In order to determine the future direction of Busan City’s tree planting policy in accordance with changes in automobile fuel and air pollutants, this study selected representative tree species planted in Busan and identified the biogenic volatile organic compounds (BVOCs) emission rate and characteristics of each species. First, representative tree species were selected for each street tree species, forest tree species, and park tree species, and the emission rate and major components of BVOCs were investigated for each tree species. Furthermore, by comparing the ozone generation potential (POCP) for each tree species, tree species with a low emission rate were selected. According to the POCP comparison, P. yedoensis, G. biloba, Z. serrata and C. retusus were selected as roadside tree species, P. densiflora and C. obtusa as forest species, and A. palmatum, C. japonica, and Q. myrsinaefolia were deemed suitable for park species. However, in the case of P. occidentalis, Quercus, and M. glyptostroboides, the emission rates of BVOCs were found to be high. Despite this, these tree species were found to display excellent CO2 absorption and carbon storage. The concentration of NOx in the city center is likely to decrease due to the current trend of transitioning to eco-friendly cars worldwide, resulting in less cars that rely on fossil fuels. Therefore, in the current climate where NOx emissions are still high, planting tree species with a low BVOCs emission rate would be an optimal approach. On the other hand, if the NOx concentration in the city is found to be very low due to changes in automobile fuel use, planting tree species with excellent BVOCs emission capacity and CO2 absorption would be ideal.

가는잎향유[Elsholtzia angustifolia (Loes.) Kitag.]는 화형 이 아름답고, 정유 특유의 향기가 좋아서 분화용 및 지피용 관 상식물로 수요가 증가하고 있고, 전초에는 약효가 있다고 알 려져 있다. 본 연구는 가는잎향유의 육묘에 미치는 플러그 트 레이 셀 사이즈, 파종립수, 차광정도, 추비농도 등의 영향을 구명하기 위하여 수행되었다. 연구결과, 플러그 트레이 셀 사 이즈는 용량이 증가할수록 유묘의 초장, 엽수, 마디수, 근장, 지상부 생체중이 유의적으로 증가하였다. 파종 립수는 2립 파 종 시 가장 효율적이었고, 파종량이 증가할수록 생육이 감소 하였다. 차광정도가 높아질수록 초장은 증가하였고, 경직경, 엽수, 마디수는 55% 차광에서 가장 우수하였다. 추비 처리 시 공시비료 1000배 처리구에서 생육이 가장 양호하였다. 따라 서 가는잎향유의 육묘 시 162셀 트레이에 원예상토를 채운 다음 셀 당 2립 파종한 후 55% 차광막이 설치된 육묘상에서 공시비료 1000배로 엽면시비하는 것이 가장 효과적인 것으로 생각된다.

본 연구는 딸기의 삽목 육묘 시 묘소질을 향상시키고 품질을 증진시키기 위한 지베렐린 효과를 검증하기 위해 수행되었다. 품종은 ‘설향’을 대상으로 하였고, 삽목 시 삽수의 기부를 30, 60분간 GA3 50, 100, 150mg·L-1에 침지 처리하고 증류수 침 지를 대조구로 두었다. 정식 시 묘소질 조사 결과 엽수와 SPAD 값은 지베렐린 침지시간이 길수록 증가하였고, 초장, 엽병장, 엽장, 엽폭, 엽면적은 침지시간과 농도 간의 상호작용에 따라 유의하게 값이 변하였다. 관부직경은 같은 농도라 할지라도 침지시간에 따른 차이가 나타났으며 30분, 100mg·L-1 처리를 제외하고 모두 직경이 8.0mm 이상으로 우량한 묘가 생성되 었으며, T/R률은 30분, 50mg·L-1 처리에서 유의하게 작아 식 물체 활력이 가장 우수했다. 양자수율은 농도가 150mg·L-1일 때 저조하였고, 지베렐린 처리 농도가 높을수록 양자수율이 감소하는 경향을 나타냈다. NPQ는 대조구 대비 30분, 150mg·L-1 처리에서 유의하게 작아 묘 스트레스 감소에 효과 가 있었다. 항산화물 함량은 30분, 50mg·L-1 처리와 60분, 150mg·L-1 처리에서 높게 나타났고, 정식 후 생육조사 결과 화아분화 정도에 미치는 지베렐린의 부정적 영향은 없었다. 따라서, ‘설향’ 딸기의 삽목 육묘 시 지베렐린 처리는 정식묘 양성에 효과가 있는 것을 확인할 수 있었으며, 이때 대조구 대 비 생육 증진 및 품질 향상을 위해서는 삽수 기부를 50mg·L-1 의 지베렐린에 30분 침지처리하는 것이 보다 적정한 것으로 판단되었다.

