Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Occupational and environmental aerosol exposure assessment: a scientific journey from the past, through the present and into the future

This paper reviews how aerosol exposure assessment, for people in both working and living environments, has evolved over the years. It charts the main scientific developments that led to progressively improved ways of thinking and methods to assess exposure to airborne particulate matter in a manner more relevant to human health. It has been a long scientific journey as one generation of pioneering contributors has handed off to the next. In the process a consistent rationale has emerged, producing aerosol sampling criteria--and in turn exposure standards--which have been increasingly relevant to actual human exposures. The journey continues as a new generation of scientists steps up to deal with the new challenges that are emerging. An appreciation of the history of what went before is essential to charting the most effective path looking forward.     

Pastoralists in a changing environment: The competition for grazing land in and around the W Biosphere Reserve,Benin Republic

Pastoralists face increasing competition for land with crop farmers and nature in and around the W Biosphere Reserve (WBR) in Benin. Our aim was to describe and analyse land use changes in order to understand their drivers, and to describe and analyse the viewpoints of relevant stakeholders in order to understand the competition for land. To this end, remote sensing data, regional statistics, and survey data were collected. We found that crop land expansion around the WBR was the direct driver of decrease of the grazing land area. Population growth and rising demand for food crops, and government support to the cotton sector were indirect drivers of grazing land reduction. Furthermore, competing claims on land among users arose from the complex interaction of crop expansion, presence of WBR and the way it is governed, the lack of support to pastoralists, and the increasing shift of pastoralists’ lifestyle into one of settled crop farmers. Pastoralism is under threat and its survival depends on the successful implementation of policies to support pastoralists and protect grazing lands.     

Monitoring saltwater intrusion in Rupert Bay,Québec,Canada, after the partial diversion of a major tributary

As part of a large hydroelectric project in northern Québec (Canada), a portion of the flow of the Rupert River was diverted toward the existing La Grande hydroelectric complex. As a result of the partial diversion, the discharge of the Rupert River at its mouth is reduced by an average of 50% annually. This corresponds to an 18% decrease in the total freshwater inflow into the bay and, thus, to a shift of the upstream limit of the saltwater intrusion in Rupert Bay. Changes in saltwater intrusion had been predicted numerically as part of the project’s environmental impact assessment (EIA). In the project’s conditions of authorization, monitoring the hydraulic conditions and the extent of saltwater intrusion in the Rupert Bay was required by government authorities. The objective of this paper is to present the results of this environmental monitoring and, more specifically, to validate the modifications predicted in the EIA in terms of both saltwater intrusion limit and hydraulic conditions in the Rupert Bay. Results obtained during 2 years of monitoring are within the predicted trends and order of magnitude of changes anticipated in the EIA. The results, thus, confirm that the shift of the upstream limit of the saltwater front along the channels of the bay was conservatively predicted by numerical modeling.     

When experts disagree: the need to rethink indicator selection for assessing sustainability of agriculture

Sustainability indicators are well recognized for their potential to assess and monitor sustainable development of agricultural systems. A large number of indicators are proposed in various sustainability assessment frameworks, which raises concerns regarding the validity of approaches, usefulness and trust in such frameworks. Selecting indicators requires transparent and well-defined procedures to ensure the relevance and validity of sustainability assessments. The objective of this study, therefore, was to determine whether experts agree on which criteria are most important in the selection of indicators and indicator sets for robust sustainability assessments. Two groups of experts (Temperate Agriculture Research Network and New Zealand Sustainability Dashboard) were asked to rank the relative importance of eleven criteria for selecting individual indicators and of nine criteria for balancing a collective set of indicators. Both ranking surveys reveal a startling lack of consensus amongst experts about how best to measure agricultural sustainability and call for a radical rethink about how complementary approaches to sustainability assessments are used alongside each other to ensure a plurality of views and maximum collaboration and trust amongst stakeholders. To improve the transparency, relevance and robustness of sustainable assessments, the context of the sustainability assessment, including prioritizations of selection criteria for indicator selection, must be accounted for. A collaborative design process will enhance the acceptance of diverse values and prioritizations embedded in sustainability assessments. The process by which indicators and sustainability frameworks are established may be a much more important determinant of their success than the final shape of the assessment tools. Such an emphasis on process would make assessments more transparent, transformative and enduring.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Matrix Diffusion Modeling Applied to Long‐Term Pump‐and‐Treat Data: 2. Results From Three Sites

