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Utilization of Banana (Musa sapientum) Peel for Removal of Pb2+ from Aqueous Solution 利用香蕉皮去除水中Pb2+
Pub Date : 2021-07-31 DOI: 10.47352/jmans.v1i2.89
Afrida Nurain, P. Sarker, Md. Shiblur Rahaman, Md. Mostafizur Rahman, Md Elias Uddin
Biosorption is a convenient process for heavy metal remediation. In this study, banana peel was experimented to eliminate lead (Pb2+) from an aqueous solution following batch experiments. The functional groups of banana peel were identified by Fourier-transform infrared spectroscopy (FTIR). The adsorption mechanism was studied by the Langmuir and Freundlich adsorption isotherm model and determined the separation factor from the Langmuir adsorption isotherm. The adsorption of Pb2+ on dried banana peel had been studied at different adsorbent doses, pH, initial concentration of Pb, contact time, temperature, and agitation speed. After adsorption, Pb2+ was measured using atomic absorption spectroscopy (AAS). Maximum adsorption had taken place at pH 5 for adsorbent dose 45 g L-1. The optimum contact time and agitation speed was 30 minutes and 150 rpm, respectively for the initial Pb concentration of 100 ppm at 25°C. Both, Langmuir and Freundlich adsorption isotherm models shows the best fitting (r2 = 0.9978 and 0.9595) for Pb2+ adsorption. The maximum Pb2+ adsorption capacity was 2.1 mg g-1. The findings indicate that the banana peel waste could be a potential adsorbent for heavy metal removal. Moreover, the waste management problem could be solved in an eco-friendly manner by utilizing it for the eradication of Pb2+ from wastewater.
生物吸附法是一种方便的重金属修复方法。在本研究中,通过批量实验,研究了香蕉皮对水溶液中铅(Pb2+)的去除作用。利用傅里叶变换红外光谱(FTIR)对香蕉皮中的官能团进行了鉴定。采用Langmuir吸附等温线模型和Freundlich吸附等温线模型研究了吸附机理,并从Langmuir吸附等温线中确定了分离因子。研究了不同吸附剂用量、pH、Pb初始浓度、接触时间、温度和搅拌速度对干香蕉皮上Pb2+的吸附作用。吸附后,用原子吸收光谱(AAS)测定Pb2+。当吸附剂剂量为45 g L-1时,pH为5时吸附效果最佳。在25℃条件下,当初始Pb浓度为100 ppm时,最佳接触时间为30 min,搅拌速度为150 rpm。Langmuir和Freundlich吸附等温线模型对Pb2+的吸附均拟合最佳(r2 = 0.9978和0.9595)。Pb2+的最大吸附量为2.1 mg g-1。研究结果表明,香蕉皮废弃物可能是一种潜在的重金属去除吸附剂。此外,利用它去除废水中的Pb2+,可以以生态友好的方式解决废物管理问题。
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引用次数: 3
Role of Agriculture sector in the era of globalization. 农业部门在全球化时代的作用。
Pub Date : 2021-05-23 DOI: 10.2139/ssrn.3851428
Dr. Iqbal Shaukat
Agriculture is the important part of world economy.Agriculture sector is the part and percell of economy.
农业是世界经济的重要组成部分。农业是经济的组成部分和支柱。
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引用次数: 0
Carbonwashing: A New Type of Carbon Data-Related ESG Greenwashing 碳洗:一种新型的与碳数据相关的ESG绿洗
Pub Date : 2021-04-25 DOI: 10.2139/ssrn.3901278
S. In, K. Schumacher
Despite the increased attention and capital incentives around corporate sustainability, the development of sustainability reporting standards and monitoring systems has been progressing at a slow pace. As a result, companies have misaligned incentives to deliberately or selectively communicate information not matched with actual environmental impacts or make largely unsubstantiated promises around future ambitions. These incidents are broadly called “greenwashing,” but there is no clear consensus on its definition and taxonomy. We pay particular attention to the threat of greenwashing concerning carbon emission reductions by coining a new term, “carbonwashing.” Since carbon mitigation is the universal goal, the corporate carbon performance data supply chain is relatively more advanced than that of the entire sustainability data landscape. Nonetheless, the threat of carbonwashing persists, even far more severe than general greenwashing due to the financial values attached to corporate carbon performance. This paper contextualizes sustainable finance-related carbonwashing via an outline of the communication as well as the measurement, reporting, and verification (MRV) of carbon emission mitigation performance. Moreover, it proposes several actionable policy recommendations on how industry stakeholders and government regulators can reduce carbonwashing risks.
