{"title":"利用真空热剥离和酸吸收工艺优化原液奶牛粪便中氨氮的去除和回收:采用响应面方法的建模方法","authors":"Srijana Sapkota, Arif Reza, Lide Chen","doi":"10.3390/nitrogen5020026","DOIUrl":null,"url":null,"abstract":"Dairy manure adds a substantial amount of nitrogen to wastewater due to its high levels of associated nutrients. Removal and recovery of ammonia nitrogen (NH3-N) from raw liquid dairy manure (RLDM) is greatly valued. This study was focused on the vacuum thermal stripping–acid absorption (VTS-AA) process for NH3-N from RLDM, followed by modeling and optimization. Using the response surface methodology (RSM)-based central composite design (CCD) approach, the critical operational parameters of the vacuum thermal stripping process, including temperature (50–70 °C), pH (9–11), vacuum pressure (35–55 kPa), and treatment time (60–90 min), were optimized. With the specified parameters set at temperature 69.9 °C, pH 10.5, vacuum pressure 53.5 kPa, and treatment time 64.2 min, the NH3-N removal efficiency attained was 98.58 ± 1.05%, aligning closely with the model prediction. Furthermore, the recovered ammonium sulfate ((NH4)2SO4) closely matched their commercial counterparts, confirming the effectiveness of the VTS-AA process in recovering NH3-N from RLDM. The distinct advantage of the employed technology lies in the concurrent energy demand reduction achieved by introducing a vacuum system. These findings contribute valuable insights into the practical implementation of the VTS-AA process for treating raw dairy manure, particularly in large-scale operational contexts.","PeriodicalId":509275,"journal":{"name":"Nitrogen","volume":" 16","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of Ammonia Nitrogen Removal and Recovery from Raw Liquid Dairy Manure Using Vacuum Thermal Stripping and Acid Absorption Process: A Modeling Approach Using Response Surface Methodology\",\"authors\":\"Srijana Sapkota, Arif Reza, Lide Chen\",\"doi\":\"10.3390/nitrogen5020026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dairy manure adds a substantial amount of nitrogen to wastewater due to its high levels of associated nutrients. Removal and recovery of ammonia nitrogen (NH3-N) from raw liquid dairy manure (RLDM) is greatly valued. This study was focused on the vacuum thermal stripping–acid absorption (VTS-AA) process for NH3-N from RLDM, followed by modeling and optimization. Using the response surface methodology (RSM)-based central composite design (CCD) approach, the critical operational parameters of the vacuum thermal stripping process, including temperature (50–70 °C), pH (9–11), vacuum pressure (35–55 kPa), and treatment time (60–90 min), were optimized. With the specified parameters set at temperature 69.9 °C, pH 10.5, vacuum pressure 53.5 kPa, and treatment time 64.2 min, the NH3-N removal efficiency attained was 98.58 ± 1.05%, aligning closely with the model prediction. Furthermore, the recovered ammonium sulfate ((NH4)2SO4) closely matched their commercial counterparts, confirming the effectiveness of the VTS-AA process in recovering NH3-N from RLDM. The distinct advantage of the employed technology lies in the concurrent energy demand reduction achieved by introducing a vacuum system. These findings contribute valuable insights into the practical implementation of the VTS-AA process for treating raw dairy manure, particularly in large-scale operational contexts.\",\"PeriodicalId\":509275,\"journal\":{\"name\":\"Nitrogen\",\"volume\":\" 16\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nitrogen\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/nitrogen5020026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nitrogen","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/nitrogen5020026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of Ammonia Nitrogen Removal and Recovery from Raw Liquid Dairy Manure Using Vacuum Thermal Stripping and Acid Absorption Process: A Modeling Approach Using Response Surface Methodology
Dairy manure adds a substantial amount of nitrogen to wastewater due to its high levels of associated nutrients. Removal and recovery of ammonia nitrogen (NH3-N) from raw liquid dairy manure (RLDM) is greatly valued. This study was focused on the vacuum thermal stripping–acid absorption (VTS-AA) process for NH3-N from RLDM, followed by modeling and optimization. Using the response surface methodology (RSM)-based central composite design (CCD) approach, the critical operational parameters of the vacuum thermal stripping process, including temperature (50–70 °C), pH (9–11), vacuum pressure (35–55 kPa), and treatment time (60–90 min), were optimized. With the specified parameters set at temperature 69.9 °C, pH 10.5, vacuum pressure 53.5 kPa, and treatment time 64.2 min, the NH3-N removal efficiency attained was 98.58 ± 1.05%, aligning closely with the model prediction. Furthermore, the recovered ammonium sulfate ((NH4)2SO4) closely matched their commercial counterparts, confirming the effectiveness of the VTS-AA process in recovering NH3-N from RLDM. The distinct advantage of the employed technology lies in the concurrent energy demand reduction achieved by introducing a vacuum system. These findings contribute valuable insights into the practical implementation of the VTS-AA process for treating raw dairy manure, particularly in large-scale operational contexts.