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Article ; Online: Factors Affecting the Promotion of Conservation Tillage in Black Soil—The Case of Northeast China

Yan Qu / Chulin Pan / Hongpeng Guo

Sustainability, Vol 13, Iss 9563, p

2021 Volume 9563

Abstract: Taking the conservation tillage influences of black soil in Northeast China as the research object, the paper is written according to the advice of relevant experts and technicians in Northeast China, the study also calculates the weight of each ... ...

Abstract	Taking the conservation tillage influences of black soil in Northeast China as the research object, the paper is written according to the advice of relevant experts and technicians in Northeast China, the study also calculates the weight of each influencing factor through the Delphi and Analytic Hierarchy Process (AHP) method. Then, the significance of the factors affecting the benefit of conservation tillage is analyzed. The results show that, based on the comprehensive analysis, it is concluded that the economic factor is the primary factor affecting the benefit of black soil conservation tillage in Northeast China. Among the twelve influencing factors, eight of them have a significant impact on the development of conservation tillage benefits on black soil in Northeast China. Such as the degree of government subsidy; the adaptability of agricultural machinery; the input of new technology; relevant policies, laws and regulations; the quality of conservation tillage; the income of agricultural machinery farmers; practical application capacity; government publicity. Therefore, in the process of implementing the black soil conservation tillage, we should focus on these influencing factors, which will effectively promote the sustainable development of agriculture in Northeast China.
Keywords	Northeast China ; black soil conservation tillage ; Analytic Hierarchy Process ; influencing factors ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	950
Language	English
Publishing date	2021-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: How Do the Population Structure Changes of China Affect Carbon Emissions? An Empirical Study Based on Ridge Regression Analysis

Chulin Pan / Huayi Wang / Hongpeng Guo / Hong Pan

Sustainability, Vol 13, Iss 3319, p

2021 Volume 3319

Abstract: This study focuses on the impact of population structure changes on carbon emissions in China from 1995 to 2018. This paper constructs the multiple regression model and uses the ridge regression to analyze the relationship between population structure ... ...

Abstract	This study focuses on the impact of population structure changes on carbon emissions in China from 1995 to 2018. This paper constructs the multiple regression model and uses the ridge regression to analyze the relationship between population structure changes and carbon emissions from four aspects: population size, population age structure, population consumption structure, and population employment structure. The results showed that these four variables all had a significant impact on carbon emissions in China. The ridge regression analysis confirmed that the population size, population age structure, and population employment structure promoted the increase in carbon emissions, and their contribution ratios were 3.316%, 2.468%, 1.280%, respectively. However, the influence of population consumption structure (−0.667%) on carbon emissions was negative. The results showed that the population size had the greatest impact on carbon emissions, which was the main driving factor of carbon emissions in China. Chinese population will bring huge pressure on the environment and resources in the future. Therefore, based on the comprehensive analysis, implementing the one-child policy will help slow down China’s population growth, control the number of populations, optimize the population structure, so as to reduce carbon emissions. In terms of employment structure and consumption structure, we should strengthen policy guidance and market incentives, raising people’s low-carbon awareness, optimizing energy-consumption structure, improving energy efficiency, so as to effectively control China’s carbon emissions.
Keywords	carbon emissions ; population structure ; time series ; ridge regression ; China ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	950
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

Hongpeng Guo / Sidong Xie / Chulin Pan

International Journal of Environmental Research and Public Health, Vol 18, Iss 705, p

2021 Volume 705

Abstract: This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, ... ...

Abstract	This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, carbon absorptions and net carbon sinks of the planting industry by using crop parameter estimation and carbon emissions inventory estimation methods. In addition, the multiple linear regression model and panel data model were used to analyze and test the carbon emissions and net carbon sinks of the planting industry. The results show that: (1). The increase of the planting area of rice, corn, and peanuts in the three northeastern provinces of China will promote carbon emissions, while the increase of the planting area of wheat, sorghum, soybeans, and vegetables will reduce carbon emissions; (2). Fertilizer application, technological progress, and planting structure factors have a significant positive effect on net carbon sinks, among which the changes in the planting industry structure have the greatest impact on net carbon sinks. Based on the comprehensive analysis, it is suggested that, under the guidance of the government, resource endowment and location advantages should be given full play to, and the internal planting structure of crops should be reasonably adjusted so as to promote the development of low-carbon agriculture and accelerate the development process of agricultural modernization.
Keywords	three provinces in Northeast China ; low-carbon agriculture ; plantation structure ; carbon emissions ; net carbon sinks ; Medicine ; R
Subject code	550
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Spatial Characteristics of Sustainable Development for Agricultural Products E-Commerce at County-Level

