Charlie Zhang | University of Louisville (original) (raw)
Papers by Charlie Zhang
Research Square (Research Square), Dec 29, 2022
Background: Exposure to harmful lead is a critical public health concern due to its toxic nature ... more Background: Exposure to harmful lead is a critical public health concern due to its toxic nature and widespread distribution in the environment. Given the fact that policy solutions in the past several decades have signi cantly decreased the risks of environmental lead exposure, a remaining threat is toxic lead emissions from industrial facilities. This study examined the racial and economic disparities in proximity to lead-releasing industrial facilities and the concomitant lead exposure in Kentucky in the U.S. Methods: We applied unique geospatial analysis methods including distance buffer, location quotients, and population-weighted exposures to analyze the spatial patterns of lead-releasing industrial facilities and lead exposure concerning environmental injustice between blacks and whites and between the below-poverty and above-poverty populations. Pearson's linear correlation and paired samples t-test were performed to examine the statistical signi cance of racial and economic inequalities measured by distance to polluting facilities, lead concentration, and population-weighted exposure to lead. Results: We identi ed a negative correlation between percent of the population that was black and distance to Toxic Release Inventory (TRI) sites (r =-0.240, p <0.001) and opposite results were observed for whites (r = 0.284, p <0.001). Likewise, median household income was positively associated with distance to TRI facilities (r = 0.197, p < 0.001) while poverty rate was inversely related to distance to TRI facilities (p =-0.189, p <0.001). Moreover, blacks and the below-poverty group had larger mean population-weighted lead exposures than whites and the above-poverty group respectively although the mean differences for each pair was statistically insigni cant. Conclusions: Results of this study provide new evidence supporting the environmental injustice proposition that assets low-income and ethnic minorities are more likely to reside in the vicinity of toxicreleasing industrial facilities and are therefore disproportionately exposed to airborne lead. Findings can help promote the need for reduced national ambient air quality standards for lead releases and mitigate environmental injustice.
International Journal of Applied Geospatial Research, 2022
Using data obtained from the Louisville Metro Emergency Medical Services, this article examined t... more Using data obtained from the Louisville Metro Emergency Medical Services, this article examined the spatial and temporal patterns of opioid overdoses in Louisville, Kentucky. We aggregated opioid overdoses to street segments and applied the optimized hot spot analysis to identify areas with significant high overdose rates. Multiple spatial regression models were used to explore the ecological risk factors potentially associated with the spatial variations of the epidemic. The results suggest an overall clustered pattern of opioid overdoses with all overdose incidents concentrated in less than 8% of all the street segments. The consecutive hot spots largely overlapped with the most disadvantaged inner-city neighborhoods in Louisville. Regression results provided statistical evidence regarding the effects of socioeconomic correlates including uninsured, vacancy rates, and criminal activity. The spatial discrepancy between the overdose hot spots and lack of medical facilities or hospit...
BMJ Open, 2020
IntroductionFly ash is a waste product generated from burning coal for electricity. It is compris... more IntroductionFly ash is a waste product generated from burning coal for electricity. It is comprised of spherical particles ranging in size from 0.1 µm to over 100 µm in diameter that contain trace levels of heavy metals. Large countries such as China and India generate over 100 million tons per year while smaller countries like Italy and France generate 2 to 3 million tons per year. The USA generates over 36 million tons of ash, making it one of the largest industrial waste streams in the nation. Fly ash is stored in landfills and surface impoundments exposing communities to fugitive dust and heavy metals that leach into the groundwater. Limited information exists on the health impact of exposure to fly ash. This protocol represents the first research to assess children’s exposure to coal fly ash and neurobehavioural outcomes.MethodsWe measure indoor exposure to fly ash and heavy metals, and neurobehavioural symptoms in children aged 6 to 14 years old. Using air pollution samplers a...
