Newswise — Global Navigation Satellite Systems (GNSS) transmit extremely weak signals that are vulnerable to interference and intentional jamming. Flex power technology allows ground controllers to redistribute signal energy, strengthening specific transmissions without increasing total satellite power. While this improves anti-interference capability, it also alters signal characteristics and introduces unexpected errors into high-precision positioning processes. Variations in signal strength can affect parameters such as code bias, satellite clock offset, and ionospheric corrections, potentially degrading positioning accuracy. Existing detection approaches remain limited, especially for the rapidly evolving BDS, and conventional processing models struggle to adapt to dynamic signal behavior. Based on these challenges, in-depth research is needed to understand and mitigate the impacts of flex power on satellite navigation performance.

Researchers from Space Engineering University, the Beijing Institute of Tracking and Telecommunications Technology, the Shanghai Astronomical Observatory of the Chinese Academy of Sciences, Henan Polytechnic University, Shandong University of Science and Technology, and Wuhan University reported the findings (DOI: 10.1186/s43020-026-00190-3) in Satellite Navigation (2026) a comprehensive investigation into flex power operations in the GPS and the BDS. The study analyzed operational modes, developed a new detection method combining signal-to-noise measurements with hardware delay indicators, and evaluated impacts across positioning algorithms. Published in 2026, the work presents an integrated framework designed to maintain resilient PNT services under dynamically changing satellite signal conditions.

The team first examined how flex power redistributes signal energy across satellite channels. Unlike normal operations, flex power produces step-like variations in carrier-to-noise ratios, creating detectable signatures in observation data. Building on this insight, researchers proposed a dual-indicator detection approach combining carrier-to-noise density (C/N₀) measurements with hardware delay variations. This method significantly reduces false alarms while enabling accurate detection across both GPS and BDS.

The study then evaluated how flex power influences multiple components of high-precision navigation. Results showed that GPS signals remain relatively stable, whereas BDS satellites exhibit stronger sensitivity, with noticeable changes in code bias and observation consistency. To address these disruptions, the researchers introduced “resilient” estimation strategies that dynamically adjust processing models in response to flex power events.

New algorithms were developed for code bias correction, satellite clock offset estimation, and phase bias modeling, allowing navigation systems to switch seamlessly between normal and flex-power states. The framework also improves ionospheric modeling accuracy by compensating for signal fluctuations that traditional models treat as constant. Validation experiments demonstrated improved continuity and stability in Precise Point Positioning (PPP), confirming that navigation accuracy can be preserved even during active signal power redistribution.

According to the researchers, resilient positioning is becoming essential as satellite systems adopt more adaptive signal strategies. Flex power enhances anti-jamming capability but fundamentally changes signal behavior, meaning traditional static models are no longer sufficient. The team emphasized that detecting flex power in real time and adapting processing algorithms accordingly represents a key step toward next-generation integrated PNT systems. By linking signal monitoring with adaptive estimation, the approach ensures that navigation services remain reliable for both civilian and scientific users operating in challenging electromagnetic environments.

The proposed framework has broad implications for aviation navigation, autonomous transportation, disaster monitoring, and precision timing infrastructure. As GNSS systems increasingly employ adaptive transmission strategies to counter interference, resilient processing methods will be critical for maintaining uninterrupted services. The study’s detection and correction strategies could be integrated into global monitoring networks and next-generation GNSS receivers, improving robustness without requiring hardware changes. Beyond GPS and BDS, the methodology may also support future multi-constellation navigation systems, contributing to more secure and dependable global positioning services. Ultimately, the work advances the transition from static navigation models toward adaptive, interference-resilient satellite navigation architectures.

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References

DOI

10.1186/s43020-026-00190-3

Original Source URL

https://doi.org/10.1186/s43020-026-00190-3

Funding information

This research was funded by Scientific Research Key Laboratory Fund (Grant No. SYS-ZX02-2024-01).

About Satellite Navigation

Satellite Navigation (E-ISSN: 2662-1363; ISSN: 2662-9291) is the official journal of Aerospace Information Research Institute, Chinese Academy of Sciences. The journal aims to report innovative ideas, new results or progress on the theoretical techniques and applications of satellite navigation. The journal welcomes original articles, reviews and commentaries.

