不同种类有机肥施用对稻田CH4和N2O排放的综合影响

以麦茬稻田为对象,研究基肥施用不同有机肥对稻田CH4和N2O排放的综合影响.结果表明:有机肥施用对稻田CH4和N2O排放的季节变化模式无明显影响,但影响其排放量.与施用化肥(化肥处理)相比,施用菜饼+化肥(菜饼处理)促进CH4和N2O的排放,其季节排放总量分别增加了252%和22%;施用小麦秸秆+化肥(秸秆处理)和牛厩肥+化肥(牛厩肥处理)明显增加CH4排放,增加量分别为250%和45%,同时却减少N2O排放,分别减少18%和21%;施用猪厩肥+化肥(猪厩肥处理)降低CH4和N2O的排放,分别降低4%和18%.对CH4和N2O排放的综合温室效应分析表明,菜饼和秸秆处理的全球增温潜势(GWP)约为化肥处理的2.5倍,牛厩肥和化肥处理基本持平,但施用猪厩肥可减少10%～15%.各处理的GWP从高到低依次为菜饼、秸秆、牛厩肥、化肥和猪厩肥.单位产量的GWP以秸秆处理最高,菜饼次之,牛厩肥比化肥处理略高,猪厩肥处理最低.从本生长季来看,猪厩肥的施用对于实现环境效益与生产效益的协调发展具有一定作用.     

TWO STRATEGIES FOR LEARNING A ROUTE IN A DRIVING SIMULATOR

The study of human navigation has long been dominated by the so-called stage theory, i.e. the notion that there are three distinct types of spatial knowledge (landmark, route, and survey knowledge), that are acquired sequentially during spatial learning and development. Based on the results of a route learning experiment in a driving simulator, an alternative to the stage theory is proposed. The authors suggest that subjects follow either a visually dominated or a spatially dominated strategy to solve a route-learning problem. In the visually dominated strategy, subjects base their wayfinding decisions on visually recognizing decision points along a route; the decision points are not integrated into any kind of survey representation. In the spatially dominated strategy, on the other hand, subjects represent the environment as a survey map right from the start; that is, they do not pass through a landmark or route stage. These strategies may be subserved by different cortical areas recently characterized in neurophysiological studies of animals solving maze problems.     

A multi-objective assessment of an air quality monitoring network using environmental,economic, and social indicators and GIS-based models

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O₃) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs’ objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O₃ was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O₃, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O₃ monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the performance of air quality monitoring networks in urban regions.

Implications:The U.S. Environmental Protection Agency issued a directive in 2006 that air pollution agencies assess the performance of their AQMNs; as a result, we developed a GIS-based, multi-objective assessment approach that integrates environmental, economic, and social indicators, and demonstrates its use through assessing the O₃ and PM₁₀ monitoring networks in the Phoenix metropolitan area. We exhibit a method of assessing network performance and identifying areas that would benefit from new monitoring stations; also, we demonstrate the effect of adding weights to the indicators. Our study shows that using a multi-indicator approach gave detailed assessment results for the Phoenix AQMN.     

Anti-oviposition activities of used sock media against a dengue vector: prospects of eco-friendly control and solutions to pollution

Yearly, huge amounts of sock refuse are discarded into the environment. Socks contain many molecules, and worn ones, which are rich in smell-causing bacteria, have a strong influence on animals’ behaviors. But the impacts of sock odor on the oviposition behavior of dengue vectors are unknown. We assessed whether Aedes albopictus changes its oviposition activity in response to the presence of used socks extract (USEx) in potential breeding grounds, using choice and no-choice bioassays (NCB). When furnished even chances to oviposit in two sites holding USEx and two others containing water (control), Ae. albopictus deposited significantly less eggs in USEx than in water sites. A similar pattern of oviposition preference was also observed when there were more oviposition options in water. When there were greater oviposition opportunities in USEx sites, Ae. albopictus oviposited preferentially in water. Females laid significantly more eggs during the NCB involving water than USEx. Also, significantly more mature eggs were retained by females in the NCB with USEx than in that with water. These observations strongly suggest the presence of molecules with either repellent or deterrent activities against Ae. albopictus females and provide an impetus to advocate the integration of used socks in dengue control programs. Such applications could be a realistic end-of-life recourse to reroute this waste from landfills.

