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The Geography of Long Term Exposure to Particulate Matter 2.5 and COVID-19 Mortality;An Assessment of the Fragility and spatial Sensitivity of a Significant Finding

The Geography of Long Term Exposure to Particulate Matter 2....

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作者： Badger, Jennifer Beth University of California Los Angeles

学位级别：M.A., Master of Arts

Air pollution is directly linked to death. In December 2020, a UK coroner ruled that air pollution was the cause of a fatal asthma attack that led to the 2013 death of nine-year-old Ella Adoo-Kissi Debrah who lived adjacent to a busy motorway (BBC News, 2022). The assignment of air pollution as the official cause of death on a death certificate was the first of its kind in the world (Reynolds, 2020). Though this was the first official assignment of air pollution as a cause of death, there are numerous studies linking air pollution exposure with mortality all over the world. Before the COVID-19 pandemic, the air pollutant PM 2.5 was identified as the “largest environmental risk factor in the United States” (Goodkind et al. 2019, p. 8780) and the cause of more annual premature deaths than traffic accidents and homicides combined (Goodkind et al. 2019). With the onset of the COVID-19 pandemic, researchers began assessing the impact of air pollution exposure on COVID-19 incidence and death. In a widely received, nationwide study linking air pollution exposure to COVID-19 mortality, Harvard T.H. Chan School of Public Health researchers, Wu et al., produced significant findings linking the impact of long term exposure to PM 2.5 to COVID-19 mortality across the contiguous United States. This 2020 study, published in ScienceAdvances, has been cited over 600 times, covered by 131 news outlets and downloaded over 15,000 times. Georeferenced data is routinely used in public health research such as this, however, the substantive influence of geography in the relationship between the treatment and outcome variable is often not considered in the model specifications, research design, nor the sampling strategy (Goldhagen et al., 2005; Matisziw, Grubesic, and Wei 2008). Additionally, the mechanism of data aggregation to an administrative unit may spatially misrepresent the data (Delmelle et al., 2022). As air pollution is a local, regional, and transboundary phenomenon (Nordenstam

关键词： Air pollution COVID-19 exploratory spatial data analysis Health geography PM2.5 United States

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An Approach of Identifying and Extracting Urban Commercial Areas Using the Nighttime Lights Satellite Imagery

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REMOTE SENSING 2020年第6期12卷 1029-1029页

作者： Duan, Xuzhe Hu, Qingwu Zhao, Pengcheng Wang, Shaohua Ai, Mingyao Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430070 Peoples R China

Urban commercial areas can reflect the spatial distribution of business activities. However, the scope of urban commercial areas cannot be easily detected by traditional methods because of difficulties in data collection. Considering the positive correlation between business scale and nighttime lighting, this paper proposes a method of urban commercial areas detection based on nighttime lights satellite imagery. First, an imagery preprocess model is proposed to correct imageries and improve efficiency of cluster analysis. Then, an exploratory spatial data analysis and hotspots clustering method is employed to detect commercial areas by geographic distribution metric with urban commercial hotspots. Furthermore, four imageries of Wuhan City and Shenyang City are selected as an example for urban commercial areas detection experiments. Finally, a comparison is made to find out the time and space factors that affect the detection results of the commercial areas. By comparing the results with the existing map data, we are convinced that the nighttime lights satellite imagery can effectively detect the urban commercial areas. The time of image acquisition and the vegetation coverage in the area are two important factors affecting the detection effect. Harsh weather conditions and high vegetation coverage are conducive to the effective implementation of this method. This approach can be integrated with traditional methods to form a fast commercial areas detection model, which can then play a role in large-scale socio-economic surveys and dynamic detection of commercial areas evolution. Hence, a conclusion can be reached that this study provides a new method for the perception of urban socio-economic activities.

关键词： urban commercial area nighttime lights satellite imagery exploratory spatial data analysis urban hot spots detection

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spatial pattern matching analysis of grain production and rainfall in the Ziya River Basin

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2021年第2期193卷 88-88页

作者： Li, Fawen Wang, Yachen Cao, Runxiang Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China