Newswise — As the global demand for electric vehicles and portable electronics surges, high-energy-density and inherently safe energy storage systems has become more important than ever. However, while solid-state lithium batteries (SSLBs) offer high safety due to their non-flammability, traditional solid electrolytes face significant bottlenecks, including low ionic conductivity, poor interfacial contact, and mechanical brittleness.

In a review published in Supramolecular Materials, a team of researchers from China highlight a new approach: using supramolecular chemistry to engineer “smart” battery components. The study provides a molecular engineering foundation for realizing practical, high-efficiency, and safe next-generation batteries.

“Unlike traditional materials that rely on rigid covalent bonds, supramolecular materials utilize reversible non-covalent interactions such as hydrogen bonding, halogen bonding, and π-π stacking to create highly ordered, self-assembled structures,” explains senior and corresponding author Kai Liu.

Notably, supramolecular chemistry provides a programmable molecular-level design framework for solid-state batteries. “These dynamic interactions act as a ‘smart glue,’ allowing electrolytes to self-heal microcracks and adapt to the volume changes of electrodes during cycling,” adds Liu. “This flexibility is crucial for suppressing lithium dendrite growth, which often leads to short circuits in conventional designs.”

The researchers also detailed how these molecular interactions build efficient ion transport pathways, lowering energy barriers and improving the battery’s rate performance. “By precisely regulating the interfacial composition, supramolecular strategies significantly reduce impedance and enhance long-term cycling stability,” says Liu.

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References

DOI

10.1016/j.supmat.2025.100118

Original Source URL

https://doi.org/10.1016/j.supmat.2025.100118

Funding Information

This research was supported by the Tsinghua University-China Petrochemical Corporation Joint Institute for Green Chemical Engineering (224247) and the Tsinghua-Toyota Joint Research Fund.

About Supramolecular Materials

Supramolecular Materials is a publication of peer-reviewed research. It covers all aspects of these materials, which are based on supramolecular interactions or self-assembly.

Newswise — As global demand for clothing continues to rise, the textile and apparel industry has become a significant contributor to climate change. In China, the world’s largest textile producer and exporter, rapid urbanization, income growth, and shifting consumption patterns have driven a surge in apparel demand. Traditional studies often focus on factory-level energy use, overlooking emissions embedded in supply chains, exports, and household consumption. This fragmented perspective limits the effectiveness of mitigation strategies. Moreover, fast fashion and short garment lifespans exacerbate resource use and waste. Based on these challenges, there is an urgent need to conduct in-depth research that captures the full carbon footprint of the textile industry and identifies scalable pathways for emission reduction.

Researchers from Nanjing University, in collaboration with international partners, reported (DOI: 10.1007/s11783-026-2109-9) on January 9, 2026, in Engineering Environment a comprehensive analysis of carbon emissions in China’s textile and apparel industry. Using national household consumption data and supply-chain input–output modeling, the team examined emission trends from 2000 to 2018 and projected future mitigation scenarios through 2035. Their study reveals how production, consumption, and exports jointly shape the sector’s carbon footprint and highlights practical strategies—particularly renewable energy and clothing recycling—to curb emissions while supporting sustainable industrial development.

The analysis shows that demand-side forces dominate carbon emissions in China’s textile industry. Household consumption and exports together account for roughly 85% of total emissions growth, far outweighing the contribution from direct energy use in factories. Urban households, in particular, generate more than four times the carbon emissions of rural households due to higher clothing consumption, underscoring the climate impact of lifestyle changes.

By constructing detailed carbon flow diagrams, the study identifies wet processing, electricity use, and long, fragmented supply chains as major emission hotspots. While electrification has reduced emissions from fossil fuels, carbon embodied in upstream sectors—such as chemicals, transportation, and logistics—continues to rise.

