Abstract Semivolatile organic compounds (SVOCs) emitted from building materials, consumer products, and occupant activities alter the composition of air in residences where people spend most of their time. Exposures to specific SVOCs potentially pose risks to human health. However, little is known about the chemical complexity, total burden, and dynamic behavior of SVOCs in residential environments. Furthermore, little is known about the influence of human occupancy on the emissions and fates of SVOCs in residential air. Here, we present the first-ever hourly measurements of airborne SVOCs in a residence during normal occupancy. We employ state-of-the-art semivolatile thermal-desorption aerosol gas chromatography (SV-TAG). Indoor air is shown consistently to contain much higher levels of SVOCs than outdoors, in terms of both abundance and chemical complexity. Time-series data are characterized by temperature-dependent elevated background levels for a broad suite of chemicals, underlining the importance of continuous emissions from static indoor sources. Substantial increases in SVOC concentrations were associated with episodic occupant activities, especially cooking and cleaning. The number of occupants within the residence showed little influence on the total airborne SVOC concentration. Enhanced ventilation was effective in reducing SVOCs in indoor air, but only temporarily; SVOCs recovered to previous levels within hours.
The traditional multiple audio objects codec extracts the parameters of each object in the frequency domain and produces serious confusion because of high coincidence degree in subband among objects. This paper uses sparse domain instead of frequency domain and reconstruct audio object using the binary mask from the down-mixed signal based on the sparsity of each audio object. In order to overcome high coincidence degree of subband among different audio objects, the sparse autoencoder neural network is established. On this basis, a multiple audio objects codec system is built up. To evaluate this proposed system, the objective and subjective evaluation are carried on and the results show that the proposed system has the better performance than SAOC.
Coke production is a significant source of ambient volatile organic compound emissions; thus, stringent control measures must be applied. We fully characterized the trends in volatile organic compound emissions by the coking industry in China between 1949 and 2016 based on a factory-based database and process-specific emission factors. We then projected the reduction potentials in these emissions if different control policies were implemented in 2020 based on three emission scenarios. The results indicate that: (1) the emission factor of volatile organic compounds for coke plants under uncontrolled conditions was 3.065 g/kg coke, and benzene, toluene, and acetone were the most abundant emission species. (2) The annual volatile organic compound emissions from the coking industry increased by an order of magnitude from 3.38 Gg in 1949 to 1376.54 Gg in 2016. The emissions show distinct spatial characteristics, with significantly higher emissions in northern China than in other areas. (3) Compared to the uncontrolled scenario, if basic or more stringent control measures were fully implemented in China in 2020, then volatile organic compound emissions would be reduced by 59% or 82%, respectively. (4) Controlling coke oven flue gases through efficient combustion, sealing and cleaning the openings of coke ovens, and using gas blanketing or carbon absorbers in by-product facilities were the most effective technologies for controlling volatile organic compound emissions from coke production.
Ambient exposure to fine particulate matter (PM2.5) is known to harm public health in China. Satellite remote sensing measurements of aerosol optical depth (AOD) were statistically associated with in-situ observations after 2013 to predict PM2.5 concentrations nationwide, while the lack of surface monitoring data before 2013 have created difficulties in historical PM2.5 exposure estimates. Hindcast approaches using statistical models or chemical transport models (CTMs) were developed to overcome this limitation, while those approaches still suffer from incomplete daily coverage due to missing AOD data or limited accuracy due to uncertainties of CTMs. Here we developed a new machine learning (ML) model with high-dimensional expansion (HD-expansion) of numerous predictors (including AOD and other satellite covariates, meteorological variables and CTM simulations). Through comprehensive characterization of the nonlinear effects of, and interactions among different predictors, the HD-expansion parameterized the association between PM2.5 and AOD as a nonlinear function of space and time covariates (e.g., planetary boundary layer height and relative humidity). In this way, the PM2.5-AOD association can vary spatiotemporally. We trained the model with data from 2013 to 2016 and evaluated its performance using annually-iterated cross-validation, which iteratively held out the in-situ observations for a whole calendar year (as testing data) to examine the predictions from a model trained by the rest of the observations. Our estimates were found to be in good agreement with in-situ observations, with correlation coefficients (R2) of 0.61, 0.68, and 0.75 for daily, monthly and annual averages, respectively. To interpolate the missing predictions due to incomplete AOD data, we incorporated a generalized additive model into the ML model. The two-stage estimates of PM2.5 sacrificed the prediction accuracy on a daily timescale (R2 = 0.55), but achieved complete spatiotemporal coverage and improved the accuracy of monthly (R2 = 0.71) and annual (R2 = 0.77) averages. The model was then used to predict daily PM2.5 concentrations during 2000–2016 across China and estimate long-term trends in PM2.5 for the period. We found that population-weighted concentrations of PM2.5 significantly increased, by 2.10 (95% confidence interval (CI): 1.74, 2.46) μg/m3/year during 2000–2007, and rapidly decreased by 4.51 (3.12, 5.90) μg/m3/year during 2013–2016. In this study, we produced AOD-based estimates of historical PM2.5 with complete spatiotemporal coverage, which were evidenced as accurate, particularly in middle and long term. The products could support large-scale epidemiological studies and risk assessments of ambient PM2.5 in China and can be accessed via the website (http://www.meicmodel.org/dataset-phd.html).
