Spatio-temporal modeling of the impact of climate change on road accidents: A Case Study of New Brunswick

Shohel Amin, Alireza Zareie, Luis Amador

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

The objective of this research is to study the impact of climate change on the hazardous weather-related road accidents. The New Brunswick province of Canada is considered as a case study. The study uses road accident data collected from police accident reports for the period of 1997-2007. The climate change modeling uses thirty-year weather records of seven climate zones of New Brunswick, National Centers for Environmental Prediction (NCEP) re-analysis dataset, and large-scale simulation data from the Canadian Global Circulation Model, General Climate Model, and Coupled Global Climate Model (CGCM3). The large-scale simulation data from CGCM under SRES-A2 scenario during 21st century are used to model the climate in the future. This study develops an Exposure to Weather-Accident Severity (EWAS) index and estimate the relationship between EWAS index and weather-related explanatory variables of road accidents by applying negative binomial regression and Poisson regression models. The regression models find out that surface-weather condition, weather-driver’s gender, weather-driver’s age, weather-driver’s experience and weather-vehicle’s age have strong positive correlation with EWAS index. The surface-road alignment and surface-road characteristics have negative relationship with EWAS index. The spatial pattern of EWAS index with respect to weather-related explanatory variables is examined for the fifteen census divisions of New Brunswick province, which derives similar relationships. The climate change modeling estimates that the number of rainy days may increase in all climate zones and the number of snowy days and freezing days may decrease or stay the same in most of the climate zones during three 30-year periods of 21st century (i.e. 2011-2040, 2041-2070, 2071-2100). The findings of this study imply that more hazardous weather in future will result in increased accident severity.
Original languageEnglish
Title of host publicationFederal Committee on Statistical Methodology Research Conference 2013
Number of pages15
Publication statusPublished - 4 Nov 2013
EventFederal Committee on Statistical Methodology Research Conference 2013 - Washington Convention Center, Washington DC, United States
Duration: 4 Nov 20136 Nov 2013
http://www.copafs.org/seminars/fcsm2013research.aspx

Conference

ConferenceFederal Committee on Statistical Methodology Research Conference 2013
Abbreviated titleFCSM 2013
CountryUnited States
CityWashington DC
Period4/11/136/11/13
Internet address

Fingerprint

accident
road
weather
climate change
modeling
twenty first century
climate
climate modeling
simulation
freezing
general circulation model
global climate
census
gender
exposure
index

Keywords

  • Accident severity
  • Climate change
  • Statistical downscaling
  • Negative binomial regression
  • Poisson regression

Cite this

Amin, S., Zareie, A., & Amador, L. (2013). Spatio-temporal modeling of the impact of climate change on road accidents: A Case Study of New Brunswick. In Federal Committee on Statistical Methodology Research Conference 2013

Spatio-temporal modeling of the impact of climate change on road accidents : A Case Study of New Brunswick. / Amin, Shohel; Zareie, Alireza; Amador, Luis.

Federal Committee on Statistical Methodology Research Conference 2013. 2013.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Amin, S, Zareie, A & Amador, L 2013, Spatio-temporal modeling of the impact of climate change on road accidents: A Case Study of New Brunswick. in Federal Committee on Statistical Methodology Research Conference 2013. Federal Committee on Statistical Methodology Research Conference 2013, Washington DC, United States, 4/11/13.
Amin S, Zareie A, Amador L. Spatio-temporal modeling of the impact of climate change on road accidents: A Case Study of New Brunswick. In Federal Committee on Statistical Methodology Research Conference 2013. 2013
Amin, Shohel ; Zareie, Alireza ; Amador, Luis. / Spatio-temporal modeling of the impact of climate change on road accidents : A Case Study of New Brunswick. Federal Committee on Statistical Methodology Research Conference 2013. 2013.
@inproceedings{b21f18099cb141d5a1e23894ef1e26c4,
title = "Spatio-temporal modeling of the impact of climate change on road accidents: A Case Study of New Brunswick",
abstract = "The objective of this research is to study the impact of climate change on the hazardous weather-related road accidents. The New Brunswick province of Canada is considered as a case study. The study uses road accident data collected from police accident reports for the period of 1997-2007. The climate change modeling uses thirty-year weather records of seven climate zones of New Brunswick, National Centers for Environmental Prediction (NCEP) re-analysis dataset, and large-scale simulation data from the Canadian Global Circulation Model, General Climate Model, and Coupled Global Climate Model (CGCM3). The large-scale simulation data from CGCM under SRES-A2 scenario during 21st century are used to model the climate in the future. This study develops an Exposure to Weather-Accident Severity (EWAS) index and estimate the relationship between EWAS index and weather-related explanatory variables of road accidents by applying negative binomial regression and Poisson regression models. The regression models find out that surface-weather condition, weather-driver’s gender, weather-driver’s age, weather-driver’s experience and weather-vehicle’s age have strong positive correlation with EWAS index. The surface-road alignment and surface-road characteristics have negative relationship with EWAS index. The spatial pattern of EWAS index with respect to weather-related explanatory variables is examined for the fifteen census divisions of New Brunswick province, which derives similar relationships. The climate change modeling estimates that the number of rainy days may increase in all climate zones and the number of snowy days and freezing days may decrease or stay the same in most of the climate zones during three 30-year periods of 21st century (i.e. 2011-2040, 2041-2070, 2071-2100). The findings of this study imply that more hazardous weather in future will result in increased accident severity.",
keywords = "Accident severity, Climate change, Statistical downscaling, Negative binomial regression, Poisson regression",
author = "Shohel Amin and Alireza Zareie and Luis Amador",
year = "2013",
month = "11",
day = "4",
language = "English",
booktitle = "Federal Committee on Statistical Methodology Research Conference 2013",

