North Korean CO emissions reconstruction using DMZ ground observations, TROPOMI space-borne data, and the CMAQ air quality model

Emission uncertainty in North Korea can act as an obstacle when developing air pollution management plans in the country and neighboring countries when the transboundary transport of air pollutants is considered. This study introduces a novel approach for adjusting and reallocating North Korean CO emissions, aiming to complement the limited observational and emissions data on the country's air pollutants. We utilized ground observations from demilitarized zone (DMZ) and vertical column density (VCD) data from a TROPOspheric Monitoring Instrument (TROPOMI), which were combined with the Community Multi-Scale Air Quality (CMAQ) chemistry transport model simulations. The Clean Air Support System (CAPSS) and Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) emissions inventories served as the basis for our initial simulations. A two-step procedure was proposed to adjust both the emission intensity and the spatial distribution of emissions. First, air quality simulations were conducted to explore model sensitivity to changes in North Korean CO emissions with respect to ground concentrations. DMZ observations then constrained these simulations to estimate corresponding emission intensity. Second, the spatial structure of North Korean CO emission sources was reconstructed with the help of TROPOMI CO VCD distributions. Our two-step hybrid method outperformed individual emissions adjustment and spatial reallocation based solely on surface or satellite observations. Validation using ground observations from the Chinese Dandong site near the China-North Korea border revealed significantly improved model simulations when applying the updated CO emissions. The adjusted CO emissions were 10.9 times higher than those derived from the bottom-up emissions used in this study, highlighting the lack of information on North Korean pollutants and emission sources. This approach offers an efficient and practical solution for identifying potential missing emission sources when there is limited on-site information about air quality on emissions.

Development of surface observation-based two-step emissions adjustment and its application on CO, NOx, and SO2 emissions in China and South Korea

It is challenging to estimate local emission conditions of a downwind area solely based on concentrations in the downwind area. This is because air pollutants that have a long residence time in the atmosphere can be transported over long distances and influence air quality in downwind areas. In this study, a Two-step Emissions Adjustment (TEA) approach was developed to adjust downwind emissions of target air pollutants with surface observations, considering their long-range transported emission impacts from upwind areas calculated from air quality simulations. Using the TEA approach, CO, NOx, and SO2 emissions were adjusted in China and South Korea between 2016 and 2021 based on existing bottom-up emissions inventories. Simulations with the adjusted emissions showed that the 6-year average normalized mean biases of the monthly mean concentrations of CO, NOx, and SO2 improved to 0.3 %, -2 %, and 2 %, respectively, in China, and to 5 %, 7 %, and 4 %, respectively, in South Korea. When analyzing the emission trends, it was estimated that the annual emissions of CO, NOx, and SO2 in China decreased at a rate of 7.2 %, 4.5 %, and 10.6 % per year, respectively. The decrease rate of emissions for each of these pollutants was similar to that of ambient concentrations. When considering upwind emission impacts in the emissions adjustment, CO emissions increased by 1.3 %/year in South Korea, despite CO concentrations in the country decreasing during the study period. During the study period, NOx and SO2 emissions in South Korea decreased by 3.9 % and 0.5 %/year, respectively. Moreover, the TEA approach can account for drastic short-term emission changes (e.g., social distancing due to COVID-19). Therefore, the TEA approach can be used to adjust emissions and improve reproducibility of concentrations of air pollutants suitable for health studies for areas where upwind emission impacts are significant.

Adjusting elemental carbon emissions in Northeast Asia using observed surface concentrations of downwind area and simulated contributions

In this study, we developed a practical approach to augment elemental carbon (EC) emissions to improve the reproducibility of the most recent air quality with photochemical grid modeling in support of source-receptor relationship analysis. We demonstrated the usefulness of this approach with a series of simulations for EC concentrations over Northeast Asia during the 2016 Korea-United States Air Quality study. Considering the difficulty of acquiring EC observational data in foreign countries, our approach takes two steps: (1) augmenting upwind EC emissions based on simulated upwind contributions and observational data at a downwind EC monitor considered as the most representative monitor for upwind influences and (2) adjusting downwind EC emissions based on simulated downwind contributions, including the effects of updated upwind emissions from the first step and observational data at the downwind EC monitors. The emission adjustment approach resulted in EC emissions 2.5 times higher than the original emissions in the modeling domain. The EC concentration in the downwind area was observed to be 1.0 μg m-3 during the study period, while the simulated EC concentration was 0.5 μg m-3 before the emission adjustment. After the adjustment, the normalized mean error of the daily mean EC concentration decreased from 48 % to 22 % at ground monitor locations. We found that the EC simulation results were improved at high altitudes, and the contribution of the upwind areas was greater than that of the downwind areas for EC concentrations downwind with or without emission adjustment. This implies that collaborating with upwind regions is essential to alleviate high EC concentrations in downwind areas. The developed emission adjustment approach can be used for any upwind or downwind area when transboundary air pollution mitigation is needed because it provides better reproducibility of the most recent air quality through modeling with improved emission data.

