Saving old cities: Land use regression model for traffic emissions in the Historical Peninsula of Istanbul

Research output: Contribution to journalArticle

Abstract

This study aims to develop a pollution distribution model for estimating traffic related intra-urban concentrations of nitrogen dioxide (NO 2 ) levels. Weekly concentrations of NO 2 were measured at 45 different locations in the Historical Peninsula of Istanbul during spring, summer and winter seasons in 2010. The range of NO 2 was 14.2-155 µg/m 3 . A land use regressing (LUR) model was developed to explore the impact of independent variables on the measured levels. Independent model variables were selected based on land use characteristics, traffic and road network information, and meteorological data. Results suggest that 150 metre range is the most effective buffer zone for NO 2 distribution characteristics in the study area. Average wind speed and temperature data have significant influences (up to 25%) on the prediction performances. Better estimations were produced for spring and winter seasons, particularly for in land stations compared with costal ones. As a result, the overall prediction performance of the constructed model is satisfactory (R 2 = 0.64).

Original languageEnglish
Pages (from-to)24-40
Number of pages17
JournalInternational Journal of Global Environmental Issues
Volume18
Issue number1
DOIs
Publication statusPublished - Jan 1 2019

Fingerprint

traffic emission
land use
traffic
regression
winter
buffer zone
nitrogen dioxide
road network
prediction
performance
wind velocity
pollution
city
summer
temperature
distribution

Keywords

  • Air pollution
  • Clean cities
  • Exposure modelling
  • Geographic information systems
  • Spatial regression

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Management, Monitoring, Policy and Law

Cite this

@article{bd489ca011104df9bbcff84afe9c19a6,
title = "Saving old cities: Land use regression model for traffic emissions in the Historical Peninsula of Istanbul",
abstract = "This study aims to develop a pollution distribution model for estimating traffic related intra-urban concentrations of nitrogen dioxide (NO 2 ) levels. Weekly concentrations of NO 2 were measured at 45 different locations in the Historical Peninsula of Istanbul during spring, summer and winter seasons in 2010. The range of NO 2 was 14.2-155 µg/m 3 . A land use regressing (LUR) model was developed to explore the impact of independent variables on the measured levels. Independent model variables were selected based on land use characteristics, traffic and road network information, and meteorological data. Results suggest that 150 metre range is the most effective buffer zone for NO 2 distribution characteristics in the study area. Average wind speed and temperature data have significant influences (up to 25{\%}) on the prediction performances. Better estimations were produced for spring and winter seasons, particularly for in land stations compared with costal ones. As a result, the overall prediction performance of the constructed model is satisfactory (R 2 = 0.64).",
keywords = "Air pollution, Clean cities, Exposure modelling, Geographic information systems, Spatial regression",
author = "Ferhat Karaca and Tugrul Yanik and Ali Turkyilmaz",
year = "2019",
month = "1",
day = "1",
doi = "10.1504/IJGENVI.2019.098893",
language = "English",
volume = "18",
pages = "24--40",
journal = "International Journal of Global Environmental Issues",
issn = "1466-6650",
publisher = "Inderscience Enterprises Ltd",
number = "1",

}

TY - JOUR

T1 - Saving old cities

T2 - Land use regression model for traffic emissions in the Historical Peninsula of Istanbul

AU - Karaca, Ferhat

AU - Yanik, Tugrul

AU - Turkyilmaz, Ali

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This study aims to develop a pollution distribution model for estimating traffic related intra-urban concentrations of nitrogen dioxide (NO 2 ) levels. Weekly concentrations of NO 2 were measured at 45 different locations in the Historical Peninsula of Istanbul during spring, summer and winter seasons in 2010. The range of NO 2 was 14.2-155 µg/m 3 . A land use regressing (LUR) model was developed to explore the impact of independent variables on the measured levels. Independent model variables were selected based on land use characteristics, traffic and road network information, and meteorological data. Results suggest that 150 metre range is the most effective buffer zone for NO 2 distribution characteristics in the study area. Average wind speed and temperature data have significant influences (up to 25%) on the prediction performances. Better estimations were produced for spring and winter seasons, particularly for in land stations compared with costal ones. As a result, the overall prediction performance of the constructed model is satisfactory (R 2 = 0.64).

AB - This study aims to develop a pollution distribution model for estimating traffic related intra-urban concentrations of nitrogen dioxide (NO 2 ) levels. Weekly concentrations of NO 2 were measured at 45 different locations in the Historical Peninsula of Istanbul during spring, summer and winter seasons in 2010. The range of NO 2 was 14.2-155 µg/m 3 . A land use regressing (LUR) model was developed to explore the impact of independent variables on the measured levels. Independent model variables were selected based on land use characteristics, traffic and road network information, and meteorological data. Results suggest that 150 metre range is the most effective buffer zone for NO 2 distribution characteristics in the study area. Average wind speed and temperature data have significant influences (up to 25%) on the prediction performances. Better estimations were produced for spring and winter seasons, particularly for in land stations compared with costal ones. As a result, the overall prediction performance of the constructed model is satisfactory (R 2 = 0.64).

KW - Air pollution

KW - Clean cities

KW - Exposure modelling

KW - Geographic information systems

KW - Spatial regression

UR - http://www.scopus.com/inward/record.url?scp=85064189372&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85064189372&partnerID=8YFLogxK

U2 - 10.1504/IJGENVI.2019.098893

DO - 10.1504/IJGENVI.2019.098893

M3 - Article

AN - SCOPUS:85064189372

VL - 18

SP - 24

EP - 40

JO - International Journal of Global Environmental Issues

JF - International Journal of Global Environmental Issues

SN - 1466-6650

IS - 1

ER -