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Related papers: Analyzing Ozone Concentration by Bayesian Spatio-t…

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Here we report a modelling study of the spring ozone maximum and its interhemispheric asymmetry in the remote marine boundary layer (MBL). The modelled results are examined at the surface and on a series of time-height cross sections at…

Atmospheric and Oceanic Physics · Physics 2008-11-20 Kuo-Ying Wang , Dudley E. Shallcross , John A. Pyle

This study develops a Bayesian hierarchical model to explore the effects of air pollution on respiratory and cardiovascular mortality in Los Angeles County. The model takes into account various pollutants such as PM2.5, PM10, CO, SO2, NO2…

Applications · Statistics 2025-01-29 Yanfei Qu , David A. Stephens

This study investigates the hourly concentrations of Ground-level Ozone (O3), Nitric Oxide (NO), Nitrogen Dioxide (NO2), and Oxides of Nitrogen (NOx) in ambient air, along with the various meteorological parameters viz., ambient…

Atmospheric and Oceanic Physics · Physics 2023-03-28 Suchetana Sadhukhan , Satish Bhagwatrao Aher , Pon Harshavardhanan , Dharma Raj , Subroto Shambhu Nandi

Ambient air pollution measurements from regulatory monitoring networks are routinely used to support epidemiologic studies and environmental policy decision making. However, regulatory monitors are spatially sparse and preferentially…

Applications · Statistics 2026-03-02 Wenlong Gong , Brian J. Reich , Joseph Guinness

In the matter of selection of sample time points for the estimation of the power spectral density of a continuous time stationary stochastic process, irregular sampling schemes such as Poisson sampling are often preferred over regular…

Statistics Theory · Mathematics 2010-07-19 Radhendushka Srivastava , Debasis Sengupta

Predicting the occurrence, level and duration of high air pollution concentrations exceeding a given critical level enables researchers to study the health impact of road traffic on local air quality and to inform public policy action.…

Applications · Statistics 2017-05-30 János Gyarmati-Szabó , Leonid V. Bogachev , Haibo Chen

Air pollution is a major driver of climate change. Anthropogenic emissions from the burning of fossil fuels for transportation and power generation emit large amounts of problematic air pollutants, including Greenhouse Gases (GHGs). Despite…

Machine Learning · Computer Science 2021-09-01 Linus Scheibenreif , Michael Mommert , Damian Borth

Air pollution stands as the fourth leading cause of death globally. While extensive research has been conducted in this domain, most approaches rely on large datasets when it comes to prediction. This limits their applicability in…

Machine Learning · Computer Science 2024-01-10 Mulomba Mukendi Christian , Hyebong Choi

Climate change and the rapid growth of urban populations are intensifying environmental stresses within cities, making the behavior of urban atmospheric flows a critical factor in public health, energy use, and overall livability. This…

Machine Learning · Computer Science 2026-03-19 Nishant Kumar , Franck Kerhervé , Lionel Agostini , Laurent Cordier

Accurate air quality index (AQI) forecasting is essential for the protecting public health in rapidly growing urban regions, and the practical model evaluation and selection are often challenged by the lack of rigorous, region-specific…

Machine Learning · Computer Science 2026-03-30 Khawja Imran Masud , Venkata Sai Rahul Unnam , Sahara Ali

Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants. However, current ground-level NO2 concentration data are lack of either high-resolution coverage or full coverage national wide, due to the poor quality of source…

Atmospheric and Oceanic Physics · Physics 2022-07-20 Xinyu Dou , Cuijuan Liao , Hengqi Wang , Ying Huang , Ying Tu , Xiaomeng Huang , Yiran Peng , Biqing Zhu , Jianguang Tan , Zhu Deng , Nana Wu , Taochun Sun , Piyu Ke , Zhu Liu

We derive the properties and demonstrate the desirability of a model-based method for estimating the spatially-varying effects of covariates on the quantile function. By modeling the quantile function as a combination of I-spline basis…

Methodology · Statistics 2019-05-02 Halley Brantley , Montserrat Fuentes , Joseph Guinness , Eben Thoma

We study the variability of major atmospheric absorption features in the disk-integrated spectra of the Earth with future application to Earth-analogs in mind, concentrating on the diurnal timescale. We first analyze observations of the…

Earth and Planetary Astrophysics · Physics 2015-06-12 Yuka Fujii , Edwin L. Turner , Yasushi Suto

Air pollution constitutes the highest environmental risk factor in relation to heath. In order to provide the evidence required for health impact analyses, to inform policy and to develop potential mitigation strategies comprehensive…

Applications · Statistics 2021-08-23 Matthew L. Thomas , Gavin Shaddick , Daniel Simpson , Kees de Hoogh , James V. Zidek

Atmospheric ozone is a crucial absorber of solar radiation and an important greenhouse gas. However, most climate models participating in the Coupled Model Intercomparison Project (CMIP) still lack an interactive representation of ozone due…

Observed chemical species in the Venusian mesosphere show local-time variabilities. SO2 at the cloud top exhibits two local maxima over local time, H2O at the cloud top is uniformly distributed, and CO in the upper atmosphere shows a…

Earth and Planetary Astrophysics · Physics 2021-12-15 Wencheng D. Shao , Xi Zhang , João Mendonça , Thérèse Encrenaz

We develop a mechanistic model to analyze the impact of sulfur dioxide emissions from coal-fired power plants on average sulfate concentrations in the central United States. A multivariate Ornstein-Uhlenbeck (OU) process is used to…

Methodology · Statistics 2020-10-12 Nathan B. Wikle , Ephraim M. Hanks , Lucas R. F. Henneman , Corwin M. Zigler

Using a free-running distributed-feedback quantum cascade laser (QCL) emitting at 9.54 $\mu$m, the pressure shift parameters of four intense rovibrational transitions in the $\nu_3$ fundamental band of ozone induced by oxygen (O$_2$), air…

Intelligent Transportation Systems increasingly depend on heterogeneous data from roadside cameras, UAV imagery, LiDAR, and in-vehicle sensors, yet the lack of unified data standards, model interfaces, and evaluation protocols across these…

Air contamination in urban areas has risen consistently over the past few years. Due to expanding industrialization and increasing concentration of toxic gases in the climate, the air is getting more poisonous step by step at an alarming…

Machine Learning · Computer Science 2021-05-13 Satvik Garg , Himanshu Jindal