Use and misuse of motor-vehicle crash death rates in assessing highway-safety performance

OBJECTIVES: The objectives of the article are to assess the extent to which comparisons of motor-vehicle crash death rates can be used to determine the effectiveness of highway-safety policies over time in a country or to compare policy effectiveness across countries. METHODS: Motor-vehicle crash death rates per mile traveled in the 50 U.S. states from 1980 to 2003 are used to show the influence on these rates of factors independent of highway-safety interventions. Multiple regression models relating state death rates to various measures related to urbanization and demographics are used. RESULTS: The analyses demonstrate strong relationships between state death rates and urbanization and demographics. Almost 60% of the variability among the state death rates can be explained by the independent variables in the multiple regression models. When the death rates for passenger vehicle occupants (i.e., excluding motorcycle, pedestrian, and other deaths) are used in the regression models, almost 70% of the variability in the rates can be explained by urbanization and demographics. CONCLUSIONS: The analyses presented in the article demonstrate that motor-vehicle crash death rates are strongly influenced by factors unrelated to highway-safety countermeasures. Overall death rates should not be used as a basis for judging the effectiveness (or ineffectiveness) of specific highway-safety countermeasures or to assess overall highway-safety policies, especially across jurisdictions. There can be no substitute for the use of carefully designed scientific evaluations of highway-safety interventions that use outcome measures directly related to the intervention; e.g., motorcyclist deaths should be used to assess the effectiveness of motorcycle helmet laws. While this may seem obvious, there are numerous examples in the literature of death rates from all crashes being used to assess the effectiveness of interventions aimed at specific subsets of crashes.     

Prediction of mono- and polycyclic aromatic hydrocarbon degradation in spiked soils using cyclodextrin extraction

In this study, an aqueous-based hydroxypropyl-beta-cyclodextrin (HPCD) extraction technique was assessed for its capacity to determine the microbially degradable fraction of mono- and polycyclic aromatic hydrocarbons in four dissimilar soils. A linear relationship (slope=0.90; R2=0.89), approaching 1:1 between predicted and observed phenanthrene mineralization, was demonstrated for the cyclodextrin extraction; however, the water only extraction underestimated the microbially available fraction by a factor of three (slope=3.35; R2=0.64). With respect to determining the mineralizable fraction of p-cresol in soils, the cyclodextrin extraction (slope=0.94; R2=0.84) was more appropriate than the water extraction (slope=1.50; R2=0.36). Collectively, these results suggested that the cyclodextrin extraction technique was suitable for the prediction of the mineralizable fraction of representative PAHs and phenols present in dissimilar soils following increasing soil-contaminant contact times. The assessment of the microbial availability of contaminants in soils is important for a more representative evaluation of soil contamination.     

Stationary sources of airborne lead: a comparison of emissions data for southern California

Estimates for the air releases of lead from stationary point sources are considered for the South Coast Air Basin of California. We have examined four databases published by U.S. Environmental Protection Agency, the California Air Resources Board, and the South Coast Air Quality Management District. Our analysis indicates that none of the databases includes every emitting facility in the South Coast Air Basin of California and that other discrepancies among the databases exist. Additionally, the data have been analyzed for temporal variation, and some of the California Air Resources Board data are not current. The South Coast Air Quality Management District inventory covers 12 times more facilities in 2001 than in 1996. From this analysis, we conclude that all four of the databases would benefit by sharing data, increasing transparency, analyzing uncertainty, and standardizing emission estimation methods.     

Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.     

Elements of a cost-benefit analysis for improving salmonid spawning habitat in the River Wye

Contingent valuation methods were used to derive an economic value for salmonid spawning habitat restoration. Anglers' willingness to pay for such restoration and farmers' willingness to accept compensation for lost productivity due to the restoration were investigated using questionnaire and face-to-face surveys, respectively. These elements were combined with the Wye Habitat Improvement Project (WHIP) budget into a cost-benefit analysis (CBA) based upon direct use values only. The CBA assumed that the WHIP will improve salmonid stock. Different levels of investment were considered and the CBA gave a positive net present value indicating an economically viable project and benefit-to-cost ratios greater than one for minor projects. However, the number of anglers using the Wye would need to double or triple in order to justify the full WHIP budget. Management of an environmental resource must consider users' and stakeholders' needs and opinions. It was found that anglers on the Wye value habitat/scenery in its own right and that this played an important part in the activity. Farmers' agreement regarding involvement in such projects was more likely to be determined by their political and ethical views than receiving an economic compensation.     

