Reductive dissolution and sequestration of arsenic by microbial iron and thiosulfate reduction

Environmental Geochemistry and Health - Iron oxide and oxy-hydroxide are commonly used for remediation and rehabilitation of arsenic (As)-contaminated soil and water. However, the stability of As...     

Colloid mobilization and heavy metal transport in the sampling of soil solution from Duckum soil in South Korea

Environmental Geochemistry and Health - Colloid mobilization is a significant process governing colloid-associated transport of heavy metals in subsurface environments. It has been studied for the...     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.     

New directions for exploring the consequences of proactive behaviors: Introduction to the special issue

This special issue introduces new directions for exploring the consequences of proactive behaviors. The authors summarize the new scopes of consequences, new social contexts, and new methods in this exploration. They also identify several limitations of the existing literature and call for more future research in this stream.     

Transformational leadership and creativity: A meta‐analytic review and identification of an integrated model

We conduct a meta‐analytic review that yields important insights about the existing research on transformational leadership and creativity. Additionally, we propose and test an integrated model using meta‐analytic structural equation modeling (MASEM) and full information MASEM (FIMASEM) techniques to better understand the intervening mechanism through which transformational leadership acts on creativity. The results of the meta‐analysis of 127 studies show that most of the bivariate relationships among transformational leadership, employee creativity, and pre‐identified mediators are significant; further, geographic base of studies significantly moderates some of the relationships. The MASEM results indicate that several mediators intervene in the relationship between transformational leadership and creativity. Although the total effect of transformational leadership on creativity is positive, its direct effect is negative when mediators are included. Additionally, there are significant relationships among the mediators that can be theoretically supported, but have not been investigated in prior transformational leadership and creativity studies. On the basis of these findings, we provide conclusions and directions for future studies.     

Development of a probabilistic blood lead prediction model

A partially probabilistic blood lead prediction model has been developed, based on the US Environmental Protection Agency integrated exposure-uptake-biokinetic blood lead model (IEUBK model). This study translated the IEUBK model into a spreadsheet format. The uptake submodel incorporates uncertainty distributions for exposure and bioavailability parameters. The biokinetic submodel is duplicated with a table incorporating partitioning and decay of lead levels in the body. As a case study, the probabilistic model is applied to a lead exposure scenario involving a former smelter site in Sandy, Utah. The probabilistic model produces less biased estimates of means and standard deviations than the deterministic model. Parameter uncertainty is propagated in the model by the use of Monte Carlo simulation. Thus, sensitivity analysis is possible, and driving variables can be determined.     

Environmental factors affecting the standing crop of foraminifera in sublittoral and psammolittoral communities of a Long Island salt marsh

Representative samples from the epiphytic and psammolittoral communities were made during the summer of 1968 in North Sea Harbor, Southampton, Long Island, USA. In the epiphytic communities, the foraminifera were very patchy; 2.6% of the total samples accounted for 56.4% of the total foraminifera collected. The standing crop and species composition of the foraminifera changed throughout the summer. Two seasonal peaks were observed in the epiphytes. In early summer Protelphidium tisburyensis was the dominant form. In late July and August Elphidium incertum was dominant. Taken as a whole over the entire summer, the following species comprised the epiphytic foraminiferan community: Elphidium incertum (46.63%); Protelphidium tisburyensis (25.64%); Ammotium salsum (9.88%); Elphidium clavatum (6.74%); E. translucens (3.47%); Ammonia beccarii (2.83%); Ammobaculites dilatatus (2.08%); Trochammina inflata (1.8%); Elphidium advenum (< 1%); E. galvestonense (< 1%); E. gunteri (< 1%); Quinqueloculina lata (< 1%); Q. seminulum (< 1%) and Trochammina macrescens (< 1%). Although fewer species were found, many more foraminifera live in the benthos than in the epiphytic community. Taken as a whole, over the entire summer, the following species comprised the foraminifera in the psammolittoral community: Trochammina inflata (49.6%); Elphidium incertum (31.8%); Ammotium salsum (10.9%); Quinqueloculina seminulum (4.2%); Elphidium sp. (1.5); Protelphidium tisburyensis (0.9%); Ammonia beccarii (0.7%); Elphidium clavatum (< 0.1%); and E. translucens (< 0.1%). Three species, Ammotium salsum, Elphidium incertum and Trochammina inflata bloomed successively in the psammolittoral community. The distribution of the latter two species was correlated with the vertical and horizontal changes of grain size; Elphidium incertum distribution clustered around a median grain size of 0.1 mm, whereas Trochammina inflata clustered around a median grain size of 0.46 mm. The sediments were sampled both at high and low tide. No evidence was obtained to suggest migration of foraminifera through the sediments as a function of tidal cycle. Horizontal distribution of the foraminifera in the marsh was correlated with the flow patterns of very small rivulets in the study area. With respect to many species of foraminifera, the overlying epiphytic communities are not continuous with the psammolittoral communities below them in the water column. Protelphidium tisburyensis was an early summer dominant epiphyte, but was rare in the psammolittoral communities. Trochammina inflata, on the other hand, was dominant in the coarser, deeper sediments and was rare in the epiphytic community. Elphidium incertum is presumably a generalist species. It formed half the foraminiferan population throughout the water column. Ammotium salsum was also abundant in both communities.Supported by US AEC Contract AT (30-1) 3995. Ref. No. NYO 3995-16.Summarized from a thesis submitted by N. J. Matera in partial fulfillment of the requirements of Master of Arts at The City College of New York.University Institute of Oceanography of CUNY, Contribution No. 1.     

Non-renewable resource prices: Deterministic or stochastic trends?

In this paper, we examine temporal properties of 11 natural resource real price series from 1870 to 1990. Recent studies by Ahrens and Sharma [Trends in natural resource commodity prices: deterministic or stochastic? J. Environ. Econom. Manage. 33(1997)59–74], Berck and Roberts [Natural resource prices: will they ever turn up? J. Environ. Econom. Manage. 31(1996)65–78], and Slade [Grade selection under uncertainty: least cost last and other anomalies, J. Environ. Econom. Manage. 15(1988)189–205], among others, find that many non-renewable resource prices have a stochastic trend. We revisit this issue by employing a Lagrangian multiplier unit root test that allows for two endogenously determined structural breaks with and without a quadratic trend. Contrary to previous research, we find evidence against the unit root hypothesis for all price series. Our findings support characterizing natural resource prices as stationary around deterministic trends with structural breaks. We additionally show that both pre-testing for unit roots with breaks and allowing for breaks in the forecast model can improve forecast accuracy. Overall, the results in this paper are important in both a positive and normative sense; without an appropriate understanding of the dynamics of a time series, empirical verification of theories, forecasting, and proper inference are potentially fruitless.