Instream sensor results suggest soil–plant processes produce three distinct seasonal patterns of nitrate concentrations in the Ohio River Basin

The Ohio River Basin (ORB) is responsible for 35% of total nitrate loading to the Gulf of Mexico yet controls on nitrate timing require investigation. We used a set of submersible ultraviolet nitrate analyzers located at 13 stations across the ORB to examine nitrate loading and seasonality. Observed nitrate concentrations ranged from 0.3 to 2.8 mg L⁻¹ N in the Ohio River's mainstem. The Ohio River experiences a greater than fivefold increase in annual nitrate load from the upper basin to the river's junction with the Mississippi River (74–415 Gg year⁻¹). The nitrate load increase corresponds with the greater drainage area, a 50% increase in average annual nitrate concentration, and a shift in land cover across the drainage area from 5% cropland in the upper basin to 19% cropland at the Ohio River's junction with the Mississippi River. Time-series decomposition of nitrate concentration and nitrate load showed peaks centered in January and June for 85% of subbasin-year combinations and nitrate lows in summer and fall. Seasonal patterns of the terrestrial system, including winter dormancy, spring planting, and summer and fall growing-harvest seasons, are suggested to control nitrate timing in the Ohio River as opposed to controls by river discharge and internal cycling. The dormant season from December to March carries 51% of the ORB's nitrate load, and nitrate delivery is high across all subbasins analyzed, regardless of land cover. This season is characterized by soil nitrate leaching likely from mineralization of soil organic matter and release of legacy nitrogen. Nitrate experiences fast transit to the river owing to the ORB's mature karst geology in the south and tile drainage in the northwest. The planting season from April to June carries 26% of the ORB's nitrate and is a period of fertilizer delivery from upland corn and soybean agriculture to streams. The harvest season from July to November carries 22% of the ORB's nitrate and is a time of nitrate retention on the landscape. We discuss nutrient management in the ORB including fertilizer efficiency, cover crops, and nitrate retention using constructed measures.     

Pesticides in rain in four agricultural watersheds in the United States

Rainfall samples were collected during the 2003 and 2004 growing seasons at four agricultural locales across the USA in Maryland, Indiana, Nebraska, and California. The samples were analyzed for 21 insecticides, 18 herbicides, three fungicides, and 40 pesticide degradates. Data from all sites combined show that 7 of the 10 most frequently detected pesticides were herbicides, with atrazine (70%) and metolachlor (83%) detected at every site. Dacthal, acetochlor, simazine, alachlor, and pendimethalin were detected in more than 50% of the samples. Chlorpyrifos, carbaryl, and diazinon were the only insecticides among the 10 most frequently detected compounds. Of the remaining pesticide parent compounds, 18 were detected in fewer than 30% of the samples, and 13 were not detected. The most frequently detected degradates were deethylatrazine; the oxygen analogs (OAs) of the organophosphorus insecticides chlorpyrifos, diazinon, and malathion; and 1-napthol (degradate of carbaryl). Deethylatrazine was detected in nearly 70% of the samples collected in Maryland, Indiana, and Nebraska but was detected only once in California. The OAs of chlorpyrifos and diazinon were detected primarily in California. Degradates of the acetanilide herbicides were rarely detected in rain, indicating that they are not formed in the atmosphere or readily volatilized from soils. Herbicides accounted for 91 to 98% of the total pesticide mass deposited by rain except in California, where insecticides accounted for 61% in 2004. The mass of pesticides deposited by rainfall was estimated to be less than 2% of the total applied in these agricultural areas.     

