Pyrethroid pesticide effects on behavioral responses of aquatic isopods to danger cues

The present study sought to evaluate the behavioral responses of non-target organisms in order to determine whether phototactic responses of isopods to danger cues are altered as a function of exposure to the pyrethroid pesticides λ-cyhalothrin and bifenthrin. Experiments conducted on Gnorimosphaeroma oregonensis identified sublethal behavioral responses to pyrethroids, λ-cyhalothrin and bifenthrin at concentrations 0.15 ng/mL, 0.025 ng/mL, and 0.005 ng/mL. Experimental setup tested isopod phototactic responses across six treatments: control, pyrethroid, hemolymph, predator, hemolymph?+?pyrethroid, and predator?+?pyrethroid. Isopods exhibited no preference for phototactic responses in the control and pyrethroid treatments. When exposed to danger cues (hemolymph or predator), isopods exhibited significant negative phototaxis, as expected. When exposure to danger cues was combined with pyrethroids, isopods again exhibited no preference for phototactic response. Experiments indicate that pyrethroids diminish isopod’s negatively phototactic response to danger cues.     

Major ionic compositions of fine particulate matter in an animal feeding operation facility and its vicinity

Animal feeding operations (AFOs) produce particulate matter (PM) and gaseous pollutants. Investigation of the chemical composition of PM_2.5 inside and in the local vicinity of AFOs can help to understand the impact of the AFO emissions on ambient secondary PM formation. This study was conducted on a commercial egg production farm in North Carolina. Samples of PM_2.5 were collected from five stations, with one located in an egg production house and the other four located in the vicinity of the farm along four wind directions. The major ions of NH₄⁺, Na⁺, K⁺, SO₄^2?, Cl^?, and NO₃^? were analyzed using ion chromatography (IC). In the house, the mostly abundant ions were SO₄^2?, Cl^?, and K⁺. At ambient stations, SO₄^2?, and NH₄⁺ were the two most abundant ions. In the house, NH₄⁺, SO₄^2?, and NO₃^? accounted for only 10% of the PM_2.5 mass; at ambient locations, NH₄⁺, SO₄^2?, and NO₃^? accounted for 36–41% of the PM_2.5 mass. In the house, NH₄⁺ had small seasonal variations indicating that gas-phase NH₃ was not the only major force driving its gas–particle partitioning. At the ambient stations, NH₄⁺ had the highest concentrations in summer. In the house, K⁺, Na⁺, and Cl^? were highly correlated with each other. In ambient locations, SO₄^2? and NH₄⁺ had a strong correlation, whereas in the house, SO₄^2? and NH₄⁺ had a very weak correlation. Ambient temperature and solar radiation were positively correlated with NH₄⁺ and SO₄^2?. This study suggests that secondary PM formation inside the animal house was not an important source of PM_2.5. In the vicinity, NH₃ emissions had greater impact on PM_2.5 formation.

ImplicationsThe chemical composition of PM_2.5 inside and in the local vicinity of AFOs showed the impact of the AFO emissions on ambient secondary PM_2.5 formation, and the fate and transport of air pollutants associated with AFOs. The results may help to manage in-house animal facility air quality, and to develop regional air quality control strategies and policies, especially in animal agriculture-concentrated areas.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

Volatile Organic Compounds from Coal Tar and Soil Vapor Samples at MGP Sites

This study characterized organic compounds found in New York State manufactured gas plant (MGP) coal tar vapors using controlled laboratory experiments from four separate MGP sites. In addition, a limited number of deep (0.3–1.2 m above coal tar) and shallow (1.2–2.4 m above coal tar) soil vapor samples were collected above the in situ coal tar source at three of these sites. A total of 29 compounds were consistently detected in the laboratory-generated coal tar vapors at 50°C, whereas 24 compounds were detected at 10°C. The compounds detected in the field sample results were inconsistent with the compounds found in the laboratory-generated samples. Concentrations of compounds in the shallow soil vapor sample were either non-detectable or substantially lower than those found in deeper samples, suggesting attenuation in the vadose zone. Laboratory-generated data at 50°C compared the (% non-aromatic)/(% aromatic) ratio and indicated that this ratio may provide good discrimination between coal tar vapor and common petroleum distillates.     