     

Cues from a common predator cause survival-linked behavioral adjustments in Mojave Desert tortoises (Gopherus agassizii)

Behavioral Ecology and Sociobiology - Adult animals of many species often behave in a cannibalistic manner when encountering conspecific offspring. Kin discrimination is critical for avoiding the...     

Preformed Amide-containing biopolymer for Improving the Environmental Performance of Synthesized Urea–formaldehyde in Agro-fiber Composites

Investigations have continued for production high performance agro-based composites using environmentally acceptable approaches. This study examines the role of adding amide-containing biopolymers during synthesis of urea–formaldehyde (UF) on properties of adhesive produced, especially its adhesion potential. The environmental performance of UF-resin synthesized in the presence of modified amide-containing biopolymer was evaluated by evaluating the free-HCHO of both adhesive (during processing) and of the eventual engineered composite product. Also, the benefits of this synthesis-modified adhesive in enhancing the bondability of sugar-cane fibers used in engineered composite panels was evaluated and compared to using UF-resin. The results obtained show that, static bending of the produced composites varied from 27.7 to 33.13 N/mm² of modulus of rupture (MOR) and from 2860 to 3374 N/mm² of Modulus of Elasticity (MOE); while for internal bond (IB) it’s varied from 0.64 to 0.866 N/mm². Based on the ANSI and EN Standards modified UF-based agro composites produced meet the performance requirements for high grade particleboards with respect to static bending strength. These agro-based composite also tested out as having free-HCHO values of ~13 mg/100 g board.     

The 1999 Fresno Particulate Matter Exposure Studies: Comparison of Community,Outdoor, and Residential PM Mass Measurements

ABSTRACT

Two collaborative studies have been conducted by the U.S. Environmental Protection Agency (EPA) National Exposure Research Laboratory (NERL) and National Health and Environmental Effects Research Laboratory to determine personal exposures and physiological responses to par-ticulate matter (PM) of elderly persons living in a retirement facility in Fresno, CA. Measurements of PM and other criteria air pollutants were made inside selected individual residences within the retirement facility and at a central outdoor site on the premises. In addition, personal PM exposure monitoring was conducted for a subset of the participants, and ambient PM monitoring data were available for comparison from the NERL PM research monitoring platform in central Fresno. Both a winter (February 1-28, 1999) and a spring (April 19-May 16, 1999) study were completed so that seasonal effects could be     

Statistical Considerations in Determining the Health Significance of Constituents of Airborne Particulate Matter

ABSTRACT

Because of the U.S. Environmental Protection Agency’s (EPA) new ambient air quality standard for fine particles, the need is likely to continue for more detailed scientific investigation of various types of particles and their effects on human health. Epidemiology studies have become the method of choice for investigating health responses to such particles and to other air pollutants in community settings. Health effects have been associated with virtually all of the gaseous criteria pollutants and with the major constituents of airborne particulate matter (PM), including all size fractions less than about 20 gm, inorganic ions, carbonaceous particles, metals, crustal material, and biological aerosols. In many of the more recent studies, multiple pollutants or agents (including weather variables) have been significantly associated with health responses, and various methods have been used to suggest which ones might be the most important. In an ideal situation, classical least-squares regression methods are capable of performing this task. However, in the real world, where most of the pollutants are correlated with one another and have varying degrees of measurement precision and accuracy, such regression results can be misleading. This paper presents some guidelines for dealing with such collinearity and model comparison problems in both single- and multiple-pollutant regressions. These techniques rely on mean effect (attributable risk) rather than statistical significance per se as the preferred indicator of importance for the pollution variables.