• Title/Summary/Keyword: negative emission

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Analysis of Surface Urban Heat Island and Land Surface Temperature Using Deep Learning Based Local Climate Zone Classification: A Case Study of Suwon and Daegu, Korea (딥러닝 기반 Local Climate Zone 분류체계를 이용한 지표면온도와 도시열섬 분석: 수원시와 대구광역시를 대상으로)

  • Lee, Yeonsu;Lee, Siwoo;Im, Jungho;Yoo, Cheolhee
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1447-1460
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    • 2021
  • Urbanization increases the amount of impervious surface and artificial heat emission, resulting in urban heat island (UHI) effect. Local climate zones (LCZ) are a classification scheme for urban areas considering urban land cover characteristics and the geometry and structure of buildings, which can be used for analyzing urban heat island effect in detail. This study aimed to examine the UHI effect by urban structure in Suwon and Daegu using the LCZ scheme. First, the LCZ maps were generated using Landsat 8 images and convolutional neural network (CNN) deep learning over the two cities. Then, Surface UHI (SUHI), which indicates the land surface temperature (LST) difference between urban and rural areas, was analyzed by LCZ class. The results showed that the overall accuracies of the CNN models for LCZ classification were relatively high 87.9% and 81.7% for Suwon and Daegu, respectively. In general, Daegu had higher LST for all LCZ classes than Suwon. For both cities, LST tended to increase with increasing building density with relatively low building height. For both cities, the intensity of SUHI was very high in summer regardless of LCZ classes and was also relatively high except for a few classes in spring and fall. In winter the SUHI intensity was low, resulting in negative values for many LCZ classes. This implies that UHI is very strong in summer, and some urban areas often are colder than rural areas in winter. The research findings demonstrated the applicability of the LCZ data for SUHI analysis and can provide a basis for establishing timely strategies to respond urban on-going climate change over urban areas.

Analysis of the Long-Range Transport Contribution to PM10 in Korea Based on the Variations of Anthropogenic Emissions in East Asia using WRF-Chem (WRF-Chem 모델을 활용한 동아시아의 인위적 배출량 변동에 따른 한국 미세 먼지 장거리 수송 기여도 분석)

  • Lee, Hyae-Jin;Cho, Jae-Hee
    • Journal of the Korean earth science society
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    • v.43 no.2
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    • pp.283-302
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    • 2022
  • Despite the nationwide COVID-19 lockdown in China since January 23, 2020, haze days with high PM10 levels of 88-98 ㎍ m-3 occurred on February 1 and 2, 2020. During these haze days, the East Asian region was affected by a warm and stagnant air mass with positive air temperature anomalies and negative zonal wind anomalies at 850 hPa. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to analyze the variation of regional PM10 aerosol transport in Korea due to decreased anthropogenic emissions in East Asia. The base experiment (BASE), which applies the basic anthropogenic emissions in the WRF-Chem model, and the control experiment (CTL) applied by reducing the anthropogenic emission to 50%, were used to assess uncertainty with ground-based PM10 measurements in Korea. The index of agreement (IOA) for the CTL simulation was 0.71, which was higher than that of BASE (0.67). A statistical analysis of the results suggests that anthropogenic emissions were reduced during the COVID-19 lockdown period in China. Furthermore, BASE and CTL applied to zero-out anthropogenic emissions outside Korea (BASE_ZEOK and CTL_ZEOK) were used to analyze the variations of regional PM10 aerosol transport in Korea. Regional PM10 transport in CTL was reduced by only 10-20% compared to BASE. Synthetic weather variables may be another reason for the non-linear response to changes in the contribution of regional transport to PM10 in Korea with the reduction of anthropogenic emissions in East Asia. Although the regional transport contribution of other inorganic aerosols was high in CTL (80-90%), sulfate-nitrate-ammonium (SNA) aerosols showed lower contributions of 0-20%, 30-60%, and 30-60%, respectively. The SNA secondary aerosols, particularly nitrates, presumably declined as the Chinese lockdown induced traffic.

