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Abstract The residential sector accounts for most of energy-consumption in developing countries in the form of traditional energy. The use of commercial energy is nominal and confined mostly to urban areas where fuelwood is already monetized. A model, based on an end-use/process analysis approach, is developed on a spreadsheet, which is capable of simulating scenarios to address issues of increasing traditional energy-demand caused by population growth, sustainable supply capacity of the existing energy resources, potential for development of new and renewable energy resources, technology. This paper is divided into two parts: general energy issues and the modelling approach, and the application of this approach to Nepal in the context of fuelwood-supply sustainability.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

Xuanwei City (formerly known as Xuanwei County) locates in the northeastern of Yunnan Province and is rich in coal, iron, copper and other mines, especially the smoky (bituminous) coal. Unfortunately, the lung cancer morbidity and mortality rates in this region are among China's highest, with a clear upward trend from the mid-1970s to mid-2000s. In 2004-2005, the crude death rate of lung cancer was 91.3 per 100,000 in the whole Xuanwei City, while that for Laibin Town in this city was 241.14 per 100,000. The epidemiologic distribution (clustering patterns by population, time, and space) of lung cancer in Xuanwei has some special features, e.g., high incidence in rural areas, high incidence in females, and an early age peak in lung cancer deaths. The main factor that associates with a high rate of lung cancer incidence was found to be indoor air pollution caused by the indoor burning of smoky coal. To a certain extent, genetic defects are also associated with the high incidence of lung cancer in Xuanwei. Taken together, lung cancer in this smoky coal combustion region is a unique model for environmental factor-related human cancer, and the current studies indicate that abandoning the use of smoky coal is the key to diminish lung cancer morbidity and mortality.

In developing an algal treatment system, selenium (Se) removal efficiency by Chlorella vulgaris was evaluated under various conditions such as Se concentration, algal density, temperature and pH. A maximum removal efficiency plateau of ∼90% was observed between 1000-3000 μg Se/L while the tolerance of Se toxicity was found at 6000 μg Se/L. C. vulgaris of 0.75 g DW/L showed the highest removal efficiency (84%), and volatilization was dominant below 1.37 g DW/L. Se volatilization was two times higher at 25 °C than at 20 °C in the first 24 h. Moreover, the highest removal efficiency (77%) was obtained at pH 8.0, compared to 66.5% at pH 6.5 and 40% at pH 10.0. To prevent ecotoxicity, Se laden algae were further burned to ashes or filtered out by Anodonta woodiana. After burning, biomass Se was reduced by 99%, with organo-Se entirely converted into inorganic Se, lowering Se bioavailability. A. woodiana removed 54% of Se in 24 h, leading to Se bioaccumulation in soft tissues, which may serve as dietary Se supplements for human health. Our results suggest the cleanup of Se-contaminated water from either agricultural runoff or industrial discharge could be achieved using an algal treatment system with minimum potential ecotoxicity.

Promoting biodiesel industrialization is not only an important measure in addressing the energy crisis and global warming but is also a driver for industrial restructuring and rural development. To...

Volatile organic compounds (VOCs) can lead to environmental pollution and threaten human health due to their toxic and carcinogenic nature. The emission of VOCs increases dramatically with the accelerated industrialization and economic growth. Adsorption is identified as one of the most promising recovery technologies owing to its cost-effectiveness, flexible operation, and low energy consumption. In particular, adsorption-based technologies have a high potential to recycle both adsorbents and adsorbates, typically to capture valuable aromatic VOCs from industrial exhaust. Porous materials such as carbon-based materials, zeolite-based materials, and organic polymers and their composites have been extensively developed for VOCs adsorption focusing in adsorption capacity, hydrophobic property, thermal stability and regenerability. Among them, porous carbons as VOCs adsorbents have attracted increasingly attention, because they can be regulated by tuning the pore structure for VOCs accessibility during the adsorption process. Moreover, porous carbons can adsorb target VOCs by controlling the pore structure and surface functional groups. Significantly, the pore size distribution of porous carbons mostly controls the VOCs sorption process. Micropores provide the main adsorption sites, while mesopores enhance the diffusion of VOCs. In this review, the adsorption mechanism of VOCs onto porous carbons was generally concluded. Porous carbons can be designed as a specific structure for adsorption of aromatic VOCs by controlling the pore structure, hydrophobic sites, π-electronic structure, and surface functional groups. Since there are limited review literatures on porous carbons derived from renewable resources for VOCs adsorption, this paper will provide an overview on the synthesis of porous carbons from biomass and other organic wastes for VOCs adsorption or integrated oxidation processes (e.g., photocatalysis, non-thermal plasma catalysis, chemical catalysis) under ambient conditions with the objective of guiding ...

