Influencing factors and spatiotemporal heterogeneity of livestock greenhouse gas emission: Evidence from the Yellow River Basin of China.

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO2e) in 2000 to 77.568 Mt CO2e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively.

Influencing factors and spatiotemporal heterogeneity of net carbon sink of conservation tillage: evidence from China.

Conservation tillage is an important reform of traditional tillage, which has significant carbon sequestration and emission reduction effects. It is important to investigate the influencing factors and spatiotemporal heterogeneity of net carbon sink of conservation tillage for realizing the "dual carbon" target, and facilitating agricultural sustainable development. This study used the coefficient accounting method to calculate the carbon sink and carbon emission of conservation tillage in China from 2000 to 2019, respectively. Based on this, the net carbon sink of conservation tillage was measured. Then, the spatiotemporal heterogeneity of influencing factors on net carbon sink of conservation tillage was analyzed by using the geographically and temporally weighted regression model. The results showed that (1) the net carbon sink of conservation tillage in China was significant and had potential to have a constant rise; (2) spatially, the net carbon sink of conservation tillage changed more variably in longitudinal direction. Specifically, the promotion effect of conservation tillage machinery gradually decreased from west to east. The planting structure and conservation tillage promotion intensity played key roles in improving net carbon sink of conservation tillage. (3) Temporally, the effect of conservation tillage machinery showed positive effect of decreasing yearly, while the positive effect of promotion intensity increased year by year. Planting structure and economic development negatively affected improvement on the net carbon sink of conservation tillage and the negative effect increased year by year. Additionally, the effect of education on the net carbon sink shifted from positive to negative over time. The study aims to provide a reference for the government to promote conservation tillage according to local conditions and to achieve the "dual carbon" target.

Identifying carbon emission characteristics and carbon peak in China based on the perspective of regional clusters.

Global warming has endangered the natural ecosystem's balance, as well as human existence and development, and it is mostly caused by carbon dioxide. Identifying carbon emission characteristics and predicting carbon emission reasonably is helpful to provide indication for the effective design of emission reduction path. The most literature use a single prediction model; this paper predicts carbon emission using a number of strategies based on previous research. Considering the prediction accuracy, advantages, and disadvantages of each method, a new method combining autoregressive integrated moving average (ARIMA) model and NAR neural network (NAR-NN) is proposed; in addition, this paper attempts to explain the carbon emission characteristics and emission reduction paths of each region from the new perspective of clustering. First, the results show that China's carbon emission features can be divided into four categories: low-carbon demonstrative type, low-carbon potential type, high-carbon developed type, and high-carbon traditional type. Moreover, low-carbon demonstrative type includes merely Beijing and Shanghai, low-carbon potential type is distributed in the southeast coastal areas of China, the high-carbon developed type is mainly distributed in Northeast China, and the western region basically belongs to high-carbon traditional type. Second, ARIMA model and NAR-NN are the two best methods in terms of prediction effect, and the combined model has better prediction effect than the single model. Third, carbon emissions in most regions of China will increase in the next few years; the time of carbon peak in the east is earlier than that in the west regions of China. Beijing will probably be the first region in China to complete the carbon peak. Besides, there is a certain correlation between the carbon peak time and the type of carbon emission in each region.

Evaluation of the Ecological Effects of Ecological Restoration Programs: A Case Study of the Sloping Land Conversion Program on the Loess Plateau, China.

The Sloping Land Conversion Program (SLCP) is the largest ecological restoration program in the world. Evaluating the ecological effects of the SLCP not only provides a scientific basis for China to improve the SLCP but also provides a reference for other countries in the world to evaluate the ecological effects of ecological restoration programs being implemented or to be implemented. To this end, we took the Loess Plateau, the core area for the implementation of the SLCP, as an example and, based on multi-source remote sensing data and GIS technology, we conducted a comprehensive evaluation of the ecological effects of the implementation of the SLCP on the Loess Plateau. The results showed that, first, from 2000 to 2018, a total of 12,372.05 km2 of cultivated land was converted into forest land and grassland on the Loess Plateau, and this contributed to an increase in vegetation cover from 45.09% in 2000 to 64.15% in 2018, and a decrease in the soil erosion modulus from 26.41 t·hm-2·yr-1 in 2000 to 17.92 t·hm-2·yr-1 in 2018. Second, the 6-25° slope range is the core area of the Loess Plateau for implementation of the SLCP. In this range, the area of cultivated land converted into forest land and grassland accounts for 60.16% of the total area of transferred cultivated land. As a result, the 6-25° slope range has become the most significant area for improving vegetation cover and reducing the soil erosion intensity, and it is mainly concentrated in the southwestern, central and central-eastern hilly and gully areas of the Loess Plateau. Third, from 2000 to 2018, the climate of the Loess Plateau tended to be warm and humid and was conducive to the implementation of the SLCP. Among these factors, precipitation is the dominant factor in determining the spatial distribution of vegetation on the Loess Plateau, and the increase in precipitation is also the main reason for the promotion of vegetation growth. Fourthly, from 2000 to 2018, the ecological environment of the Loess Plateau was significantly improved as a result of the combined effects of the implementation of the SLCP and climate warming and humidification, but the primary reason is still the implementation of the SLCP.

