Global Emission Ceiling Versus International Cap and Trade: What is the Most Efficient System to Solve the Climate Change Issue?

We model the climate change issue as a pollution control game with the purpose of comparing two possible departures from the business as usual (BAU) where countries noncooperatively choose their emission levels. In the first scenario, players have to agree on a global emission cap (GEC) that is enforced by a uniform taxation scheme. They still behave strategically when choosing emission levels but are now subject to the coupled constraint imposed by the cap. The second scenario consists of the implementation of an international cap and trade (ICT) system. In this case, players decide on their emission quotas, and emission trading is allowed. A three heterogenous player quadratic game serves as a basis for the analysis. When the cap is binding, among all the coupled constraints Nash equilibria, we select a particular normalized equilibrium by solving a variational inequality. Comparing the normalized equilibrium with the Nash equilibria of the BAU and the ICT, we first show that if the cap is appropriately chosen, then the GEC system improves all players’ payoffs, relative to the BAU. The GEC system may thus be unanimously approved whereas the ICT is not, because moving from the BAU to the ICT is costly for one player. Second, for some values of the cap, all players get a higher payoff under the GEC than under the ICT. Therefore, the GEC outperforms the ICT both in terms of feasibility and efficiency.     

The Contribution of Mathematical Models to Climate Policy Design: a Researcher’s Perspective

Energy and the environment are closely interconnected. In particular, energy-related carbon dioxide emissions are major contributors to climate change. To analyze options within the energy sector to curb greenhouse gas emissions, or to study alternative climate strategies such as adaptation and geoengineering measures, policy-makers can rely on mathematical decision support models, in particular E3 (economy/energy/environment) models and integrated assessment models (IAMs). This paper reviews some of my recent contributions to climate policy design using different types of E3 models and IAMs.     

Associations between self-reported odour annoyance and volatile organic compounds in ‘Chemical Valley’, Sarnia, Ontario

Annoyance produced by air pollution has been suggested as a useful proxy for determining ambient air pollution exposure. However, most of the studies, to date, have focused on nitrogen dioxide and sulphur dioxide, with no work done on volatile organic compounds (VOC). This study is aimed at examining the associations between odour annoyance and VOC in ‘Chemical Valley’, Sarnia, Ontario, Canada. Annoyance scores were extracted from a community health survey (N?=?774), and exposures to VOC were estimated from respondents’ six-digit alphanumeric postal codes using land use regression models. Univariate analyses were used to explore the relationships between odour annoyance and modelled pollutants, whilst multivariate ordinal logistic regression was utilized to examine the determinants of odour annoyance. The results indicate that odour annoyance is significantly associated with modelled benzene, toluene, ethylbenzene, o-xylene and (m?+?p)?xylene (BTEX) pollutants. The findings also show that the determinants of odour annoyance in the context of VOC include gender, number of relatives in the community, perception of air pollution, community satisfaction, medical checkups, ability to cope with daily life demands and general symptoms. When compared, the analysis indicates that Sarnia residents respond to considerably lower BTEX concentrations than the allowable ‘safe’ levels in the province of Ontario. In general, the results exhibit a dose–response gradient with annoyance score increasing with rising modelled pollutant concentrations. The observed relationships suggest that odour annoyance might be a function of true exposure and may serve as a proxy for air quality and ambient air pollution monitoring. However, questionnaire-based odour annoyance scores need to be longitudinally validated across different geographical scales and pollutants if they are to be adopted at the national level.     

Geostatistical Analysis of data on AIR Temperature and Plant Phenology From Baden-Württemberg (GERMANY) as a Basis for Regional Scaled Models of Climate Change

The rise of the air temperature is assured to be part of the global climatic change, but there is still a lack of knowledge about its effects at a regional scale. The article tackles the correlation of air temperature with the phenology of selected plants by the example of Baden-Württemberg to provide a spatial valid data base for regional climate change models. To this end, the data on air temperature and plant phenology, gathered from measurement sites without congruent coverage, were correlated after performing geostatistical analysis and estimation. In addition, geostatistics are used to analyze and cartographically depict the spatial structure of the phenology of plants in spring and in summer. The statistical analysis reveals a significant relationship between the rising air temperature and the earlier beginning of phenological phases like blooming or fruit maturation: From 1991 to 1999 spring time, as indicated by plant phenology, has begun up to 15 days earlier than from 1961 to 1990. As shown by geostatistics, this holds true for the whole territory of Baden-Württemberg. The effects of the rise of air temperature should be investigated not only by monitoring biological individuals, as for example plants, but on an ecosystem level as well. In Germany, the environmental monitoring should be supplemented by the study of the effects of the climatic change in ecosystems. Because air temperature and humidity have a great influence on the temporal and spatial distribution of pathogen carriers (vectors) and pathogens, mapping of the environmental determinants of vector and pathogen distribution in space and time should be performed in order to identify hot spots for risk assessment and further detailed epidemiological studies.     

Measurement Research on the Influence of China’s Provincial Technological Innovation Capacity upon Green Economy Development

Environmental Modeling & Assessment - Based on the global entropy method to evaluate the technological innovation ability and the development level of green economy in Chinese provinces from...