The exploratory spatial data analysis (ESDA) method, which includes global spatial autocorrelation and local spatial autocorrelation, is used to analyze the spatial pattern of the annual grain production and annual grain production increment in the Ziya River Basin from 2007 to 2017. Then, the spatial mismatch index is used to analyze the spatial mismatch relationship between the annual grain output and annual precipitation in the Ziya River Basin in 2015. The results showed that (1) the spatial pattern of the annual grain production in the Ziya River Basin is stable, with Low-Low clusters and High-High clusters concentrated on the left and right sides of the Ziya River Basin, respectively. The overall difference in the annual grain production of each district and county increased gradually from 2013 to 2017. (2) The local spatial correlation structure of the annual grain production of adjacent districts and counties in the Ziya River Basin had strong stability, and its space-time transition had a certain path dependence or spatial-locking characteristics. The reason why the High-High clusters are concentrated on the right side of the Ziya River is that there are large cultivated areas, such as the Shijin irrigation district, on the right side of the Ziya River Basin. (3) A spatial change rule "the proportion of grain production is low and the proportion of rainfall is high" changed to "the proportion of grain production and rainfall is balanced" and then to "the proportion of grain production is high and the proportion of rainfall is low" in the Ziya River Basin in 2015. The Shijin irrigation district is mainly located in the area where the spatial mismatch between the annual grain output and the average annual rainfall in the Ziya River Basin in 2015 is assessed as grade V, which indicates that the spatial mismatch between the annual grain output and the annual average rainfall is serious. In summary, grain production in the Shijin irrigation district has been inc

关键词： exploratory spatial data analysis Mismatch index Grain production Precipitation

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spatial effects and impact factors of food nitrogen footprint in China based on spatial durbin panel model

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ENVIRONMENTAL RESEARCH 2022年第PartB期204卷 112046-112046页

作者： Liu, Chun Nie, Guihua Wuhan Univ Technol Sch Econ Wuhan 430070 Hubei Peoples R China Wuhan Technol & Business Univ Sch Management Wuhan 430065 Hubei Peoples R China Hubei Prov Res Ctr E Business Big Data Engn Techn Wuhan 430070 Hubei Peoples R China

Reactive nitrogen (Nr) has far-reaching advantages and disadvantages on human beings. Nitrogen footprint (NF) is a tool to quantify the use of Nr in the environment. Food nitrogen footprint (FNF) accounts for the largest proportion of the total NF, and the differences between provinces in China exist objectively. In order to explore the spatial correlation and socio-economic driving factors of China's FNF, this paper uses N-calculator tool to calculate the FNF of 30 provinces in China from 2000 to 2018, and uses exploratory spatial data to analyze the spatial correlation and changes of provincial FNF, The driving factors and spatial effects of FNF change in the province were analyzed by using spatial Durbin panel model and spatial regression partial differential method. The results showed that: (1) There is a significant and stable positive spatial dependence and heterogeneity in the FNF among provinces;(2) The direct effect factors of promoting the growth of FNF in the province are urban household Engel coefficient, per capita disposable income of rural residents and rural household Engel coefficient. The main factors of restraining the growth of FNF in the province are wastewater discharge per unit GDP and per capita GDP;(3) the spillover effect is mainly manifested as the negative effect of the increase of urban household Engel coefficient on neighboring provinces, and the spillover effect of per capita disposable income of urban residents and nitrogen fertilizer application rate per unit grain yield on the growth of FNF of neighboring provinces is significant. From the policy level, it is necessary to guide healthy and scientific eating habits, reduce the proportion of meat and fish in the diet structure, reduce the nitrogen fertilizer application per unit grain yield, and improve the efficiency of chemical fertilizer utilization. When formulating relevant policies, government departments should give consideration to the cooperation between provincial and region

关键词： Food nitrogen footprint exploratory spatial data analysis spatial durbin panel Spillover effect

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Exploring the spatial Impact of Green Infrastructure on Urban Drainage Resilience

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WATER 2021年第13期13卷 1789页

作者： Rodriguez, Mayra Fu, Guangtao Butler, David Yuan, Zhiguo Sharma, Keshab Univ Exeter Ctr Water Syst QUEX Inst North Pk Rd Exeter EX4 4QF Devon England Univ Exeter Ctr Water Syst CEMPS North Pk Rd Exeter EX4 4QF Devon England Univ Queensland Adv Water Management Ctr Level 4Gehrmann Labs Bldg 60 Brisbane Qld 4072 Australia

This paper explores the spatial impact of green infrastructure (GI) location on the resilience of urban drainage systems by the application of exploratory spatial data analysis (ESDA). A framework that integrates resilience assessment, location sensitivity analysis and ESDA is presented and applied to an urban catchment in the United Kingdom. Three types of GI, namely a bioretention cell, permeable pavement, and green roof, are evaluated separately and simultaneously. Resilience is assessed using stress-strain tests, which measure the system performance based on the magnitude and duration of sewer flooding and combined sewer overflows. Based on the results of a location sensitivity analysis, ESDA is applied to determine if there is spatial autocorrelation, spatial clusters, and spatial outliers. Results show a stronger spatial dependency using sewer flooding indicators. Different GI measures present differences in spatial autocorrelation and spatial cluster results, highlighting the differences in their underlying mechanisms. The finding of conflicting spatial clusters indicates that there are trade-offs in the placement of GI in certain locations. The proposed framework can be used as a tool for GI spatial planning, helping in the development of a systematic approach for resilience-performance orientated GI design and planning.

