Air Pollution

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8 papers in the last four weeks, up 167% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 36

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Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting
Sep 28, 2026Gary Myler, James Holmes, Manish Patel +1Atmospheric Dynamics Era5 Reanalysis Data
The Open University, UK.
Cheap, open agents make LLM pollution harder to mitigate
Sep 25, 2026Raluca Rilla, Anne-Marie Nussberger, Rui Mata +1Air Pollution
Center for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany · International Max Planck Research School on Learning, Institutions, and Future Evolution (LIFE), Berlin, Germany · University of Basel, Basel, Switzerland +2
High-resolution Nitrogen Dioxide Maps Reveal Exposure Limit Breaches across Europe
Sep 21, 2026Linus Scheibenreif, Konrad SchindlerAir Pollution Greenhouse Gas
Photogrammetry & Remote Sensing, ETH Zurich, Stefano-Franscini-Platz 5, Zurich, 8093, Switzerland.
Semi-automated reconstruction of indoor geometry from 360-degree video for CFD-based airflow analysis in classrooms
Sep 20, 2026Dhruv Gamdha, James Afful, Shambhavi Joshi +3Geometric Reconstruction Computational Fluid Dynamic
Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA · Department of Architecture, Iowa State University, Ames, IA 50011, USA
Personalized Federated Hierarchical Gaussian Processes for Privacy-Preserving Modeling of Heterogeneous Distributed Systems
Sep 16, 2026Xianjian Xie, Hao YanGaussian Process Distributed Optimization
Arizona State University
MambaMPD: A Mamba-Driven Segmentation Framework for Marine Pollution Detection from Remote Sensing Imagery
Sep 14, 2026Shuaiyu Chen, Wei Han, Peng Ren +2Remote Sensing Image Segmentation Feature Pyramid
Department of Computer Science, University of Exeter, Exeter, United Kingdom · School of Computer Science, China University of Geosciences, Wuhan, China · College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China
Semi-Supervised Learning under Spatially Biased Sampling
Sep 7, 2026Bright Wiredu Nuakoh, Francky Fouedjio, Stephen Bradshaw +4Semi-Supervised Learning Spatial Supervision
African Institute for Mathematical Sciences (AIMS), 17 KN 16 Ave, Kigali, Rwanda · Mathematical Application & Data Analytics Group, School of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia · Data & Analytics, Rio Tinto, 152-158 St Georges Terrace, Perth, WA 6000, Australia +2
Predicting Spatiotemporal Mobile Sensing-Based PM2.5 Concentrations Using Low-Rank Adapted Spatially Attentive Graph Neural Network
Sep 7, 2026Om Chiddarwar, Priyanka Mandal, Praveen Kumar Chandaliya +1Air Pollution Temporal Graph Neural Networks
IIITDM Kurnool, Kurnool, Andhra Pradesh 518002, India · Sardar Vallabhbhai National Institute of Technology Surat, Gujarat 394210, India
Integrating Traffic Noise Emission Modelling into Variable Speed Limit Control
Sep 1, 2026Jiawen Meng, John Pravin Arockiasamy, Alexey VinelStandard Traffic Speed Benchmarks Traffic
Institute AIFB, Karlsruhe Institute of Technology, Germany · School of Information Technology, Halmstad University, Sweden
Air Quality Station Simulation via LSTM and Attention-Based Modelling
Aug 12, 2026Alexander Kostadinov, Petar O. Hristov, Dessislava Petrova-AntonovaAir Pollution Cnn-Lstm
GATE Institute Sofia University “St Kliment Ohridski” 5 James Bourchier Blvd, 1164, Sofia
AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting
Aug 10, 2026Fan Yang, Nan Chen, Yijie Dong +2Air Pollution State Space Models
School of Software Technology, Zhejiang University Hangzhou, Zhejiang 310000, China
From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations
Jul 28, 2026Abhishek A. Sabnis, Mihai Mitrea, Lya Lugon +5Air Pollution Deterministic Reconstruction
CEREA, ENPC, Institut Polytechnique de Paris, Île-de-France, France. · Department of Computing, Imperial College London, London, UK. · Dynamic Systems Lab, University College London, London, UK. +1
Identifiability-Aware Source Apportionment in City-Scale Advection-Diffusion Systems
Jul 25, 2026Ankit Bhardwaj, Lakshminarayanan SubramanianAir Pollution Identifiability
Department of Computer Science, New York University
Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis
Jul 19, 2026Maede Azani Hassan Abadi, Shouyi WangAir Pollution Respiratory Sound Classification
Department of Industrial, Manufacturing, & Systems Engineering, The University of Texas at Arlington
Air Quality Downscaling with Station-Guided Pseudo-Supervision
Jul 6, 2026Guorun Wang, Simone Foti, Andreas D. Demou +5Air Pollution Dynamical Downscaling
Imperial College London, UK · The Cyprus Institute, Cyprus · Northeastern University London, UK +1
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution
Jul 6, 2026Saadeldine Eletter, Ruihong Zeng, Yuxia Wang +3Question-Answering Benchmarks Misinformation
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) · INSAIT, Sofia University St. Kliment Ohridski
Environmental Drivers of Respiratory Disease: A District Level Analysis
Jul 5, 2026Rahim Iqbal, Asfi Ahamed, Izzath Nisfer +6Air Pollution Respiratory Motion
Dept. of Computer Science & Engineering, University of Moratuwa, Sri Lanka.
Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications
Jun 23, 2026Arindam Sengupta, Paul Jeanney, Ricardo Vinuesa +2Tensor Decomposition Singular Value Decomposition
ETSI Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Plaza Cardenal Cisneros, 3, Madrid, 28040, Spain · Ove Arup, C. de Alfonso XI, 12, Retiro, Madrid, 28014, Spain · Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109, United States
Auto-Configured Explainable Graph Neural Networks for Multi-Site Pollution Prediction
Jun 23, 2026Abdelkader Dairi, Fouzi Harrou, Ying SunAir Pollution Graph Neural Networks
Department of Computer Science University of Science and Technology of Oran-Mohamed Boudiaf (USTO-MB) El Mnaouar, BP 1505, Bir El Djir 31000, Oran, Algeria · Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900, Saudi Arabia
MVG-KAN: Multi-View Geo-Wind Guided KAN for PM $_{2.5}$ Forecasting
