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As part of the Megacity Air Pollution Studies (MAPS)-Seoul campaign, three types of research flights were conducted over the Seoul Metropolitan Area (SMA) from May till June 2015 to measure the spatial distribution of a pollution plume near a power plant and petrochemical complex, the vertical profiles of pollutants on the western coast of Korea, and the pollutant distribution in the SMA. The pollution plume (~0–700 m) was highly concentrated and dominated by organic aerosol (OA), which very likely oxidized in the plume, as it showed slightly less oxidation near the source and significantly less oxidation at altitudes above the plume. One vertical profile displayed transitions in concentration and changes in the dominant components, suggesting that the particle sources and/or processing differed above ~1000 m; below 1000 m, where the total mass and OA concentrations were high, sulfate and likely transport sources predominated. The other profile, which was assessed during a separate flight, exhibited sharp increases in the OA number concentration and mean diameter, less oxidized organic content, and higher organic and nitrate concentrations above 1400 m, indicating high-altitude transport and a cleaner boundary layer. Finally, flights investigating the distributions of pollutants in the central, upwind, and downwind SMA regions generally detected high levels of oxidation downwind as well as different aerosol masses between the low and high altitudes. This study highlights the necessity of understanding the complex vertical structures of particle layers, such as those identified in and around the SMA, in order to facilitate the adoption of efficient air quality control strategies and enhance air quality forecasting.

Clouds, fogs, and rain can serve as useful integrators of both atmospheric aerosols and soluble trace gases. To better understand the chemical characteristics of sea fog and rain in the North and South Pacific Ocean, fog and rain were measured aboard the R/V ARAON in 2012 and 2014, respectively, as part of the Ship-borne Pole-to-Pole Observations (SHIPPO) project. The mean sea fog pH (3.59) was lower than the mean rain pH (4.54), reflecting greater inputs of non-sea-salt (nss)-SO42−. For the collected rain, nss-Ca2+ and nss-Mg2+ from mineral dust particles were the major contributors to acidity neutralization. NO3− concentrations, which are derived from scavenging of gaseous nitric acid and aerosol nitrate, were higher than NH4+ concentrations, indicating that terrestrial and/or local anthropogenic NO3− sources outweighed contributions from anthropogenic or biological oceanic NH3/NH4+ sources. The ratio of Cl−/Na+ in the sea fog was slightly lower than that in the sea water due to HCl volatilization from scavenged sea-salt particles. The ratio of NH4+/ nss-Ca2+ was lower in the rain than in the sea fog, revealing the influence of mineral dust particles at altitudes above the sea fog layer. The average sea fog water TOC concentration, 13.2 ppmC, was much higher than the measured TOC concentrations in marine fogs and clouds in other remote environments, likely due to continental influence; the TN and TOC concentrations in the fog water were much higher than those in the rain. The sea fog and rain chemical properties measured during research cruises like these enhance our understanding of wet deposition and cloud condensation nuclei sources and processes in the Pacific Ocean.

Ketene, a rarely measured reactive VOC, was quantified in the emission plumes from Daesan petrochemical facility in South Korea using airborne PTR-TOF-MS measurements. Ketene mixing ratios as high as ~ 40–50 ppb were observed in the emission plumes. Emission rates of ketene from the facility were estimated using a horizontal advective flux approach and ranged from 84–316 kg h−1. These emission rates were compared to the emission rates of major VOCs such as benzene, toluene, and acetaldehyde. Significant correlations (r2 > 0.7) of ketene with methanol, acetaldehyde, benzene, and toluene were observed for the peak emissions, indicating commonality of emission sources. The calculated average ketene OH reactivity for the emission plumes over Daesan ranged from 3.33–7.75 s−1, indicating the importance of the quantification of ketene to address missing OH reactivity in the polluted environment. The calculated average O3 production potential for ketene ranged from 2.98–6.91 ppb h−1. Our study suggests that ketene has the potential to significantly influence local photochemistry and therefore, further studies focusing on the photooxidation and atmospheric fate of ketene through chamber studies is required to improve our current understanding of VOC OH reactivity and hence, tropospheric O3 production.