U.S. National PM2.5 Chemical Speciation Monitoring Networks—CSN and IMPROVE: Description of networks

The U.S. Environmental Protection Agency (EPA) initiated the national PM_2.5 Chemical Speciation Monitoring Network (CSN) in 2000 to support evaluation of long-term trends and to better quantify the impact of sources on particulate matter (PM) concentrations in the size range below 2.5 μm aerodynamic diameter (PM_2.5; fine particles). The network peaked at more than 260 sites in 2005. In response to the 1999 Regional Haze Rule and the need to better understand the regional transport of PM, EPA also augmented the long-existing Interagency Monitoring of Protected Visual Environments (IMPROVE) visibility monitoring network in 2000, adding nearly 100 additional IMPROVE sites in rural Class 1 Areas across the country. Both networks measure the major chemical components of PM_2.5 using historically accepted filter-based methods. Components measured by both networks include major anions, carbonaceous material, and a series of trace elements. CSN also measures ammonium and other cations directly, whereas IMPROVE estimates ammonium assuming complete neutralization of the measured sulfate and nitrate. IMPROVE also measures chloride and nitrite. In general, the field and laboratory approaches used in the two networks are similar; however, there are numerous, often subtle differences in sampling and chemical analysis methods, shipping, and quality control practices. These could potentially affect merging the two data sets when used to understand better the impact of sources on PM concentrations and the regional nature and long-range transport of PM_2.5. This paper describes, for the first time in the peer-reviewed literature, these networks as they have existed since 2000, outlines differences in field and laboratory approaches, provides a summary of the analytical parameters that address data uncertainty, and summarizes major network changes since the inception of CSN.

ImplicationsTwo long-term chemical speciation particle monitoring networks have operated simultaneously in the United States since 2001, when the EPA began regular operations of its PM_2.5 Chemical Speciation Monitoring Network (IMPROVE began in 1988). These networks use similar field sampling and analytical methods, but there are numerous, often subtle differences in equipment and methodologies that can affect the results. This paper describes these networks since 2000 (inception of CSN) and their differences, and summarizes the analytical parameters that address data uncertainty, providing researchers and policymakers with background information they may need (e.g., for 2018 PM_2.5 designation and State Implementation Plan process; McCarthy, 2013) to assess results from each network and decide how these data sets can be mutually employed for enhanced analyses. Changes in CSN and IMPROVE that have occurred over the years also are described.     

Climate change impacts on vegetation and water cycle in the Euro-Mediterranean region,studied by a likelihood approach

Scientific community and policy-makers share the common interest in identifying and evaluating potential impacts of climate change on ecosystems, relying mainly on probabilistic methods of exploring the risks. In this perspective, the concept of ensemble forecasting makes possible to handle uncertainties associated with climate risk analysis by focusing on a range of potential or probable impact scenarios rather than actualizing a single case. In this paper, an ensemble of simulations based on the Lund-Potsdam-Jena (LPJ) model was used to investigate the uncertainty upon predictions of the future Euro-Mediterranean vegetation distribution, carbon dynamics, and water budget. Twenty simulations from past to future were based on the combination of different climate inputs, vegetation model parameterizations, and configurations. The evaluation of results combined the separate deterministic future projections from the LPJ model into a single probabilistic projection, associating a likelihood degree in accordance with the most recent Intergovernmental Panel on Climate Change terminology. Results projected a general critical situation in terms of water availability, made more serious if considering that also the occurrence of extreme-related events, e.g., fires, is expected to become more frequent as favored by more recurrent drought episodes. Although more uncomfortable climate conditions were projected for vegetation, net primary production (NPP) was predicted to increase due to the potential enrichment of CO₂ in atmosphere and its fertilization effects on vegetation. The combination of rising NPP and fire frequency may shape the carbon cycle components, as the carbon losses by fire also were projected to increase.     

