In this study, the hydrogen sulfide removal performance of materials that can be used instead of NaOH was evaluated to reduce the amount of NaOH, a harmful substance used in chemical cleaning methods. Three alternative chemical agents were evaluated: commercially available chemical-based CB, enzyme-based EB, and natural substance-based NB. The hydrogen sulfide removal performance evaluation consisted of three lab tests: the EL608 method, a method using a bag, a method using a sensor and a chamber, and a field test conducted on a scrubber in operation in the actual field. As a result of evaluation by the EL608 Method, CB was 92.3% (±2.9%), EB 60.5% (±5.8%), and NB 88.3% (±3.6%), similar or somewhat similar to NaOH (5%) 99.8% (0.1%). In the evaluation of the hydrogen sulfide removal performance using Bag, the Michaelis-Menten coefficient was CB 4.30 and EB 5.30, lower than NaOH 6.60, and the affinity for hydrogen sulfide was evaluated to be stronger. Even in the method using the sensor and chamber, CB and EB showed similar hydrogen sulfide removal performance of NaOH, but NB showed low treatment performance. In the evaluation using the scrubber in the actual field, the treatment efficiency of CB and EB was higher than that of NaOH under all hydrogen sulfide inlet concentration conditions. If microorganisms grow on the packing material filled inside the scrubber, treatment efficiency may decrease. In order to prevent this phenomenon, the microbial growth inhibitory function of alternative materials was evaluated, and CB, EB, and NB were all superior to NaOH. As a result of this study, it was shown that CB and EB can replace NaOH because they have excellent performance in removing hydrogen sulfide and inhibiting microbial growth.

Public complaints arising from centralized animal manure treatment plants are increasing due to the odors produced during animal manure treatment. Various physico chemical and biological methods are used to mitigate such odors. Still, many problems exist, such as a lack of fundamental data on odor generation characteristics and design standards for odor mitigation facilities. Therefore, this study evaluated the characteristics of NH3 and H2S gas produced from a centralized animal manure treatment plant. The centralized animal manure treatment plant selected in this study has a treatment capacity of 150 tons (animal manure and food waste) per day. The composting matrix was mechanically turned from 9:00 am to 6:00 pm on weekdays and not turned all day on weekends. The NH3 concentrations measured during the day on weekdays (96.4 ± 7.8 ppmv) were about 14% higher than on weekends (84.9 ± 15.9 ppmv). During the week, the ammonia concentration during the day was about 15% higher than at night, but there was no difference between day and night on weekends. The hydrogen sulfide concentration during the day (4,729 ± 3,687 ppbv) on a weekday was about 4.7 times higher than at night (1,007 ± 466 ppbv). The results of this study provide valuable information that is necessary for the operation of odor mitigation facilities. It is expected that the results will contribute to establishing an operational strategy that can reduce the energy required to collect exhaust gas.

This study evaluated the odor mitigation effect of rice husk biochar addition to the bedded pack dairy barn floor using lab-scale reactors for five days. Rice husk biochar mixed with dairy manure and sawdust mixture at different ratios (5%-addition test unit: adding biochar by 5% of the total solid weight of the mixture, 10%-addition test unit: adding biochar by 10% of the total solid weight of the mixture). Cumulative NH3 and H2S emissions of 10%-addition test unit were reduced by 26% (p< 0.05) and 46% (p = 0.0655), respectively, compared with control. However, 5%-addition test unit did not show NH3 and H2S emission reduction. Further research is needed to determine the appropriate level of biochar addition between 5 and 10%, and to evaluate applicability in the field through economic analysis.

Odor is a type of sensory pollution that can stimulate the human sense of smell when it occurs, causing discomfort and making it difficult to create a pleasant environment. For this reason, there is a high possibility of complaints regarding odors if odors occur in pigsties near residential properties, and the number of such complaints is also increasing. In addition, odors emanating from pigsties around military installations can cause physical and psychological harm, not only to the soldiers living in these type of facilities but also to the families belonging to military personnel living there as well. Because the concentration of odors varies due to diverse factors such as temperature, humidity, wind direction, wind speed, and interaction between causative materials, predicting odors based on only one factor is not proper or appropriate. Therefore, in this work, we sought to construct models that are based on several regression techniques of machine learning using data collected in field. And we selected and utilized the model that has the highest-accuracy in order to notify and warn residents of odors in advance. In this work, 3672 data items were used to train and test the model. The several machine learning algorithms to build the models are polynomial regression, ridge regression, K-nearest neighbor regression (KNN Regression), and random forest. Comparing the performance of models based on each algorithm, the study found that KNN Regression was the most suitable model, and the result obtained from KNN regression was significant.