Neurotoxicology and Teratology, 2021
Manganese (Mn) is an essential element, however, children with moderate to high Mn exposure can e... more Manganese (Mn) is an essential element, however, children with moderate to high Mn exposure can exhibit neurobehavioral impairments. One way Mn appears to affect brain function is through altering dopaminergic systems involved with motor and cognitive control including frontal-striatal brain systems. Based on the risk for motor and attention problems, we evaluated neurobehavioral function in 255 children at risk for Mn exposure due to living in proximity to coal ash storage sites. Proton Induced X-ray Emissions (PIXE) analysis was conducted on finger and toenails samples. Multiple neuropsychological tests were completed with the children. Fifty-five children had Mn concentrations above the limit of detection (LOD) (median concentration = 3.95 ppm). Children with detectable Mn concentrations had reduced visual motor skills (β = −5.62, CI: −9.11, −2.12, p=0.008) and more problems with sustained attention, based on incorrect responses on a computerized attention test, (β = 0.40, CI: 0.21, 0.59, p<0.001) compared with children who had Mn concentrations below the LOD. Findings suggest that Mn exposure impacts attention and motor control possibly due to neurotoxicity involving basal ganglia and forebrain regions. Visual-motor and attention tests may provide a sensitive measure of Mn neurotoxicity, useful for evaluating the effects of exposure in children and leading to better treatment options.
Science of The Total Environment, 2021
Background The US COVID-19 epidemic impacted counties differently across space and time, though l... more Background The US COVID-19 epidemic impacted counties differently across space and time, though large-scale transmission dynamics are unclear. The study's objective was to group counties with similar trajectories of COVID-19 cases and deaths and identify county-level correlates of the distinct trajectory groups. Methods Daily COVID-19 cases and deaths were obtained from 3141 US counties from January through June 2020. Clusters of epidemic curve trajectories of COVID-19 cases and deaths per 100,000 people were identified with Proc Traj. We utilized polytomous logistic regression to estimate Odds Ratios for trajectory group membership in relation to county-level demographics, socioeconomic factors, school enrollment, employment and lifestyle data. Results Six COVID-19 case trajectory groups and five death trajectory groups were identified. Younger counties, counties with a greater proportion of females, Black and Hispanic populations, and greater employment in private sectors had higher odds of being in worse case and death trajectories. Percentage of counties enrolled in grades 1–8 was associated with earlier-start case trajectories. Counties with more educated adult populations had lower odds of being in worse case trajectories but were generally not associated with worse death trajectories. Counties with higher poverty rates, higher uninsured, and more living in non-family households had lower odds of being in worse case and death trajectories. Counties with higher smoking rates had higher odds of being in worse death trajectory counties. Discussion In the absence of clear guidelines and personal protection, smoking, racial and ethnic groups, younger populations, social, and economic factors were correlated with worse COVID-19 epidemics that may reflect population transmission dynamics during January–June 2020. After vaccination of high-risk individuals, communities with higher proportions of youth, communities of color, smokers, and workers in healthcare, service and goods industries can reduce viral spread by targeting vaccination programs to these populations and increasing access and education on non-pharmaceutical interventions.
The Journal of Rural Health, 2020
Abstract Purpose This ecological analysis investigates the spatial patterns of the COVID‐19 epide... more Abstract Purpose This ecological analysis investigates the spatial patterns of the COVID‐19 epidemic in the United States in relation to socioeconomic variables that characterize US counties. Methods Data on confirmed cases and deaths from COVID‐19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state‐level measure of the percent of the population that has been tested for COVID‐19 was used to control for the impact of testing. Findings The impact of COVID‐19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID‐19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested. Conclusions Knowledge about the spatial aspects of the COVID‐19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to “shelter‐in‐place” should continue to stem the spread of COVID‐19.
