The Water Poverty Index: Development and application at the community scale

The article details the development and uses of the water poverty index (WPI). The index was developed as a holistic tool to measure water stress at the household and community levels, designed to aid national decision makers, at community and central government level, as well as donor agencies, to determine priority needs for interventions in the water sector. The index combines into a single number a cluster of data directly and indirectly relevant to water stress. Subcomponents of the index include measures of: access to water; water quantity, quality and variability; water uses (domestic, food, productive purposes); capacity for water management; and environmental aspects.
The WPI methodology was developed through pilot projects in South Africa, Tanzania and Sri Lanka and involved intensive participation and consultation with all stakeholders, including water users, politicians, water sector professionals, aid agency personnel and others. The article discusses approaches for the further implementation of the water poverty index, including the possibilities of acquiring the necessary data through existing national surveys or by establishing interdisciplinary water modules in school curricula. The article argues that the WPI fills the need for a simple, open and transparent tool, one that will appeal to politicians and decision makers, and at the same time can empower poor people to participate in the better targeting of water sector interventions and development budgets in general.     

The emergence of an environmental governance network: the case of the Arizona borderlands

Regional Environmental Change - Across the country, government agencies increasingly collaborate with non-governmental actors on environmental dilemmas to gain access to resources, expertise, and...     

Emerging Tools for Continuous Nutrient Monitoring Networks: Sensors Advancing Science and Water Resources Protection

Sensors and enabling technologies are becoming increasingly important tools for water quality monitoring and associated water resource management decisions. In particular, nutrient sensors are of interest because of the well‐known adverse effects of nutrient enrichment on coastal hypoxia, harmful algal blooms, and impacts to human health. Accurate and timely information on nutrient concentrations and loads is integral to strategies designed to minimize risk to humans and manage the underlying drivers of water quality impairment. Using nitrate sensors as the primary example, we highlight the types of applications in freshwater and coastal environments that are likely to benefit from continuous, real‐time nutrient data. The concurrent emergence of new tools to integrate, manage, and share large datasets is critical to the successful use of nutrient sensors and has made it possible for the field of continuous monitoring to rapidly move forward. We highlight several near‐term opportunities for federal agencies, as well as the broader scientific and management community, that will help accelerate sensor development, build and leverage sites within a national network, and develop open data standards and data management protocols that are key to realizing the benefits of a large‐scale, integrated monitoring network. Investing in these opportunities will provide new information to guide management and policies designed to protect and restore our nation's water resources.     

Estimating plant-available nitrogen release from manures, composts, and specialty products

Recent adoption of national rules for organic crop production have stimulated greater interest in meeting crop N needs using manures, composts, and other organic materials. This study was designed to provide data to support Extension recommendations for organic amendments. Specifically, our objectives were to (i) measure decomposition and N released from fresh and composted amendments and (ii) evaluate the performance of the model DECOMPOSITION, a relatively simple N mineralization/immobilization model, as a predictor of N availability. Amendment samples were aerobically incubated in moist soil in the laboratory at 22 degrees C for 70 d to determine decomposition and plant-available nitrogen (PAN) (n = 44), and they were applied preplant to a sweet corn crop to determine PAN via fertilizer N equivalency (n = 37). Well-composted materials (n = 14) had a single decomposition rate, averaging 0.003 d(-1). For uncomposted materials, decomposition was rapid (>0.01 d(-1)) for the first 10 to 30 d. The laboratory incubation and the full-season PAN determination in the field gave similar estimates of PAN across amendments. The linear regression equation for lab PAN vs. field PAN had a slope not different from one and a y-intercept not different than zero. Much of the PAN released from amendments was recovered in the first 30 d. Field and laboratory measurements of PAN were strongly related to PAN estimated by DECOMPOSITION (r(2) > 0.7). Modeled PAN values were typically higher than observed PAN, particularly for amendments exhibiting high initial NH(4)-N concentrations or rapid decomposition. Based on our findings, we recommend that guidance publications for manure and compost utilization include short-term (28-d) decomposition and PAN estimates that can be useful to both modelers and growers.     

Applying the zoo model to conservation of threatened exceptional plant species

Maintaining a living plant collection is the most common method of ex situ conservation for plant species that cannot be seed banked (i.e., exceptional species). Viability of living collections, and their value for future conservation efforts, can be limited without coordinated efforts to track and manage individuals across institutions. Using a pedigree-focused approach, the zoological community has established an inter-institutional infrastructure to support long-term viability of captive animal populations. We assessed the ability of this coordinated metacollection infrastructure to support the conservation of 4 plant species curated in living collections at multiple botanic gardens around the world. Limitations in current practices include the inability to compile, share, and analyze plant collections data at the individual level, as well as difficulty in tracking original provenance of ex situ material. The coordinated metacollection framework used by zoos can be adopted by the botanical community to improve conservation outcomes by minimizing the loss of genetic diversity in collections. We suggest actions to improve ex situ conservation of exceptional plant species, including developing a central database to aggregate data and track unique individuals of priority threatened species among institutions and adapting a pedigree-based population management tool that incorporates life-history aspects unique to plants. If approached collaboratively across regional, national, and global scales, these actions could transform ex situ conservation of threatened plant species.     

