بهبود تولید بیودیزل با کمک اولتراسونیک حاصل از ضایعات صنعت گوشت (چربی خوک) با استفاده از نانوکاتالیزور اکسید مس سبز: مقایسه سطح پاسخ و مدل سازی شبکه عصبی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 25
سوخت زیستی سبز ، تمیز و پایدار تنها گزینه به منظور کاهش کابرد سوخت های فسیلی ، پاسخگویی به تقاضای زیاد انرژی و کاهش آلودگی هوا است. تولید بیودیزل زمانی ارزان می شود که از یک پیش ماده ارزان ، کاتالیزور سازگار با محیط زیست و فرآیند مناسب استفاده کنیم. پیه خوک از صنعت گوشت حاوی اسید چرب بالا است و به عنوان یک پیش ماده موثر برای تهیه بیودیزل کاربرد دارد. این مطالعه بیودیزل را از روغن پیه خوک از طریق فرآیند استری سازی دو مرحله ای با کمک اولتراسونیک و کاتالیزور تولید می کند. عصاره Cinnamomum tamala (C. tamala) برای تهیه نانوذرات CuO مورد استفاده قرار گرفت و با استفاده از طیف مادون قرمز ، پراش اشعه ایکس ، توزیع اندازه ذرات ، میکروسکوپ الکترونی روبشی و انتقال مشخص شد. تولید بیودیزل با استفاده از طرح Box-Behnken (BBD) و شبکه عصبی مصنوعی (ANN) ، در محدوده متغیرهای زمان اولتراسونیک (us )(20-40 min)، بارگیری نانوکاتالیزور 1-3) CuO درصد وزنی( ، و متانول به قبل از نسبت مولی PTO (10:1e30:1) مدلسازی شد. آنالیز آماری ثابت کرد که مدل سازی شبکه عصبی بهتر از BBD است. عملکرد بهینه 97.82٪ با استفاده از الگوریتم ژنتیک (GA) در زمان US: 35.36 دقیقه ، بار کاتالیزور CuO: 2.07 درصد وزنی و نسبت مولی: 29.87: 1 به دست آمد. مقایسه با مطالعات قبلی ثابت کرد که اولتراسونیک به میزان قابل توجهی موجب کاهش بار نانوکاتالیزور CuO می شود ، و نسبت مولی را افزایش می دهد و این فرایند را بهبود می بخشد.
کلمات کلیدی: چربی خوک | التراسونیک | اکسید مس | سنتز سبز | شبکه عصبی | سطح پاسخ
|مقاله ترجمه شده|
Performance assessment of coupled green-grey-blue systems for Sponge City construction
ارزیابی عملکرد سیستم های سبز و خاکستری-آبی همراه برای ساخت و ساز شهر اسفنجی-2020
In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source, grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal. However, the current approaches for assessing the performance of Sponge City construction are confined to green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river system models are coupled to provide quantitative simulation evaluations of a number of indicators of landbased and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement. This framework can be applied to Sponge City projects to achieve the enhancement of urban water management.
Keywords: Low impact development | Sponge City | Green-grey-blue system | Performance assessment | TOPSIS
Goal heterogeneity at start-up_ are greener start-ups more innovative?
ناهمگنی هدف در شروع کار: آیا استارت آپ های سبزتر نوآورتر هستند؟-2020
Start-ups differ in the extent to which they introduce innovations to markets and, hence, in their potential contribution to society. Understanding the heterogeneous character of start-ups is key to explaining the varia- bility in innovation. In this study, we explore whether start-ups that place more emphasis on environmental value creation versus economic value creation (‘greener start-ups’) are more innovative. We also examine how environmental regulations at the country level affect this relationship. We theorize that the fundamental dif- ference between economic value creation (private wealth generation, i.e., self-regarding interest) and en- vironmental value creation (environmental gains for society, i.e., other-regarding interest) influences en- trepreneurial opportunity identification and exploitation. When considering the regulatory context, we draw on the innovation inducement effect of environmental regulations and expect these regulations to be most effective for entrepreneurs with a strong emphasis on economic value creation. Performing multi-level ordered logit regressions with 2,945 start-up entrepreneurs in 31 countries (Global Entrepreneurship Monitor data), we find that ‘greener start-ups’ are more likely to engage in product and process innovations. We find some evidence of a positive moderation effect for environmental regulations. We advance research on innovative entrepreneurship by theorizing and finding evidence that other-regarding goals are relevant in explaining start-up innovativeness.
