Potential energy production from organic waste and its environmental and economic impacts at a tertiary institution in Palestine

Municipal solid waste (MSW) is one of the most well-known biomass resources that can be utilized to produce renewable energy. Numerous countries are plagued by the proliferation of waste, particularly organic waste that can be utilized for energy recovery. Palestine suffers from inefficient solid waste management, and only recently have a few projects focused on bioenergy production been implemented. Throughout the years, the city of Tulkarm experiences power outages which cause a challenge to the Palestine Technical University-Kadoorie campus in Tulkarm. Thus, the possibility of energy recovery from the organic portion in Palestine Technical University-Kadoorie was evaluated. The analysis of an economic impact included discussions of a number of economic aspects, including Levelized cost of energy, internal rate of return, present worth, annual worth, and payback period. On the other hand, a carbon dioxide savings analysis and gas emission were evaluated. The outcomes of the energy optimization demonstrated that the suggested system could supply the institution with an average of roughly 7 MWh of electrical energy. According to the economic study, this project offers 0.25 million dollars in present value, 0.144 million dollars in annual value, a 13 percent internal rate of return, a payback period of 6 years, and a levelized cost of energy of 0.11 dollars for each kWh generated. Additionally, the environmental assessment revealed that this system might reduce CO₂ emissions by around 8,343,778 tons. For effective waste management, energy recovery, and emission reduction, it is advised to implement anaerobic digestion technology.     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

Boosting freshwater fish conservation with high-resolution distribution mapping across a large territory

The lack of high-resolution distribution maps for freshwater species across large extents fundamentally challenges biodiversity conservation worldwide. We devised a simple framework to delineate the distributions of freshwater fishes in a high-resolution drainage map based on stacked species distribution models and expert information. We applied this framework to the entire Chinese freshwater fish fauna (>1600 species) to examine high-resolution biodiversity patterns and reveal potential conflicts between freshwater biodiversity and anthropogenic disturbances. The correlations between spatial patterns of biodiversity facets (species richness, endemicity, and phylogenetic diversity) were all significant (r = 0.43–0.98, p < 0.001). Areas with high values of different biodiversity facets overlapped with anthropogenic disturbances. Existing protected areas (PAs), covering 22% of China's territory, protected 25–29% of fish habitats, 16–23% of species, and 30–31% of priority conservation areas. Moreover, 6–21% of the species were completely unprotected. These results suggest the need for extending the network of PAs to ensure the conservation of China's freshwater fishes and the goods and services they provide. Specifically, middle to low reaches of large rivers and their associated lakes from northeast to southwest China hosted the most diverse species assemblages and thus should be the target of future expansions of the network of PAs. More generally, our framework, which can be used to draw high-resolution freshwater biodiversity maps combining species occurrence data and expert knowledge on species distribution, provides an efficient way to design PAs regardless of the ecosystem, taxonomic group, or region considered.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Why bees are critical for achieving sustainable development

Reductions in global bee populations are threatening the pollination benefits to both the planet and people. Whilst the contribution of bee pollination in promoting sustainable development goals through food security and biodiversity is widely acknowledged, a range of other benefits provided by bees has yet to be fully recognised. We explore the contributions of bees towards achieving the United Nation’s Sustainable Development Goals (SDGs). Our insights suggest that bees potentially contribute towards 15 of the 17 SDGs and a minimum of 30 SDG targets. We identify common themes in which bees play an essential role, and suggest that improved understanding of bee contributions to sustainable development is crucial for ensuring viable bee systems.     

Physico-chemical characterization of Residual Household Waste for energy recovery in insular territories: Case study of Reunion Island

Waste-to-energy is a promising approach to face the current challenge of waste overproduction in Reunion Island, a French territory. In this particular context of an isolated and tropical territory, it is essential to study the properties of potential feedstocks to choose the most appropriate conversion process. This article reports on the composition of Residual Household Waste from Reunion Island and its physico-chemical parameters. Twelve representative samples of Residual Household Waste were subjected to thermal and elemental analysis. The results showed that their composition had a significant influence on the physico-chemical properties, including calorific value. Residual Household Waste from the selective sorting (rich in wood, plastic, and sanitary textiles) as well as dry mixed RHW are the most interesting for energy recovery. Due to their high volatile matter and high carbon content, and their low moisture content, these types of waste have a high calorific value exceeding 18 MJ/kg. Furthermore, the RHW sample comply with the environmental and health criteria applied by French regulations concerning halogen and heavy metal. Thus, it seems that Residual Household Waste can be an alternative to conventional fuels used in incineration or pyro-gasification processes. However, the study also points the need for a pre-treatment process for these wastes. Indeed, it is necessary to sort them correctly in order to avoid the risks of pollution and important maintenance. And more importantly, drying beforehand is unavoidable to improve combustibility and obtain optimal energy conversion.     

