Effectively identifying and restoring the livelihood resilience of rural vulnerable populations are essential for consolidating poverty alleviation achievements. Previous studies have focused on low-income populations and have classified assistance for monitoring rural vulnerability. However, little research has defined the rural vulnerable and their key influencing factors from a multi-dimensional perspective. This paper constructs an indicator system for monitoring the return to poverty from a multi-dimensional perspective, based on survey data from rural households in poverty-stricken areas in 2005 and 2015. The dual cut-off method is used to identify the rural vulnerable and their key influencing factors from a multi-dimensional perspective. The results show that: (1) The incidence of multi-dimensional poverty has significantly decreased from 2005 to 2015; However, a vulnerable group still exists in rural China in 2015, and types of multi-dimensional poverty vary among regions. (2) Geographical environment and social resources are the primary influencing factors of rural vulnerability, followed by living standards. Income remains an important influencing factor of severe multi-dimensional poverty. (3) To restore the livelihood resilience of the rural vulnerable, targeted policies should be implemented based on influencing factors such as geographical environment and social resources. This study has significant reference value for policy implementation aimed at restoring the livelihood resilience of the rural vulnerable.

Poverty is a pressing social and economic issue that demands attention. Reducing and eliminating poverty are shared objectives globally. Current studies often rely on existing theoretical models or survey questions when selecting dimensions and indicators, which may have limitations. Few researchers have offered a comprehensive framework for indicator selection based on data sources. The measurement of multi-dimensional poverty primarily relies on the use of the Multi-dimensional Poverty Index (MPI). However, there is a lack of systematic research on the selection of indicator systems and their respective weights. This study used in-depth literature analysis and systematic literature review (SLR) methods to sort out and integrate indicator systems and evaluation methods of multi-dimensional poverty evaluation (MPE). The results indicate that: (1) The indicator systems of MPE should include the following dimensions: economic, health, education, living standard, social relationship and natural environment for both household and regional level; (2) MPE based on multi-source data could reduce the difficulty and costs of field survey, increase comparability and convenience, and be more objective and reliable, which would be an important direction for future related research; And (3) Hybrid method would be more reasonable than the single weighting method, which could minimize the loss of information and make the weighting result as close as possible to the actual result. We propose to establish a dynamic monitoring system based on multi-source data, which could offer new insights for sustainable poverty monitoring.

Reliable and affordable energy supply is the key to achieving sustainable development goals (SDGs) aimed at alleviating poverty. However, few studies explore renewable energy and poverty alleviation (RE-PA) practices and RE-PA nexus from a text mining perspective. This paper aims to find the research concerns of the RE-PA nexus and propose a conceptual framework for the synthesis of renewable energy, poverty alleviation, and SDGs. Topic modelling method and Latent Dirichlet Allocation model were adopted, and 5333 records were obtained from Web of Science and the 12-topic model was used to reveal the latent intellectual structure of the current research on RE-PA nexus. The results suggest that the top research concerns of the RE-PA nexus are sustainable energy development, country resource policy, and economic-environmental-social sustainability. Energy access of rural households, ecosystem services, and renewable energy performance are three essential future research directions. The top research concerns and future research directions would help to further explore the RE-PA nexus. This study could also provide a basis for integrated policy recommendations for renewable energy development and poverty alleviation while pursuing SDGs on energy and poverty.

Eradicating poverty is the primary goal for pursuing equitable and sustainable development of the world. Rural land consolidation (RLC) aims to achieve efficient and sustainable land use while promoting poverty alleviation. This study empirically examined the impact of RLC on multi-dimensional poverty, using the difference-indifferences (DID) method and survey data from impoverished households. Additionally, the role of human capital in moderating the impact of RLC on poverty alleviation is also emphasised. We found that (1) The RLC has had a positive and significant impact on the improvement of impoverished households' livelihoods in China. (2) Human capital (migrant worker, labour force, and education) has a positive moderating effect on the impact of RLC on poverty alleviation, and education exerts the most obvious moderating effect. We suggest that the Chinese government should not only continue to increase investment in and provide supporting policy for RLC, but also develop targeted RLC strategies. Education, labour capability, sustainable poverty reduction, sustainable land use, and sustainable rural development require sustained attention. It also could help to improve policy and decision-making for effective poverty reduction, sustainable rural development, and rural revitalisation.