History and future of water footprint in the Yangtze River Delta of China.

Quantifying the drivers of water footprint evolution in the Yangtze River Delta is vital for the optimization of China's total water consumption. The article aims to decompose and predict the water footprint of the Yangtze River Delta and provide policy recommendations for optimizing water use in the Yangtze River Delta. The paper applies the LMDI method to decompose the water footprint of the Yangtze River Delta and its provinces into five major drivers: water footprint structure, water use intensity, R&D scale, R&D efficiency, and population size. Furthermore, this paper combines scenario analysis and Monte Carlo simulation methods to predict the potential evolution trends of water footprint under the basic, general, and enhanced water conservation scenario, respectively. The results show that (1) the expansion of R&D scale is the main factor promoting the growth of water footprint, the improvement of R&D efficiency, and the reduction of water intensity are the main factors inhibiting the increase of water footprint, and the water footprint structure and population size have less influence on water footprint. (2) The evolution trend of water footprint of each province under three scenarios is different. Compared to the basic scenario, the water footprint decreases more in Shanghai, Zhejiang, and Anhui under the general and enhanced water conservation scenario. The increase in water footprint in Jiangsu under the enhanced scenario is smaller than that of the general water conservation scenario.

Characteristics and health risk assessment of heavy metals in dust of a waste printed circuit board recycling workshop, China.

Physical separation is the most widely used technology concerning waste printed circuit board (WPCB) recycling in practical terms. The dust generated from the process poses a significant environmental and human health risk. Amounts of heavy metals in dust present in each processing zone of the workshop showed differences. However, to date, few studies have reported this. The mean metal concentrations in workshop dust from different processing zones were investigated in this study and it was found that Zn, Pb, and Sn appeared in higher levels than other metals, followed by Mn > Cr > Ni > V > As > Cd. The enrichment factors (EFs) ranged from 1.15 to 207.4, and decreased in the order of Cu > Sn > Pb > Zn > Cd > Cr > Ni > V > As, which was exactly consistent with the geo-accumulation index values. The comparison of the EF values of workshop dust in and outside showed that the EFs in workshop dust were mostly smaller. Metals in the dust of the crushing zone (CrZ) showed significant and strong enrichment. The non-carcinogenic risk for different processing zones was all less than 1, which is recognized safety for people's health. The total carcinogenic risk from Cr, and Ni in all zones and As in the CrZ exposure was not negligible. The carcinogenic and non-carcinogenic risks in the CrZ were significantly higher than in the other zones. Masks to filter dust, a ventilation system, daily work hours reduction, and automation improvement was proposed for reducing workers' exposure to heavy metal.

Carbon emission of China's power industry: driving factors and emission reduction path.

The low-carbon development of power industry is the key to low-carbon development of the whole society. In order to determine appropriate and feasible emission reduction policies, it is necessary to identify the contribution of different drivers to the change of carbon emissions in China's power sector and to simulate the potential evolution trend of carbon emissions. This paper constructs LMDI model to analyze the driving factors of carbon emission changes in China's power industry from 2000 to 2018 and uses Monte Carlo algorithm to simulate the evolution trend of carbon emission under different scenarios. We can find (1) economic output effect reached 3.817 billion tons from 2000 to 2018, which was the primary factor to increase the carbon emission. Population scale effect reached 251million tons, which had a weak promotion impact on carbon emission. (2) Conversion efficiency effect played a role in restraining carbon emissions, reaching 699 million tons from 2000 to 2018. (3) Emission factor effect and power intensity effect have obvious volatility. The power structure effect showed great volatility before 2013 and mainly played a role in restraining carbon emission after 2013. (4) Under the baseline scenario, the carbon emission of China's power industry shows a growth trend. Under green development scenario and enhanced carbon reduction scenario, the carbon emission shows a trend of first increasing and then decreasing.