Maktabifard M, Zaborowska E, Makinia J
Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Narutowicza Street 11/12, 80-233 Gdansk, Poland E-mail:
Water Sci Technol. 2019 Jun;79(11):2211-2220. doi: 10.2166/wst.2019.224.
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 CO equivalents (CO). 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 CO 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 NO emissions from wastewater treatment are recommended due to high uncertainty in CF estimation based on fixed emission factors (EFs). While applying the lowest and the highest NO EFs reported in the literature, the total CF would change even by 2-3 times.
如今，污水处理厂（WWTPs）期望实现低温室气体（GHG）排放。然而，排放量化与评估仍面临与数据可用性和不确定性相关的难题。本研究的目的是对位于波兰北部的两座城市污水处理厂进行碳足迹（CF）分析。斯武普斯克污水处理厂是一座大型生物营养物去除（BNR）设施（250,000人口当量），受益于现场利用沼气发电。另一座被研究的工厂是位于斯塔罗加尔的中型BNR设施（60,000人口当量）。在这座污水处理厂中，所有所需电力均由电网提供。两个废水处理系统均由活性污泥组成，在营养物去除效率和污泥处理流程方面存在差异。CF计算基于考虑各类输入参数的经验模型，随后汇总以二氧化碳当量（CO）表示的排放量。经过敏感性分析，确定了温室气体排放的主要贡献因素。斯武普斯克和斯塔罗加尔污水处理厂的总比CF分别为每人当量（PE）17.3和38.8 CO。在这两种情况下，均发现污泥管理、电力消耗以及污水处理的直接排放对CF有显著影响。总CF的很大一部分源自间接排放，主要由能源消耗所致。通过增加可再生能源的份额，可部分克服这种负面影响。在应用热电联产厂从沼气中回收能源时，总CF可降低30%以上。农田和堆肥后的农田被认为是污泥管理的最合适策略。由于替代了合成肥料，它们可产生CF信用（占总CF的8%）。鉴于基于固定排放因子（EFs）的CF估算存在高度不确定性，建议对污水处理过程中的一氧化氮排放进行可靠的全规模测量。在应用文献中报道的最低和最高一氧化氮EFs时，总CF甚至会变化2至3倍。
