• Environmental and Resource Economics Review
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• v.25 no.3
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• pp.403-419
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• 2016

Cap-and-trade policies that allow firms to trade emission allowances are designed to reduce emissions at least cost and are shown to be efficient when there is no uncertainty over emissions. This paper examines how uncertainty in emissions affects firms' decisions about permit purchase and abatement. The results show that whether firms abate more under uncertainty compared to a case with no uncertainty depends on the expected penalty cost and marginal abatement cost. If the expected marginal penalty cost is greater than the marginal abatement cost, the firm will choose to reduce emissions and abate more under uncertainty. When the expected marginal penalty is greater than the marginal cost of abatement, increases in uncertainty result in reduced emissions. This paper also examines whether the order of abatement and permit trading and the realization of uncertainty affect firms' decisions. The results show that total expected emissions are the same regardless of the order of moves.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.307-316
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• 2019

In the agricultural sector, greenhouse gas emissions vary depending on the interaction of all ecosystem changes such as soil environment, weather environment, crop growth, and anthropogenic farming activities. Agricultural sector greenhouse gas emissions resulting from many of these interactions are highly variable. Uncertainty-based evaluation that defines the interval with confidence level of greenhouse gas emission and absorption is necessary to take account of the variance characteristics of individual emissions, but research on uncertainty evaluation method is insufficient. This study aims to decide on the effect of reducing N₂O emissions from upland soils using an uncertainty-based approach. An uncertainty-based approach confirmed whether there was a difference between confidence intervals in the 5 different fertilizer treatment groups to reduce greenhouse gas emissions. Unlike the statistically significant test with three repetition averages, the uncertainty-based approach method estimated in this study is able to estimate the confidence interval considering the distribution characteristics of the emissions, such as the dispersion characteristics of individual emissions. Therefore, it is considered that the reliability of emissions can be improved by statistically testing the variance characteristics of emissions such as the uncertainty-based approach. It is hoped that the direction of the uncertainty-based approach for the effect of reducing greenhouse gas emissions in agriculture will be helpful in the future development of agricultural greenhouse gas emission reduction technology, adaptation to climate change, and further development of sustainable eco-social system.

• Asian Journal of Atmospheric Environment
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• v.8 no.4
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• pp.212-224
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• 2014

There are several studies on the effects of emissions of highly reactive volatile organic compounds (HRVOC) from the industrial sources in the Houston-Galveston-Brazoria (HGB) area on the high ozone events during the Texas Air Quality Study (TexAQS) in summer of 2000. They showed that the modeled atmosphere lacked reactivity to produce the observed high ozone event and suggested "imputation" of HRVOC emissions from the base inventory. Byun et al. (2007b) showed the imputed inventory leads to too high ethylene concentrations compared to the measurements at the chemical super sites but still too little aloft compared to the NOAA aircraft. The paper suggested that the lack of reactivity in the modeled Houston atmosphere must be corrected by targeted, and sometimes of episodic, increase of HRVOC emissions from the large sources such as flares in the Houston Ship Channel (HSC) distributed into the deeper level of the boundary layer. We performed retrospective meteorological and air quality modeling to achieve better air quality prediction of ozone by comparison with various chemical and meteorological measurements during the Texas Air Quality Study periods in August-September 2006 (TexA QS-II). After identifying several shortcomings of the forecast meteorological simulations and emissions inputs, we prepared new retrospective meteorological simulations and updated emissions inputs. We utilized assimilated MM5 inputs to achieve better meteorological simulations (detailed description of MM5 assimilation can be found in F. Ngan et al., 2012) and used them in this study for air quality simulations. Using the better predicted meteorological results, we focused on the emissions uncertainty in order to capture high peak ozone which occasionally happens in the HGB area. We described how the ozone predictions are affected by emissions uncertainty in the air quality simulations utilizing different emission inventories and adjustments.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.261-290
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• 2022

