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Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1–12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991–1994 for 38 months and the driest one in 2015–2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition.

Virtual water flows have a profound impact on the natural water system of a country or region, and they may help conserve local water resources or exacerbate water scarcity in some areas. However, current research has only focused on the measurement of virtual water flows, without analysis of the causes of virtual water flow patterns. This study first obtained virtual water flow patterns across provinces by constructing a multi-regional input–-output (MRIO) model of the Yellow River basin in 2012 and 2017, and then analyzed its driving factors by applying the extended STIRPAT model to provide directions for using virtual water trade to alleviate water shortages in water-scarce areas of the basin. We found the following: (1) The Yellow River basin as a whole had a net virtual water inflow in 2012 and 2017, and the net inflow has increased from 2.14 billion m3 to 33.67 billion m3. (2) Different provinces or regions assume different roles in the virtual water trade within the basin. (3) There is an obvious regional heterogeneity in the virtual water flows in different subsectors. (4) Per capita GDP, tertiary industry contribution rate, consumer price index, and water scarcity are the main positive drivers of virtual water inflow in the Yellow River Basin provinces, while primary industry contribution rate, per capita water resources, and water use per unit arable area promote virtual water outflow. The results of this paper present useful information for understanding the driving factors of virtual water flow, which could promote the optimal allocation of water resources in the Yellow River basin and achieve ecological protection and high-quality development in this area.

The output of municipal solid waste is growing rapidly, which has brought tremendous pressure to urban development. The supply chain of municipal solid waste (MSW) in China mainly contains three processes: collection, transportation, and disposal. The waste is sorted at the collection and disposed of according to the classification. However, it is mixed at the transportation stage. Mixed transportation remixes the separately collected waste, which seriously affects the disposal effect. The supply chain of MSW urgently needs to be redesigned to improve the MSW disposal effect. First of all, on the ground of the waste treatment situation, we redesigned the supply chain of MSW in China. Secondly, combined with the redesign of the MSW supply chain, this paper established the function allocation model for collection stations, making a collection station only gather one type of waste, and built the transportation path planning model for vehicles, reducing the impact of waste storage on residents. Finally, based on the data of Xuanwu District in Beijing, the supply chain redesigning practical example of incinerable waste was given. The supply chain redesigning model in this paper not only makes full use of the existing infrastructure but also improves the disposal effect of waste. The supply chain redesigning model has practical application value.

Exploring the sensitivity of rural households’ livelihood strategies to livelihood capital is of great significance for improving rural households’ livelihood levels. This paper selects 23 livelihood capital measurement indicators and conducts an in-depth survey of rural households. In addition, the entropy method and a weighted comprehensive model are used to explore the basic characteristics of rural households’ livelihood capital in the upper reaches of the Min River, China, in 2017. Furthermore, econometric models are used to analyze the sensitivity of rural households’ livelihood strategies to livelihood capital. As indicated from the research, the livelihood capital levels of different types of rural households in the study area are not equivalent. The types of rural households with different livelihood strategies can be ordered in terms of quantity as follows: non-agricultural type > non-agricultural dominant type > agricultural dominant type > pure agricultural type. Livelihood strategies have different sensitivities to different livelihood capital measurement indicators. Among these indicators, cash income, the number of relatives and friends available for financial assistance, and the number of civil servants have positive effects on the livelihood strategy selection of non-agricultural dominant rural households and non-agricultural rural households. However, the average age of laborers, area of cultivated land and gardens, number of livestock and poultry, and present value of production tools have negative effects. These evaluation results can provide a scientific decision-making basis for the formulation of poverty alleviation policies by relevant government departments.

In this work, the impact of exogenous aerobic bacteria mixture (EABM) on municipal solid waste (MSW) is well evaluated in the following aspects: biogas production, leachate analysis, organic waste degradation, EABM population, and the composition of microbial communities. The study was designed and performed as follows: the control bioreactor (R1) was filled up with MSW and the culture medium of EABM and the experimental bioreactor (R2) was filled up with MSW and EABM. The data suggests that the composition of microbial communities (bacterial and methanogenic) in R1 and R2 were similar at day 0, while the addition of EABM in R2 led to a differential abundance of Bacillus cereus, Bacillus subtilis, Staphylococcus saprophyticus, Staphlyoccus xylosus, and Pantoea agglomerans in two bioreactors. The population of exogenous aerobic bacteria in R2 greatly increased during hydrolysis and acidogenesis stages, and subsequently increased the degradation of volatile solid (VS), protein, lipid, and lignin by 59.25%, 25.68%, 60.47%, and 197.62%, respectively, compared to R1. The duration of hydrolysis and acidogenesis in R2 was 33.33% shorter than that in R1. At the end of the study, the accumulative methane yield in R2 (494.4 L) was almost three times more than that in R1 (187.4 L). In addition, the abundance of acetoclasic methanogens increased at acetogenesis and methanogenesis stages in both bioreactors, which indicates that acetoclasic methanogens (especially Methanoseata) could contribute to methane production. This study demonstrates that EABM can accelerate organic waste degradation to promote MSW biodegradation and methane production. Moreover, the operational parameters helped EABM to generate 20.85% more in accumulative methane yield. With a better understanding of how EABM affects MSW and the composition of bacterial community, this study offers a potential practical approach to MSW disposal and cleaner energy generation worldwide.

In the karst area of southern China, karst water is important for supporting the sustainable production and home living for the local residents. Consequently, it is of significance to fully understand the water cycle, so as to make full use of water resources. In karst areas, epikarst and conduits are developed, participating in the hydrological cycle actively. For conventional lumped hydrologic models, it is difficult to simulate the hydrological cycle accurately. These models neglect to consider the variation of underlying surface and weather change. Meanwhile, for the original distributed hydrological model, the existence of epikarst and underground conduits as well as inadequate data information also make it difficult to achieve accurate simulation. To this end, the framework combining the advantages of lumped model–reservoir model and distributed hydrologic model–Soil and Water Assessment Tool (SWAT) model is established to simulate the water cycle efficiently in a karst area. Xianghualing karst watershed in southern China was selected as the study area and the improved SWAT model was used to simulate the water cycle. Results show that the indicators of ENS and R2 in the calibration and verification periods are both above 0.8, which is evidently improved in comparison with the original model. The improved SWAT model is verified to have better efficiency in describing the hydrological cycle in a typical karst area.

As an important livelihood strategy choice to promote the sustainable development of themselves and regions, returnees’ entrepreneurship has played a vital role in the governance of all-level Chinese local governments since the 21st century. The policy attention reflects the importance that the local governments attach to this issue, and the evolution process also reflects relevant policies’ internal rules and characteristics. Based on this, this paper, taking 242 policy texts related to returnees’ entrepreneurship issued by local governments from 2000 to 2021 as the research objects, uses grounded theory and social network analysis in order to explore the policy attention evolution from the aspects of time, space, specific policy domains and cooperative relationship among policy subjects. Finally, this research finds the main conclusions as follows: (1) The policy attention evolution on time dimension has the characteristic of synchronism, different levels and “reciprocal U”. (2) The policy attention evolution on space dimension is closely linked to “pull” and “push” forces of local population flow and has neighborhood effects. (3) The policy attention evolution on specific policy areas will gradually spread and diversify with the change in local governance environment and stage goals. (4) The evolution trend of collaborative social network among policy objects has the characteristic of “loose-central-loose”.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.