• Energy Research
• 2021-2025close
• 6. Clean water close
• 16. Peace & justice close

In recent years, the rapid development of the rare earth industry has had a serious impact on the environment. Some enterprises have taken measures to improve the production process. In order to explore the sustainability of this industry and these improvements’ environmental benefits, this paper combines emergy analysis and lifecycle assessment to evaluate and compare the production process of rare-earth oxides considering the three aspects of emergy flow, pollutant emissions, and emergy-based indicators. Changes in the emergy of pollutant emissions before and after improvement of the production process are discussed. The results show that the greatest inputs in the mining and beneficiation stage and smelting separation stage are labor force and service and non-renewable resources, respectively. These two production stages are highly dependent on external input and have weak competitiveness. Both stages place great pressure on the environment, so the bastnasite production process would be unsustainable in the long term. After the improvement, the environmental impact of the production process for bastnaesite changed significantly, indicating that the improvement effect of the wastewater treatment facilities and the change of fuel from coal to natural gas is remarkable.

This study uses the structured–pragmatics–situational case study approach to explore the intrinsic mechanism of enterprise digital enablement using affordance theory and how traditional enterprises enable customers to participate in value co-creation through information technology, then realize business model innovation and maintain continuous consumption. The study revealed the following: (1) Product affordance drives customers’ original willingness to engage in value co-creation in four dimensions: economy, reliability, uniqueness, and selectivity; (2) The visibility, convenience, association, and persistence of the platform affordance enhance users’ abilities to engage in value co-creation; (3) The interaction of affordance, structural enablement, and digital enablement drives the interaction of willingness and capability to engage in value co-creation; and (4) User participation behaviors in value co-creation can be divided into three dimensions (informational, actionable, and attitudinal participation)and four stages. The findings explain how traditional enterprises use IT enablement to promote business model innovation of customer participation in value co-creation and enrich the theories of digital enablement. The conclusions reveal the managerial implications of the ways, paths, and mechanism of business model innovation by IT enabling customers to participate in value co-creation.

The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

Renewable energy (RE) can play a vital role in ensuring a sustainable energy platform for the future, and in addressing climate change. Investment in RE in the upper middle-income countries (UMICs), which are a major contributor to global carbon dioxide (CO[Formula: see text] emissions, can be an important recovery strategy for mitigating climate change damage. Existing literature suggests that governance (also referred to as ‘institutional quality’) is an important determinant of renewable energy investment (RE investment). Yet, governance conditions in UMICs have remained almost unchanged in the recent past, despite the substantive increases in income levels and investment in the RE sector. This paper outlines an investigation into the role of governance in RE investment in UMICs and considers whether the influence of governance on RE investment depends on a country’s income level. This analysis used pooled ordinary least squares (OLS), panel-corrected standard errors and panel-fixed effects models to evaluate data from 35 UMICs, from 1996 to 2017. The results suggest that good governance raises RE investment in UMICs. In particular, the control of corruption, government effectiveness, regulatory quality and rule of law are statistically significant aspects of good governance that boost RE investment. However, this effect is conditional on the level of economic development (income level) of a country. The marginal effect of governance on RE investment is larger in lower income countries and vice versa. Among the controls, trade openness in UMICs is predicted to have an adverse impact on RE investment.

Reducing natural resources caused by the growth of the world’s population, meeting the growing demands of consumers, and preventing environmental pollution requires the development of sustainable and efficient procedures that include the valorization of wastes [...]

The Nigerian government is committed to sustaining rice production to meet national demand. Nevertheless, political tension and climate-induced stressors remain crucial constraints in achieving policy targets. This study examines whether climate change and political instability significantly threaten rice production in Nigeria. First, we employed nonparametric methods to estimate the country's rainfall and temperature trends between 1980Q1 and 2015Q4. Second, we employed the autoregressive distributed lag (ARDL) technique to examine the effects of climate change and political instability on rice production. The results show that while temperature has an increasing pattern, rainfall exhibits no significant trend. The findings from the ARDL estimate reveal that rice production responds negatively to temperature changes but is less sensitive to changes in rainfall. In addition, political instability adversely affects rice production in Nigeria. We argue that Nigeria's slow growth in rice production can be traced back to the impact of climate change and political tension in rice farming areas. As a result, reducing the overall degree of conflict to ensure political stability is critical to boosting the country's self-sufficiency in rice production. We also recommend that farmers be supported and trained to adopt improved rice varieties less prone to extreme climate events while supporting them with irrigation facilities to facilitate rice production.

Humidification dehumidification water desalination system using two cycles of air flow (open and closed-air cycles).