Abstract: Ship ballast water has been identified as one of four major environmental threats by the international maritime organization. This paper presents a portable on-site rapid detection system of microalgae in ship ballast water. The system consists of a microfluidic chip platform, LED light source and drive systems, optical detection system, ARM software and hardware system, power supply system and so on. Microalgae particles can go through the detection area inside the micro channels one by one by using a sheath fluid focus. The resulting chlorophyll fluorescence is converted to the electrical pulse signal by photodiode. The experimental results show that the system can quickly and accurately detect the ballast water living microalgae concentration. The minimum detectable microalgae size is about 3μm (mean diameter). This system has some advantages such as miniaturized, portable, fast, accurate and label free, and has great potential for on-site rapid detection of ship ballast water.
Abstract: In order to precisely determinate absorbance of all kinds of heavy metals in soil,7- important factors were optimized by mixed-level orthogonal design.For example Pb,discuss the factors influence degree on digestion and determination of Pb.Pb-absorbance trends within the area is expressed by the change of two-dimensional planar contour.Pb-absorbance distribution was drawn by 3D visualization technology.In order to optimize the orthogonal design,taking the optimal value of decentralized points in orthogonal test convert into taking the optimal value on a continuous plane. Using Minitab16 software analyzed the experimental results.The results showed that affecting Pb digestion Primary and secondary order is B(HF)> C(HNO3)> A(HClO4)> I(Acetylene flow rate)>D(HCL)>G (Assistant combustion gas)>H(Lamp current)>F(Burner height),that was adding 9 mlHNO3, 3mLHF, 3 mlHClO4 in soil samples, after microwave digestion, got the optimal Pb-absorbance value 0.304 under the the working conditions of atomic absorption spectrophotometer for Pb 217.0nm, slit width 1.3nm, burner height 4nm, assistant combustion gas 2.4 L/min, the lamp current 4.0mA, propane flow rate 4.0 L/min.
Abstract: The objective of this research is to construct an efficient way of monitoring water quality and assessing trophic state using remote sensing techniques in Qinshan Lake of Hangzhou, China. Two Landsat ETM+ images were acquired and simultaneous in situ measurements, sampling and analysis were conducted. Results of the study indicated that the ratio of ETM+1/ETM+3 was the most effective single band in estimating chlorophyll-a (Chl-a), followed by normalized ratio vegetation index (NRVI). Two multiple regression models with determination coefficients were further constructed between logarithmically transformed Chl-a and the combination of ETM+1/ETM+3, ETM+2/ETM+3, and ETM+3/ETM+4 of ten sample sites. The resulting models, Log (Chl-a)=1.65 + 0.87*(ETM+1 / ETM+3) 3.39*(ETM+2 / ETM+3) + 0.89*(ETM+3 / ETM+4), and Log (Chl-a)=2.94 1.37*(ETM+1 / ETM+3) + 0.40*(ETM+2 / ETM+3) 0.20*(ETM+3 / ETM+4), both showed strong ability to evaluate the distribution of Chl-a, with R2 of 0.72 and 0.92, respectively. Then two trophic state maps generated for Qinshan Lake using this model could identify zones with a higher potential for eutrophication, which turned out to be an appropriate method for synoptic monitoring of water quality in lakes. Similar modeling can be made for any given subtropical lake, to provide rapid and long term assessment of water quality and also useful information for decision making.
Abstract: Air quality has been deteriorated seriously in Shanghai as a result of urbanization and modernization. Meteorological conditions affect air pollution levels in the urban atmosphere significantly due to their important role in transport and dilution of the pollutants. This paper aims to investigate usability of statistical methods for prediction of SO2 concentration. Multiple linear regression (MLR) model and artificial neural network (ANN) model were used to predict next days SO2 concentrations. The calculated R2 values were 0.56 and 0.55 for MLR and ANN model, respectively. This result shows the MLR analysis, providing simple and faster application facilities, may also be useful for modeling the impacts of meteorological factors on SO2 levels besides the time consuming ANN model.
Abstract: Surface sediments of the west coast of Svalbard near Ny-Ålesund Spitsbergen were collected. PAHs of lake sediments (mean: 260, range: 11 - 1100 ng/g dry wt) were higher than previously report of surface lake sediment in Svalbard 1995, suggesting significant PAH contamination is occurring due to long-term atmospheric transport and local coal mining and fossil fuel sources, pointing to the role of Arctic lakes as potential reservoirs of semi-volatile organic compounds, including PAHs. Compound-specific analysis revealed different PAH patterns between Svalbard lakes and European high mountain lakes, showing higher proportions of low molecular weight compounds and lower levels of high molecular weight PAHs in Svalbard lakes. PAH indicator ratios suggest that the majority of PAHs in lake sediments have pyrogenic origins (coal mining, fossil fuel and biomass combustion), while coastal marine sediments were mainly contaminated by petroleum-derived PAHs (shipping activities in coastal areas, and perhaps as a result of an oil spill in 1986). Sediment fluxes of PAHs were estimated to be 0.2 - 22 ng cm-2 yr-1. The current PAH levels exceeded Canadian sediment quality guidelines, suggesting the presence of possible risks for aquatic organisms and the need for further studies.
Abstract: Dew is the condensation of atmospheric moisture on objects that have radiated sufficient heat to lower their temperature below the dew point temperature. Dew amount was collected by woodstick in Craex lasiocarpa which the main community at Sanjiang Plain. The average daily cumulated dew yield, which is the important parameter for dew harvesting, reach the peak in August or September. The result implies there are around one fifth days are unsuitable for dew condensation. Dew amount correlated negatively with wind speed.
Abstract: Environmental monitoring is increasingly playing a significant role in such aspects as environment protection, emergency disaster response and rescue, and macro decision-making etc. However, the intrinsic characteristics of complexity and spatial-temporal diversity, multi-scale features and heterogeneity brought from various means of data acquisition make the integration of multi-source data with high-efficiency becomes an international challenge nowadays. In this paper, the design and implementation of a vehicle-borne platform based on Internet of Things for environmental monitoring has been achieved. And then, by merging and matching environmental data and spatial data, more intensive multi-source environmental parameters and information can be obtained to act as meaningful supplementation of fixed environmental monitoring stations. The research of this paper is conductive to the transition of environmental monitoring from static methods to dynamic methods and from a small amount of data-based empirical model to sensor network-based quantitative model. Mobile environmental monitoring platform integrating with multiple sensors that can make environmental monitoring more timely, dynamic, integrated and intelligent will be the beneficial attempt and the development trend.
Abstract: Air quality has been deteriorated seriously in Shanghai as a result of urbanization and modernization. A three-layer Artificial Neural Network (ANN) model was developed to forecast the surface SO2 concentration. The subsequent SO2 concentration being the output parameter of this study was estimated by six input parameters such as preceding SO2 concentrations, average daily temperature, sea-level pressure, relative humidity, average daily wind speed and average daily precipitation. Levenberg-Marquarde (LM) backpropagation was tested as the best algorithm and the optimal neuron number for the LM algorithm was found to be eight. ANN testing outputs were proven to be satisfactory with correlation coefficients of about 0.765.
Abstract: The influences of Pacific sea-surface temperature (SST) change on the dust storm in Northern China are discussed by using the the singular value decomposition (SVD) method and the integrated numerical simulation and forecast system of dust weather in this paper. The statistical analysis show that the frequency of dust storms in the most of Northern China are increased during the La Niña, while decreased during the El Niño. The results of the control experiment by using the integrated numerical simulation and forecast system of dust weather are similar to the SVD analysis results.