Keywords: Goal heterogeneity | Start-ups | Green entrepreneurship | Environmental regulations | Innovation | Global Entrepreneurship | Monitor
Prediction and management of solar energy to power electrochemical processes for the treatment of wastewater effluents
پیش بینی و مدیریت انرژی خورشیدی به قدرت فرآیندهای الکتروشیمیایی برای تصفیه پساب فاضلاب-2020
A highly versatile software tool able to predict and manage the solar power coming from photovoltaic panels and to assess the environmental remediation of wastewater effluents has been developed. The prediction software tool is made up of four modules. The first one predicts the solar radiation by a phenomenological model. Secondly, an energy optimization algorithm manages the solar power towards the third and fourth modules, an environmental remediation treatment (electrooxidation) and an energy storage system (redox flow battery), respectively. The software tool is aimed to the best solar power management to obtain the highest remediation treatment. Results shows a daily solar radiation prediction with a high accuracy, attaining correlation coefficients of 0.89. Furthermore, the prediction of the removal of an organochlorinated compound from a wastewater effluent at different time of the year was studied. Different percentages of the total solar power are sent directly to the electrooxidation reactor and to the redox flow battery. At non-solar production hours, the electrooxidation reactor is powered by the redox flow battery in order to exploit the total solar power produced. The results show that, the higher the solar radiation, the higher the power percentage that must be directly sent to the electrooxidation treatment in order to attain the best energy management and the higher remediation. Thus, an 82.5% of the total solar power must be sent to the electrooxidation treatment in summer days in contrast to the 25% that have to be powered in winter days to attain the highest removal of pollutant. Consequently, it is important to evaluate the connection between devices to get the best green energy management and the lower energy losses.
Keywords: Energy management | Solar power | Green sources | Electrolysis | Redox flow batteries | Forecasting
A selective disassembly multi-objective optimization approach for adaptive reuse of building components
روش بهینه سازی چند منظوره جداسازی انتخابی برای استفاده مجدد از سازه از اجزای ساختمان-2020
Adaptive reuse of buildings plays a key role in the transition from a resource-based economy and towards a Circular Economy (CE) in the construction industry. Adaptive reuse has the potential to maximize the residual utility and value of existing assets through green design methods such as selective disassembly planning. Studies in the field of selective disassembly are scarce and there is no evidence of established methodologies for the optimization of the environmental and financial benefits. A multi-objective analysis is key to obtaining several effective selective disassembly plans for the adaptive reuse of an existing asset through the combination of different deconstruction methods. The analysis is carried out in terms of the physical, environmental, and economic constraints of the deconstruction methods per building component. The Sequential Disassembly Planning for Buildings (SDPB) method is used in order to generate the optimized disassembly plans for retrieving target components. At the end, a weighted multi-objective optimization analysis is incorporated to generate the set of noninferior solutions that minimizes environmental impacts and building cost. The results show that different complete disassembly plans exist for all the possible combinations. The possible combinations are driven by the deconstruction methods per component, as well as the dismantling interdependence. The method described in this study can be used to improve the project outcomes according to specific goals and constraints (e.g. environmental, economic, technical). The results of this study improve the decision-making process for adaptive reuse building projects by adding comprehensive quantitative analysis towards sustainable management and conservation of resources.
Keywords: Circular economy | Adaptive reuse | Multi-objective optimization | Selective disassembly planning | Green design | Building components reuse
The harmonizing effect of Smart Snacks on the association between state snack laws and high school students fruit and vegetable consumption, United States—2005–2017
اثر هماهنگ کننده میان وعده های هوشمند در ارتباط بین قوانین میان وعده ایالتی با مصرف میوه و سبزیجات دانش آموزان دبیرستانی ، ایالات متحده — 2005-2017-2020
Despite national guidelines recommending daily fruit and vegetable (FV) consumption, intake of FV among adolescents is low. Over the past 10–15 years, state and federal laws have reduced the availability of junk foods in schools. This study examined the association between state snack laws and high school (HS) student FV consumption. The overall sample included 99,785 HS students (outcome samples ranged from 96,209-97,328) included in the Youth Risk Behavior Survey (YRBS). National Cancer Institute Classification of Laws Associated with School Students data for 2004–2016 were lagged on to 2005–2017 YRBS data. Separate analyses examined the state law-youth FV consumption relationship pre- and post-federal Smart Snacks standards (effective school year 2014–2015). Analyses were conducted between 2018 and 2020. Overall, state laws were associated with any vegetable, salad, and other vegetable consumption. The relationship between state laws and vegetable consumption primarily occurred pre-Smart Snacks. Pre-Smart Snacks, state laws were associated with higher odds of youth consumption of any vegetable, salad, carrots, and other vegetables (all compared to students in states without snack laws). The only association post-Smart Snacks was between strong state laws and salads. This study illustrates the important role that standards restricting the availability of junk foods in schools can have on increasing student vegetable consumption. Given current efforts to roll-back federal school meal standards, findings from this study illustrate how federal standards harmonized the patchwork of state laws that existed prior to Smart Snacks and the important role that consistent national standards can play in supporting student consumption of vegetables.
