Greenhouse Gas Emissions, Response And Vulnerability To Climate Change In The Yangtze River Basin

The Yangtze River Basin (YRB) was one of the main regional economic integration in China.The industrialization and urbanization process of YRB developing relatively fast. However the YRB was very sensitive response to various disasters. The risk relate to the global climate change was increasing notable. The meteorological disasters, for example, drought, floods, frost et al, had made the direct economic loss raised steadily. Climate change includes not only short-term severe impact; also include long-term slow accumulation properties change effects, such as change of water resources, ecosystem succession fundamental problem. So YRB in the future will face a more serious risk. How to deal with the risk of climate change and reduce the vulnerability of the YRB were key issues for policy makers and stakeholders.In this paper, we studied the list of greenhouse gas emissions (GHGE) of the YRB, and analysed the correlation between the economic developments with GHGE. Then we applied the SCIAMACHY and TES satellite remote sensing (RS) data to get the GHG temporal and spatial distribution in YRB. So we could joint the GHGE with atmospheric radiation forced change through the RS data as intermediary. Next we analyzed the influence of YRB GHGE to regional climate change. And we constructed the climate change scenarios in future. Finally, the vulnerable to climate change of YRB had been analyzed based on above results. The main research contents and results including the following aspects(1) This paper, we applied the IPCC method and the characteristic coefficient what got from the national GHG inventory guide. Accounted three main GHG (CO2, CE4 and N2O) emissions from Energy, Industry, Agriculture, Waste treatment and Forestry sectors. The result shows that:? The GHGE inventory had been analyzed and result show that from 1990 to 2012, the total greenhouse gas emissions from 1.518 billion tonnes of CO2-eq growth to 4.414 billion tonnes of CO2-eq (CO2 equivalent), average annual growth rate of about 4.9%. Forestry carbon sink absorption CO2 increased from 111 million tons to 184 million tons, annual average growth rate of about 11.6%; Average emission values for many years, according to the three kinds of proportion of CO2 accounted for about 75.4% of greenhouse gases, CH4-eq accounted for about 10.2%, N2O-eq accounted for about 14.4%; Energy ccount for 40% of the ratio; Industrial 15.2%; Agriculture 26.6% (animal husbandry accounted for 17.7%) Waste 0.7%; According to 17% in jiangsu, hubei 13%,12% in anhui, hunan,12%, 10% in guizhou, Shanghai,8%,7% of jiangxi province; According to upstream watershed points (31%), middle reaches 25%, the downstream accounted for 44%.We studied the GHGE of three gorges reservoir. And we estimate there are 4.7125 million tons of CO2- eq emissions from the reservoir area annually. And we applied the RS data (TES) analyzed the temporal and spatial variation of CH4 concentration the region. We discovered the CH4 concentration changed was very small compared before and after the reservoir builted. So we think the reservoir has limited influence on CH4 concentration in the area.(2) We analyzed the time series of GHGE of provinces and the results show that the annual growth rate of greenhouse gas emissions in jiangsu province (32.8%), and Sichuan and Chongqing area (22.5%), hubei province(16.5%), anhui province (16%), hunan province(14.6%), guizhou province (11.7%), jiangxi province (9.2%) and Shanghai (5.2%); Greenhouse gas emissions intensity of annual growth rate Shanghai(-11.5%), Sichuan and Chongqing area (-11.1%), hunan (-10.9%), jiangxi (10.4%), guizhou (-10.3%), anhui (-9.7%), hubei province(-9.7%) and jiangsu province (-9.2%); Annual rate of growth of per capita emissions (6.7%), followed by jiangsu, anhui province (4.8%), hubei(4.4%),jiangxi (3.9%), guizhou (3.9%), hunan (3.8%), Sichuan and Chongqing area(3.6%) and Shanghai (0.2%). Shanghai has thow the EKC curve trend and the rest are in rising stage.?The decoupling analysis of GHGE and economic development show Shanghai occured weak decoupling relationship. In last five years. Shanghai show strong drama decoupling relationship in three. The first industry, in the last 10 years, Jiangsu and Chuanyu were show strong decoupling relationship for seven years. The second industry, Shanghai showed strong decoupling relationship since 1996. The gravity position transfer trajectory analysis shows that economic development is the main driving force of the GHG. The spatial autocorrelation test analysis show characteristics of GHG, due to the regional economic development imbalance in the space, strong differences in the space. Local Moran's I index value showed Shanghai has negative correlation with surrounding areas in space of research district. The above results showed that the change of GHGE on the whole and the relationship between economic developments was closely, both positive correlations. On the other hand, the Shanghai was found has different change trend with other provinces and cities. The main reason was the economic structure of Shanghai different with others.(2) Based on 3S technology, the spatial distribution pattern of CO2, CH4 and N2O in the YRB were studied by using SCIAMACHY and TES satellite RS data. The the concentrations spatial distribution of three kinds of GHG showed that CO2 and N2O higher in eastern and low in western, while CH4 showed the opposite distribution, there is a high value region in western. The concentrations of three kinds of GHG were growing in the YRB area, from 2005 to 2010. We compared the RS data with the global ground observation network data contrast (WMO) and think them growth rate were match the observed value. The CO2 contributed about 90% added value of radiative forcing increased. And the spatial distribution of the radiative forcing increases gradually from upstream to downstream. The average air temperature increased about 0.69 ?? form 1990 to 2010.(3) MAGICC/SCENGEN model was used to study the change characteristics of mean air temperature and precipitation in the YRB. The results show that the air temperature and the precipitation were increased in studied period. However, the air temperature and precipitation were significant increasing in winter. The precipitation in the middle and lower YRB reaches was increasing and decreasing in the upper reaches. Especially in the YRB Delta region precipitation increased than other region. Precipitation has two opposite change centers, the upper reaches of the Yangtze River in Sichuan basin in the eastern part of the precipitation reduction center, the middle reaches of the Yangtze River in Jiangxi as the center of the center of precipitation increase.(4) The VRIP model (Vulnerability-Resilience Indicator Prototype model), DEA model (data envelopment analysis model) and Spatial Panel Data model were used to analyze the vulnerability of climate change in the study area. We applied the system dynamics theory to simulate the trend of economic development and vulnerability to climate change in YRB. The result showed that the vulnerability continuously reduced due to the increase of the adaptability. The Jiangsu has the highest climate change exposure; the Hunan has the highest sensitivity and the Shanghai has the highest adaptability. The Jiangsu has the most relative vulnerability than others. The Shanghai has the lowest relative vulnerability. The vulnerability variables spatial autocorrelation analyzed showed that some variables have effect of spatial autocorrelation. The system dynamics analysis showed that:under the condition of no significant increase in exposure pressure, the climate change vulnerability of all regions showed a downward trend. Also found in the study area of the frailty distribution can be divided into district (Shanghai) increase, short and stable region (Jiangsu, Anhui, Jiangxi and Sichuan Chongqing region) and continuous improvement (Hubei, Hunan and Guizhou Province). In addition, the study also found that 2030 is a key period of climate change in the study area, if it can achieve the peak of GHGE at that time period, will be conducive to improving the region's vulnerability to climate change.