Assessment of the sources of suspended particulate matter aerosol using US EPA PMF 3.0

The main purpose of this paper was to carry out a source apportionment of suspended particulate matter (SPM) samples using positive matrix factorization procedure. The central and local Government of Japan introduced strict emission regulations in 2002/10 and 2003/10, respectively, in curbing SPM pollution from major metropolitans. This paper also highlighted the impact of the measures taken by the central and local Government of Japan on the reduction of SPM and the contributions of sources. SPM samples were collected for 6 years starting from 1999 to 2005 at two sites, i.e., site A (urban) and site B (suburban) of Yokohama, Japan. Microwave digestion and inductively coupled plasma-mass spectroscopy (ICP-MS) were employed to measure Mg, Al, Ca, V, Cr, Mn, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ag, Cd, Cs, Ba, Pb and Bi, while water soluble ions (Na⁺, NH₄  ⁺_{4}^{\ \,+}, K⁺, Ca^2 +, Mg^2 +, Cl⁻, NO₃  ^-_{3}^{\ \,-} and SO₄  ^2-)_{4}^{\ \,2-}) as well as carbonaceous mass (EC and OC) were analyzed using ion chromatograph and CHN analyzer, respectively. The sources identified at two sites were automobile, soil dust, marine aerosol, mixed sources, and secondarily formed aerosol. Also, source quantification was performed. Automobile and soil dust were striking contributors at site A. Automobile and soil dust of SPM aerosol might be produced from local origin at current study areas. Besides, Asian dust had an impact on high concentrations of SPM aerosol in some certain period of the year due to the outflows of East Asian emission. In contrast, secondary aerosol in the form of sulfate and ammonium as well as mixed sources (coal, long-transported Cs, and other unknown sources) were remarkable at site B. Stationary/industrial combustion has apparently more impact on the release of SPM components at site B than A. Automobile regulations in 2002 and 2003, respectively, resulted in reduction of SPM by 28% for site A and 16% for site B. There was also net reduction of automobile contribution at both sites due to the above measures being implemented.     

Chemometric application in identifying sources of organic contaminants in Langat river basin

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.     

Discriminant analysis for the prediction of sand mass distribution in an urban stormwater holding pond using simulated depth average flow velocity data

The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m³ s^?1, representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size?>?0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5 %. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20 %) compared to group 2 (16.90 to 45.55 %). Two Fisher’s linear discriminant functions, F ₁ and F ₂, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F ₁?=??9.405?+?4232.119?×?A???1795.805?×?B?+?281.224?×?C, and F ₂?=??2.842?+?2725.137?×?A???1307.688?×?B?+?231.353?×?C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m³ s^?1, respectively. The model correctly predicts 88.9 and 100.0 % of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8 % are correctly classified. The model predicts that 31.4 % of the model domain areas consist of high-sand mass composition areas and the remaining 68.6 % comprise low-sand mass composition areas.     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature

This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.     

An Optimised Direct Lysis Method for Viral RNA Extraction and Detection of Foodborne Viruses on Fruits and Vegetables

Detection of norovirus (NoV) and hepatitis A virus (HAV) on fruits and vegetables using current standard methodologies can be inefficient. Method optimisat     

Geo-accumulation index and contamination factors of heavy metals (Zn and Pb) in urban river sediment

The aim of the present study was to appraise the levels of heavy metal contamination (Zn and Pb) in sediment of the Langat River (Selangor, Malaysia). Samples were collected randomly from 15 sampling stations located along the Langat River. The parameters measured were pH, redox potential, salinity, electrical conductivity, loss of ignition, cation exchanges capacity (Na, Mg, Ca, K), and metal ions (Zn and Pb). The geo-accumulation index (I _geo) and contamination factor (C _f) were applied to determine and classify the magnitude of heavy metal pollution in this urban river sediment. Results revealed that the I _geo of Pb indicated unpolluted to moderately polluted sediment at most of the sampling stations, whereas Zn was considered to be within background concentration. The I _geo results were refined by the C _f values, which showed Pb with very high C _f at 12 stations. Zinc, on the other hand, had low to moderate C _f values. These findings indicated that the sediment of the Langat River is severely polluted with Pb. The Zn concentration at most sampling points was well below most sediment quality guidelines. However, 40% of the sampling points were found to have a Pb concentration higher than the consensus-based probable effect concentration of 128 mg/kg (concentrations above this value are likely to cause harmful effects). This result not only highlights the severity of Pb pollution in the sediment of the Langat River, but also the potential risk it poses to the environment.     

Dissipation pattern and pre-harvest residue limit of abamectin in perilla leaves

The pre-harvest residue limit (PHRL) of abamectin (abamectin B1a and B1b) in Perilla frutescens leaves grown under greenhouse conditions were investigated using high-performance liquid chromatography with a fluorescence detector. Samples were extracted with acetonitrile. The extract was purified through a solid phase extraction procedure. Then the purified extract was derivatized with trifluoroacetic anhydride and N-methylimidazole to form a strong stable fluorescent derivative of abamectin. Finally, derivatized abamectins were conveyed to the detector via an Atlantis C₁₈ column, with water and methanol as a mobile phase. Calibration curves were linear over the calibration ranges with coefficients of determinants r ²?≥?0.999. The limits of detection and quantification were 0.0033 and 0.01 mg kg^?1 for abamectin B_1a and B_1b, respectively. Recovery was assessed in a control matrix at two different fortification concentrations, with three replicates for each concentration. Good recoveries were obtained for the target analytes and ranged from 82.11 to 93.03 %, with relative standard deviations of less than 8 %. The rate of disappearance of total abamectin on perilla leaves for recommended and double the recommended doses was described as first-order kinetics with a half-life of 0.7 days. Using the PHRL curve, we could predict the residue level of total abamectin to be 0.92 mg kg^?1 at 7 days before harvest or 0.26 mg kg^?1 at 4 days before harvest, which would be below the provisional MRL designed by the Korea Food and Drug Administration.