Claudio Guarnaccia, Aurora Mascolo, Pierre Aumond, Arnaud Can, Domenico Rossi
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引用次数: 0
Abstract
Purpose of the Review
This paper is devoted to the review of the most popular literature Road Traffic Noise Models (RTNMs) frameworks, from the oldest ones to the recent machine learning techniques. A dedicated section is reserved to the review of Noise Emission Models (NEMs), with specific focus on approaches that allow the assessment of single vehicles’ emissions. Finally, some propagation models are also briefly presented, along with the assessment of the impact on the population of road traffic noise, in terms of time-averaged indicators and exposure descriptors.
Recent Findings
In recent years, many efforts have been devoted to developing methods and models to assess the impact of environmental noise. Considering the primary role of road traffic as a noise source, estimating its impact is fundamental when evaluating the acoustic environment of a specific urban area. The scope of RTNMs is to provide an assessment of the noise emitted by the source in terms of traffic flows, propagate it at any desired point, including possible corrective factors, assess the impact at the receiver, and use this information to provide maps and other useful outputs.
Summary
This review summarizes the so-far developed approaches for road traffic noise evaluation and furthermore underscores the ongoing necessity for research to develop more precise tools useful for managing road traffic noise’s adverse effects on urban environments and public well-being. Challenges and limitations of such models are discussed in the conclusions, highlighting the need for providing high quality input data and avoiding site-dependent approaches.
期刊介绍:
Current Pollution Reports provides in-depth review articles contributed by international experts on the most significant developments in the field of environmental pollution.By presenting clear, insightful, balanced reviews that emphasize recently published papers of major importance, the journal elucidates current and emerging approaches to identification, characterization, treatment, management of pollutants and much more.