Energy profiles of an agricultural frontier: the American Great Plains, 1860–2000

Regional Environmental Change - Agro-ecosystem energy profiles reveal energy flows into, within, and out of US Great Plains farm communities across 140 years. This study evaluates external...     

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.

     

Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada’s Regional Air Quality Deterministic Prediction System

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr.

Implications: This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.     

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.