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.

Particulate matter is known to have adverse effects on health, making it crucial to accurately gauge its concentration levels. While the recent advent of low-cost air sensors has enabled real-time measurement of particulate matter, discrepancies in concentrations can arise depending on the sensor used, the measuring environment, and the manufacturer. In light of this, we aimed to propose a method to calibrate measurements between low-cost air sensor devices. In our study, we introduced decision tree techniques, commonly used in machine learning for classification and regression problems, to categorize particulate matter concentration intervals. For each interval, both univariate and multivariate multiple linear regression analyses were conducted to derive calibration equations. The concentrations of PM10 and PM2.5 measured indoors and outdoors with two types of LCS equipment and the GRIMM 11-A device were compared and analyzed, confirming the necessity for distinguishing between indoor and outdoor spaces and categorizing concentration intervals. Furthermore, the decision tree calibration method showed greater accuracy than traditional methods. On the other hand, during univariate regression analysis, the proportion exceeding a PM2.5/PM10 ratio of 1 was significantly high. However, using multivariate regression analysis, the exceedance rate decreased to 79.1% for IAQ-C7 and 89.3% for PMM-130, demonstrating that calibration through multivariate regression analysis considering both PM10 and PM2.5 is more effective. The results of this study are expected to contribute to the accurate calibration of particulate matter measurements and have showcased the potential for scientifically and rationally calibrating data using machine learning.

Industrial complex areas are an important factor that contributes to economic development. However, these areas also produce a significant amount of noxious air pollutants. In particular, PM10 emitted from industrial complex areas can lead to detrimental effects on human health. This study was conducted to survey environmental conditions and measure the concentration of PM10 in indoor and outdoor living spaces in Yeosu and Gwangyang. In Yeosu, the level of PM10 concentration in indoor living spaces was measured at 49.38 μg/m3, while the outdoor level was measured at 43.60 μg/m3. In Gwangyang, the PM10 concentration in indoor living spaces was measured at 20.08 μg/m3 while the outdoor measurement came to 18.14 μg/m3. When analyzing the percentage of those who were highly concerned with environmental pollution among a survey group of 200 people, Yeosu City had a rate of 76.5%, while Gwangyang City had a comparable rate of 73%. When looking at the time-activity patterns of residents in both locations, Yeosu residents spend more than 80.0% of their time inside their living spaces, while Gwangyang residents spend more than 70.0% of time inside their living spaces. These high rates are largely due to the fact that most of the residents of these areas are elderly. In both Yeosu and Gwangyang, it was found that 40% of residents use TV and radio rather than newspapers or handouts to obtain information about environmental pollution problems in their area.

수인성 질산 노출에 대한 향어의 독성 영향을 확인하기 위해 96시간 동안 0, 4, 20, 100, 500 및 2,500 mg NO3 -/L의 수인성 질산에 노출을 실시하였다. 질산 96시간 급성 노출에 의한 향 어의 반수치사농도(LC50)는 1,433.54 mg NO3 -/L로 나타났다. 혈액학적 성상을 통해 수인성 질 산 노출이 향어에게 미치는 생리학적 변화를 평가하였으며, RBC count는 유의적인 감소를 나 타내었다(p < 0.05). 혈장 무기성분을 통해 수인성 질산 노출에 따른 향어의 이온 조절 능력 변화를 평가하였으며, 혈장 무기성분에서 calcium과 magnesium은 유의적으로 감소하였다(p < 0.05). 혈장 유기성분을 통해 수인성 질산 노출로 인한 향어의 건강도와 스트레스 상태를 평 가하였으며, 혈장 유기성분인 glucose는 유의적인 증가를 나타내었다(p < 0.05). 혈장 효소성분 을 통해 수인성 질산 노출로 인한 간 손상도 및 효소 활성의 변화를 평가하였으며, 혈장 효소 성분인 AST, ALT 및 ALP는 높은 수준의 수인성 질산 노출에서 유의적으로 감소하였다(p < 0.05). 본 연구의 결과는 C. carpio nudus에 대한 수인성 질산 노출이 생존율, 혈액학적 성상 및 혈장성분에 독성으로 영향을 미칠 수 있음을 의미한다.

