Mental disorders have been associated with various aspects of anthropogenic change to the environment, but the relative effects of different drivers are uncertain. Here we estimate associations between multiple environmental factors (air quality, residential greenness, mean temperature, and temperature variability) and self-assessed mental health scores for over 20,000 Chinese residents. Mental health scores were surveyed in 2010 and 2014, allowing us to link changes in mental health to the changes in environmental variables. Increases in air pollution and temperature variability are associated with higher probabilities of declined mental health. Mental health is statistically unrelated to mean temperature in this study, and the effect of greenness on mental health depends on model settings, suggesting a need for further study. Our findings suggest that the environmental policies to reduce emissions of air pollution or greenhouse gases can improve mental health of the public in China.
CeO2-AgI, synthesized via depositing AgI nanoparticles onto CeO2 nanorods, was utilized for bacterial disinfection and organic contaminant degradation. Escherichia coli (E. coli) and Bisphenol A (BPA) were used as the model bacteria and emerging organic contaminant to test the photocatalytic activity of CeO2-AgI, respectively. Results showed that CeO2-AgI with the optimal AgI content exhibited superior photocatalytic activity over pure CeO2 or AgI for both inactivation of E. coli cells and BPA removal. However, the photocatalytic mechanisms for E. coli inactivation and BPA degradation were different. Specifically, the photo-generated holes (h+), photo-generated electrons (e−) and superoxide radicals (O2−) were the dominated active species for E. coli inactivation, whereas, BPA degradation relied on the generation of O2− and e−. Cell membrane disruption was found to be the main disinfection mechanism. The decomposition of BPA was clarified by detecting the degradation intermediates by LC–MS and DFT calculation. The facile synthesized CeO2-AgI exhibited good photocatalytic stability in four reused cycles and thus could be potentially applied to purify water.
While it has been acknowledged that exposure to endocrine-disrupting chemicals (EDCs) is associated with human diseases, the overall disease burden attributable to the exposure to a specific EDC has rarely been evaluated. Based on existing models for assessing probabilities of causation and a comprehensive review of available data, we analyzed the burden of three diseases, i.e., male infertility, adult obesity, and diabetes, among the general Chinese population resulting from exposure to phthalates. Our estimation indicates that exposure to phthalates is associated with ~2.50 million cases of the three diseases across China in 2010, causing ~57.2 billion Chinese Yuan (equivalent to ~9 billion US dollars) of health care costs in a year. Male infertility has the largest number of cases, followed by adult obesity and diabetes. Based on these phthalate-specific estimates, we further estimated that the total disease cost due to exposure to the overall EDCs amounted to ~429.43 billion Chinese Yuan in China in 2010, accounting for 1.07% of nationwide gross domestic product (GDP). When comparing our results with an earlier estimate for the European Union (EU) member countries, we find that exposure to phthalates leads to quite a similar disease burden per unit of GDP in both regions. Our study illustrates the considerable socio-economic impact of EDC exposure on human society, implying the imperative need for global risk reduction actions on EDCs, especially in view of the 2030 Sustainable Development Goals.
In this paper, a method for modeling distance dependent head-related transfer functions is presented. The HRTFs are first decomposed by spatial principal component analysis. Using deep neural networks, we model the spatial principal component weights of different distances. Then we realize the prediction of HRTFs in arbitrary spatial distances. The objective and subjective experiments are conducted to evaluate the proposed distance model and the distance variation function model, and the results have shown that the proposed model has less spectral distortions than distance variation function model, and the virtual sound generated by the proposed model has better performance in terms of distance localization.
Abstract Plant pathogens are increasingly considered as important agents in promoting plant coexistence, while plant symbionts like ectomycorrhizal fungi (EMF) can facilitate plant dominance by helping conspecific individuals to defend against plant pathogens. However, we know little about their relationships with plants at large scales. Here, using soil fungal data collected from 28 forest reserves across China, we explored the latitudinal diversity gradients of overall fungi and different fungal functional guilds, including putative plant pathogens, EMF and saprotrophic fungi. We further linked the spatial patterns of alpha diversities of putative plant pathogens and EMF to the variation of plant species richness. We found that the relationships between latitude and alpha diversities of putative plant pathogens and EMF were region-dependent with sharp diversity shifts around the mid-latitude (~ 35 oN), which differed from the unimodal diversity distributions of the overall and saprotrophic fungi. The variations in the diversities of putative plant pathogens and EMF were largely explained by the spatial regions (south Vs north / subtropical zone Vs temperate zone). Additionally, the alpha diversities of these two fungal guilds exhibited opposing trends across latitude. EMF could alter the relationship between diversities of putative plant pathogens and plants in the south/subtropical region, but not vice versa. We also found that the ratio of their alpha diversities (EMF to putative plant pathogens) was negatively related to plant species richness across the spatial regions (north to south), and explained ~10% of the variation of plant species richness. Overall, our findings suggest that plant-microbe interactions not only shape the local plant diversity but also may have non-negligible contributions to the large-scale patterns of plant diversity in forest ecosystems.