To explore mitigation pathways, the researchers modeled five future scenarios. Energy-saving technologies alone delivered limited reductions, while large-scale renewable energy adoption significantly lowered emissions by reducing carbon intensity across the entire supply chain. Clothing recycling emerged as another powerful lever, as extending garment lifespans directly reduces the need for new production. Most notably, a combined strategy integrating renewable energy and recycling could reduce total emissions by nearly 10% compared with a business-as-usual trajectory, effectively flattening long-term emission growth.

“This study shows that decarbonizing the textile industry is not just a technological challenge, but also a consumption challenge,” said the study’s corresponding author. “Focusing only on factories misses the bigger picture. Our results demonstrate that household demand, urban lifestyles, and export-oriented production play decisive roles in driving emissions. By aligning clean energy transitions with circular economy strategies—especially clothing recycling—we can achieve meaningful emission reductions without sacrificing economic vitality. These insights provide a scientific foundation for designing more effective and balanced climate policies.”

The findings have important implications for policymakers, industry leaders, and consumers. For governments, the study highlights the need to integrate demand-side measures—such as promoting clothing reuse and recycling—into climate strategies for the textile sector. For industry, it underscores the value of transitioning to renewable energy while redesigning supply chains to be shorter and more efficient. For consumers, the research quantifies how everyday clothing choices contribute to carbon emissions, reinforcing the climate benefits of longer garment lifespans. Together, these pathways suggest that a shift toward greener production and more responsible consumption can transform textiles from a climate liability into a key contributor to a low-carbon future.

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References

DOI

10.1007/s11783-026-2109-9

Original Source URL

https://doi.org/10.1007/s11783-026-2109-9

Funding information

The study was financially supported by the National Natural Science Foundation of China (Nos. 72304136, 72234003, and 72488101).

About Engineering Environment

Engineering Environment is the leading edge forum for peer-reviewed original submissions in English on all main branches of environmental disciplines. FESE welcomes original research papers, review articles, short communications, and views & comments. All the papers will be published within 6 months after they are submitted. The Editors-in-Chief are Academician Jiuhui Qu from Tsinghua University, and Prof. John C. Crittenden from Georgia Institute of Technology, USA. The journal has been indexed by almost all the authoritative databases such as SCI, EI, INSPEC, SCOPUS, CSCD, etc.

Newswise — As renewable energy deployment accelerates worldwide, large-scale energy storage technologies must become more affordable, safer, and resource-efficient. Sodium-ion batteries stand out because sodium is abundant and inexpensive, yet their commercialization is hindered by the lack of high-performance anode materials. Hard carbon is widely regarded as the most promising anode candidate, but its performance strongly depends on poorly controlled internal pores and defect structures. Excessive open pores often trigger electrolyte decomposition, unstable interfacial layers, and severe initial capacity loss. Based on these challenges, it is necessary to conduct in-depth research on how molecular-level precursor design and interfacial regulation can jointly enhance hard carbon anodes.

Researchers from Jiangxi Normal University and Gannan Normal University report a new strategy to stabilize hard carbon anodes for sodium-ion batteries, published (DOI: 10.1007/s10118-025-3461-0) online on November 19, 2025, in Chinese Journal of Polymer Science. The study introduces intramolecular heteroatom doping within polymer precursors, followed by controlled chemical presodiation, to engineer closed-pore structures and robust interfacial layers. This synergistic design significantly improves reversible capacity, initial Coulombic efficiency, and long-term cycling stability, addressing key bottlenecks that have constrained sodium-ion battery development.

The research begins by designing polymer precursors with specific functional groups—such as sulfonyl, ether, and carbonyl units—embedded directly within aromatic backbones. During carbonization, these intramolecular dopants decompose in a controlled manner, generating abundant closed nanopores while avoiding excessive surface area. Structural analyses, including X-ray diffraction, Raman spectroscopy, and small-angle X-ray scattering, reveal that the optimized hard carbon contains a high volume of closed pores that favor low-voltage sodium storage.

Electrochemical tests demonstrate that the optimized material delivers a reversible capacity of 307.9 mAh g⁻¹, with strong rate capability and minimal structural degradation. However, the researchers identified that irreversible sodium loss during initial cycling still limited practical efficiency. To address this, a brief chemical presodiation step was introduced, supplying sodium in advance and pre-forming a stable interfacial layer. As a result, the initial Coulombic efficiency increased dramatically to 94.4%.