Although market stabilization measures have been triggered in the K-ETS, carbon price is still under uncertainty. Considering Korea's 2030 enhanced reduction target announced in October 2021, it is crucial to have practical stabilization measures to appropriately deal with price uncertainty. This study examines the quantitative effects of a price collar, which is considered as a means of alleviating price uncertainty, on expected cumulative emissions and abatement costs. There are three main scenarios: carbon tax, emissions trading system, and emissions trading system with a price collar. Monte Carlo simulation was conducted to reflect uncertainty in emission. There are several results as follows: 1) In a price collar, domestic emission target is likely to be achieved with a lower expected abatement cost than other scenarios. In addition, there is a small amount of excess emissions in this research and it would be not critical(0.1% excess than target); 2) Prohibiting banking increases the expected abatement cost. This is because firms can not intertemporally reallocate allowances to match the firm's optimal emissions path; 3) With the adoption of a price collar, government's net revenue can be positive even if the government's purchase volume of emissions allowances is more than sales volume. This is because the government sells them at price ceiling and purchases them at price floor.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.228-236
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• 2020

BACKGROUND: The closed chamber method is the most commonly used for measuring greenhouse gas emissions from rice fields. This method has the advantages of being simple, easily available and economical. However, a measurement result using the chamber method is an estimated value and is complete when the uncertainty is estimated. The methane emissions from a rice paddy account for the largest portion of the greenhouse gas emissions in the agriculture sectors. Although assessment of uncertainty components affecting methane emission from a rice paddy is necessary to take account of dispersion characteristics, research on these uncertainty components is very rare to date. The goal of this study was to elucidate influencing factors on measurement uncertainty of methane concentrations measured by a closed automated chamber system from a rice paddy. METHODS AND RESULTS: The methane sampling system is located in the rice paddy in Gyeonggi-do Agricultural Research and Extension Services (37°13'15"N, 127°02'22"E). The primary measurement uncertainty components influencing methane concentrations (influencing factors) investigated in this research were repeatability, reproducibility and calibration in the aspects of methane sampling and analytical instrumentation. The magnitudes of the relative standard uncertainty of each influencing factor were quantified and compared. CONCLUSION: Results of this study showed what influencing factors were more important in determination of methane concentrations measured using the chamber system and analytical instrumentation located in the monitoring site. Quantifying the measurement uncertainty of the methane concentrations in this study would contribute to improving measurement quality of methane fluxes.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.237-245
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• 2020

BACKGROUND: The closed chamber method is the most commonly used for measuring greenhouse gas emissions from upland fields. This method has the advantages of being simple, easily available and economical. However, uncertainty estimation is essential for accurate assessment of greenhouse gas emissions and verification of emission reductions. The nitrous oxide emissions from upland field is very important for the nitrogen budget in the agriculture sectors. Although assessment of uncertainty components affecting nitrous oxide emission from upland field is necessary to take account of dispersion characteristics, research on these uncertainty components is very rare to date. This study aims at elucidation of influencing factors on measurement uncertainty of nitrous oxide concentrations measured by an automated open closed chamber method from upland field. METHODS AND RESULTS: The nitrous oxide sampling system is located in the upland field in Gyeonggi-do Agricultural Research and Extension Services (37°13'22"N, 127°02'22"E). The primary measurement uncertainty components influencing nitrous oxide concentrations (influencing factors) investigated in this research are repeatability, reproducibility and calibration in the aspects of nitrous oxide sampling and analytical instrumentation. The magnitudes of the relative standard uncertainty of each influencing factor are quantified and compared. CONCLUSION: Results of this study show what influencing factors are more important in determination of nitrous oxide concentrations measured using the automated open closed chambers located in the monitoring site. Quantifying the measurement uncertainty of the nitrous oxide concentrations in this study would contribute to improving measurement quality of nitrous oxide fluxes.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.751-771
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• 2011

Biogenic Volatile Organic Compound (BVOC) emissions are estimated with BEIS3.12 (Biogenic Emissions Inventory System version 3.12) over the Seoul Metropolitan Area (SMA) and then used in CMAQ (Community Multiscale Air Quality) simulations for two high ozone episodes in 2004 and 2007 June. The first- and second-order sensitivity coefficients of ozone to BVOC emissions are estimated with High-order Decoupled Direct Method (HDDM) simulation in order to estimate the influence of BVOC emissions on ozone using the Zero-Out Contribution (ZOC) approach. ZOC analysis shows that relative contribution of BVOC emissions on daily maximum 1-hr ozone is as high as 30% for high ozone days above 100 ppb. However simulated isoprene concentrations were over-estimated by a factor of 2 when compared to the observations at the PAMS (Photochemical Air Monitoring Station) for the 2007 episode. When assumed that actual BVOC emissions are 50% less than estimated, the ZOC of BVOC emissions on daily maximum ozone drops by more than 10 ppb for the episode. The result indicates that uncertainty in BVOC emissions may have significant impact on high ozone prediction in the SMA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.294-304
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• 2019

