Ecosystem-inspired model and artificial intelligence predicts pollutant consumption capacity by coagulation in drinking water treatment

Conventional methods for water and wastewater treatment are energy-intensive, notably at the stage of coagulation–flocculation, calling for new strategies to predict pollutant reduction because the amount of energy consumed is related to how much of the pollutant is treated. Here we developed a model, named Bio-logic, inspired by ecosystems, where pollutants represent organisms, coagulants are food, and the wider environmental conditions are the living environment. Artificial intelligence was used to learn the biological behavior, which enabled an accurate prediction of the amount of pollutant reduction. Results show that pseudo-biological objects that have a strong affinity for biological food, such as turbidity, total phosphorus, ammonia nitrogen and the potassium permanganate index, induced a strong correlation, between measured pollutant consumption capacity and predicted values. For instance, R² correlation coefficients are 0.97 for turbidity and 0.92 for the potassium permanganate index in the laboratory; and 0.99 for turbidity, 0.90 for total phosphorus, 0.75 for ammonia nitrogen and 0.63 for the potassium permanganate index in water treatment plants. Overall, our findings demonstrate that artificial intelligence can use the water Bio-logic model to predict the pollutant consumption capacity.

     

A call to action for climate change research on Caribbean dry forests

Regional Environmental Change - Tropical dry forest (TDF) is globally one of the most threatened forest types. In the insular Caribbean, limited land area and high population pressure have resulted...     

Occurrence and fate of the phytotoxin juglone in alley soils under black walnut trees

Juglone (5-hydroxy-1,4-napthoquinone) is a chemical released by walnut trees, which can be toxic at various levels to several plant species. A balance among competing source and sink mechanisms and rates will ultimately determine whether juglone is capable of attaining sufficient levels to be allelopathic to intercrops in a walnut tree agroforestry system. In this study, juglone's release, accumulation, and decline in soil are explored using data from soil beneath a black walnut tree (Juglans nigra L) alley cropping system, greenhouse pot studies, and laboratory sorption/degradation studies. Juglone pore water concentrations estimated from extracts of surficial soil from beneath the alley cropping system exceeded the lowest solution culture toxicity levels reported for some plants of 10(-7) M, but did not exceed the inhibition threshold reported for typical intercrops such as maize and soybeans 10(-5) M. Further assessment of the likely persistence of juglone in soils indicated that juglone is both microbially and abiotically degraded, and that it will be particularly short-lived in soils supporting microbial activity. However, walnut seedlings planted in sand-filled pots clearly showed that juglone is released in measurable quantities to the soil's rhizosphere. Therefore, juglone accumulation in low fertility soils is plausible, and may still be worthy of consideration in management of alley agroforestry systems.     

Modeling military trampling effects on glacial soils in the humid continental climate of southern New York

The purpose of this research is to create a baseline model of soil compaction response to trampling and a methodology to model the effects of trampling on soil. Although trampling studies have been conducted in the past, the analysis of military training in part provides a different perspective and approach. The data showed bulk densities remained relatively constant for a time and then began to increase at an increasing rate for several hundred passes and finally leveled and remained at or below 1.30 g/cm3 through the remainder of the experiment. Mathematical models were created based on empirical data from a trampling experiment using a more standard logistical growth curve as well as curves based on Weibull and gamma cumulative distribution functions (CDFs). The experiment and the resulting models give quantifiable continuous inference on the effects of trampling, as opposed to the existing qualitative assessments. These baseline models will be the foundation for future studies of land management when trampling occurs.     

Consumer product-related eye injury in the United States, 1998-2002

PROBLEM: Eye injury is currently a leading cause of visual impairment and monocular blindness in the United States. Information regarding consumer products associated with eye injuries can have important implications for the prevention of these injuries. METHODS: The National Electronic Injury Surveillance System (NEISS) was used to describe the types of consumer products associated with emergency department treated eye injuries in the United States from 1998 through 2002. RESULTS: The leading product type associated with eye injuries was welding equipment followed by household cleaners, basketball equipment, workshop equipment, and adhesives. Eye injuries attributed to hardware, tools, construction, sports, toys, and lawn equipment were more common among males. In females, eye injuries attributable to chemicals, housewares, storage and organization, and bed and bath items were more common. Differences were also apparent across the age spectrum. CONCLUSION: This study identified specific products and categories of products frequently associated with eye injury and prevention initiatives should focus on these items. IMPACT ON INDUSTRY: This study has identified consumer products associated with eye injuries requiring medical treatment in the United States. Manufacturers of these products could be encouraged to add or strengthen safety messages regarding the potential for eye injury.     