Long-term tests further show that the presodiated hard carbon retains 93.6% of its capacity after 3,000 charge–discharge cycles. Microscopic and spectroscopic analyses confirm the formation of a thin, dense, and sodium-fluoride-rich interphase, which enhances ion transport while suppressing electrolyte decomposition.

“This work shows that the performance limits of hard carbon are not fixed but can be fundamentally reshaped through molecular design,” said one of the study’s corresponding authors. “By controlling how heteroatoms are incorporated within polymer precursors, we can regulate pore formation from the inside out. When combined with presodiation, this strategy not only boosts efficiency but also stabilizes the electrode–electrolyte interface over thousands of cycles. The results suggest a scalable and versatile route for building next-generation sodium-ion battery anodes.”

The findings offer important implications for the future of large-scale energy storage, particularly in grid applications where cost, safety, and durability are critical. The molecular-level engineering strategy demonstrated in this study can be extended to other polymer-derived carbons and potentially adapted for potassium-ion or multivalent battery systems. By simultaneously improving capacity, efficiency, and lifespan, the approach brings sodium-ion batteries closer to commercial viability. More broadly, the work highlights how precursor chemistry and interfacial control can be integrated to overcome long-standing materials challenges in electrochemical energy storage.

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References

DOI

10.1007/s10118-025-3461-0

Original Source URL

https://doi.org/10.1007/s10118-025-3461-0

Funding information

This work was financially supported by the Ministry of Industry and Information Technology of China, the National Natural Science Foundation of China (No. 52403263), Technology Research Project of Jiangxi Provincial Department of Education (No. GJJ2200385), and Jiangxi Provincial Natural Science Foundation (Nos. 20244BCE52213, 20242BAB23031 and 20232BAB204006).

About Chinese Journal of Polymer Science

Chinese Journal of Polymer Science is a monthly journal published in English and sponsored by the Chinese Chemical Society and the Institute of Chemistry, Chinese Academy of Sciences. CJPS is edited by a distinguished Editorial Board headed by Professor Qi-Feng Zhou and supported by an International Advisory Board in which many famous active polymer scientists all over the world are included. Manuscript types include Editorials, Rapid Communications, Perspectives, Tutorials, Feature Articles, Reviews and Research Articles. According to the Journal Citation Reports, 2024 Impact Factor (IF) of CJPS is 4.0.

Newswise — Agricultural pest management has traditionally relied on chemical insecticides, but their overuse has led to environmental contamination, health risks, and rapidly evolving pesticide resistance. Meanwhile, natural variation in pest resistance exists within crops and their wild relatives, offering valuable resources for breeding. However, resistance traits are difficult to measure accurately, as they are often scored visually using coarse categories that fail to capture continuous variation. This limits the effectiveness of genome-wide association studies and genomic selection. Advances in deep learning provide new opportunities to extract detailed phenotypic information directly from images, overcoming subjectivity and labor constraints. Based on these challenges, there is a pressing need to conduct in-depth research on AI-enabled phenotyping and genomic breeding for pest resistance.

Researchers from the Chinese Academy of Agricultural Sciences and collaborating institutions report (DOI: 10.1093/hr/uhaf128) on 7 May 2025 in Horticulture Research that deep learning can substantially improve genomic selection for pest-resistant grapevine. The team developed convolutional neural networks to automatically assess insect damage on grape leaves and combined these data with genome resequencing, genome-wide association studies, and transcriptomic analyses. By linking AI-derived phenotypes with genetic markers, the study identifies key resistance genes and demonstrates highly accurate machine-learning-based prediction of pest resistance, offering a new framework for precision breeding.

