Transport Research Arena 2014, Paris
Evaluation of road transport effect on atmospheric air: method of
emission computations and use of results
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski *
Joint-Stock Company “Scientific and Research Institute of Motor Transport”(NIIAT), Moscow, Russia
Abstract
The subject is methods for computation of road transport emissions inventory used in the Russian Federation.
The results of comparative computation analysis using updated NIIAT OJSC and CORINAIR methods are
provided. The estimated emissions have been verified using findings of field atmospheric air studies within
roadside areas. Estimation of pollutant emissions from road transport in Moscow made by the use of NIIAT
procedure are laid down.
Keywords: road transport, emissions, pollutants, computational procedures, model verification
Résumé
Le sujet est des méthodes de calcul de l'inventaire des émissions du transport routier utilisé dans la Fédération de
Russie. Les résultats de l'analyse comparative de la mise à jour NIIAT OJSC et méthodes CORINAIR sont
fournis. Les estimations des émissions provenant du trafic et des données sur Moscou conventionnel ont été
vérifiés en utilisant les résultats des études de l'air atmosphérique sur le terrain dans les zones en bordure de
route.
Mots-clés: le transport routier, les émissions, les polluants, les procédures de calcul, la vérification de modèle
_________________
* Corresponding author information there. Tel: +7-495-496-55-23; fax: +7-495-496-61-36.
E-mail address: Donchenko@niiat.ru; Kunin.U@mail.ru; Ruzsky@niiat.ru;
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
1. Introduction
Road transport in the Russian Federation remains one of the major sources of atmospheric air pollutants. In
major cities it accounts for up to 90% of emissions.
In the Russian governmental environment quality management system the procedures for computational
evaluation (inventory) of pollutant emissions and climatic gases from road transport play essential role.
Quantitative evaluation of pollutant emissions from road transport is needed for accomplishment of practical
tasks aimed at enhancing stability of the transport systems performance, in particular, for:


evaluation of ecological efficiency of various engineering and planning concepts in road transport area
and taking various measures and decisions in the transport policy;
computation of fees for environment pollution by road transport operators and fines for environment
pollution above permissible limits.
Inclusion of the modules for computation of road transport pollutant emissions distribution and exposure,
estimation of the health effect in the system of ecological appraisals makes it possible to accomplish a large
number of tasks related to environment quality management (Fig.1).
Evaluation
of
Оценка
экологоenvironmental
and
экономического
ущерба
economic
damage
Исходная
Baseline
инфорdata
мация
Module of
Модуль
road
расчета
transport
emissions
выброcomputation
сов от
АТ
Evaluation
Оценка of
efficiency of
эффективности
мероприятий
measures
taken
Pollutant
Выбросы
emission
ЗВ
s
Расчет платыof
Computations
за
environment
загрязнение
pollution
fee
ОС
Estimation of
Риски
Risk of
diseases
возникновения
заболеваний
Проведение
environment
ОВОС
проектов
impact evaluation
projects
Module
Модульof
pollutant
расчета
рассеdissipation
ивания
computation
загрязнений
КонценPollutant
трации
concentrations
ЗВ
Расчет of
Computation
штрафных
fines for
санкций за
environmental
экологические
contraventions
нарушения
Модуль
Module
of
расчета
impact
экспоcomputation
зиции
воздействия
Pollutant
Дозы
поглаabsorption
щения
rate
ЗВ
Module
Модульof
health
оценки
воздейimpact
ствия на
evaluation
здоровье
Evaluation
Оценка ущерба
of damage
от
потери
to health
здоровья
Economic instruments
Экономические
инструменты
Fig.1. The system for evaluation of road transport effect on environment and human health
In the Russian Federation the first methods for road transport emissions inventory were approved for use as far
back as in 80s of the last century. These Methods are widely used in practice and are completed and reproduced
in commercial software.
2. Research methods
Methodologies for evaluation of road transport pollutant emissions adopted in various countries (CORINAIR,
MOBILE, IVE etc.) are rather similar. Calculation of emissions may be based on fuel consumption (simple
approach) or results of traffic flow studies (or modelling). In the second case specific running exhaust emissions
are used.
Emissions of gaseous substances which aren`t regulated by requirements of international regulations concerning
design of vehicles are computed on the basis of percentage of these substances in non-methane volatile organic
compounds (NМVОС).
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
The Methods accepted in Russia are based on the well-known approach which may be generally expressed as
follows:
h
M i 106  mik N k Lk (1)
k 1
where:
Mi