Sparse matrix multiplication (spGEMM) is widely used to analyze the sparse network data, and extract important information based on matrix representation. As it contains a high degree of data parallelism, many efficient implementations using data-parallel programming platforms such as CUDA and OpenCL have been introduced on graphic processing units (GPUs). Several well-known spGEMM techniques, such as cuS- PARSE and CUSP, often do not utilize the GPU resources fully, owing to the load imbalance between threads in the expansion process and high memory contention in the merge process. Furthermore, even though several outer-product-based spGEMM techniques are proposed to solve the load balancing problem on expansion, they still do not utilize the GPU resources fully, because severe computation load variations exist among the multiple thread blocks.To solve these challenges, this paper proposes a new optimization pass called Block Reorganizer, which balances the total computations of each computing unit on target GPUs, based on the outer-product-based expansion process, and reduces the memory pressure during the merge process. For expansion, it first identifies the actual computation amount for each block, and then performs two thread block transformation processes based on their characteristics: 1) B-Splitting to transform a heavy-computation blocks into multiple small blocks and 2) B- Gathering to aggregate multiple small-computation blocks to a larger block. While merging, it improves the overall performance by performing B-Limiting to limit the number of blocks on each computing unit. Experimental results show that it improves the total performance of kernel execution by 1.43x, on an average, when compared to the row-product-based spGEMM, for NVIDIA Titan Xp GPUs on real-world datasets.

Graphics processing units (GPUs) have been commonly utilized to accelerate multiple emerging applications, such as big data processing and machine learning. While GPUs are proven to be effective, approximate computing, to trade off performance with accuracy, is one of the most common solutions for further performance improvement. Precision scaling of originally high-precision values into lower-precision values has recently been the most widely used GPU-side approximation technique, including hardware-level half-precision support. Although several approaches to find optimal mixed-precision configuration of GPU-side kernels have been introduced, total program performance gain is often low because total execution time is the combination of data transfer, type conversion, and kernel execution. As a result, kernel-level scaling may incur high type-conversion overhead of the kernel input/output data. To address this problem, this paper proposes an automatic precision scaling framework called PreScaler that maximizes the program performance at the memory object level by considering whole OpenCL program flows. The main difficulty is that the best configuration cannot be easily predicted due to various application- and system-specific characteristics. PreScaler solves this problem using search space minimization and decision-tree-based search processes. First, it minimizes the number of test configurations based on the information from system inspection and dynamic profiling. Then, it finds the best memory-object level mixed-precision configuration using a decision-tree-based search. PreScaler achieves an average performance gain of 1.33x over the baseline while maintaining the target output quality level.

The characteristics of primary gas/aerosol and secondary aerosol emissions were identified for small passenger vehicles using typical fuel types in South Korea (gasoline, liquefied petroleum gas (LPG), and diesel). The generation of secondary organic aerosol (SOA) was explored using the potential aerosol mass (PAM) oxidation flow reactor. The primary emissions did not vary significantly between fuel types, combustion technologies, or aftertreatment systems, while the amount of NH3 was higher in gasoline and LPG vehicle emissions than that in diesel vehicle emissions. The SOA emission factor was 11.7–66 mg kg-fuel−1 for gasoline vehicles, 2.4–50 mg kg-fuel−1 for non-diesel particulate filter (non-DPF) diesel vehicles (EURO 2–3), 0.4–40 mg kg-fuel−1 for DPF diesel vehicles (EURO 4–6), and 3–11 mg kg-fuel−1 for LPG vehicles (lowest). The carbonaceous aerosols (equivalent black carbon (eBC) + primary organic aerosol + SOA) of diesel vehicles in EURO 4–6 were reduced by up to 95% compared to those in EURO 2–3. The expected SOA yield increased through the hot-condition combustion section of a vehicle, over the SOA range of 0.2–155 μg m−3. These results provide the necessary data to analyze all types of SOA generated by the gas-phase oxidation in vehicle emissions in metropolitan areas.

In this report, magnetically recoverable sulfur-doped SnFe2O4/graphene (S-SFO/GR) nanohybrids have been successfully developed via a facile solvothermal method. The characterizations on the structural, morphology, and optical properties of the nanohybrids indicate that S-SFO particles are successfully embedded on the GR nanosheets. The photocatalytic activity has been evaluated by photocatalytic degradation of chlorotetracycline under visible light irradiation. Among the composites with various mass ratios, the quasi-first-order rate constant of the nanohybrids formed with 9wt% S in SFO and 15wt% GR (9S-SFO/GR-15) can reach as high as 1.83min-1, which is much higher than that of SFO (0.68min-1) and SFO/GR (0.91min-1), confirming the important role of S and GR for the photocatalytic process. The combination of the three components of S, SFO, and GR has enhanced the visible light absorption capability and inhibited the recombination of photogenerated electron-hole. The 9S-SFO/GR-15 nanohybrids can be recovered easily by a magnet and reused for five times with remained photocatalytic efficiency about 70%. A possible catalytic mechanism explaining the efficient photocatalytic performances of the prepared nanohybrids has been proposed.