Evaluation and dynamic prediction of ecological security from the perspective of sustainable development: a case study of Shaanxi Province, China.

How to measure the overall level of regional social economy, resources, and environment and how to grasp the coordinated development between them has become a hot issue. In this paper, the driving force-pressure-state-response (DPSR) model is used to build an ecological security index (ESI) system to measure the overall ecological security level of social economy, resources, and environment. In addition, dynamic nonlinear auto regressive (NAR) neural network is used to predict the ESI level to achieve the purpose of early warning. First, the results show that the weight of the employment rate, the proportion of students in colleges, and the per capita consumption level are relatively high, which play an important role for the ecological security level of Shaanxi Province. Second, Xi'an City has been the best level in ecological security level, the ecological security of Southwest Shaanxi is relatively good, which is related to its economic development and comparative advantage geographical conditions, while the ecological security level of Weinan and Shangluo are poor. Third, the ESI of most cities in Shaanxi Province is maintained at grade III. The ESI in Shaanxi has an upward trend from 2000 to 2006; however, the trend of this increase has not been maintained, and nearly half of the cities in Shaanxi have slightly decreased the ecological security level. Four, the ESI of Xi'an and Hanzhong will remain at a high level in the future, while the ecological security situation of Shangluo, Weinan, and Yulin probably become very poor in the next years.

[Ecological compensation strategy of the old revolutionary base areas along the route of Long March based on ecosystem service value evaluation]. / 基于生态系统服务价值评估的长征沿线革命老区生态补偿策略.

The conflict between ecological protection and socio-economic development in the old revolutionary base areas along the route of Long March can be addressed by ecological compensation. In this study, we collected 2018 data of land use, net primary productivity of vegetation, climate factors and so on. The ecosystem service value of 310 counties in the old revolutionary base areas was calculated using the data and modified equivalent factor. Then, the regional differentiated ecological compensation estimation method was applied to estimate the priority and amount of ecological compensation within the area. We further proposed the ecological compensation strategy adopted for the old revolutionary base areas along the route of Long March. The results showed that the total value of ecosystem services in the old revolutionary base areas along the route of Long March amounted to 2593.74 billion yuan in 2018. Forest services took the highest proportion (58.8%), followed by grassland and waters. The total amount of ecological compensation made for the old revolutionary base areas along the route of Long March reached 183.405 billion yuan. Compared with this amount, there was a large gap in the actual compensation funds available to the region. In addition, the total amount of ecological compensation accounted for only 0.04% of the aggregate GDP in this area, which put some strain on local fiscal resources and showed certain viability in ecological compensation. In 2018, totally 100 old revolutionary base areas along the route of Long March were designated as the priority areas for ecological compensation, consistent with the national key eco-function zone policy. However, there were deviations in the allocation of ecological compensation funds, with some priority areas receiving no compensation. As for the compensation strategy, it is necessary to put in place a diversified, market-oriented and comprehensive ecological compensation mechanism to increase the sources of ecological compensation funds at first. Then, efforts should be continued to optimize the spatial selection of ecological compensation in the old revolutionary base areas along the route of Long March and to improve the efficiency of regional ecological compensation mechanism.

Spatial-temporal differentiation and its influencing factors of agricultural eco-efficiency in China based on geographic detector.

Exploring the spatial-temporal variations of agricultural eco-efficiency (AEE) and its driving factors is of vital importance to achieve high-quality agro-ecological development in China. In this study, we used the super efficiency slack-based measure (SBM) model to measure the inter-provincial AEE based on the relevant panel data of 30 provinces/regions/cities in China from 2000 to 2018. Based on the time series analysis, spatial visualization, and trend surface analysis, the geographical detector model was further used to identify the core factors driving the spatial-temporal variations of AEE. The results showed that China's AEE level maintained stable upward progress from 2000 to 2018, which was still at a low level with much room for improvement. The AEE in China exhibited a significant spatial-temporal variation, presenting higher levels in the eastern and western parts but lower in the central part. The spatial variation of AEE was influenced by many factors, including agricultural resource endowment, socioeconomic condition, and the natural ecological environment. There were obvious variations in the influence factors on the spatial-temporal variation of AEE. The interactions among factors would enhance the spatial variation of AEE. Therefore, due to the spatial-temporal variation of AEE, emphasis should be placed on its core driving factors as well as the inter-parts agricultural cooperation in order to achieve high-quality agro-ecological development in China.