mass emission of i pollutant, t;
mik

Nk

specific distance-related i pollutant emissions from a motor vehicle of the k-th type,
g/km;
total number of motor vehicles of the k-th type;
Lk
h

aggregate distance travelled by motor vehicles of the k-th type, km;

number of motor vehicle types under study.
Below we shall examine in detail the basic provisions of recently updated procedure for calculation of emissions
from road transport in the biggest cities. In calculations for segments of road networks by the source of emission
is meant a linear segment of a street (road) of specified traffic volume and relatively uniform traffic conditions
(in this case Lk =L is meant the length of such a segment and Nk is meant volume of motor vehicles of k-th type
traffic on the segment). The set of such segments defines the real urban road network with real traffic flows.
Such approach makes it possible to obtain rather accurate evaluation of aggregate emissions. When evaluating
emissions from motor vehicles within selected areas it is advisable to take account of the emissions related to
vehicle start-up and engine warm-up on the parking areas and emissions of pollutants generated by fuel
evaporation. With these components the formula (1) may be rewritten as follows:

M i  10
where:
Pik ( t )

Tk ( t )

Qik

h
h
-6  h
  m N L   P (t )T (t )  Q
ik
k
k
ik
k
ik
k 1
k 1
k 1






(2)
specific emissions of i pollutant on vehicle start-up and engine warm-up in a vehicle
of the k-th type (according to ambient air temperature), g/min;
average time of vehicle`s start-up and engine warm-up for the k-th type vehicle
(according to temperature), min;
emissions of i pollutant due to fuel evaporation from k-th type vehicle.
It should be underlined that in spite of similarity of used approaches specific features of the Russian motor
vehicle fleet and conditions of its operation do not allow direct use for calculation of respective foreign specific
emission figures. These specific features include:




considerable congestion of urban transport networks and, hence, significant difference between real
traffic conditions and traffic conditions simulated in standard driving cycles;
significant share in the fleet and traffic of motor vehicles with obsolete construction and environmental
performances which are much lower than those for motor vehicles of similar environmental class in
European countries;
low efficiency of technical inspection of environmental performances of motor vehicles in use;
lower stability of СО and VOC content in exhaust gases of Russian motor vehicles according to growth
of their mileage.
As an example in the Table 1 there are presented average values of specific emissions from motor vehicles of
pre-EURO class in accordance with CORINAIR and NIIAT Methods.
In view of the above the Russian Methods for calculation of road transport emissions in biggest cities on the one
hand is fully harmonized with the European EMEP/CORINAIR Methods but on the other hand differs from it
by:



more differentiated classification of urban traffic conditions;
more differentiated categories of motor vehicles under review ;
taking into account of specific emission indices for the Russian motor vehicles of pre-Euro, Euro-1 and 2
environmental classes.
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
Table 1. Specific emissions indices used in CORINAIR and NIIAT Methods (example)
Specific emissions, g/km
Motor vehicle type
CO
VOC
NOx
NIIAT
CORINAIR
NIIAT
CORINAIR
NIIAT
CORINAIR
Car (gasoline)
19,8
8,22
3,6
1,33
1,4
1,9
Truck with total mass less than
3500 kg (gasoline)
26,8
13,5
3,9
1,69
2,7
2,44
Truck with total mass more
than 3500 kg (diesel)
3,0
3,54
1,6
3,51
8,7
4,18
As opposed to the CORINAIR Methods where emissions are evaluated by three characteristic traffic conditions
– urban traffic , suburban traffic and highway traffic, the NIIAT Methods for traffic conditions typical for
Moscow and other biggest cities considers 5 levels of scale for running emissions indices according to traffic
conditions:
I.П
I.МП
II
III
IV
trunk roads with controlled traffic and arterial urban streets of city-wide importance with controlled
traffic, arterial urban streets of city-wide importance with uninterrupted traffic and motorways and
also district-level streets during rush-hours at traffic speed of Vc≤ 15 km/h;
trunk roads with controlled traffic and arterial urban streets of city-wide importance with controlled
traffic
between rush-hours at traffic speed of Vc>15 km/h;
district-level streets between rush-hours at traffic speed of Vc>15 км/ч, local streets and roads;
arterial urban streets of city-wide importance with uninterrupted traffic at Vc> 15 km/h;
motorways at Vc > 15 km/h.
The large-scale block diagram of the calculation model for estimation of emissions used in the NIIAT's updated
Methods is shown in Fig.2. The model includes three calculation units:



