Canada Wide Land-use Regression Models Created From Fixed Site Monitors and Validated With Independent City-specific Measurements

Hystad, Perry; Setton, Eleanor; Cervantes-Larios, Alejandro; Poplawski, Karla; Deschenes, Steeve; Martin, Randall V.; Donkelaar, Aaron van; Atari, Odwa; Demers, Paul A.

doi:10.1097/01.ede.0000392343.84709.4c

Cited by 2 publications

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“…Land use regression (LUR) has become a popular method to explore the spatial variation of outdoor air pollution in environmental studies and to assess the health risks of human exposure to pollutants in epidemiological and public health studies in Europe − and North America. − The application of LUR is also increasing in other regions. − The reason for such extensive applications of LUR models is mainly because it can be used to evaluate human exposure to air pollution in unmonitored areas and to identify urban air pollution hotspots which are vital to epidemiological and environmental studies …”

Section: Introductionmentioning

confidence: 99%

Developing Street-Level PM_2.5 and PM₁₀ Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Shi

Lau

2016

Environ. Sci. Technol.

137

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Monitoring street-level particulates is essential to air quality management but challenging in high-density Hong Kong due to limitations in local monitoring network and the complexities of street environment. By employing vehiclebased mobile measurements, land use regression (LUR) models were developed to estimate the spatial variation of PM 2.5 and PM 10 in the downtown area of Hong Kong. Sampling runs were conducted along routes measuring a total of 30 km during a selected measurement period of total 14 days. In total, 321 independent variables were examined to develop LUR models by using stepwise regression with PM 2.5 and PM 10 as dependent variables. Approximately, 10% increases in the model adjusted R 2 were achieved by integrating urban/ building morphology as independent variables into the LUR models. Resultant LUR models show that the most decisive factors on street-level air quality in Hong Kong are frontal area index, an urban/building morphological parameter, and road network line density and traffic volume, two parameters of road traffic. The adjusted R 2 of the final LUR models of PM 2.5 and PM 10 are 0.633 and 0.707, respectively. These results indicate that urban morphology is more decisive to the street-level air quality in highdensity cities than other cities. Air pollution hotspots were also identified based on the LUR mapping.

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Section: Introductionmentioning

confidence: 99%

Developing Street-Level PM_2.5 and PM₁₀ Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Shi

Lau

2016

Environ. Sci. Technol.

137

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Relationship between Land-Use Type and Daily Concentration and Variability of PM10 in Metropolitan Cities: Evidence from South Korea

Kim

Hong

2021

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Since urban areas with high air pollution are known to have higher mortality rates compared to areas with less air pollution, accurately understanding and predicting the distribution of particulate matter (PM) in cities is important for urban planning policies that seek to emphasize the health of citizens. Therefore, this study aims to investigate the relationship between PM and land use in metropolitan cities in South Korea using the land-use regression model. We use daily data from the air quality monitoring stations (AQMS) in seven cities in South Korea for the year 2018. For analysis, K-means clustering is employed to identify the land-use pattern surrounding the AQMSs and two log-lin regression models are used to investigate the effects of each land-use type on PM. The findings show a statistically significant difference in PM concentration and variability in the business, commercial, industrial, mixed, and high-density residential areas compared to parks and green areas, and that PM concentration and variability were less in mixed areas than in single land use, thus verifying the effectiveness of a mixed land-use planning strategy. Moreover, microclimatic, seasonal, and regional factors affect PM concentration and variability. Finally, to minimize exposure to PM, various policies such as mixed land use need to be established and implemented differently, depending on the season and time.

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Canada Wide Land-use Regression Models Created From Fixed Site Monitors and Validated With Independent City-specific Measurements

Cited by 2 publications

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Developing Street-Level PM_2.5 and PM₁₀ Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Developing Street-Level PM_2.5 and PM₁₀ Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Relationship between Land-Use Type and Daily Concentration and Variability of PM10 in Metropolitan Cities: Evidence from South Korea

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Canada Wide Land-use Regression Models Created From Fixed Site Monitors and Validated With Independent City-specific Measurements

Cited by 2 publications

References 0 publications

Developing Street-Level PM2.5 and PM10 Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Developing Street-Level PM2.5 and PM10 Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Relationship between Land-Use Type and Daily Concentration and Variability of PM10 in Metropolitan Cities: Evidence from South Korea

Contact Info

Product

Resources

About

Developing Street-Level PM_2.5 and PM₁₀ Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors

Developing Street-Level PM_2.5 and PM₁₀ Land Use Regression Models in High-Density Hong Kong with Urban Morphological Factors