Interinstrument comparison of remote-sensing devices and a new method for calculating on-road nitrogen oxides emissions and validation of vehicle-specific power

Emissions of nitrogen oxides (NOx) by vehicles in real driving environments are only partially understood. This has been brought to the attention of the world with recent revelations of the cheating of the type of approval tests exposed in the dieselgate scandal. Remote-sensing devices offer investigators an opportunity to directly measure in situ real driving emissions of tens of thousands of vehicles. Remote-sensing NO₂ measurements are not as widely available as would be desirable. The aim of this study is to improve the ability of investigators to estimate the NO₂ emissions and to improve the confidence of the total NOx results calculated from standard remote-sensing device (RSD) measurements. The accuracy of the RSD speed and acceleration module was also validated using state-of-the-art onboard global positioning system (GPS) tracking. Two RSDs used in roadside vehicle emissions surveys were tested side by side under off-carriageway conditions away from transient pollution sources to ascertain the consistency of their measurements. The speed correlation was consistent across the range of measurements at 95% confidence and the acceleration correlation was consistent at 95% confidence intervals for all but the most extreme acceleration cases. VSP was consistent at 95% confidence across all measurements except for those at VSP ≥ 15 kW t^?1, which show a small underestimate. The controlled distribution gas nitric oxide measurements follow a normal distribution with 2σ equal to 18.9% of the mean, compared to 15% observed during factory calibration indicative of additional error introduced into the system. Systematic errors of +84 ppm were observed but within the tolerance of the control gas. Interinstrument correlation was performed, with the relationship between the FEAT and the RSD4600 being linear with a gradient of 0.93 and an R² of 0.85, indicating good correlation. A new method to calculate NOx emissions using fractional NO₂ combined with NO measurements made by the RSD4600 was constructed, validated, and shown to be more accurate than previous methods.

Implications: Synchronized remote-sensing measurements of NO were taken using two different remote-sensing devices in an off-road study. It was found that the measurements taken by both instruments were well correlated. Fractional NO₂ measurements from a prior study, measurable on only one device, were used to create new NO_x emission factors for the device that could not be measured by the second device. These estimates were validated against direct measurement of total NO_x emission factors and shown to be an improvement on previous methodologies. Validation of vehicle-specific power was performed with good correlation observed.     

Assessing groundwater quality and its sustainability in Joypurhat district of Bangladesh using GIS and multivariate statistical approaches

Sustainable groundwater quality is a key global concern and has become a major issue of disquiets in most parts of the world including Bangladesh. Hence, the assessment of groundwater quality is an important study to ensure its sustainability for various uses. In this study, a combination of multivariate statistics, geographical information system (GIS) and geochemical approaches was employed to evaluate the groundwater quality and its sustainability in Joypurhat district of Bangladesh. The results showed that the groundwater samples are mainly Ca–Mg–HCO₃ type. Principal component analysis (PCA) results revealed that geogenic sources (rock weathering and cation exchange) followed by anthropogenic activities (domestic sewage and agro-chemicals) were the major factors governing the groundwater quality of the study area. Furthermore, the results of PCA are validated using the cluster analysis and correlation matrix analysis. Based on the groundwater quality index (GWQI), it is found that all the groundwater samples belong to excellent to good water quality domains for human consumption, although iron, fluoride and iodide contaminated to the groundwater, which do not pose any significant health hazard according to World Health Organization’s and Bangladesh’s guideline values. The results of irrigation water quality index including sodium adsorption ratio (SAR), permeability index and sodium percentage (Na %) suggested that most of the groundwater samples are good quality water for agricultural uses. The spatial distribution of the measured values of GWQI, SAR, Fe (iron), EC (electrical conductivity) and TH (total hardness) were spatially mapped using the GIS tool in the study area.     

