The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters (MODIS) is the main aerosol optical depth (AOD) monitoring satellite instrument, and its accuracy and uncertainty need to be validated against ground based measurements routinely. The comparison between two ground AOD measurement programs, the United States Department of Agriculture (USDA) Ultraviolet-B Monitoring and Research Program (UVMRP) and the Aerosol Robotic Network (AERONET) program, confirms the consistency between them. The intercomparison between the MODIS AOD, the AERONET AOD, and the UVMRP AOD suggests that the UVMRP AOD measurements are suited to be an alternative ground-based validation source for satellite AOD products. The experiments show that the spatial-temporal dependency between the MODIS AOD and the UVMRP AOD is positive in the sense that the MODIS AOD compare more favorably with the UVMRP AOD as the spatial and temporal intervals are increased. However, the analysis shows that the optimal spatial interval for all time windows is defined by an angular subtense of around 1° to 1.25°, while the optimal time window is around 423 to 483 minutes at most spatial intervals. The spatial-temporal approach around 1.25° & 423 minutes shows better agreement than the prevalent strategy of 0.25° & 60 minutes found in other similar investigations.

On continental shelves, a front that separates the sea into well-mixed and stratified zones is usually formed in warm seasons due to spatial variations of tidal mixing. In this paper, using eight years of in situ hydrographic observations, satellite images of sea surface temperature (SST) and chlorophyll-a (Chl-a) concentration, and results of a tidal model, we investigate summer stratification in the Taiwan Strait and its dependence on tidal mixing, upwelling, and river diluted water plumes. In most regions of the strait the dominant role of tidal mixing in determining the thermohaline structure is confirmed by the correlation between the two; there are some regions, however, where thermohaline structure varies in different ways owing to significant influences of upwelling and river diluted water plumes. The well-mixed regions are mainly distributed on the Taiwan Bank and in the offshore regions off the Dongshan Island, Nanao Island, and Pingtan Island, while the northern and central Taiwan Strait and the region south of the Taiwan Bank are stratified. The critical Simpson-Hunter parameter for the region is estimated to be 1.78.

Resource-based water-saving potential has been recognized as the reduction of evapotranspiration and water loss of inefficient irrigation systems. In this paper, an improved evapotranspiration control model is applied to calculate resource-based water-saving potential, considering the influences of effective rainfall (uncontrolled evapotranspiration) and irrigated water (controlled evapotranspiration). Farmland in Baiyangdian Watershed, a highly productive area in northern China, is analyzed to determine the water-saving potential of irrigation processes. The water-saving potential was zero, 163.90 × 10⁶ m³, and 318.24 × 10⁶ m³ in wet, normal, and dry years, respectively, and was greater in years with less rainfall. Under the combined effect of rainfall, crop water consumption, and crop water requirements, the water-saving potential showed obvious temporal and spatial variations. July and August comprised almost 98.6% of the annual potential. In the northeast and southwest corner of the study area, potential approached zero. The potential was 1.53 times greater in the north-central than in the south-central area. The model can furnish the appropriate timing and region to water managers for implementing water-saving strategies.

We use the aerosol optical depth (AOD) measured by the moderate resolution imaging spectrometer (MODIS) onboard the Terra satellite, air pollution index (API) daily data measured by the Shanghai Environmental Monitoring Center (SEMC), and the ensemble empirical mode decomposition (EEMD) method to analyze the air quality variability in Shanghai in the recent decade. The results indicate that a trend with amplitude of 1.0 is a dominant component for the AOD variability in the recent decade. During the World Expo 2010, the average AOD level reduced 30% in comparison to the long-term trend. Two dominant annual components decreased 80% and 100%. This implies that the air quality in Shanghai was remarkably improved, and environmental initiatives and comprehensive actions for reducing air pollution are effective. AOD and API variability analysis results indicate that semi-annual and annual signals are dominant components implying that the monsoon weather is a dominant factor in modulating the AOD and API variability. The variability of AOD and API in selected districts located in both downtown and suburban areas shows similar trends; i.e., in 2000 the AOD began a monotonic increase, reached the maxima around 2006, then monotonically decreased to 2011 and from around 2006 the API started to decrease till 2011. This indicates that the air quality in the entire Shanghai area, whether urban or suburban areas, has remarkably been improved. The AOD improved degrees (IDS) in all the selected districts are (8.6±1.9)%, and API IDS are (9.2±7.1)%, ranging from a minimum value of 1.5% for Putuo District to a maximum value of 22% for Xuhui District.

An important and practical pattern of industrial symbiosis is rapidly developing: eco-industrial parks. In this study, we used social network analysis to study the network connectedness (i.e., the proportion of the theoretical number of connections that had been achieved) and related attributes of these hybrid ecological and industrial symbiotic systems. This approach provided insights into details of the network’s interior and analyzed the overall degree of connectedness and the relationships among the nodes within the network. We then characterized the structural attributes of the network and sub-network nodes at two levels (core and periphery), thereby providing insights into the operational problems within each eco-industrial park. We chose ten typical eco-industrial parks in China and around the world and compared the degree of network connectedness of these systems that resulted from exchanges of products, by-products, and wastes. By analyzing the density and nodal degree, we determined the relative power and status of the nodes in these networks, as well as other structural attributes such as the core-periphery structure and the degree of sub-network connectedness. The results reveal the operational problems created by the structure of the industrial networks and provide a basis for improving the degree of completeness, thereby increasing their potential for sustainable development and enriching the methods available for the study of industrial symbiosis.