The study analyzed 231 grapevine accessions subjected to natural infestations of the tobacco cutworm, a major leaf-feeding pest. Deep convolutional neural networks were trained to classify pest damage as mild or severe, achieving over 95% accuracy, while a custom regression model generated continuous damage scores strongly correlated with human assessments. These AI-derived phenotypes enabled more precise genetic analyses than traditional categorical scoring. Genome-wide association studies identified 69 quantitative trait loci and 139 candidate genes linked to pest resistance, many involved in jasmonic acid, salicylic acid, ethylene, and calcium-mediated signaling pathways. By integrating transcriptomic data, the researchers pinpointed key defense genes, including calcium-transporting ATPase ACA12 and the protein kinase CRK3, both strongly induced during herbivore attack. Machine-learning-based genomic selection models further demonstrated high predictive power, reaching 95.7% accuracy for binary traits and strong correlations for continuous traits. Together, these results show that combining deep learning phenotyping with genomics reveals subtle resistance mechanisms and enables reliable prediction of complex, polygenic pest-resistance traits.

“This work highlights how artificial intelligence can fundamentally change plant breeding,” said the study’s senior authors. “By replacing subjective visual scoring with fast, objective deep-learning-based phenotyping, we can capture continuous variation in pest damage that was previously overlooked. When these high-quality phenotypes are integrated with genomics and transcriptomics, they reveal the true polygenic architecture of pest resistance. This approach not only improves prediction accuracy, but also allows breeders to make informed selections much earlier in the breeding cycle.”

The findings have broad implications for sustainable agriculture and crop improvement. AI-driven phenomics enables rapid, large-scale assessment of pest resistance without increasing labor costs, making it suitable for breeding programs worldwide. By identifying resistance genes and accurately predicting pest tolerance, breeders can reduce reliance on chemical pesticides while improving crop resilience. The framework established in grapevine can be readily adapted to other crops and stress traits, supporting the development of automated, data-driven breeding platforms. Ultimately, integrating deep learning, genomics, and machine learning could accelerate the creation of pest-resistant varieties essential for food security under increasing environmental pressure.

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References

DOI

10.1093/hr/uhaf128

Original Source URL

https://doi.org/10.1093/hr/uhaf128

Funding information

This work was supported by the National Key Research and Development Program of China (No. 2023YFD2200702), the project of National Key Laboratory for Tropical Crop Breeding (No. NKLTCB202325), the National Natural Science Foundation of China (No. 32372662), and the Science Fund Program for Distinguished Young Scholars of the National Natural Science Foundation of China (Overseas) to Yongfeng Zhou.

About Horticulture Research

Horticulture Research is an open access journal of Nanjing Agricultural University and ranked number one in the Horticulture category of the Journal Citation Reports ™ from Clarivate, 2023. The journal is committed to publishing original research articles, reviews, perspectives, comments, correspondence articles and letters to the editor related to all major horticultural plants and disciplines, including biotechnology, breeding, cellular and molecular biology, evolution, genetics, inter-species interactions, physiology, and the origination and domestication of crops.

Newswise — With the global shift toward renewable energy, solid oxide–based electrochemical devices have become essential for hydrogen production, energy storage, and fuel-to-electricity conversion. Traditional oxygen-ion–conducting cells require high operating temperatures, creating cost, durability, and material compatibility challenges. Protonic ceramic cells (PCCs) offer an alternative, operating efficiently at 300–600 °C and allowing the use of cheaper components, improved thermal cycling, and enhanced stability. Despite rapid progress in materials engineering, the fundamental mechanisms governing hydration, proton conduction, and electrode reactions remain insufficiently understood. These gaps hinder rational catalyst design and slow the translation of new materials into practical PCC devices. Based on these challenges, there is a critical need to deeply investigate proton behavior, interfacial chemistry, and catalytic mechanisms.

Researchers from Idaho National Laboratory and collaborating universities published (DOI: 10.1016/j.esci.2025.100437) a comprehensive review on August 2025, in eScience, detailing how diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) is transforming protonic ceramic cell research. The article summarizes recent breakthroughs in applying DRIFTS to oxygen electrodes, proton-conducting electrolytes, and hydrogen electrodes under realistic operating conditions. By capturing surface intermediates and hydration signatures, the review highlights DRIFTS as an essential technique for understanding reaction pathways, improving proton uptake, and guiding next-generation materials design for high-performance PCC systems. This platform was recently reported in a research article by the same group in Energy Environmental Science, providing the substantial evidence on how it is powerful in electrochemical system at elevated temperatures, specifically for PCC.