Present and future climate resources for various types of tourism in the Bay of Palma,Spain

The Bay of Palma, in Mallorca, is a leading region for beach holidays in Europe. It is based on a mass tourism model strongly modulated by seasonality and with high environmental costs. Main tourism stakeholders are currently implementing complementary activities to mitigate seasonality, regardless of climate change. But climate is—and will remain—a key resource or even a limitation for many types of tourism. Assessing the present conditions and exploring the future evolution of climate potential for these activities have become a priority in this area. To this end, the climate index for tourism (CIT)—originally designed to rate the climate resource of beach tourism—is adapted to specifically appraise cycling, cultural tourism, football, golf, motor boating, sailing and hiking. Climate resources are derived by using observed and projected daily meteorological data. Projections have been obtained from a suite of Regional Climate Models run under the A1B emissions scenario. To properly derive CITs at such local scale, we apply a statistical adjustment. Present climate potentials ratify the appropriateness of the Bay of Palma for satisfactorily practicing all the examined activities. However, optimal conditions are projected to degrade during the peak visitation period while improving in spring and autumn. That is, climate change could further exacerbate the present imbalance between the seasonal distributions of ideal climate potentials and high attendance levels. With this information at hand, policy makers and regional tourism stakeholders can respond more effectively to the great challenge of local adaptation to climate change.     

Performance,combustion and emission characteristics of a single-cylinder,four-stroke,direct injection diesel engine operated on a dual-fuel mode using Honge oil methyl ester and producer gas derived from biomass feedstock of different origin

Renewable and alternative fuels have numerous advantages compared with fossil fuels, as they are renewable and biodegradable, and provide food and energy security and foreign exchange savings besides addressing environmental concerns and socio-economic issues. In this context, present work was carried out to investigate the feasibility of alternative and renewable fuels derived from biomass feedstock of different origin for engine applications. The present study was also extended to study the effect of producer gas composition derived from different biomass feedstock on the performance, combustion and emission characteristics of a single-cylinder, four-stroke, direct injection stationary diesel engine operated on a dual-fuel mode using Honge oil methyl ester (HOME) and producer gas induction. The performance of the engine was evaluated with a constant injection timing of 27° before top dead centre, an injection pressure of 205 bar for the diesel–producer gas combination and 230 bar for the HOME–producer gas combination and a compression ratio of 17.5. The results showed that the performance of the dual-fuel engine varies with the composition of the producer gas and depends on the type of biomass feedstock used in the gasifier. Experimental investigations on the dual-fuel engine showed that brake thermal efficiency values for the engine operated using HOME–producer gas derived from babul, neem and honge woods were found to be 17.2, 14.3 and 11.56% respectively, compared to 23.8% for diesel–producer gas operation at 80% load. However, the results showed better engine performance with lower exhaust emission levels for the operation of HOME–producer gas derived from the ordinary or babul wood compared with the operation of that derived from the neem and Honge woods. In view of this, present study reveals that use of alternative and renewable fuels for dual fuel engine can be considered as an immediate solution for the development of rural areas and emergency use in the event of severe diesel fuel shortage.     

Effects of compression ratio,swirl augmentation techniques and ethanol addition on the combustion of CNG–biodiesel in a dual-fuel engine

The diminishing resources and continuously increasing cost of petroleum in association with their alarming pollution levels from diesel engines has led to an interest in finding alternative fuels to diesel. Emission control and engine efficiency are two of the most important parameters in current engine design. The impending introduction of emission standards such as Euro IV and Euro V has forced research towards developing new technologies for combating engine emissions. This paper examines the effects of compression ratio, swirl augmentation techniques and ethanol addition on the combustion of compressed natural gas (CNG) blended with Honge oil methyl esters (HOME) in a dual fuel engine. The present results show that the combustion of HOME and 15% ethanol blend with CNG induction in a dual-fuel engine operated in optimized parameters at an injection timing of 27° Before Top Dead Centre and a compression ratio of 17.5 resulted in acceptable combustion emissions and improved brake thermal efficiencies. The implementation of swirl augmentation techniques increased brake thermal efficiencies (BTEs) and considerably reduced combustion emissions such as smoke, HC, CO and NO_x. The addition of ethanol also increased BTEs. However, at more than 15% of ethanol in HOME, NO_x emissions increased dramatically.