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基于降雨量、环境温度和废物组成估算垃圾填埋场的甲烷排放量:CLEEN 模型。

Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

机构信息

Department of Civil Engineering, 416 Yates Street, Suite 425, University of Texas at Arlington, Arlington, TX 76019, United States.

Department of Civil Engineering, 416 Yates Street, Suite 425, University of Texas at Arlington, Arlington, TX 76019, United States.

出版信息

Waste Manag. 2015 Dec;46:389-98. doi: 10.1016/j.wasman.2015.07.030. Epub 2015 Sep 4.

Abstract

Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual.

摘要

准确估算垃圾填埋场甲烷排放量对于量化垃圾填埋场的温室气体排放和发电潜力非常重要。当前的模型,包括 LandGEM 和 IPCC,通常大大简化了降雨和环境温度等因素的处理,而这些因素会对气体产生产生重大影响。新开发的“满足能源需求的垃圾填埋场排放捕获”(CLEEN)模型旨在提高垃圾填埋场甲烷生成估算值,但仍需要相当容易获得的输入:废物成分、年降雨量和环境温度。为了开发该模型,从 27 个实验室规模的垃圾填埋场反应器中测量了甲烷生成量,这些反应器的废物成分(从 0%到 100%)变化;平均降雨量分别为 2、6 和 12 毫米/天;温度分别为 20、30 和 37°C,根据统计实验设计。考虑的垃圾成分包括主要的可生物降解废物、食物、纸张、庭院/木材和纺织品以及惰性无机废物。根据收集的数据,开发了一个多元线性回归方程(R²=0.75),将一阶甲烷生成率常数 k 作为废物成分、年降雨量和温度的函数进行预测。由于实验室甲烷生成率高于现场速率,因此使用来自高收入国家 11 个常规运营的垃圾填埋场的实际气体回收数据,开发了第二个 k 的比例回归方程。将两个回归方程纳入基于一阶衰减的模型中,开发了“满足能源需求的垃圾填埋场排放捕获”(CLEEN)模型,用于估算垃圾填埋场的甲烷生成率。将 CLEEN 模型值与来自美国 6 个垃圾填埋场的实际现场数据以及 LandGEM 和 IPCC 的估算值进行了比较。在 6 个案例中的 4 个案例中,CLEEN 模型的估算值最接近实际值。

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