Street-scale black carbon modelling over the West Midlands, United Kingdom: Sensitivity test of traffic emission factor adjustments
Environment International,
Год журнала:
2025,
Номер
196, С. 109265 - 109265
Опубликована: Янв. 10, 2025
Язык: Английский
Telematics data for geospatial and temporal mapping of urban mobility: Fuel consumption, and air pollutant and climate-forcing emissions of passenger cars
The Science of The Total Environment,
Год журнала:
2023,
Номер
894, С. 164940 - 164940
Опубликована: Июнь 20, 2023
In
this
study,
we
use
the
approach
of
geospatial
and
temporal
(GeoST)
mapping
urban
mobility
to
evaluate
speed-time-acceleration
profile
(dynamic
status)
passenger
cars.
We
then
a
pre-developed
model,
fleet
composition
real-world
emission
factor
(EF)
datasets
translate
vehicles
dynamics
status
into
real-urban
fuel
consumption
(FC)
exhaustive
(CO2
NOx)
emissions
with
high
spatial
(15
m)
(2
h)
resolutions.
Road
transport
in
West
Midlands,
UK,
for
2016
2018
is
scope
study.
Our
enables
analysis
influence
factors
such
as
road
slope,
non-rush/rush
hour
weed
days/weekends
effects
on
characteristics
environment.
The
results
show
that
NOx
EFs
reduced
by
more
than
14
%
2016-18.
This
can
be
attributed
increasing
contribution
Euro
6
63
%,
diesel
13
%.
However,
variations
FC
CO2
are
less
significant
(±2
%).
found
estimated
driving
under
NEDC
(National
European
Driving
Cycle)
qualified
benchmark
evaluating
FCs.
Considering
role
slope
increases
FC,
NOx,
weighted
average
4.8
3.9
3.0
respectively.
Time
travel
(non-rush/rush
or
days/weekends)
has
profound
effect
vehicle
related
emissions,
free-flowing
conditions.
Язык: Английский
A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques
npj Climate and Atmospheric Science,
Год журнала:
2024,
Номер
7(1)
Опубликована: Дек. 19, 2024
Abstract
Particulate
Matter
(PM)
air
pollution
poses
significant
threats
to
public
health.
We
introduce
a
novel
machine
learning
methodology
predict
PM
2.5
levels
at
30
m
long
segments
along
the
roads
and
temporal
scale
of
10
seconds.
A
hybrid
dataset
was
curated
from
an
intensive
campaign
in
Selly
Oak,
Birmingham,
UK,
utilizing
citizen
scientists
low-cost
instruments
strategically
placed
static
mobile
settings.
Spatially
resolved
proxy
variables,
meteorological
parameters,
properties
were
integrated,
enabling
fine-grained
analysis
.
Calibration
involved
three
approaches:
Standard
Random
Forest
Regression,
Sensor
Transferability
Road
Evaluations.
This
significantly
increased
spatial
resolution
beyond
what
is
possible
with
regulatory
monitoring,
thereby
improving
exposure
assessments.
The
findings
underscore
importance
approaches
science
advancing
our
understanding
pollution,
small
number
participants
enhancing
local
quality
assessment
for
thousands
residents.
Язык: Английский
Car rental fleet and demand management: An optimization framework
Elsevier eBooks,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
Язык: Английский
High spatio-temporal resolution estimation of urban road traffic carbon dioxide emissions and analysis of influencing factors using GPS trajectory data
Environmental Monitoring and Assessment,
Год журнала:
2025,
Номер
197(6)
Опубликована: Май 21, 2025
Язык: Английский
A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 9, 2024
Abstract
Particulate
Matter
(PM)
air
pollution
poses
significant
threats
to
public
health.
Existing
models
for
predicting
PM
levels
range
from
Chemical
Transport
Models
statistical
approaches,
with
Machine
Learning
(ML)
tools
showing
superior
performance
due
their
ability
capture
highly
non-linear
atmospheric
responses.
This
research
introduces
a
novel
methodology
leveraging
ML
predict
PM
2.5
at
fine
spatial
resolution
of
30
metres
and
temporal
scale
10
seconds.