calculation of mass emissions from moving motor vehicle (the so-called «hot emissions»);
calculation of mass emissions during engine start-up and warm-up («cold» emissions);
calculation of mass emissions due to fuel evaporation.
Specific road transport emissions data base
Running pollutant
Пробеговые
выбросы
emissions
preset
motor
ЗВ для for
расч.
типов
vehicle types
АТС
Pollutant ЗВ
emissions
from
Выбросы
на участках
running
on road
УДСtraffic
при streams
движении
network segments
трансп.
потоков
Traffic congestion
Интенсивность
structure
in road
иand
состав
трансп.
network
потока
на УДС
pollutant
Уд.Specific
выбросы
ЗВ при
emissions
ICE startпусках from
и прогреве
up and
warm-up
ДВС
Pollutant
emissions
Выбросы
ЗВ в
from
ICE warm-up
местах
стоянкиon
parking lots
при прогреве ДВС
Category and
Категория
и
road congestion
уровень
level
загрузки
дорог
Distance travelled
Пробег
(длина
(road network
участка
УДС)
segment length)
Specific
pollutant
Уд.
выбросы
ЗВ в
emissions
due to
результате
evaporation
испарения
Pollutant
emissions
Выбросы
ЗВ due
в to
fuel evaporation
on
результате
испарения
parking
lots
топлива
в местах
стоянки
Computationпериод
period
Расчетный
(24 hours,
month,
(сутки,
месяц,
quarter,
year)
квартал,
год)
Aggregate
Суммарные
pollutantЗВ
выбросы
emissions
Climatic
Климатические
characteristics
характеристики
Baseline data characterizing district and region obtained from investigation
Fig. 2 Block diagram of computational model for pollutant emissions evaluation
Fuel quality
Качество
топлива
(экологический
(ecological class)
класс)
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
The pollutant emissions from motor vehicles are also influenced by the type and quality of fuel used. The
regulations with stricter requirements to motor vehicle exhaust emissions and engine fuel quality adopted in
Russia in 2005-2008 accelerated the process of upgrading the fleet by vehicles with higher environmental
performances. Now the Russian fuel market offers gasoline and diesel fuel of Euro-3, -4, and -5 classes. In this
connection in NIIAT updated Methods in 2013 it was included calculation unit which takes account of the effect
of the used fuel quality on emissions. To obtain correction factors for NMVOC and non-rated pollutants specific
(running) emission indices for motor vehicles with gasoline engines there were used equations obtained within
the European program on emissions, fuels and engine design (EPEFE) (ACEA and Europe, 1996) and Russian
gasoline quality performances for different environmental classes (Table 2). In the Methods the effect of diesel
oil environmental class was taken into account regarding sulfur dioxide emission. With respect to other
substances in exhaust gases (CO, VOC, PM, etc.) correction of specific (running) emission indices was
abandoned due to insignificant changes in their concentration in exhaust gases emissions (below 5%).
Table 2. Correction factors used to take account of gasoline class effect on specific NMVOC and non-rated
pollutant emissions
Environmental motor vehicle class
Class 2
Gasoline class according to the Russian regulations
Class 3
Class 4
Class 5
Euro-0-2
Euro-3
Euro-4
1.0
1.110
1.168
0.901
1.0
1.053
0.856
0.950
1.0
0.847
0.940
0.989
Euro-5
1.181
1.064
1.011
1.0
3. The main results of the study
The important objective of the work was comparison of results of emissions calculation carried out by the use of
updated NIIAT Methods and CORINAIR Methods. To make such a comparison there was performed field study
of the traffic flow volume, its structure and traffic conditions at different time of the day on Volokolamsk
Highway in Moscow which is a typical city exit (outgoing) motorway with combined traffic conditions. Results
of calculation of some pollutants emission with the use of two approaches are shown in Table 3.
Table 3. Results of the test pollutant emissions calculation with the use of NIIAT and CORINAR Methods
Emissions, kg/day
CO
NOx
VOC
NMVOC
PM
NIIAT
3,761
415
356
350
4.49
CORINAIR
2,566
489
230
224
5.16
As it`s possible to see from the Table calculations made with the use of these Methods did not produce
identically equal results. The NIIAT and CORINAIR Methods displayed appreciable differences in estimation of
emissions of СО and volatile organic compounds (VOC, NMVOC and a group of unconventional substances)
and produced similar results relating to NOx (calculated on NO2 basis), РМ and a number of other substances. It
may be explained by a higher share in the traffic flow as compared to European countries of motor vehicles with
poor environmental performances which have no catalytic systems or are fitted with inadequately efficient
catalytic systems.
For verification of the Methods there was used the approach which based on comparison between ratios of
calculated emissions of various substances and measured concentrations of these substances in ambient air in the
roadside areas. Such comparison may not serve to be the grounds for conclusion relating to accuracy of
quantitative estimates obtained by the use of each Methods. But it enables qualitative comparison between
various Methods to be made.
To compare between concentration ratios of any substances in atmosphere in roadside areas and ratios of the
substance emissions the following conditions are to be met:


monitoring of concentrations in ambient air of compared pairs of substances is to be reliable and long
enough;
background concentrations of these substances typical of the city are to be known;
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris

assurance is required that emissions from motor vehicles form concentrations in ambient air of considered
substances on roadside areas.
In Moscow there are a few automated atmosphere pollution monitoring stations which are located near to
motorways and meet the above-mentioned conditions. Content of pollutants in ambient air is measured on the
year-round basis each 20 seconds. Total number of measurements per year exceeds 20,000.
For comparative evaluation of the Methods under study we have taken the СО/NOx concentration ratio. This
particular ratio of substances in ambient air and road transport emissions meets the said conditions most of all.
First automated atmosphere pollution monitoring stations exercise long monitoring of СО, NO and NO2 both in
the roadside area and in the background monitoring station. Secondly these are motor vehicles which form
concentrations of these substances near to major motorways.
In the NIIAT and CORINAIR Methods the values of nitrogen oxides emissions are taken as an aggregate of NO х
calculated on NO2 basis.
The ratios of CO/NOx concentrations were computed with consideration given to the urban background of the
said substances:
CO/NOx = (СОi – COФ)/(NOxi – NОxФ)
where:
СОi, NOxi

COФ,
NОxФ

(3),
measured concentrations of carbon oxide and nitrogen oxides on i-th station,
mg/m3;
background concentrations of carbon oxide and nitrogen oxides on the background
station (MSU), mg/m3.
For motorway sections located in vicinity of the foregoing automated atmosphere pollution monitoring stations
there were determined average annual concentrations of carbon monoxide and nitrogen oxides in 2012 which are
shown in Table 4.
Table 4. Average annual concentrations of carbon monoxide and nitrogen oxides in atmosphere in 2012
Station
СО, mg/m3
NO, mg/m3
NO2, mg/m3
NOx, mg/m3
MSU
0.26±0.003*
0.013±0.0003
0.041±0.00025
0.062±0.00081
0.69±0.006
0.061±0.0006
0.028±0.00013
0.121±0.0010
Veshnyaki
0.51±0.0048
0.026±0.0006
0.045±0.00024
0.085±0.0011
Kozhukhovski Lane
0.95±0.0082
0.060±0.0007
0.039±0.00024
0.131±0.0015
Moscow Automobile and Road
Construction Institute (MADI)
* confidence interval at reliability level 0.95
Means of ratios of average annual CO/NOx concentrations with the exception of background concentration are
given in Table 5. For the same road segments there were calculated pollutant emissions using the Methods in
question. Ratio between concentrations in ambient air on roadside areas and СО/NOx emissions are shown in
Fig. 3. The picture shows that CO/NOX ratio for emissions calculated by the use of NIIAT Methods is closer to
the ratio between real concentrations of these substances in atmosphere as compared to calculations using
CORINAIR Methods.
Table 5. Mean of average annual concentrations and concentration ratios of carbon oxide and nitrogen oxides
in ambient air
(СОst-СОb)/(NОxst-NОxb)
Station
MADI
(СОst-СОb), mg/m3
(NОxst-NОxb), mg/m3
0.43±0.0057
0.059±0.00084
7.3±0.1
Veshnyaki
0.25±0.0050
0.023±0.00091
10.9±0.2
Kozhukhovski Lane
0.69±0.0081
0.069±0.0013
10.0±0.1
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
12
Движение
по улицам
и дорогам
II
Traffic
on streets
and roads
of Category
категории (ст. Вешняки)
II (Veshnyaki station)