Journal of Exposure Science & Environmental Epidemiology, 2021
Chinese Geographical Science, 2018
Smart urban development is an inevitable choice, and is essential to overall strength improvement... more Smart urban development is an inevitable choice, and is essential to overall strength improvement. It is important to explore an urban smart development path which unites smart growth with driving shrinkage perfectly in forming scientific and sustainable development concept and responding to new normal strategic opportunities. Based on statistic data of 294 prefecture-level cities and above in China from 2000 to 2015, we analyzed spatial and temporal evolution of urban smart development in China by constructing a dynamic fitting model of urban land expansion, population growth, and economic development as well as the coefficient of variation of urban smart development (CVSD). Further efforts were then made to consider differential distribution regularity of urban smart development so as to understand the driving mechanisms of heterogeneous classification of urban smart development in China from different scales and scale variation. Our results indicate that: 1) the disordered growth tendency of urban cities in China is overall well controlled in the middle, and late research and it mainly presented a doublet coexistence of shrinkage disordered cities and smart developing cities. It is particularly obvious that Northeast China and East China have regarded shrinkage disordered cities and smart developing cities as main development tendency separately. 2) Areas with basic stability and relative variation were relatively dispersed across the time period, but the proportion was far beyond areas with significant variation. It demonstrates a relative equilibrium spatial and temporal differential evolution pattern of prefecture-level cities and above in China, except for Tongling, Lanzhou and Chaoyang. 3) prefecture-level cities and above in China are mostly characterized by shrinkage disordered and smart development classification under the background of different scale and scale variation from 2000–2015; however, the spatial resonance relation is not obvious. 4) There are many interaction factors forming an important driving mechanism in developing the spatial and temporal pattern of urban smart development in China, including natural geographical factors, industrial structure adjustment, human capital radiation, regional traffic accessibility, and government decision-making intervention.
Habitat International, 2018
Abstract Given the fact that China has been experiencing rapid urbanization since the 1980s, limi... more Abstract Given the fact that China has been experiencing rapid urbanization since the 1980s, limited empirical research has analyzed the spatial patterns of urban land expansion across Chinese cities using national data sets. This article attempts to explore evidence of urban sprawl and its relationship with levels of economic development using novel geospatial data on urban area boundaries and development densities for all Chinese cities. Different from existing studies, we used a decomposition approach to examine the differences between the 1990 urban boundaries and their newly developed suburbs (1990–2010) in population density and road intersection density, two key characteristics of urban sprawl. The main results show that Chinese cities have experienced dramatic increases in built-up areas but substantial decreases in development densities in the newly urbanized areas in comparison to their inner city counterparts, signifying concrete evidence of urban sprawl. Moreover, results from regression analyses indicate that a city's economic development level was positively related to urban land expansion after controlling for confounding factors, largely due to the nature of China's land-centered urbanization and economic development strategies. Findings from this article can help raise awareness about the staggering reality of urban land expansion across Chinese cities and urge urban planners and policymakers to tighten their rural-to-urban land conversion systems and curb urban sprawl.
International journal of environmental research and public health, Jan 31, 2018
Ovarian cancer is the fifth leading cause of female cancer mortality in the U.S. and accounts for... more Ovarian cancer is the fifth leading cause of female cancer mortality in the U.S. and accounts for five percent of all cancer deaths among women. No environmental risk factors for ovarian cancer have been confirmed. We previously reported that ovarian cancer incidence rates at the state level were significantly correlated with the extent of pulp and paper manufacturing. We evaluated that association using county-level data and advanced geospatial methods. Specifically, we investigated the relationship of spatial patterns of ovarian cancer incidence rates with toxic emissions from pulp and paper facilities using data from the Environmental Protection Agency's Toxic Release Inventory (TRI). Geospatial analysis identified clusters of counties with high ovarian cancer incidence rates in south-central Iowa, Wisconsin, New York, Pennsylvania, Alabama, and Georgia. A bivariate local indicator of spatial autocorrelation (LISA) analysis confirmed that counties with high ovarian cancer rat...
Papers in Applied Geography, 2018
for my enrichment and growth as a researcher. I would like to express my gratitude to Dr. Rasul R... more for my enrichment and growth as a researcher. I would like to express my gratitude to Dr. Rasul Ramji for his guidance and encouragement in personal and professional matters. I am also thankful to colleagues, classmates, and faculty in the UPA department who made this experience enjoyable and contributed to a supportive learning environment. My colleagues Dr. Emmanuel Frimpong Boamah, Dr. Wes Grooms, and Matthew Fischer were especially helpful with their contributions in reviewing and editing written work, as well as in our discussions throughout the years. I would like to thank my family and loved ones whose thoughts and good wishes uplifted and comforted me in this journey. I am infinitely grateful to my mother, Khairun, for her unwavering love and support in every moment. I dedicate this dissertation to her.
