Empirical Study Of Sensitivity Model In China's Sustainable Development Related To Global Climate Change

This paper analyzes the change of empirical effect of global climate changes using 27 anthropogenic, economic and natural variables from industrial, transportation, natural sectors in China over the period 1970–2007. The present empirical study reveals that the listed variables cannot be evaluated unambiguously using either variation in carbon emission factor or product of many factors put together as the criteria. This is because the different levels of CO2 emission intensities in different regions resulting from different causes is not a constant or evaluated using constant variables. These include large variations in explanatory and interrelated factors linked in the data, the measure of economic development, and structural comparability.The study employs logical, scientific understanding and prediction of a Sensitivity Model (SM) which is an integer tool in the assessment of climate change for China. It simulated a smooth environmental sustainable transition for the next 10 years, given the 11 partial simulated variables. The positive coefficient for GDP growth variable suggests that estimated emissions initially rise with GDP growth, and eventually fall, the impact of population on emissions has been more pronounced in lower than in higher income ranges contradicting Environmental Kuznet Curve (EKC). The other appealing finding is the differentiating effects of energy efficiency on emissions in China of various affluence levels. The role of energy efficiency on emissions has been the greatest when the total amount of CO2 emission is at it peak. To test the hypothesis that population pressure has exhibited different impacts on emissions across China with different levels of affluence. This model is hierarchical to the baseline model, and these models are nested. The model fits the data well, which is indicated by a further significant reduction of Akaike Information Criterion (AIC) statistics as compared with that of baseline model (-852 verse -826), relative to the change of one degree of freedom ((n-1) which +26.0 percent). The negative coefficient for the interaction term suggests that the marginal effect of population on emissions diminishes as income level stabilises.The goal of SM is to help the governments make informed decisions and take appropriate action. For those municipalities that are already developing adaptation measures, this research will help enhance an understanding of climate change adaptation among several listed variables and it implication to future climate change not only to China but to the World at large. The SM provided a suitable approach for modeling interlocking repercussions of climatic change and sustainability. In contrast to alternative approaches, it offers a special advantage: its cybernetic methodology takes account of the holistic character of systemic structures and means non-quantifiable factors (risk perception, the quality of the natural landscape) can be modeled.