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  1. Article ; Online: Exploring the spatial pattern of house collapse rates caused by extreme rainfall in central China: The role of natural and social factors.

    Feng, Yuqing / Hu, Maogui / Xu, Chengdong / Zhou, Ling / Nie, Juan

    The Science of the total environment

    2023  Volume 897, Page(s) 165411

    Abstract: The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the ... ...

    Abstract The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the factors that specifically contribute to house collapse triggered by extreme rainfall. This study endeavors to address this knowledge gap by proposing a hypothesis that the occurrence of house collapse, induced by extreme rainfall, demonstrates spatial heterogeneity and is subject to the interactive impacts of various factors. In the study, we investigate the relationship between house collapse rates and natural and social factors in the provinces of Henan, Shanxi, and Shaanxi provinces in 2021. These provinces are representative of flood-prone areas in central China. Spatial scan statistics and GeoDetector model were used to analyze spatial hotspot areas of house collapse rates and determinant power of natural and social factors on the spatial heterogeneity of house collapse rates, respectively. Our analysis reveals that the spatial hotspot areas predominantly concentrated in regions characterized by high rainfall, including areas along riverbanks and low-lying regions. Multiple factors contribute to the variations in house collapse rates. Among these factors, precipitation (q = 0.32) is the most significant, followed by the ratio of brick-concrete houses (q = 0.24), per capita GDP (q = 0.13), elevation (q = 0.13) and other factors. Notably, the interaction of precipitation and slope explains 63 % of the damage pattern, making it the strongest causal factor. The results substantiate our initial hypothesis and underscore the fact that the pattern of damage does not solely rely on a singular factor but rather on the interaction of multiple factors. These findings hold significance in advancing the formulation of more precise strategies aimed at bolstering safety measures and safeguarding properties within regions susceptible to flooding.
    Language English
    Publishing date 2023-07-08
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 121506-1
    ISSN 1879-1026 ; 0048-9697
    ISSN (online) 1879-1026
    ISSN 0048-9697
    DOI 10.1016/j.scitotenv.2023.165411
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: A new method for interpolation of missing air quality data at monitor stations.

    Xu, Chengdong / Wang, Jinfeng / Hu, Maogui / Wang, Wei

    Environment international

    2022  Volume 169, Page(s) 107538

    Abstract: Studies in environmental fields often suffer from air quality datasets incomplete at certain places and times. Here, a Spatial-Temporal Point Interpolation based on Biased Sentinel Hospitals Areal Disease Estimation (STPI-BSHADE) interpolation method was ...

    Abstract Studies in environmental fields often suffer from air quality datasets incomplete at certain places and times. Here, a Spatial-Temporal Point Interpolation based on Biased Sentinel Hospitals Areal Disease Estimation (STPI-BSHADE) interpolation method was introduced to address this issue. The method was based on the spatial statistic trinity theory, where the statistical error is determined by the population properties, the condition of the sample, and the method of estimation. In our study, the spatial association of the variables was quantified by the covariance and the ratio of air quality data between stations, resulting in linear unbiased estimates of the missing data. STPI-BSHADE was compared with two widely used statistical methods, inverse distance weighting (IDW) and Kriging. Theoretically, IDW and Kriging are short of the capacity of using the heterogeneous characteristics of the population and remedying the sample bias. Empirically, the accuracy of the STPI-BSHADE method was assessed using hourly particulate matter 2.5 data, collected from May 13 to December 31, 2014, in the Beijing-Tianjin-Hebei areas, where air quality presents spatial heterogeneity. The experimental results also demonstrated that STPI-BSHADE significantly outperformed the traditional methods.
    MeSH term(s) Air Pollutants/analysis ; Air Pollution/analysis ; Beijing ; Environmental Monitoring/methods ; Particulate Matter/analysis ; Spatial Analysis
    Chemical Substances Air Pollutants ; Particulate Matter
    Language English
    Publishing date 2022-09-21
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 554791-x
    ISSN 1873-6750 ; 0160-4120
    ISSN (online) 1873-6750
    ISSN 0160-4120
    DOI 10.1016/j.envint.2022.107538
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: A new method for interpolation of missing air quality data at monitor stations

    Xu, Chengdong / Wang, Jinfeng / Hu, Maogui / Wang, Wei

    Environment international. 2022 Sept. 19,

    2022  

    Abstract: Studies in environmental fields often suffer from air quality datasets incomplete at certain places and times. Here, a Spatial-Temporal Point Interpolation based on Biased Sentinel Hospitals Areal Disease Estimation (STPI-BSHADE) interpolation method was ...

