In this study, the performances of H2S, NH3, and HCl sensors for real-time monitoring in small emission facilities (4, 5 grades in Korea) were evaluated at high concentration conditions of those gases. And the proper approach for the collection of reliable measurement data by sensors was suggested through finding out the effect on sensor performances according to changes in temperature and humidity (relative humidity, RH) settings. In addition, an assessment on sensor data correction considering the effects produced by environmental settings was conducted. The effects were tested in four different conditions of temperature and humidity. The sensor performances (reproducibility, precision, lower detection limit (LDL), and linearity) were good for all three sensors. The intercept (ADC0) values for all three sensors were good for the changes of temperature and humidity conditions. The variation in the slope value of the NH3 sensor showed the highest value, and this was followed by the HCl, H2S sensors. The results of this study can be helpful for data collection by enabling the more reliable and precise measurements of concentrations measured by sensors.

We used the measurement data derived from a proton transfer reaction time-offlight mass spectrometry (PTR-ToF-MS) to ascertain the source profile of volatile organic compounds (VOCs) from 4 major industrial classifications which showed the highest emissions from a total of 26 industrial classifications of A industrial complex. Methanol (MOH) was indicated as the highest VOC in the industrial classification of fabricated metal manufacture, and it was followed by dichloromethane (DM), ethanol (EN) and acetaldehyde (AAE). In the industrial classification of printing and recording media, the emission of ethylacetate (EA) and toluene (TOL) were the highest, and were followed by acetone (ACT), ethanol (EN) and acetic acid (AA). TOL, MOH, 2-butanol (MEK) and AAE were measured at high concentrations in the classification of rubber and plastic manufacture. In the classification of sewage, wastewater and manure treatment, TOL was the highest, and it was followed by MOH, H2S, and ethylbenzene (EBZ). In future studies, the source profiles for various industrial classifications which can provide scientific evidence must be completed, and then specified mitigation plans of VOCs for each industrial classification should be established.

This study was carried out in order to provide suggestions with regard to optimal control methods for various odor emission facilities (162 companies and 26 industrial classifications) through comparative analysis of effective odor treatment technologies for each type of odor substance by literature reviews, based on measured 22 odor substance data for 162 samples taken from A city. The industrial classification of Pulp showed the highest odor quotient (7,589 as average value) and was followed by the industrial classifications of Wastewater, Woods, and Furniture, indicating average odor quotient values of 2,361, 1,396 and 1,392, respectively. Absorption using chlorine dioxide and sodium hydroxide can be an optimal treatment method to remove the odor substances of sulfide and aldehyde groups. Biofilers with microbial communities will be effective to remove odors caused by volatile organic compounds (VOCs) and an absorption method using sulfuric acid is proper for the removal of odor substances caused by nitrogens.

This study was conducted to identify and assess key parameters affecting greenhouse gas emissions and odor intensity at a naturally ventilated dairy farm. Measurement data of greenhouse gases (CO2, CH4, N2O), odorants (NH3 and H2S), and meteorological data (wind speed, temperature, relative humidity, and solar radiation) were posited as the parameters influencing those emissions. Carbon dioxide and methane emissions correlated well to CO2-equivalent emissions and the contribution of carbon dioxide emissions (R2=0.9181) was greater than that of methane emissions (R2=0.8854). Hydrogen sulfide emissions were highly correlated with odor intensity (R2=0.9989), but the contribution of ammonia emissions to odor intensity was not significant (R2=0.0081). No correlation among CO2-equivalent and odor intensity emissions and meteorological parameters was observed. In this study, the relationship between emissions of greenhouse gases and odor intensity in a naturally ventilated dairy barn mainly depended upon carbon dioxide and hydrogen sulfide emissions. The results in this study will be helpful in the mitigation planning of greenhouse gases and odor in animal feeding operations (CFOs).

Environmental fundamental facilities have different odor emission characteristics depending on the type of treatment facilities. To overcome the limitations of the olfactometry method, research needs to be conducted on how to calculate the dilution factor from the individual odor concentrations. The aim of this study was to determine the air dilution factor estimated from manually measured concentration data of individual odor substances (22 specified odor species) in three environmental treatment facilities. In order to calculate the optimum algorism for each environmental fundamental facility, three types of facilities were selected, the concentration of odor substances in the exhaust gas was measured, and the contribution of the overall dilution factor was evaluated. To estimate the dilution factor, four to six algorism were induced and evaluated by correlation analysis between substance concentration and complex odor data. Dilution factors from O municipal water treatment (MWT) and Y livestock wastewater treatment (LWT) facilities showed high level of dilution factors, because concentration levels of hydrogen sulfide and methylmercaptan, which had low odor threshold concentrations, were high. In S food waste treatment (FWT) facility, the aldehyde group strongly influenced dilution the factor (dominant substance: acetaldehyde, i-valeraldhyde and methylmercaptan). In the evaluation of four to six algorism to estimate the dilution factor, the vector algorism (described in the text) was optimum for O MWT and Y LWT, while the algorism using the sum of the top-three dominant substances showed the best outcome for S FWT. In further studies, estimation of the dilution factor from simultaneously monitored data by odor sensors will be developed and integrated with the results in this study.

