• Title/Summary/Keyword: carbon footprints

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Comparison of Land Farming and Chemical Oxidation based on Environmental Footprint Analysis (환경적 footprint 분석을 통한 토양경작법과 화학적산화법의 비교)

  • Kim, Yun-Soo;Lim, Hyung-Suk;Park, Jae-Woo
    • Journal of Soil and Groundwater Environment
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    • v.20 no.3
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    • pp.7-14
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    • 2015
  • In this study, land farming and chemical oxidation of a diesel-contaminated site is compared to evaluate the environmental impact during soil remediation using the Spreadsheet for Environmental Footprint Analysis by U.S. EPA. Each remediation process is divided into four phases, consisting of soil excavation, backfill and transportation (Phase 0), construction of remediation facility (Phase 1), remediation operation (Phase 2), and restoration of site and waste disposal (Phase 3). Environmental footprints, such as material use, energy consumption, air emission, water use and waste generation, are analyzed to find the way to minimize the environmental impact. In material use and waste generation, land farming has more environmental effect than chemical oxidation due to the concrete and backfill material used to construct land farming facility in Phase 1. Also, in energy use, land farming use about six times more energy than chemical oxidation because of cement production and fuel use of heavy machinery, such as backhoe and truck. However, carbon dioxide, commonly considered as important factor of environmental impact due to global warming effect, is emitted more in chemical oxidation because of hydrogen peroxide production. Water use of chemical oxidation is also 2.1 times higher than land farming.

A Study on the Applicability of Water Footprint Methodology in Korea by Analyzing Domestic Water Resources Statistics (국내 물 자원 통계자료 분석을 통한 물발자국 방법론 국내 적용 가능성 확인 연구)

  • Kim, Sun Uk;Jo, Seo Weon;Ahn, Jae Hyun;Lee, Han Woong;Yeon, Sung Mo
    • Clean Technology
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    • v.24 no.2
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    • pp.146-153
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    • 2018
  • The water footprint is an important component of the Single Market for Green Product initiative based on the EU's Roadmap to a Resource Efficient Europe. In July 2014, the EU has established the International Standard for Water Footprint (ISO 14046) and Korea has complied with the Korean Industrial Standard (KS I ISO 14046) in April 2015. If a certification system based on the international standard (ISO 14046) is introduced, developing countries such as India and Vietnam, which are not equipped with bases, can become a trade barriers in exporting, so Korea should establish a strategy to reverse them. On the other hand, water footprints are designed to take into account local environmental impacts when compared to similar footprints (eg, carbon footprint) using LCA, so that products manufactured and manufactured in Korea will have an impact on domestic waters Should be considered. Therefore, the method of the water footprint should conform to the standard for compatibility with other countries. In order to consider the domestic water condition, it is necessary to identify suitable indicator or factor for estimating water footprint on Korea. For this purpose, this study analyzed the water footprint estimation study conducted at domestic and foreign based on international standards and through the analysis of statistical data related to domestic water resources, we confirmed the applicability of the water footprint methodology in Korea.

Long Term Flux Variation Analysis on the Boseong Paddy Field (보성 농업지역에서의 장기간 플럭스 특성 분석)

  • Young-Tae Lee;Sung-Eun Hwang;Byeong-Taek Kim;Ki-Hun Kim
    • Atmosphere
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    • v.34 no.1
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    • pp.69-81
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    • 2024
  • In this paper, Annual flux variations in the Boseong Tall Tower (BTT) from 2016 to 2020 were analyzed using data from three levels (2.5 m, 60 m, and 300 m). BTT was installed in Boseong-gun, Jeollanam-do in February 2014 and continued to conduct energy exchange observations such as CO2, sensible heat, and latent heat using the eddy covariance method until March 2023. The BTT was located in a very flat and uniform paddy field, and flux observations were conducted at four levels: 2.5 m, 60 m, 140 m, and 300 m above ground. Surface energy balance was confirmed from observed data of net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. Additionally, 2.5 m height surface fluxes, which are most influenced by agricultural land, were compared with data from Local Data Assimilation and Prediction System (LDAPS) of the Korea Meteorological Administration to evaluate the accuracy of LDAPS flux data. The correlation coefficient between LDAPS flux data and observed values was 0.95 or higher. Excluding summer latent heat flux data, there was a general tendency for LDAPS data to be higher than observed values. The footprint areas estimated below 60 m height mainly covered agricultural land, and flux observations at 2.5 m and 60 m heights showed typical agricultural characteristics. In contrast, the footprint estimated at 300 m height did not show agricultural characteristics, indicating that observations at this height encompassed a wide range, including mountains, sea, and roads. The analysis results of long-term flux observations can contribute to understanding the energy and carbon dioxide fluxes in agricultural fields. Furthermore, these results can be utilized as essential data for validating and improving numerical models related to such fluxes.