산오이풀(Sanguisorba hakusanensis)은 한국의 자생식물 이며 정원소재로써 가치가 있지만, 생육 및 생리적 특성 및 정 원 적응 여부에 대하여 알려진 정보가 많지 않아 이용에 어려 움을 겪고 있다. 본 연구에서는 자생식물인 산오이풀의 관수 주기 및 NaCl 농도에 따른 생장, Fv/Fm, NPQ, 성분 변화, 무기성분 변화를 조사하여 내건 및 내염성 보유 여부, 생육 한 계 범위, 스트레스 환경에서 생육을 유지하기 위한 반응을 파 악하고자 했다. 실험 결과 NaCl 무처리구의 관수주기에 따른 성분 분석에서 엽록소 함량의 감소를 제외하고 유의한 차이가 나타나지 않았으나 이는 토양수분함량이 건조 스트레스를 유 발할 정도로 감소하지 않았기 때문으로 보인다. 염 처리에서 는 2주 이후 급격한 스트레스 반응이 나타났고 3주차부터 고 사하기 시작하여 6주차에 모든 개체가 최종 고사했다. 이러한 결과는 2주까지 염 스트레스에 의해 유발되는 2가지 스트레 스 중 초기에 나타나는 삼투 스트레스에는 저항하였으나 이후 나타나는 NPQ의 감소 등 이온 스트레스에 의해 유발된 광합 성 기구 붕괴로 인해 정상적인 생육을 유지할 수 없었기 때문 에 나타난 것으로 보인다. 그러나 무기이온 분석은 이온 스트 레스에 저항하기 위한 메커니즘의 존재 가능성을 시사하였다. 상대적으로 염 농도가 낮을 때에는 세포내 Ca2+ 및 K+ 수준이 높았는데, 이는 Ca2+ 수준이 높아짐에 따라 Na+를 세포 밖으 로 방출시키는 단백질, Na+를 K+와 함께 수송하는 단백질이 기능하여 Na+축적을 지연시키는 반응이 있었음을 시사한다. 그러나 NaCl을 고농도로 처리했을 때는 이러한 반응이 관찰 되지 않았다. 따라서 산오이풀은 염 스트레스에 의해 야기되 는 삼투 스트레스에 강한 저항성을 가지고 있고 이온 독성을 줄이기 위한 메커니즘으로 Na+ 세포내 축적을 지연시키는 것으로 보이지만, 심한 염 스트레스를 받았을 때 나타나는 급격 한 반응에서 이러한 메커니즘이 기능하지 못하고 이온독성에 매우 취약한 것으로 여겨진다. 본 연구를 통해 자생식물인 산 오이풀의 활용을 늘리는 데 기초적인 자료를 제공할 수 있을 것으로 생각된다.

