Health benefits from risk information of air pollution in China.

Risk-related information regarding air pollution can help people understand the risk involved and take preventive measures to reduce health loss. However, the health benefits through these protective behaviors and the health threat of information inequality have not been systematically measured. This article reports the health gains and losses caused by the interaction of "air pollution-air pollution information-human", and studies the heterogeneity and impact of this interaction. Based on field investigations and transfer learning algorism, this study compiled the first nationwide city-level risk-related information (ERI) response parameter set in China. Then, we developed a Information-Behavioral Equivalent PM2.5 Exposure Model (I-BEPEM) model to project the health benefits caused by the impact of environmental risk-related information on residents' protective behaviors under different scenarios. The protective behavior led by air pollution risk information reduces 5.7% PM2.5-related premature deaths per year. With a 1% increase in regional ERI reception, PM2.5-related premature mortality decreases by 0.1% on average; If the level of information perception and behavioral protection in all cities is the same as that in Beijing, PM2.5-related premature deaths will decrease by 6.9% annually in China. Further, changing the air quality standard issued by China to the American standard can reduce the overall PM2.5-related premature deaths by 9.9%. Meanwhile, compared with men, other age groups and rural residents, women, older persons, and urban residents are more likely to conceive risk information and adopt protective behaviors to reduce the risk of premature death from air pollution. Air pollution risk information can significantly reduce people's health loss. Changing the real-time air quality monitoring information indicator standard to a more stringent level can quickly and effectively enhance this effect. However, the uneven distribution of this information in regions and populations has resulted in the inequality of health gains and losses.

Pandemics erode poverty alleviation process: Impact on productive livelihood and poverty return.

Pandemics such as COVID-19 threaten income growth by disrupting productive activities for households, especially those who have just escaped from poverty. We provide empirical evidence on how pandemic disproportionately threatens the rural productive livelihood based on 48 months of household production electricity consumption data. The results show that after COVID-19, the productive livelihood activities of 51.11% households who have just overcome poverty have returned to the level before poverty alleviation. Their productive livelihood activities dropped by 21.81% on average during the national COVID-19 epidemic and by 40.57% during the regional epidemic. The households with lower income, lower level of education and less labor force even suffer more. We estimate 3.74% decline in income owing to the decrease in productive activities, resulting in 5.41% of households potentially falling back into poverty. This study provides an important reference for countries being at risk of returning to poverty after pandemic.

Does electricity price reduction bring a sustainable development of business: Evidence from fine-grained industrial electricity consumption data in China.

This paper studies the impact of electricity price reduction policy on the economic activities and carbon emissions of different industries. Since 2018, the Chinese government has advocated reducing electricity price for industrial customers in order to alleviate the non-tax burden on businesses. Using monthly electricity consumption and user data from 2016 to 2019, we find that the electricity price reduction has significantly increased the industrial electricity consumption and users. Heterogeneity analyses show that the effect is greater in heavy polluted industries and industries in low and medium GDP regions. The results of threshold impact analysis show that the threshold value of heavy pollution industries was lower than that of general industry and commerce, while heavy pollution industries are more sensitive to electricity prices than general industries. Moreover, the reduction of electricity prices results in a higher percentage of carbon emissions growth in heavy pollution industries. Our result can also help the policymakers access the costs and benefits of electricity price reduction for industrial customers more accurately.

The discrepancies in the impacts of COVID-19 lockdowns on electricity consumption in China: Is the short-term pain worth it?

The COVID-19 pandemic caused severe economic contraction and paralyzed industrial activity. Despite a growing body of literature on the impacts of COVID-19 mitigation measures, scant evidence currently exists on the impacts of lockdowns on the economic and industrial activities of developing countries. Our study provides an empirical assessment of lockdown measures using 298,354 data points on daily electricity consumption in 396 sub-industries. To infer causal relationships, we employ difference-in-differences models that compare cities with and without lockdown policies and provide quantitative evidence on whether the long-term gain of lockdowns outweighs the short-term loss. The results show that lockdown policies led to a significant short-term drop in electricity consumption of 15.2% relative to the control group. However, the electricity loss under the no-lockdown scenario is 2.6 times larger than that under the strict lockdown scenario within 4 months of the outbreak. Discrepancies in the impacts among industries are identified, and even within the same industry, lockdowns have heterogeneous effects. The impact of lockdowns on small and medium-sized enterprises in developing countries is seriously underestimated, raising concerns about the distributional impact of subsidy measures. This study serves as a crucial reference for the government when facing public health emergencies and shocks to support better policies.

Ultrasound-assisted probiotics fermentation suspension treatment under mild heat to improve the storage quality of freshly cut lotus root.

Ultrasound-assisted probiotic fermentation suspension treatment under mild heat was applied to freshly cut lotus root. Combined treatment significantly (p < 0.05) improved the bactericidal effect: S. aureus, E. coli O157:H7, A. flavus spores, and yeast were completely killed at 55℃ for 6 min, morphological and structural changes of cells were observed. Combined treatment inhibited enzymatic browning via decreasing the activities of PPO, POD, PAL, and decreasing TPC, soluble quinone content. The decrease of external resistance, capacitance and the increase of internal resistance reflected the loss of structural integrity of cells after combined treatment. For combined treatment samples, no obvious color change was observed during 12 days of storage but weight loss rate, total acid increased significantly (p < 0.05) and hardness decreased, the shelf life was extended to 12 d. Ultrasound-assisted probiotic fermentation suspension treatment under mild heat had the dual effects of sterilization and inhibition of browning.

The application of response surface methodology in studying the effect of heat and high hydrostatic pressure on anthocyanins, polyphenol oxidase, and peroxidase of mulberry (Morus nigra) juice.

BACKGROUND: Mulberry juice is an excellent source of phytochemicals with medicinal properties. The effects of four independent variables (temperature, heating time, pressure, and pressurising time) on three response variables [% anthocyanin retained, and % residual activities of the enzymes polyphenol oxidase (PPO), and peroxidase (POD)] of mulberry juice were studied using response surface methodology. Mathematical models and optimum levels of the response variables were generated. RESULTS: Temperature had the greatest effect on all the response variables. The synergistic effect of temperature and pressure had significant effect (P < 0.05) on anthocyanin retained and residual PPO activity. The prediction of the desirability model, based on 95% confidence in the range of the independent variables, gave optimal treatment conditions of 83.39°C, 2.38 min, 480.00 MPa, and 21.67 min, respectively for temperature, heating time, pressure, and pressurising time. At these levels, the corresponding response variables were 91.68%, 44.69% and 20.17% for the amounts of anthocyanin retained, and residual activities of PPO and POD, respectively. The desirability index obtained was 0.741. CONCLUSION: The results were desirable and the mathematical models developed could be used to predict the outcome of the response variables to a high degree of accuracy.