尽管对公司可持续性的关注和资本激励日益增加,但可持续性报告标准和监测系统的发展进展缓慢。因此,企业的动机不一致,故意或有选择地传达与实际环境影响不相符的信息,或者对未来的雄心做出基本上没有根据的承诺。这些事件被广泛地称为“洗绿”,但对其定义和分类没有明确的共识。我们特别关注与减少碳排放有关的“洗绿”威胁,并创造了一个新名词“carbonwashing”。由于碳减排是普遍目标,企业碳绩效数据供应链相对于整个可持续性数据格局更为先进。尽管如此,“洗碳”的威胁依然存在,甚至比一般的“洗绿”还要严重得多,因为企业的碳排放表现带来了财务价值。本文通过概述碳排放减缓绩效的沟通以及测量、报告和验证(MRV),将可持续金融相关的碳清洗纳入背景。此外,它还就行业利益相关者和政府监管机构如何降低碳清洗风险提出了若干可行的政策建议。
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引用次数: 6
Nigeria’s Petroleum Industry Bill: A Missed Opportunity to Prepare for the Zero-Carbon Future 尼日利亚石油工业法案:错失了为零碳未来做准备的机会
Pub Date : 2021-02-10 DOI: 10.7916/D8-DBS8-P927
S. Kennedy, Martin Dietrich Brauch, P. Toledano, Tehtena Mebratu-Tsegaye
With Nigeria’s National Assembly debating the proposed Petroleum Industry Bill (PIB) in the first quarter of 2021 — after nearly two decades of attempted reform of the country’s petroleum sector — Nigeria has a unique opportunity to rethink the role of the oil and gas industry in Nigeria’s economy and build out the country’s energy sector and economic capacity for the long term.

This piece provides a brief analysis of Nigeria’s PIB, highlighting the PIB’s laudable steps while identifying gaps and outlining recommendations for Nigeria to prepare for and seize the opportunity of the energy transition.
经过近20年的石油行业改革尝试,尼日利亚国民议会将在2021年第一季度辩论拟议的石油工业法案(PIB),这是一个独特的机会,可以重新思考石油和天然气行业在尼日利亚经济中的作用,并建立该国的能源部门和长期经济能力。本文简要分析了尼日利亚的PIB,强调了PIB值得称赞的步骤,同时确定了差距,并概述了尼日利亚为能源转型做好准备和抓住机遇的建议。
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引用次数: 0
Iot and Neural Network Based Multi Region and Simultaneous Leakage Detection in Pipelines 基于物联网和神经网络的管道多区域同步泄漏检测
Pub Date : 2019-11-30 DOI: 10.34218/ijaret.10.6.2019.008
Pradyot Aramane, Akshay J Bhattad, M. M., Nishant Aithal, A. P., Prof.Prapulla S.B, Dr.Shoba .G
The increasing demand for water arising from global population growth and urbanization in recent years is stressing the water supply to its limits. By 2025, 1.8 billion people will experience absolute water scarcity, and 2/3 of the world will be living under water-stressed conditions [1-2]. Neural networks have proved to be an apt approach for water leakage detection as they have the best and most extensive reach on the problem owing to their computational nature. They do not any have basic flaws unlike alternate methods like leakage detection using acoustic sensors which cannot differentiate between spikes in flow and leakage. They are a flexible and efficient approach to detection of leakages in water distribution networks. According to an inquiry made by the International Water Supply Association (IWSA), the amount of lost or “unaccounted for water” (UFW) is typically in the range of 20–30% of production[3]. In this project, a neural network model is proposed for detection and location of leakages in the pipes based on pressure values from sensors deployed along the pipeline. The network is initially trained using these pressure values and can then be used to detect abnormalities in the readings which can be due to leakages. The open source tool used to develop this model is Neuroph Studio. Neuroph is a neural network framework written in Java. It can be used to create and train neural networks in Java programs. Neuroph provides Java class library as well as GUI tool to quickly create Java neural network components. The model consisting of a multilayer perceptron neural network identifies simultaneous leakages in multiple regions successfully. When the size of the input dataset increases from a set of 10 values to a set of 1500 values, the mean square error of outputs increases by 128 times. But when this change is from a set of 1500 values to a set of 12000 values, the mean square error increases by 1.6 times. Thus, the total mean square error decreases drastically with the increase in input size, leading to the conclusion that the model is stable and scalable.
