Assessment of externalities related to global and local air pollutants with the NEEDS-TIMES Italy model

Pietrapertosa, Filomena; Cosmi, C.; Leo, Senatro Di; Loperte, Simona; Macchiato, M.; Salvia, Monica; Cuomo, V.

doi:10.1016/j.rser.2009.08.011

Cited by 13 publications

(6 citation statements)

References 4 publications

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“…We developed a link between the TIMES PanEU energy system model and the health impact assessment model EcoSense to analyze the interaction between GHG mitigation and air pollution and to assess the health impacts from energy-related emissions. The impacts of such a link on the energy transition have already been analyzed in different studies [3,8]. The link itself is depicted in the upper part of Figure 2, together with the relevant data exchange.…”

Section: Linking Energy System Model With Health Impact Assessment Modelmentioning

confidence: 99%

“…According to this link, the unit health damage costs caused by the pollutants are calculated exogenously and they are fed back to the energy system model. The synergy between the environmental taxes on pollutants and different CO 2 mitigation scenarios in Italy are discussed in detail in [8]. Similar analyses are also delivered at the EU level to see the impact of externalities in the energy system [3].…”

Section: Introductionmentioning

confidence: 99%

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On the Way to a Sustainable European Energy System: Setting Up an Integrated Assessment Toolbox with TIMES PanEU as the Key Component

et al. 2020

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The required decarbonization of the energy system is a complex task, with ambitious targets under the Paris Agreement, and related policy analysis should consider possible impacts on the economy and society. By coupling the energy system model TIMES PanEU with the impact assessment model EcoSense and the computable general equilibrium model NEWAGE, we present an integrated assessment toolbox for the European energy system capable of internalizing health damage costs of air pollution while simultaneously accounting for demand changes in energy services caused by economic feedback loops. The effects of each coupling step are investigated in a scenario analysis. Additionally, CO2 decomposition analysis is applied to identify the main drivers to decarbonize the energy system. Our results show that integrating externalities forces the system to take early action, which provides benefits on the societal level. Including macro-economic variables has a negative effect on energy service demands and generally reduces the need for structural change, which are still the main drivers of decarbonization. The tighter the models are coupled, the fewer the iterations needed and the lower the CO2 prices resulting from the carbon cap and trade system. In this aspect, an integrated view can provide valuable insights to determine efficient and effective decarbonization paths.

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Section: Linking Energy System Model With Health Impact Assessment Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Way to a Sustainable European Energy System: Setting Up an Integrated Assessment Toolbox with TIMES PanEU as the Key Component

et al. 2020

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“…This variant has been used, for instance, to optimize for social costs of the energy or electricity sector at the national, continental, or global level, − to determine external costs associated with the chemical or metal industry in the EU27, and to quantify (potentially) avoided external costs of the Chinese electricity and household sector subject to CO 2 reduction policies …”

Section: Existing Approaches For Assessing Environmental Externalitie...mentioning

confidence: 99%

Assessing Air Pollutant-Induced, Health-Related External Costs in the Context of Nonmarginal System Changes: A Review

Bachmann

2015

Environ. Sci. Technol.

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Marginal analysis is the usual approach to environmental economic assessment, for instance, of health-related external costs due to energy-associated air pollutant emissions. However, nonlinearity exists in all steps of their assessment, i.e., atmospheric dispersion, impact assessment, and monetary valuation. Dedicated assessments thus appear necessary when evaluating large systems or their changes such as in green accounting or the implications of economy-wide energy transitions. Corresponding approaches are reviewed. Tools already exist that allow assessing a marginal change (e.g., one power plant's emissions) for different background emission scenarios that merely need to be defined and implemented. When assessing nonmarginal changes, the top-down approach is considered obsolete, and four variants of the bottom-up approach with different application domains were identified. Variants 1 and 2 use precalculated external cost factors with different levels of sophistication, suitable for energy systems modeling, optimizing for social (i.e., private and external) costs. Providing more reliable results due to more detailed modeling, emission sources are assessed individually or jointly in variants 3 and 4, respectively. Aiming at considering nonlinearity more fully and simultaneously following marginal analysis principles, I propose a variant 3-based approach, subdividing an aggregate (i.e., a nonmarginal change) into several smaller changes. Its strengths and drawbacks, notably the associated effort, are discussed.

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“…Other authors developed models involving more than one sectors, in order to take into account the interdependencies among them. Two examples are given by Pietrapertosa et al [16] and Amirnekooei et al [17].…”

Section: Introductionmentioning

confidence: 99%

“…In particular, Pietrapertosa et al [16] developed a detailed model of the Italian energy system by using the TIMES modelling platform by focusing on the analysis of air pollutants and greenhouse gas (GHG) emissions. They analyzed different policies to mitigate the impact of the emissions.…”

Section: Introductionmentioning

confidence: 99%

Forecasting Energy Consumption in the EU Residential Sector

Bianco

Marchitto

Scarpa

et al. 2020

IJERPH

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The present paper aims to introduce a top down methodology for the forecasting of residential energy demand in four European countries, namely Germany, Italy, Spain, and Lithuania. The methodology employed to develop the estimation is based on econometric techniques. In particular, a logarithmic dynamic linear constant relationship of the consumption is proposed. Demand is estimated as a function of a set of explaining variables, namely heating degree days and gross domestic product per capita. The results confirm that the methodology can be applied to the case of Germany, Italy, and Spain, whereas it is not suitable for Lithuania. The analysis of elasticities of the demand with respect to the gross domestic product per capita shows a negative value for Germany, −0.629, and positive values for Italy, 0.837, and Spain, 0.249. The forecasting of consumption shows that Germany and Italy are more sensitive to weather conditions with respect to Spain and an increase in the demand of 8% and 9% is expected in case of cold climatic conditions.

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Assessment of externalities related to global and local air pollutants with the NEEDS-TIMES Italy model

Cited by 13 publications

References 4 publications

On the Way to a Sustainable European Energy System: Setting Up an Integrated Assessment Toolbox with TIMES PanEU as the Key Component

On the Way to a Sustainable European Energy System: Setting Up an Integrated Assessment Toolbox with TIMES PanEU as the Key Component

Assessing Air Pollutant-Induced, Health-Related External Costs in the Context of Nonmarginal System Changes: A Review

Forecasting Energy Consumption in the EU Residential Sector

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