   
\conclusions[Discussion and Conclusions]  
In this manuscript we introduce the development of the Vehicular Emission INventory (VEIN model v0.2.2), an open source model, to produce high resolution spatial and hourly emission estimation. 
VEIN is a tool suited for application in complex environmental science studies, including regional atmospheric modeling. It generates inputs for air quality models in order to forecast air pollutant concentrations or for studies of greenhouse gas emissions from vehicular sources. 
It can be used to study the relationship between emissions and health effects. A recent study used VEIN estimates with a grid of 10 m resolution to determine the relationship between vehicular emissions and birth outcomes in the western area of São Paulo \citep{fink}. 
VEIN can be used as a tool for urban planning in order to estimate vehicular emissions due to interventions at road networks in most cities. 
It was written in an R package that includes several methods for estimating vehicular emissions in a harmonized way.

    VEIN provides functions to easily produce inputs of regional air quality models such as WRF-Chem \citep{Grelletal2005} and BRAMS/SPM \citep{Freitasetal2005}. In Fig. \ref{fig:emis_grid}, the comparison between VEIN and EDGAR \citep{edgar} of CO emissions shows that emissions are heavily concentrated in few streets with a high volume of traffic. EDGAR emissions do not provide this level of detail and they are lower than VEIN estimates. Furthermore, the highest spatial resolution of EDGAR is 0.1 degree, approximately 12 km and it is possible to have better resolution with VEIN. 
    Based on these factors, it can be concluded that EDGAR is suitable for modeling air pollution in larger domains without considering meteorological meso-scale interactions, including feedbacks. 
    However, with the progressing computational advances, it would be possible to perform air pollution modeling for larger domains with higher resolution and level of detail. VEIN can produce these necessary inputs with a bottom-up approach. 
    
    VEIN currently experiences some limitations. 
    The first limitation is the availability of activity data. VEIN needs at least one hour of traffic data for each street considered in the estimation. This data can based on traffic simulation or traffic counts, however, most of cities do not count with this type of data in developing countries. In this case, new data should be generated with traffic counts and interpolations. In addition, the widespread use of applications for smart-phones such as Waze (R) or Uber (R), among others, produce traffic data that eventually could be used as activity data for estimating vehicular emissions. For example, currently Google Traffic (https://developers.google.com/maps/coverage) cover several countries and this data could provide valuable information to estimate vehicular emissions in cities with non-traffic simulation or traffic counts.
    It is expected that new features will be added in future versions of VEIN. One very promising feature will be the migration of the spatial dependencies into the new spatial features \textbf{sf} package. This package provides S3 classes for handling spatial data faster than its predecessor, the package \textbf{sp} \citep{PebesmaBivand2005}.
    
	The emission factors are another aspect of VEIN that can be enhanced in future versions. They could be sourced from several emissions studies, such as tunnel studies \citep{perez2014emission, martins2006emission}, or others based on traffic situations whereby emissions are sourced from driving cycles (ARTEMIS for example, \citealt{andre2004artemis}) or other experimental campaigns \citep{CorvalanVargas2003}. The International Vehicular Emissions (IVE) is a top-down vehicular emission model that has been used in different countries to estimate vehicular emissions \citep{Gonzalezetal2017, Wangetal2008}. It could be possible to derive emission factors from IVE and estimate their corresponding emissions in VEIN, in order to use the capabilities of VEIN.
	
	VEIN's purpose is to serve as a tool for air quality research and environmental management. Since air quality models need detailed emissions species, VEIN was created with the function \textit{speciate}. VEIN will add several new speciations into these functions, such as those in the EMEP/EEA guidelines \citep{NtziachristosSamaras2016}. In the case of Brazil, there are several studies of tropospheric ozone, which use speciation of VOC emissions as an input \citep{VaraVelaetal2015, abou2017contributions}. 