Zhiheng Chen / Wen Shu / Hongpeng Guo / Chulin Pan

Sustainability, Vol 13, Iss 6557, p

Based on the Empirical Analysis of China

2021 Volume 6557

Abstract: This paper used the sectional data of Chinese counties to analyze the spatial distribution characteristics of sustainable development of e-commerce for agricultural products in China at the county-level. The standard deviation ellipses and Moran’s index ... ...

Abstract	This paper used the sectional data of Chinese counties to analyze the spatial distribution characteristics of sustainable development of e-commerce for agricultural products in China at the county-level. The standard deviation ellipses and Moran’s index were used to research this subject. Then, by constructing spatial measurement models, the spatial spillover effects and influencing factors of the development of county-level agricultural products e-commerce were analyzed from economic development, economic structure, economic vitality, and agricultural development. The results show that: (1) the top 100 counties of agricultural products e-commerce mainly concentrate in southeastern China, spreading along the northeast and southwest; (2) the county-level agricultural products e-commerce shows significant negative spatial spillover effects; (3) the level of economic development and public services have a positive impact on the development of county-level agricultural products e-commerce, while the level of industrial development shows a negative correlation; (4) the level of agricultural development and industrial development have a significant negative external effect on the development of agricultural products e-commerce. This study is of great significance to promote the sustainable development of agricultural products e-commerce, the process of rural urbanization and the optimization of county industrial patterns.
Keywords	chinese county ; factor analysis ; spatial spillover ; standard deviation ellipse ; spatial durbin model ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Assessment on Agricultural Drought Vulnerability and Spatial Heterogeneity Study in China

Hongpeng Guo / Jia Chen / Chulin Pan

International Journal of Environmental Research and Public Health, Vol 18, Iss 4449, p

2021 Volume 4449

Abstract: Reducing drought vulnerability is a basis to achieve sustainable development in agriculture. The study focuses on agricultural drought vulnerability in China by selecting 12 indicators from two aspects: drought sensitivity and resilience to drought. In ... ...

Abstract	Reducing drought vulnerability is a basis to achieve sustainable development in agriculture. The study focuses on agricultural drought vulnerability in China by selecting 12 indicators from two aspects: drought sensitivity and resilience to drought. In this study, the degree of agricultural drought vulnerability in China has been evaluated by entropy weight method and weighted comprehensive scoring method. The influencing factors have also been analyzed by a contribution model. The results show that: (1) From 1978 to 2018, agricultural drought vulnerability showed a decreasing trend in China with more less vulnerable to mildly vulnerable cities, and less highly vulnerable cities. At the same time, there is a trend where highly vulnerable cities have been converted to mildly vulnerable cities, whereas mildly vulnerable cities have been converted to less vulnerable cities. (2) This paper analyzes the influencing factors of agricultural drought vulnerability by dividing China into six geographic regions. It reveals that the contribution rate of resilience index is over 50% in the central, southern, and eastern parts of China, where agricultural drought vulnerability is relatively low. However, the contribution rate of sensitivity is 75% in the Southwest and Northwest region, where the agricultural drought vulnerability is relatively high. Among influencing factors, the multiple-crop index, the proportion of the rural population and the forest coverage rate have higher contribution rate. This study carries reference significance for understanding the vulnerability of agricultural drought in China and it provides measures for drought prevention and mitigation.
Keywords	agricultural drought vulnerability ; spatial heterogeneity ; entropy weight method ; contribution model ; China ; Medicine ; R
Subject code	950
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Sustainability of Fresh Agricultural Produce Live Broadcast Development

Hongpeng Guo / Xiangnan Sun / Chulin Pan / Shuang Xu / Nan Yan

Sustainability, Vol 14, Iss 7159, p

Influence on Consumer Purchase Intentions Based on Live Broadcast Characteristics

2022 Volume 7159

Abstract: This paper is based on consumer purchase decisions and uses the consumers of live fresh agricultural products as the research object. We analyze consumers’ intention to purchase and analyze the role of perceived risk and value co-creation in consumers’ ... ...

