Emissions

This research report published by Waka Kotahi NZ Transport Agency details the modern integration of vehicle operating cost (VOC) models with environmental emissions modeling frameworks for transport evaluation in New Zealand. As national policies emphasize carbon reduction and environmental sustainability alongside economic efficiency, traditional VOC appraisal tools must be updated to dynamically model fuel consumption, greenhouse gas (GHG) emissions (CO2, CH4, N2O), and airborne pollutants (PM2.5, NOx) across modern vehicle fleets. The study updates traditional HDM-4 vehicle operating cost algorithms to reflect New Zealand's evolving fleet profile, including hybrid, plug-in hybrid, and battery electric vehicles (EVs). It establishes integrated mathematical models that calculate energy consumption and emissions as functions of road geometry, gradient, surface roughness (IRI), speed variance, and congestion levels. Field validation using real-world driving data confirms that smoother road surfaces and optimized gradients yield measurable reductions in energy use and carbon output across both internal combustion and electric powertrains. The integrated model is incorporated into New Zealand's Monetised Benefits and Costs Manual (MBCM), providing transport planners with a unified analytical tool to evaluate the economic and environmental trade-offs of roading investments, pavement maintenance policies, and decarbonization strategies.

Understanding the environmental impacts of roadway management strategies is essential not only to the estimation of construction cost, but also the protection of the environment and the conservation of the global ecological system. Vehicle speed and fuel consumptions may vary with driving conditions. Vehicle emissions can be estimated based on the speed, acceleration rate, and Vehicle Specific Power (VSP), which could normally be listed in an Operating Mode Identification (OMID) table. The relationships between pavement roughness (indicated by International Roughness Index or IRI) and speed/fuel consumption could be reflected by linear models, while the IRI is nonlinearly correlated to the emissions. It is recommended further identifying the relationships between IRI and emissions with more on-road tests for all types of vehicles on different types of roadway systems, so as to minimize the environmental, ecological, and even public health impacts through proper roadway management strategies.

MIRAVEC Report D2.1.  This is a report of the findings in Work Package 2 (WP2) in MIRAVEC. The objective of this WP is to describe existing modelling tools and evaluate their capabilities with respect to analysing the effects identified in WP1 “Road infrastructure influence effects on vehicle energy consumption and associated parameters”. The variables identified in WP1 and considered to be the most important to take into consideration when estimating the impact of road infrastructure on road traffic energy use are texture (MPD), IRI (unevenness), rut depth (RUT), gradient (RF), crossfall, horizontal curvature (ADC), road width, traffic volume (AADT) and speed (v). In this report, a selection of projects that have evaluated road characteristics and the effect on energy use are described and analysed. The results of these project shows that there can be benefits energy wise in taking the energy aspect into consideration when planning a new road or choosing rehabilitation measure of the pavement. 

MIRAVEC Report D5.3.  The objective of MIRAVEC was to build on existing knowledge and models in order to achieve a more holistic view considering a broad variety of effects. The project results are compiled in this final report of MIRAVEC project. The first part of this final report is a short summary on the findings and outputs of all Work Packages (WP), while the second part is a summary of all recommendations to National Road Administrations (NRAs) on how to implement the findings, models and tools in pavement and asset management systems. The main findings and recommendations of the project can be summarised as follows:  Five major groups of parameters influencing road vehicle energy and fuel consumption were identified, of which a subset was selected based on impact, potential for influence by National Roads Administrations and integration into existing fuel consumption models. Further analysis showed that while currently monitored parameters can be used for modelling several effects of the infrastructure influence, knowledge gaps remain with respect to other parameters and the correct modelling of associated effects.  There is no current model which takes all infrastructure-related effects into account. Most models for fuel consumption and CO2 emission of road vehicles focus on vehicle and traffic flow characteristics and tend to neglect details of the infrastructure. The Swedish VETO model is one of the most advanced models in this respect and was the basis of many analyses. As the knowledge about the infrastructure influence increases, these models offer the possibility to integrate this knowledge into decision making.  The spreadsheet tool developed in WP3 allows the comparison of the effects of different infrastructure-related measures on fuel consumption and CO2 emission. It requires data about the most widely available pavement and road layout parameters and uses information about traffic flow and vehicles as background information. While the tool can be applied even with limited data, the strong influence of these background data found in the analysis may supersede the infrastructure effects in some cases.  The investigation of the current situation with regard to the occurrence of this topic in pavement and asset management found a growing awareness of its importance with road managers, but so far very limited implementation in the actual systems. While future models based on the more commonly monitored infrastructure parameters will make the integration of vehicle CO2 emission feasible, acceptance and weight in decision making in the view of limited financial resources for maintenance still remain to be achieved. 