The review outlines how DRIFTS enables direct observation of surface species and dynamic reactions across PCC components. For oxygen electrodes, DRIFTS detects hydroxyl stretching bands associated with proton uptake, providing insights into triple-conducting materials such as PrNi₀.₅Co₀.₅O₃–δ, PrBaCo₂O₅+δ, and high-entropy perovskites. Doping-induced enhancements—such as Zn-stabilized hydration sites or Cs-driven oxygen vacancy formation—are revealed through stronger –OH peaks and temperature-dependent hydration behavior. DRIFTS also verifies steam-induced structural transformations, including monoclinic-to-cubic transitions and the emergence of multi-phase composites that improve catalytic performance.

For protonic electrolytes, DRIFTS distinguishes Zr–OH–Zr and Zr–OH–X environments, enabling researchers to identify proton trapping, dehydration kinetics, and dopant-dependent hydrogen-bonding effects in materials like Sc- and Y-doped BaZrO₃. The technique further detects carbonate residues that impair sintering, guiding optimized fabrication routes.

In catalytic applications, DRIFTS captures intermediates during CO₂ hydrogenation, methane reforming, and chemical-fuel co-conversion, identifying formates, carbonates, and CO adsorption species crucial to mechanistic understanding. Emerging operando DRIFTS configurations with applied voltage demonstrate the movement of surface protons during real electrochemical reactions, validating proton migration and reaction coupling at electrode interfaces. Collectively, the review shows how DRIFTS bridges fundamental chemistry with practical PCC engineering.

According to the authors, DRIFTS provides a uniquely powerful lens for understanding how PCC materials behave under realistic conditions. They emphasize that the ability to monitor hydration, proton uptake, and catalytic intermediates in real time offers insights unavailable from traditional characterization tools. The authors note that integrating DRIFTS with complementary methods—such as synchrotron-based IR, X-ray spectroscopy, and computational modeling—will further expand its impact. They conclude that establishing operando DRIFTS systems capable of applying electrical load represents a critical next step for unraveling the complex, surface-driven processes that dictate PCC performance.

The review underscores that advancing DRIFTS techniques will accelerate the rational design of PCC materials for clean-energy technologies. Improved understanding of hydration behavior and proton migration can guide the development of durable oxygen electrodes, CO₂-tolerant electrolytes, and carbon-resistant hydrogen electrodes. Insights into reaction intermediates also support catalyst optimization for hydrogen production, CO₂ reduction, methane reforming, and value-added chemical synthesis. As energy systems evolve toward efficiency and sustainability, DRIFTS-enabled mechanistic knowledge will help bridge laboratory discoveries and scalable PCC devices. Ultimately, the authors note that expanding operando DRIFTS capabilities will be essential for building the next generation of robust, high-performance ceramic energy systems.

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References

DOI

10.1016/j.esci.2025.100437

Original Source URL

https://doi.org/10.1016/j.esci.2025.100437

Funding information

This work is supported by the HydroGEN Advanced Water Splitting Materials Consortium, established as part of the Energy Materials Network under the U.S. Department of Energy (USDOE); the Office of Energy Efficiency and Renewable Energy (EERE); and the Hydrogen and Fuel Cell Technologies Office (HFTO), under DOE Idaho Operations Office, under contract no. DE-AC07-05ID14517.

About eScience

eScience – a Diamond Open Access journal cooperated with KeAi and published online at ScienceDirect. eScience is founded by Nankai University (China) in 2021 and aims to publish high quality academic papers on the latest and finest scientific and technological research in interdisciplinary fields related to energy, electrochemistry, electronics, and environment. eScience provides insights, innovation and imagination for these fields by built consecutive discovery and invention. Now eScience has been indexed by SCIE, CAS, Scopus and DOAJ. Its impact factor is 36.6, which is ranked first in the field of electrochemistry.