Abstract	This paper is based on consumer purchase decisions and uses the consumers of live fresh agricultural products as the research object. We analyze consumers’ intention to purchase and analyze the role of perceived risk and value co-creation in consumers’ purchase of fresh agriculture products. Structural equation modeling analysis and stepwise regression coefficient analysis were used. The results show that: (1) the fresh agricultural products’ live features can positively influence consumers’ intention to buy; (2) the authenticity of fresh agricultural products live broadcast shows a significant negative correlation with perceived risk, and the visibility of fresh agricultural products live broadcast shows a significant positive correlation with value co-creation; (3) the perceived risk and value co-creation mediate between the live-stream features of fresh agricultural products and consumers’ intention to buy. The study results provide a basis for management decisions on the live broadcast of fresh agricultural products. It also has important implications for the sustainability of live broadcast of fresh agricultural products.
Keywords	fresh agricultural products ; live broadcast ; consumer purchase intention ; sustainability ; China ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	630
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study on Mechanisms Underlying Changes in Agricultural Carbon Emissions

Hongpeng Guo / Boqun Fan / Chulin Pan

International Journal of Environmental Research and Public Health, Vol 18, Iss 919, p

A Case in Jilin Province, China, 1998–2018

2021 Volume 919

Abstract: Reducing agricultural carbon emissions (ACE) is a key point to achieve green and sustainable development in agriculture. Based on the ACE statistics of Jilin Province in China from 1998 to 2018, this article considers the sources of ACE in depth, and ... ...

Abstract	Reducing agricultural carbon emissions (ACE) is a key point to achieve green and sustainable development in agriculture. Based on the ACE statistics of Jilin Province in China from 1998 to 2018, this article considers the sources of ACE in depth, and fourteen different carbon sources are selected to calculate ACE. Besides, the paper explores the variation characteristics of ACE in Jilin Province, their structure, and the relationship between the intensity and density of the dynamic changes in ACE in the province in terms of time. Finally, this paper uses the Kaya identity and logarithmic mean Divisia index (LMDI) to analyze the influential factors in ACE. The results show the following: (1) During 1998–2018, the amount of ACE in Jilin Province increased, with an average annual growth rate of 1.13%. However, the chain growth rate has been negative in recent years, which reflects that carbon emission reduction has been achieved to a certain extent. (2) The characteristics of ACE in Jilin Province during the years is that of the low-intensity, high density category. Furthermore, agricultural resource input is the main source of the planting industry’s carbon emissions. From the perspective of animal husbandry, the proportion of CH 4 decreased, while the proportion of N 2 O is relatively stable. (3) Based on the LMDI decomposition model, production efficiency, industrial structure, and labor are the three main factors that reduce ACE in Jilin Province. The economic level is the main factor of ACE, and it will be the most important factor leading to an increase in ACE in the short term. On the basis of comprehensive analysis, this article puts forward reasonable suggestions in terms of policy improvement, production mode and industrial structure adjustment, technological innovation, and talent introduction.
Keywords	China Jilin Province ; agricultural carbon emissions ; carbon emission influential factors ; LMDI decomposition model ; strategy for carbon emission reduction ; Medicine ; R
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Analysis in the Influencing Factors of Climate-Responsive Behaviors of Maize Growers

Hongpeng Guo / Yujie Xia / Chulin Pan / Qingyong Lei / Hong Pan

International Journal of Environmental Research and Public Health, Vol 19, Iss 4274, p

Evidence from China

2022 Volume 4274

Abstract: Due to the natural production properties, agriculture has been adversely affected by global warming. As an important link between individual household farmers and modern agriculture, it is crucial to study the influence of agricultural productive ... ...