Role of vertical advection and diffusion in long-range PM2.5 transport in Northeast Asia

This study quantitatively analyzed the role of vertical mixing in long-range transport (LRT) of PM_2.5 during its high concentration episode in Northeast Asia toward the end of February 2014. The PM_2.5 transport process from an upwind to downwind area was examined using the Community Multi-scale Air Quality (CMAQ) modeling system with its instrumented tool and certain code modifications. We identified serial distinctive roles of vertical advection (ZADV) and diffusion (VDIF) processes. The surface PM_2.5 in an upwind area became aloft by VDIF- during daytime-to the planetary boundary layer (PBL) altitude of 1 km or lower. In contrast, ZADV updraft effectively transported PM_2.5 vertically to an altitude of 2-3 km above the PBL. Furthermore, we found that the VDIF and ZADV in the upwind area synergistically promoted the vertical mixing of air pollutants up to an altitude of 1 km and higher. The aloft PM_2.5 in the upwind area was then transported to the downwind area by horizontal advection (HADV), which was faster than HADV at the surface layer. Additionally, VDIF and ZADV over the downwind area mixed down the aloft PM_2.5 on the surface. During this period, the VDIF and ZADV increased the PM_2.5 concentrations in the downwind area by up to 15 μg·m^-3 (15%) and 101 μg·m^-3 (60%), respectively. This study highlights the importance of vertical mixing on long-range PM_2.5 transport and warrants more in-depth model analysis with three-dimensional observations to enhance its comprehensive understanding.

An observation-based adjustment method of regional contribution estimation from upwind emissions to downwind PM2.5 concentrations

We propose a method to adjust contributions from upwind emissions to downwind PM_2.5 concentrations to account for the differences between observed and simulated PM_2.5 concentrations in an upwind area. Emissions inventories (EI) typically have a time lag between the inventory year and the release year. In addition, traditional emission control policies and social issues such as the COVID-19 pandemic cause steady or unexpected changes in anthropogenic emissions. These uncertainties could result in overestimation of the emission impacts of upwind areas on downwind areas if emissions used in modeling for the upwind areas were larger than the reality. In this study, South Korea was defined as the downwind area while other regions in Northeast Asia including China were defined as the upwind areas to evaluate applicability of the proposed adjustment method. We estimated the contribution of emissions released from the upwind areas to PM_2.5 concentrations in South Korea from 2015 to 2020 using a three-dimensional photochemical model with two EIs. In these two simulations for 2015-2020, the annual mean foreign contributions differed by 4.1-5.5 µg/m³. However, after adjustment, the differences decreased to 0.4-1.1 µg/m³. The adjusted annual mean foreign contributions were 12.7 and 8.8 µg/m³ during 2015-2017 and 2018-2020, respectively. Finally, we applied the adjustment method to the COVID-19 pandemic period to evaluate the applicability for short-term episodes. The foreign contribution of PM_2.5 during the lockdown period in China decreased by 30% after adjustment and the PM_2.5 normalized mean bias in South Korea improved from 15% to -4%. This result suggests that the upwind contribution adjustment can be used to alleviate the uncertainty of the emissions inventory used in air quality simulations. We believe that the proposed upwind contribution adjustment method can help to correctly understand the contributions of local and upwind emissions to PM_2.5 concentrations in downwind areas.

