Sérgio Ramos Pereira

Assessment of potential improvements on regional air quality modelling related with implementation of a detailed methodology for traffic emission estimation

The accuracy and precision of air quality models are usually associated with the emission inventories. Thus, in order to assess if there are any improvements on air quality regional simulations using detailed methodology of road traffic emission estimation, a regional air quality modelling system was applied. For this purpose, a combination of top-down and bottom-up approaches was used to build an emission inventory. To estimate the road traffic emissions, the bottom-up approach was applied using an instantaneous emission model (Vehicle Specific Power - VSP methodology), and an average emission model (CORINAIR methodology), while for the remaining activity sectors the top-down approach was used. Weather Research and Forecasting (WRF) and Comprehensive Air quality (CAMx) models were selected to assess two emission scenarios: (i) scenario 1, which includes the emissions from the top-down approach; and (ii) scenario 2, which includes the emissions resulting from integration of top-down and bottom-up approaches. The results show higher emission values for PM10, NOx and HC, for scenario 1, and an inverse behaviour to CO. The highest differences between these scenarios were observed for PM10 and HC, about 55% and 75% higher (respectively for each pollutant) than emissions provided by scenario 2. This scenario gives better results for PM10, CO and O3. For NO2 concentrations better results were obtained with scenario 1. Thus, the results obtained suggest that with the combination of the top-down and bottom-up approaches to emission estimation several improvements in the air quality results can be achieved, mainly for PM10, CO and O3.

Empirical assessment of route choice impact on emissions over different road types, traffic demands, and driving scenarios

ABSTRACT Eco-routing has been shown as a promising strategy to reduce emissions. However, during peak periods, with limited additional capacity, the eco-friendliness of various routes may change. We have explored this issue empirically by covering about 13,300 km, in three different areas, using GPS-equipped vehicles to record second-by-second vehicle dynamics. This study has confirmed the importance of the eco-routing concept given that the selection of eco-friendly routes can lead to significant emissions savings. Furthermore, these savings are expected to be practically unchanged during the peak period. However, some potential negative externalities may arise from purely dedicated eco-friendly navigation systems.

Traffic restriction policies in an urban avenue: A methodological overview for a trade-off analysis of traffic and emission impacts using microsimulation

ABSTRACT Urban traffic emissions have been increasing in recent years. To reverse that trend, restrictive traffic measures can be implemented to complement national policies. We have proposed a methodology to assess the impact of three restrictive traffic measures in an urban arterial by using a microsimulation model of traffic and emissions integrated platform. The analysis is extended to some alternative roads and to the overall network area. Traffic restriction measures provided average reductions of 45%, 47%, 35%, and 47% for CO2, CO, NOX, and HC, respectively, due to traffic being diverted to other roads. Nevertheless, increases of 91%, 99%, 55%, and 121% in CO2, CO, NOX, and HC, respectively, can be expected on alternative roads.

Integrated computational methods for traffic emissions route assessment

This paper focuses on the integration of multiple computational tools towards the objective of assessing emission impacts of different routes. Data from real life GPS tracks was integrated with traffic emission modelling for multiple pollutants (NOx, HC, CO and PM10) to investigate different routing strategies. The main conclusion is that different pollutants dictate different best routes. Hence, strategies for assigning relative weights to pollutants are devised in order to be able to select the best environment-friendly route.

Driving around turbo-roundabouts vs. conventional roundabouts: Are there advantages regarding pollutant emissions?

ABSTRACT This article addresses the impact of turbo-roundabouts located in urban areas on pollutant emissions using field measurements of vehicle activity data and road congestion levels. The research also compares the emissions of vehicles moving along a turbo-roundabout and a conventional multilane roundabout. Based on field measurements taken at turbo-roundabouts without curb dividers located in Grado, Spain, and multilane roundabouts in Aveiro, Portugal, three representative speed profiles for each speed trajectory were identified: no stop (I), stop once (II), and multiple stops (III). This study also develops discrete models for turbo-roundabouts and multilane roundabouts in which the relative occurrence of those speed profiles is expressed as a function of the entry and conflicting traffic flows. The vehicle specific power (VSP) methodology is then employed to estimate second-by-second pollutant emissions. This study tests the hypotheses that emissions are impacted by the differences in (1) the characteristics of speed profiles in each movement, (2) the volumes of entry and conflicting flows, (3) the overall saturation level, and (4) the transportation facility considered (turbo-roundabout / multilane roundabout). Considering the selected case studies and traffic demands, vehicles at turbo-roundabouts generated more emissions (15–22%, depending on the pollutant) than multilane conventional roundabouts, especially under medium and high congestion levels. These findings suggest that there are no advantages in implementing turbo-roundabouts from an environmental point of view, regardless of the traffic congestion levels.

Application of Artificial Neural Networks to Predict the Impact of Traffic Emissions on Human Health

Artificial Neural Networks (ANN) have been essentially used as regression models to predict the concentration of one or more pollutants usually requiring information collected from air quality stations. In this work we consider a Multilayer Perceptron (MLP) with one hidden layer as a classifier of the impact of air quality on human health, using only traffic and meteorological data as inputs. Our data was obtained from a specific urban area and constitutes a 2-class problem: above or below the legal limits of specific pollutant concentrations. The results show that an MLP with 40 to 50 hidden neurons and trained with the cross-entropy cost function, is able to achieve a mean error around 11%, meaning that air quality impacts can be predicted with good accuracy using only traffic and meteorological data. The use of an ANN without air quality inputs constitutes a significant achievement because governments may therefore minimize the use of such expensive stations.

