In the present study, which shall serve as a prototype, we selected three components and 22 Protein Tyrosine Kinase inhibitor variables under the components and applied equal weighting for aggregation as PF-02341066 nmr an exercise for this Chinese case study. Table 5 Calculated z-scores of variables under the resources component (2000 and 2005) Energy Water Waste/material Fuel oil/GRP Coal/GRP Industrial water/GRP Water supply/GRP Water availability/capita selleck chemicals Solid waste utilization 2000 2005
2000 2005 2000 2005 2000 2005 2000 2005 2000 2005 Beijing −0.90 −0.49 0.78 1.17 0.44 0.66 1.84 1.26 1.74 1.28 0.83 0.65 Tianjin −0.90 0.04 0.38 0.27 −0.29 −0.34 0.41 0.29 1.74 1.74 1.27 1.23 Hebei 0.04 0.04 −0.42 −0.47 −0.38 −0.63 0.16 0.90 1.28 1.28 −0.33 −0.38 Shanxi 0.04 1.32 −2.86 −2.79 −1.67 −1.59 −0.54 −0.32 0.82 1.01 −1.13 −0.41 Inner Mongolia 1.32 0.04 −1.14 −1.82 −1.35 −1.06
−0.21 0.09 −0.27 −0.20 −1.62 −1.11 Liaoning −2.07 −0.90 −0.35 −0.08 −0.41 −0.03 −1.14 −0.56 0.68 0.29 −0.74 −0.62 Jilin −0.90 0.04 −0.31 −0.22 −0.08 −0.35 −1.75 −1.62 0.10 −0.27 0.01 −0.05 Heilongjiang −0.90 0.04 −0.28 −0.08 −0.45 0.12 −0.65 0.65 −0.30 −0.20 0.52 0.71 Shanghai −1.24 −0.49 0.55 0.73 −0.46 0.15 FAD −0.53 −0.44 1.74 1.74 1.54 1.23 Jiangsu −0.49 −0.49 0.35 0.30 −0.01 0.39 −0.10 0.22 0.37 0.56 1.08 1.12 Zhejiang −0.49 −0.49 0.62 0.66 0.29 0.36 0.44 0.28 0.10 −0.27 0.91 1.02 Anhui 0.04 0.04 0.00 −0.02 −0.58 −0.37 −1.42 −1.25 −0.13 0.10 0.66 0.78 Fujian −0.49 0.04 1.15 0.80 1.13 0.86 0.18 0.73 −0.33 −0.70 −0.40 0.44 Jiangxi 0.04 0.04 0.16 0.07 0.33 0.07 −1.08 −0.99 −0.55 −0.61 −2.61 −1.56 Shandong −0.90 0.04 0.11 0.08 0.08 0.15 0.44 0.69 0.68 0.82 0.82 1.04 Henan 0.04 0.04 −0.30 −0.27 −0.56 −0.43 −0.06 0.42 0.45 0.56 0.39 0.42 Hubei 0.04 0.04 0.14 0.18 −0.02 0.22 −1.52 −0.79 −0.27 −0.09 0.39 0.61 Hunan 0.04 0.04 0.30 0.34 0.72 0.60 −1.64 −1.16 −0.44 −0.41 0.34 0.44 Guangdong −2.30 −1.82 1.10 1.12 0.67 0.88 0.34 −0.17 −0.17 −0.20 0.50 0.83 Guangxi 0.04 1.32 0.04 0.09 0.56 −0.06 −0.90 −0.54 −0.68 −0.64 0.06 0.20 Hainan 0.04 1.32 1.37 1.51 1.75 1.58 1.26 1.73 −0.63 −0.64 0.10 0.43 Chongqing 1.32 1.32 −0.10 0.38 −0.58 −0.34 0.48 0.51 −0.20 −0.17 0.58 0.57 Sichuan 1.32 1.32 0.02 0.23 0.53 0.44 −0.63 0.76 −0.51 −0.63 −0.43 0.