Keywords: Legal epidemiology | Nutrition | Schools | Fruit | Vegetables
Green house based on IoT and AI for societal benefit
خانه سبز مبتنی بر اینترنت اشیا و هوش مصنوعی برای منافع اجتماعی-2020
The paper “Greenhouse based on IoT and AI for societal benefit” using a native microcontroller (LPC2138), environment monitoring sensors, communication module (ESP8266), along with a server design (which takes into account the real time weather forecast, and data analysis on the data gathered by sensors for irrigation decision) is focused on achieving automation, IoT deployment level -3, wrong weather forecast counter-action in real time with automation and intelligent control for water utilisation and optimization which will result in a uniform yield. The system described optimizes water utilisation on the basis of plant’s water need instead of cultivator’s assumptions by working on static data such as plant and soil type and environment dynamic data gathered from sensors. The data has been tested for algorithms such as Naïve Bayes, C4.5 and SMO (svm). A web page has been created which can be used for monitoring the data of green house
Keywords: server | IoT | C4.5 | weather forecast | automation | irrigation | plant need
Environmental justice in the context of urban green space availability, accessibility, and attractiveness in postsocialist cities
عدالت زیست محیطی در چارچوب در دسترس بودن ، دسترسی و جذابیت فضای سبز شهری در شهرهای پساجتماعی-2020
This article aims to position post socialist cities in Central and Eastern Europe in the broader debate on urban environmental justice. The article crosscuts through all three dimensions of justice (distributive/distributional, procedural/participatory, and interactional/recognition) in the context of urban green and blue space provision. Environmental justice is still an emerging topic in post socialist cities, constrained by market-orientation and neoliberal trends within society, privatization, and the primacy of private interests. The respective situation in post socialist cities provides insights into the international debate on environmental justice, by highlighting some extremes related to neoliberal and populist governments and very rapid processes that lack long-term democratic consensus within societies. The findings of this study are discussed in the context of a post socialist legacy, which includes broad tolerance for inequalities, a lack of solidarity in society, a lack of responsibility for the public interest, and extreme individualization and disregard for social interests. This has gradually led to the corporatization of local authorities and various business–government coalitions. This setting is more likely to favor business models related to the use and management of urban green and blue spaces than the environmental justice discourse.
Keywords: Central and Eastern Europe | Green and blue infrastructure | Transition economies | Environmental planning | Environmental governance | Neoliberalism
Energy management for cost minimization in green heterogeneous networks
مدیریت انرژی برای به حداقل رساندن هزینه در شبکه های ناهمگن سبز-2020
With the fast development of cyber–physical systems, mobile applications and traffic demands have been significantly increasing in this decade. Likewise, the concerns about the electricity consumption impacts on environments and the energy costs of wireless networks have also been growing greatly. In this paper, we study the problem of energy cost minimization in a heterogeneous networks with hybrid energy supplies, where the network architecture consists of radio access part and wireless backhaul links. Owing to the diversities of mobile traffic and renewable energy, the energy cost minimization problem involves both temporal and spatial dimensional optimization. We decompose the whole problem into four subproblems and correspondingly our proposed solution consists of four parts: At first, we obtain estimated average energy consumption profiles for all base stations based on the temporal traffic statistics; Second, we formulate the green energy allocation optimization in the temporal domain to minimize energy cost for each BS. Third, given the allocated green energy and practical user distribution in each slot, we propose a centralized and a distributed user association algorithm to minimize total energy cost in the spatial dimension. Fourth, based on the actual user association scheme, we readjust the green energy allocation for each BS to further improve green energy utilization. Simulation results show that our proposed solution can significantly reduce the total energy cost, compared with the recent peer algorithms.
Keywords: Energy cost minimization | Green energy | Heterogeneous networks | Cyber–physical systems
Renewable energy diversification: Considerations for farm business resilience
متنوع سازی انرژی تجدیدپذیر: ملاحظاتی برای انعطاف پذیری مشاغل مزرعه-2020
With a varied landscape, Wales is resource rich in terms of wind and water and a suitable location to develop many different forms of sustainable energy. Whilst farm businesses face increasing challenges in terms of economic stability and traditional production methods, this paper considers the role of renewable energy production as a form of diversification. The study adopts mixed methods as a means of undertaking an in-depth investigation into the role of renewable energy generation in supporting agribusinesses in Wales. Initially a questionnaire obtained 118 responses from farmers in Wales. Subsequently, 15 follow-up semi-structured interviews with farmers were conducted to further investigate the issues from the initial questionnaire. The theoretical contribution of this paper is a segmentation of farmer businesses which allows for distinctions to be made of different attitudes to off-farm income and the adoption of renewable energy sources. Five farm types were identified, varying in relation to farm characteristics, attitudes to diversification, access to renewable energy and resource allocation. These farm types highlight the need for specific policies towards facilitating the increase in renewable energy along with sustaining farming incomes. Furthermore the research provides valuable information to the farming industry on opportunities in renewable energy production, particularly for farmers and farm businesses who are considering diversification strategies.
Keywords: Green economy | Farm diversification | Agribusiness | Entrepreneurship | Renewable energy