Multi-dimensional Air Quality model
The Multi-scale Air Quality (MAQ) system is an integrated assessment model that aims to support regional policymakers in selecting efficient strategies for reducing air pollution at minimum cost.
Air pollution is referred to as an Air Quality Index (AQI), which is a composite value indicating the level of air pollution concentration within a specified area. The model estimates the yearly average concentrations of fine and coarse particulate matter (PM2.5 and PM10), nitrogen dioxides (NO2), and SOMO35 (Sum of Ozone Means Over 35ppb).
This system allows for two different approaches: scenario analysis and multi-objective optimization. In scenario analysis, the users set the specific measures they plan to implement, and the system computes how these measures will affect air quality.
In multi-objective optimization, the model identifies the most effective set of measures to achieve optimal air quality and implementation cost. The control variables of the system are the degree of application of emission reduction measures (that are categorized into end-of-pipe, energy and fuel switch measures).
The computation of AQI starts from the precursors’ emissions scenario per cell with a source receptor model, in particular the Artificial Neural Network.
The model outputs are the air quality indexes, the emission reduction, including GHGs, the total costs of applied measures, and the health impact.
For more information about the model, please read “A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions” by Turrini et al., 2018.
Preprocessing module
The preprocessing module produces the emission and measures database, combining the local emission inventory with the national scenarios.
The emission database contains information for each cell of a gridded domain about the emissions of the different sectors and activities for a set of pollutants linked to the air quality index that has to be evaluated.
The measures database includes information describing the set of emission abatement measures that can be applied to the different sectors and activities.
The MAQ system adopts a 4-level classification database used to compute the emissions (macro-sector, sector, activity, technology) derived from the IIASA GAINS model (https://gains.iiasa.ac.at/models/).
APPLICATIONS
The Role of Energy Policies for Air Pollution Control in the Po Valley
Zecchi, L., Arrighini, M.F., Guariso, G., Volta, M. (2024) IFAC-PapersOnLine, 58 (2), pp. 174-179. DOI: 10.1016/j.ifacol.2024.07.110
ABSTRACT: This paper examines the use of integrated assessment modelling to select policies aimed at reducing air pollution in response to growing concerns about the deterioration of air quality, especially in highly populated and industrialized areas. The study focuses on the Po Valley region in northern Italy, renowned for its intricate environmental difficulties arising from industrial operations, extensive farming, and topographic characteristics. The goal of the multi-objective decision problem is to find the best plans for reducing emissions that will minimize the average annual concentrations of PM2.5 while also considering the costs of putting these plans into action and incorporating end-of-pipe, energy, and fuel switch measures. Results highlight the trade-offs between air quality improvement and associated costs, presenting a Pareto curve of optimal solutions. Copyright © 2024 The Authors.
KEYWORDS: air quality; Integrated modelling; multi-objective optimization; Po valley
Assessing air pollution emissions vs. abatement costs in agricultural practices
Arrighini, M., Zecchi, L., Guariso, G., Volta, M. (2023) Academia Engineering. 1 (1), DOI: 10.20935/AcadEng6149
ABSTRACT: Agriculture is a vital component of human civilization, providing food, fiber, and fuel for billions of people worldwide. However, the agricultural sector has also been identified as a significant contributor to air pollution. This study investigates and analyses the impact of agrofarming activities on air pollution in very productive areas such as Northern Italy. It explores the various sources and mechanisms through which agriculture affects air quality compared to all the other emission sectors and the types of pollutants involved, and quantifies the consequences for human health of agricultural emissions. As a further and novel step, it highlights the technologies that can mitigate these negative impacts and promote sustainable agriculture by adopting an integrated assessment modeling approach. This study defines policy recommendations for the area at hand, determining the optimal compromises between air quality improvement and pollution abatement costs. For instance, it shows that it is possible to reduce the average PM2.5 concentration by 17% with an annual expenditure of 300 M€. Four percent of this improvement is due to end-of-pipe abatement measures in the agricultural sector. Such an improvement in air quality would translate into a reduction of tens of thousands of years of life lost by the resident population. This study concludes with an outlook of additional options for addressing the air pollution challenges associated with agro-farming activities that constitute a limit of the current study, but could open new research lines. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license
KEYWORDS: agrofarming activities, emission abatement, particulate matter, integrated assessment modelling, surrogate models, Northern Italy
Integrated Modelling Assessment of Low Carbon and Air Quality Plan Synergies
Arrighini, M., Zecchi, L., Volta, M. (2023) IFAC-PapersOnLine, 56 (2), pp. 8308-8313. DOI: 10.1016/j.ifacol.2023.10.1019
ABSTRACT: Climate Change and Air Quality are the most crucial environmental challenges for population health and our societies. Decision makers at different scales (European, national, and regional) define low carbon and air quality plans to reduce GHG (CO2, CH4, N2O) and air pollution precursors (NOx, NMVOC, NH3, SOx, primary PM2.5) emissions. Integrated Assessment Modelling is a methodology that can support decision makers. In this paper, we formalize a decision problem based on a multi-objective approach. The solution to the problem is the efficient low carbon and air quality emission reduction measure set for the Lombardy region, one of the most polluted areas in Europe, assuming the current energy legislation in 2030. Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license
KEYWORDS: air quality; energy plan; Integrated modelling; multi-objective optimization; win-win policy
The cost of inaction in air pollution abatement policies
Arrighini, M., Guariso, G., Volta, M., Zecchi, L. (2022) IFAC-PapersOnLine, 55 (5), pp. 13-17. DOI: 10.1016/j.ifacol.2022.07.632
ABSTRACT: Two alternative air quality policies are compared: one is the application of only mandatory abatement measures from 2020 to 2030. The second is the definition of a more active and locally-based policy that will lead to a better air quality at the end of the decade. Using an integrated modelling system, we demonstrate that the active policy is quite more convenient from the economic viewpoint, at least for the specific situation of the Lombardy region, considered in the study. Improving particulate matter concentrations may however produce worse ozone values. A full view of all pollutants is thus necessary when planning for air quality at regional level. © 2022 Elsevier B.V.. All rights reserved.
