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A high temporal-spatial emission inventory and updated emission factors for coal-fired power plants in Shanghai, China

机译:中国上海燃煤电厂的高时空排放清单和最新排放因子

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With the implementation of the ultra-low emission policy in China, emission factors (EFs) of power plant pollutants are constantly changing. Emission inventories developed using the recommended EFs contain high levels of uncertainty and it is difficult to achieve a high temporal resolution. Detailed sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission data based on a continuous emission monitoring system (CEMS) were obtained from 33 units at 13 power plants in Shanghai in 2017. The data were used to develop an hourly unit-based emission inventory and to devise updated EFs for coal-fired power plants. Emissions of SO2, NOx, and PM typically met the ultra-low emission limit, with total emissions of SO2, NOx, and PM of 2895.0, 5348.3, and 503.8 tons, respectively. Emission proportions of SO2 and NOx for 300-600, 600-1000, and above 1000 MW units were similar, while the emission proportion of PM decreased with an increase in unit capacity. Emissions of SO2, NOx, and PM displayed similar monthly variations, peaking in winter and summer. Diurnal hourly variations of SO2, NOx, and PM emissions displayed a bimodal trend, with higher emissions at night on weekends than on weekdays. EFs based on CEMS (EFC) of SO2, NOx, and PM were 0.10, 0.36, and 0.04 g kg(-1) of coal, respectively, which were one or two orders of magnitude lower than the widely-used EFs and 4-30 times lower than EFs based on the mass balance approach. After replacing the recommended fixed decontamination efficiencies with individually fitted values, the calculated EFs were consistent with the corresponding EFC and discrepancies were further reduced. The new inventory and updated EFs will enable a better understanding of the temporal variations of power plant emissions and reduce the uncertainty caused by the overestimation of EFs after the implementation of ultra-low emissions technology. (C) 2019 Elsevier B.V. All rights reserved.
机译:随着中国实施超低排放政策,电厂污染物的排放因子(EFs)不断变化。使用推荐的EF制定的排放清单存在高度不确定性,很难实现高时间分辨率。基于连续排放监测系统(CEMS)的详细二氧化硫(SO2),氮氧化物(NOx)和颗粒物(PM)排放数据是2017年从上海13个电厂的33个机组获得的。这些数据用于制定基于小时的单位排放清单,并为燃煤电厂设计更新的EF。 SO2,NOx和PM的排放量通常达到超低排放限值,SO2,NOx和PM的总排放量分别为2895.0、5348.3和503.8吨。 300-600、600-1000和1000 MW以上机组的SO2和NOx排放比例相似,而PM的排放比例随着单位容量的增加而降低。 SO2,NOx和PM的排放显示类似的每月变化,在冬季和夏季达到峰值。 SO2,NOx和PM排放的每日小时变化显示出双峰趋势,周末晚上的排放高于工作日。基于SO2,NOx和PM的CEMS(EFC)的EFs分别为煤的0.10、0.36和0.04 g kg(-1),比广泛使用的EFs和4-降低了两个数量级。基于质量平衡方法,比EF低30倍。用单独拟合的值代替推荐的固定去污效率后,计算出的EF与相应的EFC一致,并且进一步减少了差异。新的清单和更新的EF将使人们能够更好地了解电厂排放的时间变化,并减少实施超低排放技术后因EF的高估而造成的不确定性。 (C)2019 Elsevier B.V.保留所有权利。

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