Nitrogen Recovery and Storage: Separation and Recovery of Nitrous Oxide Generated from Wastewater Treatment Processes

( Sudheer Kumar Shukla ),( Tuan Van Doan ),( Jangho Lee ),( Joonhong Park ) 한국폐기물자원순환학회(구 한국폐기물학회) 2014 한국폐기물자원순환학회 춘계학술발표논문집 Vol.2014 No.-

Conventionally Nitrous oxide (N₂O) is considered as a harmful gas, contributing to the ozone layer depletion and to the greenhouse effect (310 and 21 times more powerful than CO₂ and CH₄, respectively). At present global warming mitigation cost for N₂O is 3600 USD/ton (at the rate of 12 USD/ton CO₂), (EPA 2011; EESI, 2012; Science daily, 2008). However, N₂O is a powerful oxidant in combustion reactions. It is commonly used to supercharge the engines of high performance vehicles (i.e. “Nitrox”) and as an oxidant in hybrid rocket motors in the aerospace industry. But it is very costly resource and the current N₂O selling cost is 18000-20000 USD/ton, approximate. Wastewater treatment sector is one of the significant contributors to N₂O generation. In the wastewater treatment emission N₂O is emitted with CO₂ and CH₄. Researchers are trying to enhance N₂O production during N2 removal these days. In our previous study we introduced a new nitrogen removal strategy from waste water, that exploits the thermodynamic properties of N₂O for energy recovery (Scherson et al. 2013). But to make N₂O usable, it should be free from other impurities especially from CO₂ and also should be at significantly high concentration. In spite of several studies N₂O and CO₂ separation is still a challenge. Because N₂O and CO₂ exhibit almost similar physical and chemical properties, that is why separation is very difficult. Even people have been using N₂O to study CO₂ properties to use their similarities (Anthony et al. 2005; Revelli et al. 2010; Sema et al. 2011). There have been several attempts made to separate N₂O and CO₂ (Hughes and Jiang 1995; Saha and Deng 2010; Shiflett et al. 2011; Saha et al. 2010) but none of them got any significant success in separating N₂O and CO₂. We used batch mode method for this study. Glass flask was used as a reactor, amine and hydroxide based solutions from sigma chemicals were used as absorbents. Operating conditions were standard temperature and pressure (STP). Six concentrations i.e. 0.5, 1, 2, 3, 4, 5 percent (w/w) were used for hydroxide based solution and 20 and 30% for amine solution. Reaction time was 60 minutes for each experiment, stirrer speed 180rpm. 99.9 % percent CO₂ and N₂O gas were used in 1:1 ratio. Gas Chromatograph (hp5890 model) was used to detect CO₂ and N₂O. We took gas samples at 5, 10, 15, 20, 30, 40, and 60 minutes interval to observe the absorption trends. Selectivity for CO₂ in the hydroxide solution was found to be more than N₂O gas. Amine solution absorbed CO₂ and N₂O both but it also preferred CO₂ more in comparison to N₂O. In the hydroxide solution case CO₂ absorption is increasing with time up to 20-30 minutes reaction time but it start releasing after 30 minutes. After 20 minute it hydroxide solution starts absorbing N₂O also. So, we can collect N₂O in the headspace at around 20 minutes. We can recover around 80 to 90% N₂O at/before 20 minutes reaction time. In amine case results were not very encouraging but it also preferred CO₂ over N₂O in the same reaction conditions. It can be concluded that N₂O can be separated from CO₂ using hydroxide absorption, while amine is not suitable for N₂O and CO₂ separation, which is also mentioned in the previous studies (Saha et al. 2010; Shiflett et al. 2011). Proposed method could be used to separate N₂O and CO₂ generated during various wastewater treatment process. As per our knowledge this is first study which reports N₂O and CO₂ separation using chemical absorption. This research will help our society in two ways; one hand it will help in minimizing global warming mitigation cost (present N₂O mitigation cost: 3600 USD/ton @ 12 USD/ton CO₂), in the other hand it will help in compensating current N₂O selling cost, (18000-20000 USD/ton, approximate).

