• Title/Summary/Keyword: $PM_{10}$ Forecasting

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A Study of the Effects of SST Deviations on Heavy Snowfall over the Yellow Sea (해수면 온도 변화가 서해상 강설에 미치는 영향 연구)

  • Jeong, Jaein;Park, Rokjin
    • Atmosphere
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    • v.23 no.2
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    • pp.161-169
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    • 2013
  • We examine the effects of the sea surface temperature (SST) distribution on heavy snowfall over the Yellow Sea using high-resolution SST products and WRF (Weather Research and Forecasting) model simulations in 30 December 2010. First, we evaluate the model by comparing the simulated and observed fresh snowfall over the Korean peninsula (Ho-Nam province). The comparison shows that the model reproduces the distributions and magnitudes of the observed snowfall. We then conduct sensitivity model simulations where SST perturbations by ${\pm}1.1^{\circ}C$ relative to baseline SST values (averaged SST for $5{\sim}15^{\circ}C$) are uniformly specified over the region of interest. Results show that ${\pm}1.1^{\circ}C$ SST perturbation simulations result in changes of air temperature by $+0.37/-0.38^{\circ}C$, and by ${\pm}0.31^{\circ}C$ hPa for sea level pressure, respectively, relative to the baseline simulation. Atmospheric responses to SST perturbations are found to be relatively linear. The changes in SST appear to perturb precipitation variability accounting for 10% of snow and graupel, and 18% of snowfall over the Yellow Sea and Ho- Nam province, respectively. We find that anomalies of air temperature, pressure, and hydrometeors due to SST perturbation propagate to the upper part of cloud top up to 500 hPa and show symmetric responses with respect to SST changes.

Impact of East Asian Summer Atmospheric Warming on PM2.5 Aerosols (동아시아 지역의 여름철 온난화가 PM2.5 에어로졸에 미치는 영향)

  • So-Jeong Kim;Jae-Hee Cho;Hak-Sung Kim
    • Journal of the Korean earth science society
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    • v.45 no.1
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    • pp.1-18
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    • 2024
  • This study analyzed the effect of warming on PM2.5 aerosol production in mid-latitude East Asia during June 2020 using PM2.5 aerosol anomalies, which were identified by incorporating meteorological and climate data into the Weather Research Forecasting model coupled with Chemistry (WRF-Chem) model. The decadal temperature change trend over a 30-year period (1991-2020) in East Asia showed that recent warming has been greater in summer than in winter. Summer warming in East Asia generated low and high pressure in the lower and upper troposphere, respectively, over China. The boundary between the lower tropospheric low and upper tropospheric high pressure sloped along the terrain from the Tibetan Plateau to Korea. The eastern China, Yellow Sea, and Korean regions experienced a convergence of warm and humid southwesterly airflows originating from the East China Sea with the development of a northwesterly Pacific high pressure. In June 2020, the highest temperatures were observed since 1973 in Korea. Meanwhile, enhanced warming in East Asia increased the production of PM2.5 aerosols that travelled long distances from eastern China to Korea. PM2.5 anomalies, which were derived solely by inputting meteorological and climatic data (1991-2020) into the WRF-Chem model and excluding emission variations, showed a positive distribution extending from eastern China to South Korea across the Yellow Sea as well as over the Pacific Northwest. Thus, the contribution of warming to PM2.5 aerosols in East Asia during June 2020 was more than 50%. In particular, PM2.5 aerosols were transported from eastern China to Korea through the Yellow Sea, where the warm and humid southwesterly airflows implied wet scavenging of sulfate but promoted nitrate production.

Analysis of PM2.5 Impact and Human Exposure from Worst-Case of Mt. Baekdu Volcanic Eruption (백두산 분화 Worst-case로 인한 우리나라 초미세먼지(PM2.5) 영향분석 및 노출평가)

