Evaluation of Bayesian Maximum Entropy Data Fusion Approaches to Estimate Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes and to Inform Epidemiological Analyses in the US Gulf States.

The Gulf States are home to industries emitting styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX). Presently, adverse health effects of ambient SBTEX exposure in highly polluted regions, such as the Gulf States, must be evaluated. Epidemiologists, however, are limited by inadequate estimates of ambient SBTEX.

A Physically Constrained Deep-Learning Fusion Method for Estimating Surface NO Concentration from Satellite and Ground Monitors.

Accurate estimation of atmospheric chemical concentrations from multiple observations is crucial for assessing the health effects of air pollution. However, existing methods are limited by imbalanced samples from observations. Here, we introduce a novel deep-learning model-measurement fusion method (DeepMMF) constrained by physical laws inferred from a chemical transport model (CTM) to estimate NO concentrations over the Continental United States (CONUS).

Performance evaluation of a photochemical model using different boundary conditions over the urban and industrialized metropolitan area of Vitória, Brazil.

Metropolitan areas may suffer with increase of air pollution due to the growth of urbanization, transportation, and industrial sectors. The Metropolitan Area of Vitória (MAV) in Brazil is facing air pollution problems, especially because of the urbanization of past years and of having many industries inside the metropolitan area. Developing air quality system is crucial to understand the air pollution mechanism over these areas.

Current and future particulate-matter-related mortality risks in the United States from aviation emissions during landing and takeoff.

Demand for air travel is projected to increase in the upcoming years, with a corresponding influence on emissions, air quality, and public health. The trajectory of health impacts would be influenced by not just emissions growth, but also changes in nonaviation ambient concentrations that influence secondary fine particulate matter (PM(2.5) ) formation, population growth and aging, and potential shifts in PM(2.

Measurement and analysis of the relationship between ammonia, acid gases, and fine particles in eastern North Carolina.

An annular denuder system, which consisted of a cyclone separator; two diffusion denuders coated with sodium carbonate and citric acid, respectively; and a filter pack consisting of Teflon and nylon filters in series, was used to measure acid gases, ammonia (NH3), and fine particles in the atmosphere from April 1998 to March 1999 in eastern North Carolina (i.e., an NH3-rich environment).

Chemical coupling between ammonia, acid gases, and fine particles.

The concentrations of inorganic aerosol components in the fine particulate matter (PM(fine)< or =2.5 microm) consisted of primarily ammonium, sodium, sulfate, nitrate, and chloride are related to the transfer time scale between gas to particle phase, which is a function of the ambient temperature, relative humidity, and their gas phase constituent concentrations in the atmosphere. This study involved understanding the magnitude of major ammonia sources; and an up-wind and down-wind (receptor) ammonia, acid gases, and fine particulate measurements; with a view to accretion gas-to-particle conversion (GTPS) process in an agricultural/rural environment.