Motor vehicle fatalities among Gulf War era veterans: characteristics, mechanisms, and circumstances

OBJECTIVES: Our objective was to describe fatal motor vehicle crashes (MVC) among veterans of the 1991 Gulf War era and to compare the distribution of crash and individual characteristics between those deployed to the Gulf War (GWV) and those not deployed (NDV). METHODS: We compared individual characteristics, crash mechanisms, and crash circumstances between 765 GWV and 553 NDV who died from MVC within the first five years of the war, between May 1991 and December 1995. RESULTS: Overall, GWV and NDV who died from a MVC were more likely to be enlisted males (97%), 21-30 years old (72%), have a high school education or less (91%), drive a passenger car (52%), and not use restraints (60%). The overall annual rate of motor vehicle fatalities for GWV (23.6 per 100,000; 95% confidence interval: 21.9-25.3) was significantly greater than the rate for NDV (15.9, 95% CI: 14.6-17.3). GWV with the highest motor vehicle fatality rates include males (24.8, 95% CI: 23.0-26.6), 17-20 year olds (105.0, 95% CI: 78.2-138.1), and those not married (27.3, 95% CI: 25.1-30.1). Adjusting for differences in age distribution across GWV and NDV did not account for the difference in rates. Characteristics of MVC fatalities that were over-represented among GWV include serving as regular active duty (p = 0.001), having a high school education or less (p = 0.01), being involved in a single-vehicle crash (p = 0.008), and dying within the first hour following the crash (p = 0.004). Also, we identified a greater proportion of alcohol-related crashes among GWV during the late night and early morning hours. CONCLUSIONS: The highest rates of motor vehicle fatality among young, single males in the military mirror the experience of the general population. Further research is necessary to determine modifiable risk factors that can be targeted for specific interventions and whether the elevated late night alcohol-related crash rate among GWV is an effect of deployment or an inherent population bias among those selected for operational deployments.     

Effects of Glomus mosseae on the toxicity of heavy metals to Vicia faba

A glasshouse pot experiment was conducted to investigate effects of the arbuscular mycorrhizal fungus Glomus mosseae on the growth of Vicia faba and toxicity induced by heavy metals （HMs） （Cu, Zn, Pb and Cd） in a field soil contaminated by a mixture of these metals. There was also uninoculation treatment （NM） simultaneously. Mycorrhizal （GM） plants have significantly increased growth and tolerance to toxicity induced by heavy metals compared with NM plants. P uptake was significantly increased in GM plants. Mycorrhizal symbiosis reduced the transportation of HMs fi＇om root to shoot by immobilizing HMs in the mycorrhizal, shown by increasing the ratios of HMs from root to shoot. Oxidative stress, which can induce DNA damage, is an important mechanism of heavy metal toxicity. GM treatment decreased oxidative stress by intricating antioxidative systems such as peroxidases and non-enzymic systems including soluble protein. The DNA damage induced by heavy metals was detected using comet assay, which showed DNA damage in the plants was decreased by the GM treatment.     

Towards a multidisciplinary and integrated strategy in the assessment of adverse health effects related to air pollution: the case study of Cracow (Poland) and asthma

Complex interaction between anthropogenic activities, air quality and human health in urban areas, such as in Cracow sustains the need for the development of an interdisciplinary and integrated risk-assessment methodology. In such purpose, we propose a pilot study performed on asthmatics and based on a combined use of a biomarker, such as metallothionein 2A (MT-2A) in the characterization of human exposure to one or a mixture of pollutants and of Geographical Information Systems (G.I.S.) which integrates climatic and urban anthropogenic parameters in the assessment of spatio-temporal dispersion of air pollutants. Considering global incidence of air pollution on asthma and on peripheral blood lymphocytes MT-2A expression should provide a complementary information on biological risks linked to urban anthropogenic activities. Such study would help for the establishment of a sustainable development in urban areas that can maintain the integrity of air quality and preserve human health.     

Impact of coal mine dump contaminated soils on elemental uptake by Spinacia oleracea (spinach)

The elemental uptake and the growth response of Spinacia oleracea (spinach) to the soil contaminated with the South African bituminous coal mine dump soil, viz. 0%, 5%, 15%, and 25% w/w, was investigated. The contaminated soils were analyzed for pH, cation exchange capacity (CEC), soil organic matter (SOM), and concentrations of selected heavy metals. The pH, SOM, and CEC decreased with an increase in contamination indicating the acidic nature of coal mine soil and the raise in the soil binding sites. The distribution of Fe, Mn, Ni, Cd, and Pb in the in roots and leaves of the plants was determined in two stages of plant growth. Spinach showed high accumulation of Fe and increased levels of Ni and Cd with an increase in contamination. No plant growth was recorded with 25% contamination.     

Air emission inventories in North America: a critical assessment

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.