The data mining/groundwater modeling methodology developed in McDade et al. (2013) was performed to determine if matrix diffusion is a plausible explanation for the lower‐concentration but persistent chlorinated solvent plumes in the groundwater‐bearing units at three different pump‐and‐treat systems. Capture‐zone maps were evaluated, and eight wells were identified that did not draw water from any of the historical source areas but captured water from the sides of the plume. Two groundwater models were applied to study the persistence of the plumes in the absence of contributions from the historical source zones. In the wells modeled, the observed mass discharge generally decreased by about one order of magnitude or less over 4 to 10 years of pumping, and 1.8 to 17 pore volumes were extracted. In five of the eight wells, the matrix diffusion model fit the data much better than the advection dispersion retardation model, indicating that matrix diffusion better explains the persistent plume. In the three other wells, confounding factors, such as a changing capture zone over time (caused by changes in pumping rates in adjacent extraction wells); potential interference from a high‐concentration unremediated source zone; and limited number of pore volumes removed made it difficult to confirm that matrix diffusion processes were active in these areas. Overall, the results from the five wells indicate that mass discharge rates from the pumping wells will continue to show a characteristic “long tail'' of mass removal from zones affected by active matrix diffusion processes. Future site management activities should include matrix diffusion processes in the conceptual site models for these three sites. © 2013 Wiley Periodicals, Inc.     

Formation of indoor nitrous acid (HONO) by light-induced NO<Subscript>2</Subscript> heterogeneous reactions with white wall paint

Gaseous nitrogen dioxide (NO₂) represents an oxidant that is present in relatively high concentrations in various indoor settings. Remarkably increased NO₂ levels up to 1.5 ppm are associated with homes using gas stoves. The heterogeneous reactions of NO₂ with adsorbed water on surfaces lead to the generation of nitrous acid (HONO). Here, we present a HONO source induced by heterogeneous reactions of NO₂ with selected indoor paint surfaces in the presence of light (300 nm?<?λ?<?400 nm). We demonstrate that the formation of HONO is much more pronounced at elevated relative humidity. In the presence of light (5.5 W m^?2), an increase of HONO production rate of up to 8.6?·?10⁹ molecules cm^?2 s^?1 was observed at [NO₂]?=?60 ppb and 50 % relative humidity (RH). At higher light intensity of 10.6 (W m^?2), the HONO production rate increased to 2.1?·?10¹⁰ molecules cm^?2 s^?1. A high NO₂ to HONO conversion yield of up to 84 % was observed. This result strongly suggests that a light-driven process of indoor HONO production is operational. This work highlights the potential of paint surfaces to generate HONO within indoor environments by light-induced NO₂ heterogeneous reactions.     

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.     

Variation of raw wastewater microbiological quality in dry and wet weather conditions

The microbiological quality of urban wastewaters presents important environmental, sanitary, and political challenges. However, the variability of untreated wastewater quality is seldom known when it comes to microbial parameters. This study aims to evaluate the variability of microbiological quality in wastewater influents from different wastewater treatment plants connected to combined and partially separate sewer networks in the Parisian area and to evaluate the impact of this variability on the treatment efficiency and on the accuracy of wastewater effluent monitoring. The densities of fecal indicator bacteria (FIB), Escherichia coli and intestinal enterococci, and their partitioning on settleable particles were analyzed at the inlet of two wastewater treatment plants during dry weather (130 composite samples and 7 days sampled every 2 hours) and storm events (39 composite samples, and 7 rain courses) from 2008 to 2012. The results showed that fecal indicator densities vary according to the network characteristics and according to the meteorological conditions. During storm events, a significant dilution of E. coli and enterococci was observed, as well as a decrease in the settleable fraction of E. coli during the maximal impact of the storm. However, storm events did not significantly impact the regular FIB monitoring. FIB removals by primary and secondary treatment were significantly correlated with FIB densities in influent wastewater; however, meteorological conditions also influenced the removal of FIB.