Various reports and presentations from the EU MIRAVEC looking at the impact of infrastructure on vehicle energy.

MIRAVEC Report D1.1: This document describes the different road infrastructure parameters which can contribute to the overall road vehicle energy consumption and highlights those which can be influenced by infrastructure design. It is a report on the effects and parameters that need be considered in order to determine the influence of road infrastructure on road vehicle energy consumption by modelling. The effects and properties were divided into the following five groups: A. Effects of pavement surface characteristics (rolling resistance, texture, longitudinal and transversal unevenness, cracking, rutting, other surface imperfections) B. Effects of road design and layout (e.g. road curvature, gradient and crossfall, lane provision) C. Traffic properties and interaction with the traffic flow (e.g. free flowing traffic vs. stop-and-go, speed limits, access restrictions) D. Vehicle and tyre characteristics including the potential effect of technological changes in this area E. Meteorological effects (e.g. temperature, wind, water, snow, ice)

Detailed reference book on the different types of driving cycles used for modelling emissions.

The current work being undertaken for the Ministry of Transport, focuses on the effects of road transport on aquatic ecosystems and by default is concerned with the contaminants and their loads generated by motor vehicles. All of the stormwater quality models that are commonly in use deal with the overall loads produced by all activities within urban areas. This report focuses on three aspects of the information required by the VFEM-W. These aspects are those that provide the framework for the emissions hub within the model (refer Figure. 1.1). The
cells for any given source within the hub contain three key pieces of information that allow emissions of contaminants to be calculated over time within a given section of roadway. These are:

• The concentration of contaminant present. 
• The rate that the contaminant is released by an individual motor-vehicle.\\\\
• The rate at which the emission from a particular source is deposited to the road surface and is then available for stormwater transport.

A wide range of contaminants are emitted from motor vehicles. Typically estimates of emissions are only required for those contaminants whose discharge to the environment is of environmental significance. The focus of this report is for those key sources known to contribute contaminants and those contaminants identified as being of potential environmental concern (COPC). Typically the COPC include the USEPA priority inorganic and organic pollutants in addition to a range of motor vehicle specific organic compounds. However where data is available on other significant contaminants in emissions from motor vehicles it is identified in this document.

The report presents information on the emissions from motor vehicles in seven sections:

• Section 2 provides an overview of the vehicle fleet and how it is categorised and how VFEM-W handles vehicle types and some of the core factors that influence emissions.
• Section 3 provides information about emissions from brake systems.
• Section 4 presents information about emissions from motor vehicle tyres.
• Section 5 presents information about emissions of lubricants and greases.
• Section 6 provides information about emissions of coolants.
• Section 7 provides information about the emissions from vehicle exhaust systems and includes specific discussion on the emission of contaminants from vehicles with catalytic converters.
• Section 8 examines the wear of material from bitumen road surfaces.

In each of these sections information is presented on the contaminants present in that source and the available information on emission rates for that source. Finally in Section 9 information is presented in relation to the pathway from the source to the road surface, as not all of the emitted contaminant is likely to end up on the road surface and then be available for stormwater transport to a fresh or coastal receiving environment. Factors are identified that provide a first estimate of air to road deposition.