Use of CALPUFF for exposure assessment in a near-field,complex terrain setting

CALPUFF is an atmospheric source-receptor model recommended by the U.S. Environmental Protection Agency for use on a case-by-case basis in complex terrain and wind conditions. The ability of the model to provide useful information for exposure assessments in areas with those topographical and meteorological conditions has received little attention. This is an important knowledge gap for use of CALPUFF outside of regulatory applications, such as exposure analyses conducted in support of risk assessments and health studies. We compared deposition of cadmium (Cd), lead (Pb), and zinc (Zn) calculated with CALPUFF as a result of emissions from a zinc smelter with corresponding concentrations of the metals measured in attic dust and soil samples obtained from the surrounding area. On a point-by-point analysis, predictions from CALPUFF explained 11% (lead) to 53% (zinc) of the variability in concentrations measured in attic dust. Levels of heavy metals in soil interpolated to 100 residential addresses from the distribution of concentrations measured in soil samples also agreed well with deposition predicted with CALPUFF: R² of 0.46, 0.76, and 079 for Pb, Cd, and Zn, respectively. Community-average concentrations of Cd, Pb, and Zn measured in soil were significantly (p < 0.0001) and strongly correlated (R² ranged from 0.77 to 0.98) with predicted deposition rates. These findings demonstrate that CALPUFF can provide reasonably accurate predictions of the patterns of long-term air pollutant deposition in the near-field associated with emissions from a discrete source in complex terrain. Because deposition estimates are calculated as a linear function of air concentrations, CALPUFF is expected to be reliable model for prediction of long-term average, near-field ambient air concentrations in complex terrain as well.     

Improvements to lawn and garden equipment emissions estimates for Baltimore, Maryland

Lawn and garden equipment are a significant source of emissions of volatile organic compounds (VOCs) and other pollutants in suburban and urban areas. Emission estimates for this source category are typically prepared using default equipment populations and activity data contained in emissions models such as the U.S. Environmental Protection Agency's (EPA) NONROAD model or the California Air Resources Board's (CARB) OFFROAD model. Although such default data may represent national or state averages, these data are unlikely to reflect regional or local differences in equipment usage patterns because of variations in climate, lot sizes, and other variables. To assess potential errors in lawn and garden equipment emission estimates produced by the NONROAD model and to demonstrate methods that can be used by local planning agencies to improve those emission estimates, this study used bottom-up data collection techniques in the Baltimore metropolitan area to develop local equipment population, activity, and temporal data for lawn and garden equipment in the area. Results of this study show that emission estimates of VOCs, particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen oxides (NO(x)) for the Baltimore area that are based on local data collected through surveys of residential and commercial lawn and garden equipment users are 24-56% lower than estimates produced using NONROAD default data, largely because of a difference in equipment populations for high-usage commercial applications. Survey-derived emission estimates of PM and VOCs are 24 and 26% lower than NONROAD default estimates, respectively, whereas survey-derived emission estimates for CO, CO2, and NO(x) are more than 40% lower than NONROAD default estimates. In addition, study results show that the temporal allocation factors applied to residential lawn and garden equipment in the NONROAD model underestimated weekend activity levels by 30% compared with survey-derived temporal profiles.     

Influence of regional development policies and clean technology adoption on future air pollution exposure

Future air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 μg m^?3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by ～1 μg m^?3 relative to the base-case over most of the SJV with the exception of increases (～1 μg m^?3) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC). Low-density development increased the PM2.5 concentrations by 1–4 μg m^?3 over most of the region, with decreases (0.5–2 μg m^?3) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 μg m^?3. Exposure to primary PM components such as EC and OC increased 10–15% for high density development scenarios and decreased by 11–19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.     

Partitioning of metals in a degraded acid sulfate soil landscape: influence of tidal re-inundation

The oxidation and acidification of sulfidic soil materials results in the re-partitioning of metals, generally to more mobile forms. In this study, we examine the partitioning of Fe, Cr, Cu, Mn, Ni and Zn in the acidified surface soil (0-0.1 m) and the unoxidised sub-soil materials (1.3-1.5 m) of an acid sulfate soil landscape. Metal partitioning at this acidic site was then compared to an adjacent site that was previously acidified, but has since been remediated by tidal re-inundation. Differences in metal partitioning were determined using an optimised six-step sequential extraction procedure which targets the “labile”, “acid-soluble”, “organic”, “crystalline oxide”, “pyritic” and “residual” fractions. The surficial soil materials of the acidic site had experienced considerable losses of Cr, Cu, Mn and Ni compared to the underlying parent material due to oxidation and acidification, yet only minor losses of Fe and Zn. In general, the metals most depleted from the acidified surface soil materials exhibited the greatest sequestration in the surface soil materials of the tidally remediated site. An exception to this was iron, which accumulated to highly elevated concentrations in the surficial soil materials of the tidally remediated site. The “acid-soluble”, “organic” and “pyritic” fractions displayed the greatest increase in metals following tidal remediation. This study demonstrates that prolonged tidal re-inundation of severely acidified acid sulfate soil landscapes leads to the immobilisation of trace metals through the surficial accumulation of iron oxides, organic material and pyrite.