제충국(Tanacetum cineariaiaefolium), 데리스(Derris elliptica), 고삼(Sophora flavescens) 추출물은 다양한 해충을 방제하는데 사용되고 있다. 하지만, 국내에서 판매되고 있는 식물추춞물 자재는 유효성분의 표기가 없고, 살충농도와 살충시간에 대한 자료가 전무한 상황이다. 본 연구에서는 상 용화된 주요 식물추출물의 살충유효성분의 농도를 결정하고 복숭아혹진딧물에 대해 살충농도와 살충시간을 측정하였다. 식물추출물의 살충활성성분 인 pyrethrins, rotenone, matrine과 oxymatrine의 농도는 액체 크로마토그래피에서 표준물질을 활용하여 질량분석을 통해 측정하였다. 식물추출 물을 농도별로 희석하여 복숭아혹진딧물에 살포하여 살충력을 측정하였다. 표준화합물과 비교한 후 질량분석 및 결정했습니다. Myzus persicae에 대 한 lethal concentation과 lethal time을 조사했다. 살포 후 48시간 후 치사 농도(LC50)는 pyrethrins (20.4 ppm), roteone (34.1 ppm), matrine (29.6 ppm)였고, 100 ppm 살포한 LT50은 pyrethrins (13.4시간), rotenone (15.1시간), matrine (14.4시간)로 측정되었다. Kaplan-Meier 생존분 석 결과, 100 ppm에서 세 가지 식물 추출물의 LT50은 대조구인 화학 살충제인 Sulfoxaflor를 살포 처리구보다 유의하게 빨랐습니다. 본 결과는 복숭 아혹진딧물 방제를 위해 식물추출물의 제형화에 단일 또는 혼합 제제를 개발하는데 기준 살충농도와 살충시간을 제고하는데 의미가 있다.

본 연구는 국내에서 실내 관상용으로 많이 활용되는 스킨답 서스의 실내재배 시 적정 인공광원, 수경재배 전기전도도 농 도 및 용토를 선발하기 위하여 수행하였다. 실내재배 시 인공 광원은 형광등, 적청 LED, 백색 LED로 처리하였다. 수경재배 시 양액 농도는 EC 1.2, 1.6, 2.0ds·m-1 수준으로 하였고, 재 배용토는 제올라이트, 코코피트, 펄라이트, 황토볼 4가지로 달리하였다. 스킨답서스의 실내 재배 시 줄기 길이는 형광등 과 적청 LED 처리보다 백색 LED 처리에서 길어졌다. 잎의 크기는 적청 LED 처리에서 형광등과 백색 LED 처리보다 커 지는 경향이었다. 엽록소 지수값은 백색 LED>적청 LED>형광 등 순으로 높았다. 수경재배 시 스킨답서스의 줄기길이는 EC 농도가 높아질수록 길어지는 경향이었고, 용토별로 비교하면 제올라이트와 코코피트에서 높은 경향이었다. 엽록소 지수값 도 EC 농도와 비례하여 높아졌고, 용토별로는 제올라이트와 코코피트에서 높았다. 스킨답서스의 생체중도 EC 농도가 높 을수록 높았고, 제올라이트와 코코피트에 높은 경향이었다. 상기 결과들을 종합할 때, 스킨답서스의 NFT를 이용한 실내 재배 시 적정 인공광원으로는 백색 LED를, 수경재배 양액의 농도는 EC 1.6∼2.0ds·m-1를, 그리고 NFT 용토는 제올라이 트나 코코피트가 적합하다는 것을 알 수 있었다.

This study investigates the influence of particulate matter concentrations on the incidence of asthma, focusing on the delayed onset of symptoms and subsequent medical consultations. Analysis incorporates a four-day lag from the initiation of fine dust exposure and compares asthma patterns before and after the World Health Organization's (WHO) classification of fine dust as a Group 1 carcinogen in November 2013. Utilizing daily PM10 data and asthma-related medical visit counts in Seoul from 2008 to 2016, the study additionally incorporates Google search frequencies and newspaper article counts on fine dust to assess public awareness. Results reveal a surge in search frequencies and article publications after WHO announcement, indicating heightened public interest. To standardize the long-term asthma occurrence trend, the daily asthma patient numbers are ratio-adjusted based on annual averages. The analysis uncovers an increase in asthma medical visits 2 to 3 days after fine dust events. Additionally, greater public awareness of fine dust hazards correlates with a significant reduction in asthma occurrence after such events, even within 'normal' fine dust concentrations. Notably, behavioral changes, like limiting outdoor activities, contribute to this decrease. This study highlights the importance of analyzing accumulated medical data over an extended period to identify general public behavioral patterns, deviating from conventional survey methods in social sciences. Future research aims to extend data collection beyond 2016, exploring recent trends and considering the potential impact of decreased fine dust awareness amid the COVID-19 pandemic.