This technical report details the mathematical specification, engine physics, and algorithmic implementation of the vehicle exhaust emissions model developed for the Highway Development and Management (HDM-4) system under the ISOHDM initiative. The model bridges the gap between traditional macroscopic highway evaluation tools and microscopic vehicle emission models by utilizing vehicle power demand, engine rotational speed, fuel consumption, and instantaneous traffic dynamics to predict exhaust emissions under varied operating conditions. Emissions of carbon dioxide, carbon monoxide, unburned hydrocarbons, oxides of nitrogen, and particulate matter are calculated for diverse vehicle categories, ranging from light passenger vehicles to heavy multi-axle freight trucks. A central feature of the report is the inclusion of acceleration noise algorithms—measuring speed variability caused by traffic congestion, roadside friction, and vertical or horizontal geometry—to accurately capture transient engine operations during high-power acceleration phases that significantly elevate pollutant generation rates. Fuel composition parameters, fuel sulfur content, engine thermal efficiency, catalytic converter degradation factors, and ambient altitude/temperature corrections are fully incorporated into the predictive equations. The resulting exhaust model enables transportation planners to assess the environmental footprint of alternative highway maintenance standards, road alignment improvements, and traffic management interventions, providing reliable data for national emissions inventories and sustainable transport policy formulation. Overall, the report emphasizes rigorous empirical validation, standardized data acquisition protocols, and modular integration into the broader Highway Development and Management analytical engine. By combining physical principles with statistical calibration across international trial sites, this working paper provides a robust theoretical and practical baseline for highway authorities to evaluate long-term

This technical working paper presents the second refined proposal for incorporating a vehicle exhaust emissions sub-model into the HDM-4 software package under the ISOHDM initiative. Building on the preliminary conceptual framework, this document advances the mathematical formulation for predicting emission rates based on engine power output, instantaneous fuel consumption, and drive cycle characteristics. Specific attention is given to modeling the influence of traffic congestion, road gradients, and speed fluctuations on engine load and resultant pollutant formation. Emitted compounds analyzed include carbon dioxide, carbon monoxide, unburned hydrocarbons, nitrogen oxides, and exhaust particulate matter. The paper introduces cold-start emissions correction factors, vehicle fleet aging degradation coefficients, and catalytic converter efficiency profiles to reflect modern vehicle fleets across different geographic regions. Guidance is provided on structuring emission lookup tables and default parameter libraries within the HDM-4 database, enabling users to perform rapid environmental screening or detailed project-level environmental cost-benefit assessments. This proposal served as a key technical milestone prior to finalized software coding and model integration. Overall, the report emphasizes rigorous empirical validation, standardized data acquisition protocols, and modular integration into the broader Highway Development and Management analytical engine. By combining physical principles with statistical calibration across international trial sites, this working paper provides a robust theoretical and practical baseline for highway authorities to evaluate long-term infrastructure policy options, allocate maintenance budgets efficiently, and maximize economic returns across regional and national road networks. In summary, this study provides highway engineers, transport planners, and economic analysts with an essential mechanistic-empirical tool for evaluating life-cycle

This initial proposal document sets out the rationale, objectives, and preliminary technical approach for incorporating environmental exhaust emission modeling into HDM-4 under the ISOHDM research framework. Recognizing that traditional road appraisal tools focused almost exclusively on economic costs to road agencies and vehicle operators, this paper argues for the inclusion of environmental externalities to support sustainable transport planning. The document outlines the target pollutants—including greenhouse gases like CO2 and local air contaminants such as CO, HC, NOx, and lead—and reviews candidate emission modeling approaches ranging from simple speed-based functions to detailed power-demand models. Key input requirements are identified, such as traffic volumes, fleet composition, vehicle technology types, road geometry (vertical grades), and fuel properties. The proposal defines a work plan for developing computationally efficient algorithms suitable for network-level planning without requiring overly complex microscopic traffic data. This baseline document laid the ground work for subsequent ISOHDM technical working groups to establish formal exhaust emission relationships within the HDM-4 system. Overall, the report emphasizes rigorous empirical validation, standardized data acquisition protocols, and modular integration into the broader Highway Development and Management analytical engine. By combining physical principles with statistical calibration across international trial sites, this working paper provides a robust theoretical and practical baseline for highway authorities to evaluate long-term infrastructure policy options, allocate maintenance budgets efficiently, and maximize economic returns across regional and national road networks. In summary, this study provides highway engineers, transport planners, and economic analysts with an essential mechanistic-empirical tool for evaluating life-cycle infrastructure costs, optimizing maintenance