近年来,全球人口增长和城市化对水的需求不断增加,使供水压力达到极限。到2025年,18亿人将经历绝对缺水,世界2/3的人口将生活在缺水条件下[1-2]。由于神经网络的计算特性,它在水泄漏检测方面具有最好和最广泛的应用范围,已被证明是一种合适的方法。与使用声学传感器的泄漏检测等替代方法不同,它们没有任何基本缺陷,而声学传感器无法区分流量峰值和泄漏。它们是一种灵活而有效的供水管网泄漏检测方法。根据国际供水协会(IWSA)的一项调查,损失或“未计算的水”(UFW)的数量通常在产量的20-30%之间[3]。在这个项目中,提出了一个神经网络模型,用于根据沿管道部署的传感器的压力值来检测和定位管道中的泄漏。该网络最初使用这些压力值进行训练,然后可用于检测由于泄漏引起的读数异常。用于开发该模型的开源工具是Neuroph Studio。Neuroph是一个用Java编写的神经网络框架。它可以用来在Java程序中创建和训练神经网络。Neuroph提供Java类库和GUI工具来快速创建Java神经网络组件。该模型由多层感知器神经网络组成,成功地识别了多个区域的同时泄漏。当输入数据集的大小从10个值增加到1500个值时,输出的均方误差增加了128倍。但是当这个变化从1500个值变成12000个值时,均方误差增加了1.6倍。因此,总均方误差随着输入大小的增加而急剧减小,从而得出模型稳定且可扩展的结论。
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引用次数: 3
Increasing Pace of Urbanization and Implications for Food Security and Sustainable Agriculture 城市化步伐加快及其对粮食安全和可持续农业的影响
Pub Date : 2019-11-18 DOI: 10.2139/ssrn.3488892
R. Jha
The increasing pace of urbanization in emerging market economies poses a challenge for agricultural production in these countries. On the one hand, agricultural productivity is not keeping pace with the speed of urbanization and growth in food demand and, on the other, the demand for food is highly skewed making for an inordinate amount of food going for non-human consumption and wastage. This paper reviews the trends in urbanization in as well as in in agricultural productivity and comes to the conclusion that some parts of the world may well be facing a neo Malthusian future. Policy measures designed to address this situation are considered. Implications for international trade and domestic agricultural policies are also considered.
新兴市场经济体日益加快的城市化步伐对这些国家的农业生产构成了挑战。一方面,农业生产力跟不上城市化的速度和粮食需求的增长,另一方面,粮食需求高度倾斜,导致大量粮食被用于非人类消费和浪费。本文回顾了城市化和农业生产力的趋势,并得出结论,世界上一些地区很可能面临新马尔萨斯的未来。审议了旨在解决这一情况的政策措施。还考虑了对国际贸易和国内农业政策的影响。
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引用次数: 0
A Stochastic Simulation Approach to Estimating the Economic Impacts of Climate Change in Bangladesh 估算孟加拉国气候变化经济影响的随机模拟方法
Pub Date : 2012-08-01 DOI: 10.1111/j.1467-9361.2012.00671.x
J. Thurlow, P. Dorosh, Winston Yu
Climate change assessments often inadequately address uncertainty when estimating damages. Using a dynamic economy-wide model of Bangladesh, we estimate and decompose damages from historical climate variability and future anthropogenic climate change. Our stochastic simulation approach avoids biases caused by non-linear damage functions and fixed occurrences of extreme events in historical data. Using ten climate projections, we find that future anthropogenic climate change damages until 2050 are, on average, one-fifth of those from historical climate variability. Climate change also alters the temporal distribution of damages and slows Bangladeshâ..s long- run shift (adaptation) into dry (winter) season rice production.
气候变化评估在评估损害时往往不能充分处理不确定性。利用孟加拉国的动态经济模型,我们估计和分解了历史气候变率和未来人为气候变化造成的损害。我们的随机模拟方法避免了非线性损伤函数造成的偏差和历史数据中极端事件的固定发生。通过对10个气候预测,我们发现,到2050年,未来人为气候变化造成的损失平均是历史气候变率造成的损失的五分之一。气候变化也改变了损害的时间分布,减缓了孟加拉国的发展速度。长期转变(适应)为干(冬)季水稻生产。
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引用次数: 36
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Agricultural Sustainability & Security eJournal
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