis. Some smaller discrepancies were identified for the other instruments, but overall, the median values from were within 25 % of each other. Instruments’ operation principles and covered concentration ranges need to be carefully considered especially in emission measurements where the aerosols can have high temporal variation as well as high BC concentrations. In general, the results can decrease the uncertainties in climate and air quality studies by providing tools for more accurate and comparable BC measurements and when the existing BC data is interpreted.

Tepidibacter aestuarii sp. nov., isolated from the Bach Dang Estuary, Haiphong, Vietnam.

A mesophilic, anaerobic, endospore-forming, fermentative bacterium designated strain 8C15bT was isolated from bank sediment of the Bach Dang Estuary, Haiphong, Vietnam. The Bach Dang Estuary, where Haiphong harbour is located, is subject to strong anthropogenic influence, resulting in high concentrations of black carbon and heavy metals. Strain 8C15bT grew optimally at 30 °C, pH 7.5 and with 2.5 % (w/v) NaCl. The main cellular fatty acids consisted of iso-C15 : 0 (51 %), iso-C15:1 ω7c (32 %) and iso-C13 : 0 (5 %). Genomic considerations of strain 8C15bT and comparisons with the phylogenetically closest strains of the genus Tepidibacter provide evidence that Tepidibacter thalassicus SC562T (=DSM 15285T), Tepidibacter formicigenes DV1184T (=DSM 15518T), Tepidibacter mesophilus B1T (=JCM 16806T) and strain 8C15bT could be differentiated at the species level. We propose the name Tepidibacter aestuarii sp. nov. for the type strain 8C15bT (=JCM 35983T=KCTC 25692T). Finally, the nickel-tolerance properties of strain 8C15bT are highlighted in this study.

Trends of Atmospheric Black Carbon Concentration over the Bengaluru

This study investigates the spatial and temporal variations of atmospheric black carbon (BC) concentrations in Bangalore, focusing on the period from June 2018 to May 2020. BC mass concentrations were measured using a portable micro-Aethalometer (model: AethLabs AE-51) at seven different locations, representing a range of land use types from rural to urban areas. The study aimed to assess BC pollution levels, identify hotspots, and understand the factors influencing BC concentrations. The results revealed significant variations in BC concentrations among the different locations. The highest BC concentrations were observed in urban traffic and industrial areas, with average concentrations of 6.21 µg/m³ and 6.78 µg/m³, respectively. Urban centres also exhibited high BC levels, with an average concentration of 7.40 µg/m³. In contrast, rural areas recorded the lowest BC concentrations, with an average of 2.51 µg/m³. These findings highlight the influence of anthropogenic activities and land use patterns on BC pollution levels. Diurnal variations in BC concentrations exhibited distinct patterns, with significant peaks during morning and evening hours, primarily associated with increased traffic emissions. The study also identified seasonal trends, with higher BC concentrations observed during winter months, attributed to stable atmospheric conditions and increased fuel consumption for heating purposes. Notably, BC concentrations were generally lower during summer months due to higher wind speeds and increased vertical mixing of pollutants. The findings of this study emphasize the need for targeted mitigation strategies to reduce BC pollution in Bangalore. The identified hotspots, such as urban traffic and industrial areas, require specific attention to mitigate the adverse health and environmental effects of BC emissions. Furthermore, the study underscores the importance of comprehensive air pollution management approaches that consider both local emissions and meteorological factors to effectively tackle BC pollution.

