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Zhixiang Xie
Key Laboratory of Geospatial Technology for Middle and Low Yellow River Regions, Henan University, Kaifeng 475004, China

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Journal article
Published: 13 October 2020 in International Journal of Environmental Research and Public Health
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The global pandemic of COVID-19 has made it the focus of current attention. At present, the law of COVID-19 spread in cities is not clear. Cities have long been difficult areas for epidemic prevention and control because of the high population density, high mobility of people, and high frequency of contacts. This paper analyzed case information for 417 patients with COVID-19 in Shenzhen, China. The nearest neighbor index method, kernel density method, and the standard deviation ellipse method were used to analyze the spatio-temporal characteristics of the COVID-19 spread in Shenzhen. The factors influencing that spread were then explored using the multiple linear regression method. The results show that: (1) The development of COVID-19 epidemic situation in Shenzhen occurred in three stages. The patients showed significant hysteresis from the onset of symptoms to hospitalization and then to diagnosis. Prior to 27 January, there was a relatively long time interval between the onset of symptoms and hospitalization for COVID-19; the interval decreased thereafter. (2) The epidemic site (the place where the patient stays during the onset of the disease) showed an agglomeration in space. The degree of agglomeration constantly increased across the three time nodes of 31 January, 14 February, and 22 February. The epidemic sites formed a “core area” in terms of spatial distribution and spread along the “northwest–southeast” direction of the city. (3) Economic and social factors significantly impacted the spread of COVID-19, while environmental factors have not played a significant role.

ACS Style

Shirui Liu; Yaochen Qin; Zhixiang Xie; Jingfei Zhang. The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases. International Journal of Environmental Research and Public Health 2020, 17, 7450 .

AMA Style

Shirui Liu, Yaochen Qin, Zhixiang Xie, Jingfei Zhang. The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases. International Journal of Environmental Research and Public Health. 2020; 17 (20):7450.

Chicago/Turabian Style

Shirui Liu; Yaochen Qin; Zhixiang Xie; Jingfei Zhang. 2020. "The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases." International Journal of Environmental Research and Public Health 17, no. 20: 7450.

Journal article
Published: 08 July 2019 in Polish Journal of Environmental Studies
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Based on the data of population size, industrial development, energy consumption and technological level from 2013 in the Beijing-Tianjin-Hebei region, the fairness of PM2.5 pollution emissions were analyzed using Gini coefficient and contribution coefficient. In addition, a reduction allocation plan of PM2.5 concentration by 2020 in 13 cities was determined according to a minimized model of Gini coefficient model. The results showed that: (1) Gini coefficients of industrial development and technological level were greater than 0.4, implying that the PM2.5 pollution emissions in the region were significantly unfair from the perspective of industry and technology, especially in the aspect of technological level. (2) The spatial distribution of industrial and technological contribution coefficients presented a downward trend from Beijing and Tianjin to the periphery, and cities in Hebei Province were central to the unfairness of PM2.5 pollution emissions across the whole region. (3) The reduction values of PM2.5 concentration were between 16.7 1μg/m³ and 57.49 μg/m³, and a reduction allocation plan of PM2.5 concentration could improve the overall fairness of PM2.5 pollution emissions in the Beijing-Tianjin- Hebei region, but the unfairness of PM2.5 pollution emissions would not change dramatically.

ACS Style

Zhixiang Xie; Yang Li; Yaochen Qin; Zhicheng Zheng. Optimal Allocation of Control Targets for PM2.5 Pollution in China’s Beijing-Tianjin-Hebei Regions. Polish Journal of Environmental Studies 2019, 28, 3941 -3949.

AMA Style

Zhixiang Xie, Yang Li, Yaochen Qin, Zhicheng Zheng. Optimal Allocation of Control Targets for PM2.5 Pollution in China’s Beijing-Tianjin-Hebei Regions. Polish Journal of Environmental Studies. 2019; 28 (5):3941-3949.

Chicago/Turabian Style

Zhixiang Xie; Yang Li; Yaochen Qin; Zhicheng Zheng. 2019. "Optimal Allocation of Control Targets for PM2.5 Pollution in China’s Beijing-Tianjin-Hebei Regions." Polish Journal of Environmental Studies 28, no. 5: 3941-3949.

