본 연구의 목적은 2023년 4월 충청남도 홍성군 대형산불피해지를 대상으로 산불로 인한 온실가스 배출량을 산정하여 국가 온실가스 인벤토리 고도화에 기여하고자 한다. 산불로 인한 온실가스 배출량은 2006년 IPCC 가이드라인에 따라 산정하였으며, 산정 인자인 연소면적은 Sentinel-2A 위성영상 기반의 differenced Normalized Burn Ratio (dNBR)을 활용하여 제작한 산불피해등급도를 이용하였고 지표층 및 수관층의 연료량 및 연소효율은 현장자료를 바탕으로 추정하였다. dNBR을 활용하여 제작한 산불피해등급도를 기반으로 산정한 온실가스 배출량은 약 19,336.9톤으로, 국립산림과학원 자료를 이용한 결과보다 약 4.0% 증가한 것으로 나타났다. 본 연구는 현장자료를 반영하여 산불로 인한 온실가스 배출량을 보다 정밀하게 산정한 데 의의가 있다. 향후에는 국내 생태계 특성을 반영한 각 요소별 고유 지표의 도입이 요구된다.

Accurate estimation of vehicle exhaust emissions at urban intersections is essential to assess environmental impacts and support sustainable traffic management. Traditional emission models often rely on aggregated traffic volumes or measures of average speed that fail to capture the dynamic behaviors of vehicles such as acceleration, deceleration, and idling. This study presents a methodology that leverages video data from smart intersections to estimate vehicle emissions at microscale and in real time. Using a CenterNet-based object detection and tracking framework, vehicle trajectories, speeds, and classifications were extracted with high precision. A structured preprocessing pipeline was applied to correct noise, missing frames, and classification inconsistencies to ensure reliable time-series inputs. Subsequently, a lightweight emission model integrating vehicle-specific coefficients was employed to estimate major pollutants including CO and NOx at a framelevel resolution. The proposed algorithm was validated using real-world video data from a smart intersection in Hwaseong, Korea, and the results indicated significant improvements in accuracy compared to conventional approaches based on average speed. In particular, the model reflected variations in emissions effectively under congested conditions and thus captured the elevated impact of frequent stopand- go patterns. Beyond technical performance, these results demonstrate that traffic video data, which have traditionally been limited to flow monitoring and safety analysis, can be extended to practical environmental evaluation. The proposed algorithm offers a scalable and cost-effective tool for urban air quality management, which enables policymakers and practitioners to link traffic operations with emission outcomes in a quantifiable manner.

The textile tentering process generates exhaust gases characterized by elevated temperature and humidity, accompanied by complex odors, fine particulate matter, and visible white smoke, all of which frequently contribute to public grievances and environmental concerns. This study evaluated a field-installed, multi-stage emissioncontrol system consisting of a scrubber, a wet electrostatic precipitator (WEFC), and a heat exchanger, with emphasis on the effect of routine plate cleaning over a ht ree-month operation. Real-time monitoring at 5-minute intervals measured temperature, humidity, total volatile organic compounds (TVOCs), particulate matter (PM2.5, PM10, TSP), and odor intensity. Odor activity values (OAVs) and odor contributions (OC) were determined from samples collected according to the Korean Odor Measurement Standard. The emission-control system reduced exhaust temperature from 150oC to below 50oC while maintaining stack outlet temperature differences within 5oC, thereby suppressing visible white smoke. The multistage system achieved mean removal efficiencies of 88.6±5.0% for TVOCs and 96.2±6.5% for PM10, with a gravimetric PM10 removal of 99.4%. Weekly cleaning of the electrostatic plates constrained day-to-day variability in odor and PM levels within ±10%, significantly lowering the frequency of white-smoke episodes. Isovaleraldehyde and acetaldehyde accounted for >90% of total OAVs, indicating the need for supplementary treatment targeting aldehydes. These results provide quantitative evidence to guide maintenance scheduling and emission-control policy for the textile processing industry.

The IMO’S 72nd MEPC meeting proposed the goal of reducing greenhouse gas emissions by up to 50% by 2050. Thus, various eco-friendly fuels are proposed as alternatives, but there are also various issues that need to be tackled, such as storage stability and supply system issues in a special environment a ship has. Therefore, in this study, the possibility of reducing greenhouse gases was analyzed by applying MGO as an alternative to boilers operated with HFO, a Bunker-C series. As a result, the exhaust gas temperature decreased by about 11.54% from 316.9℃ to 280.3℃, and the amount of oxygen content increased by about 0.38% from 6.27% to 6.65%. It can be seen that carbon monoxide can be reduced by about 45.28% by simply converting fuel from 45.29 ppm to 24.78 ppm, and carbon dioxide, which is a typical greenhouse gas, can be reduced by about 0.49% from HFO by 11.08% to MGO by 10.59%. This means that some greenhouse gas reduction is possible only by shifting between ship fuels that satisfy ISO-8217, but since there are limitations to achieving strong carbon neutrality proposed by IMO, it will be necessary to actively utilize the use of various alternative fuels in the future.

Gas sensors play a crucial role in monitoring harmful gas concentrations and air quality in real-time, ensuring safety and protecting health in both environmental and industrial settings. Additionally, they are essential in various applications for energy efficiency and environmental protection. As the demand for hydrogen refueling stations and hydrogen fuel cell vehicles increases with the growth of the hydrogen economy, accurate gas concentration measurement technology is increasingly necessary given hydrogen's wide explosion range. To ensure safety and efficiency, gas sensors must accurately detect a wide range of gas concentrations in real-world environments. This study presents two types of gas sensors with high sensitivity, stability, low cost, fast response time, and compact design. These sensors, based on volume and pressure analysis principles, can measure gas filling amounts, solubility, diffusivity, and the leakage of hydrogen, helium, nitrogen, and argon gases in high-density polyethylene charged under high-pressure conditions. Performance evaluation shows that the two sensors have a stability of 0.2 %, a resolution of 0.12 wt･ppm, and can measure gas concentrations ranging from 0.1 wt･ppm to 1400 wt･ ppm within one second. Moreover, the sensitivity, resolution, and measurement range of the sensors are adjustable. Measurements obtained from these sensors of gas filling amounts and the diffusivity of four gases showed consistent results within uncertainty limits. This system, capable of real-time gas detection and characterization, is applicable to hydrogen infrastructure facilities and is expected to contribute to the establishment of a safe hydrogen society in the future.