关键词： CSO exploratory spatial data analysis green infrastructure resilience resilience cluster sewer system urban flooding

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Agricultural Water Utilization Efficiency in China: Evaluation, spatial Differences, and Related Factors

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WATER 2022年第5期14卷 684-684页

作者： Liu, Kai Xue, Yuting Lan, Yu Fu, Yuxuan Shandong Normal Univ Coll Geog & Environm Jinan 250358 Peoples R China Shandong Normal Univ Univ Shandong Collaborat Innovat Ctr Human Nat & Green Dev Jinan 250358 Peoples R China

Agricultural water utilization efficiency (AWUE) reflects the rational utilization of water resources in agricultural production. Improving AWUE is important for both improving the levels of agricultural production and reducing consumption of water resources, and it is significant to explore the spatial differences between different cities and regions and the various factors related to AWUE, both theoretically and practically. The AWUE of totally 281 cities at the prefecture level or above in China between 2003 and 2018 was evaluated using the super-efficiency slacks-based measure (SBM). The spatial differences in AWUE were simulated by exploratory spatial data analysis (ESDA), and the various factors affecting AWUE were simulated using the graphical statistical tool, Geodetector. The results of this study are as follows: (1) The mean value of AWUE across the country was merely 0.23 when it registered a record high in 2018, indicating that the AWUE in China was low;(2) AWUE showed significant spatial differences judging from the results of ESDA, and the low-low type was the principal spatial type, which was distributed mainly in the North China Plain and the Loess Plateau;and (3) agricultural technology was the main factor affecting AWUE.

关键词： agricultural water utilization efficiency spatial differences related factors super-efficiency slacks-based measure exploratory spatial data analysis Geodetector

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exploratory study on the spatial relationship between emerging infectious diseases and urban characteristics: Cases from Korea

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SUSTAINABLE CITIES AND SOCIETY 2021年 66卷 102672-102672页

作者： Kim, Donghyun Pusan Natl Univ Dept Urban Planning & Engn 2 Busandaehak Ro 63beon Gil Busan 46241 South Korea

In the modern global context of interconnected populations, the recent emergence of infectious diseases involves complex interactions. The purpose of this study is to investigate the spatial correlations between urban characteristics, taking into account the socio-ecological aspects, and the emergence of infectious diseases. Using exploratory spatial data analysis and spatial regression between the infectious disease emergence data and 14 urban characteristics, we analyzed 225 spatial units in South Korea, where there was a re-emergence of measles and a 2015 outbreak of Middle East Respiratory Syndrome. As results of exploratory spatial data analysis, the emerging infectious diseases had spatial dependence and showed spatial clusters. spatial regression models showed that urban characteristic factors had different effects according to the type of infectious disease. Common factors were characteristics related to low socioeconomic status in water or food-borne diseases and manageable infectious diseases. Intermittent infections disease epidemics are related to high-quality residential environments and the response capacity of the local government. New infectious diseases are different than other infectious diseases, which are related to the ecological environment. This study suggests spatial policies for preventing infectious diseases considering the spatial relationships between urban characteristics and infectious diseases as well as the management of public health.

关键词： Infectious diseases Urbanization Disease prevention Social-ecology exploratory spatial data analysis

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spatial Differences and Influencing Factors of Carbon Emission Intensity in China's Urban Agglomerations toward the Carbon Neutrality Target

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ATMOSPHERE 2024年第6期15卷 641页

作者： Wang, Yilin Hui, Xianke Liu, Kai Shandong Normal Univ Coll Geog & Environm Jinan 250358 Peoples R China Shandong Normal Univ Collaborat Innovat Ctr Human Nat & Green Dev Univ Jinan 250358 Peoples R China

It is of great scientific value to study the spatial differences and influencing factors of carbon emission intensity (CEI) in urban agglomerations (UAs), and it also has reference significance for China in formulating energy-saving and emission-reduction policies to achieve the target of carbon neutrality. Taking 165 prefecture-level cities in 19 UAs in China from 2007 to 2019 as the research object, this study investigated the spatial differences of CEI in UAs using exploratory spatial data analysis and explored the influencing factors of CEI via Geodetector. The results showed the following: (1) The CEI of the UAs showed a downward trend. (2) The CEI of the UAs has typical spatial agglomeration characteristics, where the North comprises mainly high-high and low-high types, whereas the South is primarily high-low and low-low types. (3) The influencing factors of CEI have undergone a transformation from industrial structure to population urbanization.