Land Use Regression Models for Particle Number Concentration and Black Carbon in Lanzhou, Northwest of China

It is necessary to predict the spatial variation in particle number concentration (PNC) and black carbon (BC) because they are considered air pollutants associated with traffic and many diseases. In this study, land use regression (LUR) models for PNC and BC were developed based on a mobile monitoring campaign in January 2020 in Lanzhou, and the performance of models was evaluated with hold-out validation (HV) and leave-one-out cross-validation (LOOCV). The results show that the adjusted R2 of the LUR models for PNC and BC are 0.51 and 0.53, respectively. The R2 of HV and LOOCV are 0.43 and 0.44, respectively, for the PNC model and 0.42 and 0.50, respectively, for the BC model. The performances of the LUR models are of a moderate level. The spatial distribution of the predicted PNC is related to the distance from water bodies. The high PNC is related to industrial pollution. The BC concentration decreases from south to north. High BC concentrations are associated with freight distribution centres and coal-fired power plants. The range of PNC particle sizes in this study is larger than in most studies. As one of few studies in Lanzhou to develop LUR models of air pollutants, it is important to accurately estimate pollutant concentrations to improve air quality and provide health benefits for residents.

Лесные пожары как источник черного углерода в Арк­тике летом 2022 г.

The assessment of aerosol pollution of the atmosphere in the high-latitude regions of the Arctic is among the most important environmental and climate problems. In the summer of 2022, due to abnormal temperatures and a lack of precipitation, the wildfire areas in the Western Siberia and European part of the Russian Federation reached record levels. At the polar aerosol station of the Moscow State University “Island Bely” (the Kara Sea), continuous aethalometric measurements of the short-lived climatic tracer namely black carbon are carried out. In August 2022, seven episodes of pollution were recorded, significantly exceeding the background typical for the Arctic summer. An analysis of the aerosol absorption capacity in a wide range of solar radiation revealed a significant effect of wildfire plumes on the aerosol composition of the Arctic atmosphere. The distribution of high concentrations of black carbon depending on the wind direction and speed pointed to the southern direction, Yamal Peninsula, as a source of high pollution. Regional distribution of black carbon sources calculated by the method of assigning air mass transfer trajectories to measured concentrations on Bely Island identifies the regions of the Western Siberia, the northern and central regions of the European part of Russia, the steppe regions of the East European Plain, and the Southern Urals. Wildfires from identified source regions impacted significantly the composition of the climatically active aerosol component of the atmosphere.

Black carbon emissions in the rural Indian households: Sources, exposure, and associated threats

In this study, we present the indoor Black Carbon (BC) measurements with the help of Aethalometer (AE‐33) from various sites in Eastern India in a typical kitchen room situated in a rural area. Analysis was done on how various cooking activities performed in the home affected the indoor level of BC. The activities resulting in elevated indoor concentrations included three different periods of cooking breakfast, lunch, and dinner with three different kinds of kitchen structures open, semi‐open and closed kitchen. Close kitchen resulted in the highest BC concentrations, while open kitchen resulted in the lowest level. The burning of low‐grade fuels resulted in the largest increases in indoor BC concentration. We calculated the average BC concentrations for three distinct kitchens, with open kitchens emitting 260.14 μgm−3, semi‐open kitchens emitting 441.14 μgm−3, and closed kitchens emitting 477.25 μgm−3. The biomass burning % was high during the entire research. Because BC mass concentration was found to be high in indoor sampling, as a result, the health risk assessment is also considered to be high in all types of kitchens. As people spend a significant amount of time at home, especially in a future where remote work is anticipated to be easier, finding the activities, sources, and health effects that increase indoor pollution is vital to lowering indoor exposure.

An innovative passive sampler to reveal the high contribution of biomass burning to black carbon over Indo-China Peninsula: Radiocarbon constraints

Black carbon (BC) is an important component of the brown clouds, contributing to climate and health effects of air pollution. In this work, we developed a new method for measuring BC concentrations and its radiocarbon isotope (14C) using quartz wool disk passive air samplers (Pas-QW). A field calibration study was conducted at two sampling sites (Guangzhou and Yantai), using an improved thermal/optical method to measure BC. Uptake profiles of Pas-QW were linear over the 77 days that the samplers were deployed, and the average sampling rate of BC measured was 1.1 ± 0.2 m3/day. The method was found to be reproducible with coefficients of variation as low as 17% for BC measured in ambient passive samples. Furthermore, passive sampling was carried out at six sites in the Indo-China Peninsula (ICP) from January to April and June to September of 2016. The high BC concentrations and the high fraction of modern carbon (fM) values emphasizes that ICP is still dominated by biomass burning emissions (residential cooking and agricultural burning), both in dry and wet seasons. This study provides a proof concept and methodology for the application of Pas-QW to cost-effectively expand measurements of BC at the global scale.