흡수제를 이용한 아산화질소와 이산화탄소의 분리

( Sudheer Kumar Shukla ),( Tuan Van Doan ),( Jang Ho Lee ),( Joon Hong Park ) 한국물환경학회(구 한국수질보전학회) 2014 한국물환경학회·대한상하수도학회 공동 춘계학술발표회 Vol.2014 No.-

Decision tree-based data mining and rule induction for identifying hydrogeological parameters that influence groundwater pollution sensitivity

Yoo, Keunje,Shukla, Sudheer Kumar,Ahn, Jae Joon,Oh, Kyungjoo,Park, Joonhong Elsevier 2016 Journal of Cleaner Production Vol.122 No.-

<P><B>Abstract</B></P> <P>This study aims to develop a new field-based approach that can estimate patterns of groundwater pollution sensitivity using data mining algorithms. Hydrogeological and pollution sensitivity data were collected from the Woosan Industrial Complex, Korea, which is a site contaminated by trichloroethylene (TCE). The proposed data mining algorithm procedure uses seven hydrogeological properties as input variables: depth to water, net recharge, aquifer media, soil media, topography, vadose zone media, and hydraulic conductivity. The observed TCE sensitivity was used as the target data. Initially, four data mining algorithms artificial neural network (ANN), decision tree (DT), case-based reasoning (CBR), and multinomial logistic regression (MLR) were tested. We found that the DT-based data mining and rule induction method shows better prediction accuracy and consistency than the other methods. We also used the ordinal pairwise partitioning (OPP) algorithm to improve the accuracy and consistency of the DT model. A classification and regression tree (CART) analysis of the OPP-DT model indicated that the net recharge (R), soil media (S), and aquifer media (A) were the major hydrogeological factors that influence groundwater sensitivity to TCE at the site. The results of this study demonstrate that the proposed model can provide more accurate and consistent estimates of groundwater vulnerability to TCE compared to the existing models.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We use data mining method to estimate groundwater pollution vulnerability. </LI> <LI> Applicability is measured using trichloroethylene and hydrogeological data. </LI> <LI> Proposed method shows better correlation between input and target variables. </LI> <LI> Proposed model can be used to predict groundwater vulnerability at unmeasured points. </LI> <LI> Proposed method could be used in decision making process for environmental projects. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Effect of Algal Inoculation on COD and Nitrogen Removal, and Indigenous Bacterial Dynamics in Municipal Wastewater

( Jangho Lee ),( Jaejin Lee ),( Sudheer Kumar Shukla ),( Joonhong Park ),( Tae Kwon Lee ) 한국미생물 · 생명공학회 2016 Journal of microbiology and biotechnology Vol.26 No.5

The effects of algal inoculation on chemical oxygen demand (COD) and total nitrogen (TN) removal, and indigenous bacterial dynamics were investigated in municipal wastewater. Experiments were conducted with municipal wastewater inoculated with either Chlorella vulgaris AG10032, Selenastrum gracile UTEX 325, or Scenedesmus quadricauda AG 10308. C. vulgaris and S. gracile as fast growing algae in municipal wastewater, performed high COD and TN removal in contrast to Sc. quadricauda. The indigenous bacterial dynamics revealed by 16S rRNA gene amplification showed different bacterial shifts in response to different algal inoculations. The dominant bacterial genera of either algal case were characterized as heterotrophic nitrifying bacteria. Our results suggest that selection of indigenous bacteria that symbiotically interact with algal species is important for better performance of wastewater treatment.

Effect of electricity current on autotrophic BED denitrification and N₂O accumulation

Tuan Van Doan,Tae Kwon Lee,Sudheer Kumar Shukla,Joonhong Park 대한토목학회 2013 대한토목학회 학술대회 Vol.2013 No.10

Molecular approaches for the detection and monitoring of microbial communities in bioaerosols: A review

Yoo, Keunje,Lee, Tae Kwon,Choi, Eun Joo,Yang, Jihoon,Shukla, Sudheer Kumar,Hwang, Sang-il,Park, Joonhong Editorial Dept. of Journal of Environmental Scienc 2017 JOURNAL OF ENVIRONMENTAL SCIENCES -BEIJING- Vol.51 No.-