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- P-ISSN2765-2203
- E-ISSN2765-2211
- KCI Candidate
Abstract
This study aimed to determine the applicability of drones and air quality sensors in environmental monitoring of air pollutant emissions by developing and testing two new methods. The first method used orthoimagery for precise monitoring of pollutant-emitting facilities. The second method used atmospheric sensors for monitoring air pollutants in emissions. Results showed that ground sample distance could be established within 5 cm during the creation of orthoimagery for monitoring emissions, which allowed for detailed examination of facilities with naked eyes. For air quality monitoring, drones were flown on a fixed course and measured the air quality in point units, thus enabling mapping of air quality through spatial analysis. Sensors that could measure various substances were used during this process. Data on particulate matter were compared with data from the National Air Pollution Measurement Network to determine its future potential to leverage. However, technical development and applications for environmental monitoring of pollution-emitting facilities are still in their early stages. They could be limited by meteorological conditions and sensitivity of the sensor technology. This research is expected to provide guidelines for environmental monitoring of pollutant-emitting facilities using drones.
Abstract
Species distribution models are a useful tool for predicting future distribution and establishing a preemptive response of invasive species. However, few studies considered the possibility of habitat for the aquatic organism and the number of target sites was relatively small compared to the area. Environmental DNA (eDNA) is the emerging tool as the methodology obtaining the bulk of species presence data with high detectability. Thus, this study applied eDNA survey results of Micropterus salmoides and Lepomis macrochirus to species distribution modeling by seasons in the Anyang stream network. Maximum Entropy (MaxEnt) model evaluated that both species extended potential distribution area in October compared to July from 89.1% (12,110,675 m2) to 99.3% (13,625,525 m2) for M. salmoides and 76.6% (10,407,350 m2) to 100% (13,724,225 m2) for L. macrochirus. The prediction value by streams was varied according to species and seasons. Also, models elucidate the significant environmental variables which affect the distribution by seasons and species. Our results identified the potential of eDNA methodology as a way to retrieve species data effectively and use data for building a model.
Abstract
Methods for detecting the presence of genetically modified (GM) crops are evolving to comply with legislation and to enhance monitoring by biotechnology companies and regulators. In order to cover a broad range of detection methods for a new GM crop, conventional multiplex PCR methods are required. Based on the genetic information on three GM alfalfa varieties (J101, J163, and KK179), which were recently approved in South Korea, we developed a fast, reliable, and highly specific multiplex polymerase chain reaction (PCR) method with basic PCR equipment and inexpensive reagents. To validate and verify the newly developed multiplex PCR method, we applied a limit of detection assay and random reference material analysis. We also monitored the unintentional environmental release of GM alfalfa in South Korea by performing the multiplex PCR analysis with 91 feral alfalfa specimens collected from 2000 to 2018. Our methodology is a sensitive, simple, quick, and inexpensive tool for detecting and identifying three GM alfalfa varieties.
Abstract
We conducted a study to investigate the characteristics of the carbon cycle of two streams (located in Shiga Prefecture, Japan), having similar size, namely, the Adokawa stream (length: 52 km, area: 305 km2, watershed population: 8,000) and the Yasukawa stream (length: 62 km, area: 380 km2, watershed population: 120,000), but with different degree of human activity. Samples were collected from these two streams at 14 (Adokawa stream) and 23 (Yasukawa stream) stations in the flowing direction. The dissolved inorganic carbon (DIC) concentration and the stable carbon isotope ratio of DIC (δ13C-DIC) were measured in addition to the watershed features and the chemical variables of the stream water. The δ13C-DIC (-9.50 ± 2.54‰), DIC concentration (249 ± 76 μM), and electric conductivity (52 ±13 μS/cm) in Adokawa stream showed small variations from upstream to downstream. However, the δ13C-DIC (-8.68 ± 2.3‰) upstream of Yasukawa stream was similar to that of Adokawa stream and decreased downstream (-12.13 ± 0.43‰). DIC concentration (upstream: 272 ± 89 μM, downstream: 690 ± 37 μM) and electric conductivity (upstream: 69 ± 17 μS/cm, downstream: 193 ± 37 μS/cm) were higher downstream than upstream of Yasukawa stream. The DIC concentration of Yasukawa stream was significantly correlated with watershed environmental variables, such as, watershed population density (r = 0.8581, p<0.0001, n = 23), and forest area percentage of the watershed (r = -0.9188, p<0.0001, n = 23). δ13C-DIC showed significant negative correlation with the DIC concentration (r = -0.7734, p<0.0001, n = 23), electric conductivity (r = -0.5396, p = 0.0079, n = 23), and watershed population density (r = -0.6836, p = 0.0003, n = 23). Our approach using a stable carbon isotope ratio suggests that DIC concentration and δ13C-DIC could be used as indicators for monitoring the health of stream ecosystems with different watershed characteristics.
