Continuous OTM 33A Analysis of Controlled Releases of Methane with Various Time Periods, Data Rates and Wind Filters
Continuous OTM 33A Analysis of Controlled Releases of Methane with Various Time Periods, Data Rates and Wind Filters
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DOI：
10.3390/environments7090065
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发表时间：
2020-09-01
期刊：
影响因子：
3.7
通讯作者：
Johnson, Derek R.
中科院分区：
文献类型：
--
作者：
Heltzel, Robert S.;Zaki, Mohammed T.;Johnson, Derek R.
自环境保护局（EPA）引入其他测试方法（OTM）33 A以来，该方法已用于量化天然气站点的排放量。该方法依赖于点源高斯（PSG）的假设，以估计从目标站点或源的排放率。然而，该方法通常导致低准确度（通常+/-70%，即使在有利条件下）。这些准确度与控制释放实验进行了验证。通常，控制释放是在适宜于有效羽流迁移的大气条件下进行的，时间较短（15-20分钟）。我们研究了三个甲烷释放率从三个距离在不同的时间段，从七个小时到七天。数据从固定塔连续记录。大气条件变化很大，并不总是有利于传统的OTM 33 A计算。当平均风向对应于从受控释放到塔的方向的+/- 90度时，对20分钟的时间段进行OTM 33 A估计。通过改变数据的频率、各个OTM 33 A周期的长度和用于过滤数据的风向角的大小来进行进一步的分析。结果表明，不同的（比传统使用的）周期长度，风过滤器，数据采集频率和数据质量过滤器影响的OTM 33 A的准确性时，应用于长期测量。
Other test method (OTM) 33A has been used to quantify emissions from natural gas sites since it was introduced by the Environmental Protection Agency (EPA). The method relies on point source Gaussian (PSG) assumptions to estimate emissions rates from a targeted site or source. However, the method often results in low accuracy (typically +/- 70%, even under conducive conditions). These accuracies were verified with controlled-release experiments. Typically, controlled releases were performed for short periods (15-20 min) under atmospheric conditions that were ideal for effective plume transport. We examined three methane release rates from three distances over various periods of time ranging from seven hours to seven days. Data were recorded continuously from a stationary tower. Atmospheric conditions were highly variable and not always conducive to conventional OTM 33A calculations. OTM 33A estimates were made for 20-min periods when the mean wind direction corresponded to +/- 90 degrees of the direction from the controlled release to the tower. Further analyses were performed by varying the frequency of the data, the length of the individual OTM 33A periods and the size of the wind angle used to filter data. The results suggested that different (than conventionally used) period lengths, wind filters, data acquisition frequencies and data quality filters impacted the accuracy of OTM 33A when applied to long term measurements.