Explaining the natural and anthropogenic factors driving glacier recession in Kashmir Himalaya, India.

Glaciers across the Kashmir Himalayan region are melting at an accelerated pace compared to other regions across the Himalayan arc. This study analyzed the recession patterns of nine glaciers in the Kashmir Himalaya region over 28years between 1992 and 2020 using satellite images and field measurements. The recession patterns were correlated with debris cover, topographic factors, and ambient black carbon (BC) concentration at glacier sites. HYSPLIT model was used to track the air mass sources at a 7-day time-step from September 1, 2014, to September 28, 2014, over the selected region. All nine glaciers revealed high recession as indicated by changes in the area (average recession: 20.8%) and snout position (~ 14m a-1). The relative percentage of debris on each glacier varied between ~ 0% (clean glacier) and 43%. Although the investigated glaciers lie in the same climatological regime, their topographical behavior is dissimilar with mean altitude ranging between 4000 and ~ 4700m asl and the average slope varying from 17 to 24°. All the investigated glaciers are north-facing except G3 (southerly aspect). Our results indicate anomalously high ambient BC concentrations, ranging from 500 to 1364ngm-3, at the glacier sites, higher than previously studied for glaciers in the Himalayas and neighboring Tibetan Plateau. The backward air-mass trajectory modeling indicated both local and global sources of particulate matter in the study area. A comparative analysis of BC measurements and glacier recession with the studies conducted across high Asia indicated the influence of BC in accelerating the melting of glaciers in the Kashmir region.

High concentration of black carbon in northern Pakistan: Characteristics, source apportionment and emission source regions

Atmospheric Black Carbon (BC) is one of the absorbing components of solar radiation which potentially affects human health and regional climate. In the current study, BC mass concentrations were regularly observed for pre-monsoon and monsoon seasons using the seven-channel aethalometer (AE-33) over Peshawar, Pakistan. The scarcity of BC measurement in this region is critical for air quality assessment, hence providing much importance to this article for control policy recommendations. The monthly mean BC showed a maximum value of 12.1 ± 5.4 μg/m3 during March and a minimum value of 6.4 ± 3.1 μg/m3 during July. The bimodal diurnal BC concentration was observed in between 05:00–08:00 and 20:00–24:00 LST having a maximum night/day ratio of 3.4 during April. Furthermore, the weekdays BC concentration was higher than weekend days having the highest weekdays concentration during March (12.9 ± 5.6 μg/m3) and the lowest concentration during July (6.9 ±0 .9 μg/m3). Moreover, BC contributed maximum of 22% to PM2.5 during April and minimum of 7% during June. The source apportionment of BC revealed that maximum value of BC emitted from fossil fuel (BCFF) and biomass burning (BCBB) were 9.90 ± 0.50 μg/m3 and 2.61 ± 0.49 μg/m3 during March showed a clear dominancy of BCFF over BCBB emission. Further the highest percentage contribution of BCFF and BCBB were found to be 80.45% and 22.27% to total BC during May and April, respectively. Finally, the cluster trajectory analysis showed that majority of the air pollutants were due to local emission rather than long range transport.

