Assessment of anthropogenic influences on surface water quality in urban estuary, northern New Jersey: multivariate approach

Concentrations of selected heavy metals (Cd, Cr, Cu, Pb, Ni, Fe, and Zn), nutrients (NO ₃ ^? and NH₃), fecal coliform colonies, and other multiple physical–chemical parameters were measured seasonally from 12 locations in an urban New Jersey estuary between 1994 and 2008. Stepwise regression, principal component analysis, and cluster analysis were used to group water quality results and sampling locations, as well as to assess these data’s relationship to sewage treatment effluents and the distance to the mouth of the river. The BOD₅, NH₃, NO ₃ ^? and fecal coliform counts clustered as one group and positively correlated to the distances from treated effluent and the measures of magnitude at the discharge points. Dissolved solids and most metal species scored high along a single principal component axes and were significantly correlated with the proximity to the industrialized area. From these data, one can conclude that the effluent discharge has been a main source of anthropogenic input to the Hackensack River over the past 15 years. Therefore, the greatest improvement to water quality would come from eliminating the few remaining combined sewer overflows and improving the removal of nutrients from treated effluents before they are discharged into the creeks and river.     

Artificial neural network analysis for reliability prediction of regional runoff utilization

Many factors in the reliability analysis of planning the regional rainwater utilization tank capacity need to be considered. Based on the historical daily rainfall data, the following four analyzing procedures will be conducted: the regional daily rainfall frequency, the amount of runoff, the water continuity, and the reliability. Thereafter, the suggested designed storage capacity can be obtained according to the conditions with the demand and supply reliability. By using the output data, two different types of artificial neural network models are used to build up small area rainfall–runoff supply systems for the simulation of reliability and the prediction model. They are also used for the testing of stability and learning speed assessment. Based on the result of this research, the radial basis function neural network (RBFNN) model, using the Gaussian function that has a similar trend as the nature as basic function, has better stability than using the back-propagation neural network (BPNN) model. Despite the fact that RBFNN was more reliable than BPNN, it still made a conservative estimate for the actual monitoring data. The error rate of RBFNN was still higher than the correction of BPNN 4-3-1-1. This should have significant benefit in the future application of the instantaneous prediction or the development of related intelligent instantaneous control equipment.     

Analysis of spatial and seasonal distributions of MODIS aerosol optical properties and ground-based measurements of mass concentrations in the Yellow Sea region in 2009

Satellite-retrieved data on aerosol optical depth (AOD) and Ångström exponent (AE) using a moderate resolution imaging spectrometer (MODIS) were used to analyze large-scale distributions of atmospheric aerosols in East Asia. AOD was relatively high in March (0.44?±?0.25) and low in September (0.24?±?0.21) in the East Asian region in 2009. Sandstorms originating from the deserts and dry areas in northern China and Mongolia were transported on a massive scale during the springtime, thus contributing to the high AOD in East Asia. However, whereas PM10 with diameters ≤10 μm was the highest in February at Anmyon, Cheongwon, and Ulleung, located leeward about halfway through the Korean Peninsula, AOD rose to its highest in May. The growth of hygroscopic aerosols attendant on increases in relative humidity prior to the Asian monsoon season contributed to a high AOD level in May. AE typically appears at high levels (1.30?±?0.37) in August due to anthropogenic aerosols originating from the industrial areas in eastern China, while AOD stays low in summer due to the removal process caused by rainfall. The linear correlation coefficients of the MODIS AOD and ground-based mass concentrations of PM10 at Anmyon, Cheongwon, and Ulleung were measured at 0.4~0.6. Four cases (6 days) of mineral dustfall from sandstorms and six cases (12 days) of anthropogenically polluted particles were observed in the central area of the Korean Peninsula in 2009. PM10 mass concentrations increased at both Anmyon and Cheongwon in the cases of mineral dustfall and anthropogenically polluted particles. Cases of dustfall from sandstorms and anthropogenic polluted particles, with increasing PM10 mass concentrations, showed higher AOD values in the Yellow Sea region.     

