scholarly journals Analysis of Agricultural Eco-Efficiency and Influencing Factors in Henan Province

2022 ◽  
Vol 10 (01) ◽  
pp. 78-93
Author(s):  
Bingjun Li ◽  
Wenyan Li ◽  
Wenya Ma ◽  
Yifan Zhang
Keyword(s):  
Influencing Factors ◽  
Henan Province

scholarly journals Prevalence and risk factors of worry among teachers during the COVID-19 epidemic in Henan, China: a cross-sectional survey

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e045386
Author(s):  
Yanqing Wang ◽  
Quanman Li ◽  
Clifford Silver Tarimo ◽  
Cuiping Wu ◽  
Yudong Miao ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Age Groups ◽  
Educational Status ◽  
Henan Province ◽  
Anxiety Level ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
School Location ◽  
Fear Level ◽  
Attention Level

ObjectiveTo evaluate the level of worry and its influencing factors during the COVID-19 epidemic among teachers in Henan Province in China.Study designA cross-sectional study was conducted.MethodsWe designed a cross-sectional survey that included 88 611 teachers from three cities in Henan Province, China between 4 February 2020 and 12 February 2020. Level of worry was measured using a five-item Likert scale, with 1 being ‘not worried’ and 5 being ‘very worried’. The OR and 95% CI of potential influencing factors for level of worry among study participants were estimated using ordinal logistic regression models.ResultsAbout 59% of teachers reported being ‘very worried’ about the COVID-19 epidemic. The proportion of female teachers was higher than of male teachers (60.33% vs 52.89%). In all age groups considered in this study, a ‘very worried’ condition accounted for the highest proportion. The age group 40–49 years had the lowest proportion of participants who were very worried, 52.34% of whom were men and 58.62% were women. After controlling for potential confounding factors, age, education level, type of teacher, school location, attention level, fear level, anxiety level and behaviour status were all related to level of worry (all p<0.05).ConclusionDuring the COVID-19 epidemic, there was a high proportion of teachers who were ‘very worried’ about the situation in Henan Province, China. Our study may remind policymakers to consider factors including age, educational status, type of teacher, school location, source of information on COVID-19, attention level, anxiety level, fear level and behaviour status to alleviate worry.

Tobit model-based analysis on the influencing factors of wheat loss during harvesting by the combine harvester

2021 ◽  
pp. 1-14
Author(s):  
Hong Ji ◽  
Xun He ◽  
Li Ding ◽  
Zhe Qu ◽  
Wenkang Huang ◽  
...  
Keyword(s):  
Regression Model ◽  
Influencing Factors ◽  
Loss Rate ◽  
Henan Province ◽  
Normal Operation ◽  
Tobit Regression ◽  
Wheat Field ◽  
Combine Harvester ◽  
Main Factors ◽  
Tobit Regression Model

Based on the investigation data of wheat mechanized harvest in eight major wheat producing areas from the south to the north of Henan Province, the main factors affecting wheat mechanized harvest loss were identified and the influence of each factor was decomposed. In this article, the loss rate of wheat mechanical harvest was calculated by using the method of artificial measurement of wheat yield in the field, and the influencing factors of wheat mechanical harvest operation in 8 regions of Henan province were treated and analyzed by using Tobit regression model. In this paper, the loss rate of wheat mechanical harvest was calculated by using the method of wheat field artificial yield measurement and the influencing factors of wheat mechanical harvest operation in eight regions of Henan province were treated and analyzed by using Tobit regression model. The results show that the average harvest loss rate in the field amounts to 2.96%, the average harvest loss rate at the edge of field amounts to 3.06%, whereas the loss rate in the normal operation area amounts 2.86%. The main factors that caused the harvest loss of wheat field machinery were the maturity of wheat, the area of operation field, the diseases and pests, weather conditions and the accumulated working hours of harvester drivers in a single day. Therefore, the main technical measures to reduce the operation loss of wheat combine harvester were put forward to provide a theoretical basis for promoting the deep integration of agricultural machinery and agronomy.

scholarly journals Urban Ecological Efficiency and Its Influencing Factors—A Case Study in Henan Province, China

