We reviewed recent studies about detection and attribution of climate change in the globe and China, with focus on the detection and attribution of temperature, precipitation and major extreme events changes since 1950s. The detection and attribution of historical climate change at a longer time scale are not considered in the paper. The investigation shows that there are very quick advance in the international field of detection and attribution. Many studies cover the field from the detection and attribution of temperature at global scale to regional scale, and from temperature to multi-variables. However, in China, the relevant study is still at an initial stage. Although some studies explore the physical reasons behind the dry North China and wet South China since 1970s, the detection and attribution studies based on statistical inference methods are still very little and need to be strengthened. Many important issues, such as the reasons for regional climate change, the contribution from various factors and their difference with those at global scale, are needed to answer.

Based on monthly precipitation and temperature dataset (1986-2005) of 142 stations in the Yangtze River basin, the capability of the COSMO model in Climate Mode (CCLM) to reproduce the spatial and temporal variability of the observed precipitation and temperature was examined. The bias between simulation and observation was corrected by the equidistant cumulative distribution functions (EDCDF). The analysis shows that the spatial changes of simulated annual precipitation and mean temperature are broadly comparable with the observations. CCLM tends to overestimate temperature at both seasonal and annual time scales. CCLM fails to simulate the monsoon precipitation, thereby to underestimate precipitation in summer and autumn, and overestimate it in winter and spring. On the whole, temperature is better simulated than precipitation. Based on the bias-corrected projection, annual mean temperature over the whole basin will increase 0.66℃, while annual precipitation will reduce 2.2% in 2016-2035 under the RCP4.5 scenario, relative to the observations of 1986-2005.

Tree-ring width of Picea schrenkiana sampled at Jinchuan and its response to climate change were analyzed. Correlation analysis indicates that the tree-ring chronology and the June mean air temperature at Jinchuan station in the West Sichuan Plateau was significantly correlated. The June mean air temperature series of 1713-2010 at Jinchuan was well reconstructed. Its reliability was substantiated by the leave-one-out method. According to the reconstructed temperature series, the June mean air temperature over the period was 18.2℃. The reconstructed series contained three warm periods: 1825-1839, 1854-1892 and 1951-1961, as well as four cold periods: 1792-1804, 1842-1853, 1864-1893 and 1911-1924. Power spectrum analysis and wavelet analysis show that the series had variation periods of 2-3, 7-8, 20-30, 32-64 and 70-130 years.

The NCEP-1, ERA-40, and 20CR reanalysis precipitation data were evaluated by comparing their means, interannual variations, linear trends, and correlations with the observations in China. The results indicate that on the average, the ERA-40 data agreed better with the observations than the other two reanalysis datasets although it underestimated precipitation slightly. Both the NCEP-1 and 20CR data overestimated precipitation obviously, the percentage deviations of annual precipitation of the ERA-40, 20CR, and NCEP-1 from the observations over China were -1.3%, 55.0% and 36.9%, respectively. The maximum precipitation deviation usually occurred in Southwest China, with a value more than 600 mm. Percentage deviations of annual precipitation of the ERA-40 and NCEP-1 showed some fluctuations since the mid-1970s while the 20CR’s showed stability over the whole period. Basically, all three datasets well described the interannual variation of annual precipitation over China, but their correlations with the observations were usually better in the eastern China than in the western China. Of them the ERA-40 exhibited a better correlation in most of China than the other two datasets, and the ERA-40 and 20CR described trends of annual precipitation in most of China better than the NCEP-1.

The paper reviews the CO₂ emissions data provided by various international organizations and databases (namely IEA, BP, EDGAR/PBL/JRC, CDIAC, EIA and CAIT), and compares them with China’s official data and estimation. The differences among these data are due to different scope, method and basic data, particularly the differences in fossil fuel consumption are highlighted. Compared with data from other databases, the IEA and CAIT data have the best comparability with China’s official data. The paper recommends that China should enhance its coal statistics, increase the frequency of official data publication and improve the inventory completeness.

Based on the MAP-CGE model, this paper simulates the impacts on the output, energy consumption and pollutant emission of different cement production processes when implementing the low carbon cement standard in China, calculates the impacts on the marginal abatement cost and equilibrium price of cement industry, and analyzes the co-abatement effects of different pollutants. The results show that implementing the low carbon cement standard will be beneficial to promoting the upgrading of cement production process, and strengthening the energy conservation and emission reduction in the cement industry. When reducing every ton of CO₂ emission, if the existing technology keeps unchanged, the cement industry will reduce SO₂ emission by 1.17 kg and NO_x emission by 4.44 kg at the same time. Implementing low carbon cement standard can also promote NO_x abatement in the cement industry. However, the cement industry will bear the abatement costs, and their equilibrium price will increase to a small extent.

Based on fuel-cycle method, this paper tries to conduct a quantitative analysis on the energy and environmental performances of battery electric vehicle (BEV) in China. Four critical indicators, energy consumption, CO₂, NO_x and SO₂ emission, are selected for the comparison of the performances of BEV, internal combustive engineering vehicle (ICEV) and hybrid electric vehicle (HEV) in 2010 and 2020. The findings show that in 2010, the diffusion of BEV could reduce energy consumption and CO₂ emission, but BEV’s fuel-cycle NO_x and SO₂ emissions are higher than fuel-engined vehicles’ (both ICEV and HEV) by 50% at least. In 2020, if the targets in government planning are reached, BEV’s fuel-cycle energy consumption and CO₂ emission could be reduced by around 30% and its NO_x and SO₂ emissions could be reduced by around 80% compared with its counterpart in 2010. However, BEV’s fuel-cycle CO₂, NO_x and SO₂ emissions are still higher than HEV’s as a result of several reasons. In the end, policy recommendations for how to improve BEV’s energy and environmental performances are proposed, such as integrating the deployment of BEV into the progress of desulfurization and denitrification in electricity system, the management policy for automobiles should be based on vehicles’ energy efficiency, and so on.