Variations in stream water and sediment phosphorus among select Ozark catchments

Stream sediments play a large role in the transport and fate of soluble reactive phosphorus (SRP) in stream ecosystems, and equilibrium P concentrations (EPC 0) of benthic sediments at which P is neither adsorbed nor desorbed are often related to stream water SRP concentrations. This study evaluated (i) the variation among water chemistry and sediment-P interactions among streams draining catchments that varied in the land use; (ii) the relations between SRP concentration, sediment EPC 0, and other measured abiotic factors (e.g., particle size distribution, slope of linear sorption isotherms, etc.) in the stream sediments; and (iii) the use of the traditional Mehlich-3 (M3) soil extraction on stream sediments to elucidate other abiotic factors (e.g, M3P, P saturation ratio, etc.) related to SRP concentration in stream sediments. Stream water and sediments were sampled at 22 selected Ozark streams in northwest Arkansas during fall 2003 and spring 2004. Nitrate-N concentrations in the water column (r = 0.69) and modified P saturation ratios (PSR mod) ) of the benthic sediments (r = 0.79) at the selected streams increased with an increase in percent pasture in the catchments, whereas SRP concentration (r = -0.56) and Mehlich-3-extractable P (M3P) content (r = -0.47) decreased with an increase in the percent forested area. Soluble reactive P concentrations in the stream water were positively correlated to sediment EPC 0 (r = 0.51), although sediment EPC(0) was generally greater than SRP. The M3 soil extraction was useful in identifying abiotic factors related to SRP concentrations in the selected streams, in particular SRP concentrations were positively correlated to M3P contents (r = 0.50) and PSR mod (r = 0.71) of the benthic sediments. Thus, M3P and EPC 0 estimates from stream sediments may be valuable yet simple indicators of whether benthic sediments act as sinks or sources of P in fluvial systems, as well as estimating changes in stream SRP concentrations.     

Vertical distribution of phosphorus in agricultural drainage ditch soils

Pedological processes such as gleization and organic matter accumulation may affect the vertical distribution of P within agricultural drainage ditch soils. The objective of this study was to assess the vertical distribution of P as a function of horizonation in ditch soils at the University of Maryland Eastern Shore Research Farm in Princess Anne, Maryland. Twenty-one profiles were sampled from 10 agricultural ditches ranging in length from 225 to 550 m. Horizon samples were analyzed for total P; water-extractable P; Mehlich-3 P; acid ammonium oxalate-extractable P, Fe, and Al (P ox, Fe ox, Al ox); pH; and organic C (n = 126). Total P ranged from 27 to 4882 mg kg(-1), P ox from 4 to 4631 mg kg(-1), Mehlich-3 P from 2 to 401 mg kg(-1), and water-extractable P from 0 to 17 mg kg(-1). Soil-forming processes that result in differences between horizons had a strong relationship with various P fractions and P sorption capacity. Fibric organic horizons at the ditch soil surface had the greatest mean P ox, Fe ox, and Al ox concentrations of any horizon class. Gleyed A horizons had a mean Fe ox concentrations 2.6 times lower than dark A horizons and were significantly lower in total P and P ox. Variation in P due to organic matter accumulation and gleization provide critical insight into short- and long-term dynamics of P in ditch soils and should be accounted for when applying ditch management practices.     

NUTRIENT AND β17‐ESTRADIOL LOSS IN RUNOFF WATER FROM POULTRY LITTERS1

ABSTRACT: A main water quality concern is accelerated eutrophication of fresh waters from nonpoint source pollution, particularly nutrient transport in surface runoff from agricultural areas and confined animal feeding operations. This study examined nutrient and β₁₇‐estradiol concentrations in runoff from small plots where six poultry litters were applied at a rate of about 67 kg/ha of total phosphorus (TP). The six poultry litter treatments included pelleted compost, pelleted litter, raw litter, alum (treated) litter, pelleted alum litter, and normal litter (no alum). Four replicates of the six poultry litter treatments and a control (plots without poultry litter application) were used in this study. Rainfall simulations at intensity of 50 mm/hr were conducted immediately following poultry litter application to the plots and again 30 days later. Composite runoff samples were analyzed for soluble reactive phosphorus (SRP), ammonia (NH₄), nitrate (NO₃), TP, total nitrogen (TN) and β₁₇‐estradiol concentrations. In general, poultry litter applications increased nutrient and β₁₇‐estradiol concentrations in runoff water. Ammonia and P concentrations in runoff water from the first simulation were correlated to application rates of water extractable NH₄ (R²= 0.70) and P (R²= 0.68) in the manure. Results suggest that alum applications to poultry litter in houses in between flocks is an effective best management practice for reducing phosphorus (P) and β₁₇‐estradiol concentrations in runoff and that pelleted poultry litters may increase the potential for P and β₁₇‐estradiol loss in runoff water. Inferences regarding pelleted poultry litters should be viewed cautiously, because the environmental consequence of pelleting poultry litters needs additional investigation.     

Forecasting air quality time series using deep learning

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O₃) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O₃ exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours.

Implications: Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.     

Evaluation of PCR-based quantification techniques to estimate the abundance of atrazine chlorohydrolase gene atzA in rhizosphere soils

There are many challenges in the accurate quantification of bacterial genes, such as the atrazine-degrading enzyme antA from Pseudomonas sp. strain ADP, from soil samples. We compared four quantitative methods for enumeration of atrazine-degrading bacteria in rhizosphere environments and utilized the optimal probe-based real-time polymerase chain reaction (PCR)-based method in an ongoing bioremediation experiment to monitor atzA copy number over time. We compared three quantitative PCR (qPCR) based methods--quantitative competitive PCR and two real-time qPCR methods--to traditional dilution-plate counting techniques. The optimal real-time qPCR assay was then used to monitor atzA copy number over time in the robust atrazine-degrading Pseudomonas sp. strain ADP-spiked rhizosphere environment. The use of sensitive and reliable probe-based real-time qPCRs for the enumeration of bacterial catabolic genes allows for their detection from soil samples and monitoring of potential degradative populations over time. The addition of arrazine-biodegrading bacteria into arrazine-contaminated sites to remove entrapped atrazine is a promising approach for mitigating atrazine pollution and its metabolites. The methodology contained herein will allow for optimal monitoring of atzA in rhizosphere soil with or without the addition of biodegradative Pseudomonas sp. strain ADP of bacteria.