Critical pedagogy of place to enhance ecological engagement activities

Scientists in higher education institutions around the globe recognize the importance of engaging with public stakeholders to share their enthusiasm, explain their science, and encourage primary and secondary students to enter the sciences. However, without direct consideration of students’ and teachers’ perspectives and interests, scientists may design activities around their own goals, limiting the impact on school stakeholders (i.e., students, teachers, paraprofessional staff, students’ parents, and other caregivers). We drew from natural and social science research to describe how expanding the conception of place beyond the biophysical can help engage school stakeholders in meaningful ways. We describe the multidimensional PLACE framework that we developed to integrate perspectives, knowledge, and values of all stakeholders in engagement programming. The framework is organized around topics that stakeholders should discuss early on to ensure successful partnerships. We recommend that scientists identify and use pedagogy that is inclusive; language framed around dialogic communication methods; aims and motivations centered on engagement; cultural funds of knowledge of place (i.e., disciplinary, personal, or experiential knowledge); and evaluation of engagement based on meaningful metrics. Two case studies are presented to illustrate how the PLACE framework components, when addressed, can lead to robust, successful partnerships between scientists and schools.     

Effect of ambient polycyclic aromatic hydrocarbons and nicotine on the structure of Aβ42 protein

● B[a]P, nicotine and phenanthrene molecules altered the secondary structure of Aβ₄₂. ● β-content of the peptide was significantly enhanced in the presence of the PAHs. ● Nicotine made stable cluster with Aβ₄₂ peptide via hydrogen bonds. ● Phenanthrene due to its small size, interfered with the Aβ₄₂ monomer more strongly. Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons (PAHs) with the progression of neurodegenerative disorders, either by using statistical data from various cities, or via tracking biomarkers during in-vivo experiments. Among different neurodegenerative disorders, PAHs are known to cause increased risk for Alzheimer’s disease, related to the development of amyloid beta (Aβ) peptide oligomers. However, the complex molecular interactions between peptide monomers and organic pollutants remains obscured. In this work, we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ₄₂ peptide monomer in the presence of benzo[a]pyrene, nicotine, and phenanthrene. Interestingly the results revealed strong hydrophobic, and hydrogen-bond based interactions between Aβ peptides and these environmental pollutants that resulted in the formation of stable intermolecular clusters. The strong interactions affected the secondary structure of the Aβ₄₂ peptide in the presence of the organic pollutants, with almost 50 % decrease in the α-helix and 2 %–10 % increase in the β-sheets of the peptide. Overall, the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβ peptide oligomers, and consequent progression of Alzheimer’s disease.     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

Systematic review of conservation interventions to promote voluntary behavior change

Understanding human behavior is vital to developing interventions that effectively lead to proenvironmental behavior change, whether the focus is at the individual or societal level. However, interventions in many fields have historically lacked robust forms of evaluation, which makes it hard to be confident that these conservation interventions have successfully helped protect the environment. We conducted a systematic review to assess how effective nonpecuniary and nonregulatory interventions have been in changing environmental behavior. We applied the Office of Health Assessment and Translation systematic review methodology. We started with more than 300,000 papers and reports returned by our search terms and after critical appraisal of quality identified 128 individual studies that merited inclusion in the review. We classified interventions by thematic area, type of intervention, the number of times audiences were exposed to interventions, and the length of time interventions ran. Most studies reported a positive effect (n = 96). The next most common outcome was no effect (n = 28). Few studies reported negative (n = 1) or mixed (n = 3) effects. Education, prompts, and feedback interventions resulted in positive behavior change. Combining multiple interventions was the most effective. Neither exposure duration nor frequency affected the likelihood of desired behavioral change. Comparatively few studies tested the effects of voluntary interventions on non-Western populations (n = 17) or measured actual ecological outcome behavior (n = 1). Similarly, few studies examined conservation devices (e.g., energy-efficient stoves) (n = 9) and demonstrations (e.g., modeling the desired behavior) (n = 5). There is a clear need to both improve the quality of the impact evaluation conducted and the reporting standards for intervention results.