# Measuring the Performance of Wastewater Treatment in China
## 3 Empirical Analysis and Results
### Analysis of Outputs Efficiency Results from Year 2011 to 2015  
Observing Table 4, we see the wastewater efficiencies of 31 regions did not exhibit a big difference through the years 2011 to 2015. As we know, the wastewater discharged amounts increased only little. We can see overall water quality continuously improved. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**2011**} & \multicolumn{2}{c}{**2012**} & \multicolumn{2}{c}{**2013**} & \multicolumn{2}{c}{**2014**} & \multicolumn{2}{c}{**2015**} \\ \hline
**DMU** & **Was Eff \({}^{*}\)** & **COD** & **Was** & **COD** & **Was** & **COD** & **Was** & **COD** & **Was** & **COD** \\  & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** & **Eff \({}^{*}\)** \\ \hline Beijing & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Tianjin & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Inn-M \({}^{*}\) & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Shan \({}^{*}\) & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Jiangsu & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Zhejiang \({}^{*}\) & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Shandong & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Guang \({}^{*}\) & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\ Tibet & 1 & 1 & 1 & 1 & 0.991 & 0.991 & 1 & 1 & 1 & 1 \\ Hainan & 1 & 1 & 1 & 1 & 0.959 & 0.957 & 0.990 & 0.986 & 0.977 & 0.972 \\ NingGa & 1 & 1 & 0.955 & 0.955 & 0.901 & 0.900 & 0.936 & 0.936 & 0.935 & 0.933 \\ Henan & 0.993 & 0.993 & 0.945 & 0.943 & 0.896 & 0.882 & 0.881 & 0.930 & 0.929 \\ Xinjiang & 0.951 & 0.960 & 0.899 & 0.897 & 0.859 & 0.859 & 0.871 & 0.869 & 0.924 & 0.924 \\ Liaoning & 0.931 & 0.930 & 0.885 & 0.885 & 0.858 & 0.857 & 0.834 & 0.833 & 0.916 & 0.916 \\ Hebei & 0.895 & 0.895 & 0.868 & 0.867 & 0.837 & 0.834 & 0.832 & 0.831 & 0.896 & 0.896 \\ Shanni & 0.870 & 0.868 & 0.849 & 0.848 & 0.825 & 0.823 & 0.831 & 0.830 & 0.853 & 0.851 \\ Shanxi & 0.856 & 0.854 & 0.816 & 0.815 & 0.812 & 0.811 & 0.816 & 0.812 & 0.840 & 0.837 \\ Sichuan & 0.840 & 0.839 & 0.813 & 0.811 & 0.805 & 0.802 & 0.814 & 0.813 & 0.835 & 0.834 \\ Hunan & 0.820 & 0.818 & 0.811 & 0.809 & 0.793 & 0.796 & 0.814 & 0.812 & 0.827 & 0.824 \\ Heilion \({}^{*}\) & 0.817 & 0.813 & 0.811 & 0.808 & 0.774 & 0.783 & 0.795 & 0.799 & 0.821 & 0.819 \\ Jilin & 0.811 & 0.808 & 0.785 & 0.783 & 0.778 & 0.774 & 0.799 & 0.795 & 0.817 & 0.814 \\ Hubieu & 0.804 & 0.803 & 0.777 & 0.774 & 0.753 & 0.750 & 0.780 & 0.778 & 0.793 & 0.789 \\ Guizhou & 0.803 & 0.802 & 0.770 & 0.767 & 0.747 & 0.746 & 0.766 & 0.763 & 0.784 & 0.780 \\ Qinghai & 0.790 & 0.790 & 0.763 & 0.762 & 0.743 & 0.741 & 0.745 & 0.742 & 0.732 & 0.729 \\ Gansu & 0.776 & 0.774 & 0.760 & 0.758 & 0.742 & 0.740 & 0.724 & 0.723 & 0.728 & 0.725 \\ Fujian & 0.764 & 0.763 & 0.732 & 0.729 & 0.722 & 0.720 & 0.714 & 0.711 & 0.722 & 0.719 \\ Chong \({}^{*}\) & 0.749 & 0.748 & 0.722 & 0.720 & 0.715 & 0.714 & 0.709 & 0.707 & 0.716 & 0.714 \\ Anhui & 0.718 & 0.717 & 0.713 & 0.713 & 0.709 & 0.706 & 0.693 & 0.691 & 0.700 & 0.698 \\ Yunnan & 0.690 & 0.688 & 0.676 & 0.673 & 0.682 & 0.680 & 0.690 & 0.688 & 0.688 & 0.686 \\ Jiangxi & 0.676 & 0.674 & 0.657 & 0.655 & 0.662 & 0.660 & 0.690 & 0.688 & 0.670 & 0.668 \\ Guangxi & 0.655 & 0.653 & 0.615 & 0.613 & 0.657 & 0.655 & 0.661 & 0.659 & 0.661 & 0.659 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Efficiency results of outputs from 2011 to 2015.