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Approach to Vehicle Emission Modelling
Rajesh B. Biniwale
Scientist
Air Pollution Control Division, NEERI, Nagpur-440 020
Introduction
Vehicle emission estimation is essential for calculating vehicle pollution
load and its impact on ambient air quality. The emission inventory technique is
used for estimation of pollutant loads. The dispersion modeling gives the
resulting ambient air quality. Source apportionment studies are carried out using
receptor modeling. This paper discusses all three approaches in brief. Common
models used for this purpose are also mentioned
Emission Inventory Models
The objective of emission inventory preparation should be very clearly
spelt out to facilitate selection of the appropriate model. The major objective of
emission inventory preparation, in general is estimation of emission loads under
various scenarios with technological or policy interventions planned.
Several models are available for preparation of emission inventories.
Some of the models are however, CORINAIR, IPIECA tool kit, and few more are
specific for the prediction of pollution load.
CORINAIR takes into account emissions from point, line and area sources
and gives percentage-wise or mass emission load per year from 11 different
categories of sources.
The IPIECA toolkit is a PC-based emission inventory model. The Toolkit
allows users to develop comprehensive emission inventories and assess the
effect of a range of future energy, transport, commercial and industrial scenarios
238
on emission. The model is highly flexible and can be adapted to characterize
emissions within a city, region or country and at various temporal scales up to
one hundred years. The Toolkit, using built-in options and equations, can also be
used where only incomplete sets of local data are available. The model provides
a sound balance between complexity, accuracy and user friendliness.
Two approaches can be employed to evaluate source contribution from
source emissions data and ambient monitoring data : source-oriented models
and receptor-oriented models. Source-oriented models use emissions data and
fluid mechanically explicit transport calculations to predict pollutant
concentrations at specific receptor air monitoring locations. This type of model is
validated by comparison of the predicted spatial and temporal distribution of
pollutant concentrations against measured concentrations. Receptor oriented
models infer source contributions by determining the best fit linear combination of
emission source chemical composition profiles needed to reconstruct the
measured chemical composition of ambient air.
Dispersion Modelling - Source Oriented Models
Dispersion models may be used to predict the concentration of pollutants
at various locations due to dispersion under prevailing meteorological conditions.
The dispersion models could be source-type specific e.g. for line source, models
which may be used are Caline, Mobile 5 etc. For point sources ISCST3 may be
used. The dispersion models suggested do not account for the regional scenario.
Mesoscale meteorological models such as MM5 in combination with models such
as Calpuff facilitate detailed regional air quality modeling.
Using emission inventory and dispersion modeling estimates of emission
loads and concentration of various pollutants in ambient air may be predicted.
However, the above approach needs to be integrated using receptor modelling.
o o r
Chemical Mass Balance (CMB) - Receptor Model
The CMB model uses the chemical composition of ambient pollution samples
to estimate the concentration of different source types to the measured pollutant
concentrations. The model quantifies contributions from chemically distinct
source types rather than contributions from individual emitters. Sources, which
have similar chemical composition, can not be separated by the model. The
particle characteristics must be such that;
i. they are present in different proportion in different source emissions,
ii. these proportions remain relatively constant for each source type,
iii. change in these proportions between sources and receptor are negligible,
iv. chemical species do no react with each other, i.e., they add linearly, and
v. the number of sources is less than or equal to the number of chemical
species
The contribution of automotive exhaust to ambient air quality depends on
engine type, traffic movement and fuel quality. A detailed study is, therefore,
needed to develop vehicle emission norms keeping in view all these aspects.
240

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Approach to vehicle emission modelling

  • 1. Approach to Vehicle Emission Modelling Rajesh B. Biniwale Scientist Air Pollution Control Division, NEERI, Nagpur-440 020 Introduction Vehicle emission estimation is essential for calculating vehicle pollution load and its impact on ambient air quality. The emission inventory technique is used for estimation of pollutant loads. The dispersion modeling gives the resulting ambient air quality. Source apportionment studies are carried out using receptor modeling. This paper discusses all three approaches in brief. Common models used for this purpose are also mentioned Emission Inventory Models The objective of emission inventory preparation should be very clearly spelt out to facilitate selection of the appropriate model. The major objective of emission inventory preparation, in general is estimation of emission loads under various scenarios with technological or policy interventions planned. Several models are available for preparation of emission inventories. Some of the models are however, CORINAIR, IPIECA tool kit, and few more are specific for the prediction of pollution load. CORINAIR takes into account emissions from point, line and area sources and gives percentage-wise or mass emission load per year from 11 different categories of sources. The IPIECA toolkit is a PC-based emission inventory model. The Toolkit allows users to develop comprehensive emission inventories and assess the effect of a range of future energy, transport, commercial and industrial scenarios 238
  • 2. on emission. The model is highly flexible and can be adapted to characterize emissions within a city, region or country and at various temporal scales up to one hundred years. The Toolkit, using built-in options and equations, can also be used where only incomplete sets of local data are available. The model provides a sound balance between complexity, accuracy and user friendliness. Two approaches can be employed to evaluate source contribution from source emissions data and ambient monitoring data : source-oriented models and receptor-oriented models. Source-oriented models use emissions data and fluid mechanically explicit transport calculations to predict pollutant concentrations at specific receptor air monitoring locations. This type of model is validated by comparison of the predicted spatial and temporal distribution of pollutant concentrations against measured concentrations. Receptor oriented models infer source contributions by determining the best fit linear combination of emission source chemical composition profiles needed to reconstruct the measured chemical composition of ambient air. Dispersion Modelling - Source Oriented Models Dispersion models may be used to predict the concentration of pollutants at various locations due to dispersion under prevailing meteorological conditions. The dispersion models could be source-type specific e.g. for line source, models which may be used are Caline, Mobile 5 etc. For point sources ISCST3 may be used. The dispersion models suggested do not account for the regional scenario. Mesoscale meteorological models such as MM5 in combination with models such as Calpuff facilitate detailed regional air quality modeling. Using emission inventory and dispersion modeling estimates of emission loads and concentration of various pollutants in ambient air may be predicted. However, the above approach needs to be integrated using receptor modelling. o o r
  • 3. Chemical Mass Balance (CMB) - Receptor Model The CMB model uses the chemical composition of ambient pollution samples to estimate the concentration of different source types to the measured pollutant concentrations. The model quantifies contributions from chemically distinct source types rather than contributions from individual emitters. Sources, which have similar chemical composition, can not be separated by the model. The particle characteristics must be such that; i. they are present in different proportion in different source emissions, ii. these proportions remain relatively constant for each source type, iii. change in these proportions between sources and receptor are negligible, iv. chemical species do no react with each other, i.e., they add linearly, and v. the number of sources is less than or equal to the number of chemical species The contribution of automotive exhaust to ambient air quality depends on engine type, traffic movement and fuel quality. A detailed study is, therefore, needed to develop vehicle emission norms keeping in view all these aspects. 240