Sudhir Gota
Without reliable data, transport
emissions forecasting is as good as “fortune telling”
We
are investing millions of dollars in transport sector in developing countries
with minuscule data and inconsistent arguments.
In order to understand the implications of poor data, limited capacity
and institutional strength and black-box approach, let us consider the case of
India.
The
official estimates suggest that the total number of registered vehicles in the
country has increased from 5.4 million in 1981 to 99.6 million in 2007. Some
researchers argue that the total number of vehicles on road can be as high as
40% less than the total registered vehicles[1]
(say 60 million in 2007) and some industry reports suggest that the on-road
vehicular population exceeded 94.7 million in 2010[2].
The private vehicles once registered have 15 years validity. The information on
actual number of on-road commercial vehicles is more or less accurate as they
are registered every year. There is no annual record system of deregistration
or scrappage. This results in a huge variation in estimating total number of
active vehicles on road.
The
most official estimate of transport CO2 emissions is the 2007 green house gas
inventory[3].
It has been estimated that the road transport sector emitted, 121.21 million
tons of CO2 in 2007. Surprisingly, the same institution which quantified the
emissions had reported in a scientific journal[4]
that the total number of motor vehicles in 2000 was 48 million and the CO2
emissions from road transport sector is 105
million tons in 2000. Interestingly,
while the number of vehicles doubled in 7 years, the emissions increased by
only 16 million tons i.e. mere 15%.
The
below table summarizes the activity data availability at national level. This
is true for other developing countries also.
Sl.No
|
Parameter
|
Availability
|
Vehicle
|
Registered vehicles
|
Yes
|
PARC data (vehicles
on road)
|
No
|
|
Fuel split
|
No
|
|
Technology split
|
No
|
|
Average age
|
No
|
|
Emission factor
|
Yes
|
|
Activity
|
Average VKT/Year
|
No
|
Average VKT/Corridor
type
|
No
|
|
Average speed per
Corridor
|
No
|
|
Average occupancy
|
Yes ( city)
|
|
Average loading
|
Yes ( at corridor level)
|
The
data issues get magnified further in freight sector. For example, the general
lack of data and reliable data for India’s freight sector makes it difficult to
understand, plan and manage freight transport, and makes it virtually
impossible to measure the effectiveness of any policies to improve
competitiveness and efficiency. For example, at present there is no mechanism
in place for regular collecting and reporting data on freight and haulage (ton
kilometer or TKM). No comprehensive data on freight movement is available that
indicates origin, destination, type and size of freight carried on roads by
motorized transport[5].
Furthermore, freight transport is not segregated by different types of trucks
such as light commercial vehicles (LCVs), two-axle, three-axle, etc. As a
consequence, road infrastructure plans and investments and policies are based
on projections that have a high degree of variation and thus uncertainty, as
shown in below table for road freight activity in billion ton-km.
Different
Projections of Road Freight Activity in India
Year
|
Billion ton-km by road
|
Source
|
2001
|
1128
|
Road Transport
Demand Forecast for 2000 AD revisited and demand forecast for 2021
|
2005
|
317
|
SMP
Model-IEA
|
2005
|
656
|
The working
group report for Road Transport for the eleventh Five Year Plan
|
2007
|
518
|
Interim
report of the expert group on low carbon strategies for inclusive growth
|
2007
|
755
|
Building
India Transforming the nation’s logistics infrastructure
|
The
below figures summarizes many studies (14 different studies by reputed institutions) which have looked at road transport CO2
estimation and projections for business as usual growth for the Indian road
transport in future.
There
is no consistency (except that emissions are set to grow) among results
and such a huge variation in baseline for the CO2 transport emissions in future
in India is shocking.
1.
The variation in 2030 is approximately
three times i.e. from 395 to 1200 million tons of CO2 emissions.
2.
This variation in 2050 is from 743
million tons to 2300 million tons.
The
problem is not with only the future projections but also current estimates. For
example, the 2005 estimates vary from 98 to 216 million tons. (see below
figure)
If it is not even possible to establish the
baseline, how do we measure the impact of policies?
The
discussion is not India specific and it applies to many of our developing
countries. There is lack of transparency
with regards to data availability and quality which results in questionable
outcomes. Unfortunately we see little discussion on data availability and
quality even though they remain the cornerstone of policy formulation and
investments in transport sector.