Role of emissions and meteorology in the recent PM2.5 changes in China and South Korea from 2015 to 2018

In this study, we examined the change rates of PM_2.5 concentrations, aerosol optical depth (AOD), and the concentrations of PM_2.5 precursors, such as SO₂ and NO₂, in China and South Korea using surface and satellite observations from 2015 to 2018. To quantify the impacts of the emissions and meteorology on the concentration changes, we performed a series of air quality simulations with year-specific meteorology and a fixed anthropogenic emissions inventory. The surface PM_2.5 observations in China and South Korea decreased at rates of 9.1 and 4.3%/yr during the study period, respectively. The AODs from Moderate Resolution Imaging Spectroradiometer (MODIS) and Geostationary Ocean Color Imager (GOCI) also decreased faster over China than the AODs over South Korea. For the PM_2.5 decrease in China, the emission impact was more significant (73%) than the meteorology impact (27%). On the contrary, in South Korea, the emissions and meteorology impacts on PM_2.5 reductions were similar (51% vs 49%). The SO₂ concentration over China in 2018 significantly reduced to approximately half of the level in 2015. In turn, the sulfate concentration in Baengnyeong (BN), located in a downwind pathway from China to South Korea, decreased at a rate of 0.79%/month. However, the nitrate concentration in BN showed an increasing trend due to the non-linear chemical reactions among sulfate-nitrate-ammonium. The increased nitrate compensated for the reduced PM_2.5 concentration from the sulfate decrease at BN. Additionally, the number of high (>50 μg/m³) PM_2.5 concentration days continuously decreased in China, but the number in South Korea increased. It is noted that emission reductions in an upwind area do not guarantee corresponding air quality improvement in the downwind area when complex secondary aerosol formation processes, as well as spatiotemporal changes in meteorology, are involved in the transboundary transport of air pollutants.

Sensitivity of fine particulate matter concentrations in South Korea to regional ammonia emissions in Northeast Asia

Ammonia (NH3) is an important precursor for forming PM2.5. In this study, we estimated the impact of upwind transboundary and local downwind NH3 emissions on PM2.5 and its inorganic components via photochemical grid model simulations. Nine sensitivity scenarios with ±50% perturbations of upwind (China) and/or downwind (South Korea) NH3 emissions were simulated for the year 2016 over Northeast Asia. The annual mean PM2.5 concentrations in the downwind area were predicted to change from -3.3 (-18%) to 2.4 μg/m3(13%) when the NH3 emissions in the upwind and downwind areas were perturbed by -50% to +50%. The change in PM2.5 concentrations in the downwind area depending on the change in NH3 emissions in the upwind area was the highest in spring, followed by winter. This was mainly attributed to the change in nitrate (NO3-), a secondary inorganic aerosol (SIA) that is a predominant constituent of PM2.5. Since NH3 is mainly emitted near the surface and vertical mixing is limited during the night, it was modeled that the aloft nitric acid (HNO3)-to-NO3- conversion in the morning hours was increased when the NH3 accumulated near the surface during nighttime begins to mix up within the Planetary Boundary Layer (PBL) as it develops after sunrise. This implies that the control of upwind and/or downwind NH3 emissions is effective at reducing PM2.5 concentrations in the downwind area even under NH3 rich conditions in Northeast Asia.

Direct and cross impacts of upwind emission control on downwind PM2.5 under various NH3 conditions in Northeast Asia

Emissions reductions in upwind areas can influence the PM_2.5 concentrations in downwind areas via long-range transport. However, few studies have assessed the impact of upwind PM_2.5 precursor controls on changes in downwind PM_2.5 concentrations. In this study, we analyzed the overall impact of PM_2.5 precursor emission controls in upwind areas on PM_2.5 in downwind areas with two types of impacts: "direct impact" and "cross impact." The former refers to PM_2.5 changes in downwind areas due to the transported PM_2.5 itself, whereas the latter represents PM_2.5 changes due to reactions between the transported gaseous precursors and intermediates (i.e., HNO₃) originating from upwind areas and locally emitted precursors (i.e. NH₃) in the downwind areas. As a case study, we performed air quality modeling for Northeast Asia for January 15-17, 2016 by setting China and South Korea as the upwind and downwind areas, respectively. To account for potential spatiotemporal variations in NH₃ emissions in downwind areas, we considered two NH₃ conditions. When NOx emissions in China were reduced by 35%, in downwind areas the PM_2.5 concentrations decreased by 2.2 μg/m³ under NH₃-rich conditions, while PM_2.5 concentrations increased by 2.3 μg/m³ under NH₃-poor conditions. The direct impact increased by 4.0 μg/m³ in both cases due to upwind NO_x disbenefit effects. However, the cross impacts led to a PM_2.5 decrease of 6.2 μg/m³ under NH₃-rich conditions versus a PM_2.5 increase of 1.7 μg/m³ under NH₃-poor conditions. We noted that PM_2.5 concentrations in the downwind areas may not improve unless a cross impact outweighs a direct impact. This may be one of the reasons why South Korea PM_2.5 concentrations have not declined despite efforts by China to reduce their PM_2.5 precursor emissions.