Changes of Soil Enzyme Activities By Simulated Acid and Nitrogen Deposition

Effects of acid and nitrogen depositions on soil microbial activities were studied in a laboratory-based experiment. Five treatments were added to forest soil for five weeks, and soil enzyme activities were determined along with chemical properties. There was little change in pH and nitrogen availability. Dehydrogenase, phosphatase and arylsulphatase activities were decreased by all the acidic treatments compared to the control, while urease activity was increased by the pH 4 treatment. at the same pH treatment, different nitric acid contents induced different urease activities. the results suggest that acid deposition would inhibit microbial activities and that more study is needed to elucidate the impact on nitrogen cycling in forests.     

Quaternary stratigraphy, sediment characteristics and geochemistry of arsenic-contaminated alluvial aquifers in the Ganges–Brahmaputra floodplain in central Bangladesh

This study focuses on the Quaternary stratigraphy, sediment composition, mineralogy, and geochemistry of arsenic (As)-contaminated alluvial aquifers in the Ganges–Brahmaputra floodplain in the central Bangladesh. Arsenic concentrations in 85 tubewells in Manikganj area, 70 km northwest of Dhaka City, range from 0.25 µg/L to 191 µg/L with a mean concentration of 33 µg/L. Groundwater is mainly Ca–HCO₃ type with high concentrations of dissolved As, Fe, and Mn, but low level of SO₄. The uppermost aquifer occurs between 10 m and 80 m below the surface that has a mean arsenic concentration of 35 µg/L. Deeper aquifer (> 100 m depth) has a mean arsenic concentration of 18 µg/L. Sediments in the upper aquifer are mostly gray to dark-gray, whereas sediments in the deep aquifer are mostly yellowing-gray to brown. Quartz, feldspar, mica, hornblende, garnet, kyanite, tourmaline, magnetite, ilmenite are the major minerals in sediments from both aquifers. Biotite and potassium feldspar are dominant in shallow aquifer, although plagioclase feldspar and garnet are abundant in deep aquifer sediments. Sediment composition suggests a mixed provenance with sediment supplies from both orogenic belts and cratons. High arsenic concentrations in sediments are found within the upper 50 m in drilled core samples. Statistical analysis shows that As, Fe, Mn, Ca, and P are strongly correlated in sediments. Concentrations of Cd, Cu, Ni, Zn, and Bi also show strong correlations with arsenic in the Manikganj sediment cores. Authigenic goethite concretions, possibly formed by bacteria, are found in the shallow sediments, which contain arsenic of a concentration as high as 8.8 mg/kg. High arsenic concentrations in aquifers are associated with fine-grained sediments that were derived mostly from the recycled orogens and relatively rapidly deposited mainly by meandering channels during the Early to Middle Holocene rising sea-level conditions.     

Hydrochemistry of urban groundwater, Seoul, Korea: the impact of subway tunnels on groundwater quality

Hydrogeologic and hydrochemical data for subway tunnel seepage waters in Seoul (Republic of Korea) were examined to understand the effect of underground tunnels on the degradation of urban groundwater. A very large quantity of groundwater (up to 63 million m³ year^− 1) is discharged into subway tunnels with a total length of 287 km, resulting in a significant drop of the local groundwater table and the abandonment of groundwater wells. For the tunnel seepage water samples (n = 72) collected from 43 subway stations, at least one parameter among pathogenic microbes (total coliform, heterotrophic bacteria), dissolved Mn and Fe, NH₄⁺, NO₃⁻, turbidity, and color exceeded the Korean Drinking Water Standards. Locally, tunnel seepage water was enriched in dissolved Mn (avg. 0.70 mg L^− 1, max. 5.58 mg L^− 1), in addition to dissolved Fe, NH₄⁺, and pathogenic microbes, likely due to significant inflow of sewage water from broken or leaking sewer pipes.Geochemical modeling of redox reactions was conducted to simulate the characteristic hydrochemistry of subway tunnel seepage. The results show that variations in the reducing conditions occur in urban groundwater, dependent upon the amount of organic matter-rich municipal sewage contaminating the aquifer. The organic matter facilitates the reduction and dissolution of Mn- and Fe-bearing solids in aquifers and/or tunnel construction materials, resulting in the successive increase of dissolved Mn and Fe. The present study clearly demonstrates that locally significant deterioration of urban groundwater is caused by a series of interlinked hydrogeologic and hydrochemical changes induced by underground tunnels.     