Spatiotemporal Evolution and Influencing Factors of Carbon Sink Dynamics at County Scale: A Case Study of Shaanxi Province, China.

To explore the spatiotemporal evolution of carbon sinks in Shaanxi Province, and their impact mechanisms, this study used panel data from 107 counties (districts) in Shaanxi Province from 2000 to 2017. First, we conducted spatial distribution directional analysis and exploratory spatial data analysis (ESDA). Then, we constructed a geographic spatial weight matrix and used the spatial panel Durbin model to analyze the driving factors of carbon sink changes in Shaanxi Province, from the perspective of spatial effects. The results showed that: (1) The temporal evolution of carbon sinks during the study period showed an overall upward trend, but the carbon sinks of counties (districts) differed greatly, and the center of gravity of carbon sinks, as a whole, showed the characteristics of "south to north" migration. (2) The carbon sinks of Shaanxi Province have a significant positive global spatial autocorrelation in geographic space. The local spatial pattern was characterized by low-value agglomeration (low-low cluster) and high-value agglomeration (high-high cluster), supplemented by high-value bulge (high-low outlier) and low-value collapse (low-high outlier). (3) The result of the spatial measurement model proved that the spatial Durbin model, with dual fixed effects of time and space, should be selected. In the model results, factors such as population, per capita gross domestic product (GDP), local government general budget expenditure, and local government general budget revenue all reflect strong spatial spillover effects. Accordingly, in the process of promoting "carbon neutrality", the government needs to comprehensively consider the existence of spatial spillover effects between neighboring counties (districts), and strengthen the linkage-management and control roles of counties (districts) in increasing carbon sinks.

[Relationship Between Urban Industrialization and PM2.5 Concentration in China and the Internal Mechanism of EKC].

Based on the panel data of 255 cities in China, this study built a spatial Durbin model to study the impact of China's industrialization on the PM2.5 pollution level. Meanwhile, an environmental governance tool characterized by forest and grass coverage was introduced to explore the internal mechanism and exogenous driving force of EKC. The results show that ① the relationship between industrialization and PM2.5 concentration is obviously an inverted u-shaped, and the EKC hypothesis was verified. ② The formation of the EKC curve was caused by the external factors and not the endogenous mechanism of economic growth. Forest-grass coverage plays a regulating role in the relationship between industrialization and PM2.5 pollution level, namely the inverted u-shaped structure of environmental EKC results from environmental governance tool with forest and grass cover rather than the automatic adjustment of economic growth. ③ The influence of industrialization on PM2.5 concentration has a spatial spillover effect. Urban industrialization not only affects the PM2.5 concentration in local regions but also its neighboring region.

An empirical analysis of the effects of China's Land Conversion Program on farmers' income growth and labor transfer.

In this article, we hypothesize that in addition to participation status and household characteristics, the impact of China's Sloping Land Conversion Program on income growth and labor transfer is determined by local economic conditions, program range, and political leadership, and the degree of impact on income may vary among different economic sectors. To test these propositions, we have compiled a panel data set of 600 households in three counties in the Loess Plateau region, with observations for times both prior to and after the program's inception (1999 and 2006), for both aggregate and categorical incomes, and for both participating and non-participating households. Using a difference in differences model and repeated cross-sectional data, we find that participation status, local economic conditions, program extent, and political leadership indeed have significant impacts on household income and off-farm employment. Moreover, the effects of participation on crop production income, animal husbandry income, and off-farm income vary substantially. These results carry major policy implications in terms of how to improve the effectiveness and impact of ecological restoration efforts in and outside of China.

Agricultural productivity changes induced by the sloping land conversion program: an analysis of Wuqi county in the Loess Plateau region.

This paper examines the agricultural productivity change induced by the Sloping Land Conversion Program (SLCP) using the Malmquist index method and household data collected from Wuqi. We find that during the period of 1998-2004, the total factor productivity (TFP) grew by 15.8%. While numerous households suffered a TFP decline, the majority of them experienced a large gain. By decomposing the TFP, we further show that its increase is due exclusively to the improvement of technical efficiency rather than to technological change. To validate these findings and put them in perspective, we also estimated the TFP change with county-level aggregate data. It is revealed that driven by technological change and scale efficiency, the TFP grew slightly during the period of 1992-1998. Because of the tremendous cropland reduction and production mode shift caused by implementing the SLCP, the TFP declined substantially during the first three years of the program; due to continued improvement of technical efficiency; however, its growth accelerated later. Altogether, our evidence consistently suggests that implementing the SLCP has contributed to the agricultural TFP growth in the longer term and that the efficiency improvement has resulted mainly from the increased public expenditures for extension services and diffusion of technical knowledge. Wuqi's experience proves that it is possible to achieve environmental conservation and increase productivity simultaneously, even when facing a cropland reduction and production mode alternation.