b) Low carbon scenario (LCS)

• The LCS was constructed from BLS described previously. For each of the first 17 measures described in Section 5, input data and assumptions were integrated impacting the fuel economy and traveled kilometers, and also to obtain the energy consumed for each of the mitigation measures in the analyzed period. In this simulation the number of vehicles is mostly not a ffected by modal changes, except in few specified cases.

Source: Based on [28–34].


### *3.2. Methodology Development in LEAP Software*

The LEAP software [35] is a bottom-up model that allows the energy supply and demand to be tied in a friendly way in trend and alternative scenarios. LEAP is also an accounting framework that allows to be fed with exogenous technical and economic data, contains also an environmental database from the IPCC. These features allow LEAP to carry out the analysis of the trend and alternative scenarios in terms of energy, economic and greenhouse gas emissions from di fferent levels of aggregation. LEAP also allows the analysis of di fferent mitigation measures to be represented in individual scenarios (one for each measure) and later, aggregated to represent an alternative global scenario. So, taking advantage of these features, in this article the LEAP software was used as follows:


### *3.3. Assumptions about the Interaction, Additivity and Linearity of the Transport Systems*

Given this methodology, this article does not consider the interactivity or the e ffects of additionality that real transport systems have, either in the BLS or in the LCS, except for the interactions that are described precisely and clearly in the description of the 21 mitigation measures. Thus, in this article that deals with Mexican transport systems, it is considered that both in the BLS and in particular in the LCS, it is assumed that di fferent transport systems have a dynamic of a linear nature, independent of other transport systems evolution. For this reason, there are no e ffects of interaction or additionality between Mexican transport systems in most of the 21 mitigation measures analyzed, in this way the demand for energy estimated in each of the transport systems as well as GHG emissions are not influenced by the interaction between transport systems, except for those required in the description of mitigation measures in Section 5, nor by the additive e ffects that may exist in these systems.

Consequently, this article considers for most of the 21 mitigation measures only direct interventions within the same transport system, except in certain measures where it is explicitly established that there are interactions with other transport systems. These considerations about the low interactivity, the null additionality and the linearity in the dynamics of transport systems could lead to conservative results in the reduction of GHG and in the economic calculations presented in this article, both for each mitigation measure as above all for the evaluation of the LCS.

### **4. Reference Year Establishment and Construction of Baseline Scenario (BLS)**

Table 3 shows the structure of Mexican road transport vehicle fleet in the reference year 2010. From this year´s structure, the energy demand was estimated using equations 1, 2, and 3 toward the year 2035 for each type of vehicle. To do so, first it was necessary to estimate the evolution of the age of the vehicle fleet, the annual national sales and imported used vehicles by type of vehicle, the survival factors, the vehicle fuel economy and the annual average distance travelled by each type of vehicle.


**Table 3.** Mexican vehicle fleet structure and fuel type in year 2010 (millions).

The AAGR used to estimate the growth of sales of new LDVs in Mexico was obtained from the historical sales' analysis for the 1995–2009 period, coming to an average annual rate of approximately 6.0%. Concerning the introduction of imported used vehicles to Mexico, an AAGR of 4.3% from 2010 to 2035 was assumed for both light and heavy vehicles.

The survival curves (*f*) from [26] for the di fferent vehicle types is shown in Figure 1. The *f* values for vehicles are relatively optimistic because they reflect the conditions and times in which the vehicle stock is used in Mexico and whose main feature is a slow renewal of the vehicle stock, especially the HDV freight, because users try to delay the purchase of new trucks due to their relatively high costs. This situation is worse for the imported used vehicles from the United States to Mexico. Thus, in 2009, the vehicle stock of vehicles that have been sold in Mexico had an average age of 12.98 years while that of imported used vehicles was 18.01 years old, which resulted in a vehicle stock being in circulation that had an average age of 16.34 years according to [39].

**Figure 1.** Survival curves by vehicle type. Source: [26].

Regarding fuel economy by vehicle type, the values in Table 4 from [36] were used in the energy consumption calculations in the BLS. These values represent the average performance of the future vehicle fleet comprising: existing, new and imported used vehicles. These values are relatively low because this work is considering a high growth percentage of imported used vehicles (5% per year) and comparable to that of new vehicles (6% per year) as well as the high survival factors that characterize the existing Mexican vehicle fleet. Finally, these values allow that the total volume calculation of gasoline and diesel are in accordance with the official prospective of these fuels [27].


**Table 4.** Fuel economy evolution by vehicle type.

Finally, Table 5 shows the evolution of annual kilometers travelled by vehicle type for theperiod2010–2035.


**Table 5.** Evolution of annual kilometers travelled by vehicle type.

\* Reference year. Source: [36].

The data in this table come from [36] which considers the introduction of a degradation factor in the use intensity that depends on vehicle age (see Supplementary Material), which is associated with the high survival factors that characterize the Mexican vehicle fleet. Altogether these assumptions result in a conservative growth in the annual kilometers travelled by LDVs and even a decrease in this parameter by HDVs.

Regarding other fuels that are used for transportation in Mexico, such as Natural Gas, LP gas, fuel oil, kerosene, and electricity, their consumption in this sector in the BLS was estimated following the official consumption outlook of each of these fuels in the transport sector [27,28]. Finally, CO2 emissions were estimated considering the emission factors shown in Table 6.


**Table 6.** Emission factors by fuel type.

Source: [40].

### **5. Construction of a Low Carbon Scenario (LCS)**

The following paragraphs will give information on descriptions, assumptions, and costs of the 21 mitigation measures proposed. These measures have been classified into three important groups: those that favor increasing energy efficiency, those that use biofuels, and those that introduce new technologies using electric motors.
