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1.
Environ Pollut ; 223: 161-169, 2017 Apr.
Article in English | MEDLINE | ID: mdl-28131482

ABSTRACT

Aquaculture is a booming industry in the world and China is the largest producer and exporter of aquatic products. To prevent and treat diseases occurred in aquaculture, antibiotics are widely applied. However, the information of antibiotics used in Chinese aquaculture is still limited. Based on peer-reviewed papers, documents, reports, and even farmer surveys, this review summarized antibiotics used in Chinese aquaculture. In 2014, more than 47.4 million tonnes of farmed aquatic products were produced in mainland China. The outputs in the east and south parts of China can reach as much as 600 times higher than those in the northwest areas, which is clearly separated by the "Hu Line" - a line that marks a striking difference in the distribution of population. A total of 20 antibiotics belonging to eight categories have been reported for use, mainly via oral administration. However, only 13 antibiotics have been authorized for application in Chinese aquaculture and 12 antibiotics used are not authorized. Totally, 234 cases on antibiotic residues in Chinese aquatic products were recorded, including 24 fish species, eight crustacean species, and four mollusk species. Thirty-two antibiotics have been detected in aquatic products; quinolones and sulfonamides were the dominated residual chemicals. For specific compound, ciprofloxacin, norfloxacin, and sulfisoxazole have the highest concentrations. Except for a few cases, all residual concentrations were lower than the maximum residue limits. Through the consumption of aquatic products tainted by antibiotics, humans may acquire adverse drug reactions or antibiotic-resistant bacteria. However, the risk of antimicrobial resistance in human body, when exposed to antibiotics at sub-inhibitory concentrations, has not been exhaustively considered in the risk assessment. In addition, a national comprehensive investigation on the amount of antibiotics used in Chinese aquaculture is still needed in future studies.


Subject(s)
Anti-Bacterial Agents/toxicity , Aquaculture/methods , Fishes , Food Contamination , Animals , Anti-Bacterial Agents/analysis , Bacteria/drug effects , China , Drug Residues/analysis , Drug Residues/toxicity , Drug Utilization , Humans , Risk Assessment
2.
Environ Pollut ; 219: 612-619, 2016 Dec.
Article in English | MEDLINE | ID: mdl-27344088

ABSTRACT

Rapid industrialization and urbanization has caused large emission and potential contamination of mercury (Hg) in urban environment. However, little is known about the impact of socioeconomic factor on Hg accumulation in sediment. In the present study, historical record of anthropogenic Hg deposition of Shanghai was reconstructed by using three sediment cores from three park lakes (C1: Luxun Park; C2: Fuxing island Park; C3: Xinjiangwan Park). Meanwhile, the influence of socioeconomic factor to Hg emissions and sedimentary record was calculated based on an extended STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The profiles of Hg levels and fluxes in the three sediment cores showed that Shanghai has recently undergone urbanization. The anthropogenic Hg fluxes exhibited fluctuant increases from ∼1900 to present and accelerated after the establishment of the People's Republic of China in 1949 and the implementation of reform and opening up policy in 1978. The mean flux ratios of Hg in post-2000 were 2.2, 12, and 2.7 in the C1, C2 and C3 cores, respectively. The extended STIRPAT model was constructed based on strong positive relationships between socioeconomic factors and Hg fluxes, revealing that the proportion of coal consumption, the urbanization rate, and the proportion of heavy industry were the three most important driving factors for Hg accumulations in urban sediment of Shanghai.


Subject(s)
Coal , Geologic Sediments/chemistry , Industrial Development , Lakes/chemistry , Mercury/analysis , Urbanization , Water Pollutants, Chemical/analysis , Water Pollutants, Chemical/economics , China , Models, Statistical
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