KEYWORDS: air quality; Integrated modelling; multi-objective optimization; pollutant trade-offs
Low Emission Road Transport Scenarios: An Integrated Assessment of Energy Demand, Air Quality, GHG Emissions, and Costs
De Angelis, E., Carnevale, C., Marcoberardino, G.D., Turrini, E., Volta, M. (2022) IEEE Transactions on Automation Science and Engineering, 19 (1), pp. 37-47. DOI: 10.1109/TASE.2021.3073241
ABSTRACT: This article proposes an integrated assessment methodology aimed at supporting decision-makers in design energy production scenarios to power a low emissions traffic fleet. The Multidimensional Air Quality (MAQ) system is used to define and solve a decision problem that selects a set of energy production scenarios minimizing costs, impacts on air quality, and greenhouse gases (GHGs) emissions. This study focuses on the road transport sector, that is responsible for 25% of European GHGs emissions and 39% of NOx emission, a precursor of both NO2 and PM10 concentrations. The electrification of the light vehicle fleet and the use of biomethane to power heavy vehicles are analyzed, estimating the electricity demand increase, exploring different energy production mixes, and assessing the impacts on air quality, costs, and GHGs according to the fuels/sources used to satisfy the energy demand. A case study over Lombardy region, in Northern Italy, is proposed. Note to Practitioners – The study designs a new decision problem implemented and solved through the Multidimensional Air Quality system (MAQ), an integrated assessment modeling tool. Such system integrates a set of databases, models, optimization, and enumeration algorithms. Composing these elements, specific multiobjective decision problems can be designed defining domain (mesoscale, regional, urban), objectives (air quality index, greenhouse gas emissions, costs, population exposure, health impacts), decision variables (technologies, behavioral measures, energy production, fuel switch), and constraints. MAQ system allows the comprehensive analysis of energy, technological, behavioral policies estimating impacts on air quality, human health, GHGs emissions, and costs. © 2004-2012 IEEE.
KEYWORDS: Air quality integrated assessment modeling; decision support systems; energy policies; environmental system analysis; multiobjective decision problems
Co-benefits of changing diet. A modelling assessment at the regional scale integrating social acceptability, environmental and health impacts
Volta, M., Turrini, E., Carnevale, C., Valeri, E., Gatta, V., Polidori, P., Maione, M. (2021) Science of the Total Environment, 756, art. no. 143708. DOI: 10.1016/j.scitotenv.2020.143708
ABSTRACT: Several commentaries have suggested that the overconsumption of animal foods exerts several detrimental effects on human and environmental health. However, no studies have accurately estimated the impact of a reduction in animal food consumption on mortality due to the direct effects on metabolic health (i.e. animal protein and saturated fat intake as modulators of pathways leading to cardiovascular disease, cancer and accelerated ageing), and indirect effects on health due to excessive exposure to pollutants (i.e. PM10 concentrations originated by livestock ammonia emissions). The proposed modelling approach is innovative since it integrates social acceptability, environmental and health impacts. It is adopted to investigate different scenarios at a regional scale presenting the Lombardy region case study. The work focuses on the impact on the human and environmental health of diets characterized by three different animal protein intake levels. Our integrated assessment modelling approach faces the issue from two points of view. On one side, it estimates the mortality due to the population exposure to PM10 concentrations including the inorganic fraction originated by livestock ammonia emissions, on the other, it evaluates the mortality (i.e. total, cardiovascular and cancer) due to high dietary animal protein and/or saturated fat intake. The impacts of the mentioned animal protein intake levels of diets are also estimated through the people willingness to change their eating behaviour. The importance of putting in place end-of-pipe and energy measures in order to reduce ammonia and methane emissions from the breeding activities, going further the current EU legislation on air quality and climate, is emphasized. © 2020 The Authors
KEYWORDS: Air quality; Climate; Discrete choice modelling; Health impact; Integrated assessment modelling; Metabolic impact
Source apportionment and integrated assessment modelling for air quality planning
De Angelis, E., Carnevale, C., Turrini, E., Volta, M. (2020) Electronics (Switzerland), 9 (7), art. no. 1098, pp. 1-16. DOI: 10.3390/electronics9071098