Sustainability
Although industrial agglomeration and specialization have been studied for more than 100 years, i... more Although industrial agglomeration and specialization have been studied for more than 100 years, it is still a controversial field. In the era of big data, it is of great significance to study industrial agglomeration and regional specialization by using firm-level data. Based on 3,053,024 pieces of firm-level big data, the spatial evolution and spatial patterns of industrial agglomeration and specialization of 9 major industries in the Yangtze River Delta, China were revealed. Results show that: (1) the degree of industrial agglomeration is highly related to industrial attributes; industries which are directly related to production tend to be geographically concentrated, while industries that serve for production tend to be spatially dispersed; (2) the evolution characteristics and trajectories of industrial agglomeration vary by industries: wholesale and retail trade and real estate are becoming more spatially dispersed; information industries, leasing and commercial services, scie...
Sustainability
The floor area ratio is a comprehensive index that plays an important role in urban planning and ... more The floor area ratio is a comprehensive index that plays an important role in urban planning and sustainable development. Remote sensing data are widely used in floor area ratio calculations because they can produce both two-dimensional planar and three-dimensional stereo information on buildings. However, remote sensing is not adequate for calculating the number of floors in a building. In this paper, a simple and practical pixel-level model is established through defining a quantitative relationship among the floor area ratio, building density, and average number of floors (ANF). The floor area ratios are calculated by combining remote sensing data with publicly available Internet data. It incorporates supplemental map data and street-level views from Internet maps to confirm building types and the number of floors, thereby enabling more-accurate floor area ratio calculations. The proposed method is tested in the Tiantongyuan neighborhood, Changping District, Beijing, and the resu...
Air Quality, Atmosphere & Health
Journal of Maps, 2012
This article explores the spatiotemporal patterns of school segregation between blacks and whites... more This article explores the spatiotemporal patterns of school segregation between blacks and whites in Jefferson County and its affiliated Louisville metropolitan area. The classical dissimilarity index and the GIS-oriented spatial segregation measure – S index are used to estimate school segregation based on public school enrollment data (1987–2008). Findings call for the significance of measuring school segregation from a metropolitan-wide perspective rather than focusing on the urban school district alone. Also, results indicate that between-district segregation represents the majority of overall segregation in the entire Louisville metropolitan area. Most importantly, the GIS-based S Index enriches segregation studies by mapping the dynamic patterns of racial disparities while permitting a statistical estimate of segregation.
Research Square (Research Square), Dec 29, 2022
Background: Exposure to harmful lead is a critical public health concern due to its toxic nature ... more Background: Exposure to harmful lead is a critical public health concern due to its toxic nature and widespread distribution in the environment. Given the fact that policy solutions in the past several decades have signi cantly decreased the risks of environmental lead exposure, a remaining threat is toxic lead emissions from industrial facilities. This study examined the racial and economic disparities in proximity to lead-releasing industrial facilities and the concomitant lead exposure in Kentucky in the U.S. Methods: We applied unique geospatial analysis methods including distance buffer, location quotients, and population-weighted exposures to analyze the spatial patterns of lead-releasing industrial facilities and lead exposure concerning environmental injustice between blacks and whites and between the below-poverty and above-poverty populations. Pearson's linear correlation and paired samples t-test were performed to examine the statistical signi cance of racial and economic inequalities measured by distance to polluting facilities, lead concentration, and population-weighted exposure to lead. Results: We identi ed a negative correlation between percent of the population that was black and distance to Toxic Release Inventory (TRI) sites (r =-0.240, p <0.001) and opposite results were observed for whites (r = 0.284, p <0.001). Likewise, median household income was positively associated with distance to TRI facilities (r = 0.197, p < 0.001) while poverty rate was inversely related to distance to TRI facilities (p =-0.189, p <0.001). Moreover, blacks and the below-poverty group had larger mean population-weighted lead exposures than whites and the above-poverty group respectively although the mean differences for each pair was statistically insigni cant. Conclusions: Results of this study provide new evidence supporting the environmental injustice proposition that assets low-income and ethnic minorities are more likely to reside in the vicinity of toxicreleasing industrial facilities and are therefore disproportionately exposed to airborne lead. Findings can help promote the need for reduced national ambient air quality standards for lead releases and mitigate environmental injustice.