Two lab-scale trickle-bed type biofilters with a single fungal species (Aspergillus fumigatus, Acidomyces acidophilus, respectively) have been studied to investigate the simultaneous removal of inorganic (hydrogen sulfide) and organic (butyl acetate) compounds. The biofilter with Aspergillus fumigatus treated simultaneously two different compounds with removal capacity of 1,511 mgS/m3/hr and 6,324 mgC/m3/hr; and the biofilter inoculated with Acidomyces acidophilus had the removal capacity of 1,254 mgS/m3/hr and 6,045 mgC/m3/hr. Stable operational performance was observed in both biofilters under an acidic condition of pH 2 to 4. Based on pseudo-first-order removal rates as a function of depth in the biofilter, Aspergillus fumigatus showed a twice faster rate of hydrogen sulfide removal than Acidomyces acidophilus, 15.9% (Aspergillus fumigatus) and 17.9% (Acidomyces acidophilus) of total sulfur removed were oxidized to produce sulfates, and 77.8% (Aspergillus fumigatus) and 79.4% (Acidomyces acidophilus) were accumulated in the form of S0 through the bed in both biofilters, respectively.

A lab-scale biofilter with fungal growth has been studied to investigate the removal of gas-phase hydrogen sulfide. The biofilter inoculated initially with the aerobic activated sludge was operated for 100 days under acidic condition, and 0.36 L/d of the buffered nutrient with 0.05 g/L Chloramphenicol and Gentamicin was injected into the biofilter. The critical removal capacity of hydrogen sulfide was up to 22 g/m³/h. The pH of the effluent liquid was stable at pH 1.5-2, corresponding to the volatile suspended solids of 20-50 mg/L. In microbial analysis through the plate count method, it was found that fungi were dominant over bacteria. The fungi isolated from biomass in the bilfilter were identified as Acidomyces acidophilus and Aspergillus fumigatus. Sulfate and thiosulfate were also detected in liquid samples, as a result of the biological sulfur oxidation in the biofilter bed. For the analysis of sulfur mass balance, the accumulated mass of sulfate and thiosulfate reached up to 67.5% of inlet sulfur. Sulfur was also detected on the biomass collected from the biofilter through Scanning electron microscopy/Energy dispersive X-ray spectroscopy.

Nickel oxide(NiO) thin films, nanorods, and carbon nanotube(CNT)/NiO core-shell nanorod structures are fabricated by sputtering Nickel at different deposition time on alumina substrates or single wall carbon nanotube templates followed by oxidation treatments at different temperatures, 400 and 700 oC. Structural analyses are carried out by scanning electron microscopy and x-ray diffraction. NiO thinfilm, nanorod and CNT/NiO core-shell nanorod structurals of the gas sensor structures are tested for detection of H2S gas. The NiO structures exhibit the highest response at 200 oC and high selectivity to H2S among other gases of NO, NH3, H2, CO, etc. The nanorod structures have a higher sensing performance than the thin films and carbon nanotube/NiO core-shell structures. The gold catalyst deposited on NiO nanorods further improve the sensing performance, particularly the recovery kinetics.

Acidic and basic mixtures of odorous compounds are commonly emitted from various sources, and, in an absorption process, pH conditions in the liquid phase significantly affect the performance. In this study, the effect of pH on mass transfer in a bubble column reactor was evaluated using hydrogen sulfide and ammonia as a model mixture. Their mass transfer coefficients were then calculated. Furthermore, the total mass transfer coefficients as a function of pH were evaluated, and the experimental data were fitted into an empirical equation using dimensionless numbers. The mass transfer rates of hydrogen sulfide, the non-ionic form, increased dramatically with increasing pHs, while those of ammonia were almost unchanged because of its high solubility. As a result, a favorable pH condition for less soluble compounds must be selected to achieve high absorption capacity. The total mass transfer rates, which took into account pH effects as well as all the non-ionic and ionic constituents together, were found to be from 2.2 to 2.4 × 10−3 min−1 for hydrogen sulfide and ammonia, respectively, and they were almost constant at different pHs. The empirical equations, which were derived to obtain the best fit for the total mass transfer rates, implied that a method to increase diffusivity of each compound should be applied to improve overall mass transfer. In addition, when using the empirical equation, a mass transfer coefficient at a given set of pH and operating conditions can be calculated and used to design a water scrubbing process.

