Vibration accelerations were measured on a compact wheel loader during 11 operations with two drivers and with/without the activated boom suspension system (BSS). Two standards, ISO 2631-1 (1985) and ISO 2631-1 (1997), were used to assess the effect of wheel loader vibration on comfort. The assessment results of ISO 2631-1 (1985) showed that vibration in the frequency range from 4 to 20 Hz in the vertical direction and in the frequency range from 1.6 to 3.15 Hz in the vertical and driving directions plays an important role in comfort assessment. The overall total values of vibration measured on the wheel loader in all operations exceeded the ‘uncomfortable’ boundary specified in ISO 2631-1 (1997). The speed had a larger influence on the vibration intensity than the bucket load, the BSS or the driver biodynamic response during driving. During driving and V-cycle, the difference of vibration intensity with two drivers in the z-direction is larger than that in the x- and y-direction.

The evaluation of community disaster resilience is of great practical importance for building low-risk, sustainable, and disaster-resistant cities. With 12 communities in Luoyang as the objects, this paper adopts entropy weight TOPSIS and obstacle diagnosis to study the community disaster resilience of Luoyang from seven dimensions, such as demographic characteristics, economic development, and infrastructure. The results of the study are as follows: (1) the community disaster resilience of Luoyang (0.48) is at a medium level. Community capital is the main influencing factor of community disaster resilience. Government governance, community capacity, and community intelligence are the components that need attention in the construction of Luoyang’s community disaster resilience. (2) The community disaster resilience of Luoyang presents a decreasing trend from rural to urban areas. Moreover, communities with high disaster resilience are less than communities with low disaster resilience. (3) The obstacle to community disaster resilience of Luoyang focuses on population, economic development, and infrastructure. In addition, community trust, community dependence, popularization and intellectualization of disaster prevention information, and disaster information sharing also significantly restrict the construction of Luoyang community disaster resilience. (4) According to the results of sensitivity analysis, the entropy weight TOPSIS evaluation results are less sensitive. Moreover, changing the weight value, weight method, and evaluation method will not lead to major changes in the rankings.

Improving agricultural eco-efficiency (AEE) is a promising way to achieve the sustainability of agricultural development. Although AEE evaluation and driving forces were widely explored, few studies have systematically examined how urbanization, the core driving force, affected AEE. To supplement the existing literature, the GB-US-SBM model was used to assess AEE in China during 2004–2020. Furtherly, it used the mediation effect model to investigate how urbanization influenced the AEE in different agriculture development regions by reducing agricultural labor and changing rural residents’ income. The results showed that: 1) During 2004–2020, China’s AEE revealed a stable improvement, with the mean score increasing from 0.138 to 0.744. Regarding spatial distribution, AEE exhibited a gradient decrease: optimized development region > moderate development region > protected development region. 2) Urbanization had a significantly positive effect on AEE, with the magnitude of the effect greatest in the protected development region, followed by the moderate development region and the optimized development region. 3) The mediator variables, agricultural labor and rural residents’ income, positively mediated the relationship between urbanization and AEE, and the former had a larger mediating effect. Notably, rural residents’ income did not mediate the effect of urbanization on AEE in the protected development region. According to the findings, to improve sustainable agriculture development and urbanization development in China, some policy suggestions were put forward from the aspects of transforming agricultural development mode, accelerating the urbanization process, enhancing vocational education for the middle-aged and young rural labor force, and expanding channels for increasing rural residents’ income.

The inequality in CO₂ emissions from agricultural energy consumption is a major challenge for coordinating low-carbon agricultural development across regions in China. However, the evolutionary characteristics and driving factors of inequality in China’s agricultural energy-related CO₂ emissions are poorly understood. In response, the Kaya–Theil model was adopted to examine the three potential factors influencing CO₂ emission inequality in China’s agricultural energy consumption. The results revealed that, from 1997 to 2021, agricultural energy-related CO₂ emissions per capita showed a significant upward trend, with prominent polarization and right-tailing phenomena. Overall, the inequality was on a downward trend, with the Theil index falling from 0.4109 in 1997 to 0.1957 in 2021. Meanwhile, the decomposition of the national inequality revealed that the within-group inequality declined from 0.3991 to 0.1634, which was greater than between-group inequality, based on zoning the 28 provinces into three grain production functional areas. As for the three kaya factors, the energy intensity contributed the most to the overall inequality, followed by the agricultural economic development and CO₂ emission intensity. Based on these results, this study provided some potential strategies to reduce agricultural-related CO₂ emissions.

Economic development highly depends on resources and the environment, especially in the Yellow River Basin (YRB), a crucial ecological protection and high-quality development pilot zone in China. Thus, evaluating high-quality economic development (HQED) and its decoupling relationship with the resource environment is conducive to planning future regional development. First, this paper used the two-stage entropy method to measure the high-quality economic development of cities in the YRB from 2010 to 2019. Then, the comprehensive decoupling analysis of the resource environment and high-quality economic development was carried out based on the Tapio decoupling model. The results showed that: (1) The high-quality economic development level improved slowly in the YRB. Nevertheless, the resource and environmental pressure gradually decreased. (2) Compared with the resource decoupling index, the environmental decoupling index had a greater impact on the comprehensive decoupling index in the YRB. The strong decoupling displayed a spatial diffusion trend from point to surface. (3) Despite the decoupling types having a positive transfer trend in the YRB, the decoupling states of cities fluctuated considerably, and the phenomenon of recoupling occurred frequently. According to the above findings, this study put forward some policy recommendations for achieving strong decoupling in the YRB.

The current article aimed to characterize the spatial–temporal characteristics and the driving factors of disaster-induced grain yield loss. Taking the world’s largest agricultural country, China, as the research object, this study evaluated China’s disaster-induced grain yield loss from 1978 to 2019 and investigated the contribution of three driving factors, using a logarithmic mean Divisia index (LMDI) approach. The results showed that drought and flood were the main disasters causing grain yield losses in China. China’s grain disaster loss peaked in 2000 and then entered a declining period. In terms of spatial distribution, disaster-induced grain yield loss mainly concentrated in the regions including the Middle-Lower Yangtze region, the Huang-Huai-Hai region, and Northeast China. The gravity center of disaster-induced grain yield loss shifted northward in China. Disaster intensity contributed the most to change in disaster-induced grain yield loss, followed by yield loss density, and the grain planting area. Thus, addressing drought and flood disasters, and enhancing disaster prevention and reduction capacity are critical to reduce disaster-induced grain yield loss, especially in the Middle-Lower Yangtze, the Huang-Huai-Hai region, and Northeast China.