GIS 表示システムのための AML プログラミング開発(人間環境学)

A geographic data representation system for the area of Kyoto Prefecture was developed with Arc/Info^1 geographic information system (GIS). The Arc/Info system has a macro language called as AML (ARC Macro Language). Although AML is an interpreted language and has limited programming capabilities, it provides programming environment to implement complex applications using the all commands of Arc/Info and enhances productivity and user interface of the software. The presentation system was developed based on AML programming taking advantage of modular programming that is one of the features of AML. The basic geographic data used are obtained mainly from the publications on CD-ROM\u27s. The whole programming was constructed to have as simple block structures as possible to make the program easy to debug and reuse for future development. Here we discuss the method used for preparing the basic geographic data and the AML programming of the present system

Breast cancer risk and drinking water contaminated by wastewater: a case control study

BACKGROUND: Drinking water contaminated by wastewater is a potential source of exposure to mammary carcinogens and endocrine disrupting compounds from commercial products and excreted natural and pharmaceutical hormones. These contaminants are hypothesized to increase breast cancer risk. Cape Cod, Massachusetts, has a history of wastewater contamination in many, but not all, of its public water supplies; and the region has a history of higher breast cancer incidence that is unexplained by the population's age, in-migration, mammography use, or established breast cancer risk factors. We conducted a case-control study to investigate whether exposure to drinking water contaminated by wastewater increases the risk of breast cancer. METHODS: Participants were 824 Cape Cod women diagnosed with breast cancer in 1988–1995 and 745 controls who lived in homes served by public drinking water supplies and never lived in a home served by a Cape Cod private well. We assessed each woman's exposure yearly since 1972 at each of her Cape Cod addresses, using nitrate nitrogen (nitrate-N) levels measured in public wells and pumping volumes for the wells. Nitrate-N is an established wastewater indicator in the region. As an alternative drinking water quality indicator, we calculated the fraction of recharge zones in residential, commercial, and pesticide land use areas. RESULTS: After controlling for established breast cancer risk factors, mammography, and length of residence on Cape Cod, results showed no consistent association between breast cancer and average annual nitrate-N (OR = 1.8; 95% CI 0.6 – 5.0 for ≥ 1.2 vs. < .3 mg/L), the sum of annual nitrate-N concentrations (OR = 0.9; 95% CI 0.6 – 1.5 for ≥ 10 vs. 1 to < 10 mg/L), or the number of years exposed to nitrate-N over 1 mg/L (OR = 0.9; 95% CI 0.5 – 1.5 for ≥ 8 vs. 0 years). Variation in exposure levels was limited, with 99% of women receiving some of their water from supplies with nitrate-N levels in excess of background. The total fraction of residential, commercial, and pesticide use land in recharge zones of public supply wells was associated with a small statistically unstable higher breast cancer incidence (OR = 1.4; 95% CI 0.8–2.4 for highest compared with lowest land use), but risk did not increase for increasing land use fractions. CONCLUSION: Results did not provide evidence of an association between breast cancer and drinking water contaminated by wastewater. The computer mapping methods used in this study to link routine measurements required by the Safe Drinking Water Act with interview data can enhance individual-level epidemiologic studies of multiple health outcomes, including diseases with substantial latency

Biogeographical analyses to facilitate targeted conservation of orchid diversity hotspots in Costa Rica

