Oscar Samuelsson , Erik U. Lindblom , Kenneth Djupsjö , Linda Kanders , Lluís Corominas
{"title":"基于模型的污水处理厂设计中减少不确定性的迁移率数据","authors":"Oscar Samuelsson , Erik U. Lindblom , Kenneth Djupsjö , Linda Kanders , Lluís Corominas","doi":"10.1016/j.wroa.2025.100418","DOIUrl":null,"url":null,"abstract":"<div><div>Model-based design is an emerging tool for dealing with the uncertain dynamic loads entering wastewater treatment plants (WWTPs). But our understanding about the load-driving population-dynamics is limited. Therefore, we studied if mobility data (mobile telecommunications data) could be used to reduce uncertainties during design. Mobility data from Uppsala, Sweden between 2019–2022 clearly quantified population movement patterns that were useful for simulating load scenarios such as seasonal load-shifts, without data gaps from irregular influent sampling. Further, they showed fair correlations with the daily influent nitrogen load (R<sup>2</sup> = 0.49), which resulted in a more precise person load estimate than assuming a static population (23 % reduced variance). Unfortunately, BOD load variations showed little correlation with the population variations (R<sup>2</sup> = 0.21). Nevertheless, model-based reactor sizing based on mobility data successfully reduced the de-/nitrification volume safety factor with 5 percentage points, which demonstrates their practical usefulness for WWTP design.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100418"},"PeriodicalIF":8.2000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mobility data for reduced uncertainties in model-based WWTP design\",\"authors\":\"Oscar Samuelsson , Erik U. Lindblom , Kenneth Djupsjö , Linda Kanders , Lluís Corominas\",\"doi\":\"10.1016/j.wroa.2025.100418\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Model-based design is an emerging tool for dealing with the uncertain dynamic loads entering wastewater treatment plants (WWTPs). But our understanding about the load-driving population-dynamics is limited. Therefore, we studied if mobility data (mobile telecommunications data) could be used to reduce uncertainties during design. Mobility data from Uppsala, Sweden between 2019–2022 clearly quantified population movement patterns that were useful for simulating load scenarios such as seasonal load-shifts, without data gaps from irregular influent sampling. Further, they showed fair correlations with the daily influent nitrogen load (R<sup>2</sup> = 0.49), which resulted in a more precise person load estimate than assuming a static population (23 % reduced variance). Unfortunately, BOD load variations showed little correlation with the population variations (R<sup>2</sup> = 0.21). Nevertheless, model-based reactor sizing based on mobility data successfully reduced the de-/nitrification volume safety factor with 5 percentage points, which demonstrates their practical usefulness for WWTP design.</div></div>\",\"PeriodicalId\":52198,\"journal\":{\"name\":\"Water Research X\",\"volume\":\"29 \",\"pages\":\"Article 100418\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2025-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Research X\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589914725001173\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Research X","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589914725001173","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Mobility data for reduced uncertainties in model-based WWTP design
Model-based design is an emerging tool for dealing with the uncertain dynamic loads entering wastewater treatment plants (WWTPs). But our understanding about the load-driving population-dynamics is limited. Therefore, we studied if mobility data (mobile telecommunications data) could be used to reduce uncertainties during design. Mobility data from Uppsala, Sweden between 2019–2022 clearly quantified population movement patterns that were useful for simulating load scenarios such as seasonal load-shifts, without data gaps from irregular influent sampling. Further, they showed fair correlations with the daily influent nitrogen load (R2 = 0.49), which resulted in a more precise person load estimate than assuming a static population (23 % reduced variance). Unfortunately, BOD load variations showed little correlation with the population variations (R2 = 0.21). Nevertheless, model-based reactor sizing based on mobility data successfully reduced the de-/nitrification volume safety factor with 5 percentage points, which demonstrates their practical usefulness for WWTP design.
Water Research XEnvironmental Science-Water Science and Technology
CiteScore
12.30
自引率
1.30%
发文量
19
期刊介绍:
Water Research X is a sister journal of Water Research, which follows a Gold Open Access model. It focuses on publishing concise, letter-style research papers, visionary perspectives and editorials, as well as mini-reviews on emerging topics. The Journal invites contributions from researchers worldwide on various aspects of the science and technology related to the human impact on the water cycle, water quality, and its global management.