Air quality and its response to satellite-derived urban form in the Yangtze River Delta, China

She, Qiannan; Peng, Xia; Xu, Qian; Long, Lingbo; Wei, Ning; Liu, Min; Jia, Wenxiao; Zhou, Taoye; Han, Ji; Xiang, Wei-Ning

doi:10.1016/j.ecolind.2016.12.045

Cited by 140 publications

(81 citation statements)

References 43 publications

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“…From this, we can see that air pollution has a considerable impact on the sustainable development of cities [1][2][3]. In addition, numerous studies have shown that air pollution has a significant impact on human health [4][5][6]. The most common air pollutants in cities include carbon dioxide (CO 2 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), hydrocarbons (HC), suspended particulate matter (SPM, including PM10, PM2.5), heavy metals (HM), ozone (O 3 ), smog, and chlorofluorocarbons (CFC).…”

Section: Introductionmentioning

confidence: 83%

“…The deterioration of air quality in urban areas is often closely related to urban development, public facilities, and traffic patterns. As urbanization has resulted in rapid population growth and increased economic activities, this has led to changes in land use and transportation modes, which have also led to a significant increase in energy consumption and the massive emission of air pollutants, thereby exacerbating the current state of air pollution [6,8,9]. The appropriate implementation of urban planning also has a significant impact on the air quality of the same areas and the possible extent of air quality deterioration [10].…”

Section: Introductionmentioning

confidence: 99%

“…Based on the aforementioned studies, we can see that research on urban land use and air quality is becoming increasingly important. Nevertheless, it is not only the types of land use, but also the patterns and structures of land use that can have an impact on urban functions and air pollution [2,6,13,16]. More specifically, the impact of urban land use patterns on pollutant emissions can be explored through population density, emissions from motorized vehicles, and street layout among other factors [2,14,15].…”

Section: Introductionmentioning

confidence: 99%

“…More specifically, the impact of urban land use patterns on pollutant emissions can be explored through population density, emissions from motorized vehicles, and street layout among other factors [2,14,15]. Therefore, gaining a better understanding of the relationship between urban spatial patterns and air quality will help us to determine the most effective use of urban land that will enable the healthier development of cities [6,17]. Liu and Shen [18] focused on the pattern in changes in green spaces within the Taipei Metropolitan area in order to investigate their impact on air pollution.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Ku¹

2020

Sustainability

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The deterioration of air quality in urban areas is often closely related to urbanization, as this has led to a significant increase in energy consumption and the massive emission of air pollutants, thereby exacerbating the current state of air pollution. However, the relationship between urban development and air quality is complex, thus making it difficult to be analyzed using traditional methods. In this paper, a framework integrating spatial analysis and statistical methods (based on 170 regression models) is developed to explore the spatial and temporal relationship between urban land use patterns and air quality, aiming to provide solid information for mitigation planning. The thresholds for the influence of urban patterns are examined using different buffer zones. In addition, the differences in the effects of various types of land use pattern on air quality were also explored. The results show that there were significant differences between 1999 and 2013 with regards to the correlations between land use patterns and air pollutant concentrations. Among all land uses, forest, water and built-up areas were proved to influence concentrations the most. It is suggested that the developed framework should be applied further in the real-world mitigation planning decision-making process Sustainability 2020, 12, x FOR PEER REVIEW 3 of 16 (AWMPFD), Shannon's diversity index (SHDI), and Shannon's evenness index (SHEI) of residential 95 areas were highly correlated with acoustic noise level and PM10 concentration. Furthermore, higher 96 ED and PD of built-up areas led to higher acoustic noise levels and PM10 concentration. Detailed 97 definition of the landscape metrics mentioned above could be found in [5,16,19]. 98In order to gain a deeper understanding of the effectiveness of strategies for improving future 99 urban air quality, integrated research methods, including the quantification of urban spatial patterns 100 and structures and the correlation analysis between air quality and urban form, should be carried 101 out. In view of this, a spatiotemporal analytical framework is constructed in this study, which 102 involves first a correlation analysis between land use type indicators and air quality indicators at 103 different spatial distances, followed by multiple sets of regression analysis based on data from 104 different years. Our aim is to clearly quantify the correlation between different land use patterns and 105 air quality in cities, which can serve as a reference for the future formulation of mitigation and 106 adaptation planning strategies. This study will calculate the land use patterns within the different 107 buffer radii of air quality monitoring stations and will explore the association between urban land 108 use patterns and air quality using statistical analysis in order to serve as an important reference for 109 the formulation of adaptation strategies related to air quality, which can benefit future land use 110 planning. This proposed framework aims to provide useful information for public sec...

