Existing research on the emission reduction effects of policies in the road transport industry primarily involves modeling and simulation. This approach utilizes mathematical and computer methods to model and simulate real policy issues, creating an emerging research direction that integrates economics, geography, computer science, and other disciplines. Policy simulation does not fully possess the characteristics of empirical science. The results of its simulation are outcomes of computer experiments, and the effects of various simulated policies cannot all be applied and tested in the real world because once a policy takes effect, it changes the real world, and there is no way to return to the starting point(quotes from medcom).


Some international research institutions have developed models and tools to assess the emission reduction effects of traffic systems, including MoMo, LEAP, CDM, TEEMP, and CTF. Different models have varying scales of focus:


MoMo (Mobility Model): Suitable for national-level studies, including all modes of transportation. Developed by the International Energy Agency (IEA), users include IEA, BP, Shell, Toyota, etc. Input data includes ASIF framework data and factors such as GDP and population growth, fuel economy, costs, travel demand, etc. It is a convenient tool for estimating, predicting, and backcasting international and regional emissions. The current version covers the entire Asian region (subdivided into China, India, and other Asian regions). However, the model cannot be applied for analysis at the city, neighborhood, or project levels, and its accessibility is limited.


LEAP (Long-range Energy Alternatives Planning system): Regional in scope, applicable at the national, provincial, state, and city levels. Developed by the Stockholm Environment Institute, users include government agencies, academic institutions, non-governmental organizations, etc. It requires input of information such as transport vehicle details, passenger and freight demand, mode splits, technology application details, average fuel efficiency for various technologies, emission factors, etc. The model provides reliable macro-level analysis data but does not consider behavioral factors and cannot be used for micro-level project analysis. A major advantage of the LEAP model is its high independence from initial data and software availability.


CDM (Clean Development Mechanism): Developed based on the United Nations Framework Convention on Climate Change, primarily for use by CDM project developers and validators. Requires detailed bottom-up local data and parameters to be monitored at least annually. It focuses on the project level, is technically reliable but data-intensive, and has difficulty defining project boundaries. The “rebound effect” needs to be quantified.


TEEMP (Transport Emissions Evaluation Model for Projects): Co-developed by the Clean Air Initiative for Asian Cities (CAI-Asia) and the Institute for Transportation and Development Policy (ITDP). Users include the Asian Development Bank (ADB), World Bank, etc. Input data includes ASIF framework parameters, project-specific traffic activities over the project period, mode splits, fuel economy, and emission factors, building materials, induced traffic volume, etc. The model is flexible, with default parameter values, and supports data from different boundary frameworks. Emissions of PM and NOx can also be calculated. However, its accuracy is limited by method constraints.


CTF (Guidelines for calculating GHG benefits from clean technology fund investments in the transport sector): Supported by the Clean Technology Fund (CTF) for use by CTF co-financed transportation operators. Input data includes specific categorizations of vehicle activities, average passenger occupancy/load, various types of vehicle activity durations, average travel speeds and road conditions, fuel consumption and emission factors, improvements in fuel economy during the project period, etc. CTF guidelines require complex data and specific output results from a four-step model. The model can provide highly accurate conclusions, considering capacity, costs, and data, and can be compared with CDM methods(sources from medcom.com.pl).


CDM, TEEMP, and CTF models are project-scale, analyzing the emission reduction effects of specific projects such as building a public transportation system. The modeling approaches of these tools often belong to the bottom-up type, allowing for the study of comprehensive effects caused by technological micro-level changes at the lower units. Therefore, they have higher credibility in evaluating the substitution effects of resource production technologies and can clearly explain the mechanisms of changes in resource consumption, greenhouse gas emissions, or pollutant emissions caused by the introduction of certain technologies. Such models have been widely applied in the field of traffic policy emission reduction assessments. Additionally, some economic models, including system dynamics models, input-output models, and Computable General Equilibrium (CGE) models, can also be applied to the analysis and research of the emission reduction effects of traffic policies.

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