Multi-platform observations and constraints reveal overlooked urban sources of black carbon in Xuzhou and Dhaka

High-resolution observations and multi-waveband optical constraints from ground-based and satellite data in Xuzhou, China, and Dhaka, Bangladesh, reveal that urban riverbanks and small industrial sites are often overlooked sources of black carbon emissions in Asian cities.
Published in Earth & Environment
Multi-platform observations and constraints reveal overlooked urban sources of black carbon in Xuzhou and Dhaka
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Small Particles, Big Problems: Black Carbon's Far-Reaching Impacts and Quantification Hurdles

When we think about air pollution and climate change, the usual culprits—carbon dioxide and methane—immediately come to mind. But there’s another powerful player in the mix that doesn’t get nearly enough attention: black carbon (BC). Often referred to as "soot", BC is a product of incomplete combustion and poses serious threats to both the climate and air quality.

BC is a powerful climate and health threat. Its contributes to direct climate forcing by altering the Earth's energy balance . Imparts indirect effects by altering cloud properties as well as have been known for their  semi-direct effects that include heating the surrounding air, reducing cloud cover, and enhancing regional warming. When deposited on snow and ice, BC darkens surfaces, accelerating melting and disrupting ecosystems, which can contribute to rising sea levels. Beyond climate, BC worsens air quality by forming fine particulate matter , a major health hazard linked to respiratory and cardiovascular diseases, especially in densely populated cities like Dhaka and Xuzhou.

Despite these wide-ranging impacts, accurately measuring and modeling black carbon, remains a major challenge. Its physical and optical properties—such as particle size, mixing state, and morphology—are highly variable and influenced by source types, atmospheric conditions, and aging processes. Conventional methods often rely on simplified assumptions, in-terms of their morphology and  limited waveband measurements, leading to uncertainties and underestimations of its actual impact.

To address these challenges, the recent study combined multi-waveband data from both ground-based and satellite observations, offering a novel approach to constrain black carbon’s complex properties. Let’s explore how this approach provided new insights into overlooked black carbon sources and their impacts in two rapidly developing cities: Xuzhou, China, and Dhaka, Bangladesh.

Confining Complexity: Multi-Waveband Constraints on Black Carbon’s Morphology

In pursuit of a robust methodology,  aimed at  understanding BC's complex behavior, this study employed a multi-platform approach that integrates satellite and ground-based remote sensing data. Specifically, it combined observations from TROPOMI (on Sentinel-5P) with ground-based measurements from NASA’s AERONET and China's SONET networks, focusing on regions within a 150 km radius of the SONET/AERONET sites in Xuzhou and Dhaka. A two component Mie modeling framework was used with BC core and sulfate shell to constrain black carbon’s  size, mixing state, and other optical properties by rigorously analyzing multi-waveband data across ultraviolet, visible, and near-infrared wavelengths.

 Constraining BC morphology using multi-platform, multi-waveband  observed  Single scattering albedo (SSA) -ranges

This approach ensured that only pixels meeting strict multi-waveband observational constraints—accounting for uncertainty across multiple wavelengths—were included in the analysis. The derived solutions were then used to develop high-resolution column products, such as black carbon mass and number concentrations, which captured the spatial and temporal variability of black carbon emissions with exceptional detail. These products allowed the study to go beyond traditional seasonal averages, uncovering regional dynamics and overlooked sources with day-to-day and grid-by-grid precision.

Tailoring Regional Black Carbon Loadings: Integrating Optical Observations and Modeling

Broadening the Spectrum: The Role of UV in Black Carbon Analysis

Our study demonstrates how ultraviolet (UV) wavebands, combined with visible and near-infrared data, provided additional information on BC's morphological quantification in urban environments. In Xuzhou, the inclusion of UV data increased the representation of smaller BC core sizes (60–90 nm) by nearly 12%, capturing emissions that were previously underrepresented. In Dhaka, UV wavebands revealed a 40% increase in smaller particles (below the 30th percentile) compared to using visible and near-infrared wavebands alone. The range of BC core sizes varied between the cities, with Xuzhou showing sizes from 50 to 340 nm, while Dhaka exhibited a slightly narrower range of 50 to 320 nm, however, the BC sizes observed in Xuzhou across percentiles were smaller and more mixed than those in Dhaka.  Month-by -Month analysis across the derived sizes also differed: in Xuzhou, BC properties were influenced by heating demands and low solar insolation in winter, while in Dhaka, biomass burning and post-monsoon humidity played a dominant role.

