Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

Religion and environmental politics in the US House of Representatives

Does religion affect legislators’ behavior on environmental policy in the US? Studies of environmental policy making have not examined this question, although the literature suggests that religion might affect legislative behavior on environmental policy. This study examines the relationship between US House members’ religion and roll-call voting on environmental legislation from 1973 to 2009. It finds significant differences across religious traditions. Legislators’ party and characteristics of constituencies relevant to environmental politics increasingly, but not entirely, mediate these differences.     

Recovery of Sediment Characteristics in Moraine,Headwater Streams of Northern Minnesota After Forest Harvest1

Merten, Eric C., Nathaniel A. Hemstad, Randall K. Kolka, Raymond M. Newman, Elon S. Verry, and Bruce Vondracek, 2010. Recovery of Sediment Characteristics in Moraine, Headwater Streams of Northern Minnesota After Forest Harvest. Journal of the American Water Resources Association (JAWRA) 46(4): 733-743. DOI: 10.1111/j.1752-1688.2010.00445.x Abstract: We investigated the recovery of sediment characteristics in four moraine, headwater streams in north-central Minnesota after forest harvest. We examined changes in fine sediment levels from 1997 (preharvest) to 2007 (10 years postharvest) at study plots with upland clear felling and riparian thinning, using canopy cover, proportion of unstable banks, surficial fine substrates, residual pool depth, and streambed depth of refusal as response variables. Basin-scale year effects were significant (p < 0.001) for all responses when evaluated by repeated-measures ANOVAs. Throughout the study area, unstable banks increased for several years postharvest, coinciding with an increase in windthrow and fine sediment. Increased unstable banks may have been caused by forest harvest equipment, increased windthrow and exposure of rootwads, or increased discharge and bank scour. Fine sediment in the channels did not recover by summer 2007, even though canopy cover and unstable banks had returned to 1997 levels. After several storm events in fall 2007, 10 years after the initial sediment input, fine sediment was flushed from the channels and returned to 1997 levels. Although our study design did not discern the source of the initial sediment inputs (e.g., forest harvest, road crossings, other natural causes), we have shown that moraine, headwater streams can require an extended period (up to 10 years) and enabling event (e.g., high storm flows) to recover from large inputs of fine sediment.     

Enzyme-based resource allocated decomposition and landscape heterogeneity in the Florida Everglades

Enzyme catalyzed reactions are generally considered the rate-limiting step in organic matter degradation and may be significantly influenced by the structure and composition of plant communities. Changes in these rates have the potential to effect long-term peat accumulation and influence the topography of a wetland ecosystem. To determine habitat influences on enzyme activities, we examined slough and sawgrass plots within enriched and reference phosphorus (P) sites in the Everglades. Assays were performed for the enzymes involved in carbon (C), nitrogen (N), and P cycling and lignin depolymerization. Enzyme activities were normalized and analyzed in terms of a resource allocation strategy. Plant composition was found to significantly alter the allocation of enzymatic resources due to varying substrate complexities. Potential decomposition in the slough was less influenced by lignin than in the sawgrass habitats. Additionally, an index relating hydrolytic and oxidative enzymes was significantly greater in the slough habitats, whereas C/N ratios were significantly lower. These indices suggest more favorable decomposition conditions and thus slower peat accretion within the slough communities, which may contribute to the development of elevation differences within the sawgrass ridge and slough topography of the Everglades.     

Sorption and degradation of pesticides in nursery recycling ponds

Knowledge of pesticide distribution and persistence in nursery recycling pond water and sediment is critical for preventing phytotoxicity of pesticides during water reuse and to assess their impacts to the environment. In this study, sorption and degradation of four commonly used pesticides (diazinon, chlorpyrifos, chlorothalonil, and pendimethalin) in sediments from two nursery recycling ponds was investigated. Results showed that diazinon and chlorothalonil were moderately sorbed [K(OC) (soil organic carbon distribution coefficient) from 732 to 2.45 x 10(3) mL g(-1)] to the sediments, and their sorption was mainly attributable to organic matter content, whereas chlorpyrifos and pendimethalin were strongly sorbed (K(OC) > or = 7.43 x 10(3) mL g(-1)) to the sediments, and their sorption was related to both organic matter content and sediment texture. The persistence of diazinon and chlorpyrifos was moderate under aerobic conditions (half-lives = 8 to 32 d), and increased under anaerobic conditions (half-lives = 12 to 53 d). In contrast, chlorothalonil and pendimethalin were quickly degraded under aerobic conditions with half-lives < 2.8 d, and their degradation was further enhanced under anaerobic conditions (half-lives < 1.9 d). The strong sorption of chlorpyrifos and pendimethalin by the sediments suggests that the practice of recycling nursery runoff would effectively retain these compounds in the recycling pond, minimizing their offsite movement. The prolonged persistence of diazinon and chlorpyrifos, however, implies that incidental spills, such as overflows caused by storm events, may contribute significant loads of such pesticides into downstream surface water bodies.     

Soil organic carbon and nitrogen accumulation in plots of rhizoma perennial peanut and bahiagrass grown in elevated carbon dioxide and temperature

Carbon sequestration in soils might mitigate the increase of carbon dioxide (CO2) in the atmosphere. Two contrasting subtropical perennial forage species, bahiagrass (BG; Paspalum notatum Flügge; C4), and rhizoma perennial peanut (PP; Arachis glabrata Benth.; C3 legume), were grown at Gainesville, Florida, in field soil plots in four temperature zones of four temperature-gradient greenhouses, two each at CO2 concentrations of 360 and 700 micromol mol(-1). The site had been cultivated with annual crops for more than 20 yr. Herbage was harvested three to four times each year. Soil samples from the top 20 cm were collected in February 1995, before plant establishment, and in December 2000 at the end of the project. Overall mean soil organic carbon (SOC) gains across 6 yr were 1.396 and 0.746 g kg(-1) in BG and PP, respectively, indicating that BG plots accumulated more SOC than PP. Mean SOC gains in BG plots at 700 and 360 micromol mol(-1) CO2 were 1.450 and 1.343 g kg(-1), respectively (not statistically different). Mean SOC gains in PP plots at 700 and 360 micromol mol(-1) CO2 were 0.949 and 0.544 g kg(-1), respectively, an increase caused by elevated CO2. Relative SON accumulations were similar to SOC increases. Overall mean annual SOC accumulation, pooled for forages and CO2 treatments, was 540 kg ha(-1) yr(-1). Eliminating elevated CO2 effects, overall mean SOC accumulation was 475 kg ha(-1) yr(-1). Conversion from cropland to forages was a greater factor in SOC accumulation than the CO2 fertilization effect.     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

Ambient Air Monitoring for Sulfur Compounds

The role of sulfur compounds in our environment has been the subject of much speculation during the past two decades. An evaluation of the effect of man-made contributions to the biogeochemical sulfur cycle requires a comprehensive examination of source magnitudes, atmospheric concentrations and removal processes. Many voids exist in our present knowledge of these parameters despite the contributions of numerous researchers. Adequate information is needed concerning the various forms of sulfur as well as other critical constituents which exist in our biosphere so that their interrelationship and role in the mechanisms of the sulfur cycle may be more fully understood.