Developing a low-carbon economy is the only way for countries to achieve sustainable development. Carbon emission reduction policies and low-carbon technology (LCT) innovation play key roles in developing low-carbon economy. Under government reward and punishment regulations, based on the bilateral matching and evolutionary theories, this paper constructs an evolution model consisting of a manufacturer investing LCT and a supplier offering LCT to analyze multi-phase LCT investment strategies. Firstly, the profit optimization model of a green supply chain is constructed from the perspectives of centralized-matching (CM), decentralized-matching (DM), and mismatching (MM), and the spatial information internal evolution law of multi-phase LCT investment is described by the Markov chain. Then, a bilateral matching algorithm is proposed to solve the equilibrium solutions, and the evolution process of the three modes is analyzed by numerical simulation. Finally, based on the product green degree, we analyze the impact of subsidies and taxes on investment-production decisions. Analytical results show that the matching mechanism proposed in this paper can help supply chain firms to obtain stable matching and has a significant effect on the realization of "triple wins" of society, economy, and environment. The investment utility of CM is higher than that of DM and MM. Manufacturers are inclined to adopt LCT, and the investment level tends to be stable over time. Government reward and punishment regulations are helpful to motivate supply chain firms to invest in LCT, and the synergistic effect of subsidies and taxes is better than that of a single policy.

AbstractAutotrophs play an essential role in the cycling of carbon and nutrients, yet disease‐ecosystem relationships are often overlooked in these dynamics. Importantly, the availability of elemental nutrients like nitrogen and phosphorus impacts infectious disease in autotrophs, and disease can induce reciprocal effects on ecosystem nutrient dynamics. Relationships linking infectious disease with ecosystem nutrient dynamics are bidirectional, though the interdependence of these processes has received little attention. We introduce disease‐mediated nutrient dynamics (DND) as a framework to describe the multiple, concurrent pathways linking elemental cycles with infectious disease. We illustrate the impact of disease–ecosystem feedback loops on both disease and ecosystem nutrient dynamics using a simple mathematical model, combining approaches from classical ecological (logistic and Droop growth) and epidemiological (susceptible and infected compartments) theory. Our model incorporates the effects of nutrient availability on the growth rates of susceptible and infected autotroph hosts and tracks the return of nutrients to the environment following host death. While focused on autotroph hosts here, the DND framework is generalizable to higher trophic levels. Our results illustrate the surprisingly complex dynamics of host populations, infection patterns, and ecosystem nutrient cycling that can arise from even a relatively simple feedback between disease and nutrients. Feedback loops in disease‐mediated nutrient dynamics arise via effects of infection and nutrient supply on host stoichiometry and population size. Our model illustrates how host growth rate, defense, and tissue chemistry can impact the dynamics of disease–ecosystem relationships. We use the model to motivate a review of empirical examples from autotroph–pathogen systems in aquatic and terrestrial environments, demonstrating the key role of nutrient–disease and disease–nutrient relationships in real systems. By assessing existing evidence and uncovering data gaps and apparent mismatches between model predictions and the dynamics of empirical systems, we highlight priorities for future research intended to narrow the persistent disciplinary gap between disease and ecosystem ecology. Future empirical and theoretical work explicitly examining the dynamic linkages between disease and ecosystem ecology will inform fundamental understanding for each discipline and will better position the field of ecology to predict the dynamics of disease and elemental cycles in the context of global change.

ObjectivesThe poor safety profile of sunitinib capsules has encouraged the identification of targeted drug delivery systems against renal cell carcinoma. This study aimed to explore the effect of sunitinib‐loaded microbubbles along with ultrasound (US) treatment on proliferation and apoptosis of human GRC‐1 granulocyte renal carcinoma cells in vitro and in vivo (xenograft tumor growth in nude mice).MethodsLiposomes containing sunitinib were prepared by using the transmembrane ammonium sulfate gradient method and then absorbed into polymer microbubbles to generate sunitinib‐loaded microbubbles. Entrapment of sunitinib was verified by 25‐25‐[N‐[(7‐nitro‐2‐1,3‐benzoxadiazol‐4‐yl)methyl]amino]‐27‐norcholesterol staining. GRC‐1 cells were treated with microbubbles alone, liposomes alone, sunitinib alone, sunitinib‐loaded microbubbles without and with US, and no treatment (control). Cell survival and apoptosis were assessed at 12, 24, and 48 hours after treatment. Xenograft tumors were induced by implantation of GRC‐1 cells in nude mice. The animals with tumors were then randomly assigned to sunitinib alone, sunitinib‐loaded microbubbles − US, sunitinib‐loaded microbubbles + US, and no treatment (control; n = 10 per group). The tumor volumes were analyzed on the 7th, 15th, and 21st days.ResultsThe sunitinib entrapment efficiency in the liposomes was approximately 78%. The effective sunitinib concentration in each group was 0.1 μg/mL. The sunitinib‐loaded microbubble + US group showed a lower in vitro cell survival rate (P < .001) compared with the other groups. Greater in vivo inhibition of xenograft tumor growth was also observed in the sunitinib‐loaded microbubble + US group compared with the other groups.ConclusionsCombined sunitinib‐loaded microbubbles and US treatment significantly inhibits growth of renal carcinoma cells both in vitro and in vivo.