Abstract	Due to the natural production properties, agriculture has been adversely affected by global warming. As an important link between individual household farmers and modern agriculture, it is crucial to study the influence of agricultural productive services on farmers’ climate-responsive behaviors to promote sustainable development and improve agricultural production. In this paper, a questionnaire survey has been conducted among 374 maize farmers by using the combination of typical sampling and random sampling in Jilin Province of China. Moreover, the Poisson regression and the multi-variate Probit model have been used to analyze the effects of agricultural productive services on the choices of climate-responsive behaviors as well as the intensity of the behaviors. The results have shown that the switch to suitable varieties according to the frost-free period have been mostly common among maize growers in Jilin province. Agricultural productive services have a significant effect on the adoption intensity of climate- responsive behaviors, at the 1% level. Based on this conclusion, this paper proposes policy recommendations for establishing a sound agricultural social service system and strengthening the support for agricultural productive services. It has certain reference significance for avoiding climate risk and reducing agricultural pollution in regions with similar production characteristics worldwide.
Keywords	multi-variate Probit model ; Poisson regression model ; agricultural productive services ; Medicine ; R
Subject code	381
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Greenhouse Gas Emissions from Beef Cattle Breeding Based on the Ecological Cycle Model

Hongpeng Guo / Zixu Su / Xiao Yang / Shuang Xu / Hong Pan

International Journal of Environmental Research and Public Health, Vol 19, Iss 9481, p

2022 Volume 9481

Abstract: Over the past few decades, the supply of beef has increasingly become available with the great improvement of the quality of life, especially in developing countries. However, along with the demand for meat products of high quality and the transformation ...

Abstract	Over the past few decades, the supply of beef has increasingly become available with the great improvement of the quality of life, especially in developing countries. However, along with the demand for meat products of high quality and the transformation of dietary structure, the impact of massive agricultural greenhouse gas emissions on the environmental load cannot be ignored. Therefore, the objective of this study is to predict the annual greenhouse gas emissions of 10 million heads of beef cattle under both the ecological cycle model (EC model) and the non-ecological cycle model (non-EC model), respectively, in order to compare the differences between these two production models in each process, and thus explore which one is more sustainable and environmentally friendly. To this end, through the life cycle assessment (LCA), this paper performs relevant calculations according to the methodology of 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2019 IPCC Inventories). The results have shown that the total GHG emissions of the non-EC model were almost 4 times higher than those of the EC model, and feed-grain cultivation and manure management were main emission sources in both models. The non-EC model produced significantly more emissions than the EC model in each kind of GHG, especially the largest gap between these two was in CO 2 emissions that accounted for 68.01% and 56.17% of the respective planting and breeding systems. This study demonstrates that the transformation of a beef cattle breeding model has a significant direct impact on cutting agricultural GHG emissions, and persuades other countries in the similar situation to vigorously advocate ecological cycling breeding model instead of the traditional ones so that promotes coordinated development between planting industry and beef cattle breeding industry.
Keywords	life cycle assessment ; ecological cycle ; beef cattle breeding ; greenhouse gas emissions ; Medicine ; R
Subject code	660
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Measurement of the Spatial Complexity and Its Influencing Factors of Agricultural Green Development in China

Hongpeng Guo / Shuang Xu / Chulin Pan

Sustainability, Vol 12, Iss 9259, p

2020 Volume 9259

Abstract: The article focuses on the spatial complexity of agricultural green development (AGD) in different regions. The article first constructs an evaluation index system for the level of AGD from four dimensions: Social development, economic benefits, resource ...

Abstract	The article focuses on the spatial complexity of agricultural green development (AGD) in different regions. The article first constructs an evaluation index system for the level of AGD from four dimensions: Social development, economic benefits, resource input, and ecological environment. Then, the article uses an improved entropy weight method to evaluate the level of AGD with panel data of 31 provinces in China from 2007 to 2018. Finally, on the basis of Moran Index and the Spatial Durbin Model, the article analyzes the spatial heterogeneity of the factors that affect the green development of agriculture in China. The results show that: (1) From 2007 to 2018, the overall level of AGD shows a fluctuating upward trend in China, and there are differences among provinces. The level of AGD in the three major regions presents the characteristics of Eastern > Central > Western; (2) China’s provincial AGD level has an obvious positive autocorrelation in spatial distribution, showing significant spatial agglomeration characteristics in space; (3) the four factors of urbanization level, agricultural mechanization level, scientific and technological R&D investment, and arable area, have different effects on the level of AGD in three major regions. This study provides a reference for understanding the status of China’s agricultural green development level and policy recommendations on how to improve the level of agricultural green development. The results imply that some effective policy measures, such as prompting the integrated development of the three major industries and optimizing the industrial structure, should be taken to coordinate “green” with “development” from national and regional perspectives.
Keywords	agricultural green development ; entropy weight method ; spatial heterogeneity ; spatial spillover effect ; China ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2020-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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