A vehicle fleet representative of passenger vehicles driven in the Seoul Metropolitan Region was investigated for primary emissions and secondary chemistry. Exhaust was photochemically oxidized in a flow reactor to determine the ammonium nitrate (NH4NO3) aerosol formation potential from vehicles of gasoline, diesel and liquid petroleum gasoline (LPG) fuel types. Secondary formation of aerosol NH4NO3, was larger than primary emissions for all vehicle fuel types except diesel, for which negligible secondary NH4NO3 production was observed. Although diesel vehicles emitted more primary nitrogen oxides than other vehicle types, ammonia emitted from gasoline and liquid petroleum gasoline fuels types limited the secondary production of NH4NO3. The results suggest that gasoline and liquid petroleum gasoline vehicles with three-way catalysts could be an important source of ammonia for NH4NO3 aerosol formation in ammonia-limited environments, including the Seoul Metropolitan Region.

Modern GPUs are the most successful accelerators as they provide outstanding performance gain by using CUDA or OpenCL programming models. For maximum performance, programmers typically try to maximize the number of thread blocks of target programs, and GPUs also generally attempt to allocate the maximum number of thread blocks to their GPU cores. However, many recent studies have pointed out that simply allocating the maximum number of thread blocks to GPU cores does not always guarantee the best performance, and identifying proper number of thread blocks per GPU core is a major challenge. Despite these studies, most existing architectural techniques cannot be directly applied to current GPU hardware, and the optimal number of thread blocks can vary significantly depending on the target GPU and application characteristics. To solve these problems, this study proposes a just-in-time thread block number adjustment system using CUDA binary modification upon an LLVM compiler framework, referred to as the CTA-Limiter, in order to dynamically maximize GPU performance on real GPUs without reprogramming. The framework gradually reduces the number of concurrent thread blocks of target CUDA workloads using extra shared memory allocation, and compares the execution time with the previous version to automatically identify the optimal number of co-running thread blocks per GPU Core. The results showed meaningful performance improvements, averaging at 30%, 40%, and 44%, in GTX 960, GTX 1050, and GTX 1080 Ti, respectively.

Although approximate computing is widely used, it requires substantial programming effort to find appropriate approximation patterns among multiple pre-defined patterns to achieve a high performance. Therefore, we propose an automatic approximation framework called GATE to uncover hidden opportunities from any data-parallel program regardless of the code pattern or application characteristics using two compiler techniques, namely subgraph-level approximation (SGLA) and approximate thread merge (ATM). GATE also features conservative/aggressive tuning and dynamic calibration to maximize the performance while maintaining the TOQ level during runtime. Our framework achieves an average performance gain of 2.54x over the baseline with minimum accuracy loss.

The role of the gut microbiota in the pathogenesis of inflammatory bowel disease (IBD) has been in focus for decades. Although metagenomic observations in patients/animal colitis models have been attempted, the microbiome results were still indefinite and broad taxonomic presumptions were made due to the cross-sectional studies. Herein, we conducted a longitudinal microbiome analysis in a dextran sulfate sodium (DSS)-induced colitis mouse model with a two-factor design based on serial DSS dose (0, 1, 2, and 3%) and duration for 12 days, and four mice from each group were sacrificed at two-day intervals. During the colitis development, a transition of the cecal microbial diversity from the normal state to dysbiosis and dynamic changes of the populations were observed. We identified genera that significantly induced or depleted depending on DSS exposure, and confirmed the correlations of the individual taxa to the colitis severity indicated by inflammatory biomarkers (intestinal bleeding and neutrophil-derived indicators). Of note, each taxonomic population showed its own susceptibility to the changing colitis status. Our findings suggest that an understanding of the individual susceptibility to colitis conditions may contribute to identifying the role of the gut microbes in the pathogenesis of IBD.