Jun 23, 2026Cheng Huang, Muyao Guan, Jairus Yougui Railey +6Air Pollution Spatio-Temporal Forecasting
College of Artificial Intelligence, Taizhou University, Taizhou 318000, China · College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
Enhancing Graph Neural Networks Using Proximity Graphs for Dust Source Emission Forecasting
Jun 18, 2026Maryam Sanisales, Zahed Rahmati, Ali Darvishi Boloorani +1Graph Neural Networks Air Pollution
Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran · Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
AI for Social Good: An Investigation of the Causal Relationship Between Environmental Regulations and Their Effects on Air Pollution in London, UK
Jun 13, 2026Yang Han, Jacqueline CK Lam, Victor OK Li +1Air Pollution Causal
Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong
OmniPMNet: Bridging discrete and gridded PM10 forecasts via omni-query neural processes
Jun 12, 2026Shuangshuang He, Shuo WangAir Pollution Spatio-Temporal Forecasting
ColorfulClouds Technology Co., Ltd., 100875 Beijing, China. · School of Systems Science, Beijing Normal University, 100875 Beijing, China. · D-ITET, ETH Zurich, 8092 Zurich, Switzerland.
Learning to model pediatric asthma exacerbation from multiple risk factors: a case study in coastal Virginia
Jun 4, 2026Jonathan Colen, Eric Werner, Maryam Golbazi +6Air Pollution Generalized Linear Model
Joint Institute on Advanced Computing for Energy and Science, Old Dominion University, Suffolk, VA, 23535, U.S.A. · School of Data Science, Old Dominion University, Norfolk, VA, 23529, U.S.A. · Eastern Virginia Medical School, Macon & Joan Brock Virginia Health Sciences, Old Dominion University, Norfolk, VA, 23501, U.S.A. +5
AQIFormer: A Transformer-Based Multi-View Architecture for Cross-City Air Quality Classification
Jun 2, 2026Om Kathalkar, Nitin Nilesh, Sachin Chaudhari +1Air Pollution Detection Transformer
IIIT Hyderabad · India
Tracking Urban Atmospheric Pollutants using Sentinel-5P Satellite Data
May 21, 2026Alice Gomez-Cantos, Henry O. VelesacaAir Pollution Atmospheric Dynamics
Facultad de Ciencias Naturales y Matemáticas, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo, Km. 30.5 Vía Perimetral, Guayaquil, 090902, Ecuador · Software Engineering Department, Research Center for Information and Communication Technologies (CITIC-UGR), University of Granada, 18071, Granada, Spain
M $^2$ FedAQI: Multimodal Federated Learning for Air Quality Prediction on Heterogeneous Edge Devices
May 10, 2026Manjil Nepal, Kimsie Phan, Tamoghna Ojha +2Federated Learning Edge Devices
Department of Computer Science and Engineering, SRM University-AP, India · Department of Mathematics and Computing, IIT (ISM) Dhanbad, India · Department of Mathematics and the Department of Computer Science, University of Central Florida, USA
PoHAR: Understanding Hyperlocal Human Activities with Pollution Sensor Networks
May 10, 2026Prasenjit Karmakar, Karthik Reddy, Sandip ChakrabortyHuman Activity Recognition Air Pollution
Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, India.
AirQualityBench: A Realistic Evaluation Benchmark for Global Air Quality Forecasting
May 7, 2026Xing Xu, Xu Wang, Yudong Zhang +3Air Pollution Evaluation Benchmarks
University of Science and Technology of China (USTC), Hefei, Anhui, China · 2Suzhou Institute for Advanced Research, USTC, Suzhou, Jiangsu, China · 3The Hong Kong Polytechnic University, Hong Kong, China
Scalable inference of spatial regions and temporal signatures from time series
May 6, 2026Jiayu Weng, Alec KirkleySpatiotemporal Time Series
Institute of Data Science, University of Hong Kong, Hong Kong SAR, China · School of Computing and Data Science, University of Hong Kong, Hong Kong SAR, China · Department of Urban Planning and Design, University of Hong Kong, Hong Kong SAR, China +1
GraphSVR: A Graph Convolutional Support Vector Regression Framework for Robust Spatiotemporal Air Pollution Forecasting
May 5, 2026Nourin Jahan, Muhammed Navas T, Tanujit Chakraborty +1Air Pollution Spatio-Temporal Forecasting
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India · SAFIR, Sorbonne University, Abu Dhabi, UAE · SCAI - Sorbonne Cluster for Artificial Intelligence, Paris, France +1
Partial Effective Information Decomposition for Synergistic Causality
May 5, 2026Mingzhe Yang, Shuo Wang, Jiang ZhangCausal Air Pollution
School of Systems Science Beijing Normal University
Collocation-based Robust Physics Informed Neural Networks for time-dependent simulations of pollution propagation under thermal inversion conditions on Spitsbergen
Apr 24, 2026Leszek Siwik, Maciej Sikora, Natalia Leszczyńska +7One-Dimensional Viscous Burgers Equation Air Pollution
AGH University of Krakow, Faculty of Computer Science, Al. Mickiewicza 30, Kraków, 30-059, Poland · Medical University of Silesia-Katowice, Faculty of Medical Sciences, ul. Poniatowskiego 15, Katowice, 40-055, Poland · The University Centre in Svalbard, Longyearbyen, Box 156 N-9171, Longyearbyen, Norway +4
A temporal deep learning framework for calibration of low-cost air quality sensors
Apr 23, 2026Arindam Sengupta, Tony Bush, Ben Marner +2Air Pollution Deep Learning Framework
1ETSI Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Plaza Cardenal Cisneros, 3, Madrid, 28040, Spain · 2Air Quality Consultants Ltd., 3rd Floor, St. Augustine’s Court, St. Augustine’s Place,2026 Bristol, BS1 4UD, United Kingdom
Ground-Level Near Real-Time Modeling for PM2.5 Pollution Prediction
Apr 21, 2026Zachary R. Fox, Janet O. Agbaje, Dakotah Maguire +6Air Pollution Covid-19
Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37980. · Johnson & Johnson, New Brunswick, NJ 08933. · Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM 87545. +2
Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments
May 30, 2025Abhijeet Vishwasrao, Sai Bharath Chandra Gutha, Andres Cremades +8Optimal Sensor Placement Air Pollution
Department of Aerospace Engineering, University of Michigan, Ann Arbor, USA · FLOW, Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden · Division of Robotics, Perception and Learning, School of EECS, KTH Royal Institute of Technology, Stockholm, Sweden +7

