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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.

To reduce plastic waste generation from failed product batches during industrial injection molding, the sustainable production of representative prototypes is essential. Interesting is the more recent hybrid injection molding (HM) technique, in which a polymeric mold core and cavity are produced via additive manufacturing (AM) and are both placed in an overall metal housing for the final polymeric part production. HM requires less material waste and energy compared to conventional subtractive injection molding, at least if its process parameters are properly tuned. In the present work, several options of AM insert production are compared with full metal/steel mold inserts, selecting isotactic polypropylene as the injected polymer. These options are defined by both the AM method and the material considered and are evaluated with respect to the insert mechanical and conductive properties, also considering Moldex3D simulations. These simulations are conducted with inputted measured temperature-dependent AM material properties to identify in silico indicators for wear and to perform cooling cycle time minimization. It is shown that PolyJetted Digital acrylonitrile-butadiene-styrene (ABS) polymer and Multi jet fusioned (MJF) polyamide 11 (PA11) are the most promising. The former option has the best durability for thinner injection molded parts, and the latter option the best cooling cycle times at any thickness, highlighting the need to further develop AM options.

Digital Transformations (DT) play an increasingly important role in academia and business, yet their significant Environmental Footprint (EF) is often overlooked, sidelining their potential for Environmental Sustainability (ES). This paper bridges this gap by integrating ES into the discourse of DT, proposing Green Enterprise Architecture (GREAN) as a method for sustainable transformation. Utilizing a Design Science Research approach, we developed an artefact outlining a comprehensive strategy for embedding ES in DT across various layers of an organization. The tool’s need was validated via a systematic literature review (SLR), highlighting the significant research gap in Green Enterprise Architecture. The artefact provides concrete Courses of Action (CoAs) for incorporating ES into the organizational strategy, business, data, application, and technology layers and proposes relevant capabilities to address this. The paper further presents an ES-aware business capability modelling, an innovative business modelling approach that integrates environmental sustainability principles by using (in a novel way) the presentation and analysis methods that capability mapping offers. The proposed artefact serves as a starting point for environmentally sustainable DTs. Future research directions include in-depth exploration of each enterprise layer for ES, real-world validation of our proposed tools and concepts, and the expansion of these into a full framework.

Walkability has become a research topic of great concern for preserving public health, especially in the era of the COVID-19 outbreak. Today more than ever, urban and transport policies, constrained by social distancing measures and travel restrictions, must be conceptualized and implemented with a particular emphasis on sustainable walkability. Most of the walkability models apply observation and subjective methods to measure walkability, whereas few studies address walkability based on sense perception. To fill this gap, we aim at investigating the perceived neighbourhood walkability (PNW) based on sense perception in a neighbourhood of Brussels. We designed a survey that integrates 22 items grouped into 5 dimensions (cleanness, visual aesthetics, landscape and nature, feeling of pressure, feeling of safety), as well as the socio-demographic attributes of the participants. Using various statistical methods, we show that socio-demographics have almost no effects on perceived neighbourhood walkability. Nonetheless, we found significant differences between groups of different educational backgrounds. Furthermore, using a binomial regression model, we found strong associations between PNW and at least one item from each grouping dimension. Finally, we show that based on a deep neural network for classification, the items have good predictive capabilities (78% of classification accuracy). These findings can help integrate sense perception into objective measurement methods of walkable environments. Additionally, policy recommendations should be targeted based on differences of perception across socio-demographic groups.

This study investigates the extending negative effects of impression management (IM) on organizational outcomes in the nursing context. Specifically, this study aims to understand the impact of IM on workplace exclusion through workplace deviance. The data came from 277 head nurses (nurses in leadership positions) in elderly care homes in Belgium. Structured paper-and-pencil questionnaires were administered on site in the respondents’ workplaces. In the findings of the current research, IM is positively related to workplace exclusion and the relationship is mediated by workplace deviance. Although, initially, IM is performed by the actors as a natural behavior to maintain their image, at some point, the actors can become fatigued with maintaining their image. Under ego depletion theory, the exhausted IM actors will be highly experienced in deviance or bad performance. Furthermore, consistent with social information processing theory and a correlation study between employees’ poor performance and workplace exclusion, the IM actors who fail to deliver good performance or behavior following their like-based rewards may be subject to social exclusion in their workplace.

Bio-based plastics are increasingly appearing in a range of consumption products, and after use they often end up in technical recycling chains. Bio-based plastics are different from fossil-based ones and could disturb the current recycling of plastics and hence inhibit the closure of plastic cycles, which is undesirable given the current focus on a transition towards a circular economy. In this paper, this risk has been assessed via three elaborated case studies using data and information retrieved through an extended literature search. No overall risks were revealed for bio-based plastics as a group; rather, every bio-based plastic is to be considered as a potential separate source of contamination in current recycling practices. For PLA (polylactic acid), a severe incompatibility with PET (polyethylene terephthalate) recycling is known; hence, future risks are assessed by measuring amounts of PLA ending up in PET waste streams. For PHA (polyhydroxy alkanoate) there is no risk currently, but it will be crucial to monitor future application development. For PEF (polyethylene furanoate), a particular approach for contamination-related issues has been included in the upcoming market introduction. With respect to developing policy, it is important that any introduction of novel plastics is well guided from a system perspective and with a particular eye on incompatibilities with current and upcoming practices in the recycling of plastics.

Rural planning is in a state of flux, covering a range of topics. The objectives of planning have evolved over the years. To get an overview of the evolving themes and narratives on rural planning in China, a literature review is conducted here using text mining considering 145 papers published in Web of Science. Attention is given to trends over time in terms of the topics covered. Six evolving themes are revealed, namely: providing affordable and decent life under industrialization and urbanization progress, national ecological programs and practices, building a new (socialist) countryside and rural−urban relationship in planning, land planning and restructuring, rural tourism planning and activities, and other themes. It is highlighted that strategies and knowledge of “development” are a common instructional epistemology among agro-industrialism, agro-ruralism, scientific rationalism, and “economy oriented” humanism.

The environmental footprint of photovoltaic electricity is usually assessed using nominated power or life cycle energy output. If performance degradation is considered, a linear reduction in lifetime energy output is assumed. However, research has shown that the decrease in energy output over time does not necessarily follow a linear degradation pattern but can vary at different points in the module’s lifetime. Further, photovoltaic modules follow different degradation patterns in different climate zones. In this study, we address the influence of different degradation aspects on the greenhouse gas (GHG) emissions of PV electricity. Firstly, we apply different non-linear degradation scenarios to evaluate the GHG emissions and show that the differences in GHG emissions in comparison to a linear degradation can be up to 6.0%. Secondly, we use the ERA5 dataset generated by the ECMWF to calculate location-dependent degradation rates and apply them to estimate the location-specific GHG emissions. Due to the reduction in lifetime energy output, there is a direct correlation between the calculated degradation rate and GHG emissions. Thirdly, we assess the impact of climate change on degradation rates and on the respective GHG emissions of photovoltaic electricity using different climate change scenarios. In a best-case scenario, the GHG emissions are estimated to increase by around 5% until the year 2100 and by around 105% by 2100 for a worst-case scenario.