Pollution characteristics of black carbon based on MERRA-2 reanalysis data in core city of Central Plains Economic Zone, China: Historical trend and potential sources

Black carbon (BC) is one of the main factors in global climate change and human health. Based on reanalysis data from the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), the historical trends in the variation of BC and the factors affecting this were investigated in core city of Central Plains Economic Zone in China-Zhengzhou. Based on correlation analysis with ground measurements of BC concentration, it was determined that the MERRA-2 reanalysis data could be used to reveal the variations in ground-level BC concentrations. According to the variation trends of BC concentration in 1980–2020 and typical fossil fuel consumption in 2008–2017, two periods of rapidly increasing BC concentration were identified in 1980–1989 and 1999–2006. The increase in BC concentration then slowed from 2007. Since 2012, due to the adjustment of the Zhengzhou strategy and the implementation of an emission control strategy throughout Henan Province, the consumption of coal and coke decreased by 4% every year, resulting in a downward trend in the total BC emissions. However, coal and coke were still the main factors affecting the BC concentration in Zhengzhou. The contribution of transportation to BC in Zhengzhou has been particularly important since 2016. Analysis of BC seasonal variation revealed that the highest BC concentration was in winter, mainly due to the increase in industry and residential emissions. Additionally, based on the local and regional emission inventories and combined with potential source contribution function (PSCF), concentration weighted trajectory (CWT), this study revealed the potential sources regions and source types of BC in Zhengzhou, and found that the intensification of energy consumption and BC emissions in Zhengzhou and the surrounding regions of Henan Province might be the reasons for the high BC loading in Zhengzhou through regional transport.

COVID-19-associated 2020 lockdown: a study on atmospheric black carbon fall impact on human health.

The mean mass concentrations of black carbon (BC), biomass burning (BC)bb, and fossil fuel combustion (BC)ff have been estimated during March-May 2020 (during the COVID-19 outbreak) and March-May 2019 at a semiarid region of Agra over the Indo-Gangetic basin region. The daily mean mass concentration of BC in 2020 and 2019 was 3.9 and 6.9µgm-3, respectively. The high monthly mean mass concentration of BC was found to be 4.7, 3.4 and 3.3µgm-3 in Mar-2020, Apr-2020, and May-2020, respectively, whereas in Mar-2019, Apr-2019, and May-2019 was 7.7, 7.5 and 5.4µgm-3, respectively. The absorption coefficient (babs) and absorption angstrom exponent (AAE) of black carbon were calculated. The highest mean AAE was 1.6 in the year 2020 (Mar-May 2020) indicating the dominance of biomass burning. The mean mass concentration of fossil fuel (BC)ff and biomass burning (BC)bb is 3.4 and 0.51µgm-3, respectively, in 2020 whereas 6.4 and 0.73µgm-3, respectively, in 2019. The mean fraction contribution of BC with fossil fuel (BC)ff was 82.1 ± 13.5% and biomass burning (BC)bb was 17.9 ± 4.3% in 2020, while in 2019, fossil fuel (BC)ff was 86.7 ± 13.5% and biomass burning (BC)bb was 13.3 ± 6.7%. The population-weighted mean concentration of BC, fossil fuel (BC)ff, and biomass burning (BC)bb has been calculated. The health risk assessment of BC has been analyzed in the form of attributable relative risk factors and attributed relative risk during the COVID-19 outbreak using AirQ + v.2.0 model. The attributable relative risk factors of BC were 20.6% in 2020 and 29.4% in 2019. The mean attributed relative risk per 10,000,000 populations at 95% confidence interval (CI) due to BC was 184.06 (142.6-225.2) in 2020 and 609.06 (418.3-714.6) in 2019. The low attributed factor and attributed relative risk in 2020 may be attributed to improvements in air quality and a fall in the emission of BC. In 2020, due to the COVID-19 pandemic, the whole country faced the biggest lockdown, ban of the transportation of private vehicles, trains, aircraft, and construction activities, and shut down of the industry leading to a fall in the impact of BC on human health. Overall, this was like a blessing in disguise. This study will help in future planning of mitigation and emission control of air pollutants in large and BC in particular. It only needs a multipronged approach. This study may be like torch bearing to set path for mitigation of impacts of air pollution and improvement of air quality.