ABSTRACT: In Northern Italy a large fraction of the population is exposed to PM10 and PM2.5 concentrations that exceed the European limit values and the stricter WHO air quality guidelines. For this reason, in 2017 four Regions (Piemonte, Lombardia, Veneto, and Emilia Romagna) and the national Ministry of the Environment adopted a set of joint measures, namely the “Po Basin air quality plan”. The plan mainly tackles emission from road transport, residential heating, and agriculture. Air quality plans at regional and local scale are usually implemented defining a set of emission abatement measures, starting from experts’ knowledge. The aim of this work is to define a methodology that helps decision makers in air quality planning, combining two different approaches: Source-Apportionment techniques (SA) and Integrated Assessment Modelling (IAM). These techniques have been applied over a domain in Northern Italy to analyze the contribution of emission sources on PM10 concentration and to compute an optimal policy, obtained through a multi-objective optimization approach that minimizes both the PM10 yearly average concentration and the policy implementation costs. The results are compared to the Po Basin air quality plan impacts. The source-apportionment technique and the IAM optimization approach show intervention priorities in three main sectors: residential heating, agriculture, and road transport. The Po Basin air quality plan is effective in reducing PM10 concentrations, but not efficient, as a matter of fact the cost-effective policy at the same cost has a higher impact on air quality and on greenhouse gases emissions reduction. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
KEYWORDS: Air quality modelling; Decision support system; Integrated assessment modelling; Source-apportionment
Vehicle fleet electrification: Impacts on energy demand, air quality and GHG emissions. An integrated assessment approach
De Angelis, E., Turrini, E., Carnevale, C., Volta, M.(2020) IFAC-PapersOnLine, 53 (2), pp. 16581-16586. DOI: 10.1016/j.ifacol.2020.12.784
ABSTRACT: Transport sector is responsible for 25% of European GHG emissions, furthermore it has high impacts on air pollution at various scales. electric mobility is growing fast and it could be effective in reducing road transport GHGs and pollutant emissions, but its potential depends on the energy mix used to produce electricity. In this paper an Integrated Assessment Model is proposed to analyze the energetic transition to an electric vehicle fleet at regional scale. Two scenarios are proposed to assess at the same time which are the impacts of the electric power sources and of the reduced road transport emissions. Results are presented in terms of CO2 emissions, air quality indexes, energy savings and health impacts. © 2020 Elsevier B.V.. All rights reserved.
KEYWORDS: Air quality planning; control; environmental decision support systems; Impact evaluation; Integrated Assessment Modelling
Combining a multi-objective approach and multi-criteria decision analysis to include the socio-economic dimension in an air quality management problem
Turrini, E., Vlachokostas, C., Volta, M. (2019) Atmosphere, 10 (7), art. no. 381. DOI: 10.3390/atmos10070381
ABSTRACT: Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary PM10 fractions are complex and non-linear, environmental authorities need tools to assess their plans designed to improve the air quality as requested from environmental laws. Multi-criteria decision analysis (MCDA) can be applied to support decision makers, by processing quantitative opinions provided by pools of experts, especially when different views on social aspects should be considered. The results obtained through this approach, however, can be highly dependent on the subjectivity of experts. To partially overcome these challenges, this paper suggests a two-step methodology in which an MCDA is fed with the solution of a multi-objective analysis (MOA). The methodology has been applied to a test case in northern Italy and the results show that this approach is a viable solution for the inclusion of subjective criteria in decision making, while reducing the impact of uncertain expert opinions for data that can be computed through the MOA. © 2019 by the authors.
KEYWORDS: Air quality; Decision support systems; Environmental modelling; Integrated assessment modelling; Multi-criteria decision analysis; Multi-objective approach
A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions
Turrini, E., Carnevale, C., Finzi, G., Volta, M. (2018) Science of the Total Environment, 621, pp. 980-989. DOI: 10.1016/j.scitotenv.2017.10.129
ABSTRACT: This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. © 2017 Elsevier B.V.
KEYWORDS: Air quality; Control strategy; Decision support systems; Environmental modelling; Integrated assessment modelling; Optimization; Particulate matter
Evaluating economic and health impacts of active mobility through an integrated assessment model
Carnevale, C., Angelis, E.D., Finzi, G., Turrini, E., Volta, M. (2018) IFAC-PapersOnLine, 51 (5), pp. 49-54. DOI: 10.1016/j.ifacol.2018.06.198
ABSTRACT: The daily usage of cars to commute has negative impacts on population health. Mainly, a direct impact due to the increase of physical inactivity and an indirect impact due to the increase in atmospheric particulate concentration resulting from vehicular emissions. Active mobility can have instead multiple positive impacts. In this work a methodology to evaluate costs, direct and indirect impacts due to the application of active mobility strategies is presented. The methodology is based on the solution of a multi-objective problem identifying a set of optimal strategies, combined with an ex-post impact analysis. This technique has been applied to a case study in Northern Italy. © 2018
KEYWORDS: Modelling and Control of Environmental Systems; Optimal Control; Non Linear Control