Correction to: Opportunities to reduce nutrient inputs to the Baltic Sea by improving manure use efficiency in agriculture

While progress has been made in reducing external nutrient inputs to the Baltic Sea, further actions are needed to meet the goals of the Baltic Sea Action Plan (BSAP), especially for the Baltic Proper, Gulf of Finland, and Gulf of Riga sub-basins. We used the net anthropogenic nitrogen and phosphorus inputs (NANI and NAPI, respectively) nutrient accounting approach to construct three scenarios of reduced NANI-NAPI. Reductions assumed that manure nutrients were redistributed from areas with intense animal production to areas that focus on crop production and would otherwise import synthetic and mineral fertilizers. We also used the Simple as Necessary Baltic Long Term Large Scale (SANBALTS) model to compare eutrophication conditions for the scenarios to current and BSAP-target conditions. The scenarios suggest that reducing NANI-NAPI by redistributing manure nutrients, together with improving agronomic practices, could meet 54–82% of the N reductions targets (28–43 kt N reduction) and 38–64% P reduction targets (4–6.6 kt P reduction), depending on scenario. SANBALTS output showed that even partial fulfillment of nutrient reduction targets could have ameliorating effects on eutrophication conditions. Meeting BSAP targets will require addressing additional sources, such as sewage. A common approach to apportioning sources to external nutrients loads could enable further assessment of the feasibility of eutrophication management targets.

     

A synoptic survey of select wastewater-tracer compounds and the pesticide imidacloprid in Florida’s ambient freshwaters

Current wastewater treatment technologies do not remove many unregulated hydrophilic compounds, and there is growing interest that low levels of these compounds, referred to as emerging contaminants, may impact human health and the environment. A probabilistic-designed monitoring network was employed to infer the extent of Florida’s ambient freshwaters containing the wastewater (Includes reuse water, septic systems leachate, and wastewater treatment effluent.) indicators sucralose, acetaminophen, carbamazepine, and primidone and those containing the widely used pesticide imidacloprid. Extent estimates with 95% confidence bounds are provided for canals, rivers, streams, small and large lakes, and unconfined aquifers containing ultra-trace concentrations of these compounds as based on analyses of 2015 sample surveys utilizing 528 sites. Sucralose is estimated to occur in greater than 50% of the canal, river, stream, and large lake resource extents. The pharmaceuticals acetaminophen, carbamazepine, and primidone are most prevalent in rivers, with approximately 30% of river kilometers estimated to contain at least one of these compounds. Imidacloprid is estimated to occur in 50% or greater of the canal and river resource extents, and it is the only compound found to exceed published toxicity or environmental effects standards. Geospatial analyses show sucralose detection frequencies within Florida’s drainage basins to be significantly related to the percentage of urban land use (R²?=?0.36, p?<?0.001), and imidacloprid detection frequencies to be significantly related to the percentage of urban and agricultural land use (R²?=?0.47, p?<?0.001). The extent of the presence of these compounds highlights the need for additional emerging contaminant studies especially those examining effects on aquatic biota.     

Spatial distribution of metals within the liver acinus and their perturbation by PCB126

Animal studies show that exposure to the environmental pollutant 3,3′,4,4′,5-pentachlorobiphenyl (PCB126) causes alterations in hepatic metals as measured in acid-digested volume-adjusted tissue. These studies lack the detail of the spatial distribution within the liver. Here we use X-ray fluorescence microscopy (XFM) to assess the spatial distribution of trace elements within liver tissue. Liver samples from male Sprague Dawley rats, treated either with vehicle or PCB126, were formalin fixed and paraffin embedded. Serial sections were prepared for traditional H&E staining or placed on silicon nitride windows for XFM. With XFM, metal gradients between the portal triad and the central vein were seen, especially with copper and iron. These gradients change with exposure to PCB126, even reverse. This is the first report of how micronutrients vary spatially within the liver and how they change in response to toxicant exposure. In addition, high concentrations of zinc clusters were discovered in the extracellular space. PCB126 treatment did not affect their presence, but did alter their elemental makeup suggesting a more general biological function. Further work is needed to properly evaluate the gradients and their alterations as well as classify the zinc clusters to determine their role in liver function and zinc homeostasis.     

A Simulation Study to Assess the Sensitivity of a Forest Health Monitoring Network to Outbreaks of Defoliating Insects

The sensitivity of the United States Forest Health Monitoring network to outbreaks of defoliating insects was examined by means of a simulation study. A model constructed specifically for the study was used to generate a wide variety of defoliation patterns in forested landscapes. Forest configuration was that of Minnesota, USA, as expressed by the GAP land cover classification. Combinations of model parameters were based on a Latin Hypercube sample. The relationship between the average number of plots defoliated and outbreak characteristics was then examined via multiple regression. Both theoretical and model results pointed to a strong, linear relationship between the average number of plots defoliated and outbreak size. Model results provided additional insight, suggesting a significant relationship between the average number of plots defoliated and other outbreak characteristics after outbreak size was taken into account.