Determination of urine-derived odorous compounds in a source separation sanitation system.

Source separation sanitation systems have attracted more and more attention recently. However, separate urine collection and treatment could induce odor issues, especially in large scale application. In order to avoid such issues, it is necessary to monitor the odor related compounds that might be generated during urine storage. This study investigated the odorous compounds that emitted from source-separated human urine under different hydrolysis conditions. Batch experiments were conducted to investigate the effect of temperature, stale/fresh urine ratio and urine dilution on odor emissions. It was found that ammonia, dimethyl disulfide, allyl methyl sulfide and 4-heptanone were the main odorous compounds generated from human urine, with headspace concentrations hundreds of times higher than their respective odor thresholds. Furthermore, the high temperature accelerated urine hydrolysis and liquid-gas mass transfer, resulting a remarkable increase of odor emissions from the urine solution. The addition of stale urine enhanced urine hydrolysis and expedited odor emissions. On the contrary, diluted urine emitted less odorous compounds ascribed to reduced concentrations of odorant precursors. In addition, this study quantified the odor emissions and revealed the constraints of urine source separation in real-world applications. To address the odor issue, several control strategies are recommended for odor mitigation or elimination from an engineering perspective.

Characterization of induced struvite formation from source-separated urine using seawater and brine as magnesium sources.

Struvite (MgNH4PO4·6H2O) precipitation is widely used for nutrient recovery from source-separated urine in view of limited natural resources. Spontaneous struvite formation depletes the magnesium in hydrolyzed urine so that additional magnesium source is required to produce induced struvite for P-recovery. The present study investigated the morphology and purity of induced struvite crystals obtained from hydrolyzed urine by using seawater and desalination brine as low cost magnesium sources. The results demonstrated that both seawater and brine were effective magnesium sources to recover phosphorus from hydrolyzed urine. Crystals obtained from synthetic and real urine were revealed that the morphology was feather and coffin shape, respectively. Structural characterization of the precipitates confirmed that crystallized struvite was the main product. However, co-precipitates magnesium calcite and calcite were observed when seawater was added into synthetic and real urine, respectively. It was found that the presence of calcium in the magnesium sources could compromise struvite purity. Higher struvite purity could be obtained with higher Mg/Ca ratio in the magnesium source. Comparative analysis indicated that seawater and brine had similar effect on the crystallized struvite purity.

Using multiple calibration sets to improve the quantitative accuracy of partial least squares (PLS) regression on open-path Fourier transform infrared (OP/FT-IR) spectra of ammonia over wide concentration ranges.

The use of multiple calibration sets in partial least squares (PLS) regression was proposed to improve the quantitative determination of NH(3) over wide concentration ranges from open-path Fourier transform infrared (OP/FT-IR) spectra. The spectra were measured near animal farms, where the path-integrated concentration of NH(3) can fluctuate from nearly zero to as high as approximately 1000 ppm-m. PLS regression with a single calibration set did not cover such a large concentration range effectively, and the quantitative accuracy was degraded due to the nonlinear relationship between concentration and absorbance for spectra measured at low resolution (1 cm(-1) and poorer.) In PLS regression with multiple calibration sets, each calibration set covers a part of the entire concentration range, which significantly decreases the serious nonlinearity problem in PLS regression occurring when only a single calibration set is used. The relative error was reduced from approximately 6% to below 2%, and the best results were obtained with four calibration sets, each covering one quarter of the entire concentration range. It was also found that it was possible to build the multiple calibration sets easily and efficiently without extra measurements.