values
Отношение величин выбросов. НИИАТ
Ratio between
Отношение
величинemission
выбросов. CORINAR
values
Смешанный
режим
движения
(ст. МАДИ)
Combined
traffic
(MADI
station)
Ratio between emission values, NIIAT
Отношение концентраций
Ratio between concentrations
Отношение величин выбросов. НИИАТ
Ratio between
Отношение
величинemission
выбросов. CORINAR
0
Ratio between
concentrations
Отношение
концентраций
2
values
4
Ratio between
Отношение
величинemission
выбросов. CORINAR
Ratio
betweenвеличин
emission
values, NIIAT
Отношение
выбросов.
НИИАТ
6
Ratio Отношение
between concentrations
концентраций
(СО-СОф)/(Nox-NОxф)
8
Ratio between emission values, NIIAT
10
Traffic
on streets
and roads
of Category
Движение
по улицам
и дорогам
II
категории
(ст. Кожухорский
(Kozhukhovski
Laneпроезд)
station)
II
Fig.3. Ratio of СО/NOx concentrations in air on roadside areas and calculated values of their emissions
Except this for Volokolamsk Highway section studied before pollutant emissions were calculated at different
time of the day (Table 6). Average values of CO/NOx concentrations in ambient air during each hour have been
calculated using the data from MADI monitoring station in 2012. Number of in field studies pair for each hour
during a year reaches 1,000.
Diurnal changes in CO/NOx emissions and their concentrations in ambient air are shown in Figure 4.
Table 6. СО and NOx emissions from motor vehicles on Volokolamsk Highway at different time of the day
calculated by the use of NIIAT and CORINAIR Methods
Time of day
СО emissions, kg/period
NOx emissions, kg/period
NIIAT
NIIAT
CORINAIR
CORINAIR
Ratio between CO/NOx
emissions
NIIAT
CORINAIR
0 - 6 a.m.
173
81
41
39
4.21
2.09
6 - 12 a.m.
1,201
839
132
159
9.12
5.29
12 - 18 p.m.
1,133
779
125
149
9.06
5.22
18 - 24 p.m.
1,254
865
115
137
10.88
6.29
These comparisons give the possibility to conclude that NIIAT Methods for calculation of carbon monoxide
emission under real traffic conditions in Moscow provides for more correct results as compared to CORINAIR
Methods.
Similar verification with regard to other pollutants (VOC, NMVOC and non-rated pollutants) which had shown
slight differences in calculation by the use of these Methods (Table 3) is not possible for the time being due to
absence of information about background concentrations of these pollutants in atmosphere and availability of
other more powerful sources of such emissions in addition to road transport.
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
11
Отношение
концентраций
СО/NОx на станции
МАДИ
после
вычета
фоновых
концентраций
Ratio between
СО/NOx concentrations
on MADI
station
less
background
concentrations
Отошение
CO/NОx
в выбросах.
НИИАТ
CO/NOx ration
in emissions,
NIIAT
Отошение
CO/NОx
в выбросах.CORINAIR
CORINAIR
CO/NOx ration
in emissions,
10
9
(СО-СОф)/(Nox-NОxф)
8
7
6
5
4
3
2
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Время
Fig.4. Diurnal behaviour of ratios СО/NOx emissions and air concentrations
Nowadays the existing Methods is used for evaluation of efficiency of the measures to be taken to enhance
environmental safety of road transport in Moscow (switch of motor vehicles to gas fuel, control of fuel quality
on the market, various restrictions imposed on traffic of selected categories of motor vehicles etc.).
Application of the Methods may be illustrated by estimation of changes in “environmental danger” of traffic
flow composed from cars with gasoline engines for last 10 years.