Conventional aquaculture faces declining productivity, shifting to recirculating aquaculture system (RAS), known for minimizing water usage and maintaining consistent water temperatures for year-round fish growth. Rainbow trout (Oncorhynchus mykiss), a globally important cold-water species and the third most farmed fish in inland waters of Korea, valued for its fecundity and rapid growth. Dissolved oxygen, an important environmental factor affecting fish production and economics, highlights the need for smart aquaculture practices. Since 2018, the rise of intelligent aquaculture platforms, incorporating information and communications technology (ICT), emphasizes the essential role of RAS implementation. This eight-week study aimed to determine the optimal dissolved oxygen concentration for rainbow trout in RAS, utilizing a device for continuous monitoring, control and record. Dissolved oxygen concentrations were set at 5-6 mg/L, 9-10 mg/L, 14-15 mg/L and 17-18 mg/L. The growth rate significantly decreased at 5-6 mg/L, with no significant differences in other experimental groups. In hematological analysis, growth hormone (GH) was significantly highest at 5-6 mg/L, followed by 9-10 mg/L while Insulin-like growth factor-1 (IGF-1) was significantly lowest at 5-6 mg/L. In conclusion, the optimal dissolved oxygen concentration for rainbow trout in RAS is approximately 9-10 mg/L. Higher concentrations do not contribute to further growth or profitability.

This study was aimed to determine the changes in CO2 concentration according to the temperatures of daytime and nighttime in the CO2 supplemental greenhouse, and to compare calculated supplementary CO2 concentration during winter and spring cultivation seasons. CO2 concentrations in experimental greenhouses were analyzed by selecting representative days with different average temperatures due to differences in integrated solar radiation at the growth stage of leaf area index (LAI) 2.0 during the winter season of 2022 and 2023 years. The CO2 concentration was 459, 299, 275, and 239 μmol·mol-1, respectively at 1, 2, 3, and 4 p.m. after the CO2 supplementary time (10:00-13:00) under the higher temperature (HT, > 18°C daytime temp. avg. 31.7, 26.8, 23.8, and 22.4°C, respectively), while it was 500, 368, 366, 364 μmol·mol-1, respectively under the lower temperature (LT, < 18°C daytime temp. avg. 22.0, 18.9, 15.0, and 13.7°C, respectively), indicating the CO2 reduction was significantly higher in the HT than that of LT. During the nighttime, the concentration of CO2 gradually increased from 6 p.m. (346 μmol·mol-1) to 3 a.m. (454 μmol·mol-1) in the HT with a rate of 11 μmol·mol-1 per hour (240 tomatoes, leaf area 330m2), while the increase was very lesser under the LT. During the spring season, the CO2 concentration measured just before the start of CO2 fertilization (7:30 a.m.) in the CO2 enrichment greenhouse was 3-4 times higher in the HT (>15°C nighttime temperature avg.) than that of LT (< 15°C nighttime temperature avg.), and the calculated amount of CO2 fertilization on the day was also lower in HT. All the integrated results indicate that CO2 concentrations during the nighttime varies depending on the temperature, and the increased CO2 is a major source of CO2 for photosynthesis after sunrise, and it is necessary to develop a model formula for CO2 supplement considering the nighttime CO2 concentration.