Sep 28, 2026, cs.SEJ/K move · Enter open · S save

Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting

Gary Myler, James Holmes, Manish Patel, Amel Bennaceur

The Open University, UK.

Atmospheric Dynamics Era5 Reanalysis Data Air Pollution

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Martian weather forecasting is important for future exploration, but atmospheric behaviour on Mars combines spatial, temporal, vertical, and dust-driven processes in ways that challenge current modelling and forecasting approaches. This paper introduces MaGMA (Martian Graph-based Multi-horizon Atmospheric Forecasting), a graph-based data engineering framework that transforms OpenMARS reanalysis fields into structured learning objects for Martian atmospheric forecasting. Local atmospheric patches are represented as graph nodes and linked through spatial neighbourhoods, temporal continuity, longer temporal dependencies, and dynamically similar atmospheric states. The model integrates recent atmospheric history, engineered physical descriptors, and vertical atmospheric information to support forecasting across multiple horizons. We evaluate MaGMA across five unseen Martian years, including regular years and a global dust storm year. In regular years, the model achieves overall R^2 values of approximately 0.73-0.85. For dust-column forecasting, it outperforms classical and deep temporal baselines in most year-horizon comparisons. During the global dust storm year, dust-column prediction remains strong at shorter horizons, with R^2 above 0.8 for the first two horizons, while broader multivariate performance declines. The results show that graph-based data engineering can create reusable and diagnostically useful representations for planetary atmospheric forecasting, while highlighting the need for better learning under rare extreme regimes and improved use of vertical atmospheric structure.

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Latest papers 36