Hydrogen sulfide (H2S) emitted from various sources is a major odorous compound, and non-thermal plasma (NP) has emerged as a promising technique to eliminate H2S. This study was conducted to investigate lab-scale and pilot-scale NP reactors using corona discharge for the removal of H2S, and the effects of relative humidity, applied electrical power on reactor performance and ozone generation were determined. A gas stream containing H2S was injected to the lab-scale NP reactor, and the changes in H2S and ozone concentration were monitored. In the pilotscale NP experiment, the inlet concentration and flow rate were modified to determine the effect of relative humidity and applied power on the NP performance. In the lab-scale NP experiments, H2S removal was found to be the 1st-order reaction in the presence of ozone. On the other hand, when plasma reaction and ozone generation were initiated after H2S was introduced, the H2S oxidation followed the 0th-order kinetics. The ratio of indirect oxidation by ozone to the overall H2S removal was evaluated using two different experimental findings, indicating that approximately 70% of the overall H2S elimination was accounted for by the indirect oxidation. The pilotscale NP experiments showed that H2S introduced to the reactor was completely removed at low flow rates, and approximately 90% of H2S was eliminated at the gas flow rate of 15 m3/min. Furthermore, the elimination capacity of the pilot-scale NP was 3.4 g/m3·min for the removal of H2S at various inlet concentrations. Finally, the experimental results obtained from both the lab-scale and the pilot-scale reactor operations indicated that the H2S mass removal was proportional to the applied electrical power, and average H2S masses removed per unit electrical power were calculated to be 358 and 348 mg-H2S/kW in the lab-scale and the pilot-scale reactors, respectively. To optimize energy efficiency and prevent the generation of excessive ozone, an appropriate operating time of the NP reactor must be determined.

This paper presents the results of a human health effect for H2S emission standard of incinerators in Seoul, Korea. The four selected incinerators of Gangnam, Mapo, Nowon and Yangcheon were chosen as the domains of study. Air dispersion modelling (AERMOD) was used to predict the ground level concentration within 3 km distance of the emission source. The emissions at the incinerators studied ranged from 0.0721 (Yangcheon) to 0.3007 g/s (Gangnam). These values were about three orders of magnitude smaller than that of Canadian geothermal power plants. Based on the health risk assessment, different health risks were identified for short-term and long-term dispersion of the studied areas. The short-term hazard quotient (HQ) for H2S of Gangnam and Nowon incinerators were greater than the acceptable limit (i.e., 1.0) in some locations. However the long-term HQ for H2S of all incinerators were lower than the acceptable limit.

The study analyzed performance assessment factors of odor sensors from 4 different manufacturers, including minimum detection limit, humidity stability and temperature stability. In the minimum detection limit assessment, only one electrochemical gas sensor was able to detect ammonia and hydrogen sulfide at the concentration of 5 ppb. The standard deviation ratio was over 10%, and it increased as humidity rose. The range of temperatures in which the electrochemical and photoionization gas sensors could function well was between 25oC and 40oC, and the sensor output values were unstable at low temperatures. Regarding the temperature stability of the metal oxide semiconductor sensor for measuring complex odors, the sensor output values dropped considerably to 0~10oC, and were similar to the concentrations of odor gases generated at 25oC. The results of the test of odor sensor outputs after temperature and humidity pre-treatment revealed that the respective stable output values at 50% humidity and 25oC were similar to the concentrations of manufactured odors. In terms of temperature and humidity stability of the NH3, H2S and Complex odor sensors, all target substances had stable output values at 25~40oC and 50~65% relative humidity, and unstable values at low temperatures and high humidity. Therefore, implementing pretreatment systems including temperature and humidity correction (25~40oC, 50~65% RH) is necessary for the stable use of odor sensors.