International Journal of Applied Geospatial Research, 2022
Using data obtained from the Louisville Metro Emergency Medical Services, this article examined t... more Using data obtained from the Louisville Metro Emergency Medical Services, this article examined the spatial and temporal patterns of opioid overdoses in Louisville, Kentucky. We aggregated opioid overdoses to street segments and applied the optimized hot spot analysis to identify areas with significant high overdose rates. Multiple spatial regression models were used to explore the ecological risk factors potentially associated with the spatial variations of the epidemic. The results suggest an overall clustered pattern of opioid overdoses with all overdose incidents concentrated in less than 8% of all the street segments. The consecutive hot spots largely overlapped with the most disadvantaged inner-city neighborhoods in Louisville. Regression results provided statistical evidence regarding the effects of socioeconomic correlates including uninsured, vacancy rates, and criminal activity. The spatial discrepancy between the overdose hot spots and lack of medical facilities or hospit...
BMJ Open, 2020
IntroductionFly ash is a waste product generated from burning coal for electricity. It is compris... more IntroductionFly ash is a waste product generated from burning coal for electricity. It is comprised of spherical particles ranging in size from 0.1 µm to over 100 µm in diameter that contain trace levels of heavy metals. Large countries such as China and India generate over 100 million tons per year while smaller countries like Italy and France generate 2 to 3 million tons per year. The USA generates over 36 million tons of ash, making it one of the largest industrial waste streams in the nation. Fly ash is stored in landfills and surface impoundments exposing communities to fugitive dust and heavy metals that leach into the groundwater. Limited information exists on the health impact of exposure to fly ash. This protocol represents the first research to assess children’s exposure to coal fly ash and neurobehavioural outcomes.MethodsWe measure indoor exposure to fly ash and heavy metals, and neurobehavioural symptoms in children aged 6 to 14 years old. Using air pollution samplers a...
Neurotoxicology and Teratology, 2021
Manganese (Mn) is an essential element, however, children with moderate to high Mn exposure can e... more Manganese (Mn) is an essential element, however, children with moderate to high Mn exposure can exhibit neurobehavioral impairments. One way Mn appears to affect brain function is through altering dopaminergic systems involved with motor and cognitive control including frontal-striatal brain systems. Based on the risk for motor and attention problems, we evaluated neurobehavioral function in 255 children at risk for Mn exposure due to living in proximity to coal ash storage sites. Proton Induced X-ray Emissions (PIXE) analysis was conducted on finger and toenails samples. Multiple neuropsychological tests were completed with the children. Fifty-five children had Mn concentrations above the limit of detection (LOD) (median concentration = 3.95 ppm). Children with detectable Mn concentrations had reduced visual motor skills (β = −5.62, CI: −9.11, −2.12, p=0.008) and more problems with sustained attention, based on incorrect responses on a computerized attention test, (β = 0.40, CI: 0.21, 0.59, p<0.001) compared with children who had Mn concentrations below the LOD. Findings suggest that Mn exposure impacts attention and motor control possibly due to neurotoxicity involving basal ganglia and forebrain regions. Visual-motor and attention tests may provide a sensitive measure of Mn neurotoxicity, useful for evaluating the effects of exposure in children and leading to better treatment options.
Science of The Total Environment, 2021
Background The US COVID-19 epidemic impacted counties differently across space and time, though l... more Background The US COVID-19 epidemic impacted counties differently across space and time, though large-scale transmission dynamics are unclear. The study's objective was to group counties with similar trajectories of COVID-19 cases and deaths and identify county-level correlates of the distinct trajectory groups. Methods Daily COVID-19 cases and deaths were obtained from 3141 US counties from January through June 2020. Clusters of epidemic curve trajectories of COVID-19 cases and deaths per 100,000 people were identified with Proc Traj. We utilized polytomous logistic regression to estimate Odds Ratios for trajectory group membership in relation to county-level demographics, socioeconomic factors, school enrollment, employment and lifestyle data. Results Six COVID-19 case trajectory groups and five death trajectory groups were identified. Younger counties, counties with a greater proportion of females, Black and Hispanic populations, and greater employment in private sectors had higher odds of being in worse case and death trajectories. Percentage of counties enrolled in grades 1–8 was associated with earlier-start case trajectories. Counties with more educated adult populations had lower odds of being in worse case trajectories but were generally not associated with worse death trajectories. Counties with higher poverty rates, higher uninsured, and more living in non-family households had lower odds of being in worse case and death trajectories. Counties with higher smoking rates had higher odds of being in worse death trajectory counties. Discussion In the absence of clear guidelines and personal protection, smoking, racial and ethnic groups, younger populations, social, and economic factors were correlated with worse COVID-19 epidemics that may reflect population transmission dynamics during January–June 2020. After vaccination of high-risk individuals, communities with higher proportions of youth, communities of color, smokers, and workers in healthcare, service and goods industries can reduce viral spread by targeting vaccination programs to these populations and increasing access and education on non-pharmaceutical interventions.
