Real-time monitoring and accurate prediction of toxic gas concentration in the future are of great significance for emergency capability assessment and rescue work. At present, the method of gas concentration prediction based on artificial intelligence still has problems of low accuracy, slow convergence speed and equal feature importance. This paper proposes a feature-aware LSTM model to predict pollutant gas concentration. First of all, we design a set of multi-component toxic gas monitoring equipment that applies in pollution environment, which can at the same time monitor CO, NO2, NH3, HCN, H2S and SO2, six common pollutants; To accurate estimate the toxic gas concentration, we combine the collected the gas data and the environmental parameters and regard them as the input features, and then we obtain toxic gas data based on the sampling policy and the environmental data as our data-set. Finally, we train a FA-LSTM gas concentration prediction model on these data-set. We test the proposed model and compared with ARIMA, ETS and BP network on the same test set. Experimental results show that the proposed model outperforms traditional concentration prediction model. Also, it is better than other stateof-the-art models in predicting accuracy.INDEX TERMS pollution emergency decision, toxic gas, air pollution prediction, time series, LSTM.

With the rapid advance of industrialization and urbanization and the intensified impact of global climate change, the contradiction between the global water shortage and economic growth has become prominent. This paper, taking Henan province as an example, analyzed the influence of water resource policy on regional economic growth through a calculable general equilibrium model and further discussed the relevant policy recommendations. The results showed that the improvement of water supply, water efficiency and water technology could promote the growth of the regional economy and result in a positive effect on regional GDP, employment and resident income. However, the rise of water price has a negative impact on regional economic development, mainly reflected in regional GDP, employment and household income. The improvement of water price, water efficiency and water conservancy technology would lead to a decrease in regional water consumption, while only the increase of the water supply would lead to an increase in water consumption. Accordingly, the paper put forward policy suggestions, such as accelerating the improvement of water conservancy facilities, establishing a reasonable water price mechanism and actively exploring experience in water conservation and emission reduction.