Innovation contributes to the long-term economic growth. From the perspective of externality by innovation, this paper disentangles the spillover effect based on the regions’ abundance of innovation resource and separately identifies the “leader effect” and “peer effect” of innovation spillover and discusses their economic consequences. Empirical results demonstrate a negative spillover effect from innovation leaders on the economic growth and a positive spillover effect from innovation peers. Robustness checks also support main findings. This study has implication both in the endogenous economic growth theory and industry innovation practice.
In this paper, we present a scalable and general fabrication for micro-supercapacitors (MSCs) among various flexible substrates assisted by the stamp, which combines the conductive polymer composites with gravure printing process. Compared with the traditional transferring techniques, this method greatly simplifies the process and mitigates the mechanical damage during the preparation. Profiting from the composites of carbon nanotubes (CNTs) and polydimethylsiloxane (PDMS) as the printing inks, the MSCs exhibit elegant areal capacitance (10.491 μF/cm2) on the paper substrate. Meanwhile, optimizing the ratio of matrix and curing agent of PDMS, the interaction between ink and substrate is effectively enhanced. Therefore, such novel fabrication technology significantly improves the production efficiency as well as broadens the applications.
Understanding and controlling confined CO2 fluids in nanopores is at the heart of the CO2 enhanced oil recovery in shale reservoirs. Here, for the first time, qualitative and quantitative static and dynamic behavior of complex confined CO2 fluids in dual-scale nanopores are experimentally performed in nanofluidics, which combines with the theoretical model, the statistical mechanics coupled with the thermodynamic equation of state, to investigate the CO2 utilization in shale reservoirs. In experiment, a series of phase behavior and fluid flow laboratory tests are conducted through a self-manufactured nanofluidic system at different conditions; in theory, a generalized equation of state including the confinements and pore-size distributions and five dynamic models are developed and applied to calculate the vapor–liquid equilibrium and fluid dynamics. Results from this study show that the static behavior has drastic changes in the dual-scale nanopores that the measured saturation pressure of the confined CO2–C10 fluids reduces by 10.19% at T = 25.0 °C and 7.26% at T = 53.0 °C from bulk phase to nanometer scale. Furthermore, under the strong confinements in the dual-scale nanopores, the calculated phase properties including the pore-size distribution effects are more accurate. In addition, effects of the temperature and feed gas to liquid ratio on the confined fluids in nanopores share similar manners with the bulk phase cases. The proposed theoretical models are capable of calculating the static and dynamic behavior of the confined fluids and all calculations have been validated by the experimentally measured results. This study supports the foundation of more general applications pertaining to producing shale fluids and sequestrating CO2 in shale reservoir characterization and exploration.
Dissymmetric reactions, which enable differentiated functionalization of equivalent sites within one molecule, have many potential applications in synthetic chemistry and materials science, but they are very challenging to achieve. Here, the dissymmetric reaction of 1,4-dibromo-2,5-diethynylbenzene (2Br-DEB) on Ag(111) is realized by using a stepwise activation strategy, leading to an ordered two-dimensional organometallic network containing both alkynyl–silver–alkynyl and alkynyl–silver–phenyl nodes. Scanning tunneling microscopy and density functional theory calculations are employed to explore the stepwise conversion of 2Br-DEB, which starts from the H-passivation of one Br-substituted site at 300 K in accompaniment with an intermolecular reaction to form one-dimensional organometallic chains containing alkynyl–silver–alkynyl nodes. Afterwards, the other equivalent Br-substituted site undergoes metalation reaction at 320–450 K, resulting in transformation of the chains into the binodal networks. These findings exemplify the achievement of the dissymmetric reaction and its practical application for controlled fabrications of complicated yet ordered nanostructures on a surface.