Aim: We conduct a biogeographical assessment of orchids in a global biodiversity hotspot to explore their distribution and occurrences of local hotspots while identifying geographic attributes underpinning diversity patterns. We evaluate habitat characteristics associated with orchid diversity hotspots and make comparisons to other centres of orchid diversity to test for global trends. The ultimate goal was to identify an overall set of parameters that effectively characterize critical habitats to target in local and global orchid conservation efforts. Location: Costa Rica; Mesoamerica. Taxon: Orchidaceae. Methods: Data from an extensive set of herbarium records were used to map orchid distributions and to identify diversity hotspots. Hotspot data were combined with geographic attribute data, including environmental and geopolitical variables, and a random forest regression model was utilized to assess the importance of each variable for explaining the distribution of orchid hotspots. A likelihood model was created based on variable importance to identify locations where suitable habitats and unidentified orchid hotspots might occur. Results: Orchids were widely distributed and hotspots occurred primarily in mountainous regions, but occasionally at lower elevations. Precipitation and vegetation cover were the most important predictive variables associated with orchid hotspots. Variable values underpinning Costa Rican orchid hotspots were similar to those reported at other sites worldwide. Models also identified suitable habitats for sustaining orchid diversity that occurred outside of known hotspots and protected areas. Main conclusions: Several orchid diversity hotspots and potentially suitable habitats occur outside of known distributions and/or protected areas. Recognition of these sites and their associated geographic attributes provides clear targets for optimizing orchid conservation efforts in Costa Rica, although certain caveats warrant consideration. Habitats linked with orchid hotspots in Costa Rica were similar to those documented elsewhere, suggesting the existence of a common biogeographical trend regarding critical habitats for orchid conservation in disparate tropical regions.Universidad de Puerto Rico/[]/UPR/Puerto RicoUniversidad de Costa Rica/[]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Jardín Botánico Lankester (JBL

Can the Weak Surface Currents of the Cape Verde Frontal Zone Be Measured With Altimetry?

Three data types are compared in the low-current-velocity regime in the southeastern North Atlantic, between 12-degrees-N and 30-degrees-N, 29-degrees-W and 18-degrees-W: Geosat altimetric sea level and derived surface geostrophic velocities, shallow current meter velocities, and dynamic heights derived from hydrographic data from cruises 4, 6, and 9 of the research vessel Meteor. The four current meter daily time series, at depths around 200 m, were smoothed over 1 month; the altimetric geostrophic velocities were computed from sea surface slopes over 142 km every 17 days. The correlation coefficients between the current meter and altimetric geostrophic velocities range between 0.64 and 0.90 for the moorings near 29-degrees-N but between 0.32 and 0.71 for the two around 21-degrees-N; the associated rms discrepancies between the two measurement types range between 1.5 and 4.4 cm/s, which is 49% to 127% of the rms of the respective current meter time series. Dynamic heights relative to 1950 dbar for the months of November 1986 (d(M4)), November 1987 (d(M6)), and February 1989 (d(M9)) were computed from Meteor cruises 4, 6, and 9. Both dynamic heights and altimetric heights (h(M4), h(M6), h(M9)) were averaged over 1-degrees boxes for the duration of each cruise. Differences d(M4) - d(M6) and d(M9) - d(M6) were computed only at bins where at least one station from both cruises existed, Assuming that dynamic heights d in dynamic centimeters are equivalent to sea level h in centimeters, the standard deviation sigma of the differences ((h(M4) - h(M6)) - (d(M4) - d(M6))) and corresponding M9 - M6 values was 2.1 cm. This value (squared) is only 13% of the (5.8 cm)2 variance of the dynamic height differences and is indistinguishable from the 2.7- to 5.6-cm natural variability of sea level in the area expected between the times when the ship and the satellite sampled the ocean. The areally averaged discrepancy for M9 - M6 was only 0.7 cm, but the corresponding value for M4 - M6 was 5.2 cm. A systematic difference between the water vapor corrections used before and after July 1987 is responsible for the M4 - M6 difference. The average M4 - M6 discrepancy is only 0.1 cm using the Fleet Numerical Oceanography Center correction, with a standard deviation of 3.1 cm. In spite of the underlying differences in sampling and physics, including unknown barotropic components not included in our hydrographic dynamic heights, and in data errors, including water vapor, ionospheric, and orbital effects on the altimetry, consistent interannual changes of the mean sea level from the independently obtained altimetric and hydrographic data sets are obtained, and correlated seasonal changes in surface currents are observed with both altimetry and current meters

Distribution and habitat of unionid mussels and invasive sea lamprey larvae in the Paw Paw River, a tributary of Lake Michigan

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91129/1/j.1365-2427.2012.02777.x.pd

Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithms: 2. Using airborne remote sensing during SGP97 and SMEX02

