This study was conducted to identify and assess key parameters affecting greenhouse gas emissions and odor intensity at a naturally ventilated dairy farm. Measurement data of greenhouse gases (CO2, CH4, N2O), odorants (NH3 and H2S), and meteorological data (wind speed, temperature, relative humidity, and solar radiation) were posited as the parameters influencing those emissions. Carbon dioxide and methane emissions correlated well to CO2-equivalent emissions and the contribution of carbon dioxide emissions (R2=0.9181) was greater than that of methane emissions (R2=0.8854). Hydrogen sulfide emissions were highly correlated with odor intensity (R2=0.9989), but the contribution of ammonia emissions to odor intensity was not significant (R2=0.0081). No correlation among CO2-equivalent and odor intensity emissions and meteorological parameters was observed. In this study, the relationship between emissions of greenhouse gases and odor intensity in a naturally ventilated dairy barn mainly depended upon carbon dioxide and hydrogen sulfide emissions. The results in this study will be helpful in the mitigation planning of greenhouse gases and odor in animal feeding operations (CFOs).

Two man-made carbon emissions, fossil fuel emissions and land use emissions, have been perturbing naturally occurring global carbon cycle. These emitted carbons will eventually be deposited into the atmosphere, the terrestrial biosphere, the soil, and the ocean. In this study, Simple Global Carbon Model (SGCM) was used to simulate global carbon cycle and to estimate global carbon budget. For the model input, fossil fuel emissions and land use emissions were taken from the literature. Unlike fossil fuel use, land use emissions were highly uncertain. Therefore land use emission inputs were adjusted within an uncertainty range suggested in the literature. Simulated atmospheric CO2 concentrations were well fitted to observations with a standard error of 0.06 ppm. Moreover, simulated carbon budgets in the ocean and terrestrial biosphere were shown to be reasonable compared to the literature values, which have considerable uncertainties. Simulation results show that with increasing fossil fuel emissions, the ratios of carbon partitioning to the atmosphere and the terrestrial biosphere have increased from 42% and 24% in the year 1958 to 50% and 30% in the year 2016 respectively, while that to the ocean has decreased from 34% in the year 1958 to 20% in the year 2016. This finding indicates that if the current emission trend continues, the atmospheric carbon partitioning ratio might be continuously increasing and thereby the atmospheric CO2 concentrations might be increasing much faster. Among the total emissions of 399 gigatons of carbon (GtC) from fossil fuel use and land use during the simulation period (between 1960 and 2016), 189 GtC were reallocated to the atmosphere (47%), 107 GtC to the terrestrial biosphere (27%), and 103GtC to the ocean (26%). The net terrestrial biospheric carbon accumulation (terrestrial biospheric allocations minus land use emissions) showed positive 46 GtC. In other words, the terrestrial biosphere has been accumulating carbon, although land use emission has been depleting carbon in the terrestrial biosphere.

The relationship between urban spatial structures and GHG-AP integrated emissions was investigated by statistically analyzing those from 25 administrative districts of Seoul. Urban spatial structures, of which data were obtained from Seoul statistics yearbook, were classified into five categories of city development, residence, environment, traffic and economy. They were further classified into 10 components of local area, population, number of households, residential area, forest area, park area, registered vehicles, road area, number of businesses and total local taxes. GHG-AP integrated emissions were estimated based on IPCC(intergovernmental panel on climate change) 2006 guidelines, guideline for government greenhouse inventories, EPA AP-42(compilation of air pollutant emission factors) and preliminary studies. The result of statistical analysis indicated that GHG-AP integrated emissions were significantly correlated with urban spatial structures. The correlation analysis results showed that registered vehicles for GHG (r=0.803, p<0.01), forest area for AP (r=0.996, p<0.01), and park area for AP (r=0.889, p<0.01) were highly significant. From the factor analysis, three groups such as city and traffic categories, economy category and environment category were identified to be the governing factors controlling GHG-AP emissions. The multiple regression analysis also represented that the most influencing factors on GHG-AP emissions were categories of traffic and environment. 25 administrative districts of Seoul were clustered into six groups, of which each has similar characteristics of urban spatial structures and GHG-AP integrated emissions.

The university is one of the main energy consumption facilities and thereby releases a large amount of greenhouse gas (GHG). Accordingly, efforts for reducing energy consumption and GHG have been established in many local as well as international universities. However, it has been limited to energy consumption and GHG, and has not included air pollution (AP). Therefore, we estimated GHG and AP integrated emissions from the energy consumed by Seoul National University of Science and Technology during the years between 2010 and 2012. In addition, the effect of alternative energy use scenario was analysed. We estimated GHG using IPCC guideline and Guidelines for Local Government Greenhouse Inventories, and AP using APEMEP/EEA Emission Inventory Guidebook 2013 and Air Pollutants Calculation Manual. The estimated annual average GHG emission was 11,420 tonCO2eq, of which 27% was direct emissions from fuel combustion sectors, including stationary and mobile source, and the remaining 73% was indirect emissions from purchased electricity and purchased water supply. The estimated annual average AP emission was 7,757 kgAP, of which the total amount was from direct emissions only. The annual GHG emissions from city gas and purchased electricity usage per unit area (m2) of the university buildings were estimated as 15.4 kgCO2eq/m2 and 42.4 tonCO2eq/m2 and those per person enrolled in the university were 210 kgCO2eq/capita and 577 kgCO2eq/capita. Alternative energy use scenarios revealed that the use of all alternative energy sources including solar energy, electric car and rain water reuse applicable to the university could reduce as much as 9.4% of the annual GHG and 34% of AP integrated emissions, saving approximately 400 million won per year, corresponding to 14% of the university energy budget.