Regional impervious surface estimation: an urban heat island application

This paper describes a GIS-based estimation method that can be used to forecast future amounts of impervious surface as a mitigation measure for urban heat island effect in a metropolitan region. The method is unique because it employs a regression model that links the existing amount of impervious surface to population and employment at the census tract level. This approach provides a means to forecast future amounts of impervious surface based on projected population and employment. The method also includes a detailed analysis of high-resolution aerial photography to divide impervious surfaces into different categories. Subdividing impervious surfaces is necessary to evaluate potential urban heat island mitigation policies for different types of impervious surface. The analysis here shows that the impervious surface in the metropolitan Atlanta region will increase to 2638 km2 2. “The Albedo is defined as the hemispherical reflectivity averaged over the solar spectrum. A perfect reflector has a = 1, and a perfect absorber has a = 0” (Pomerantz et al. 1999 Pomerantz, M. 1999. Reflective surfaces for cooler buildings and cities. Philosophical magazine B, 79: 1457–1476. [Taylor & Francis Online], [Web of Science ®] [Google Scholar], p. 1458). View all notes in 2030, an increase of 45% from 2000. The most common type of impervious surface is dark-coloured pavement. Within this study area, the analyses showed that two-thirds of impervious surfaces are dark. Replacing dark pavement with light pavement materials, therefore, represents an important opportunity to mitigate the urban heat island effect in the Atlanta region.     

Influence of temporally variable groundwater flow conditions on point measurements and contaminant mass flux estimations

Monitoring of contaminant concentrations, e.g., for the estimation of mass discharge or contaminant degradation rates, often is based on point measurements at observation wells. In addition to the problem, that point measurements may not be spatially representative, a further complication may arise due to the temporal dynamics of groundwater flow, which may cause a concentration measurement to be not temporally representative. This paper presents results from a numerical modeling study focusing on temporal variations of the groundwater flow direction. “Measurements” are obtained from point information representing observation wells installed along control planes using different well frequencies and configurations. Results of the scenario simulations show that temporally variable flow conditions can lead to significant temporal fluctuations of the concentration and thus are a substantial source of uncertainty for point measurements. Temporal variation of point concentration measurements may be as high as the average concentration determined, especially near the plume fringe, even when assuming a homogeneous distribution of the hydraulic conductivity. If a heterogeneous hydraulic conductivity field is present, the concentration variability due to a fluctuating groundwater flow direction varies significantly within the control plane and between the different realizations. Determination of contaminant mass fluxes is also influenced by the temporal variability of the concentration measurement, especially for large spacings of the observation wells. Passive dosimeter sampling is found to be appropriate for evaluating the stationarity of contaminant plumes as well as for estimating average concentrations over time when the plume has fully developed. Representative sampling has to be performed over several periods of groundwater flow fluctuation. For the determination of mass fluxes at heterogeneous sites, however, local fluxes, which may vary considerably along a control plane, have to be accounted for. Here, dosimeter sampling in combination with time integrated local water flux measurements can improve mass flux estimates under dynamic flow conditions.     

Economic assessment of managing processionary moth in pine forests: a case-study in Portugal

This paper assesses the private and social profitability of current strategies for managing processionary moth (Thaumetopoea pityocampa) in Portuguese pine forests, looking at economic and environmental costs and benefits. Costs include the expenses for forest treatment and the social costs of threats to human health (dermatitis amongst others); benefits are assessed in terms of both revenue and social benefits such as carbon fixation and recreation. The evaluation was done using Cost Benefit Analysis (CBA) as an analytical framework. While this tool is currently applied to forest and environmental assessment and specific applications to pest management strategies are to be found in agricultural economics, rather few attempts have been made in the field of forest pest management. In order to assess and compare with--without options, a case-study was analysed for the Setúbal Peninsula, south of Lisbon, an area where extensive stands of maritime pine (Pinus pinaster) grow. The exercise has shown that CBA can be a valuable tool for assessing the economic and social profitability of pest management. The results demonstrate that the loss of revenues in the no-management option is not sufficient to make pest management profitable for private forest owners in the short-term. Conversely, a social profit is gained as pest management minimizes health risks for humans and avoids possible recreational losses.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Evaluation of a Watershed Model for Estimating Daily Flow Using Limited Flow Measurements1

Abstract: The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash‐Sutcliffe model Efficiency (NSE) and mean relative error values of daily flow estimations were 0.66 and 15% for calibration, and 0.56 and 4% for validation, respectively. Also, further evaluation of the model’s estimation of flow at multiple locations was conducted with parametric paired t‐test and nonparametric sign test at a 95% confidence level. Among the five main stem stations, four stations were statistically shown to have good agreement between predicted and measured flows. SWAT underestimated the flow of the fifth main stem station possibly because of the existence of complex flood control measures near to the station. SWAT estimated the daily flow at one tributary station well, but with relatively large errors for the other two tributaries. The spatial pattern of predicted flows matched the measured ones well. Overall, it was concluded from the graphical comparisons and statistical analyses of the model results that SWAT was capable of reproducing continuous daily flows based on limited flow data as is the case in the UOC watershed.     

Estimating the variance in before-after studies

Problem

To simplify the computation of the variance in before-after studies, it is generally assumed that the observed crash data for each entity (or observation) are Poisson distributed. Given the characteristics of this distribution, the observed value (x_i) for each entity is implicitly made equal to its variance. However, the variance should be estimated using the conditional properties of this observed value (defined as a random variable), that is, f(x_i|μ_i), since the mean of the observed value is in fact unknown.

Method

Parametric and non-parametric bootstrap methods were investigated to evaluate the conditional assumption using simulated and observed data.

Results

The results of this study show that observed data should not be used as a substitute for the variance, even if the entities are assumed to be Poisson distributed. Consequently, the estimated variance for the parameters under study in traditional before-after studies is likely to be underestimated.

Conclusions

The proposed methods offer more accurate approaches for estimating the variance in before-after studies.     

Identifying the largest individual sample value from a two-way composite sampling design

Composite sampling techniques for identifying the largest individual sample value seem to be cost effective when the composite samples are internally homogeneous. However, since it is not always possible to form homogeneous composite samples, these methods can lead to higher costs than expected. In this paper we propose a two-way composite sampling design as a way to improve on the cost effectiveness of the methods available to identify the largest individual sample value.     

上海浦东国际机场飞机尾气排放对机场附近空气质量的影响

统计2012年10月和11月浦东机场飞机机型和航班架次,根据各类飞机起降的污染物排放设计工作参数,估算出2012年浦东机场飞机起降时排放的NO2、SO2、CO和HC的估算值。利用浦东新区13个空气监测子站二氧化氮和二氧化硫数据绘制等值线图。结果显示,机场所在的江镇点位和祝桥点位二氧化氮浓度变化受飞机影响很大,而飞机排放的二氧化硫对两个点位的影响可以忽略不计。建议采用改进飞机滑行路线、探讨征收飞机碳排放税等措施减少飞机尾气排放对空气质量的影响。     

化工装置停工放空过程中VOCs排放及估算方法

通过分析化工企业典型开、停车过程的排污节点,表明停车过程中大气挥发性有机污染物主要来自装置退料结束后挂壁、底部滞留和内部空间蒸气等滞留在设备内部的残余物料。在总结化工装置停工放空过程中大气挥发性有机物来源的基础上,讨论并提出大气污染排放量估算方法。     

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 €.