Decabromodiphenyl ethane (DBDPE) is an alternative to the commercial decabromodiphenyl ether (deca-BDE) mixture but has potentially similar persistence, bioaccumulation potential and toxicity. While it is widely used as a flame retardant in electrical and electronic equipment (EEE) in China, DBDPE could be distributed globally on a large scale with the international trade of EEE emanating from China. Here, we performed a dynamic substance flow analysis to estimate the time-dependent mass flows, stocks and emissions of DBDPE in China, and the global spread of DBDPE originating in China through the international trade of EEE and e-waste. Our analysis indicates that, between 2006 and 2016, ∼230 thousand tonnes (kt) of DBDPE were produced in China; production, use and disposal activities led to the release of 196 tonnes of DBDPE to the environment. By the end of 2016, ∼152 kt of the DBDPE produced resided in in-use products across China. During the period 2000–2016, ∼39 kt of DBDPE were exported from China in EEE products, most of which (>50%) ended up in North America. Based on projected trends of China's DBDPE production, use and EEE exports, we predict that, by 2026, ∼74 and ∼14 kt of DBDPE originating in China will reside in in-use and waste stocks, respectively, in regions other than mainland China, which will act as long-term emission sources of DBDPE worldwide. This study discusses the considerable impact of DBDPE originating in China and distributed globally through the international trade of EEE; this is projected to occur on a large scale in the near future, which necessitates countermeasures.
This study focuses on the Danjiangkou reservoir, and investigates the release regulation of total nitrogen, nitrate, nitrite and ammonia from sediments as a function of temperature, perturbation and aeration conditions. Moreover, a simulation reactor was set up to explore the elimination of endogenous nitrogen pollution through high-efficient aerobic denitrification microorganism augmentation. Effects of high-efficient aerobic denitrification microorganisms on the microbial community structure in the sediments was also evaluated by means of high-throughput sequencing technology. The results indicated that increasing temperature could promote the release of nitrate and nitrite from sediments, while inhibiting the release of ammonium. Disturbances of water was beneficial to nitrogen release from sediments, and the nitrogen amount accumulated in the overlying water was proportional to the agitation speed. Concentrations of dissolved oxygen had great effects on the nitrogen release from sediments. It was found that the aeration treatment significantly reduced the release of total nitrogen and nitrite from sediments, and the subsequent accumulation in water. After addition of the a high-efficient aerobic denitrification bacteria Pseudomonas stutzeri (PCN-1) into the simulation reactor, concentrations of all the forms of nitrogen in the reactor increased at first and then decreased. On the 65th day of the experiment, removal rates of total nitrogen and nitrate released from sediments were as high as 75.87% and 79.96% respectively, suggesting effective control of the endogenous nitrogen. The relative abundance of Proteobacteria, Bacteroidetes and Spirochaetes in sediments was significantly increased after PCN-1 addition, so the microbial community structure in the sediments was changed by microbial augmentation treatment with PCN-1 as well.以丹江口水库为例,考察水库底泥在不同温度、扰动和曝气等条件下,总氮、硝氮、氨氮和亚硝氮的释放规律。设置模拟反应器,探究高效好氧脱氮微生物强化消除 水库底泥内源氮污染的效果,并运用高通量测序技术,分析高效好氧脱氮微生物对底泥微生物群落结构的影响。结果表明,温度升高会减少氨氮的释放,增加硝氮和 亚硝氮的积累;水体扰动会加速底泥中氮素释放,且上覆水中的氮素释放累积量与扰动速度成正比;溶解氧对底泥氮素释放有显著影响,曝气处理可以明显地降低底 泥中总氮和硝氮的释放及其在水体中的累积。在反应器中底泥-上覆水界面投加高效好氧脱氮微生物Pseudomonas stutzeri (PCN-1)后,反应器内各种形态的氮素都出现先上升、后下降的趋势;在反应器运行的第65天,底泥释放的总氮和硝氮的去除率分别高达75.87%和7 9.96%,底泥内源氮污染得到有效的控制。对比投加菌株前后的微生物群落结构,发现底泥中Proteobacteria, Bacteroidetes和Spirochaetes的相对丰度明显增加, PCN-1强化脱氮处理能够改变底泥的微生物群落结构。
We develop a non-perturbative approach for calculating the superconducting transition temperatures (\$T\_\c\\$) of liquids. The electron-electron scattering amplitude induced by electron-phonon coupling (EPC), from which the effective pairing interaction can be inferred, is related to the fluctuation of the \$T\$-matrix of electron scattering induced by ions. By applying the relation, EPC parameters can be extracted from a path-integral molecular dynamics simulation. For determining \$T\_\c\\$, the linearized Eliashberg equations are re-established in the non-perturbative context. We apply the approach to estimate \$T\_\c\\$ of metallic hydrogen liquids. It indicates that metallic hydrogen liquids in the pressure regime from \$0.5\$ to \$1.5$\backslash$mathrm\$\backslash$,TPa\\$ have \$T\_\c\\$ well above their melting temperatures, therefore are superconducting liquids.