The influence of water quality on the demand for residential development around Lake Erie
Notice bibliographique
Résumé
In early 1970s, it was said that Lake Erie was dead.In 1950s and 1970s, the water of the Lake was pea-green colored due to excessive phosphorous from sewage and runoffs from farmlands and homeowners.There were many closed beaches and fish from the Lake was not edible.However, water quality has improved dramatically since the Clean Water Act of 1972.The pace of residential and commercial development around the shoreline of Lake Erie increased considerably following substantial improvements in the Lake's water quality and clarity.A double-edged sword exists since increases in water quality are followed by increases in residential and lake-related development, which in turn can degrade the lake and the amenities it provides.In fact, although the phosphorous level declined in 1980s, we are observing an increasing trend starting from 1990s and the trend continues until today.As for water clarity, although its level hit the peak in 1995, we observe the decreasing trend afterwards.In this study, we focus on the effects of water quality on housing values to evaluate water quality-housing value as the relationship on the one side of the double-edged sword.Both the first and the second stage of hedonic price analysis are conducted with identified housing submarkets by using Hierarchical Clustering with quantized similarity measures in the region including Erie, Lorain, Ottawa and Sandusky Counties located Since the Clean Water Act of 1972, point source pollution has been controlled well.Nearly 100 percent of all industrial plants use control measures to reduce their toxic discharge, and the number of sewage treatment plants has doubled.Water quality of Lake Erie has improved since then.In 1983, phosphorous level in the Lake met its standard.The pace of residential and commercial development around the shoreline of Lake Erie increased considerably following substantial improvements in the lake's water quality and clarity in the 1970the 's and 1980the 's.Between 1982the and 1997, the amount of urban land use in the eight Ohio counties bordering Lake Erie increased 24.4%, an increase of 112,500 acres (USDA, National Resources Inventory).A significant portion of this development appears tied to Lake Erie.For example, the amount of urban development in Ottawa County, a county that contains a number of lake amenities and recreational sites, increased 53% during this fifteen year time period.The improvement in water quality enhanced the urban development along lakeshore counties.On the other hand, the impacts of urbanization and development in coastal areas threaten the very resources that make these areas attractive as places to live.The cumulative effects of non-point source pollution on coastal waters and aquatic life is a critical and increasing concern both nationally and in the Lake Erie watershed.Like many streams and rivers in the U.S., sedimentation and hydro-modification are cited as primary non-point sources affecting Lake Erie tributaries (Ohio EPA, 1996).Of particular concern is urban storm water pollution, which is fast becoming the most serious type of water pollution affecting Ohio's streams and near shore areas.This
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».