traffic conditions on urban roads and streets of various categories;
motor vehicles environmental classification;
structure of engine fuel market by environmental classes.
In the Table 7 there are shown the starting conditions for calculations.
Table 7. Starting conditions for calculations
Parameter
Traffic conditions
Preconditions
5 levels according to NIIAT Methods (I.П, I.МП, II, III, IV)
Length of each predetermined segment
Traffic flow volume
Traffic flow structure
Fuel quality
1 km
1,000 vehicles/hour
Motor cars with gasoline engines of 1.4-2.0 l
Environmental class of gasoline corresponds to environmental class of motor
vehicle
Based on available statistics and study of the motor fleet structure in Moscow in calculation there was used the
following distribution of motor cars in traffic flow by their environmental classes in 2002 and 2012 as shown in
Fig.5. The results of calculations obtained are shown in Fig.6, 7, 8.
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
Структура потока
легковых
по экологическим
классам classes
в 2002 г.in
и 2002
2012 г.,
% 2012, %
Distribution
of motor
carsавтомобилей
in a traffic stream
by their ecological
and
80
74
70
year
Percent
in traffic stream,
Доля в транспортном
потоке, %
%
2002 год
2012 год
year
60
50
40
35
33
30
20
11
10
10
8
7
5
10
7
0
Евро-0
Евро-1
Euro
Euro
Евро-2
Евро-3
Euro
0
0
Евро-4
Евро-5
Euro
Euro
Экологический класс автомобилей
Euro
Ecological motor vehicle class
Fig.5. Distribution of motor cars in Moscow by their environmental classes in 2002 and 2012
0.7
Year
2002
Year
2012 год
Specific nitrogen oxide emissions [g/(km*s)] by a
unit motor car stream (1,000 motor cars/hour)
Specific carbon mono oxide emissions [g/(km*s)] by a
unit motor car stream (1,000 motor cars/hour)
10
8
6
4
2
0
I.П
I.МП
II
III
IV
Year
2012
Year
2002
0.6
0.5
0.4
0.3
0.2
0.1
0.0
I.П
Categories of urban roads and streets
I.МП
II
III
IV
Категорииroads
городских
дорог
и улиц
Categories of urban
and
streets
Fig.6 Changes in specific carbon mono oxide emissions
[g/(km*s)] for a traffic flow of 1,000 motor cars/hour on urban
roads and streets of various categories in 2002 and 2012.
Fig.7 Changes in specific nitrogen oxides emission [g/(km*s)]
for a traffic flow of 1,000 motor cars/hour on urban roads and
streets of various categories in 2002 and 2012.
Specific sulfur dioxide emissions [g/(km*s)] by a
Удельные
выбросы
диоксида
серы потоком
легковых
unit motor
car [г/(км*с)]
stream (1,000
motor
cars/hour)
автомобилей (1000 авт./час)
0.025
2002
year год
2012 year
год
2002
2012
0.020
0.015
0.010
0.005
0.000
I.П
II
I.МП
Категории
городских
дорог roads
и улиц
Categories
of urban
III
IV
and streets
Fig 8 Changes in specific sulfur dioxide emissions [g/(km*s)] for a traffic flow of 1,000 motor cars/hour on
urban roads and streets of various categories in 2002 and 2012
The results of calculated evaluation of changes in emissions from road transport for the city of Moscow using
NIIAT Methods are shown in Fig.9. Also it shows the size of motor vehicle fleet in Moscow in the same period.
Motor vehicle fleet, mln. of units
Emissions, thou t
Motor vehicle fleet, mln. of units
Vadim Donchenko, Yuli Kunin, Andrei Ruzski, Vladimir Vizhenski /Transport Research Arena 2014, Paris
Emissions, thou t
Fig.9 Evolution of pollutant emissions from road transport in Moscow (calculations)
4. Summary
There were compared the results of emissions calculation on the base of NIIAT and CORINAIR Methods with
the results of field studies. There was found out that NIIAT Methods for calculation of carbon monoxide
emissions under real conditions in Moscow provides for more correct results as compared to CORINAIR
procedure.
Numerical experiments have shown that the NIIAT Methods for calculation of emissions is sensitive to both
variations in traffic structure by environmental classes of motor vehicles and changes in traffic speed on urban
roads and streets.
Estimates made by the use of NIIAT Methods give the possibility to conclude that specific СО, NOx, SO2
emissions from traffic flows (in g/km*s) for the last 10 years dropped 4-5 times due to measures taken by
municipal authorities.
The NIIAT Methods makes it possible to take into consideration the effect of gasoline quality on emissions of
sulfur dioxide, hydrocarbons and a group of high toxic and carcinogens.
Calculations prove that drastic changes in the structure of traffic flows by environmental classes of vehicles and
appreciable replacement of old motor fleet with new vehicles compensated adverse effect on ambient air quality
in Moscow of motor fleet growth and city transport network overload. As a result growth of traffic congestions
in distance and time did not cause significant growth of СО and NOx emissions and concentrations in
atmosphere. Quite the opposite since 2005 emissions of these substances from road transport tend to drop while
since 2010 total amount of emissions has remained unchanged.
5. References
Annual governmental report «On condition and protection of environment in the Russian Federation» in 2009,
2010, and 2011.
Guidelines (Methods) for inventory of road transport emissions in the biggest cities, M., NIIAT OJSC, 2006.
A.V. Ruzski, Yu.I. Kunin, E.V. Parfenov «Environmental safety of motor vehicles under operation: rates and
control», M., «Journal of Automotive Engineers», No 3 (74) 2012.
V.V. Donchenko, Yu.I. Kunin, D.M. Kazmin, G.M. Sazonova «Reduction of adverse road transport effect on
environment and human health in cities», M., NIIAT OJSC Proceedings, 2010.