Pixel-based effective soil hydraulic parameters are crucial inputs for large-scale hydroclimatic modeling. In this paper, we extend/apply a genetic algorithm (GA) approach for estimating these parameters at the scale of an airborne remote sensing (RS) footprint. To estimate these parameters, we used a time series of near-surface RS soil moisture data to invert a physically based soil-water-atmosphere-plant (SWAP) model with a (multipopulated) modified-microGA. Uncertainties in the solutions were examined in two ways: (1) by solving the inverse problem under various combinations of modeling conditions in a respective way; and (2) the same as the first method but the inverse solutions were determined in a collective way aimed at finding the robust solutions for all the modeling conditions (ensembles). A cross validation of the derived soil hydraulic parameters was done to check their effectiveness for all the modeling conditions used. For our case studies, we considered three electronically scanned thinned array radiometer (ESTAR) footprints in Oklahoma and four polarimetric scanning radiometer (PSR) footprints in Iowa during the Southern Great Plains 1997 (SGP97) Hydrology Experiment and Soil Moisture Experiment 2002 (SMEX02) campaigns, respectively. The results clearly showed the promising potentials of near-surface RS soil moisture data combined with inverse modeling for determining average soil hydrologic properties at the footprint scale. Our cross validation showed that parameters derived by method 1 under water table (bottom boundary) conditions are applicable also for free-draining conditions. However, parameters derived under free-draining conditions generally produced too wet near-surface soil moisture when applied under water table conditions. Method 2, on the other hand, produced robust parameter sets applicable for all modeling conditions used. These results were validated using distributed in situ soil moisture and soil hydraulic properties measurements, and texture-based data from the UNSODA database. In this study, we conclude that inverse modeling of RS soil moisture data is a promising approach for parameter estimation at large measurement support scale. Nevertheless, the derived effective soil hydraulic parameters are subject to the uncertainties of remotely sensed soil moisture data and from the assumptions used in the soil-water-atmosphere-plant modeling. Method 2 provides a flexible framework for accounting these sources of uncertainties in the inverse estimation of large-scale soil hydraulic properties. We have illustrated this flexibility by combining multiple data sources and various modeling conditions in our large-scale inverse modeling

Predicting invasions of North American basses in Japan using native range data and a genetic algorithm

Largemouth bass Micropterus salmoides and smallmouth bass M. dolomieu have been introduced into freshwater habitats in Japan, with potentially serious consequences for native fish populations. In this paper we apply the technique of ecological niche modeling using the genetic algorithm for rule-set prediction (GARP) to predict the potential distributions of these two species in Japan. This algorithm constructs a niche model based on point occurrence records and ecological coverages. The model can be visualized in geographic space, yielding a prediction of potential geographic range. The model can then be tested by determining how well independent point occurrence data are predicted according to the criteria of sensitivity and specificity provided by receiver–operator curve analysis. We ground-truthed GARP’s ability to forecast the geographic occurrence of each species in its native range. The predictions were statistically significant for both species (P , 0.001). We projected the niche models onto the Japanese landscape to visualize the potential geographic ranges of both species in Japan. We tested these predictions using known occurrences from introduced populations of largemouth bass, both in the aggregate and by habitat type. All analyses robustly predicted known Japanese occurrences (P , 0.001). The number of smallmouth bass in Japan was too small for statistical tests, but the 10 known occurrences were predicted by the majority of models

Formic acid synthesis using CO₂ as raw material: Techno-economic and environmental evaluation and market potential

The future of carbon dioxide utilisation (CDU) processes, depend on (i) the future demand of synthesised products with CO₂, (ii) the availability of captured and anthropogenic CO₂, (iii) the overall CO₂ not emitted because of the use of the CDU process, and (iv) the economics of the plant. The current work analyses the mentioned statements through different technological, economic and environmental key performance indicators to produce formic acid from CO₂, along with their potential use and penetration in the European context. Formic acid is a well-known chemical that has potential as hydrogen carrier and as fuel for fuel cells. This work utilises process flow modelling, with simulations developed in CHEMCAD, to obtain the energy and mass balances, and the purchase equipment cost of the formic acid plant. Through a financial analysis, with the net present value as selected metric, the price of the tonne of formic acid and of CO₂ are varied to make the CDU project financially feasible. According to our research, the process saves CO₂ emissions when compared to its corresponding conventional process, under specific conditions. The success or effectiveness of the CDU process will also depend on other technologies and/or developments, like the availability of renewable electricity and steam