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Section: Introductionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Ku¹

2020

Sustainability

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“…Six landscape metrics are calculated for 25 cities in Yangtze River Delta, China from the artificial surface class of GlobeLand30, including total urban area (CA), number of urban patches (NP), largest patch index (LPI), mean perimeter-area ratio (PARA MN), mean Euclidean nearest neighbor distance (ENN MN), and traffic coupling factor (CF) with a spatial pattern analysis program FRAGSTATS 4.2 [66,67]. These metrics were used to analyze the relationship between urban forms and air quality.…”

Section: Status and Change Analysismentioning

confidence: 99%

Analysis and Applications of GlobeLand30: A Review

Chen

Cao

Peng

et al. 2017

IJGI

157

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GlobeLand30, donated to the United Nations by China in September 2014, is the first wall-to-wall 30 m global land cover (GLC) data product. GlobeLand30 is widely used by scientists and users around the world. This paper provides a review of the analysis and applications of GlobeLand30 based on its data-downloading statistics and published studies. An average accuracy of 80% for full classes or one single class is achieved by third-party researchers from more than 10 countries through sample-based validation or comparison with existing data. GlobeLand30 has users from more than 120 countries on five continents, and from all five Social Benefit Areas. The significance of GlobeLand30 is demonstrated by a number of published papers dealing with land-cover status and change analysis, cause-and-consequence analysis, and the environmental parameterization of Earth system models. Accordingly, scientific data sharing in the field of geosciences and Earth observation is promoted, and fine-resolution GLC mapping and applications worldwide are stimulated. The future development of GlobeLand30, including comprehensive validation, continuous updating, and monitoring of sustainable development goals, is also discussed.

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Micro‐ to macro‐scaling analysis of PM_2.5 in sensitive environment of Himalaya, India

Kimothi,

Chilkoti,

Rawat

et al. 2023

Geological Journal

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Fine particulate matter (PM) in the atmosphere has become a significant air contaminant with substantial health consequences. Although airborne remote sensing and ground sensor monitoring can offer air quality datasets containing PM2.5, there are limitations to effectively analysing large long‐term datasets. The research aims to evaluate air quality over the Himalayan region using the multifractal approach for the PM2.5 data time series. Fractal dimension (FD), Hurtz exponent (H), and predictability (PI) are estimated using the rescaled range. PM2.5 is found to have high concentration and frequency throughout the day. The same is found in the night hours during peak tourism months. The hourly PM2.5 time series datasets have shown multifractality. The primary reason for this is emissions produced by vehicles and anthropocentric activities in the region. The H is used to assess the dynamic features of the PM2.5 time series in terms of persistence and self‐correlation. In the context of climate change studies, it is crucial to monitor the spatial distribution and dynamic behaviour of PM2.5 in the Himalayan foothills. This study aims to provide prediction analyses and air quality index (AQI) estimates and demonstrate how PM2.5 concentrations alter the sensitive environment throughout the micro to macro scale. This will help us to build a long‐term strategy for reducing the harmful effect of increasing pollution levels on the ecosystem and human health.

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Air quality and its response to satellite-derived urban form in the Yangtze River Delta, China

Cited by 140 publications

References 43 publications

Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Analysis and Applications of GlobeLand30: A Review

Micro‐ to macro‐scaling analysis of PM_2.5 in sensitive environment of Himalaya, India

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Air quality and its response to satellite-derived urban form in the Yangtze River Delta, China

Cited by 140 publications

References 43 publications

Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

Analysis and Applications of GlobeLand30: A Review

Micro‐ to macro‐scaling analysis of PM2.5 in sensitive environment of Himalaya, India

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Micro‐ to macro‐scaling analysis of PM_2.5 in sensitive environment of Himalaya, India