  • Park, Jae Eun;Kim, Hyerim;Sunwoo, Young
    • Korean Journal of Remote Sensing
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    • v.36 no.5_4
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    • pp.1267-1276
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    • 2020
  • To quantitatively predict the impacts of large-scale volcanic eruptions of Mt. Baekdu on air quality and damage around the Korean Peninsula, a three-dimensional chemistry-transport modeling system (Weather Research & Forecasting - Sparse Matrix Operation Kernel Emission - Comunity Multi-scale Air Quality) was adopted. A worst-case meteorology scenario was selected to estimate the direct impact on Korea. This study applied the typical worst-case scenarios that are likely to cause significant damage to Korea among worst-case volcanic eruptions of Mt. Baekdu in the past decade (2005~2014) and assumed a massive VEI 4 volcanic eruption on May 16, 2012, to analyze the concentration of PM2.5 caused by the volcanic eruption. The effects of air quality in each region-cities, counties, boroughs-were estimated, and vulnerable areas were derived by conducting an exposure assessment reflecting vulnerable groups. Moreover, the effects of cities, counties, and boroughs were analyzed with a high-resolution scale (9 km × 9 km) to derive vulnerable areas within the regions. As a result of analyzing the typical worst-case volcanic eruptions of Mt. Baekdu, a discrepancy was shown in areas between high PM2.5 concentration, high population density, and where vulnerable groups are concentrated. From the result, PM2.5 peak concentration was about 24,547 ㎍/㎥, which is estimated to be a more serious situation than the eruption of Mt. St. Helensin 1980, which is known for 540 million tons of volcanic ash. Paju, Gimpo, Goyang, Ganghwa, Sancheong, Hadong showed to have a high PM2.5 concentration. Paju appeared to be the most vulnerable area from the exposure assessment. While areas estimated with a high concentration of air pollutants are important, it is also necessary to develop plans and measures considering densely populated areas or areas with high concentrations of susceptible population or vulnerable groups. Also, establishing measures for each vulnerable area by selecting high concentration areas within cities, counties, and boroughs rather than establishing uniform measures for all regions is needed. This study will provide the foundation for developing the standards for disaster declaration and preemptive response systems for volcanic eruptions.

Forecasting of Real Time Traffic Situation (실시간 교통상황 예보)

  • 홍유식;박종국
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.4
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    • pp.330-337
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    • 2000
  • This paper proposes a new concept of coordinating green this which controls 10 traffic intersection systems. For instance, if we have a baseballs game at 8 pm today, traffic volume toward the baseball game at 8 pm today, traffic volume toward the baseball game will be incr eased 1 hour or 1 hour 30 minutes before the baseball game. at that time we can not pred ict optimal green time Even though there have smart elctrosensitive traffic light system. Therefore, in this paper to improve average vehicle speed and reduce average vehicle waiting time, we created optimal green time using fuzzy rules and neural network. Computer simulation results proved reducing average vehicle waiting time proposed coordinating green time better than electro-sensitive traffic light system. Therefore, in this paper to improvevehicle speed and reduce average vehicle waiting time, we created optiual green time fuzzy rules and neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dosen't consider coordinating green time.

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Prediction and Analysis of PM2.5 Concentration in Seoul Using Ensemble-based Model (앙상블 기반 모델을 이용한 서울시 PM2.5 농도 예측 및 분석)

  • Ryu, Minji;Son, Sanghun;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1191-1205
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    • 2022
  • Particulate matter(PM) among air pollutants with complex and widespread causes is classified according to particle size. Among them, PM2.5 is very small in size and can cause diseases in the human respiratory tract or cardiovascular system if inhaled by humans. In order to prepare for these risks, state-centered management and preventable monitoring and forecasting are important. This study tried to predict PM2.5 in Seoul, where high concentrations of fine dust occur frequently, using two ensemble models, random forest (RF) and extreme gradient boosting (XGB) using 15 local data assimilation and prediction system (LDAPS) weather-related factors, aerosol optical depth (AOD) and 4 chemical factors as independent variables. Performance evaluation and factor importance evaluation of the two models used for prediction were performed, and seasonal model analysis was also performed. As a result of prediction accuracy, RF showed high prediction accuracy of R2 = 0.85 and XGB R2 = 0.91, and it was confirmed that XGB was a more suitable model for PM2.5 prediction than RF. As a result of the seasonal model analysis, it can be said that the prediction performance was good compared to the observed values with high concentrations in spring. In this study, PM2.5 of Seoul was predicted using various factors, and an ensemble-based PM2.5 prediction model showing good performance was constructed.

A Case Study for Reasonable Emission Regulation of Odor Exhaust Stack (악취 배출구의 합리적인 배출규제를 위한 사례연구)

  • Park, Jeong-Ho;Lee, Hyung-Chun
    • Journal of Environmental Science International
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    • v.25 no.1
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    • pp.155-161
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    • 2016
  • In this study, field experiment, odor simulator, and dispersion modeling were used to evaluate the odor impact from J sewage sludge treatment facility. The height and flow rate of exhaust stack at this facility were 22.3 m and $100Nm^3/min$. The mean odor concentrations of the wet scrubber inlet and exhaust stack were $267{\pm}160$ and $93{\pm}44OU/m^3$, respectively. The odor removal efficiency of wet scrubber showed 65%. The odor simulator is used for the regulated standard calculation of the exhaust pipe(stack). Resulting odor emission rate(OER) by odor simulator was $2.4{\times}10^6(24,000OU/m^3)$. The forecasting result by Screen3 modeling showed that odor exhaust concentration up to $30,000OU/m^3$ was't exceeded maximum allowable emission level on site boundary($15OU/m^3$).

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.