The Journal of Rural Health, 2020
Abstract Purpose This ecological analysis investigates the spatial patterns of the COVID‐19 epide... more Abstract Purpose This ecological analysis investigates the spatial patterns of the COVID‐19 epidemic in the United States in relation to socioeconomic variables that characterize US counties. Methods Data on confirmed cases and deaths from COVID‐19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state‐level measure of the percent of the population that has been tested for COVID‐19 was used to control for the impact of testing. Findings The impact of COVID‐19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID‐19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested. Conclusions Knowledge about the spatial aspects of the COVID‐19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to “shelter‐in‐place” should continue to stem the spread of COVID‐19.
Journal of Exposure Science & Environmental Epidemiology, 2021
Chinese Geographical Science, 2018
Smart urban development is an inevitable choice, and is essential to overall strength improvement... more Smart urban development is an inevitable choice, and is essential to overall strength improvement. It is important to explore an urban smart development path which unites smart growth with driving shrinkage perfectly in forming scientific and sustainable development concept and responding to new normal strategic opportunities. Based on statistic data of 294 prefecture-level cities and above in China from 2000 to 2015, we analyzed spatial and temporal evolution of urban smart development in China by constructing a dynamic fitting model of urban land expansion, population growth, and economic development as well as the coefficient of variation of urban smart development (CVSD). Further efforts were then made to consider differential distribution regularity of urban smart development so as to understand the driving mechanisms of heterogeneous classification of urban smart development in China from different scales and scale variation. Our results indicate that: 1) the disordered growth tendency of urban cities in China is overall well controlled in the middle, and late research and it mainly presented a doublet coexistence of shrinkage disordered cities and smart developing cities. It is particularly obvious that Northeast China and East China have regarded shrinkage disordered cities and smart developing cities as main development tendency separately. 2) Areas with basic stability and relative variation were relatively dispersed across the time period, but the proportion was far beyond areas with significant variation. It demonstrates a relative equilibrium spatial and temporal differential evolution pattern of prefecture-level cities and above in China, except for Tongling, Lanzhou and Chaoyang. 3) prefecture-level cities and above in China are mostly characterized by shrinkage disordered and smart development classification under the background of different scale and scale variation from 2000–2015; however, the spatial resonance relation is not obvious. 4) There are many interaction factors forming an important driving mechanism in developing the spatial and temporal pattern of urban smart development in China, including natural geographical factors, industrial structure adjustment, human capital radiation, regional traffic accessibility, and government decision-making intervention.
Habitat International, 2018
Abstract Given the fact that China has been experiencing rapid urbanization since the 1980s, limi... more Abstract Given the fact that China has been experiencing rapid urbanization since the 1980s, limited empirical research has analyzed the spatial patterns of urban land expansion across Chinese cities using national data sets. This article attempts to explore evidence of urban sprawl and its relationship with levels of economic development using novel geospatial data on urban area boundaries and development densities for all Chinese cities. Different from existing studies, we used a decomposition approach to examine the differences between the 1990 urban boundaries and their newly developed suburbs (1990–2010) in population density and road intersection density, two key characteristics of urban sprawl. The main results show that Chinese cities have experienced dramatic increases in built-up areas but substantial decreases in development densities in the newly urbanized areas in comparison to their inner city counterparts, signifying concrete evidence of urban sprawl. Moreover, results from regression analyses indicate that a city's economic development level was positively related to urban land expansion after controlling for confounding factors, largely due to the nature of China's land-centered urbanization and economic development strategies. Findings from this article can help raise awareness about the staggering reality of urban land expansion across Chinese cities and urge urban planners and policymakers to tighten their rural-to-urban land conversion systems and curb urban sprawl.
