China is exploring a high-quality approach to development, which much be based on a sustainable development of resource environment and economy, so it is key to improve ecological environment, to adjust industrial structure and to increase resource allocation efficiency. This paper uses provincial panel data 2001—2016 to analyze the interaction and operating mechanism of environmental regulations, industrial transfer and resource allocation via media effect model based on measurement environmental regulations and resource allocation efficiency. Environmental regulation promotes industrial transfer with a weak upside-down U shape, and improves resource allocation over regions. Industrial transfer acts as media variable, environmental regulations push industrial transfer, which indirectly improves resource allocation efficiency. Governments shall make effective environment regulation to lead industrial transfer over areas so as to decrease wrongly-allocated resources.

 The coastal area in Jiangsu province is the major crop producer, where ensure the guarantee of Jiangsu's crop supply. This paper, based on farmland-crop-population compound system, uses farmland pressure index model to estimate the population carrying capacity model, and to evaluate the actual population carrying capacity. The population carrying capacity in three coastal cities in Jiangsu in 2025 is predicted under the condition that the 2nd Child policy is open to all, which is used to plan a rational urban population size. During 1998—2014, farmland decreased in area, but population rose continuously, leading a largely falling in farmland area per capita; however, the total crop production was a little rising. The overall population carrying capacity pressure is small in Jiangsu's coastal area, Nantong sits on top, followed by Lianyungang and then by Yancheng. It is predicted that in 2025 the appropriate population is 6.4 million in Nantong, 9.78 million in Lianyungang and 17.56 million in Yancheng, maximum up to 8.00 million, 12.23 million and 21.95 million, respectively.