Zonal management of arsenic contaminated ground water in Northwestern Bangladesh

This paper used ordinary kriging to spatially map arsenic contamination in shallow aquifers of Northwestern Bangladesh (total area  35,000 km²). The Northwestern region was selected because it represents a relatively safer source of large-scale and affordable water supply for the rest of Bangladesh currently faced with extensive arsenic contamination in drinking water (such as the Southern regions). Hence, the work appropriately explored sustainability issues by building upon a previously published study (Hossain et al., 2007; Water Resources Management, vol. 21: 1245–1261) where a more general nation-wide assessment afforded by kriging was identified. The arsenic database for reference comprised the nation-wide survey (of 3534 drinking wells) completed in 1999 by the British Geological Survey (BGS) in collaboration with the Department of Public Health Engineering (DPHE) of Bangladesh. Randomly sampled networks of zones from this reference database were used to develop an empirical variogram and develop maps of zonal arsenic concentration for the Northwestern region. The remaining non-sampled zones from the reference database were used to assess the accuracy of the kriged maps. Two additional criteria were explored: (1) the ability of geostatistical interpolators such as kriging to extrapolate information on spatial structure of arsenic contamination beyond small-scale exploratory domains; (2) the impact of a priori knowledge of anisotropic variability on the effectiveness of geostatistically based management. On the average, the kriging method was found to have a 90% probability of successful prediction of safe zones according to the WHO safe limit of 10 ppb while for the Bangladesh safe limit of 50 ppb, the safe zone prediction probability was 97%. Compared to the previous study by Hossain et al. (2007) over the rest of the contaminated country side, the probability of successful detection of safe zones in the Northwest is observed to be about 25% higher. An a priori knowledge of anisotropy was found to have inconclusive impact on the effectiveness of kriging. It was, however, hypothesized that a preferential sampling strategy that honored anisotropy could be necessary to reach a more definitive conclusion in regards to this issue.     

Population,Land Use and Deforestation in the Pan Amazon Basin: a Comparison of Brazil,Bolivia, Colombia,Ecuador, Perú and Venezuela

This paper discusses the linkages between population change, land use, and deforestation in the Amazon regions of Brazil, Bolivia, Colombia, Ecuador, Perú, and Venezuela. We begin with a brief discussion of theories of population–environment linkages, and then focus on the case of deforestation in the PanAmazon. The core of the paper reviews available data on deforestation, population growth, migration and land use in order to see how well land cover change reflects demographic and agricultural change. The data indicate that population dynamics and net migration exhibit to deforestation in some states of the basin but not others. We then discuss other explanatory factors for deforestation, and find a close correspondence between land use and deforestation, which suggests that land use is loosely tied to demographic dynamics and mediates the influence of population on deforestation. We also consider national political economic contexts of Amazon change in the six countries, and find contrasting contexts, which also helps to explain the limited demographic-deforestation correspondence. The paper closes by noting general conclusions based on the data, topics in need of further research and recent policy proposals.Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue     

Evaluating the impact of passengers on the safety of older drivers

PROBLEM: This study involved a quasi-induced exposure analysis of 4 years of crashes involving older drivers in the state of Kentucky. METHOD: Single- and multivehicle crashes were disaggregated according to the number of passengers: (a) no passenger, (b) one passenger, and (c) two or more passengers. RESULTS: Overall, the presence of two or more passengers was found to negatively impact the probability that drivers 75 years of age or older were at fault in crashes. Several potential factors were studied for interactive effects with passengers: vehicle occupant gender mix, time of the day, road curvature, grade, and number of lanes. The negative impact of passengers increased for some geometric road conditions. However, older drivers were found to be safer at night when carrying two or more passengers. The presence or absence of passengers was not found to affect the 65- to 74-year-old driver group. Groups of male vehicle occupants with a 75+ male driver were found to have high single-vehicle crash rates. IMPACT: These results are among the first to directly consider the effect of passengers on the crash-causing propensity of older drivers and the findings suggest more work is warranted to consider causes for the crash rate differences.     

Phytase,high-available-phosphorus corn,and storage effects on phosphorus levels in pig excreta