International journal of environmental research and public health, Jan 31, 2018
Ovarian cancer is the fifth leading cause of female cancer mortality in the U.S. and accounts for... more Ovarian cancer is the fifth leading cause of female cancer mortality in the U.S. and accounts for five percent of all cancer deaths among women. No environmental risk factors for ovarian cancer have been confirmed. We previously reported that ovarian cancer incidence rates at the state level were significantly correlated with the extent of pulp and paper manufacturing. We evaluated that association using county-level data and advanced geospatial methods. Specifically, we investigated the relationship of spatial patterns of ovarian cancer incidence rates with toxic emissions from pulp and paper facilities using data from the Environmental Protection Agency's Toxic Release Inventory (TRI). Geospatial analysis identified clusters of counties with high ovarian cancer incidence rates in south-central Iowa, Wisconsin, New York, Pennsylvania, Alabama, and Georgia. A bivariate local indicator of spatial autocorrelation (LISA) analysis confirmed that counties with high ovarian cancer rat...
Papers in Applied Geography, 2018
for my enrichment and growth as a researcher. I would like to express my gratitude to Dr. Rasul R... more for my enrichment and growth as a researcher. I would like to express my gratitude to Dr. Rasul Ramji for his guidance and encouragement in personal and professional matters. I am also thankful to colleagues, classmates, and faculty in the UPA department who made this experience enjoyable and contributed to a supportive learning environment. My colleagues Dr. Emmanuel Frimpong Boamah, Dr. Wes Grooms, and Matthew Fischer were especially helpful with their contributions in reviewing and editing written work, as well as in our discussions throughout the years. I would like to thank my family and loved ones whose thoughts and good wishes uplifted and comforted me in this journey. I am infinitely grateful to my mother, Khairun, for her unwavering love and support in every moment. I dedicate this dissertation to her.
Sustainability
Although industrial agglomeration and specialization have been studied for more than 100 years, i... more Although industrial agglomeration and specialization have been studied for more than 100 years, it is still a controversial field. In the era of big data, it is of great significance to study industrial agglomeration and regional specialization by using firm-level data. Based on 3,053,024 pieces of firm-level big data, the spatial evolution and spatial patterns of industrial agglomeration and specialization of 9 major industries in the Yangtze River Delta, China were revealed. Results show that: (1) the degree of industrial agglomeration is highly related to industrial attributes; industries which are directly related to production tend to be geographically concentrated, while industries that serve for production tend to be spatially dispersed; (2) the evolution characteristics and trajectories of industrial agglomeration vary by industries: wholesale and retail trade and real estate are becoming more spatially dispersed; information industries, leasing and commercial services, scie...
Sustainability
The floor area ratio is a comprehensive index that plays an important role in urban planning and ... more The floor area ratio is a comprehensive index that plays an important role in urban planning and sustainable development. Remote sensing data are widely used in floor area ratio calculations because they can produce both two-dimensional planar and three-dimensional stereo information on buildings. However, remote sensing is not adequate for calculating the number of floors in a building. In this paper, a simple and practical pixel-level model is established through defining a quantitative relationship among the floor area ratio, building density, and average number of floors (ANF). The floor area ratios are calculated by combining remote sensing data with publicly available Internet data. It incorporates supplemental map data and street-level views from Internet maps to confirm building types and the number of floors, thereby enabling more-accurate floor area ratio calculations. The proposed method is tested in the Tiantongyuan neighborhood, Changping District, Beijing, and the resu...
Air Quality, Atmosphere & Health
Journal of Maps, 2012
This article explores the spatiotemporal patterns of school segregation between blacks and whites... more This article explores the spatiotemporal patterns of school segregation between blacks and whites in Jefferson County and its affiliated Louisville metropolitan area. The classical dissimilarity index and the GIS-oriented spatial segregation measure – S index are used to estimate school segregation based on public school enrollment data (1987–2008). Findings call for the significance of measuring school segregation from a metropolitan-wide perspective rather than focusing on the urban school district alone. Also, results indicate that between-district segregation represents the majority of overall segregation in the entire Louisville metropolitan area. Most importantly, the GIS-based S Index enriches segregation studies by mapping the dynamic patterns of racial disparities while permitting a statistical estimate of segregation.