Meta analysis
Published: 20 March 2019 in International Journal of Environmental Research and Public Health
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A set of exposure–response coefficients between fine particulate matter (PM2.5) pollution and different health endpoints were determined through the meta-analysis method based on 2254 studies collected from the Web of Science database. With data including remotely-sensed PM2.5 concentration, demographic data, health data, and survey data, a Poisson regression model was used to assess the health losses and their economic value caused by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing–Tianjin–Hebei region, China. The results showed the following: (1) Significant exposure–response relationships existed between PM2.5 pollution and a set of health endpoints, including all-cause death, death from circulatory disease, death from respiratory disease, death from lung cancer, hospitalization for circulatory disease, hospitalization for respiratory disease, and outpatient emergency treatment. Each increase of 10 μg/m3 in PM2.5 concentration led to an increase of 5.69% (95% CI (confidence interval): 4.12%, 7.85%), 6.88% (95% CI: 4.94%, 9.58%), 4.71% (95% CI: 2.93%, 7.57%), 9.53% (95% CI: 6.84%, 13.28%), 5.33% (95% CI: 3.90%, 7.27%), 5.50% (95% CI: 4.09%, 7.38%), and 6.35% (95% CI: 4.71%, 8.56%) for above-mentioned health endpoints, respectively. (2) PM2.5 pollution posed a serious threat to residents’ health. In 2016, the number of deaths, hospitalizations, and outpatient emergency visits induced by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing–Tianjin–Hebei region reached 309,643, 1,867,240, and 47,655,405, respectively, accounting for 28.36%, 27.02% and 30.13% of the total number of deaths, hospitalizations, and outpatient emergency visits, respectively. (3) The economic value of health losses due to PM2.5 pollution in the study area was approximately $28.1 billion, accounting for 1.52% of the gross domestic product. The economic value of health losses was higher in Beijing, Tianjin, Shijiazhuang, Zhengzhou, Handan, Baoding, and Cangzhou, but lower in Taiyuan, Yangquan, Changzhi, Jincheng, and Hebi.

ACS Style

Zhixiang Xie; Yang Li; Yaochen Qin; Peijun Rong. Value Assessment of Health Losses Caused by PM2.5 Pollution in Cities of Atmospheric Pollution Transmission Channel in the Beijing–Tianjin–Hebei Region, China. International Journal of Environmental Research and Public Health 2019, 16, 1012 .

AMA Style

Zhixiang Xie, Yang Li, Yaochen Qin, Peijun Rong. Value Assessment of Health Losses Caused by PM2.5 Pollution in Cities of Atmospheric Pollution Transmission Channel in the Beijing–Tianjin–Hebei Region, China. International Journal of Environmental Research and Public Health. 2019; 16 (6):1012.

Chicago/Turabian Style

Zhixiang Xie; Yang Li; Yaochen Qin; Peijun Rong. 2019. "Value Assessment of Health Losses Caused by PM2.5 Pollution in Cities of Atmospheric Pollution Transmission Channel in the Beijing–Tianjin–Hebei Region, China." International Journal of Environmental Research and Public Health 16, no. 6: 1012.

Journal article
Published: 28 February 2019 in Sustainability
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The Loess Plateau is located at the transition zone between agriculture and livestock farming; its spatial and temporal pattern of drought is the key for an appropriate adaptation to climate change. This study investigated monthly meteorological observation data of 79 meteorological stations from 1955 to 2014 to calculate the standardized precipitation evapotranspiration index at different time scales. The spatial and temporal characteristics and persistence of drought were analyzed. The results showed the following: (i) The drought trend is most apparent in spring (0.096/10a) and lower in summer (0.036/10a) and autumn (0.009/10a). (ii) A higher drought level indicates a lower frequency of droughts occurrence and vice versa. The frequency of light drought was highest (11.36%), while that of extreme drought was lowest (0.12%). (iii) The mean drought intensity was highest in summer, followed by spring, autumn, and winter. The drought intensity was mainly light, showing a pattern of severe drought in the northwest and light drought in the southeast. (iv) The Loess Plateau will continue a trend of drought in the future, but the season of the continuous intensity will differ. Droughts in spring and summer are highly persistent, autumn drought trends continue but may slow, and winter droughts become random events.

ACS Style

Yang Li; Zhixiang Xie; Yaochen Qin; Haoming Xia; Zhicheng Zheng; Lijun Zhang; Ziwu Pan; Zhenzhen Liu. Drought Under Global Warming and Climate Change: An Empirical Study of the Loess Plateau. Sustainability 2019, 11, 1281 .

AMA Style

Yang Li, Zhixiang Xie, Yaochen Qin, Haoming Xia, Zhicheng Zheng, Lijun Zhang, Ziwu Pan, Zhenzhen Liu. Drought Under Global Warming and Climate Change: An Empirical Study of the Loess Plateau. Sustainability. 2019; 11 (5):1281.