Life Cylcle Assessment (LCA) on Rice Production Systems: Comparison of Greenhouse Gases (GHGs) Emission on Conventional, Without Agricultural Chemical and Organic Farming (쌀 생산체계에 대한 영농방법별 전과정평가: 관행농, 무농약, 유기농법별 탄소배출량 비교)

  • Ryu, Jong-Hee;Kwon, Young-Rip;Kim, Gun-Yeob;Lee, Jong-Sik;Kim, Kye-Hoon;So, Kyu-Ho
    • Korean Journal of Soil Science and Fertilizer
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    • v.45 no.6
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    • pp.1157-1163
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    • 2012
  • This study was performed a comparative life cycle assessment (LCA) among three rice production systems in order to analyze the difference of greenhouse gases (GHGs) emissions and environment impacts. Its life cycle inventory (LCI) database (DB) was established using data obtained from interview with conventional, without agricultural chemical and organic farming at Gunsan and Iksan, Jeonbuk province in 2011. According to the result of LCI analysis, $CO_2$ was mostly emitted from fertilizer production process and rice cropping phase. $CH_4$ and $N_2O$ were almost emitted from rice cultivation phase. The value of carbon footprint to produce 1 kg rice (unhulled) on conventional rice production system was 1.01E+00 kg $CO_2$-eq. $kg^{-1}$ and it was the highest value among three rice production systems. The value of carbon footprints on without agricultural chemical and organic rice production systems were 5.37E-01 $CO_2$-eq. $kg^{-1}$ and 6.58E-01 $CO_2$-eq. $kg^{-1}$, respectively. Without agricultural chemical rice production system whose input amount was the smallest had the lowest value of carbon footprint. Although the yield of rice from organic farming was the lowest, its value of carbon footprint less than that of conventional farming. Because there is no compound fertilizer inputs in organic farming. Compound fertilizer production and methane emission during rice cultivation were the main factor to GHGs emission in conventional and without agricultural chemical rice production systems. In organic rice production system, the main factors to GHGs emission were using fossil fuel on machine operation and methane emission from rice paddy field.

Application of LCA on Lettuce Cropping System by Bottom-up Methodology in Protected Cultivation (시설상추 농가를 대상으로 하는 bottom-up 방식 LCA 방법론의 농업적 적용)

  • Ryu, Jong-Hee;Kim, Kye-Hoon;Kim, Gun-Yeob;So, Kyu-Ho;Kang, Kee-Kyung
    • Korean Journal of Soil Science and Fertilizer
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    • v.44 no.6
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    • pp.1195-1206
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    • 2011
  • This study was conducted to apply LCA (Life cycle assessment) methodology to lettuce (Lactuca sativa L.) production systems in Namyang-ju as a case study. Five lettuce growing farms with three different farming systems (two farms with organic farming system, one farm with a system without agricultural chemicals and two farms with conventional farming system) were selected at Namyangju city of Gyeonggi-province in Korea. The input data for LCA were collected by interviewing with the farmers. The system boundary was set at a cropping season without heating and cooling system for reducing uncertainties in data collection and calculation. Sensitivity analysis was carried out to find out the effect of type and amount of fertilizer and energy use on GHG (Greenhouse Gas) emission. The results of establishing GTG (Gate-to-Gate) inventory revealed that the quantity of fertilizer and energy input had the largest value in producing 1 kg lettuce, the amount of pesticide input the smallest. The amount of electricity input was the largest in all farms except farm 1 which purchased seedlings from outside. The quantity of direct field emission of $CO_2$, $CH_4$ and $N_2O$ from farm 1 to farm 5 were 6.79E-03 (farm 1), 8.10E-03 (farm 2), 1.82E-02 (farm 3), 7.51E-02 (farm 4) and 1.61E-02 (farm 5) kg $kg^{-1}$ lettuce, respectively. According to the result of LCI analysis focused on GHG, it was observed that $CO_2$ emission was 2.92E-01 (farm 1), 3.76E-01 (farm 2), 4.11E-01 (farm 3), 9.40E-01 (farm 4) and $5.37E-01kg\;CO_2\;kg^{-1}\;lettuce$ (farm 5), respectively. Carbon dioxide contribute to the most GHG emission. Carbon dioxide was mainly emitted in the process of energy production, which occupied 67~91% of $CO_2$ emission from every production process from 5 farms. Due to higher proportion of $CO_2$ emission from production of compound fertilizer in conventional crop system, conventional crop system had lower proportion of $CO_2$ emission from energy production than organic crop system did. With increasing inorganic fertilizer input, the process of lettuce cultivation covered higher proportion in $N_2O$ emission. Therefore, farms 1 and 2 covered 87% of total $N_2O$ emission; and farm 3 covered 64%. The carbon footprints from farm 1 to farm 5 were 3.40E-01 (farm 1), 4.31E-01 (farm 2), 5.32E-01 (farm 3), 1.08E+00 (farm 4) and 6.14E-01 (farm 5) kg $CO_2$-eq. $kg^{-1}$ lettuce, respectively. Results of sensitivity analysis revealed the soybean meal was the most sensitive among 4 types of fertilizer. The value of compound fertilizer was the least sensitive among every fertilizer imput. Electricity showed the largest sensitivity on $CO_2$ emission. However, the value of $N_2O$ variation was almost zero.