Variability of ambient black carbon concentration in the Central Himalaya and its assessment over the Hindu Kush Himalayan region

During 2015–2018, eight black carbon (BC) monitoring sites were established in Nepal and Bhutan to fill a significant data gap regarding BC measurement in Central Himalaya. This manuscript analyzes and presents data from these eight stations and one additional station on the Tibetan plateau (TP). Complex topography, varied emission sources, and atmospheric transport pathways significantly impacted the BC concentrations across these stations, with annual mean concentrations varying from 36 ng m−3 to 45,737 ng m−3. Higher annual mean concentrations (5609 ± 4515 ng m−3) were recorded at low-altitude sites than in other locations, with seasonal concentrations highest in the winter (7316 ± 2541 ng m−3). In contrast, the annual mean concentrations were lowest at high-altitude sites (376 ± 448 ng m−3); the BC concentrations at these sites peaked during the pre-monsoon season (930 ± 685 ng m−3). Potential source contributions to the total observed BC were analyzed using the absorption angstrom exponent (AAE). AAE analysis showed the dominance of biomass burning sources (>50 %), except in Kathmandu. By combining our data with previously published literature, we put our measurements in perspective by presenting a comprehensive assessment of BC concentrations and their variability over the Hindu Kush Himalayan (HKH) region. The BC levels in all three geographic regions, high, mid, and low altitude significantly influenced by the persistent seasonal meteorology. However, the mid-altitude stations were substantially affected by valley dynamics and urbanization. The low-altitude stations experienced high BC concentrations during the winter and post-monsoon seasons. Concentration weighted trajectory (CWT) and frequency analyses revealed the dominance of long-range transported pollution during winter over HKH, from west to east. South Asian sources remained significant during the monsoon season. During pre- and post-monsoon, the local, regional, and long-distance pollution varied depending on the location of the receptor site.

The air quality of Palangka Raya, Central Kalimantan, Indonesia: The impacts of forest fires on visibility

ABSTRACT Airborne particles in urban Palangka Raya, Kalimantan from Oct 2011 until Oct 2020 have been collected and analyzed for PM2.5, PM10, and Black Carbon (BC) concentrations. Palangka Raya is a city that serves the capital of the Central Kalimantan province on the island of Borneo. Kalimantan is affected by peat fires that occur periodically. There were identified increases in PM2.5 and PM10 concentrations during El Niño periods. During the forest fire episode in September – October 2015, PM2.5 and PM10 concentrations increased significantly, to nearly 400 µg/m3 and 800 µg/m3, respectively, and visibility in the city was reduced to < 0.2 miles. The highest BC concentrations were observed during this massive forest fires episode. The regression analyses for PM2.5, PM10 and visibility in Palangka Raya during the period of 2011–2020, showed a non-linear correlation with reduction in visibility due to increased PM2.5 and PM10. There was no correlation for BC with visibility. Air quality in Palangka Raya was at a relatively good level with concentrations below the national ambient air quality standard when there were no forest fires event. Emissions from forest fires caused a substantial reduction in air quality reaching concentrations well above ambient air quality standards and are likely to have caused adverse health effects on the people living in the area. Implications: Indonesia has repeatedly experienced forest fires, especially on Kalimantan and Sumatera Islands, which burned large areas of peatland. The forest fires leading to increasing PM concentrations especially in the PM2.5 size range which influence visibility. The seasonal variations of BC in Palangka Raya and the relationships of fine particulates with visibility were assessed. The results of regression analyses for PM2.5 and PM10 to visibility during the period of 2011-2020 showed non-linear relationships. An increasing of PM2.5 and PM10 concentrations during El Nino periods were detected well above the ambient air quality standard. To ensure effective and continued handling and prevention of forest and peatland fires, the government set up a special task force and review on several rules, including laws and government regulations as well as governor regulations that permit the burning of forest and peatland areas. These results are expected to be used to formulate more effective mitigations in reducing forest fires events in Indonesia.