The
aims
demonstrate
its
proficiency
in
estimating
missing
measurements
urban
areas
that
lack
direct
observational
data.
A
hybrid
dataset
was
curated
an
intensive
aerosol
campaign
Selly
Oak,
Birmingham,
UK,
utilizing
citizen
scientists
low-cost
Optical
Particle
Counters
(OPCs)
strategically
placed
both
static
mobile
settings.
Spatially
resolved
proxy
variables,
meteorological
parameters,
properties
were
integrated,
enabling
fine-grained
analysis
distribution
along
road
segments.
Calibration
involved
three
approaches:
Standard
Random
Forest
Regression,
Sensor
Transferability
Evaluation,
Road
Evaluation.
Results
demonstrated
high
predictive
accuracy
(R
2
=
0.85,
MAE
1.60
µg
m
−³)
the
standard
RF
model.
transferability
evaluations
exhibited
robust
generalization
capabilities
across
different
sensors
(best
R
2
0.65,
2.76
types
0.71,
2.46
m
−³),
respectively.
has
potential
significantly
enhance
beyond
regulatory
monitoring
infrastructure,
thereby
refining
quality
predictions
improving
exposure
assessments.
findings
underscore
importance
ML-based
approaches
advancing
our
understanding
dynamics
implications
paper
important
science
initiatives,
as
it
suggests
contributions
small
number
participants
can
local
patterns
many
1000s
residents.
Язык: Английский
Mapping noise and pollutant emissions hotspots: Driving behavior and vehicle features based-analysis
Transportation Research Part D Transport and Environment,
Год журнала:
2024,
Номер
136, С. 104466 - 104466
Опубликована: Окт. 22, 2024
Язык: Английский
Assessing the Impact of Calendar Events upon Urban Vehicle Behaviour and Emissions Using Telematics Data
Smart Cities,
Год журнала:
2024,
Номер
7(6), С. 3071 - 3094
Опубликована: Окт. 24, 2024
Employing
vehicle
telematics
data,
this
study
investigates
the
transport
environment
across
urban
and
major
road
networks
during
a
two-week
period
encompassing
Easter
holidays,
considered
as
case
study.
The
analysis
spans
four
distinct
years:
2016,
2018,
2021,
2022.
Geospatial
Temporal
Mapping
captured
dependencies
of
speed,
acceleration,
vehicle-specific
power
(VSP),
emission
factors
(EFs)
for
air
pollutants
(CO2
NOx)
on
studied
calendar
period.
results
showed
that
holiday,
median
speeds
exceeded
annual
averages
by
roughly
5%,
indicating
clear
deviation
from
regular
traffic
patterns.
This
was
particularly
stark
2021
lockdown,
with
significant
drop
in
presence,
leading
to
less
congestion
thus
higher
acceleration.
emissions
analyses
revealed
individual
cars
emit
levels
CO2
NOx
Easter.
Specifically,
values
EF
were
9%
11%
than
norm.
When
combined
occupancy
demonstrate
holidays
2022
had
variable
impact
emissions,
reductions
roads
weekday
rush
hours
(15–25%)
but
slight
increases
weekend
periods.
Язык: Английский
An in-use Comparative Analysis of Diesel, CNG, and Electric Buses for a Small Island Developing State
Transportation in Developing Economies,
Год журнала:
2024,
Номер
11(1)
Опубликована: Ноя. 26, 2024
Язык: Английский
Research on Construction Technology of Communication Mechanical and Electrical Engineering
Voice of the Publisher,
Год журнала:
2024,
Номер
10(01), С. 83 - 89
Опубликована: Янв. 1, 2024
Research
on
Construction
Technology
of
Communication
Mechanical
and
Electrical
Engineering
Today,
with
the
accelerated
development
communication
engineering,
mechanical
electrical
industry,
as
an
important
pillar
industry
national
economy,
has
rapidly
developed,
laying
a
good
foundation
for
construction
engineering.
In
this
context,
quality
control
engineering
become
urgent
task,
it
is
necessary
to
strengthen
unified
management
equipment
ensure
installation
overall
equipment.
The
article
starts
entire
process
construction,
analyzes
in
detail
factors
that
affect
proposes
specific
methods,
hoping
provide
some
reference
construction.
Язык: Английский