}

TY - GEN

T1 - Spatio-temporal modeling of the impact of climate change on road accidents

T2 - A Case Study of New Brunswick

AU - Amin, Shohel

AU - Zareie, Alireza

AU - Amador, Luis

PY - 2013/11/4

Y1 - 2013/11/4

N2 - The objective of this research is to study the impact of climate change on the hazardous weather-related road accidents. The New Brunswick province of Canada is considered as a case study. The study uses road accident data collected from police accident reports for the period of 1997-2007. The climate change modeling uses thirty-year weather records of seven climate zones of New Brunswick, National Centers for Environmental Prediction (NCEP) re-analysis dataset, and large-scale simulation data from the Canadian Global Circulation Model, General Climate Model, and Coupled Global Climate Model (CGCM3). The large-scale simulation data from CGCM under SRES-A2 scenario during 21st century are used to model the climate in the future. This study develops an Exposure to Weather-Accident Severity (EWAS) index and estimate the relationship between EWAS index and weather-related explanatory variables of road accidents by applying negative binomial regression and Poisson regression models. The regression models find out that surface-weather condition, weather-driver’s gender, weather-driver’s age, weather-driver’s experience and weather-vehicle’s age have strong positive correlation with EWAS index. The surface-road alignment and surface-road characteristics have negative relationship with EWAS index. The spatial pattern of EWAS index with respect to weather-related explanatory variables is examined for the fifteen census divisions of New Brunswick province, which derives similar relationships. The climate change modeling estimates that the number of rainy days may increase in all climate zones and the number of snowy days and freezing days may decrease or stay the same in most of the climate zones during three 30-year periods of 21st century (i.e. 2011-2040, 2041-2070, 2071-2100). The findings of this study imply that more hazardous weather in future will result in increased accident severity.

AB - The objective of this research is to study the impact of climate change on the hazardous weather-related road accidents. The New Brunswick province of Canada is considered as a case study. The study uses road accident data collected from police accident reports for the period of 1997-2007. The climate change modeling uses thirty-year weather records of seven climate zones of New Brunswick, National Centers for Environmental Prediction (NCEP) re-analysis dataset, and large-scale simulation data from the Canadian Global Circulation Model, General Climate Model, and Coupled Global Climate Model (CGCM3). The large-scale simulation data from CGCM under SRES-A2 scenario during 21st century are used to model the climate in the future. This study develops an Exposure to Weather-Accident Severity (EWAS) index and estimate the relationship between EWAS index and weather-related explanatory variables of road accidents by applying negative binomial regression and Poisson regression models. The regression models find out that surface-weather condition, weather-driver’s gender, weather-driver’s age, weather-driver’s experience and weather-vehicle’s age have strong positive correlation with EWAS index. The surface-road alignment and surface-road characteristics have negative relationship with EWAS index. The spatial pattern of EWAS index with respect to weather-related explanatory variables is examined for the fifteen census divisions of New Brunswick province, which derives similar relationships. The climate change modeling estimates that the number of rainy days may increase in all climate zones and the number of snowy days and freezing days may decrease or stay the same in most of the climate zones during three 30-year periods of 21st century (i.e. 2011-2040, 2041-2070, 2071-2100). The findings of this study imply that more hazardous weather in future will result in increased accident severity.

KW - Accident severity

KW - Climate change

KW - Statistical downscaling

KW - Negative binomial regression

KW - Poisson regression

M3 - Conference proceeding

BT - Federal Committee on Statistical Methodology Research Conference 2013

ER -