Assessment of Corridors with Different Types of Intersections: Environmental and Traffic Performance Analysis

Recently, roundabouts in a series have been installed along corridors to enhance road safety. However, the benefits of this traffic-calming technique on traffic performance and pollutant emissions compared with other forms of intersections, such as traffic lights and stop-controlled solutions, are not properly known. This study used a microscopic approach to evaluate the effects of a corridor with four roundabouts on traffic performance and emissions, in comparison with traffic lights and stop-controlled solutions. Average travel time and number of vehicle stops were used as measures of traffic performance; carbon dioxide, monoxide carbon, nitrogen oxides, hydrocarbons, and particulate matter were used to quantify emissions. The traffic and emissions performance of each solution was evaluated on three levels: (a) arterial, (b) intersection, and (c) morning peak versus evening peak periods. It was found that, regardless of the time period, traffic lights in corridors at the arterial level produced higher total emissions (> 6%), while stop-controlled intersections produced lower emissions (≈12%) compared with roundabouts, mainly because of unbalanced traffic flows between main and minor roads. The results for traffic performance showed advantages in implementing roundabouts when the main concern was the number of vehicle stops. At the intersection level, an emissions improvement (between 2% and 14%) was observed at traffic lights on four-leg intersections.

Multicriteria Assessment of Crosswalk Location in Urban Roundabout Corridors

Midblock pedestrian crossing areas between closely spaced roundabouts can affect traffic operations and may result in a trade-off between capacity, environment, and safety benefits. Even though research has been conducted on the impacts of traffic performance on pedestrian crosswalks located at isolated roundabouts, few studies have focused on how pedestrian crosswalks between closely adjacent roundabouts affect traffic operations. A microsimulation approach was used to examine the integrated effect of a pedestrian crosswalk on traffic delay, carbon dioxide emissions, and relative speed between vehicles and pedestrians at different locations between closely spaced two-lane roundabouts. The main purpose of the study was to develop a simulation platform of traffic (VISSIM), emissions (vehicle-specific power), and safety (surrogate safety assessment model) to optimize such variables. The fast nondominated sorting genetic algorithm NSGA-II was mobilized to identify an optimized set of pedestrian crosswalk locations for the roundabout exit section along the midblock segment. One acceptable solution that provided a good balance between traffic performance, emissions, and pedestrian safety benefits was locating the crosswalks at 15, 20, and 30 m from the exit section. Even at low pedestrian demand, crosswalk effectiveness (as determined by capacity and environment) gradually decreased near the circulatory ring delimitation (<10 m). Findings suggest that crosswalks in the midblock segment (55 to 60 m from the exit section) also must be considered, especially under high traffic demand.

An Eco-Traffic Management Tool

Drivers routing decisions can be influenced to minimize environmental impacts by using, for instance, dynamic and intelligent road pricing schemes. However, some previous research studies have shown that often different pollutants can dictate different traffic assignment strategies which makes necessary to assign weights to these pollutants so they become comparable. In this chapter, a tool for traffic assignment taking into account eco-routing purposes is presented. The main goal of this work is to identify the best traffic volume distribution that allows a minimization of environmental costs for a given corridor with predetermined different alternative routes. To achieve this, an integrated numerical computing platform was developed by integrating microscopic traffic and emission models. The optimization tool employs non-linear techniques to perform different traffic assignment methods: User Equilibrium (UE), System Optimum (SO) and System Equitable (SE). For each method, different strategies can be assessed considering: (i) individual pollutants and traffic performance criteria; and (ii) all pollutants simultaneously. For the latter case, three different optimization approaches can be assessed based on: (i) economic costs of pollutants once released into the air; (ii) human health impacts according to the Eco-Indicator 99; and (iii) real time atmospheric pollutant concentration levels. The model was applied to a simple network, simulating three levels of traffic demand and three different strategies for traffic assignment. The system is developed in Microsoft Excel and offers a user friendly access to optimization algorithms by including a dynamic user interface.

Exploring multiple eco-routing guidance strategies in a commuting corridor

ABSTRACT The introduction of eco-routing systems has been suggested as a promising strategy to reduce carbon dioxide emissions and criteria pollutants. The objective of this study is to scrutinize the impacts of an eco-routing guidance system on emissions through the use of a case study in a commuting corridor. This research aims at assessing the potential environmental benefits in terms of different pollutant emissions. Simultaneously, it addresses the extent of variations in system travel time (STT) that each eco-routing strategy implies. The methodology consists of three distinct phases. The first phase corresponds to the adjustment of a microsimulation platform of traffic and emissions with empirical data previously collected. Second, to volume-emission-functions (VEF), developed based on the integrated modeling structure. Final, to different scenarios of traffic flow optimization performed at the network level based on a simplified assignment procedure. The results show that if the traffic assignment is performed with the objective to minimize overall impacts, then the total system environmental damage costs can be reduced up to 9% with marginal oscillations in total STT. However, if drivers are advised based on their own emissions minimization, total system emissions may be higher than under the standard user equilibrium flow pattern. Specifically, environmentally friendly navigation algorithms focused on individual goals may tend to divert traffic to roads with less capacity affecting the performance of the remaining traffic. This case study brings new insights about the difficulties and potentials of implementing such systems.