关键词： carbon emission intensity spatial differences influencing factors exploratory spatial data analysis Geodetector carbon neutrality

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Spatio-Temporal Heterogeneity of Ecological Quality in Hangzhou Greater Bay Area (HGBA) of China and Response to Land Use and Cover Change

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REMOTE SENSING 2022年第21期14卷 5613-5613页

作者： Yang, Zhenjie Sun, Chao Ye, Junwei Gan, Congying Li, Yue Wang, Lingyu Chen, Yujun Ningbo Univ Dept Geog & Spatial Informat Tech Ningbo 315211 Peoples R China Ningbo Univ Donghai Acad Ningbo 315211 Peoples R China Ningbo Univ Ningbo Univ Collaborat Innovat Ctr Land & Marine Ningbo 315211 Peoples R China

Human activities have been stressing the ecological environment since we stepped into the Anthropocene Age. It is urgent to formulate a sustainable plan for balancing socioeconomic development and ecological conservation based on a thorough understanding of ecological environment changes. The ecological environment can be evaluated when multiple remote sensing indices are integrated, such as the use of the recently prevalent Remote Sensing-based Ecological Index (RSEI). Currently, most of the RSEI-related studies have focused on the ecological quality evolution in small areas. Less attention was paid to the spatio-temporal heterogeneity of ecological quality in large-scale urban agglomerations and the potential links with Land Use and Cover Change (LUCC). In this study, we monitored the dynamics of the ecological quality in the Hangzhou Greater Bay Area (HGBA) during 1995-2020, using the RSEI as an indicator. During the construction of the RSEI, a percentile de-noising normalization method was proposed to overcome the problem of widespread noises from large-scale regions and make the RSEI-based ecological quality assessment for multiple periods comparable. Combined with the land use data, the quantitative relationship between the ecological quality and the LUCC was revealed. The results demonstrated that: (1) The ecological quality of the HGBA degraded after first improving but was still good (averaged RSEI of 0.638). It was divergent for the prefecture-level cities of the HGBA, presenting degraded, improved, and fluctuant trends for the cities from north to south. (2) For ecological quality, the improved regions have larger area (57.5% vs. 42.5%) but less increment (0.141 vs. -0.195) than the degraded regions. Mountains, downtowns, and coastal wetlands were the hot spots for the improvement and urbanization, and reclamation processes were responsible for the degradation. (3) The ecological quality was improved for forests and urban areas (oRSEI > 0.07) but degraded

关键词： ecological quality remote sensing-based ecological index (RSEI) Hangzhou Greater Bay Area land use and cover change (LUCC) exploratory spatial data analysis

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analysis of the spatial association network structure of water-intensive utilization efficiency and its driving factors in the Yellow River Basin

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ECOLOGICAL INDICATORS 2024年 158卷

作者： Han, Xinyi Zhang, Xin Lei, Hang Northwest A&F Univ Coll Water Resources & Architectural Engn Yangling 712100 Peoples R China

Achieving the efficient, synergistic and sustainable utilization of water resources is a necessary precondition and an important means through which to protect the ecological environment of the Yellow River Basin (YRB) and promote the high-quality development of the basin's economy. This paper innovatively defines water-intensive utilization efficiency (WIUE) and constructs an appropriate evaluation index system. A superefficiency network slacks-based measure (SBM) model is introduced for measurement. The gravity model is improved, and the spatial clustering and spatial association network characteristics of water use efficiency (WUE) and water conservation and purification efficiency (WCPE) are analysed using exploratory spatial data analysis (ESDA) and social network analysis (SNA). Finally, the formation mechanism of the spatial network of WCPE is explored by using quadratic assignment procedure (QAP) regression. The following conclusions are obtained. (1) The WIUE of the YRB shows a divergent trend over time, with fluctuations in the water conservation and purification stage being the main factors influencing WIUE changes in each province. (2) Currently, the spatial association network structures of WUE and WCPE are sparse. However, with the government's basin-wide water conservation policy, the spatial relationships within the basin have gradually become more closely linked. The local clustering effect of WUE in space and the communication of technical elements in the WCPE stage in the basin are the main reasons for this network formation. Focusing on the WCPE stage, this study not only proposes policy suggestions to improve the efficiency of water resource intensification in the YRB by promoting the exchange of factors but can also be used as a reference for other basins with great regional differences.

关键词： Yellow River Basin Water-intensive utilization efficiency Superefficient network slacks-based measure model exploratory spatial data analysis Social network analysis

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