The middle Yangtze Reach is one of the most developed regions of China. As a result, most lakes in this area have suffered from eutrophication and serious environmental pollution during recent decades. The aquatic biodiversity in the lakes of the area is thus currently under significant threat from continuous human activities. Testate amoebae (TA) are benthic (rarely planktonic) microorganisms characterized by an agglutinated or autogenous shell. Owing to their high abundance, preservation potential in lacustrine sediments, and distinct response to environmental stress, they are increasingly used as indicators for monitoring water quality and reconstructing palaeoenvironmental changes. However this approach has not yet been developed in China. This study presents an initial assessment of benthic TA assemblages in eight lakes of Lake Donghu in the region of Wuhan, China. Testate amoeba community structure was most strongly correlated to water pH. In more alkaline conditions, communities were dominated by Centropyxis aculeata, Difflugia oblonga, Pontigulasia compressa, Pon. elisa and Lesquereusia modesta. These results are consistent with previous studies and show that TA could be useful for reconstructing past water pH fluctuations in China. To achieve this, the next step will be to expand the database and build transfer function models.

Urban public health is an important global issue, and receives extensive attention. It is necessary to compare urban public health status among different cities, so that each city can define its own health patterns and limiting factors. The following assessment indicators were established to evaluate urban public health status: living conditions, physical health, education and culture, environmental quality, and social security. A weighted-sum model was used in combination with these indicators to compare the urban public health status in four cities— Beijing, New York, London, and Tokyo—using data for 2000–2009. Although the urban public health level of Beijing was lower than that of the other cities, it showed the greatest increase in this level over the study period. Different patterns of urban public health were identified: London had the most balanced, steady pattern (almost all factors performed well and developed stably); New York and Tokyo showed balanced, but unsteady patterns (most factors remained high, though social security and environmental quality fluctuated); Beijing had the most unbalanced, unsteady pattern (the different factors were at different levels, and education and culture and social security fluctuated). For enhanced urban public health status, environmental quality and education and culture clearly need to be improved in Beijing. This study demonstrates that a comparison of different cities is helpful in identifying limiting factors for urban public health and providing an orientation for future urban development.

Assessing the extent to which all bio-fuels that are claimed to be renewable are in fact renewable is essential because producing such renewable fuels itself requires some amount of non-renewable energy (NE) and materials. Using hybrid life cycle analysis (LCA)—from raw material collection to delivery of pellets to end users—the energy cost of wood pellet production in China was estimated at 1.35 J/J, of which only 0.09 J was derived from NE, indicating that only 0.09 J of NE is required to deliver 1 J of renewable energy into society and showing that the process is truly renewable. Most of the NE was consumed during the conversion process (46.21%) and delivery of pellets to end users (40.69%), during which electricity and diesel are the two major forms of NE used, respectively. Sensitivity analysis showed that the distance over which the pellets are transported affects the cost of NE significantly. Therefore the location of the terminal market and the site where wood resources are available are crucial to saving diesel.

It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modern cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals (from 0: 00 to 23: 59). All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600?GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy (about 10%–15% higher in RMSE), as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersections, we analyzed the spatio-temporal distribution of turn delays in three time scenarios (0: 00–0: 15, 8: 15–8: 30 and 12: 00–12: 15). It indicates that during one’s single trip in Beijing, average 60% of the travel time on the road networks is wasted on the intersections, and this situation is even worse in daytime. Although the 400?main intersections take only 2.7% of all the intersections, they occupy about 18% travel time.

Due to the influence of cloud and saturated waveforms, ICESat data contain many contaminated elevation data that cannot be directly used in examining surface elevation and change. This study provides a novel solution for removing bad data and getting clean ICESat data for land applications by using threshold values of reflectivity, saturation, and gain directly from ICESat’s GLAS (Geoscience Laser Alteimeter System) 01, 05, and 06 products. It is found that each laser campaign needs different threshold compositions to assure qualified ICESat data and that bad data removal rates range from 9.6% (laser 2A) to 62.3% (laser 2B) for the test area in the Yili watershed, China. These thresholds would possibly be used in other regions to extract qualified ICESat footprints for land applications. However, it is recommended to use the steps proposed here to further examine the transferability of threshold values for other regions of different elevations and climate regimes. As an example, the resulting ICESat data are applied to examine lake level changes of two lakes in the study area.

Using the hydrological and meteorological data in the Kaidu River Basin during 1957–2008, we simulated the hydro-climatic process by back-propagation artificial neural network (BPANN) based on wavelet analysis (WA), and then compared the simulated results with those from a multiple linear regression (MLR). The results show that the variation of runoff responded to regional climate change. The annual runoff (AR) was mainly affected by annual average temperature (AAT) and annual precipitation (AP), which revealed different variation patterns at five time scales. At the time scale of 32-years, AR presented a monotonically increasing trend with the similar trend of AAT and AP. But at the 2-year, 4-year, 8-year, and 16-year time-scale, AR presented nonlinear variation with fluctuations of AAT and AP. Both MLR and BPANN successfully simulated the hydro-climatic process based on WA at each time scale, but the simulated effect from BPANN is better than that from MLR.

It is well known that during CO₂ geological storage, density-driven convective activity can significantly accelerate the dissolution of injected CO₂ into water. This action could limit the escape of supercritical CO₂ from the storage formation through vertical pathways such as fractures, faults and abandoned wells, consequently increasing permanence and security of storage. First, we investigated the effect of numerical perturbation caused by time and grid resolution and the convergence criteria on the dissolution-diffusion-convection (DDC) process. Then, using the model with appropriate spatial and temporal resolution, some uncertainty parameters investigated in our previous paper such as initial gas saturation and model boundaries, and other factors such as relative liquid permeability and porosity modification were used to examine their effects on the DDC process. Finally, we compared the effect of 2D and 3D models on the simulation of the DDC process. The above modeling results should contribute to clear understanding and accurate simulation of the DDC process, especially the onset of convective activity, and the CO₂ dissolution rate during the convection-dominated stage.