Chicago/Turabian Style

Yang Li; Zhixiang Xie; Yaochen Qin; Haoming Xia; Zhicheng Zheng; Lijun Zhang; Ziwu Pan; Zhenzhen Liu. 2019. "Drought Under Global Warming and Climate Change: An Empirical Study of the Loess Plateau." Sustainability 11, no. 5: 1281.

Journal article
Published: 22 February 2019 in Sustainability
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The accessibility of hospital facilities is of great importance not only for maintaining social stability, but also for protecting the basic human right to health care. Traditional accessibility research often lacks consideration of the dynamic changes in transport costs and does not reflect the actual travel time of urban residents, which is critical to time-sensitive hospital services. To avoid these defects, this study considered the city of Kaifeng, China, as an empirical case, and directly acquired travel time data for two travel modes to the hospital in different time periods through web mapping API (Application Program Interface). Further, based on travel time calculations, we compared five baseline indicators. For the last indicator, we used the optimal weighted accessibility model to measure hospital accessibility for each residential area. The study discovered significant differences in the frequency and spatial distribution of hospital accessibility using public transit and self-driving modes of transportation. In addition, there is an imbalance between accessibility travel times in the study area and the number of arrivals at hospitals. In particular, different modes of transportation and different travel periods also have a certain impact on accessibility of medical treatment. The research results shed new light on the accessibility of urban public facilities and provide a scientific basis with which local governments can optimize the spatial structure of hospital resources.

ACS Style

Zhicheng Zheng; Haoming Xia; Shrinidhi Ambinakudige; Yaochen Qin; Yang Li; Zhixiang Xie; Lijun Zhang; Haibin Gu. Spatial Accessibility to Hospitals Based on Web Mapping API: An Empirical Study in Kaifeng, China. Sustainability 2019, 11, 1160 .

AMA Style

Zhicheng Zheng, Haoming Xia, Shrinidhi Ambinakudige, Yaochen Qin, Yang Li, Zhixiang Xie, Lijun Zhang, Haibin Gu. Spatial Accessibility to Hospitals Based on Web Mapping API: An Empirical Study in Kaifeng, China. Sustainability. 2019; 11 (4):1160.

Chicago/Turabian Style

Zhicheng Zheng; Haoming Xia; Shrinidhi Ambinakudige; Yaochen Qin; Yang Li; Zhixiang Xie; Lijun Zhang; Haibin Gu. 2019. "Spatial Accessibility to Hospitals Based on Web Mapping API: An Empirical Study in Kaifeng, China." Sustainability 11, no. 4: 1160.

Journal article
Published: 01 December 2018 in Carpathian Journal of Earth and Environmental Sciences
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Yang LI, Zhixiang XIE, Fen QIN, Yaochen QIN, Zhicheng ZHENG, Haoming XIA & Lijun ZHANG - GEOMORPHOLOGICAL CHARACTERISTICS OF A TRANSECT FROM THE YELLOW RIVER TO THE IRON PAGODA IN KAIFENG CITY, CHINA, Carpathian Journal of Earth and Environmental Sciences, February 2019, Vol. 14, No. 1, p. 245 - 254; DOI:10.26471/cjees/2019/014/076

ACS Style

Yang Li; Zhixiang Xie; Fen Qin; Yaochen Qin; Zhicheng Zheng; Haoming Xia; Lijun Zhang. GEOMORPHOLOGICAL CHARACTERISTICS OF A TRANSECT FROM THE YELLOW RIVER TO THE IRON PAGODA IN KAIFENG CITY, CHINA. Carpathian Journal of Earth and Environmental Sciences 2018, 14, 245 -254.

AMA Style

Yang Li, Zhixiang Xie, Fen Qin, Yaochen Qin, Zhicheng Zheng, Haoming Xia, Lijun Zhang. GEOMORPHOLOGICAL CHARACTERISTICS OF A TRANSECT FROM THE YELLOW RIVER TO THE IRON PAGODA IN KAIFENG CITY, CHINA. Carpathian Journal of Earth and Environmental Sciences. 2018; 14 (1):245-254.

Chicago/Turabian Style

Yang Li; Zhixiang Xie; Fen Qin; Yaochen Qin; Zhicheng Zheng; Haoming Xia; Lijun Zhang. 2018. "GEOMORPHOLOGICAL CHARACTERISTICS OF A TRANSECT FROM THE YELLOW RIVER TO THE IRON PAGODA IN KAIFENG CITY, CHINA." Carpathian Journal of Earth and Environmental Sciences 14, no. 1: 245-254.