Particulate matter (PM) in the atmosphere has wideranging health, environmental, and climate effects, many of which are attributed to fine-mode secondary organic aerosols. PM concentrations are significantly enhanced by primary particle emissions from traffic sources. Recently, in order to reduce CO2 and increase fuel economy, gasoline direct injected (GDI) engine technology is increasingly used in vehicle manufactures. The popularization of GDI technique has resulted in increasing of concerns on environmental protection. In order to better understand variations in chemical composition of particulate matter from emissions of GDI vehicle versus a port fuel injected (PFI) vehicle, a high time resolution chemical composition of PM emissions from GDI and PFI vehicles was measured at facility of Transport Pollution Research Center (TPRC), National Institute of Environmental Research (NIER), Korea. Continuous measurements of inorganic and organic species in PM were conducted using an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The HR-ToF-AMS provides insight into nonrefractory PM composition, including concentrations of nitrate, sulfate, hydrocarbon-like and oxygenated organic aerosol, and organic mass with 20 sec time resolution. Many cases of PM emissions during the study were dominated by organic and nitrate aerosol. An overview of observed PM characteristics will be provided along with an analysis of comparison of GDI vehicle versus PFI vehicle in PM emission rates and oxidation states.

Highly crystalline SnFe2O4 nanoparticles with high saturation magnetization and superior chlortetracycline (CTC) degradation efficiency was developed using a one-pot solvothermal method. The SnFe2O4 nanoparticles about 50 nm were prepared with a simple and cost-effective process performed at 200 °C. Superparamagnetism was observed from the SnFe2O4 nanoparticles with a high saturation magnetization of 74.3 emu g−1. The excellent photocatalytic activity of the SnFe2O4 nanoparticles was demonstrated through the high degradation efficiency of CTC under a visible light/SnFe2O4/9 mM H2O2 process. The effective degradation of CTC with the SnFe2O4 nanoparticles was attributed to the effective absorption of the visible light and the good separation ability of the electron–hole pairs. The synergy effect between SnFe2O4 and H2O2 was analysed, and the optimum initial concentration of H2O2 was determined to be 9 mM to achieve the best photocatalytic result on CTC. The SnFe2O4 nanoparticles also exhibited a fast and easy magnetic retrieval and a stable performance with continuous recycled usage.

As recent heterogeneous systems comprise multi-core CPUs and multiple GPUs, efficient allocation of multiple data-parallel applications has become a primary goal to achieve both maximum total performance and efficiency. However, the efficient orchestration of multiple applications is highly challenging because a detailed runtime status such as expected remaining time and available memory size of each computing device is hidden. To solve these problems, we propose a dynamic data-parallel application allocation framework called ADAMS. Evaluations show that our framework improves the average total execution device time by 1.85&times, over the round-robin policy in the non-shared-memory system with small data set.

According to the recent community-based structures enlargement, specification, and diversification. It needs appropriate construction materials in terms of intensity and environmental aspects. Thus, in manufacturing the cement using micro limestone powder that is main material. It is also expected to save energies and reduces CO2, by using the blast furnace slag and fly ash which are mitigated environmental load construction materials that emerged. In this research, the durability aspect tries to be grasped considering the chemical property according to the coherence of the hydration product. Consequently, the compressive strength was measured over 30Mpa on 3rd. In addition, according to the content of the limestone powder, the setting time is promoted. It has the feature expanded in the length change. And it is determined because the possibility of replacing the existing for construction material such as it is measured compared with the time to use the portland cement usually that flexural strength is high with the age 7 days ago, so it is sufficient.

In the past several decades, biofuels have emerged as candidates to help mitigate the issues of global warming, fossil fuel depletion and, in some cases, atmospheric pollution. To date, the only biofuels that have achieved any significant penetration in the global transportation sector are ethanol and biodiesel. The global consumption of biodiesel was rapidly increased from 2005. The goal of this study was to examine the chemical composition on particulate pollutant emissions from a diesel engine operating on several different biodiesels. Tests were performed on non-road diesel engine. Experiments were performed on 5 different fuel blends at 2 different engine loading conditions (50% and 75%). 5 different fuel blends were ultra-low sulfur diesel (ULSD, 100%), soy biodiesel (Blend 20% and Blend 100%) and canola biodiesel (Blend 20% and Blend 100%). The chemical properties of particulate pollutants were characterized using an Aerodyne High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS). Organic matter and nitrate were generally the most abundant aerosol components and exhibited maximum concentration of 1207 μg/m³ and 30 μg/m³, respectively. On average, the oxidized fragment families (C x H y O₁+, and C x H y O z +) account for ~13% of the three family sum, while ~87% comes from the C x H y + family. The two peaks of C₂H₃O₂ (m/z 59.01) and C₃H 7 O (m/z 59.04) located at approximately m/z 59 could be used to identify atmospheric particulate matter directly to biodiesel exhaust, as distinguished from that created by petroleum diesel in the AMS data.