Ecotoxicity of Daphnia magna and Aliivibrio fischeri on Potentially Harmful Substances Emissionsfrom Battery Manufacturing Processes: Lithium, Nickel, and Sulfate (배터리 제조공정에서 배출되는 잠재 유해 물질에 대한 물벼룩과 발광박테리아의 생태독성: 리튬, 니켈, 황산염을 대상으로)

  • Inhye Roh;Kijune Sung
    • Journal of Environmental Impact Assessment
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    • v.32 no.2
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    • pp.123-133
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    • 2023
  • Wastewater generated in the secondary battery production process contains lithium and high-concentration sulfate. Recently, as demand as demand for high-Ni precursors with high-energy density has surged, nickel emission is also a concern. Lithium and sulfate are not included in the current water pollutant discharge standard, so if they are not properly processed and discharged, the negative effect on future environment may be great. Therefore, in this study, the ecotoxicity of lithium, nickel, and sulfate, which are potential contaminants that can be discharged from the secondary battery production process, was evaluated using water flea (Daphnia magna) and luminescent bacteria (Aliivibrio fischeri). As a result of the ecotoxicity test, 24-hour and 48-hour D. magna EC50 values of lithium were 18.2mg/L and 14.5mg/L, nickel EC50 values were 7.2mg/L and 5.4mg/L, and sulfate EC50 values were 4,605.5mg/L and 4,345.0mg/L, respectively. In the case of D. magna, it was found that there was a difference in ecotoxicity according to the contaminants and exposure time (24 hours, 48 hours). Comparing the EC50 of D. magna for lithium, nickel, and sulfate, the EC50 of nickel at 24h and 48h was 39.6-37.2% compared to lithium and 0.1-0.2% compared to sulfate, which was the most toxic among the three substances. The difference appeared to be at a similarlevelregardless of the exposure time. The EC50 of sulfate was 253.0-299.7% and 639.5-804.6%, respectively, compared to lithium and nickel, showing the least toxicity among the three substances. The 30-minute EC50 values of luminescent bacteria forlithium, nickel, and sulfate were 2,755.8mg/L, 7.4mg/L, and 66,047.3mg/L,respectively. Unlike nickel, it was confirmed that there was a difference in sensitivity between D. magna and A. fischeri bacteria to lithium and sulfate. Studies on the mixture toxicity of these substances are needed.

Characteristics of Satellite-Based CO/CO2, CO/NO2 Ratio in South Korea and China (한국과 중국의 도시별 위성기반 CO/CO2, CO/NO2 비율 특성)

  • Jieun Yu;Jaemin Kim;Jin Ah Jang;Jeong-Ah Yu;Seung-Yeon Kim;Yun Gon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.129-142
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    • 2023
  • This study analyzed the ratio of carbon monoxide (CO) and carbon dioxide (CO2), CO and nitrogen dioxide (NO2) for cities and regionsin Korea and China using column-averaged carbon dioxide dry-air mole fraction (XCO2) of the Orbiting Carbon Observatory-2/3, CO and NO2 vertical column density (named XCO, XNO2 in thisstudy) of TROPOspheric monitoring instrument from April 2018 to April 2022, and presented the relationship between socioeconomic indicators (population, number of vehicles, Gross Regional Domestic Product) and ratio, and differences in characteristics between Korea and China. First, CO2 and CO were analyzed after calculating ΔXCO2 and ΔXCO removing the background value and trend line due to the difference in atmospheric residence time of three gaseous substances (CO2, CO, and NO2). Comparing the three values by regions, ΔXCO and ΔXCO2 were relatively higher in China and XNO2 were higher in Korea and the ratio of both values (ΔXCO/ΔXCO2, ΔXCO/XNO2) was higher in China than in Korea. ΔXCO/ΔXCO2, ΔXCO/XNO2 and socioeconomic indicators have a positive correlation suggesting that the concentration of air pollutants and greenhouse gases is higher as the city is large and the economic activity is active. Regarding the differences in the ratio characteristics of Korea and China, the relationship between ΔXCO and ΔXCO2 showed a negative correlation in Korea and a positive correlation in China. When the relationship between ΔXCO and XNO2 was examined for summer and winter, the change of ΔXCO by season was not significant in Korea, whereasthe change of ΔXCO and XNO2 by season waslarge in China resulting in the relationship between two countries appeared differently. These results suggest that seasonal variability and national emission characteristics should be considered in the process of analyzing the ratio of greenhouse gases to air pollutants.

Development of Quantification Methods for the Myocardial Blood Flow Using Ensemble Independent Component Analysis for Dynamic $H_2^{15}O$ PET (동적 $H_2^{15}O$ PET에서 앙상블 독립성분분석법을 이용한 심근 혈류 정량화 방법 개발)

  • Lee, Byeong-Il;Lee, Jae-Sung;Lee, Dong-Soo;Kang, Won-Jun;Lee, Jong-Jin;Kim, Soo-Jin;Choi, Seung-Jin;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.38 no.6
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    • pp.486-491
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    • 2004
  • Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.