Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in “land use” regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM_2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.     

An application of economic choice experiments to a traditional land use—deer hunting and landscape change in the Scottish Highlands

Stalking (deer hunting) is an important land use and activity in the Scottish Highlands, and deer managers have traditionally maintained large numbers of female deer in order to supply a guaranteed number of stags for stalking. Unfortunately, grazing by large numbers of deer conflicts with environmental objectives that are seeking to improve upland habitats and increase the area of native Caledonian Pine forest. This study uses a multi-attribute choice experimental approach to quantify the various characteristics of the stalking experience to determine the value that amateur stalkers attach to the stag numbers, the landscape and other attibutes. Unlike previous applications of stated preference, a large proportion (one-third) of a full factorial design is used to present stalkers with different alternative stalking packages within a postal survey. The results indicate a way forward that could be agreeable to both deer managers and conservationists.     

CO-KRIGING TO INCORPORATE SCREENING DATA: HUDSON RIVER SEDIMENT PCBs1

ABSTRACT: Kriging methods of geostatistical analysis provide valuable techniques for analysis of sediment contamination problems, including interpolation of concentration maps from point data and estimation of global mean concentrations. Sample collection efforts frequently include preliminary screening data of considerably more extensive coverage than the laboratory analyses on which estimation is usually based. How should these be incorporated in kriging? Screening and laboratory analysis constitute two separate estimates of the same spatial field but of very different characteristics. A modified version of co-kriging is developed to include the imprecise screening information in the analysis of contaminant distribution. Use of the method is demonstrated on a data set of sediment PCB samples from the Upper Hudson River, for which preliminary categorical mass spectrometry screening was used to select a smaller set of samples for gas chromatograph analysis. The method is widely applicable to many situations of contaminant and natural resource estimation.     

Uncertainty Assessment for Management of Soil Contaminants with Sparse Data

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers probability safety requirement.     

APPLICATION OF KRIGING TO ESTIMATING MEAN ANNUAL PRECIPITATION IN A REGION OF OROGRAPHIC INFLUENCE1

ABSTRACT: Estimates of mean annual precipitation (MAP) over areas are the starting point for all computations of water and chemical balances for drainage basins and surface water bodies. Any errors in the estimates of MAP are propagated through the balance computations. These errors can be due to: (1) failures of individual gages to collect the amount of precpitation that actually falls; (2) operator errors; and (3) failure of the raingage network to adequately sample the region of interest. This paper attempts to evaluate the last of these types of error by applying kriging in two different approaches to estimating MAP in New Hampshire and Vermont, USA. The data base is the 1951–1980 normal precipitation at 120 raingages in the two states and in adjacent portions of bordering states and provinces. In the first approach, kriging is applied directly to the MAP values, while in the second, kriging is applied to a “precipitation delivery factor” that represents the MAP with the orographic effect removed. The first approach gives slightly better kriged estimates of MAP at seven validation stations that were not included in the original analysis, but results in an error surface that is highly contorted and in larger maximum errors over most of the region. The second approach had a considerably smoother error surface and, thus, is generally preferable as a basis for point and areal estimates of MAP. MAP estimates in the region have 95 percent confidence intervals of about 20 cm/yr at low and moderate elevations, and up to 35 cm/yr at high elevations. These uncertainties amount to about 20 percent of estimated MAP values.     

STATISTICAL AND GEOSTATISTICAL MODELLING OF PRELIMINARILY ADJUSTED DEFOLIATION ON AN EUROPEAN SCALE

Since 1987 tree crown condition is surveyed annually in large parts of Europe mainly in terms of defoliation. The plot-wise means of defoliation from 1994 to 2000 were evaluated by General Linear Models (GLM) in order to describe country-specific levels of defoliation and age-trends. Additional runs with estimates for influences of insects and fungi were performed. The amount of variance of defoliation explained by country, age and its interaction was between 35% and 59% for the main tree species, except for Quercus ilex. Additionally, up to 10% could be explained by the inclusion of estimates for infestations by insects and fungi. Residuals of the GLMs were taken as a measure of forest condition not biased by country or age effects and interpreted as preliminarily adjusted defoliation (PAD). PAD values were analysed using geostatistical methods. The modelled spatial autocorrelations were used for kriging. The resulting maps give an overview on regions with elevated defoliation, which may pinpoint regional causes of defoliation. The elimination of methodologically caused variance is a precondition of any cause–effect oriented analyses. The combination of explorative modelling and geostatistics will promote the choice of further promising predictors.     

