BigAir – Big data to improve atmospheric emission inventories

Coordinator

Diogo José Sousa Lopes

Programme

Concurso de Projetos de IC&DT em todos os Domínios Científicos

Dates

29/03/2021 - 28/03/2024

Funding for CESAM

249999 €

Total Funding

249999 €

Funding Entity

FCT - Fundação para a Ciência e a Tecnologia

Proponent Institution

Universidade de Aveiro

URL / WWW

http://bigair.web.ua.pt/

DOI

10.54499/PTDC/EAM-AMB/2606/2020

Main objectives and innovation
The main purpose of the BigAir project is to improve the performance of the air quality modelling (AQM) applications in Portugal using big data sets (available at no cost) to calculate the historical and forecast Portuguese atmospheric emissions with high spatial (exact location of emission sources) and temporal (hourly values) resolutions. The first worldwide open and collaborative emission inventory database will be developed to the stakeholders identify inadequate atmospheric emission values and lack of emission sources. This database will also allow information sharing between scientific community (international and national) and provide a continuous improvement of the Portuguese emission inventory.

Background
Air pollution is the largest single environment risk to human health, and it is responsible for 4.2 million worldwide deaths every year. In Portugal, since the 90’s AQM has been developed and applied to provide scientific advice on definition of AQ improvement measures, AQ forecast, AQ assessment and AQ policy regulations. Although great advance in computational power and scientific research have been made, the atmospheric emissions (global and European inventories) used by AQM still to be the major source of uncertainty and the main reasons are: i) the inaccurate magnitude of emissions values related with inadequate emission factors (e.g. from road dust resuspension) and activities data: ii) imprecise emission locations due to the coarse horizontal resolution of the available inventories (between 0.0625˚ and 0.1˚); and iii) unsuitable temporal (monthly, weekday and hourly) and speciation profiles applied to the annual atmospheric emission values. In recent years, the massive collection of information (Big data) has emerged as one solution for air pollution, namely for emission inventories improvement.

Plan and methods
To accomplish the main goal, the BigAir project will be organized in 5 Tasks: Task 1) Big data sources; Task 2) Road dust resuspension; Task 3) Emission data; Task 4) Evaluation of the new approach; and Task 5) Emission inventory database.
In Task 1, the big data sets (e.g. meteorological data) will be handled, stored and processed using the UA high performance computational system, python programme language and its data science tools. Since the importance of road transport emissions from non-exhaust sources will increase and there is a lack of information regarding it, in Task 2, the emission factors from road dust resuspension will be quantified considering the USEPA (United States Environmental Protection Agency) AP-42 procedure.
In Task 3, using the data obtained in the previous tasks, historical and forecast Portuguese atmospheric emissions with high spatial and temporal resolutions will be quantified applying, whenever possible, the more accurate methodology provided by the European air pollution inventory guidebook. Regarding the forecast emissions, it will be estimated using artificial neural networks, meteorology forecast data, opening hours of the facilities and transport schedules. In addition, an ensemble approach, considering the available global and European inventories, will be developed in order to compare it with inventory developed in this research project. In Task 4, AQM performance (using Eulerian, Gaussian and Lagrangian models), inventory uncertainty and the impact of the atmospheric emission uncertainty in the AQM results will be evaluated. Finally, in last Task, the open and collaborative atmospheric emission database will be developed.

Knowledge of the project consortium
The technical and scientific challenges addressed by BigAir require a multi-disciplinary approach that will be supported by the expertise of the project consortium constituted by GEMAC (Group on Emissions, Modelling and Climate Change) and LAC (Atmospheric Chemistry Laboratory. GEMAC has proven expertise regarding atmospheric emission quantification and AQM developments/applications from regional to local scales; LAC is specialized in research on physical and chemical properties of the emission sources.

Expected outcomes
The main BigAir outcome will be the development of the Portuguese atmospheric emission inventory and its database. The consortium will also dedicate great attention and effort to disseminate and promote the knowledge developed in the project to the decision makers, stakeholders and scientific community. Besides the typical scientific disseminations indicators (i.e. conference communications) the consortium intends to create the project webpage in several platforms in order to reach a wide audience.

CESAM members in the project

Célia dos Anjos Alves

Investigadora Principal com Habilitação

Daniel Fernandes Graça

Estudante de Doutoramento

Diogo José Sousa Lopes

Investigador Doutorado

Joana Cardoso Ferreira

Investigadora Auxiliar

Johnny Daniel Conceição dos Reis

Estudante de Doutoramento

Sandra Isabel Moreira Rafael

Investigadora Júnior