Mobile source emission inventory model. Application to Paris area

Salles, J.; Janischewski, J.; Jaecker-Voirol, A.; Martin, B.

doi:10.1016/1352-2310(95)00278-2

Cited by 29 publications

(6 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Information on national vehicle fleet and technology is obtained for the main road types (urban roads, rural roads, and highways) from the Institut National de Recherche sur les Transports et leur Sécurité according to Bourdeau [1998]. In addition, information from some reports of the Paris council and from the work of Sallès et al [1996] were used in addition to the national information in order to obtain regional data on an hourly basis. Emission factors are derived from the European Computer Programme to Calculate Emissions from Road Transport (COPERT 3) methodology [ Ntziachristos and Samaras , 2000].…”

Section: The Anthropic Emission Inventory and The Chemistry Transportmentioning

confidence: 99%

Paris emission inventory diagnostics from ESQUIF airborne measurements and a chemistry transport model

et al. 2003

View full text Add to dashboard Cite

[1] During the Atmospheric Pollution Over the Paris Area (ESQUIF) experiment a series of airborne measurements were collected in the vicinity of the city of Paris during smog episodes. They are used in combination with an air quality photochemical model in order to diagnose uncertainties in the current emission inventory. Diagnostics are made by comparing simulated with observed concentrations for nitrogen oxides, carbon monoxide, and primary hydrocarbons, taking into account the chemistry and transport processes of these compounds. An emphasis is put on the uncertainty of the results, taking into account the finiteness of the measurement samples, possible errors in the model transport, and chemistry and measurement errors. We examine, in particular, possible sources of bias in the model. For instance, we show that boundary layer depth is underestimated by at most 30% on average. However, sensitivity experiments showed that these model biases, taken individually, cannot alter the qualitative aspects of our results. Only a conspiracy of these biases could possibly shift all our diagnostics toward significantly different results. There is reasonable consistency between simulated and measured concentrations. NO y simulations agree with measured concentrations to within 35%; CO concentrations agree to within a factor of 2. There are significant underestimations and overestimations in some individual primary hydrocarbons. However, the total mass and reactivity of the measured hydrocarbon mixture, which accounts for only about half of the total emitted mass, agree with modeled values to within an estimated uncertainty of 40%. The analysis of results provides clues for improving emission inventories. It is found, for instance, that temperature dependence, which is not considered here, can be a key factor and that hydrocarbon emissions from solvent use may suffer from inaccurate totals or speciation. Another source of uncertainties may be the temporal or spatial distributions of solvent activities.

show abstract

Section: The Anthropic Emission Inventory and The Chemistry Transportmentioning

confidence: 99%

Paris emission inventory diagnostics from ESQUIF airborne measurements and a chemistry transport model

et al. 2003

View full text Add to dashboard Cite

show abstract

“…Temporal variations are calculated on the basis of GENEMIS data again, for three typical days (weekdays, Saturday and Sunday), for each calendar month, each hour and each activity sector. Only the weekday diurnal profile for traffic is not taken from the GENEMIS database, but from a recent publication of the emission profile of CO in the Paris area [ Sallès et al , 1996].…”

Section: Model Formulationmentioning

confidence: 99%

Adjoint modeling for atmospheric pollution process sensitivity at regional scale

Menut

2003

J. Geophys. Res.

View full text Add to dashboard Cite

[1] During the summer 1998, a strong pollution event was documented over Paris as part of the Etude et Simulation de la Qualité de l'air en Ile-de-France (ESQUIF) project (second intensive observation period (IOP2)). From 7 to 9 August 1998 the pollution event changes from a well-marked ozone plume issued from Paris to a more general pollution over the whole Ile-de-France region. Using a three-dimensional chemistrytransport model and its adjoint part, the sensitivity of ozone, O x , and NO x peaks to model parameters is investigated. For two locations, Paris and a suburban site, the influence of both meteorological and chemical model parameters on the simulated field concentrations is hourly quantified for each day. Processes leading to a urban polluted event are compared. It is shown that the pollutant concentrations are mainly driven by traffic and solvent surface emissions and meteorological parameters such as temperature. Since the adjoint approach is limited to infinitesimal model perturbation, some scenario simulations are carried out to evaluate the linearity of the impact of the most sensitive parameters within the uncertainty range. It is shown that the sensitivities determined from the adjoint approach can be extrapolated until their uncertainty ranges except for the wind speed.

show abstract

“…However, the average speed emission factors do take into account the characteristics of the underlying driving patterns, on the basis of the estimated average speed and the location of the specific road (urban, rural, or highway) (Ntziachristos and Samaras, 2000). Therefore, this emission-factor-based approach is widely used in the modelling of traffic-related emissions (eg Jensen et al, 2001;Lin and Lin, 2002;Salles et al, 1996;Xia and Shao, 2005), with its accuracy depending very much on the reliability of traffic data (traffic volume and velocity, temporal and spatial variations, vehicle composition, etc) and the choice of emission factors (Kumari, 2008).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

An Integrated Activity-Based Modelling Framework to Assess Vehicle Emissions: Approach and Application

Beckx¹,

Panis²,

Vankerkom³

et al. 2009

Environ Plann B Plann Des

View full text Add to dashboard Cite

Owing to the richer set of concepts which are involved in activity-based transportation models, the potential advantages of an activity-based approach for air quality purposes have been recognized for a long time. However, models that have been developed along these lines are still scarce. In this research the activity-based model ALBATROSS was used in combination with the emission model MIMOSA to assess the travelled distances and the mobile source emissions produced by passenger cars in the Netherlands. The fact that this approach is based on hourly travel and emission values, rather than on aggregated results or peak hour values, a common practice within other traditional models, is an important added value. The predicted values seem to correspond well with the reported values from the Dutch Scientific Statistical Agency. Predictions for travelled distances overestimated the reported values by approximately 8%. Predictions for emissions of nitrogen oxide, carbon dioxide, volatile organic compounds, and particular matter differed by 16%, 11%, 9%, and 3%, respectively, from the officially reported values. This paper is novel in the sense that it both reports on the applied methodology and presents the practical results from a case study of the activity-based emission modelling approach.

show abstract

Mobile source emission inventory model. Application to Paris area

Cited by 29 publications

References 2 publications

Paris emission inventory diagnostics from ESQUIF airborne measurements and a chemistry transport model

Paris emission inventory diagnostics from ESQUIF airborne measurements and a chemistry transport model

Adjoint modeling for atmospheric pollution process sensitivity at regional scale

An Integrated Activity-Based Modelling Framework to Assess Vehicle Emissions: Approach and Application

Contact Info

Product

Resources

About