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Probabilistic Modeling of Sulfur and Nitrogen Pollution Controls and Their Relations With Income
- Source :
- The Journal of Environment & Development. 14:197-219
- Publication Year :
- 2005
- Publisher :
- SAGE Publications, 2005.
-
Abstract
- The objective of this article is to evaluate (via modeling) the impact of different pollution control scenarios on the shape of the income-emissions relationship. The simulation of emissions and emission controls was conducted using the Climate Change Risk Assessment Framework, which projects SO2 and NOx emissions from energy consumption and conversion and non-energy sources. The analysis of resulting scenario-, region-, and gas-specific income-emission curves suggests that income alone as a model driver of future emissions cannot adequately capture all plausible future SO2 or NOx emission pathways, or important differences among regions in those trajectories. Future social choices regarding the degree and strategy for environmental protection introduce large uncertainties in future projections and result in differing relationships between income and emissions. The analysis also suggests that the inverted-U shape (hypothesized Environmental Kuznets Curve) is only one of several plausible forms of the future relationship between income and emissions.
- Subjects :
- Pollution
business.industry
media_common.quotation_subject
05 social sciences
Geography, Planning and Development
Environmental resource management
Probabilistic logic
Climate change
Energy consumption
010501 environmental sciences
Management, Monitoring, Policy and Law
Development
01 natural sciences
0506 political science
Kuznets curve
Nutrient pollution
050602 political science & public administration
Econometrics
Environmental science
Risk assessment
business
0105 earth and related environmental sciences
media_common
Subjects
Details
- ISSN :
- 15525465 and 10704965
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- The Journal of Environment & Development
- Accession number :
- edsair.doi...........3cd8a7f0cd358d5e61685d2ba0538bb3
- Full Text :
- https://doi.org/10.1177/1070496504273611