This paper selects 8 pieces of 2016 to 2020 policy samples to establish a PMC model, which is employed to construct an evaluation system of water-saving policies on 10 tier 1 variables and 45 tier 2 variables. Text extraction is used to select the key words in the policies, and inputs & outputs from water-saving evaluation system are given values. PMC indicators and curves are employed to discover the pros and cons of policies. Representative water-saving policies in “the 13^th  five-year plan” are evaluated to summarize water-saving experience, execution progress and issues aiming at providing references for further water-saving management, and at facing new water resource situation in China. 8 pieces of policies have an average PMC indicator at 7.3, generally at the level of excellence. Five indicators in single policy which are above 7 are at the level of excellence, and at the level of acceptance if three above 6, suggesting an overall appropriate water-saving policies design in China, but along with issues in insufficient policy effectiveness, lacks of stimulating approaches, limited water saving, single viewing angle, imbalanced tool usage, and inadequate regional features. This paper presents suggestions on planning China’s water-saving policies under multiple perspectives to increase policy quality, on increasing encouraging and constraining approaches, including governmental allowance, capital investment, technical supports, preferential taxation, welcoming more participants in saving water, adding on-demand policy tools, pushing water-saving industrial development and intensifying policy’s regional features. This summary presents reference for further water-saving work.

Industrial development relies on maintaining sustainable development, optimizing industrial structure and boosting industrial GTFP amid the current economic situation. This paper, according to industrial data in Jiangsu province, uses DEA model to measure their GTFP which is used to divide the industrial sector into 5 divisions, discusses the spatial overflow and its decomposition of industrial structure on GTFP from weights of adjacent space, geographic distance and economy distance. Jiangsu's GTFP is of highly spatial concentration, and of same orientation on inside and outside of region of each industrial department, with same symbols of direct and in-direct effects. Influences of controlling variables on GTFP vary. Industrial structure is of overflow effect among Jiangsu's regions, whose industrial structure still has highly energy-consuming, highly polluting, and highly emitting companies, impeding its economic transformation and upgrading to some extent, crucial to its successful kinetic transformation of industrial structure.