Sorption and high dynamics of micropollutants in sewers

2008 ◽  
Vol 57 (11) ◽  
pp. 1791-1797 ◽  
Author(s):  
C. Ort ◽  
W. Gujer

Down-the-drain household chemicals are mostly discharged intermittently (i.e. with water pulses, e.g. pharmaceuticals from toilet flushing) and well soluble micropollutants can, therefore, be subject to significantly high short-term fluctuations. It is not known how these fluctuations are attenuated by sorption to sewer sediments or biofilm. First, we investigated in this paper the effect of sorption for substances with high, medium and low affinity to particulate matter based on computational experiments. For substances with high Koc we found that the additional attenuation of a load pattern due to sorption is in the same order of magnitude as caused by dispersion in a typical main sewer. The mass flux between wastewater and the first biofilm layer was identified as the most sensitive parameter. Furthermore, the interplay of systematic, slow diurnal variations does not affect short-term fluctuations. Second, during rain events partial erosion of the biofilm can lead to increased micropollutant loads for substances with high Koc. This increase is in the same order of magnitude as diurnal variations of the loads in the liquid phase and the TSS.

2006 ◽  
Vol 54 (6-7) ◽  
pp. 169-176 ◽  
Author(s):  
C. Ort ◽  
W. Gujer

Most commercially available auto-sampling devices do not support a continuous flow-proportional sampling mode, which would conceptually be the best for collecting representative composite samples. Instead different discrete sampling modes are available. Household chemicals can show considerable random short-term variations. With the anticorrosive benzotriazole, relating to a middle-frequent household activity, we show that, besides an accurate flow meter, mainly three factors are decisive for the representativeness of a substance's average load: the substance's load pattern, the sampling frequency and the length of the composite sample. When the sampling intervals are 10 minutes or longer, errors in the order of ±40% (standard deviation) or more have to be accepted, if the substance of interest is contained in a low number of wastewater pulses (i.e. the level of household activity). This particularly holds true for specific pharmaceuticals e.g. carbamazepine. Ammonium would be less critical, because it relates to a larger number of sources in the same catchment.


Author(s):  
Jiyoung Shin ◽  
Jongmin Oh ◽  
In Sook Kang ◽  
Eunhee Ha ◽  
Wook Bum Pyun

Background/Aim: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). Methods: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. Results: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003–1.020 for lag 0, RR: 1.010, CI: 1.000–1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October–April) and the warm season (May–September) showed a significant lag 0 effect for AMI cases in the cold season only. Conclusions: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.


2019 ◽  
Vol 247 ◽  
pp. 874-882 ◽  
Author(s):  
Yang Yang ◽  
Zengliang Ruan ◽  
Xiaojie Wang ◽  
Yin Yang ◽  
Tonya G. Mason ◽  
...  

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