Emerging Technologies for Observation of Air Pollution (3rd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 22 February 2027 | Viewed by 382

Editors


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Urban Environment and Industry Department, NILU–Norwegian Institution for Air Research, 2027 Kjeller, Norway
Interests: environmental monitoring; urban sustainability; citizen science; low-cost sensor technology; co-creation; urban living labs; transdisciplinary research
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Sustainability Engineering Laboratory, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Interests: air quality; atmospheric pollution modelling; urban meteorology; data assimilation; numerical methods
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Special Issue Information

Dear Colleagues,

This Special Issue is the third volume in a series of publications dedicated to “Emerging Technologies for Observation of Air Pollution” (1st Edition; 2nd Edition).

The problem of poor air quality still influences inhabitant’s life in all cities of the globe. During growing urbanization scientific research shows origin of air pollution from local scales and from regional and global scales including interactions with climate protection measures. Additionally, the public awareness is growing to improve management and assessment strategies and effective control policies for reducing the health impact of air pollution.

The focus of this Special Issue is on new research contributions on developments in observation techniques and data operation algorithms which enable personal air pollution exposure determination, as well as new conclusions about sources of air pollutants and emission reduction measures. New research results about spatially complete information on air pollutants, about urban air quality observations by smart air quality networks, as well as corresponding near-real time numerical simulations at the small scale are ideal contributions to this Special Issue.

We can offer substantial discounts for high-quality papers.

Prof. Dr. Klaus Schäfer
Dr. Nuria Castell
Dr. Georgios Tsegas
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • atmospheric observations
  • urban air quality
  • sensors and measurements
  • crowd sourcing
  • numerical simulations and modeling

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Published Papers (1 paper)

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Research

20 pages, 1633 KB  
Article
Atmospheric Regimes Create Structural Uncertainty in Offshore Methane Emission Estimates
by Stuart N. Riddick
Atmosphere 2026, 17(8), 720; https://doi.org/10.3390/atmos17080720 - 24 Jul 2026
Viewed by 212
Abstract
Offshore methane emissions are increasingly quantified using a range of observational approaches, yet reported estimates often show substantial variability between methods. This study examines whether disagreement can arise from atmospheric transport processes alone by investigating how the marine boundary layer influences the relationship [...] Read more.
Offshore methane emissions are increasingly quantified using a range of observational approaches, yet reported estimates often show substantial variability between methods. This study examines whether disagreement can arise from atmospheric transport processes alone by investigating how the marine boundary layer influences the relationship between measured concentrations and inferred emission rates. An idealised dispersion framework was used to compare three commonly applied approaches, Gaussian plume inversion, aircraft mass balance, and satellite-based methods, across representative offshore atmospheric regimes. By holding emissions constant and varying only atmospheric structure, the framework isolates the influence of transport processes on inferred emissions. The results show that each method exhibits regime-dependent bias arising from different physical mechanisms. Gaussian methods are highly sensitive to plume alignment and may fail under lateral displacement. Aircraft mass balance remains robust when the plume is fully sampled but becomes unreliable when the sampling volume does not intercept the plume. Satellite methods consistently detect the plume but exhibit systematic bias when plume transport is decoupled from assumed wind speeds. These results demonstrate that disagreement between offshore methane emission estimates can arise solely from changes in atmospheric regime under the conditions represented by the model. Under conditions where standard transport assumptions are not satisfied, differences between estimates reflect the influence of atmospheric structure on plume behaviour and sampling, rather than measurement error alone. Emission estimates are therefore only reliable where the underlying transport assumptions are satisfied, and convergence between methods cannot be universally assumed under realistic offshore conditions. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution (3rd Edition))
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