2019 ◽  
Vol 11 (18) ◽  
pp. 5048 ◽  
Author(s):  
Tao Liu ◽  
Jixia Li ◽  
Juan Chen ◽  
Shaolei Yang
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Efficiency Analysis ◽  
Henan Province ◽  
Measure Data ◽  
Ecological Efficiency ◽  
Ecological Civilization ◽  
Growth Trend ◽  
Static And Dynamic Analysis ◽  
Significant Difference

The urban ecological civilization construction relates to welfare of the people and the national future. It is an important field of the high-quality economic development to improve the urban ecological efficiency level. The purpose of this research is to provide a new perspective and method for the quantitative study of the urban sustainable development, and also to provide some decision-making references for the improvement of the urban ecological efficiency in Henan province. This paper uses the slacks-based measure-data envelopment analysis (SBM-DEA) model containing the undesirable output and the Malmquist index model to fully evaluate the urban ecological efficiency level in Henan province during the period of 2005–2016, via both the static and dynamic analysis. Based on this, the bootstrap regression model is applied in analyzing the influencing factors of the urban ecological efficiency. The research shows three findings. First, according to the static efficiency analysis, the urban ecological efficiency in Henan province is low as a whole and has a big promotion space. Moreover, there is a significant difference in the urban ecological efficiency level among the five regions because of the different geographical locations and social and economic development situations of the cities. Second, according to the dynamic efficiency analysis, in the last 12 years, the urban ecological efficiency in Henan province has shown an overall growth trend, and the technological progress has played a major role in promoting the urban ecological efficiency in Henan province. Third, according to the influencing factor analysis, the governmental financial support hinders the improvement of the urban ecological efficiency in Henan province, while the level of opening to the outside world, the urban population density, and the urban greening level promote it.

scholarly journals Spatial Association Pattern of Air Pollution and Influencing Factors in the Beijing–Tianjin–Hebei Air Pollution Transmission Channel: A Case Study in Henan Province

2020 ◽  
Vol 17 (5) ◽  
pp. 1598
Author(s):  
Jianhui Qin ◽  
Suxian Wang ◽  
Linghui Guo ◽  
Jun Xu
Keyword(s):  
Air Pollution ◽  
Relative Humidity ◽  
Influencing Factors ◽  
Pollution Control ◽  
Sunshine Duration ◽  
Spatial Association ◽  
Henan Province ◽  
Air Pollution Control ◽  
Transmission Channel ◽  
Pollution Transmission

The Beijing–Tianjin–Hebei (BTH) air pollution transmission channel and its surrounding areas are of importance to air pollution control in China. Based on daily data of air quality index (AQI) and air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) from 2015 to 2016, this study analyzed the spatial and temporal characteristics of air pollution and influencing factors in Henan Province, a key region of the BTH air pollution transmission channel. The result showed that non-attainment days and NAQI were slightly improved at the provincial scale during the study period, whereas that in Hebi, Puyang, and Anyang became worse. PM2.5 was the largest contributor to the air pollution in all cities based on the number of non-attainment days, but its mean frequency decreased by 21.62%, with the mean occurrence of O3 doubled. The spatial distribution of NAQI presented a spatial agglomeration pattern, with high-high agglomeration area varying from Jiaozuo, Xinxiang, and Zhengzhou to Anyang and Hebi. In addition, the NAQI was negatively correlated with sunshine duration, temperature, relative humidity, wind speed, and positively to atmospheric pressure and relative humidity in all four clusters, whereas relationships between socioeconomic factors and NAQI differed among them. These findings highlight the need to establish and adjust regional joint prevention and control of air pollution as well as suggest that it is crucially important for implementing effective strategies for O3 pollution control.

scholarly journals Inequality and Influencing Factors of Spatial Accessibility of Medical Facilities in Rural Areas of China: A Case Study of Henan Province

2019 ◽  
Vol 16 (10) ◽  
pp. 1833 ◽  
Author(s):  
Shirui Liu ◽  
Yaochen Qin ◽  
Yanan Xu
Keyword(s):  
Influencing Factors ◽  
Rural Areas ◽  
Henan Province ◽  
Spatial Accessibility ◽  
Medical Services ◽  
Basic Unit ◽  
Mountainous Areas ◽  
Geographically Weighted Regression Model ◽  
Medical Facilities ◽  
Spatial Differences

