Groundwater Remediation and Aquifer Clean-Up: A Case Study

Groundwater was being remediated with pump and treat technology at a facility where the groundwater was contaminated with commonly used degreaser solvents. Hydraulic conductivity of the heterogeneous residuum was beneficiated by applying pneumatic fracturing technology. The remedial system was controlled and monitored by a sophisticated remote telemetry system. A case history follows.     

Rapid amino acid cycling in arctic and antarctic soils

Amino acids constitute one of the largest inputs of organic nitrogen (N) to most polar soils and have been hypothesized to be important in regulating vegetational succession and productivity in Arctic ecosystems. Our understanding of amino acid cycling in these soils, however, is poor. The aim of this study was to investigate the size and rate of turnover of the amino acid pool in a range of Arctic and Antarctic soils. Our results indicate that in polar soils with either high or low ornithogenic inputs the amino acid pool is small in comparison to the inorganic N pool (NO^–₃ and NH⁺₄). The free amino acid pool constituted only a small proportion of the total dissolved organic nitrogen (DON) pool in these soils. Here we show that these low concentrations may be due to rapid use by the soil microbial community in both Arctic and Antarctic soils. The turnover of the amino acid pool in soil was extremely rapid, with a half-life ranging from 2 to 24 h, indicating that this N pool can be turned over many hundred times each summer when polar soils are frequently unfrozen. The implications of amino acids in N cycling and plant and microbial nutrition are discussed.     

Change in vegetation cover in East Timor, 1989–1999

Forest resources play a key role and provide many basic needs to communities in developing economies. To assess the patterns of vegetation cover change, as a corollary of resource utilization, satellite imagery, ground truth data, and image processing techniques can be useful. This article is concerned with identifying change in major vegetation types in East Timor between 1989 and 1999, using Landsat Thematic Mapper data. The results highlight a significant level of deforestation and decline in foliage cover. All major vegetation cover types declined from 1989 to 1999, and there was a sizeable increase in degraded woodlands. This decline has had considerable impact on the livelihoods of rural and urban communities. Causes for these changes include: economic exploitation of abundant resources; and implications of transmigration policies implemented during Indonesian rule, resulting in increased competition for land and woodland resources. As the new nation of Timor‐Leste establishes itself, it must consider its current stock and distribution of natural capital to ensure that development efforts are geared towards sustainable outcomes. Without the knowledge of historical patterns of resource consumption, development efforts may, unwittingly, lead to continuing decline in forest resources.     

Rapid amino acid cycling in arctic and antarctic soils

Amino acids constitute one of the largest inputs of organic nitrogen (N) to most polar soils and have been hypothesized to be important in regulating vegetational succession and productivity in Arctic ecosystems. Our understanding of amino acid cycling in these soils, however, is poor. The aim of this study was to investigate the size and rate of turnover of the amino acid pool in a range of Arctic and Antarctic soils. Our results indicate that in polar soils with either high or low ornithogenic inputs the amino acid pool is small in comparison to the inorganic N pool (NO^? ₃ and NH⁺ ₄). The free amino acid pool constituted only a small proportion of the total dissolved organic nitrogen (DON) pool in these soils. Here we show that these low concentrations may be due to rapid use by the soil microbial community in both Arctic and Antarctic soils. The turnover of the amino acid pool in soil was extremely rapid, with a half-life ranging from 2 to 24 h, indicating that this N pool can be turned over many hundred times each summer when polar soils are frequently unfrozen. The implications of amino acids in N cycling and plant and microbial nutrition are discussed.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

Improvements of nano-SiO2 on sludge/fly ash mortar

Sewage sludge ash has been widely applied to cementitious materials. In this study, in order to determine effects of nano-SiO(2) additives on properties of sludge/fly ash mortar, different amounts of nano-SiO(2) were added to sludge/fly ash mortar specimens to investigate their physical properties and micro-structures. A water-binding ratio of 0.7 was assigned to the mix. Substitution amounts of 0%, 10%, 20%, and 30% of sludge/fly ash (1:1 ratio) were proposed. Moreover, 0%, 1%, 2%, and 3% of nano-SiO(2) was added to the mix. Tests, including SEM and compressive strength, were carried out on mortar specimens cured at 3, 7, and 28 days. Results showed that sludge/fly ash can make the crystals of cement hydration product finer. Moreover, crystals increased after nano-SiO(2) was added. Hence, nano-SiO(2) can improve the effects of sludge/fly ash on the hydration of mortar. Further, due to the low pozzolanic reaction active index of sludge ash, early compressive strengths of sludge/fly ash mortar were decreased. Yet, nano-SiO(2) could help produce hydration crystals, which implies that the addition of nano-SiO(2) to mortar can improve the influence of sludge/fly ash on the development of the early strength of the mortar.     

Will Observation Error and Biases Ruin the Use of Simple Extinction Models?

Abstract: Estimating the risk of extinction for populations of endangered species is an important component of conservation biology. These estimates must be made from data that contain both environmental noise in the year-to-year transitions in population size (so-called "process error"), random errors in sampling, and possible biases in sampling ( both forms of observation errors). To determine how much faith to place in estimated extinction rates, it is important to know how sensitive they are to observation error. We used three simple, commonly employed models of population dynamics to generate simulated population time series. We then combined random observation error or systematic biases with those data, fit models to the time series data, and observed how close the extinction dynamics of the fitted models compared with the dynamics of the underlying models. We found that systematic biases in sampling rarely affected estimates of extinction risk. We also found that even moderate levels of random observation error do not significantly affect extinction estimates except over a small range of process errors, corresponding to the region where extinction risk is most uncertain. With more substantial sampling error, estimates of extinction risk degraded rapidly. Field census techniques for a variety of taxa often involve observation errors within ±32% of actual population sizes. For typical time series used in conservation, therefore, we often may not need to be overly concerned about observation errors as an extra source of imperfection in our estimated extinction rates.