Abstract Greenhouse Gas (GHG) emissions from agriculture and forestry sources in the energy sector have been estimated based on a top-down approach, which is an efficient way to estimate GHG emissions with the limited number of emission factors and activity data. On the other hand, for GHG abatement policies, more detailed information and data on GHG emissions are required. This study discusses how to improve the estimates of GHG emissions from the agricultural and forestry sources in the energy sector. To this end, this paper reviews the current estimation method of GHG emissions and presents three suggestions to enhance the current method. First, the development of country specific emission factors and corresponding activity data is proposed based on the 2006 IPCC Guidelines, National Greenhouse Gas Inventory Reports from other countries, and Domestic Statistics. Second, the uncertainty in CO₂ emissions from agriculture in energy sector based on 2006 IPCC Guidelines is estimated, and ways of reducing the uncertainty in CO₂ emissions are suggested. Finally, a potential way to reflect the GHG emissions from the use of renewable energy is suggested.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.508-520
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• 2020

Dam reservoirs have been reported to contribute significantly to global carbon emissions, but unlike natural lakes, there is considerable uncertainty in calculating carbon emissions due to the complex of emission pathways. In particular, the method of calculating carbon dioxide (CO2) net atmospheric flux (NAF) based on a simple gas exchange theory from sporadic data has limitations in explaining the spatiotemporal variations in the CO2 flux in stratified reservoirs. This study was aimed to analyze the spatial and temporal CO2 distribution and mass balance in Daecheong Reservoir, located in the mid-latitude monsoon climate zone, by applying a two-dimensional hydrodynamic and water quality model (CE-QUAL-W2). Simulation results showed that the Daecheong Reservoir is a heterotrophic system in which CO2 is supersaturated as a whole and releases CO2 to the atmosphere. Spatially, CO2 emissions were greater in the lacustrine zone than in the riverine and transition zones. In terms of time, CO2 emissions changed dynamically according to the temporal stratification structure of the reservoir and temporal variations of algae biomass. CO2 emissions were greater at night than during the day and were seasonally greatest in winter. The CO2 NAF calculated by the CE-QUAL-W2 model and the gas exchange theory showed a similar range, but there was a difference in the point of occurrence of the peak value. The findings provide useful information to improve the quantification of CO2 emissions from reservoirs. In order to reduce the uncertainty in the estimation of reservoir carbon emissions, more precise monitoring in time and space is required.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.2
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• pp.295-302
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• 2011

Almost half of New Zealand's greenhouse gas emissions arise from agriculture and enteric methane ($CH_4 $) emissions arising from ruminant animals constitute 30% of total $CO_2$-e emissions. Enteric $CH_4$ emissions have increased by 9% since 1990. Extensive research has been undertaken to develop reliable methods for measuring enteric $CH_4$ emissions. New Zealand studies using the SF6 tracer technique suggest that on average this technique yields similar values to the 'gold' standard of calorimetry, but with a larger variance. National inventory estimates based on results obtained using the $SF_6$ technique will therefore overestimate the uncertainty. Mitigating emissions can be achieved by changing feed type but there are practical and cost barriers to the use of alternative feeds. Forages containing condensed tannins do reduce emissions but are agronomically inferior to the forages currently used. Rumen additives have shown some success in-vitro but results from in-vivo trials with both monensin and fumaric acid have been disappointing. The development of methods for directly manipulating rumen microorganisms are at an early stage and work to develop vaccines that can inhibit methanogenesis has yielded mixed results. The successful identification of sheep with contrasting $CH_4$ yields raises the possibility that, in the long term, a breeding approach to $CH_4$ mitigation is feasible.