Overview of deaths associated with natural events, United States, 1979-2004.

Analysis of the National Center for Health Statistics' Compressed Mortality File showed that between 1979 and 2004, natural events caused 21,491 deaths in the United States. During this 26-year period, there were 10,827 cold-related deaths and 5,279 heat-related deaths. Extreme cold or heat accounted for 75 per cent of the total number of deaths attributed to natural events--more than all of deaths resulting from lightning, storms and foods, and earth movements, such as earthquakes and landslides. Cold-related death rates were highest in the states of Alaska, Montana, New Mexico, and South Dakota, while heat-related deaths were highest in the states of Arizona, Missouri, and Arkansas. These deaths occurred more often among the elderly and black men. Other deaths were attributed to lightning (1,906), storms and foods (2,741), and earth movements (738). Most deaths associated with natural events are preventable and society can take action to decrease the morbidity and mortality connected with them.     

An agenda for assessing and improving conservation impacts of sustainability standards in tropical agriculture

Sustainability standards and certification serve to differentiate and provide market recognition to goods produced in accordance with social and environmental good practices, typically including practices to protect biodiversity. Such standards have seen rapid growth, including in tropical agricultural commodities such as cocoa, coffee, palm oil, soybeans, and tea. Given the role of sustainability standards in influencing land use in hotspots of biodiversity, deforestation, and agricultural intensification, much could be gained from efforts to evaluate and increase the conservation payoff of these schemes. To this end, we devised a systematic approach for monitoring and evaluating the conservation impacts of agricultural sustainability standards and for using the resulting evidence to improve the effectiveness of such standards over time. The approach is oriented around a set of hypotheses and corresponding research questions about how sustainability standards are predicted to deliver conservation benefits. These questions are addressed through data from multiple sources, including basic common information from certification audits; field monitoring of environmental outcomes at a sample of certified sites; and rigorous impact assessment research based on experimental or quasi‐experimental methods. Integration of these sources can generate time‐series data that are comparable across sites and regions and provide detailed portraits of the effects of sustainability standards. To implement this approach, we propose new collaborations between the conservation research community and the sustainability standards community to develop common indicators and monitoring protocols, foster data sharing and synthesis, and link research and practice more effectively. As the role of sustainability standards in tropical land‐use governance continues to evolve, robust evidence on the factors contributing to effectiveness can help to ensure that such standards are designed and implemented to maximize benefits for biodiversity conservation.     

Linking irreplaceable landforms in a self‐organizing landscape to sensitivity of population vital rates for an ecological specialist

Irreplaceable, self‐organizing landforms and the endemic and ecologically specialized biodiversity they support are threatened globally by anthropogenic disturbances. Although the outcome of disrupting landforms is somewhat understood, little information exists that documents population consequences of landform disturbance on endemic biodiversity. Conservation strategies for species dependent upon landforms have been difficult to devise because they require understanding complex feedbacks that create and maintain landforms and the consequences of landform configuration on demography of species. We characterized and quantified links between landform configuration and demography of an ecological specialist, the dunes sagebrush lizard (Sceloporus arenicolus), which occurs only in blowouts (i.e., wind‐blown sandy depressions) of Shinnery oak (Quercus havardii) sand‐dune landforms. We used matrix models to estimate vital rates from a multisite mark‐recapture study of 6 populations occupying landforms with different spatial configurations. Sensitivity and elasticity analyses demonstrated demographic rates among populations varied in sensitivity to different landform configurations. Specifically, significant relationships between blowout shape complexity and vital rate elasticities suggested direct links between S. arenicolus demography and amount of edge in Shinnery oak sand‐dune landforms. These landforms are irreplaceable, based on permanent transition of disturbed areas to alternative grassland ecosystem states. Additionally, complex feedbacks between wind, sand, and Shinnery oak maintain this landform, indicating restoration through land management practices is unlikely. Our findings that S. arenicolus population dynamics depended on landform configuration suggest that failure to consider processes of landform organization and their effects on species’ population dynamics may lead to incorrect inferences about threats to endemic species and ineffective habitat management for threatened or endangered species. As such, successful conservation of these systems and the biodiversity they support must be informed by research linking process‐oriented studies of self‐organized landforms with studies of movement, behavior, and demography of species that dwell in them.