Effects of land use patterns on PM10 concentrations in urban and suburban areas. A European scale analysis

被引:7
作者
Sohrab, Seyedehmehrmanzar [1 ]
Csikos, Nandor [2 ,3 ]
Szilassi, Peter [1 ]
机构
[1] Univ Szeged, Dept Geoinformat Phys & Environm Geog, Egyet U 2-6, H-6722 Szeged, Hungary
[2] HUN REN Ctr Agr Res, Inst Soil Sci, Dept Soil Mapping & Environm Informat, Herman Otto Ut 15, H-1022 Budapest, Hungary
[3] MTA SZTE Lendulet Appl Ecol Res Grp, Koze Fasor 52, H-6726 Szeged, Hungary
关键词
Land use; Urban Atlas; Stepwise GLM model; Landscape pattern; PM10; AIR-QUALITY; PARTICULATE MATTER; HEAT-ISLAND; GREEN INFRASTRUCTURE; SOURCE APPORTIONMENT; POLLUTION; IMPROVEMENT; FORESTS; PM2.5;
D O I
10.1016/j.apr.2023.101942
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Landscape structure, the spatial characteristic of land cover, is a key factor in air quality. In this study, we investigate the connection between different land-use category areas taken from the 2018 Urban Atlas and the European Environmental Agency's monthly average coarse particulate matter (PM10) concentrations. We iden-tified the main PM10 emission-source land-use categories that restrict the transmission of PM10 and therefore reduce PM10 concentrations in urban and suburban areas. According to our results, water, forest and urban park areas inside differently sized buffer zones surrounding PM10 monitoring stations have an obvious clearing effect on PM10 concentrations throughout almost all seasons, while there is a positive correlation between areas of vacant land, railways and mine, dump and construction sites and monthly PM10 concentrations. In addition, the strong effect of the correlation between built-up areas, industrial areas and roads and monthly average PM10 concentrations changes seasonally. Air pollution from motor vehicles shows a significant positive statistical relationship with PM10 concentrations only in the summer, but in contrast, during the heating (cold) period, because of motor vehicle driving (secondary) winds, traffic corridors have a significant decreasing effect on PM10 concentrations. By understanding the effect of different land use/land cover patterns on PM10 concentrations and variability, we can derive precise spatial urban planning strategies that are adaptable for health care.
引用
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页数:20
相关论文
共 74 条
[1]   Recreational preferences along a naturalness-development continuum: Results from surveys in two unequal urban forests in Europe [J].
Aasetre, Jorund ;
Gundersen, Vegard ;
Vistad, Odd Inge ;
Holtrop, Egbert J. .
JOURNAL OF OUTDOOR RECREATION AND TOURISM-RESEARCH PLANNING AND MANAGEMENT, 2016, 16 :58-68
[2]   Evaluation of comparing urban area land use change with Urban Atlas and CORINE data [J].
Aksoy, Talha ;
Dabanli, Ahmet ;
Cetin, Mehmet ;
Kurkcuoglu, Muzeyyen Anil Senyel ;
Cengiz, Adem Emre ;
Cabuk, Saye Nihan ;
Agacsapan, Balca ;
Cabuk, Alper .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (19) :28995-29015
[3]   Spatial identification and temporal prediction of air pollution sources using conditional bivariate probability function and time series signature [J].
Althuwaynee, Omar F. ;
Pokharel, Badal ;
Aydda, Ali ;
Balogun, Abdul-Lateef ;
Kim, Sang-Wan ;
Park, Hyuck-Jin .
JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY, 2021, 31 (04) :709-726
[4]   Present and future Koppen-Geiger climate classification maps at 1-km resolution [J].
Beck, Hylke E. ;
Zimmermann, Niklaus E. ;
McVicar, Tim R. ;
Vergopolan, Noemi ;
Berg, Alexis ;
Wood, Eric F. .
SCIENTIFIC DATA, 2018, 5
[5]   Major air pollutants seasonal variation analysis and long-range transport of PM10 in an urban environment with specific climate condition in Transylvania (Romania) [J].
Bodor, Zsolt ;
Bodor, Katalin ;
Keresztesi, Agnes ;
Szep, Robert .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 27 (30) :38181-38199
[6]   Sample size requirements for estimating Pearson, Kendall and Spearman correlations [J].
Bonett, DG ;
Wright, TA .
PSYCHOMETRIKA, 2000, 65 (01) :23-28
[7]  
Calcagno V, 2010, J STAT SOFTW, V34, P1
[8]   A study of the particulate matter PM10 composition in the atmosphere of Chillan, Chile [J].
Celis, JE ;
Morales, JR ;
Zaror, CA ;
Inzunza, JC .
CHEMOSPHERE, 2004, 54 (04) :541-550
[9]  
Chang Xueli, 2022, ISCTT 2022
[10]  
7th International Conference on Information Science, Computer Technology and Transportation, P1