Unusually high-pitched neonate distress calls of the open-habitat Mongolian gazelle (<Emphasis Type="Italic">Procapra gutturosa</Emphasis>) and their anatomical and hormonal predictors

In neonate ruminants, the acoustic structure of vocalizations may depend on sex, vocal anatomy, hormonal profiles and body mass and on environmental factors. In neonate wild-living Mongolian gazelles Procapra gutturosa, hand-captured during biomedical monitoring in the Daurian steppes at the Russian-Mongolian border, we spectrographically analysed distress calls and measured body mass of 22 individuals (6 males, 16 females). For 20 (5 male, 15 female) of these individuals, serum testosterone levels were also analysed. In addition, we measured relevant dimensions of the vocal apparatus (larynx, vocal folds, vocal tract) in one stillborn male Mongolian gazelle specimen. Neonate distress calls of either sex were high in maximum fundamental frequency (800–900 Hz), but the beginning and minimum fundamental frequencies were significantly lower in males than in females. Body mass was larger in males than in females. The levels of serum testosterone were marginally higher in males. No correlations were found between either body mass or serum testosterone values and any acoustic variable for males and females analysed together or separately. We discuss that the high-frequency calls of neonate Mongolian gazelles are more typical for closed-habitat neonate ruminants, whereas other open-habitat neonate ruminants (goitred gazelle Gazella subgutturosa, saiga antelope Saiga tatarica and reindeer Rangifer tarandus) produce low-frequency (<200 Hz) distress calls. Proximate cause for the high fundamental frequency of distress calls of neonate Mongolian gazelles is their very short, atypical vocal folds (4 mm) compared to the 7-mm vocal folds of neonate goitred gazelles, producing distress calls as low as 120 Hz.     

Potential Impact of Climate Change on Hurricane Flooding Inundation,Population Affected and Property Damages in Corpus Christi1

Frey, Ashley E., Francisco Olivera, Jennifer L. Irish, Lauren M. Dunkin, James M. Kaihatu, Celso M. Ferreira, and Billy L. Edge, 2010. Potential Impact of Climate Change on Hurricane Flooding Inundation, Population Affected and Property Damages in Corpus Christi. Journal of the American Water Resources Association (JAWRA) 1–11. DOI: 10.1111/j.1752-1688.2010.00475.x Abstract: The effect of climate change on storm-surge flooding and the implications for population and structural damages on the city of Corpus Christi, Texas, was investigated. The study considered the influence of sea level rise and hurricane intensification, both influenced by climate change. Combinations of future carbon dioxide equivalent emission rates and carbon dioxide doubling sensitivities, based on findings of the Intergovernmental Panel on Climate Change, were considered to define future climate scenarios. A suite of physically based numerical models for hurricane winds and the resulting waves, surge, and morphological change at the coast were used to determine flooded areas, population affected, and property damages for Hurricanes Bret, Beulah, and a version of Carla shifted south from its original track, under present and predicted future climate conditions. A comparison of the economic damages for current climate conditions and for the 2080s climate scenario shows that, for Carla (shifted), there will be an increase in the range of $270-1,100 million; for Beulah, of $100-390 million; and, for Bret, of $30-280 million. A similar analysis was also conducted for 2030s predicted climate scenarios. Overall, the comparison of the results for the different climate conditions indicates what the destructive consequences of climate change could be, even within the somewhat short time frame of 80 years considered here.     

Characterization of indoor air quality and resident health in an Arizona senior housing apartment building

A survey of key indoor air quality (IAQ) parameters and resident health was carried out in 72 apartments within a single low-income senior housing building in Phoenix, Arizona. Air sampling was carried out simultaneously with a questionnaire on personal habits and general health of residents. Mean PM₁₀ concentrations are 66±16, 58±13, and 24±3 μg/m³ and mean PM_2.5 concentrations are 62±16, 53±13, and 20±2 μg/m³ for the living room, kitchen, and outdoor balcony, respectively. Median PM₁₀ concentrations are 17, 18 and 17 μg/m³ and median PM_2.5 concentrations are 13, 14, and 13 μg/m³, respectively. The initial results indicate that increased indoor particle concentrations coincide with residents who report smoking cigarettes. Indoor formaldehyde concentrations revealed median levels of 36.9, 38.8, and 4.3 ppb in the living room, kitchen, and balcony, respectively. Results show that 36% of living room samples and 44% of kitchen samples exceeded the Health Canada REL for chronic exposure to formaldehyde (40 ppb). Associations between occupants’ behavior, self-reported health conditions, and IAQ are evaluated.

Implications:This study provides a characterization of indoor air quality (IAQ) of subsidized apartments for seniors in Phoenix, Arizona. It is important for policy makers to understand the environments in which low-income seniors live, as they are vulnerable to the health impacts from poor IAQ. Formaldehyde concentrations were found to exceed the Health Canada 8-hr reference exposure level (REL) for up to 44% of indoor samples. Particulate matter exposure was governed by resident behavior (i.e., smoking). Associations between occupants’ behavior, IAQ, and self-reported health conditions are evaluated. This work can provide a foundation for subsequent remediation of IAQ conditions.     

Methods for Quantifying Variability and Uncertainty in AP-42 Emission Factors: Case Studies for Natural Gas-Fueled Engines

Abstract

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as ~±10% to as much as -90 to 21+180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

Road grade estimation for on-road vehicle emissions modeling using light detection and ranging data

Vehicle-specific power (VSP) is useful for explaining a substantial portion of variability in real-world vehicle emissions, such as those measured with portable emissions monitoring systems (PEMS). VSP is a function of vehicle speed, acceleration, and road grade. Road grade is shown to significantly affect estimates of both VSP and of real-world emissions via sensitivity analysis and analysis of empirical data. However, road grade is difficult to measure reliably using PEMS. Therefore, alternative methods for estimating road grade were identified and compared. A preferred method for estimating road grade was explored in more detail based on light detection and ranging (LIDAR) data. The method includes buffering LIDAR data onto roadway maps using a geographic information system tool, defining segments of roadway based on criteria pertaining to vertical curvature, quantification of roadway elevations within the buffered segments, and estimation of road grade and banking by fitting a plane to each segment. Factors influencing errors in road grade estimates are discussed. The method was evaluated by application to selected interstate highways and comparison to design drawing data. The development and application of LIDAR-based road grade data are demonstrated via a case study using PEMS data collected in the Research Triangle Park, NC, area. LIDAR data are shown to be reliable and accurate for road grade estimation for vehicle emissions modeling.     

Quantification of variability and uncertainty in lawn and garden equipment NOx and total hydrocarbon emission factors

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NOx emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NOx. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (EIs).     

The effect of environmental regulation on firms' competitive performance: the case of the building & construction sector in some EU regions

There is a considerable debate on the effects of environmental regulation on competitive performance. Based on survey data, this paper analyzesthe two main research questions, derived from literature, on the links between environmental regulation and competitiveness, by focusing on firms operating in the building and construction sector, i.e.: 1) whether environmental policy stringency affects the competitive performance of firms in the building and construction sector 2) and how a specific form of environmental regulation (direct regulation, economic instruments and soft instruments) affects this performance? By applying a regression analysis, we find that a more stringent environmental regulation, measured by inspection frequency, provides a positive impulse for increasing investments in advanced technological equipment and innovative products and on business performance. Moreover, a well-designed “direct regulation” appears to be the most effective policy instrument for prompting the positive impact of environmental policies on innovation and intangible performance while economic instruments do negatively affect business performance.