    Abstract Studies in environmental fields often suffer from air quality datasets incomplete at certain places and times. Here, a Spatial-Temporal Point Interpolation based on Biased Sentinel Hospitals Areal Disease Estimation (STPI-BSHADE) interpolation method was introduced to address this issue. The method was based on the spatial statistic trinity theory, where the statistical error is determined by the population properties, the condition of the sample, and the method of estimation. In our study, the spatial association of the variables was quantified by the covariance and the ratio of air quality data between stations, resulting in linear unbiased estimates of the missing data. STPI-BSHADE was compared with two widely used statistical methods, inverse distance weighting (IDW) and Kriging. Theoretically, IDW and Kriging are short of the capacity of using the heterogeneous characteristics of the population and remedying the sample bias. Empirically, the accuracy of the STPI-BSHADE method was assessed using hourly particulate matter 2.5 data, collected from May 13 to December 31, 2014, in the Beijing-Tianjin-Hebei areas, where air quality presents spatial heterogeneity. The experimental results also demonstrated that STPI-BSHADE significantly outperformed the traditional methods.
    Keywords air quality ; covariance ; data collection ; environment ; kriging ; particulates ; spatial variation
    Language English
    Dates of publication 2022-0919
    Publishing place Elsevier Ltd
    Document type Article
    Note Pre-press version
    ZDB-ID 554791-x
    ISSN 1873-6750 ; 0160-4120
    ISSN (online) 1873-6750
    ISSN 0160-4120
    DOI 10.1016/j.envint.2022.107538
    Database NAL-Catalogue (AGRICOLA)

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  4. Article ; Online: An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China

    Huisheng Wu / Maogui Hu / Yaping Zhang / Yuan Han

    Sustainability, Vol 13, Iss 12901, p

    2021  Volume 12901

    Abstract: Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second ... ...

    Abstract Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second largest population and the highest coal consumption in China, was chosen to analyze the spatiotemporal air quality trends. We obtained daily air quality index (AQI) values from 91 stations in the province from 1 January 2014, to 31 December 2019, based on an adaptive data analysis method, empirical mode decomposition (EMD). The distribution of AQI in Shandong Province was heterogeneous at both spatial and temporal scales. All the stations could be divided into four clusters whose AQI trends decreased from 75 to 53, 95 to 68, 128 to 82, and 148 to 82, respectively. The overall trend of pollution became more serious from east to west in the province. The AQI is the largest in winter, followed by spring and autumn, and the smallest index occurs in summer. There are four types of annual trends of the AQI of each city. The overall downward trend indicates that the air quality of each city was improving annually.
    Keywords air pollution ; spatial pattern ; temporal trend ; decomposition ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 910 ; 333
    Language English
    Publishing date 2021-11-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article: atakrig: An R package for multivariate area-to-area and area-to-point kriging predictions

    Hu, Maogui / Huang, Yanwei

    Computers & geosciences. 2020 June, v. 139

    2020  

    Abstract: Geostatistical interpolation methods are used in diverse disciplines, such as environmental science, ecology, and hydrology. With the increasing availability of areal spatial data, area-to-area and area-to-point interpolations have great application ... ...

    Abstract Geostatistical interpolation methods are used in diverse disciplines, such as environmental science, ecology, and hydrology. With the increasing availability of areal spatial data, area-to-area and area-to-point interpolations have great application potential. In this study, based on the variogram deconvolution algorithm proposed by Goovaerts (2008), an open-source area-to-area kriging package atakrig is developed in the R environment. In atakrig, point-scale variogram and cross-variogram can be automatically deconvoluted from spatial areal samples. It provides a general framework for area-to-area and area-to-point ordinary kriging and cokriging. Two applications show that the package works well in river runoff prediction and missing data interpolation for remote sensing aerosol optical depth. The package can be deployed on different operating systems and computer hardware platforms.
    Keywords aerosols ; algorithms ; computer hardware ; computer software ; ecology ; environmental science ; geostatistics ; kriging ; prediction ; remote sensing ; rivers ; runoff ; spatial data
    Language English
    Dates of publication 2020-06
    Publishing place Elsevier Ltd
    Document type Article
    ISSN 0098-3004
    DOI 10.1016/j.cageo.2020.104471
    Database NAL-Catalogue (AGRICOLA)