The impacts of COVID-19, meteorology, and emission control policies on PM2.5 drops in Northeast Asia

In January 2020, anthropogenic emissions in Northeast Asia reduced due to the COVID-19 outbreak. When outdoor activities of the public were limited, PM_2.5 concentrations in China and South Korea between February and March 2020 reduced by − 16.8 μg/m³ and − 9.9 μg/m³ respectively, compared with the average over the previous three years. This study uses air quality modeling and observations over the past four years to separate the influence of reductions in anthropogenic emissions from meteorological changes and emission control policies on this PM_2.5 concentration change. Here, we show that the impacts of anthropogenic pollution reduction on PM_2.5 were found to be approximately − 16% in China and − 21% in South Korea, while those of meteorology and emission policies were − 7% and − 8% in China, and − 5% and − 4% in South Korea, respectively. These results show that the influence on PM_2.5 concentration differs across time and region and according to meteorological conditions and emission control policies. Finally, the influence of reductions in anthropogenic emissions was greater than that of meteorological conditions and emission policies during COVID-19 period.

Surface ozone response to satellite-constrained NOx emission adjustments and its implications

Both surface and satellite observations have shown a decrease in NO_x emissions in East Asian countries in recent years. In order to reflect the recent NOx emission reduction and to investigate its impact on surface O₃ concentrations in Asian megacities, we adjusted two bottom-up regional emission inventories of which base years are 2006 (E2006) and 2010 (E2010), respectively. We applied direct and relative emission adjustments to both E2006 and E2010 to constrain NOx emissions using OMI NO₂ vertical column densities. Except for the relative emission adjustment with E2006, modeling results with adjusted emissions exhibit that NOx emissions over East Asian megacities (Beijing, Shanghai, Seoul, and Tokyo) in the bottom-up inventories are generally overestimated. When the direct emission adjustment is applied to E2006, model biases in the Seoul Metropolitan Area (SMA), South Korea are reduced from 24 ppb to 2 ppb for NOx (=NO+NO₂) and from -9 ppb to 0 ppb for O₃. In addition, NO₂ model biases in Beijing and Shanghai in China are reduced from 8 ppb to 18 ppb-0 ppb and 1 ppb, respectively. Daily maximum 8-h average O₃ model biases over the same places are decreased by 8 ppb and 14 ppb. Further analyses suggest that the reduction in domestic South Korean NO_x emissions plays a significant role in increasing O₃ concentrations in SMA. We conclude that the current strong drive to reduce NO_x emissions as part of the strategy to lower particulate matter concentrations in South Korea can account for increased O₃ concentrations in recent years and suggest that more aggressive NO_x emissions will be necessary soon.

Recent increase of surface particulate matter concentrations in the Seoul Metropolitan Area, Korea

Recent changes of surface particulate matter (PM) concentration in the Seoul Metropolitan Area (SMA), South Korea, are puzzling. The long-term trend of surface PM concentration in the SMA declined in the 2000s, but since 2012 its concentrations have tended to incline, which is coincident with frequent severe hazes in South Korea. This increase puts the Korean government’s emission reduction efforts in jeopardy. This study reports that interannual variation of surface PM concentration in South Korea is closely linked with the interannual variations of wind speed. A 12-year (2004–2015) regional air quality simulation was conducted over East Asia (27-km) and over South Korea (9-km) to assess the impact of meteorology under constant anthropogenic emissions. Simulated PM concentrations show a strong negative correlation (i.e. R = −0.86) with regional wind speed, implying that reduced regional ventilation is likely associated with more stagnant conditions that cause severe pollutant episodes in South Korea. We conclude that the current PM concentration trend in South Korea is a combination of long-term decline by emission control efforts and short-term fluctuation of regional wind speed interannual variability. When the meteorology-driven variations are removed, PM concentrations in South Korea have declined continuously even after 2012.

