A Regional Classification Scheme for Estimating Reference Water Quality in Streams Using Land-Use-Adjusted Spatial Regression-Tree Analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States.     

Tillage and field scale controls on greenhouse gas emissions

There is a lack of understanding of how associations among soil properties and management-induced changes control the variability of greenhouse gas (GHG) emissions from soil. We performed a laboratory investigation to quantify relationships between GHG emissions and soil indicators in an irrigated agricultural field under standard tillage (ST) and a field recently converted (2 yr) to no-tillage (NT). Soil cores (15-cm depth) were incubated at 25 degrees C at field moisture content and 75% water holding capacity. Principal component analysis (PCA) identified that most of the variation of the measured soil properties was related to differences in soil C and N and soil water conditions under ST, but soil texture and bulk density under NT. This trend became more apparent after irrigation. However, principal component regression (PCR) suggested that soil physical properties or total C and N were less important in controlling GHG emissions across tillage systems. The CO2 flux was more strongly determined by microbial biomass under ST and inorganic N content under NT than soil physical properties. Similarly, N2O and CH4 fluxes were predominantly controlled by NO3- content and labile C and N availability in both ST and NT soils at field moisture content, and NH4+ content after irrigation. Our study indicates that the field-scale variability of GHG emissions is controlled primarily by biochemical parameters rather than physical parameters. Differences in the availability and type of C and N sources for microbial activity as affected by tillage and irrigation develop different levels and combinations of field-scale controls on GHG emissions.     

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.

     

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.     

Evaluating anthropogenic N inputs to diverse lake basins: A case study of three Chinese lakes

The environmental degradation of lakes in China has become increasingly serious over the last 30 years and eutrophication resulting from enhanced nutrient inputs is considered a top threat. In this study, a quasi-mass balance method, net anthropogenic N inputs (NANI), was introduced to assess the human influence on N input into three typical Chinese lake basins. The resultant NANI exceeded 10 000 kg N km⁻² year⁻¹ for all three basins, and mineral fertilizers were generally the largest sources. However, rapid urbanization and shrinking agricultural production capability may significantly increase N inputs from food and feed imports. Higher percentages of NANI were observed to be exported at urban river outlets, suggesting the acceleration of NANI transfer to rivers by urbanization. Over the last decade, the N inputs have declined in the basins dominated by the fertilizer use but have increased in the basins dominated by the food and feed import. In the foreseeable future, urban areas may arise as new hotspots for nitrogen in China while fertilizer use may decline in importance in areas of high population density.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0638-8) contains supplementary material, which is available to authorized users.     

Reduction of Baltic Sea Nutrient Inputs and Allocation of Abatement Costs Within the Baltic Sea Catchment

The Baltic Sea Action Plan (BSAP) requires tools to simulate effects and costs of various nutrient abatement strategies. Hierarchically connected databases and models of the entire catchment have been created to allow decision makers to view scenarios via the decision support system NEST. Increased intensity in agriculture in transient countries would result in increased nutrient loads to the Baltic Sea, particularly from Poland, the Baltic States, and Russia. Nutrient retentions are high, which means that the nutrient reduction goals of 135 000 tons N and 15 000 tons P, as formulated in the BSAP from 2007, correspond to a reduction in nutrient loadings to watersheds by 675 000 tons N and 158 000 tons P. A cost-minimization model was used to allocate nutrient reductions to measures and countries where the costs for reducing loads are low. The minimum annual cost to meet BSAP basin targets is estimated to 4.7 billion €.     

Effect of Moisture on the Pollutant Concentration Measurement

The effects of removing moisture from gaseous samples on the measurement of pollutant concentration were studied. Simple mathematical analysis was conducted to derive the formula for correcting the measured results. It was found that the error increases with increase in relative humidity or increase in temperature. The error may become significant under extreme conditions.     

Economic Benefits of Improvements in Visibility: Acid Rain Provisions of the 1990 Clean Air Act Amendments

The Acid Rain Provisions (Title IV) of the Clean Air Act Amendments of 1990 call for about a 10 million ton reduction in annual SO₂ emissions in the United States. Although the provisions apply nationwide, most of the reduction will occur in the eastern half of the country, where use of high-sulfur coal for electricity generation is most common. One potentially large benefit of Title IV is the expected improvement in visibility conditions in the eastern United States due to the reductions in secondary sul-fate aerosols. This paper combines available economic estimates of willingness to pay for improvements in visibility with current estimates of the difference between expected visibility conditions in the eastern United States with and without Title I V, to estimate the expected visibility benefits of Title IV. The results suggest an annual value of $2.3 billion (in 1994 dollars) in the year 2010, as a result of visibility improvements due to Title IV in residential areas of the eastern United States. The results also suggest a possible additional annual value for eastern U.S. residents of as much as $1-2 billion for visibility improvements at national parks in the Southeast.     

Weekday/Weekend Ozone Differences: What Can We Learn from Them?

Abstract

A national analysis of weekday/weekend ozone (O₃) differences demonstrates significant variation across the country. Weekend 1-hr or 8-hr maximum O₃ varies from 15% lower than weekday levels to 30% higher. The weekend O₃ increases are primarily found in and around large coastal cities in California and large cities in the Midwest and Northeast Corridor. Both the average and the 95th percentile of the daily 1-hr and 8-hr maxima exhibit the same general pattern. Many sites that have elevated O₃ also have higher O₃ on weekends even though traffic and O₃ precursor levels are substantially reduced on weekends. Detailed studies of this phenomenon indicate that the primary cause of the higher O₃ on weekends is the reduction in oxides of nitrogen (NO_x) emissions on weekends in a volatile organic compound (VOC)-limited chemical regime. In contrast, the lower O₃ on weekends in other locations is probably a result of NO_x reductions in a NO_x-limited regime. The NO_x reduction explanation is supported by a wide range of ambient analyses and several photochemical modeling studies. Changes in the timing and location of emissions and meteorological factors play smaller roles in weekend O₃ behavior. Weekday/weekend temperature differences do not explain the weekend effect but may modify it.     

Relative Importance of School Bus-Related Microenvironments to Children’s Pollutant Exposure

Abstract

Real‐time concentrations of black carbon, particle‐bound polycyclic aromatic hydrocarbons, nitrogen dioxide, and fine particulate counts, as well as integrated and real‐time fine particulate matter (PM_2.5) mass concentrations were measured inside school buses during long commutes on Los Angeles Unified School District bus routes, at bus stops along the routes, at the bus loading/unloading zone in front of the selected school, and at nearby urban “background” sites. Across all of the pollutants, mean concentrations during bus commutes were higher than in any other microenvironment. Mean exposures (mean concentration times time spent in a particular microenvironment) in bus commutes were between 50 and 200 times greater than those for the loading/unloading microenvironment, and 20–40 times higher than those for the bus stops, depending on the pollutant. Although the analyzed school bus commutes represented only 10% of a child’s day, on average they contributed one‐third of a child’s 24‐hr overall black carbon exposure during a school day. For species closely related to vehicle exhaust, the within‐cabin exposures were generally dominated by the effect of surrounding traffic when windows were open and by the bus’s own exhaust when windows were closed. Low‐emitting buses generally exhibited high concentrations only when traveling behind a diesel vehicle, whereas high‐emitting buses exhibited high concentrations both when following other diesel vehicles and when idling without another diesel vehicle in front of the bus. To reduce school bus commute exposures, we recommend minimizing commute times, avoiding caravanning with other school buses, using the cleanest buses for the longest bus routes, maintaining conventional diesel buses to eliminate visible emissions, and transitioning to cleaner fuels and advanced particulate control technologies as soon as possible.