Phosphorus-based land application limits for manure have increased the importance of optimizing diet P management and accurately characterizing the bioavailability of manure P. We examined the effects of pig (Sus scrofa) diets formulated with high-available-P corn and phytase on P levels in excreta and slurry stored for 30, 60, 90, 120, and 150 d. Twenty-four pigs (approximately 14 kg each) were fed one of four low-P diets: (i) normal corn, no phytase (control); (ii) normal corn with 600 phytase units kg(-1) (PHY); (iii) high-available-P corn, no phytase (HAP); and (iv) high-available-P corn with 600 phytase units kg(-1) (HAP + PHY). Fresh fecal and stored slurry dry matter (DM) was analyzed for total phosphorus (TP), dissolved molybdate-reactive phosphorus (DRP), dissolved organic phosphorus (DOP), acid-soluble reactive phosphorus (ASRP), acid-soluble organic phosphorus (ASOP), and phytate phosphorus (PAP). The PHY, HAP, and HAP + PHY diets significantly (alpha = 0.05) decreased fecal TP 19, 17, and 40%, respectively, compared with the control. Dissolved reactive P was 36% lower in the HAP + PHY diet compared with the other diets. Relative fractions (percent of TP) of DRP, DOP, ASOP, and PAP in slurry generally decreased with storage time up to 150 d, with the largest decreases occurring within 60 to 90 d. Diet-induced differences in relative fractions of DRP, DOP, ASRP, and PAP were significant when averaged across storage times, simulating a mixed-age slurry. Relative fractions of DRP in simulated mixed-age slurries were higher in HAP and HAP + PHY diets, indicating that diet may affect P losses under certain P-based application scenarios.     

REDUCING THE RISK OF FISHERY RESOURCE DISASTERS: A BIOECONOMIC APPROACH TO SUSTAINABLE RESOURCE MANAGEMENT1

Abstract: Recognition is growing that fisheries must be both ecologically and commercially sustainable. The bioeconomic models proposed herein constitute an analytic framework capable of integrating the ethics and Societal values associated with fisheries preservation. Specifically, we focus on the normalized optimal (equilibrium) fish population, z*, a dimensionless variable representing biomass as a proportion of environmental capacity. We model z* as a function of (a) the dimensionless "bionomic growth ratio", γ, which is the ratio of the discount rate to the intrinsic population growth rate, and (b) the preservation coefficient, Ω, which is the ratio of the preservation value (a measure of Society's value for the stock) to price, assuming that the population growth rate and intrinsic growth rate are fixed. It is shown that increasing Ω significantly impacts z*, particularly for moderate values of γ (2 γ 4). Finally, stochastic population models are used to analyze the risk of a fish stock collapse due to harvesting pressures. The bioeconomic models and simulations herein described improve the accuracy and reliability of maximum sustainable yield management.     

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

     

Enhanced removal of heavy metals in primary treatment using coagulation and flocculation.

The goal of this study was to determine the removal efficiencies of chromium, copper, lead, nickel, and zinc from raw wastewater by chemically enhanced primary treatment (CEPT) and to attain a total suspended solids removal goal of 80%. Operating parameters and chemical doses were optimized by bench-scale tests. Locally obtained raw wastewater samples were spiked with heavy metal solutions to obtain representative concentrations of metals in wastewater. Jar tests were conducted to compare the metals removal efficiencies of the chemical treatment options using ferric chloride, alum, and anionic polymer. The results obtained were compared with those from other studies. It was concluded that CEPT using ferric chloride and anionic polymer is more effective than CEPT using alum for metals removal. The CEPT dosing of 40 mg/L ferric chloride and 0.5 mg/L polymer enhanced heavy metals removal efficiencies by over 200% for chromium, copper, zinc, and nickel and 475% for lead, compared with traditional primary treatment. Efficient metals capture during CEPT can result in increased allowable headworks loadings or lower metal levels in the outfall.     

An investigation of the kinetic processes influencing mercury emissions from sand and soil samples of varying thickness

Mercury flux from HgCl2-treated sand and untreated soil samples of varying thickness (0.5-15 mm) were measured in dark and light under a Teflon dynamic flux chamber. Mean emissions over a 5.5-d sampling period showed an increase with depth for sand samples between 0.5 and 2 mm, but increasing depth above 2 mm had no effect. First-order kinetic models showed strong goodness of fit to the data and explained a high degree ofvariability in the emissions profile of all sand samples (R = 0.70-0.98). Soil samples showed an initial emissions peak that was not correlated with depth, suggesting a very shallow process at work. However, longer-term "baseline" emissions, measured as mean emissions between days 4.5 and 5.5, did show a relationship with depth. First-order kinetic models showed good fit for soil samples up to 4 mm thick (R2 = 0.66-0.91); however, thicker samples did not show a consistent fit to first- or second-order kinetic models (1 degree R2 = 0.00-0.46; 2 degree R2 = 0.00-0.54). The data suggest that mercury emissions from soil samples may follow a multicomponent model for which more