Influence of fossil-fuel power plant emissions on the surface fine particulate matter in the Seoul Capital Area, South Korea

The South Korean government plans to reduce region-wide annual PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) concentrations in the Seoul Capital Area (SCA) from 2010 levels of 27 µg/m(3) to 20 µg/m(3) by 2024. At the same time, it is inevitable that emissions from fossil-fuel power plants will continue to increase if electricity generation expands and the generation portfolio remains the same in the future. To estimate incremental PM2.5 contributions due to projected electricity generation growth in South Korea, we utilized an ensemble forecasting member of the Integrated Multidimensional Air Quality System for Korea based on the Community Multi-scale Air Quality model. We performed sensitivity runs with across-the-board emission reductions for all fossil-fuel power plants in South Korea to estimate the contribution of PM2.5 from domestic fossil-fuel power plants. We estimated that fossil-fuel power plants are responsible for 2.4% of the annual PM2.5 national ambient air quality standard in the SCA as of 2010. Based on the electricity generation and the annual contribution of fossil-fuel power plants in 2010, we estimated that annual PM2.5 concentrations may increase by 0.2 µg/m(3) per 100 TWhr due to additional electricity generation. With currently available information on future electricity demands, we estimated that the total future contribution of fossil-fuel power plants would be 0.87 µg/m(3), which is 12.4% of the target reduction amount of the annual PM2.5 concentration by 2024. We also approximated that the number of premature deaths caused by existing fossil-fuel power plants would be 736 in 2024. Since the proximity of power plants to the SCA and the types of fuel used significantly impact this estimation, further studies are warranted on the impact of physical parameters of plants, such as location and stack height, on PM2.5 concentrations in the SCA due to each precursor.

IMPLICATIONS

Improving air quality by reducing fine particle pollution is challenging when fossil-fuel-based electricity production is increasing. We show that an air quality forecasting system based on a photochemical model can be utilized to efficiently estimate PM2.5 contributions from and health impacts of domestic power plants. We derived PM2.5 concentrations per unit amount of electricity production from existing fossil-fuel power plants in South Korea. We assessed the health impacts of existing fossil-fuel power plants and the PM2.5 concentrations per unit electricity production to quantify the significance of existing and future fossil-fuel power plants with respect to the planned PM2.5 reduction target.

Likelihood of achieving air quality targets under model uncertainties

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

The influence of model resolution on ozone in industrial volatile organic compound plumes

Regions with concentrated petrochemical industrial activity (e.g., Houston or Baton Rouge) frequently experience large, localized releases of volatile organic compounds (VOCs). Aircraft measurements suggest these released VOCs create plumes with ozone (O3) production rates 2-5 times higher than typical urban conditions. Modeling studies found that simulating high O3 productions requires superfine (1-km) horizontal grid cell size. Compared with fine modeling (4-kmin), the superfine resolution increases the peak O3 concentration by as much as 46%. To understand this drastic O3 change, this study quantifies model processes for O3 and "odd oxygen" (Ox) in both resolutions. For the entire plume, the superfine resolution increases the maximum O3 concentration 3% but only decreases the maximum Ox concentration 0.2%. The two grid sizes produce approximately equal Ox mass but by different reaction pathways. Derived sensitivity to oxides of nitrogen (NOx) and VOC emissions suggests resolution-specific sensitivity to NOx and VOC emissions. Different sensitivity to emissions will result in different O3 responses to subsequently encountered emissions (within the city or downwind). Sensitivity of O3 to emission changes also results in different simulated O3 responses to the same control strategies. Sensitivity of O3 to NOx and VOC emission changes is attributed to finer resolved Eulerian grid and finer resolved NOx emissions. Urban NOx concentration gradients are often caused by roadway mobile sources that would not typically be addressed with Plume-in-Grid models. This study shows that grid cell size (an artifact of modeling) influences simulated control strategies and could bias regulatory decisions. Understanding the dynamics of VOC plume dependence on grid size is the first step toward providing more detailed guidance for resolution. These results underscore VOC and NOx resolution interdependencies best addressed by finer resolution. On the basis of these results, the authors suggest a need for quantitative metrics for horizontal grid resolution in future model guidance.

