Fluorimetric determination of tetracycline antibiotics in animal derived foods using boron and nitrogen co-doped ceria-based nanoparticles.

An innovative synthesis of boron and nitrogen co-doped ceria-based nanoparticles (B/N-CeFNPs) with bright blue fluorescence emission is reported using the hydrothermal method. Based on the aggregation-induced emission enhancement (AIEE) effect between B/N-CeFNPs and chlortetracycline (CTC), a rapid detection method for CTC through fluorescence enhancement was developed. In addition, through the electron transfer process (ET), fluorescence resonance energy transfer (FRET) effect and static quenching between B/N-CeFNPs and oxytetracycline (OTC), a ratio fluorescence strategy for detecting OTC was generated. The fluorescence of B/N-CeFNPs at 410 nm can be effectively quenched by OTC, and new fluorescence emission appears at a wavelength of 500 nm. B/N-CeFNPs showed good linear responses with CTC and OTC in the range 0.1-1 µM and 1-40 µM, respectively. This system was used to simultaneously detect the CTC and OTC in milk and honey, realizing multi-residues detection of TCs in actual samples by using the same ceria-based fluorescence nanomaterial.

Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach.

Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set (5 years (2000-2004), 17 parameters) obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May (the 1st period) and June-August (the 2nd period). Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns.

Spatial distribution of heavy metals in Hong Kong's marine sediments and their human impacts: a GIS-based chemometric approach.

A geographic information system (GIS)-based chemometric approach was applied to investigate the spatial distribution patterns of heavy metals in marine sediments and to identify spatial human impacts on global and local scales. Twelve metals (Zn, V, Ni, Mn, Pb, Cu, Cd, Ba, Hg, Fe, Cr and Al) were surveyed twice annually at 59 sites in Hong Kong from 1998 to 2004. Cluster analysis classified the entire coastal area into three areas on a global scale, representing different pollution levels. Backward discriminant analysis, with 84.5% correct assignments, identified Zn, Pb, Cu, Cd, V, and Fe as significant variables affecting spatial variation on a local scale. Enrichment factors indicated that Cu, Cr, and Zn were derived from human impacts while Al, Ba, Mn, V and Fe originated from rock weathering. Principal component analysis further subdivided human impacts and their affected areas in each area, explaining 87%, 84% and 87% of the total variances, respectively. The primary anthropogenic sources in the three areas were (i) anti-fouling paint and domestic sewage; (ii) surface runoff, wastewater, vehicle emissions and marine transportation; and (iii) ship repainting, dental clinics, electronic/chemical industries and leaded fuel, respectively. Moreover, GIS-based spatial analysis facilitated chemometric methods.

Spatio-temporal patterns and source apportionment of coastal water pollution in eastern Hong Kong.

The comprehensive application of different multivariate methods and geographic information systems (GIS) was used to evaluate the spatio-temporal patterns and source apportionment of coastal water pollution in eastern Hong Kong. Fourteen variables were surveyed at 27 sites monthly from 2000 to 2004. After data pretreatment, cluster analysis grouped the 12 months into two groups, June-September and the remaining months, and divided the entire area into two parts, representing different pollution levels. Discriminant analysis determined that NO3- -N, DO, and temperature and TN, SD, PO4(3-)-P, and VSS were significant variables affecting temporal and spatial variations with 84% and 90% correct assignments, respectively. Five potential pollution sources were identified for each part by rotated principal component analysis, explaining 71% and 68% of the total variances, respectively. Receptor-based source apportionment revealed that most of the variables were primarily influenced by soil weathering and organic pollution, nutrient pollution (or agricultural runoff), and mineral pollution. Furthermore, GIS further facilitated and supported multivariate analysis results.