Ultra-violet (UV) light is one of abiotic stress factors and causes oxidative stress in plants, but a suitable level of UV radiation can be used to enhance the phytochemical content of plants. The accumulation of antioxidant phenolic compounds in UV-exposed plants may vary depending on the conditions of plant (species, cultivar, age, etc.) and UV (wavelength, energy, irradiation period, etc.). To date, however, little research has been conducted on how leaf thickness affects the pattern of phytochemical accumulation. In this study, we conducted an experiment to find out how the antioxidant phenolic content of kale (Brassica oleracea var. acephala) leaves with different thicknesses react to UV-A light. Kale seedlings were grown in a controlled growth chamber for four weeks under the following conditions: 20°C temperature, 60% relative humidity, 12-hour photoperiod, light source (fluorescent lamp), and photosynthetic photon flux density of 121±10 μmol m-2 s-1. The kale plants were then transferred to two chambers with different CO2 concentrations (382±3.2 and 1,027±11.7 μmol mol-1), and grown for 10 days. After then, each group of kale plants were subjected to UV-A LED (275+285 nm at peak wavelength) light of 25.4 W m-2 for 5 days. As a result, when kale plants with thickened leaves from treatment with high CO2 were exposed to UV-A, they had lower UV sensitivity than thinner leaves. The Fv/Fm (maximum quantum yield on photosystem II) in the leaves of kale exposed to UV-A in a low-concentration CO2 environment decreased abruptly and significantly immediately after UV treatment, but not in kale leaves exposed to UV-A in a high-concentration CO2 environment. The accumulation pattern of total phenolic content, antioxidant capacity and individual phenolic compounds varied according to leaf thickness. In conclusion, this experiment suggests that the UV intensity should vary based on the leaf thickness (age etc.) during UV treatment for phytochemical enhancement.

PURPOSES : In this study, a model was developed to estimate the concentrations of particulate matter (PM2.5 and PM10) in expressway tunnel sections. METHODS : A statistical model was constructed by collecting data on particulate matter (PM2.5 and PM10), weather, environment, and traffic volume in the tunnel section. The model was developed after accurately analyzing the factors influencing the PM concentration. RESULTS : A machine learning-based PM concentration estimation model was developed. Three models, namely linear regression, convolutional neural network, and random forest models, were compared, and the random forest model was proposed as the best model. CONCLUSIONS : The evaluation revealed that the random forest model displayed the least error in the concentration estimation model for (PM2.5 and PM10) in all tunnel section cases. In addition, a practical application plan for the model developed in this study is proposed.

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier’s abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

In this study, we analyzed the changes in concentrations of volatile fatty acids (VFA), phenols, and indoles, as well as odor contribution in pig slurry. The pig slurry was stored for approximately two months after the manure excretion of pigs which had been fed 3% level of peat moss additive. The investigation was carried out through lab-scale experiments simulating slurry pit conditions within pig house. Throughout the storage period, the concentration of VFA exhibited a tendency to be 11%-32% higher in the pig manure treated with peat moss as compared to the control group. From a concentration perspective, phenol and acetic acid accounted for the majority of the total odor compounds produced during the pig slurry storage period. However, their significance diminished when the concentration of odoros compounds are converted into odor activity value and odor contribution. Despite the odor reduction effect of the ammonia (NH3) adsorption by peat moss, if it cannot effectively reduce the high odor-contributing compounds such as indoles and p-cresol, the sole use of peat moss may not be considered an effective means of mitigating odors produced by pig slurry. According to this study, indoles, p-cresol, skatole, and valeric acid were consistently revealed as major odor-contributing substances during the two-month storage of pig slurry. Therefore, a comprehensive odor mitigation methodology should be proposed, taking into consideration the odor generation characteristics (including temporal concentration and odor contribution) of pig slurry-derived odors during storage.

본 연구에서는 복숭아혹진딧물의 포식 기생자인 콜레마니진디벌의 기능반응을 조사하였다. 이산화탄소 농도별(400, 600, 1000ppm) 복 숭아혹진딧물 밀도를 달리하여(2, 4, 8, 16, 32, 64, 128마리) 콜레마니진디벌 한 마리를 24시간 동안 노출시켰다. 각 이산화탄소 처리에서 콜레 마니진디벌은 제 3 유형의 기능반응을 보였다. 600 ppm (0.015 day)과 1000 ppm (0.014 day)에서 추정된 처리시간은 400 ppm에서 추정된 결 과(0.017 day)보다 짧았다. 이산화탄소 농도별 복숭아혹진딧물 기생률은 유사한 특징을 나타내었다. 가장 높은 기생률은 400, 600, 1000 ppm 에서 복숭아혹진딧물 16, 32, 32마리에 대해 0.57, 0.61, 0.70이었다. 이산화탄소 농도 증가는 콜레마니진디벌의 기능반응에서 공격율에는 영향 을 주지 않았지만 처리시간에는 영향을 주었다.