Tracing the Unseen: Urban Rivers and Small Industries as Black Carbon Hotspots

The contrasting BC profiles of Xuzhou and Dhaka highlight the complex role between local emission sources, regional transport, and secondary aerosol formation in shaping urban air quality over different geographical regions at different levels of development. While Dhaka exhibits higher individual BC core column concentration, Xuzhou demonstrates greater overall  total column mass density and number concentration, likely due to its more diverse and intense industrial activities. This suggests that despite potentially lower combustion efficiency in Dhaka, the sheer scale of energy use and emissions in Xuzhou results in a more significant climate impact.

Next, this study developed high-resolution black carbon (BC) column products at a 5.5 × 3.5 km resolution, revealing distinct patterns of BC distribution across Xuzhou and Dhaka. While Dhaka exhibited higher BC column mass density, reflecting intense local emissions from brick kilns, biomass burning, and small-scale industries, Xuzhou recorded higher total aerosol mass and number densities. These contrasting patterns highlight Dhaka’s localized emissions and Xuzhou’s complex mix of industrial sources and transport.

In Xuzhou, high-resolution monitoring revealed significant BC column densities in and around small industrial cities, underscoring their critical yet often overlooked role as emission sources. Shangqiu, Henan, emerged as a hotspot due to emissions from coal-fired power plants and biomass burning. Similarly, Linyi, Shandong, exhibited high BC concentrations driven by biomass power plants, vehicular emissions, and industrial activities. Bozhou, Anhui, was identified as another key contributor, with elevated aerosol levels attributed to local transport and emissions from nearby urban centers. These findings highlight the contribution of small industrial cities to regional BC distribution, emphasizing the need for targeted emission control strategies to mitigate their environmental impact.

In Dhaka, BC column mass density peaked in densely populated areas such as city centre, with secondary maxima observed near urban riverbanks and brick kiln clusters. These riverbanks, largely underrepresented in emission inventories, were found to significantly contribute to aerosol loading due to agricultural activities, crop burning, and small-scale industrial operations. The strong signals and high variability observed around Dhaka's urban rivers even during the COVID-19 protocol period are particularly noteworthy, and may indicate that while urban activities were curtailed, rural and small scale industrial activities along these riverbanks remained active. Additionally, a north-south gradient in aerosol concentrations indicated transboundary pollution from Northern India’s industrial regions and biomass burning from neighboring areas.

Panel (a) illustrates the PDF of black carbon column density metrics—BC mass, total mass, and  number—highlighting the variability in between Xuzhou and Dhaka.
Panel (b) presents the weighted climatology of these metrics, showcasing spatial trends and hotspots, including densely populated areas and key pollution sources, offering insights into the interplay of local and regional pollution sources in shaping aerosol distributions.

The detailed climatology underscores the interplay of contrasting local emissions, regional transport, and meteorological factors in shaping BC distribution across both the regions, offering critical insights into small under-examined sources  for effective pollution management.

Deciphering BC Spatio-temporal  Extremes and regional dynamics

With the developed high resolution products across a five year period, the study then aimed to explore spatio-temporal extreme variabilities  using data decomposition and pattern recognition approach. Two modes primary and secondary contributed to most of the variabilities which reveals significant insight into spatial and temporal patterns of the extreme of BC mass and total mass over both the regions.  In Xuzhou, the primary mode indicates high variability concentrated in areas with numerous biomass fuel and chemical plants, where coal and biofuel consumption fluctuates throughout the year. The secondary mode exhibits an east-west spatial polarity, suggesting a relationship with temperature gradients influenced by local topography. In Dhaka, distinct pockets of high variability are identified, particularly near peri-urban agricultural lands, and some near urban rivers, indicating that interactions between urbanization and rural land management practices maybe responsible for shaping these    variabilities.Furthermore, the differences in temporal occurrences of these variabilities suggest that different sources are influencing aerosol concentrations at different times.

