\introduction  %% \introduction[modified heading if necessary]

Emissions inventory is a quantification of pollutants discharged into the atmosphere by different sources \citep{PullesHeslinga2010}. This quantification is vital for regulatory and scientific purposes, because it allows to monitor the state of the Earth's atmosphere and climate. It also allows to create air quality standards, which will protect ecosystems and human health. For instance, the Intergovernmental Panel on Climate Change (IPCC) includes a dedicated task force, separated from the other three working groups, only for the purpose of greenhouse gas emissions inventory issues \citep{Paustianetal2006}.  

In this instance, there are several emissions inventories that use different input data and approaches for different scales. One of the most frequently used inventories is the Emission Database for Global Atmospheric Research (EDGAR; \citealt{Olivieretal1996}), which provides estimates for the total emissions worldwide. This inventory uses national statistics that do not provide detailed characterizations of high resolution applications. These detailed characterizations are needed for urban studies. There are also continental emissions inventories such as the European Monitoring and Evaluation Programme (EMEP), which compile emissions from the parties of the Convention on Long-range and Transboundary Air Pollution (CLRTAP) \citep{EEA2013}. Moreover, there is the Regional Emissions inventory in Asia (REAS), which covers China, Japan and other countries \citep{Streets2003}.\textcolor{red}{  (1) Also, there are nationwide inventories such as the National Emissions Inventory (NEI) in United States, which is released every three years, based on data from State, local and tribal agencies and compiled by the Environmental Protection Agency \citep{nei}. }However, there are many countries and cities that do not include estimates of emissions for environmental and climate planning.

 Vehicular emissions are becoming increasingly important in urban centers \citep{Andradeetal2017} and measurements have shown that compounds emitted from exhausts can be highly reactive in the atmosphere, contributing to critical episodes of photochemical smog \citep{Nogueiraetal2015}. However, obtaining this type of emissions database can be complicated, since the sources are in movement and the emissions process is complex with many variables. This can be a challenge, especially in developing countries due to the lack of information about the vehicle type, technology, age, motor size, fuel, speeds, accelerations, street type, environmental temperature and humidity, among other aspects. Besides that, there are other aspects involving the emissions inventory. The most common aspects are the accuracy and complexity relating to the exact contribution of the different pollutant sources, and that in most cases, emissions inventories are usually seen as a scapegoat when simulations do not match observation \citep{PullesHeslinga2010}. 

Vehicular emissions inventories are classified according to top-down and bottom-up approaches. Top-down are based on statistics of vehicle composition, representative speeds and country balances, while bottom-up are based on traffic counts, vehicle composition and speed recording \citep{NtziachristosSamaras2016}. \textcolor{red}{ (3) An example of bottom-up emissions model is the SPARE-Truck (Spatial Regression and Output Optimization Truck) \citep{perugu2017developing}, which produces truck activity data at link-street level and then estimate emissions using the US-EPA
MOVES \citep{koupal2003design}}. The accuracy of the emissions inventory will reflect on the representation of the pollutants in the atmosphere. It is not always related to the complexity of the model. For instance, a meta-analysis of several studies on vehicular emissions \citep{Smitetal2010} concluded that there is no evidence that the more complex models perform better than the less complex ones, and that emissions estimation technique must be chose according the available traffic data. %as already mention (ELE MENCIONOU ISTO MESMO?) / SIM Yes, esta no paper dele. . 
An emissions inventory must be comprehensive, including all the important sources and aspects regarding the emissions. %For example, just for vehicular emissions inventory, there is several of factors contributing to the amounts of pollutants: type of vehicle, age of the vehicle, speed, fuel, environment humidity and temperature, etc, and these factors change significantly from one place to other.
%Ideally, all factors concerning vehicular emissions should be incorporated into the calculations, besides a scheme for representing the emissions should. ideally, be applicable to every place in the world considering their own emissions factors in the emissions inventory. %In these countries, it is difficult to access data related to vehicular fleet emissions \citep{Nogueiraetal2015}.

%On the other hand, the bottom-up approach consists of recordings of traffic and speed by street

These complexities were addressed by the Department of Atmospheric Sciences at the University of São Paulo (USP) when modeling the atmospheric chemistry over Brazilian cities using a top-down vehicular emissions inventory with an on-line atmospheric model \citep{Andradeetal2015}. The Metropolitan Area of São Paulo (MASP), is the most populated megacity in Latin America \citep{IBGE2014} and its most important source of pollution comes from the 11 million vehicles that circulate within the Region \citep{CETESB2014, DENATRAN2015, Andradeetal2017}. Furthermore, half of all emissions of CO, HC and NOx in the MASP are from vehicles that are more than 10 years old \citep{Andradeetal2017}. \textcolor{red}{ (2) Despite that the inventories developed by \cite{Andradeetal2015} are useful, they still suffer top-down limitations using surrogates to produce spatial and temporal distributions, hence limiting the representation of the emissions. }Therefore, we decided to develop our own bottom-up vehicular emissions inventory model. With this model, we aim to generate scientific estimates and provide useful information to decision-makers and urban/environmental planners. 

The main goal of this project was to develop a high spatial and temporal resolution vehicular emissions inventory model, which was named as the Vehicular Emissions Inventory VEIN model. The VEIN model follows the bottom-up approach. It allows the classification of vehicles into several categories, different options of emission factors and specification of pollutants, and input traffic from traffic simulations or other network-based sources. It is capable of producing gridded emissions outputs. It is open source, friendly for the user, and is available to run in any computational platform (Mac, Windows, Linux, etc). 