Review on the Current Status and Policy on PM2.5 in China (중국 초미세먼지 현황 및 정책 동향)

  • Moon, Kwang-Joo;Cheo, Hyeok-gi;Jeon, Kwon-ho;Yang, Xiaoyang;Meng, Fan;Kim, Dai-gon;Park, Hyun-Ju;Kim, Jeong-soo
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.3
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    • pp.373-392
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    • 2018
  • The emission of air pollutants in China has increased rapidly as its economy expanded over the last decades. The Chinese government has recently acknowledged the seriousness of the resulting air pollution and is trying to improve air quality in many ways. Here, we review the air quality control and management policies in China, one of our closest neighbors, because these policies may also influence the air quality in Korea. This study examined the recent policies on $PM_{2.5}$ reduction and analyzed the variation in air quality and air pollutant emissions in China. The ambient air quality and emission standards in China have been strengthened, based on China's Air Pollution Prevention and Control Action Plan of 2013. As a result, the annual mean concentration of $PM_{2.5}$ in 2015 in 74 large Chinese cities declined by 23.6% compared with 2013 values. Coal consumption in China also has been reduced by more than 10% per year since 2013. Furthermore, the laws controlling atmospheric emissions were revised again in 2016, and an air pollution forecasting and warning system was implemented to help manage air pollution problems. At present, the Chinese government is trying to evaluate its policies on $PM_{2.5}$ and find a new paradigm to mitigate ongoing $PM_{2.5}$ pollution. In this context, a joint study between Korea and China has been initiated to investigate the characteristics and sources of ambient $PM_{2.5}$ and to identify factors contributing to the high $PM_{2.5}$ concentrations in northeast China. We expect that this academic collaboration will benefit both countries in their search for new policies for $PM_{2.5}$ reduction.

Analysis of the Contribution of Biomass Burning Emissions in East Asia to the PM10 and Radiation Energy Budget in Korea (동아시아의 생체연소 배출물에 대한 한국의 미세먼지 기여도 및 복사 에너지 수지 분석)

  • Lee, Ji-Hee;Cho, Jae-Hee;Kim, Hak-Sung
    • Journal of the Korean earth science society
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    • v.43 no.2
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    • pp.265-282
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    • 2022
  • This study analyzes the impact of long-range transport of biomass burning emissions from northeastern China on the concentration of particulate matter of diameter less than 10 ㎛ (PM10) in Korea using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Korea was impacted by anthropogenic emissions from eastern China, dust storms from northern China and Mongolia, and biomass burning emissions from northeast China between April 4-and 7, 2020. The contributions of long-range PM10 transport were calculated by separating biomass burning emissions from mixed air pollutants with anthropogenic emissions and dust storms using the zeroing-out method. Further, the radiation energy budget over land and sea around the Korean Peninsula was analyzed according to the distribution of biomass burning emissions. Based on the WRF-Chem simulation during April 5-6, 2020, the contribution of long-range transport of biomass burning emissions was calculated as 60% of the daily PM10 average in Korea. The net heat flux around the Korean Peninsula was in a negative phase due to the influence of the large-scale biomass burning emissions. However, the contribution of biomass burning emissions was analyzed to be <45% during April 7-8, 2020, when the anthropogenic emissions from eastern China were added to biomass burning emissions, and PM10 concentration increased compared with the concentration recorded during April 5-6, 2020 in Korea. Furthermore, the net heat flux around the Korean Peninsula increased to a positive phase with the decreasing influence of biomass burning emissions.

Monitoring The Children's Health Status and Forecasting Height with Nutritional Advice

  • Nguyen, Kim Ngan;Ton, Nu Hoang Vi;Vu, Tran Minh Khuong;Bao, Pham The
    • Journal of IKEEE
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    • v.22 no.3
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    • pp.680-692
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    • 2018
  • Children's health is interesting to parents and society. A system that assists to monitor the development of their children and gives nutritional advices is an interesting of parents. In this study, we present a system that allows to track the heights and weights of a child since he/she was born up to adulthood, to predict his age of puberty, and to provide nutritional advice. Particularly, it predicts the height in near future and the adult stature for detecting the child with abnormal development. We applied Sager's model for predicting the height in near future by using interpolation and regression techniques before puberty. After determining the puberty time, we proposed a model for predicting the height. Then we applied fuzzy logic for evaluating the health status and providing nutritional advice. Our system predicted stature in near future with error bound of $1.7361{\pm}0.0397cm$ in girls and $2.4020{\pm}0.0799cm$ in boys. Our model also gave a reliable adult stature prediction with error bound of $0.3507{\pm}0.2808cm$ in girls and $1.3414{\pm}0.7024cm$ in boys. At the same time, the nutrition was provided appropriately in terms of protein, lipid, glucid. We implemented a program based on this research. Our system promises to improve the health of every child.