A national ozone biomonitoring program--results from field surveys of ozone sensitive plants in northeastern forests (1994-2000)

Ozone biomonitoring is a detection and monitoring techniquethat involves documenting ozone-induced visible injury toknown ozone-sensitive species under conditions of ambientexposure. The USDA Forest Service administers a long-term,nationwide ozone biomonitoring program to address public andscientific concerns about ozone impacts on forest health. Asystematic grid is used as the basis for biomonitoring sitelocations. At each site, trained field crews evaluate amaximum of thirty plants of up to six species and record the amount and severity of leaf-injury on individualplants. Injury from ozone was found more often on biomonitoring sites in the eastern Unites States than in theinterior or west-coast areas. Further results from thenortheast reveal that in any year, there is a higherpercentage of ozone-injured plants with more severe symptomsin areas with relatively high ozone concentrations than inareas with relatively low ozone. In very dry years (e.g.,1999) the percentage of injured plants and injury severityestimates are both sharply reduced even though ambient ozoneexposures are high. These findings demonstrate thatbiomonitoring data provide meaningful evidence of when highozone concentrations during the growing season have biologicalsignificance. Any assessment of ozone stress in the forestenvironment must include both biomonitoring (i.e., plantresponse) and air quality data to be complete.     

THREE‐DIMENSIONAL KRIGING ANALYSIS OF SEDIMENT MERCURY DISTRIBUTION: A CASE STUDY1

ABSTRACT: This study presents an application of a three‐dimensional kriging technique to estimate spatial distribution of total mercury (Hg) in the Cedar‐Ortega Rivers watershed located in the lower St. Johns River basin, Florida. The kriging procedures, including preliminary data analysis, structural data analysis and the log kriging estimation, are presented. Results show watershed wide Hg contamination of river sediment to a depth of 1.0 m. A three‐dimensional plot of Hg against the Florida Sediment Assessment Guidelines (i.e., the probable effect level or PEL) demonstrates that the Cedar River is more contaminated with Hg than the rest of the watershed. The maximum sediment depth with Hg concentrations above PEL value (0.696 mg/kg) is 1.5 m. Hg concentrations at or above this level could pose a significant hazard to aquatic organisms. Analysis of the spatial distribution of Hg in the watershed finds multiple input sources. This study suggests that there is a need to identify the major sources of Hg in the watershed, and to determine the pathways that allow Hg to enter the river.     

The Valuation of Health Effects Caused by Stationary Sources–Related SO2 Emissions: The Adaptation of Impact Pathway Approach in Taiwan

This paper presents the externalities of sulfur dioxide (SO₂) in the Taichung metropolitan, Taiwan. The human effects of SO₂ from stationary sources are a key element for local air quality management. A methodology to evaluate those effects in monetary term had been adapted and applied. This method was modified from the EU-based impact pathway approach link to the skill of geographic information systems. The studied area was divided into 66 districts and the quantity of SO₂ was allocated to each district. Then, the ambient concentration of SO₂ was estimated by using the ordinary kriging method. A risk analysis was employed to characterize the health impacts caused by SO₂. Finally, a monetary transfer approach based on the European data was conducted to estimate local damage costs per ton of SO₂. Health impacts, especially acute mortality, dominate in term of costs. The calculation showed that damage costs ranged from 0.56 to 7.38 USD/kg SO₂ based on the 2002 emission data. The results could be used in the internalization of SO₂ externalities and management of the stationary sources in the studied area. This paper also concludes that the externalities caused by stationary-related SO₂ emissions are some 28.5 million US dollars in Taichung metropolitan (Taiwan) in 2002.     

Mapping aerial metal deposition in metropolitan areas from tree bark: a case study in Sheffield, England

We investigated the use of metals accumulated on tree bark for mapping their deposition across metropolitan Sheffield by sampling 642 trees of three common species. Mean concentrations of metals were generally an order of magnitude greater than in samples from a remote uncontaminated site. We found trivially small differences among tree species with respect to metal concentrations on bark, and in subsequent statistical analyses did not discriminate between them. We mapped the concentrations of As, Cd and Ni by lognormal universal kriging using parameters estimated by residual maximum likelihood (REML). The concentrations of Ni and Cd were greatest close to a large steel works, their probable source, and declined markedly within 500 m of it and from there more gradually over several kilometres. Arsenic was much more evenly distributed, probably as a result of locally mined coal burned in domestic fires for many years. Tree bark seems to integrate airborne pollution over time, and our findings show that sampling and analysing it are cost-effective means of mapping and identifying sources.