Editorial: Dust and polluted aerosols: sources, transport and radiative effects volume II

Editorial on the Research Topic
Dust and polluted aerosols: sources, transport and radiative effects volume II

Dust and polluted aerosols exert profound influences on the Earth’s atmosphere, hydrological cycles, ecosystems, and human health. They influence natural and anthropogenic processes through complex interactions from arid source regions to distant downwind areas. This second Research Topic, Dust and Polluted Aerosols: Sources, Transport and Radiative Effects II, explore the dynamic processes connecting aerosol emission, transport, and radiative feedbacks across multiple spatial and temporal scales.

Recent years have witnessed rapid advances in Earth observation systems, numerical modeling, and data assimilation techniques. Yet, substantial uncertainties remain regarding the sources, evolution, and radiative impacts of mineral dust and polluted aerosols. This Research Topic therefore aims to integrate observational, numerical, and data-driven approaches to better characterize aerosol dynamics and their climatic and environmental consequences. The four studies published in this Research Topic reflect this diversity of methodologies—from vertical field observation and global atmospheric modeling to deep-learning prediction frameworks—and together illuminate how dust and polluted aerosols shape both regional environments and the global atmosphere.

At the planetary boundary layer (PBL), Bao et al. examined the PBL dynamics of a severe sandstorm over Inner Mongolia, China, using multi-source vertical observations including wind-profile radar and lidar. Their analysis reveals that downward momentum transfer and the intrusion of cold advection are key triggers for explosive dust lifting. By introducing the frontogenesis function as a diagnostic for atmospheric thermodynamic structure, the study offers a new tool to assess sandstorm intensity and predictability. The lidar-derived extinction coefficient and depolarization ratio further document enhanced turbulence and dust mixing within the PBL, underscoring the importance of vertical coupling between the surface and free atmosphere. This work deepens our process-level understanding of dust outbreak mechanisms and supports the development of early-warning and mitigation strategies for severe sandstorms.

Complementing physically based air-quality models, Qin et al. present SFDformer, a Sparse Frequency Decomposition Transformer designed for PM_2.5 time-series forecasting. SFDformer couples a time-series pooling decomposition module, which separates trend and seasonal components, with a Fourier-based sparse attention mechanism that operates in the frequency domain to suppress noise and focus on the most informative frequency bands. Across eight multi-pollutant and meteorology-driven datasets from Chinese cities, the model consistently outperforms a range of state-of-the-art deep learning baselines, including Transformer, Informer and Autoformer, in both multivariate and univariate settings, while also improving computational efficiency. By jointly exploiting temporal and spectral structure in air-pollution records, SFDformer illustrates how next-generation data-driven architectures can deliver more accurate and scalable PM_2.5 forecasts for operational air-quality management.

To evaluate global anthropogenic forcing and climatic feedbacks, Han quantifies the long-term impacts of transportation emissions on PM_2.5, ozone, and associated radiative forcing from 1990 to 2019, using the global GEOS-Chem chemical-transport model. The results reveal a striking 18% and 19% global increase in transportation-induced PM_2.5 and ozone, respectively, leading to a 105% rise in associated premature mortality—dominated by China and South Asia. Interestingly, radiative forcing of PM2.5 shows opposite trends between developed and developing regions, whereas ozone forcing increases almost globally. Under future low-emission scenarios (SSP1-1.9), transportation-related mortality could decline by two-thirds by mid-century, highlighting the climate and health co-benefits of clean-transport policies. This study exemplifies how emission inventories, atmospheric chemistry, and climate feedbacks must be examined jointly to evaluate the evolving role of anthropogenic aerosols in the Earth system.

Besides atmospheric aerosols, Ma et al. conduct a numerical investigation of the atmospheric dispersion of radioactive materials under varying meteorological conditions. Using the Weather Research and Forecasting (WRF) model coupled with mesoscale transport simulations, the authors show how seasonal circulation patterns, terrain effects, and data assimilation collectively determine the dispersion and deposition of airborne contaminants. Although focused on nuclear-accident scenarios, the study highlights universal transport dynamics applicable to dust and polluted aerosols—namely, that accurate meteorological representation and dynamic data assimilation are essential for predicting the long-range spread of atmospheric pollutants. Their findings strengthen the linkage between environmental safety assessments and atmospheric process modeling, a connection increasingly relevant to both air-quality management and national emergency preparedness.

These studies reaffirm that understanding dust and polluted aerosols requires a cross-disciplinary perspective linking atmospheric physics, environmental chemistry, numerical modeling, and data science. As Earth observation networks expand and Earth-system models evolve toward higher resolution and complexity, the integration of physical realism with data-driven intelligence will be crucial for advancing predictive capability.

Looking forward, future research should prioritize multiscale model coupling—from boundary-layer dynamics to global circulation—and more integrated assessments of the climatic, ecological, and public-health impacts of polluted and dust aerosols. Moreover, particular attention should be devoted to the role of dust-associated chemical constituents in modulating atmospheric radiation and cloud microphysical processes, and consequently influencing climate change.

The editors gratefully acknowledge all authors, reviewers, and collaborators who contributed to this Research Topic. Their efforts enrich the understanding of aerosol sources, transport, and radiative effects, helping to address the pressing environmental and climatic challenges of our time.

Author contributions

RM: Writing – original draft, Writing – review and editing. ZH: Writing – review and editing. SC: Writing – review and editing. TF: Writing – review and editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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