The
continuous
release
of
pollutants
has
posed
a
significant
threat
to
both
public
health
and
the
sustainability
environment.
Consequently,
governments
across
globe
have
introduced
more
stringent
rules
pertaining
vehicle
emissions
address
this
issue.
In
addition,
Portable
Emission
Measurement
System
(PEMS)
is
now
most
widely
used
approach
for
detecting
NOx
PN
from
heavy-duty
vehicles
on
real
roads.
However,
technology
associated
with
requirements
in
terms
human
labor
resources,
making
it
expensive
time-consuming.
Hence,
imperative
put
up
novel
surveillance
actual
on-road
emissions.
Prior
research
indicated
potential
employing
soft
sensors
as
an
alternative
physical
purpose
CO2
monitoring.
there
exists
scarcity
scholarly
investigations
monitoring
PN.
present
study
presents
sensor
based
combination
genetic
algorithm
(GA)
gated
recurrent
unit
(GRU)
real-time
nitrogen
oxides
(NOx)
particle
number
(PN)
within
on-board
diagnostics
(OBD)
system.
This
addresses
existing
gap
development
specifically
designed
study,
we
evidence
that
described
exhibits
exceptional
R2
values
outperforms
other
conventional
models.
Our
findings
illustrate
operate
by
effectively
eliminating
outliers
accurately
promptly
consistently
tracking
predictions
over
lifespan
vehicle.
Moreover,
our
model
high
degree
reusability
domain
prediction
possesses
addressing
emission
emerging
gas
pollutant
constituents
forthcoming
times.
International Journal of Sustainable Transportation,
Journal Year:
2024,
Volume and Issue:
18(7), P. 589 - 604
Published: July 15, 2024
The
widening
gap
between
real-world
vehicle
energy
consumption
and
modeled
predictions
can
be
attributed
to
discrepancies
actual
ambient
temperatures
assumptions
made
in
laboratory
tests.
This
study
collected
a
detailed,
extensive
dataset
comprising
25,640,666
records
of
operating
(speed,
acceleration,
etc.)
fuel
data
alongside
124,938
hourly
meteorological
profiles
(temperature,
relative
humidity,
etc.).
High-resolution
rates
(FCRs)
based
on
temperature
were
developed,
adjustment
factors
introduced
specific
power
(VSP)
binning.
Fuel
(FCFs)
compared
across
different
by
incorporating
VSP
distributions
the
adjusted
FCRs,
revealing
larger
FCFs
at
extreme
moderate
ones.
inventories,
both
with
without
adjustments,
evaluated.
results
indicated
6%
underestimation
annual
Beijing
when
disregarding
adjustments.
variation
was
observed
months
(in
July
August,
underestimations
reach
11%)
bins
(larger
impact
low
bins).
relationship
FCR
is
similar
quadratic
curve,
lowest
occurring
10
°C–20
°C.
FCF
factor
does
not
vary
speed
intervals
cold
weather
remains
stable
approximately
1.15
−10
°C,
but
it
drops
from
1.25
1
as
increases
5
100
km/h
hot
weather.
underscores
importance
considering
modeling
necessity
temperature-adjusted
approaches
for
accurate
estimations.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(17), P. 7526 - 7526
Published: Aug. 30, 2024
Reducing
vehicle
emissions
and
minimizing
the
impact
of
transportation
industry
on
environment
are
key
to
achieving
global
sustainable
development
goals.
China-6
standard
requires
light-duty
gasoline
vehicles
meet
limit
requirements
for
particulate
number
(PN)
emissions.
Therefore,
must
also
be
equipped
with
a
filter
(GPF)
in
addition
three-way
catalytic
converter
(TWC)
within
durability
mileage
200,000
km.
Currently,
there
is
very
little
research
GPF
degradation
fuel
economy
vehicles,
especially
newly
restricted
N2O
This
study
adopts
test
method
deterioration
driving
mileage.
The
results
show
that
still
after
km,
factors
various
emission
pollutants
less
than
recommended
factors.
vehicle’s
carbon
dioxide
(CO2)
consumption
increase
by
3%,
indicating
aging
components,
including
TWC
GPF,
has
no
significant
economy.
Environment International,
Journal Year:
2024,
Volume and Issue:
193, P. 109119 - 109119
Published: Nov. 1, 2024
Accurately
estimating
vehicle
emissions
is
crucial
for
effective
air
quality
management.
As
key
data
emission
inventory
construction,
factors
(EFs)
are
influenced
by
usage
characteristics
and
experience
deterioration.
Current
deterioration
models
often
employ
single-factor
approaches
based
on
age
or
accumulated
mileage,
which
fail
to
capture
the
effects
of
varying
intensities
within
same
mileage
intervals.
This
study
addressed
this
limitation
developing
a
novel
model
that
incorporates
multi-dimensional
utilizes
large-scale
inspection
maintenance
(I/M)
dataset
light-duty
gasoline
vehicles
(LDGVs).
The
modeling
results
reveal
distinct
patterns
different
pollutants
highlight
synergistic
duration
intensity:
natural
aging
significantly
impacts
HC
NOx
emissions,
while
CO
more
strongly
affected
intensive
use.
Specifically,
China
V
LDGVs
were
driven
4
×
10
The
continuous
release
of
pollutants
has
posed
a
significant
threat
to
both
public
health
and
the
sustainability
environment.
Consequently,
governments
across
globe
have
introduced
more
stringent
rules
pertaining
vehicle
emissions
address
this
issue.
In
addition,
Portable
Emission
Measurement
System
(PEMS)
is
now
most
widely
used
approach
for
detecting
NOx
PN
from
heavy-duty
vehicles
on
real
roads.
However,
technology
associated
with
requirements
in
terms
human
labor
resources,
making
it
expensive
time-consuming.
Hence,
imperative
put
up
novel
surveillance
actual
on-road
emissions.
Prior
research
indicated
potential
employing
soft
sensors
as
an
alternative
physical
purpose
CO2
monitoring.
there
exists
scarcity
scholarly
investigations
monitoring
PN.
present
study
presents
sensor
based
combination
genetic
algorithm
(GA)
gated
recurrent
unit
(GRU)
real-time
nitrogen
oxides
(NOx)
particle
number
(PN)
within
on-board
diagnostics
(OBD)
system.
This
addresses
existing
gap
development
specifically
designed
study,
we
evidence
that
described
exhibits
exceptional
R2
values
outperforms
other
conventional
models.
Our
findings
illustrate
operate
by
effectively
eliminating
outliers
accurately
promptly
consistently
tracking
predictions
over
lifespan
vehicle.
Moreover,
our
model
high
degree
reusability
domain
prediction
possesses
addressing
emission
emerging
gas
pollutant
constituents
forthcoming
times.