The equalization of medical services has received increasing attention, and improving the accessibility of medical facilities in rural areas is key for the realization of fairness with regard to medical services. This study studies the rural areas of Henan Province, China, and uses unincorporated villages as the basic unit. The spatial pattern of accessibility in rural areas was comprehensively analyzed via geographic information system spatial analysis and coefficient of variation. The spatial heterogeneity of relevant influencing factors was assessed by using the geographically weighted regression model. The results show that: (1) The distance cost of medical treatment in rural areas is normally distributed, and most areas are within a range of 2–6 km. (2) The accessibility in rural areas has clear spatial differences, is significantly affected by terrain, and shows characteristics of significant spatial agglomeration. The eastern and central regions have good spatial accessibility, while the western regions have poor spatial accessibility. Furthermore, regions with poor accessibility are mainly located in mountainous areas. (3) The spatial equilibrium of accessibility follows a pattern of gradual deterioration from east to west. The better accessibility-unbalanced type is mostly located in the center of Henan Province, while the poor accessibility-unbalanced type is concentrated in mountainous areas. (4) The area, elevation, residential density, and per capita industrial output are positively correlated with spatial accessibility, while road network density and population density are negatively correlated.

scholarly journals Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China

2020 ◽  
Vol 12 (17) ◽  
pp. 6944
Author(s):  
Yiru Guo ◽  
Yan Hu ◽  
Ke Shi ◽  
Yuriy Bilan
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Water Resources ◽  
Environmental Pollution ◽  
Influencing Factors ◽  
Water Resource ◽  
Henan Province ◽  
Arid Areas ◽  
Efficiency Assessment

With progress in China’s industrialization and urbanization, the contradiction of social and economic development with water resource supply–demand and water environmental pollution becomes increasingly prominent. To cope with the dual constraints of resource shortage and environmental regulations, the concept of water resource green efficiency that considers economic, environmental, and ecological factors is highly involved to promote sustainable economic development. The theoretical and practice circle devote to scientific green efficiency assessment of water resources and effective recognition of relevant influencing factors. However, to an extent they neglect social benefits brought by sustainable development and possible influences of industrial restructuring on green efficiency. They also lack concern on green efficiency of water resources in inland arid areas. To offset the disadvantages of existing studies, the philosophy of sustainable development was integrated into the input–output assessment system of green efficiency of water resources, and an assessment model was constructed using the SBM–Tobit (slack-based measure and Tobit) method. Moreover, a case study based on Henan Province, China was carried out. The green efficiencies of water resources in 18 cities of Henan Province during 2011–2018 were calculated. The operation mechanism of relevant influencing factors was discussed, and the methods to improve green efficiency of water resources were determined. Results reveal that the sustainable green efficiency of water resources in Henan Province increased in fluctuation during 2011–2018. The mean green efficiency increased from 0.425 in 2011 to 0.498 in 2018. At present, green efficiency of water resources in Henan Province remains at a low level, with a mean of 0.504. Reducing water consumption intensity and increasing investment to water environmental pollution technologies can promote green efficiency of water resources significantly. Conclusions provide a new method for scientific measurement and green efficiency assessment of water resources in inland arid areas.

scholarly journals Analysis on Measurement, Decoupling Effect and Influencing Factors of Agricultural Carbon Emissions in Major Grain Producing Areas—Taking Henan Province as An Example

2021 ◽  
Vol 261 ◽  
pp. 04030
Author(s):  
YiLin Shen ◽  
Shu Yu
Keyword(s):  
Economic Development ◽  
Agricultural Economic ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Henan Province ◽  
Total Output ◽  
Chemical Fertilizers ◽  
Decoupling Analysis ◽  
Decoupling Effect ◽  
First Time

Based on the scientific calculation of agricultural carbon emissions in Henan Province, the Tapio decoupling model is used to analyze its relationship with economic development, and its driving factors are analyzed in combination with the LMDI model. The results show that the total amount of agricultural carbon emissions in Henan Province from 2010 to 2019 is on the rise, of which chemical fertilizers are the largest source of carbon emissions. The decoupling analysis shows that before 2019, the weak decoupling between agricultural carbon emissions and the total output value of the planting industry was mainly weak, and a strong decoupling state appeared for the first time in 2019. This means that the level of agricultural economic development is the main force driving the growth of carbon emissions.

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