The dynamics governing aerosol transport and dispersion are complex. The study finds that wind speed and direction significantly affect accumulation and dispersion patterns, with moderate to strong winds leading to both effects depending on their trajectory. This non-linear behavior challenges traditional assumptions about wind effects on air quality. Additionally, the absence of clear seasonal patterns in aerosol concentrations suggests that short-term meteorological conditions and high-frequency emission variations are more influential than seasonal cycles. This highlights the need for a nuanced understanding of regional air pollution dynamics, as local emissions interact intricately with meteorological factors to shape aerosol distributions in urban environments like Xuzhou and Dhaka. The findings emphasize the importance of considering both local sources and atmospheric conditions to effectively assess air quality.

Each panel shows the combined wind and divergence data for a specific day, illustrating how high wind speeds, despite similar directions, lead to diverse patterns of pollutant accumulation and dispersion across the urban area.

Key Takeaways:

  1. Synergistic Multi-Platform Methodology for BC Physio-Optical Characterization:
    This study showcased, a potential method of  integrating multi-platform data and robust theoretical constraint in developing  detailed and dynamic  microphysical, physical and optical  information on BC. The inclusion of UV wavebands significantly improved sensitivity to smaller BC cores, leading to better characterization of fresh emissions in urban and industrial regions like Xuzhou and Dhaka.

  2. High-Resolution BC Column Products with Improved Sensitivity:
    At a 5.5 × 3.5 km resolution, the study produced high-resolution BC column products that captured finer spatial details of BC variability. The analysis identified overlooked sources of BC, such as small industrial cities in Xuzhou and urban riverbanks and peri-urban regions at outskirt of major city in Dhaka.

  3. Quantifying and Interpreting the Extremes from pattern recognition:
    The use of EOF and PC analysis highlighted key variability drivers, such as local emissions, transboundary pollution, and meteorological influences. For example, EOF1 captured the dominant influence of primary emissions, while EOF2 revealed the episodic impact of long-range transport and secondary aerosol processes, providing a nuanced understanding of BC variability.
  4. Dual Nature of Wind in BC Transport :
    Divergence analysis revealed that strong winds can  play a dual role in transport, acting as both dispersive and accumulative forces depending on speed and direction.  This duality challenges traditional assumptions of high wind speed acting always acting as a dispersive agent, an oftened generalized wind effects. Additionally, the absence of clear seasonal patterns in BC dynamics over both Xuzhou and Dhaka further highlights the critical role of local meteorological and regional conditions and in shaping BC variability.

Future Research Avenues:

  • Expanding Remote Sensing Platforms and Waveband Information: To further enhance the accuracy and applicability of this methodology, future research should integrate additional remote sensing platforms, alongside expanded ground-based networks. Incorporating data from multiple platforms with diverse waveband capabilities will significantly improve the robustness of regional assumptions by providing a more comprehensive spatial and temporal coverage of aerosol properties. Moreover, the inclusion of additional waveband information will refine the Mie solutions by better constraining BC size distributions and mixing states. This would allow for more precise modeling across different environmental conditions. Enhanced observational consistency across platforms will also help address current data gaps and ensure that derived solutions are both spatially and temporally consistent, ultimately strengthening the reliability of high-resolution aerosol retrievals for regional and global applications.
  • Expanding aerosol composition Modeling: Incorporating additional aerosol components, such as secondary organic aerosols (SOA) or brown carbon (BrC), within the two-component MIE model framework would provide a more comprehensive understanding of urban aerosol composition. This could better account for the evolving optical properties of absorbing aerosols and improve the characterization of complex urban and industrial environments.

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Air Pollution and Air Quality
Physical Sciences > Earth and Environmental Sciences > Environmental Sciences > Pollution > Air Pollution and Air Quality
Atmospheric Chemistry
Physical Sciences > Earth and Environmental Sciences > Environmental Sciences > Environmental Chemistry > Atmospheric Chemistry
Remote Sensing/Photogrammetry
Physical Sciences > Earth and Environmental Sciences > Geography > Geographical Information System > Remote Sensing/Photogrammetry
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Physical Sciences > Earth and Environmental Sciences > Earth Sciences > Climate Sciences > Atmospheric Science > Atmospheric Optics

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