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Source apportionment results of particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5) from two multivariate receptor models (positive matrix factorization, PMF; solver for mixture problem, SMP) were compared to assess the comparability of the results in view of model performance, source identification and source quantification. Two receptor models applied the same filter samples of PM2.5 collected between October 2012 and September 2013 in Seoul, Korea, not only reproduced well the measured PM2.5 mass concentrations, especially the SMP model (R2 = 0.99, bias = − 0.02 μg m−3), but also identified the four major PM2.5 contributors: biomass burning (PMF: 12.0%, SMP: 13.2%), vehicles (PMF: 18.9%, SMP: 10.2%), road dust (PMF: 5.0%, SMP: 11.2%) and secondary aerosol sources (PMF: 51%, SMP: 42.5%). The large sulfate fraction in the source profile is thought to be the high vehicle fraction in PMF. The major species constituting the secondary aerosols are OC (PMF: 11.7%, SMP: 16.2%), sulfate (PMF: 21.2%, SMP: 15.3%), nitrate (PMF: 29.4%, SMP: 44.1%), and ammonium (PMF: 16.7%, SMP: 16.9%). The difference in the contribution of nitrate and sulfate between the two models underscores that multiple receptor models may need to be applied to the same dataset to better understand their sources in polluted areas, particularly reducing secondary aerosols. [ABSTRACT FROM AUTHOR]

Knowledge of the variations of mass concentration, chemical composition and size distributions of submicron aerosols near roadways is of importance for reducing exposure assessment uncertainties in health effects studies. The goal of this study is to deploy and evaluate an Atmospheric Sciences Research Center-Mobile Laboratory (ASRC-ML), equipped with a suite of rapid response instruments for characterization of traffic plumes, adjacent to the Long Island Expressway (LIE) -- a high-traffic highway in the New York City Metropolitan Area. In total, four measurement periods, two in the morning and two in the evening were conducted at a location approximately 30m south of the LIE. The mass concentrations and size distributions of non-refractory submicron aerosol (NR-PM1) species were measured in situ at a time resolution of 1 min by an Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer, along with rapid measurements (down to 1Hz) of gaseous pollutants (e.g., HCHO, NO2, NO, O3, and CO2, etc.), black carbon (BC), and particle number concentrations and size distributions. The particulate organics varied dramatically during periods with highest traffic influences from the nearby roadway. The variations were mainly observed in the hydrocarbon-like organic aerosol (HOA), a surrogate for primary OA from vehicle emissions. The inorganic species (sulfate, ammonium, and nitrate) and oxygenated OA (OOA) showed much smoother variations -- with minor impacts from traffic emissions. The concentration and chemical composition of NR-PM1 also varied differently on different days depending on meteorology, traffic intensity and vehicle types. Overall, organics dominated the traffic-related NR-PM1 composition (> 60%) with HOA being the major fraction of OA. The traffic-influenced organics showed two distinct modes in mass-weighted size distributions, peaking at ~ 120 nm and 500 nm (vacuum aerodynamic diameter, Dva ), respectively. OOA and inorganic species appear to be internally mixed in the accumulation mode peaking at ~ 500--600 nm. The enhancement of organics in traffic emissions mainly occurred at ultrafine mode dominated by HOA, with little relation to the OOA-dominated accumulation mode. From Fast Mobility Particle Sizer (FMPS)measurements, a large increase in number concentration at ~10 nm (mobility number mean diameter, Dm) was also found due to traffic influence; though these particles typically contribute a minor fraction of total particle mass. Results here may have significant implications for near-highway air pollution characterization and exposure assessments. Our results suggest that exposure assessments must take into account the rapid variations of aerosol chemistry over short distances near roadways, and also that long-term monitoring of air pollutants throughout the day on different types of days is necessary to accurately gauge exposure to individuals. [ABSTRACT FROM AUTHOR]

This study improves the estimation of the self-purification coefficient for runoff analysis of pollution load using geomorphological factors. Formerly, the assimilative capacity, K, was estimated using a single geomorphological factor, Horton's form ratio, Sf. Here, K was divided into two factors, namely, a watershed self-purification coefficient (k) and a watershed form ratio (Sf). The watershed form ratio, Sf1, is the equivalent stream density and is considered an index of accessibility of the pollution load to the water body. Even though Sf had shown a clear reciprocal relationship with k, in agricultural areas, there is a limitation that the k, estimated by using an Sf only can't reflect the variability of land coverage characteristics and/or land use. In this study, a new geo-characteristic index (GCI), SR, which is composed of Sf and weighted flow accumulation ratio (Fr), is suggested. GIS and remote sensing technique were used to calculate Sf and Fr. Interestingly, a clear reciprocal relationship exists between k and SR, and this relationship seems to be stronger for agricultural areas, as urbanized areas have easier wash off due to the sewer network or paved surfaces. [ABSTRACT FROM AUTHOR]