Personal Exposure and Inhaled Dose Estimation of Air Pollutants during Travel between Albany, NY and Boston, MA

Out of eight deaths caused worldwide, one death is caused due to air pollution exposure, making it one of the top global killers. Personal exposure measurement for real-time monitoring has been used for inhaled dose estimation during various modes of workplace commuting. However, dose-exposure studies during long commutes are scarce and more information on inhaled doses is needed. This study focuses on personal exposures to size-fractionated particulate matter (PM1, PM2.5, PM4, PM7, PM10, TSP) and black carbon (BC) inside a bus traveling more than 270 kms on a highway between Albany, NY and Boston, MA. Measurements were also made indoors, outdoors, and while walking in each city. Mean PM (PM1, PM2.5, PM4, PM7, PM10, TSP) and mean BC concentrations were calculated to estimate the inhaled exposure dose. The highest average PM2.5 and PM10 exposures concentrations were 30 ± 12 and 111 ± 193 µg/m3, respectively, during Boston to Albany. Notably, personal exposure to BC on a bus from Albany to Boston (5483 ± 2099 ng/m3) was the highest measured during any commute. The average inhaled dose for PM2.5 during commutes ranged from 0.018 µg/km to 0.371 µg/km. Exposure concentrations in indoor settings (average PM2.5 = 37 ± 55 µg/m3, PM10 = 78 ± 82 µg/m3, BC = 5695 ± 1774 ng/m3) were higher than those in outdoor environments. Carpeted flooring, cooking, and vacuuming all tended to increase the indoor particulate level. A high BC concentration (1583 ± 1004 ng/m3) was measured during walking. Typical concentration profiles in long-haul journeys are presented.

Statistical Analysis of Surface Ozone and Black Carbon over Distinct Regions of India

Since India has different climatology, statistical analysis of trace gases over distinct regions is very important to take necessary actions to control the pollutants. A network of stations has been initiated by Indian Space Research Organization in India to retrieve data on atmospheric trace gases. However, only few studies have been done on statistical analysis of trace gases on distinct regions of India. In this paper discussed statistical behavior of surface ozone (O3 ) and black carbon (BC) mass concentration in different regions of lndia like rural, semi-urban, urban, and hill stations. The diurnal variation of rate of change of O3 is used to analyze trace gases chemical environments of various locations. Results showed that surface ozone at Anantapur is similar to Kannur, and lower than that at Dayalbagh, an urban site; Darjeeling and Port Blair, a high altitude and hill site. In India, some locations reported lower surface ozone mixing ratios than Anantapur like Dibrugarh, a semi-urban location; Kullu, Pantnagar, semi-urban; Hyderabad, an urban site; Trivendrum, a coastal site; Chennai, an urban site; and Joharapur, a rural site. High concentrations of black carbon were observed at Kanpur, an urban site (6-20 µg/m3 ) followed by Hyderabd, an urban site (1.5-11.2 µg/m3 ), and Ahmedabad (0.2-10.2 µg/m3 ). Results showed that Mohal-Kullu, and Darjeeling reported high BC compared with other hill stations like Ooty and Nainital, and semi-arid rural stations also reported substantial BC

An assessment of the impact of Indian summer monsoon droughts on atmospheric aerosols and associated radiative forcing at a semi-arid station in peninsular India