The influence of model resolution on ozone in industrial volatile organic compound plumes

Regions with concentrated petrochemical industrial activity (e.g., Houston or Baton Rouge) frequently experience large, localized releases of volatile organic compounds (VOCs). Aircraft measurements suggest these released VOCs create plumes with ozone (O3) production rates 2-5 times higher than typical urban conditions. Modeling studies found that simulating high O3 productions requires superfine (1-km) horizontal grid cell size. Compared with fine modeling (4-kmin), the superfine resolution increases the peak O3 concentration by as much as 46%. To understand this drastic O3 change, this study quantifies model processes for O3 and "odd oxygen" (Ox) in both resolutions. For the entire plume, the superfine resolution increases the maximum O3 concentration 3% but only decreases the maximum Ox concentration 0.2%. The two grid sizes produce approximately equal Ox mass but by different reaction pathways. Derived sensitivity to oxides of nitrogen (NOx) and VOC emissions suggests resolution-specific sensitivity to NOx and VOC emissions. Different sensitivity to emissions will result in different O3 responses to subsequently encountered emissions (within the city or downwind). Sensitivity of O3 to emission changes also results in different simulated O3 responses to the same control strategies. Sensitivity of O3 to NOx and VOC emission changes is attributed to finer resolved Eulerian grid and finer resolved NOx emissions. Urban NOx concentration gradients are often caused by roadway mobile sources that would not typically be addressed with Plume-in-Grid models. This study shows that grid cell size (an artifact of modeling) influences simulated control strategies and could bias regulatory decisions. Understanding the dynamics of VOC plume dependence on grid size is the first step toward providing more detailed guidance for resolution. These results underscore VOC and NOx resolution interdependencies best addressed by finer resolution. On the basis of these results, the authors suggest a need for quantitative metrics for horizontal grid resolution in future model guidance.

Combined UASB reactor and DAF/BF/anoxic/aerobic process for the removal of high-concentration organic matter and nutrients from slurry-type swine waste

This research aimed to effectively remove high-concentration organic matter and nutrients from slurry-type swine waste using a combined upflow anaerobic sludge blanket reactor with the dissolved air flotation/aerobic submerged biofilm/anoxic/aerobic process. The upflow anaerobic sludge blanket reactor was operated at an organics volumetric loading rate of 3.2-6.1 kg COD/m3/day, and the removal rates of COD were 53.9-65.5%. The removal rate of COD of the overall process was more than 99%. In the aerobic submerged biofilm, over 95% of ammonium nitrogen was removed at a volumetric loading rate of 0.08-0.16 kg NH4+-N/m3/day. The specific denitrification rate was 0.257 g NO3-N/g MLVSS/day and the removal rate of total nitrogen was 86.7%. Phosphorus was removed by flocculation in the dissolved air flotation process, and 0.16 g of PO4-P was removed by 1 g of ferric ion.

Ammonium nitrogen removal from slurry-type swine wastewater by pretreatment using struvite crystallization for nitrogen control of anaerobic digestion

Precipitation of ammonium together with phosphate and magnesium is a possible alternative for lowering the nitrogen content of wastewater. In this study we examine the removal of ammonium nitrogen and phosphorus from slurry-type swine wastewater containing high concentrations of nutrients by the addition of phosphoric acid along with either calcium oxide or magnesium oxide, which leads to the crystallization of insoluble salts such as hydroxyapatite and struvite. The struvite crystallization method showed a high capacity for the removal of nitrogen when magnesium oxide and phosphoric acid were used as the magnesium and phosphate sources, respectively. When it was applied to swine wastewater containing a high concentration of nitrogen, the injection molar ratio of Mg2+:NH4+:PO4(3-) that gave maximum ammonium nitrogen removal was 3.0:1.0:1.5.

Cloning and expression of cDNA for a human Sia alpha 2,3Gal beta 1, 4GlcNA:alpha 2,8-sialyltransferase (hST8Sia III)

The cDNA encoding human Sia-alpha2,3-Gal-beta1,4-GlcNAc-R:alpha2, 8-sialyltransferase, hST8Sia III, was isolated by screening of a human brain cDNA library with polymerase chain reaction-amplified DNA probe generated from the sequence of mouse ST8Sia III (mST8Sia III) and by 5' rapid amplification of cDNA ends of mRNA isolated from human brain tissues. Comparative analysis of the predicted protein-coding region between our cloned hST8Sia III and mST8Sia III showed 92 and 96% identities in the nucleotide and the amino acid sequence, respectively. The soluble hST8Sia III protein expressed in COS-7 showed an extremely high catalytic activity of transferring sialic acid through alpha2,8-linkage to intact fetuin glycoprotein, whereas the transferring activity was completely undetectable toward either alpha2,6-sialylated glycoprotein or desialylated glycoprotein acceptors. Northern analysis of hST8Sia III showed that the transcript corresponding to 11 kb was expressed in both human fetal and adult brain, while the expression of the 5.5-kb transcript was restricted to fetal liver, indicating that the expression of hST8Sia III is developmentally and tissue-specifically regulated.