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Evaluating the effect of different operational strategies on the carbon footprint of wastewater treatment plants - case studies from northern Poland

机译:评价不同运营策略对废水处理厂碳足迹的影响 - 北波兰案例研究

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Nowadays, low greenhouse gas (GHG) emission is expected at wastewater treatment plants (WWTPs). However, emission quantification and evaluation still faces difficulties related to data availability and uncertainty. The objective of this study was to perform carbon footprint (CF) analysis for two municipal WWTPs located in northern Poland. Slupsk WWTP is a large biological nutrient removal (BNR) facility (250,000 PE) which benefits from on-site electricity production from biogas. The other studied plant is a medium-size BNR facility in Starogard (60,000 PE). In this WWTP, all the required electricity was provided from the grid. Both wastewater systems were composed of activated sludge, with differences in the nutrient removal efficiency and sludge treatment line. The CF calculations were based on empirical models considering various categories of input parameters, afterwards summing up the emissions expressed in CO2 equivalents (CO2e). After sensitivity analysis, significant contributors to GHG emissions were identified. The total specific CF of the Slupsk and the Starogard WWTP was 17.3 and 38.8 CO2e per population equivalent (PE), respectively. In both cases, sludge management, electricity consumption and direct emissions from wastewater treatment were found to significantly influence the CF. A substantial share of the total CF originated from indirect emissions, primarily caused by the energy consumption. This negative impact can be partially overcome by increasing the share of renewable energy sources. Reduction of over 30% in the total CF could be achieved while applying energy recovery from biogas by combined heat and power plants. Farmland and farmland after composting were found to be the most appropriate strategies for sludge management. They could create a CF credit (8% of the total CF) as a result of substituting a synthetic fertilizer. Reliable full-scale measurements of N2O emissions from wastewater treatment are recommended due to high uncertainty in CF
机译:如今,在废水处理厂(WWTPS)上预期低温室气体(GHG)排放。然而,发射量化和评估仍然面临与数据可用性和不确定性有关的困难。本研究的目的是对位于波兰北部的两个市政WWTP进行碳足迹(CF)分析。 SLUPSK WWTP是一种大型的生物营养去除(BNR)设施(250,000 PE),其来自沼气的现场电力生产。另一种研究的植物是Starogard的中型BNR设施(60,000 pe)。在此WWTP中,所有所需的电力都是从网格提供的。两种废水系统由活性污泥组成,营养消除效率和污泥处理线的差异。 CF计算基于考虑各种类别的输入参数的经验模型,之后总结CO2等同物(CO2E)中表达的排放量。敏感性分析后,确定了GHG排放的重要贡献者。 SLUPSK和Starogard WWTP的总特异性CF分别为每种群体当量(PE)的17.3和38.8CO2E。在两种情况下,发现废水处理的污泥管理,电力消耗和直接排放都会显着影响CF。总CF的大量份额来自间接排放,主要由能源消耗引起。通过增加可再生能源的份额,可以部分地克服这种负面影响。在通过组合的热量和发电厂施加来自沼气的能量回收率,可以实现总CF中超过30%的减少。发现堆肥后的农田和农田是污泥管理最适合的策略。他们可以因替代合成肥料而创建CF信用(总计8%)。由于CF的高不确定性,建议使用废水处理中N2O排放的可靠全尺寸测量。

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