A continuing increase in droughts/floods in Asian monsoon regions and worsening air quality due to aerosols are the two biggest threats to the health and well being of over 60% of the world's population. This study focuses on in-situ observations of atmospheric aerosols and their impact on shortwave direct aerosol radiative forcing (SDARF) during the southwest monsoon season (June–September) from 2015 to 2020 over a semi-arid station in Southern India. The Standardized precipitation index (SPI) is used to identify the droughts and normal monsoon years. Based on the SPI index, 2015, 2016, and 2018 were considered the drought monsoon years, while 2017, 2019, and 2020 were chosen as the normal monsoon years. During the drought monsoon years (normal monsoon years), the monthly mean black carbon (BC) was 1.17 ± 0.25 (0.72 ± 0.18), 1.02 ± 0.31 (0.64 ± 0.17), 1.02 ± 0.38 (0.74 ± 0.28), and 1.28 ± 0.35 μg/m3 (0.88 ± 0.21 μg/m3), for June, July, August and September respectively. The lower BC concentration during the normal monsoon years is mainly due to the enhanced wet-removal rates by high rainfall over the measurement location. In July, there was a high ventilation coefficient (VC) and low concentration of BC, while in September, low VC, and a high concentration of BC was observed in both the drought and the normal monsoon years. In addition, a plane-parallel radiative transfer model was used to estimate shortwave direct aerosol radiative forcing for composite and without BC at various surfaces, including the surface (SUF), atmosphere (ATM), and top of the atmosphere (TOA). During the drought monsoon years (normal monsoon years), the estimated monthly mean ATM forcing was 17.6 ± 2.4 (13.9 ± 2.1), 17.5 ± 7.5 (12.7 ± 4.4), 17.2 ± 4.0 (13.5 ± 1.9), and 17.4 ± 2.8 Wm−2 (14.6 ± 0.7 Wm−2) for June, July, August, and September, respectively. During the drought monsoon years, the estimated BC forcing was substantially larger (8.8 ± 2.6 Wm−2) than that of normal monsoon years (6.0 ± 1.5 Wm−2). It indicates the important role of absorbing BC aerosols during the drought monsoon years in introducing additional heat to the lower atmosphere, particularly over peninsular India.

Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert)

Abstract. Black carbon (BC) is a primary and inert pollutant often used as a traffic tracer. Even though its concentrations are generally low at the regional scale, BC presents very high concentrations in streets (at the local scale), potentially with important effects on human health and the environment. Modeling studies of BC concentrations usually underestimate BC concentrations due to uncertainties in both emissions and modeling. Both exhaust and non-exhaust traffic emissions present uncertainties, but the uncertainties with respect to non-exhaust emissions, such as tire, brake, and road wear as well as particle resuspension, are particularly high. In terms of modeling, street models do not always consider the two-way interactions between the local and regional scales. Using a two-way modeling approach, a street with high BC concentrations may influence urban background concentrations above the street, which can subsequently enhance the BC concentrations in the same street. This study uses the multiscale Street-in-Grid model (SinG) to simulate BC concentrations in a suburban street network in Paris, taking the two-way coupling between local and regional scales into account. The BC concentrations in streets proved to have an important influence on urban background concentrations. The two-way dynamic coupling leads to an increase in BC concentrations in large streets with high traffic emissions (with a maximal increase of about 48 %) as well as a decrease in narrow streets with low traffic emissions and low BC concentrations (with a maximal decrease of about 50 %). A new approach to estimate particle resuspension in streets is implemented, strictly respecting the mass balance on the street surface. The resuspension rate is calculated from the available deposited mass on the street surface, which is estimated based on particle deposition and wash-off parameterizations adapted to street-canyon geometries. The simulations show that particle resuspension presents a low contribution to BC concentrations, as the deposited mass is not significant enough to justify high resuspension rates. Non-exhaust emissions, such as brake, tire, and road wear, may largely contribute to BC emissions, with a contribution that is equivalent to exhaust emissions. Here, a sensitivity analysis of BC concentrations is performed by comparing simulations with different emission factors of tire, brake, and road wear. The different emission factors considered are estimated based on the literature. We found a satisfying model–measurement comparison using high tire wear emission factors, which may indicate that the tire emission factors usually used in Europe are probably underestimated. These results have important policy implications: public policies replacing internal combustion engines with electric vehicles may not eliminate BC air pollution but only reduce it by half.