AIMC Topic: Vehicle Emissions

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Particulate Matter Exposure of Passengers at Bus Stations: A Review.

International journal of environmental research and public health
This review clarifies particulate matter (PM) pollution, including its levels, the factors affecting its distribution, and its health effects on passengers waiting at bus stations. The usual factors affecting the characteristics and composition of PM...

A fuzzy logic urea dosage controller design for two-cell selective catalytic reduction systems.

ISA transactions
Diesel engines have dominated in the heavy-duty vehicular and marine power source. However, the induced air pollution is a big problem. As people's awareness of environmental protection increasing, the emission regulations of diesel-engine are becomi...

Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine.

Environmental science and pollution research international
The purpose of this study is to investigate the performance, emission and combustion characteristics of a four-cylinder common-rail turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends. A kernel-based extreme learning machi...

Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation.

PloS one
To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving...

Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.

PloS one
Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services f...

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

Computational intelligence and neuroscience
The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parame...

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

Neural networks : the official journal of the International Neural Network Society
Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-da...

Prenatal exposure to criteria air pollution and traffic-related air toxics and risk of autism spectrum disorder: A population-based cohort study of California births (1990-2018).

Environment international
BACKGROUND: Autism spectrum disorder (ASD) prevalence has risen steadily in California (CA) over several decades, with environmental factors like air pollution (AP) increasingly implicated. This study investigates associations between prenatal exposu...

Refining source-specific lung cancer risk assessment from PM-bound PAHs: Integrating component-based potency factors and machine learning in Ningbo, China.

Ecotoxicology and environmental safety
The component-based potency factor approach, combined with benzo[a]pyrene (BaP) unit risk values from the World Health Organization (WHO), is commonly used to assess lung excess cancer risk (LECR) from polycyclic aromatic hydrocarbons (PAHs). However...

Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning.

Journal of environmental sciences (China)
Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of traffic factors on air quality is very important for building air quality prediction models. Using re...