Implementation of the Korean Total Maximum Daily Load Act calls for new tools to quantify nutrient losses from diffuse sources at a river basin district scale. In this study, it was elucidated that the nonlinear regression model (NRM) reduces the uncertainty of the boundary conditions of the water quality model. The NRM was proposed to analyse the delivery coefficients of surface waters and retention coefficients of pollutants. Delivery coefficient of pollution load was considered as a function of two variables: the watershed form ratio, S(f), which is a measurable geomorphologic variable and the retention coefficient, phi, which is an empirical constant representing the basin-wide retarding capacity of pollutant wash-off. This model was applied on the Geum River, one of the major basins in South Korea. The QUAL2E was used to simulate stream water quality using NRM. In this paper, we elucidate the possibility to use a nonlinear regression model for delivery and retention of nutrients in a drainage basin characterized as both data-rich and data-poor, and the magnitude of the nutrient loads and sources has been uncertain for a long time.

The Suppression Subtractive Hybridization (SSH) was used to isolate large numbers of low temperature-induced genes from the cold-treated winter barley (Hordeum vulgare L. cv. Dongbori). One hundred and sixty blti (barley low temperature-induced) cDNA clones were obtained. Northern blot analyses showed that several blti clones were differentially expressed by treatment of low temperature, NaCl, dehydration and ABA. One of the clones, blti2, was induced from 3 to 72 h after cold treatment while its transcript was detected only at 12 h after ABA treatment, indicating that the expression of blti2 by low temperature was regulated by an ABA-independent pathway. The full-length cDNA sequences were 944 nucleotides long and the open reading frame consisted of 492 nucleotides encoding 164 amino acids. Nucleotide sequences showed no sequence homology with the previously reported low temperature-responsive (LTR) barley genes, and the deduced amino acid sequences revealed that the blti2 contains three membrane-spanning regions. These results suggest that blti2 is a novel transmembrane protein induced by low temperature.

This study was undertaken to analyze the quantitative impact of a municipal wastewater treatment operation on the long-term water quality changes in a tributary of the Han-river, Korea from 1994 to 1999. Changes of land use pattern in the study watershed are quantitatively analyzed on the basis of land use maps that were created by classifying Landsat TM images acquired in April 1994 and March 1999. During this period, the average increase of land use area in terms of residence, cultivation, and barren was 5.89, 0.13, and 0.12%, respectively, and the corresponding decrease in water and forest area was 0.21 and 0.16%. The annual average reductions of BOD, T-N, and T-P by the municipal wastewater treatment operation were about 89, 11 and 27%, respectively. Spatial analysis of the pollution discharge from watershed was undertaken using a geographic information system (GIS) based model. A clear reciprocal relationship was found between the basin-wide self-purification coefficient and the watershed form ratio excepting a catchment area with water drain facilities. Due to land use changes over the five year study period, water quality change in terms of BOD, T-N, and T-P were (+)1.04 mg l(-1) (corresponding to a 13.7% increase of pollution), (+)0.58 mgl(-1) (10.0% increase), and (-)0.01 mg l(-1) (1.6% decrease). On the other hand, the effect of water quality restoration assessed by outward appearance during the same period was about 67.6, 39, and 36.5%, respectively. Consequently, it is understood that total stream water quality recovery in terms of BOD, T-N, and T-P were 81.3, 49.0, and 38.1% respectively, and that this included a negative contribution resulting from increased land use and a positive contribution due to the wastewater treatment operation at Inchon.

To investigate the chemical characteristics of fine particles in the Sihwa area, Korea, atmospheric aerosol samples were collected using a dichotomous PM10 sampler and two URG PM2.5 cyclone samplers during five intensive sampling periods between February 1998 and February 1999. The Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS), ion chromatograph (IC), and thermal manganese dioxide oxidation (TMO) methods were used to analyze the trace elements, ionic species, and carbonaceous species, respectively. Backward trajectory analysis, factor analysis, and a chemical mass balance (CMB) model were used to estimate quantitatively source contributions to PM2.5 particles collected in the Sihwa area. The results of PM2.5 source apportionment using the CMB7 receptor model showed that (NH4)2SO4 was, on average, the major contributor to PM2.5 particles, followed by nontraffic organic carbon (OC) emission, NH4NO3, agricultural waste burning, motor vehicle emission, road dust, waste incineration, marine aerosol, and others. Here, the nontraffic OC sources include primary anthropogenic OC emitted from the industrial complex zone, secondary OC, and organic species from distant sources. The source impact of waste incineration emission became significant when the dominant wind directions were from southwest and west sectors during the sampling periods. It was found that PM2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.