The correlation among gaseous air pollutants (odorous compounds, greenhouse gases) and meteorological parameters was analyzed in-depth using measurement data at a barn and ambient in a naturally ventilated dairy farm. Both concentration and emission data (loading rate and emission rate), which more accurately express the actual pollutant emissions, were used in the correlation analysis. Gaseous air pollutants (ammonia, hydrogen sulfide, carbon dioxide, nitrous oxide, methane) and meteorological factors (relative humidity, temperature, wind speed, solar strength) were measured for one week in July 2013. The upper and lower outliers of measured data by inducing 1.5 times the interquartile range (IQR) were eliminated. After eliminating the outliers and grouping according to data magnitude, the correlation analysis among gaseous compounds and meteorological factors was conducted using the average values of each group. In the correlation analysis, data for the emission rate (barn) and the loading rate (ambient) showed a better correlation than concentration data. Gaseous air pollutants except for hydrogen sulfide in the barn showed a good correlation. Hydrogen sulfide might not be produced from manure or animal origin. Rather, the compound may be produced by flushing water, which was flushed at periodical times (every six hours). Ammonia emissions increased with increasing temperature, and this increase can be affected from greater exertion of feces by frequent water drinking in a high-temperature condition. In the ambient, the correlation for all gaseous air pollutants was better than that in the barn, because those air pollutants from manure, animals, and flushing water origins were sufficiently mixed in the atmosphere. Wind speed also showed a good correlation with all gaseous air pollutants.

The objectives of this study were (i) to evaluate the effects of temperature and relative humidity on two electrochemical sensors measuring hydrogen sulfide and ammonia using a laboratory testing system for various sensors, and (ii) to propose a calibration method for those concentrations to collect more reliable monitoring data. The effect of temperature and relative humidity was tested under three different conditions, respectively. The linearities measured data under all different conditions for the relative humidity and temperature were excellent, indicating more than 0.99 of R2 for both odor sensors. Under the condition of zero concentration, baselines (intercepts) at zero increased with increasing relative humidity for both hydrogen sulfide and ammonia sensors. The rate of gas concentration according to ADC variation (slopes) increased with increasing relative humidity about only the hydrogen sulfide sensor. In this study, slope, and intercept are utilized for calibration of hydrogen sulfide and ammonia concentration, and the reliability of the data of hydrogen sulfide and ammonia sensors is further enhanced by the relational expression obtained by this paper.

We used three gas sensors to monitor hydrogen sulfide, ammonia, and volatile organic compounds (VOCs), which were frequently emitted from environmental facilities, such as municipal wastewater treatment, livestock manure treatment, and food waste composting facilities. Two electrochemical (EC) sensors for detecting hydrogen sulfide and ammonia, and a photoionization detector (PID) sensor for detecting VOCs were characterized in this study. The performance of their linearity by concentration levels, lower detection limit (LDL), repeatability, reproducibility, precision, and response time were tested under the laboratory condition. The linearity according to concentration levels were favorable for all three sensors with high correlation coefficients (R2 > 0.98). The ammonia sensor showed the highest LDL (18.6 ppb) and the hydrogen sulfide and VOC sensors showed 22.3 ppb and 26.7 ppb of LDL, respectively. The reproducibility and precision were favorable for all three sensors, indicating a lower relative standard deviation (RSD) than 0.9% in the reproducibility test and 7.2% in the precision test. The response times to reach target concentration were varied from 1 to 12 minutes. The ammonia sensor needed 12 minutes of response time at 1 ppm target the NH3 concentration and the hydrogen sulfide and VOC sensors needed less than 2 minutes of response time.

In this study, the loading rates (or emission rate) and concentrations of air pollutants (ammonia, hydrogen sulfide, carbon dioxide, methane, nitrous oxide, and particulate matter (PM2.5, PM10 and TSP)) emitted from a naturally ventilated dairy facility were analyzed and compared to enable a better understanding that are in close proximity to each other, air pollution status. In general, the pollution patterns should be similar in measurement sites that are in close proximity to each other, and this hypothesis was fundamental to our approach in this study. For the comparison in nearby different sites, monitoring points were located at inside (source site) and outside the dairy building (ambient site), and concentrations and wind velocity were simultaneously monitored in real time. The patterns of PM2.5 emission rate and loading rate were similar in the source site and the ambient site which was consist with the hypothesis, while the PM2.5 mass concentration were not similar in both sites. As well as PM2.5, the emission rates (source site) of gaseous carbon dioxide (CO2) and nitrous oxide (N2O) were highly correlated to their loading rates (ambient site), while the concentrations of CO2 and N2O were not similar. Therefore, wind velocity, which is included in the emission or loading rate, should be simultaneously monitored with the concentration at the same measurement points for better understanding of the air pollution status.

This study was conducted to investigate the distribution characteristics, source identification, and health risk of polycyclic aromatic hydrocarbons (PAHs) present in particulate matter 10 (PM-10), in Gwangju. PM-10 samples were collected from September 2021 to August 2022 from three sampling sites, one located in each of the following areas: green, residential, and industrial. The average concentrations of PAHs were found to be higher in the industrial area (9.75±6.51 ng/㎥) than in the green (6.90±2.41 ng/㎥) and residential (6.74±2.38 ng/㎥) areas. Throughout the year and across all sites, five-ring PAHs accounted for the largest proportion (29.8–34.5%) of all PAHs. The concentrations of PAHs showed distinct seasonal variations, with the highest concentration observed in winter, followed by autumn, spring, and summer. Source apportionment analyses were performed using diagnostic ratios and principal component analyses, which indicated that coal/biomass combustion and vehicle emissions were the primary sources of PAHs in PM-10. The incremental lifetime cancer risk was estimated for all age groups at all sampling sites, and the results revealed a much lower risk level than the standard acceptable risk level (1×10-6).