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  6. Article ; Online: Exploring the spatial pattern of house collapse rates caused by extreme rainfall in central China: The role of natural and social factors

    Feng, Yuqing / Hu, Maogui / Xu, Chengdong / Zhou, Ling / Nie, Juan

    Science of the Total Environment. 2023 July 08, p.165411-

    2023  , Page(s) 165411–

    Abstract: The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the ... ...

    Abstract The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the factors that specifically contribute to house collapse triggered by extreme rainfall. This study endeavors to address this knowledge gap by proposing a hypothesis that the occurrence of house collapse, induced by extreme rainfall, demonstrates spatial heterogeneity and is subject to the interactive impacts of various factors. In the study, we investigate the relationship between house collapse rates and natural and social factors in the provinces of Henan, Shanxi, and Shaanxi provinces in 2021. These provinces are representative of flood-prone areas in central China. Spatial scan statistics and GeoDetector model were used to analyze spatial hotspot areas of house collapse rates and determinant power of natural and social factors on the spatial heterogeneity of house collapse rates, respectively. Our analysis reveals that the spatial hotspot areas predominantly concentrated in regions characterized by high rainfall, including areas along riverbanks and low-lying regions. Multiple factors contribute to the variations in house collapse rates. Among these factors, precipitation (q = 0.32) is the most significant, followed by the ratio of brick-concrete houses (q = 0.24), per capita GDP (q = 0.13), elevation (q = 0.13) and other factors. Notably, the interaction of precipitation and slope explains 63 % of the damage pattern, making it the strongest causal factor. The results substantiate our initial hypothesis and underscore the fact that the pattern of damage does not solely rely on a singular factor but rather on the interaction of multiple factors. These findings hold significance in advancing the formulation of more precise strategies aimed at bolstering safety measures and safeguarding properties within regions susceptible to flooding.
    Keywords environment ; models ; rain ; spatial variation ; statistics ; China ; Extreme rainfall ; House collapse rate ; GeoDetector ; Interactive effects
    Language English
    Dates of publication 2023-0708
    Publishing place Elsevier B.V.
    Document type Article ; Online
    Note Pre-press version
    ZDB-ID 121506-1
    ISSN 1879-1026 ; 0048-9697
    ISSN (online) 1879-1026
    ISSN 0048-9697
    DOI 10.1016/j.scitotenv.2023.165411
    Database NAL-Catalogue (AGRICOLA)

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  7. Article ; Online: Lagged Effects of Exposure to Air Pollutants on the Risk of Pulmonary Tuberculosis in a Highly Polluted Region.

    Feng, Yuqing / Wei, Jing / Hu, Maogui / Xu, Chengdong / Li, Tao / Wang, Jinfeng / Chen, Wei

    International journal of environmental research and public health

    2022  Volume 19, Issue 9

    Abstract: Background: Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions.: Method: A combined ... ...

    Abstract Background: Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions.
    Method: A combined Poisson generalized linear regression-distributed lag nonlinear model was used to determine the associations between long-term exposure (2005-2017) to air pollutants and the risk of PTB in the Beijing-Tianjin-Hebei region.
    Results: The monthly PTB cases exhibited a fluctuating downward trend. For each 10 μg/m
    Conclusions: Our results revealed potential associations between outdoor exposure to PM
    MeSH term(s) Air Pollutants/analysis ; Air Pollutants/toxicity ; Air Pollution/adverse effects ; Air Pollution/analysis ; China ; Environmental Exposure/adverse effects ; Environmental Exposure/analysis ; Humans ; Nitrogen Dioxide ; Particulate Matter/analysis ; Tuberculosis, Pulmonary/epidemiology
    Chemical Substances Air Pollutants ; Particulate Matter ; Nitrogen Dioxide (S7G510RUBH)
    Language English
    Publishing date 2022-05-09
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2175195-X
    ISSN 1660-4601 ; 1661-7827
    ISSN (online) 1660-4601
    ISSN 1661-7827
    DOI 10.3390/ijerph19095752
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Chidamide-BEAC plus autologous stem cell transplantation in high-risk non-Hodgkin lymphoma

