땅콩 수확시기 및 첨가제에 따른 땅콩경엽의 수량 및 사일리지용 사료가치를 비교 조사하였던 바 그 결과를 요약하면 다음과 같다. 1. 수확시기별 생육은 개화후 90일 수확시 경엽의 병해(갈색무늬병 및 흑색무늬병) 발생 정도가 낮고, 성숙협비율은 89%, 100립중은 81g으로 높았다. 2. 수확시기에 따른 경엽 및 종실 생산성은 개화후 90일에 경엽은 52 t/ha, 종실중은 3.6 t/ha이었다. 3. 경엽과 종실수량간에는 고도의 정상관(r2 =0.62** )이 있었다. 4. 땅콩경엽의 사일리지 사료가치는 땅콩경엽+볏짚+젖산균 조제시 ADF 42.2%, NDF 49.6%, CP 10.5%, TDN 55.6%이었다. 5. 땅콩경엽 사일리지의 유기산함량은 땅콩경엽+볏짚 및 땅콩경엽+보릿짚에다 젖산균 첨가시 각각 산도 5.04 및 5.10, 낙산함량 3.12% 및 4.64%, 젖산함량은 7.34% 및 2.07%이었다.

After analyzing the correlation between air pollution and visibility, TSP and NO2 is responsible for poor visibility in Pusan. After analyzing the correlation between meteorological factors and visibility, general pattern of humidity has clear negative correlation. The variation of wind speed has a positive correlation. In order to investigate the cause of poor visibility in Pusan area, the Andersen sampler and PM-2.5 are used to collect and analyze aerosol. This study was carried out to monitor the visibility using Forward scattering meter and to find out the characteristics and the cause of good visibility case and poor visibility case by measuring and analyzing a variety of parameters, such as particle size distributions, chemical compositions, and meteorological conditions in Pusan. According to the analysis of intensive sampling, NO3-, NH4+ ion concentration increased together with the mass concentration around 0.5∼2.5㎛ approximately during the case of poor visibility. NH4NO3, NH4Cl, and NaCl were thought to be the major components of fine particles.

For the efficient control of atmospheric quality, it is so important to predict the influence accurately of which the air pollutant emitted into the atmosphere. Atmospheric dispersion model enables to simulate and grasp the atmospheric condition occurred due to the emission of pollutants. The result of model is largely affected by the amount of emission, the characteristics of physical and chemical process, meteorological input data, and the receptor which the concentration is calculated. The aim of this research, therefore, is to suggest more suitable model in Pusan area than other areas by performing TCM2, CDM2.0 and ISCLT2 models. As the basic work for executing the model, we computed the amount of emission of air pollutants in Pusan at 1992 and analyzed the occurrence frequency of atmospheric stability for recent decade(1985∼1994). CDM2.0 showed the similar result relatively with observed value in the case of full year(1992), fall and winter, and ISCLT2 brought more suitable result in spring for Pusan area. As the result of this research, in future, it is necessary for us to develop the numerical model considering the topographical characteristics, to select the proper observation site and to increase the observation site for Pusan.

Pusan is the largest coastal city with a population of about four million in Korea. Because of increased and confused traffic, photochemical air pollution become a major urban environmental problem recently. The photo-chemical air pollution weather forecasting method preciser than existing air pollution forecast method has been developed to forecast ozone episode days with meteorological conditions using the data measured at 7 air quality continuous monitoring stations from June to September using 2 years (1994, 1995). The method developed in present study showed higher percentage correct and skill score than existing air pollution forecasting in KMA (Korea Meteorological Administration).