## 3 Materials and Methods
### Input Data  
Based on the above, the minimum input variables necessary to be introduced into the calculation tool are as follows:  
* Identification of emission types. * Traffic volume on the road section, refers to the annual traffic volume in each flow period, i.e., vehicles per year. * Vehicle speeds, operational speed of vehicles when traveling on the road. * Fuel consumption, pertaining to the instantaneous fuel consumption of each vehicle type, in each traffic intensity period. * Vehicle lifespan and model parameters. * Characteristics of the road section, such as section length, slopes, and road surface. * Maximum and minimum temperatures of the study area. Through a literature review, it was possible to identify the types of pollutant emissions generated by vehicles in road operations. It is important to note that the case study is located in Mexico, a developing country. Consequently, there are challenges in obtaining data for the necessary variables to create a traditional inventory. In this context, to conduct this research, aside from exploring various databases, fieldwork was essential to gather and verify statistical data about vehicles using the road and existing geometric data. The consulted databases included traffic data from the Ministry of Infrastructure, Communications, and Transportation (Secretaria de Infraestructura, Comunicaciones y Transportes, SICT, Mexico City, Mexico) [77] and data from the Public Trust for Road Funds and Investment Administration of the Centinela-Rumorosa Highway Section (Fideicomos Publico de Administracion de Fondos e Inversion del Tramo Carretero Centinela-Rumorosa, FIARUM, Mexicali, Mexico) [78], as well as environmental information data from the Ministry of Environment and Natural Resources (SEMARNAT, Mexico City, Mexico) [79]. Figure 3: Methodological approach for quantifying pollutant emissions from road operations. Traffic composition is defined as the proportions of different types of vehicles using the road [80]. To obtain the annual average daily traffic and vehicle characterization, the configuration scheme of the main vehicles circulating on the national network published in the Mexican official standard by the SICT was used [81] (Table 1). The first inputted data pertain to traffic and vehicle composition. This information was taken from the year 2018 as a complete count was available for this period and to avoid biased data due to the reduction in traffic in subsequent years caused by the COVID-19 pandemic. Additionally, it is important to mention that these data correspond to the typical highway traffic. On the other hand, it should be noted that the case study has specific characteristics along its route. Therefore, the segment was divided into three subsections. The first segment, from kilometers 0 to 18, is located in an urban area. The second subsection is situated around the Laguna Salada, spanning kilometers 18 to 42, characterized by a non-urban environment with a completely flat and straight terrain. The third subsection covers the range from kilometer 42 to 64, as it traverses a mountainous area with a series of curves and significant slopes. Furthermore, the entire route has two separate lanes of traffic. In this context, Table 2 presents the average annual daily traffic for both lanes, categorized within the three subsections. In addition to the above, Table 3 shows the vehicular classification of the road section; it is noteworthy that the highest traffic is recorded in the urban area. Vehicles of type A2 (light vehicles) account for 75% on uphill and 73% on downhill. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Section** & **km from 0–18** & **km from 18–42** & **km from 42–64** \\ \hline Uphill & 6307 & 5513 & 4185 \\ Downhill & 6358 & 5622 & 3775 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Annual average daily traffic (AADT)).