Newswise — Ground-level ozone is a major air pollutant that threatens human health, ecosystems, and climate stability. Despite aggressive reductions in nitrogen oxides and primary volatile organic compounds, ozone levels continue to exceed air quality standards in many regions. This paradox reflects the complex and nonlinear nature of atmospheric photochemistry, where reactive radicals control ozone formation. Oxygenated volatile organic compounds (OVOCs) are key intermediates in this process, acting as both sources and sinks of radicals. However, most previous studies have measured only a small subset of OVOCs, leaving major uncertainties in radical budgets. Based on these challenges, there is a critical need to systematically investigate how a broader spectrum of OVOCs drives radical cycling and ozone formation.

In a study published (DOI: 10.1016/j.ese.2026.100659) in January 2026 in Environmental Science and Ecotechnology, researchers from the Southern University of Science and Technology, The Hong Kong Polytechnic University, Hong Kong Baptist University, Beijing University of Chemical Technology, and the University of Helsinki investigated how oxygenated volatile organic compounds shape atmospheric chemistry in background air over southern China. Combining intensive field observations with photochemical box modeling, the team examined the role of OVOCs in radical cycling and ozone formation. Their results show that commonly used models relying on limited OVOC measurements substantially misrepresent radical budgets and ozone production under real atmospheric conditions.

The study combined high-resolution field measurements with a detailed photochemical box model to quantify the role of OVOCs in atmospheric radical chemistry. When models were constrained using only three commonly measured OVOCs, simulated hydroxyl radical levels were overestimated by up to 100 percent. By contrast, including measurements of 23 OVOCs brought simulations into close agreement with observations.

The analysis revealed that OVOC photolysis contributed approximately 49–61 percent of total radical production, making it the dominant radical source in background air. Surprisingly, several OVOCs present at relatively low concentrations accounted for a disproportionate share of radical generation. Errors in simulating these compounds caused cascading biases in radical budgets, altering ozone formation pathways.

The study further showed that traditional chemical mechanisms systematically overestimate some OVOCs while underestimating others, masking offsetting errors that appear acceptable when only limited measurements are used. These hidden inaccuracies significantly affect predictions of ozone production rates and sensitivity regimes. Overall, the findings demonstrate that a narrow observational focus can lead to misleading conclusions about the drivers of ozone pollution.

“This work shows that what we don’t measure can matter more than what we do,” said one of the study’s senior authors. “OVOCs have often been treated as secondary products, but our results demonstrate that they are central to controlling radical chemistry and ozone formation. Without comprehensive OVOC observations, models may appear accurate while fundamentally misrepresenting atmospheric processes. Expanding OVOC measurements is therefore essential for designing effective air quality management strategies in regions struggling with persistent ozone pollution.”

These findings have important implications for air pollution control and atmospheric modeling worldwide. Strategies focused solely on reducing traditional ozone precursors may fail if OVOC-driven radical chemistry is ignored. Incorporating comprehensive OVOC measurements can improve model accuracy, guide emission control priorities, and help policymakers identify more effective mitigation pathways. The study also highlights the need to update chemical mechanisms and expand monitoring networks to include reactive OVOC intermediates. Ultimately, recognizing the hidden role of OVOCs may be key to resolving the long-standing challenge of persistent surface ozone pollution in both developing and industrialized regions.

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References

DOI

10.1016/j.ese.2026.100659

Original Source URL

https://doi.org/10.1016/j.ese.2026.100659

Funding information

This research was funded by the Hong Kong Research Grants Council via Theme-Based Research Scheme (T24-504/17-N) and General Research Fund (HKBU 15219621), the National Natural Science Foundation of China (42325504), the National Key Research and Development Program of China (2023YFC3706205), and the Shenzhen Science and Technology Program (JCYJ20220818100611024).

About Environmental Science and Ecotechnology

Environmental Science and Ecotechnology (ISSN 2666-4984) is an international, peer-reviewed, and open-access journal published by Elsevier. The journal publishes significant views and research across the full spectrum of ecology and environmental sciences, such as climate change, sustainability, biodiversity conservation, environment & health, green catalysis/processing for pollution control, and AI-driven environmental engineering. The latest impact factor of ESE is 14.3, according to the Journal Citation Reports^TM 2024.