    Yi Xia / Li Wang / Kaiyang Ding / Jiazhu Wu / Hua Yin / Maogui Hu / Haorui Shen / Jinhua Liang / Ruize Chen / Yue Li / Huayuan Zhu / Jianyong Li / Wei Xu / Ting Gao / Xiuyuan Hao

    Chinese Medical Journal, Vol 136, Iss 12, Pp 1491-

    a phase II clinical trial

    2023  Volume 1493

    Keywords Medicine ; R
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Wolters Kluwer
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Lagged Effects of Exposure to Air Pollutants on the Risk of Pulmonary Tuberculosis in a Highly Polluted Region

    Yuqing Feng / Jing Wei / Maogui Hu / Chengdong Xu / Tao Li / Jinfeng Wang / Wei Chen

    International Journal of Environmental Research and Public Health, Vol 19, Iss 5752, p

    2022  Volume 5752

    Abstract: Background: Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions. Method: A combined ... ...

    Abstract Background: Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions. Method: A combined Poisson generalized linear regression–distributed lag nonlinear model was used to determine the associations between long-term exposure (2005–2017) to air pollutants and the risk of PTB in the Beijing–Tianjin–Hebei region. Results: The monthly PTB cases exhibited a fluctuating downward trend. For each 10 μg/m 3 increase in concentration, the maximum lag-specific risk and cumulative relative risk (RR) were 1.011 (95% confidence interval (CI): 1.0091.012, lag: 3 months) and 1.042 (1.036–1.048, 5 months) for PM 2.5 , and 1.023 (1.015–1.031, 0 months) and 1.041 (1.026–1.055, 2 months) for NO 2 . The risk of PTB was negatively correlated with O 3 exposure, and the minimum lag-specific risk and cumulative RR were 0.991 (95% CI: 0.987–0.994, lag: 0 months) and 0.974 (0.968–0.981, 4 months), respectively. No age-dependent effects were observed. Conclusions: Our results revealed potential associations between outdoor exposure to PM 2.5 , NO 2 , and O 3 and the risk of PTB. Further research should explore the corresponding interactions and potential mechanisms.
    Keywords pulmonary tuberculosis ; air pollution ; epidemic characteristics ; Medicine ; R
    Subject code 333
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Club Characteristic and the Proximity Effect of Travel Links between Cities in China

    Mingxing Chen / Xinyue Luo / Maogui Hu / Xiaoping Zhang

    Complexity, Vol

    2020  Volume 2020

    Abstract: With the increasingly close relations between cities in China, it is of great significance to explore the regular characteristics of the intercity connection. Through Tencent’s population migration heat and Baidu map big data, this paper analyzes the ... ...

    Abstract With the increasingly close relations between cities in China, it is of great significance to explore the regular characteristics of the intercity connection. Through Tencent’s population migration heat and Baidu map big data, this paper analyzes the regular characteristics of the relations between complex cities based on such index as the rich node propensity index, preference level index, and relative heat index and also investigates the influence of geographical proximity factors on the external relations of different cities. The research has the following results. Firstly, the relations between cities have obvious club characteristics. The rich nodes tend to connect with the rich nodes, while the nonrich nodes tend to connect with the nonrich nodes. Secondly, the connection between cities has the effect of hierarchical proximity, and cities mainly establish spatial connections with cities of the same level and adjacent level. Thirdly, the relations between cities also have the effect of geographical proximity, and the degree of influence of geographical proximity in low-level cities is greater than that in high-level cities. Fourthly, the external connection mode of high-level cities is to establish close contact with high-level cities adjacent to the level, with strong attraction to low-level cities adjacent to the location at the same time. The low-level cities are closely related to the high-level cities adjacent to the location and other cities of geographical proximity or adjacent level. This study helps to further understand the complex characteristics and laws of intercity connections and urban networks.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 910
    Language English
    Publishing date 2020-01-01T00:00:00Z
    Publisher Hindawi-Wiley
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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