Search

Since entering the new era, China's socialist contradiction has been transformed into the contradiction between the people's growing need for a better life and the unbalanced and inadequate development. How to improve the quality of people's life through the improvement of air quality has become an important content restricting social development and a key problem to be solved. Based on the life satisfaction (LS) method, this study takes air quality into the individual utility function, and through matching China Health and Retirement Longitudinal Study (CHARLS), two phases of microindividual tracking data with 122 urban environmental quality data innovatively investigate the impact of air quality on residents' LS and its income substitution effect. The results show that air quality significantly reduces residents' LS, among which, different air pollutants and comprehensive air quality AQI have significant negative effects. And PM10 has the highest marginal effect on different LS evaluation, SO2 has the smallest marginal effect, and AQI marginal effect is close to PM10. In terms of group heterogeneity, NO2 and SO2 have group influence differences in age group, regional economic group, gender group, and family per capita income group. But PM10 and AQI do not show group influence heterogeneity, and air quality has significant negative effect on LS of different groups. In addition, the interaction between air quality and income level shows that air quality strengthens the difference of residents' LS caused by income level difference. According to the equilibrium condition of residents' individual utility function, the improvement of air quality by 1% is equivalent to the improvement of residents' LS by 23.4402% of income. Firstly, air quality has an important impact on residents' LS, and different air pollutants have different effects. Secondly, the impact of air quality on LS of different groups is heterogeneous and mainly diversified in age group, regional economic group, gender group, and family per capital income group. Finally, there is substitution effect between air quality and regional GDP growth and household income, which affects residents' LS. Thirdly, the conclusion shows that the improvement of air quality is difficult to be replaced by other ways. Good air quality can not only directly improve residents' LS, but also has economic effect.

Food waste is a major issue in the context of pollution, climate change, and the future circular economy. Composting kitchen waste is a promising method to recycle elements, yet the efficiency of composting is limited, calling for new processes that degrade rapidly and thoroughly organic matter. Here, we built a rapid laboratory-scale aerobic composting system, equipped with a water bath fueled with either solar energy, or electricity under low sunlight. We tested compositing with and without energy. Results show that only three days are needed to raise the temperature to over 45 °C by energy composting in winter, leading to notable increases in pH, total nitrogen, and cation exchange capacity after 7 days. Composting materials were thoroughly decomposed and mature in 10 days, displaying pH of 7.5, ratio of total organic carbon to total nitrogen of 9.9, cation exchange capacity of 65.61 cmol kg−1, and germination index of 80.4%. Overall, energy composting starts biodegradation quickly in 2 days, reduces effectively the inhibition from some waste compounds, decomposes organic substances well, and yields mature compost.

Monitoring on urban water environment and analysis of engineering improvement measures are intricate and time-consuming tasks. In previous studies, the integration of hydrodynamic and water quality models and geographical information system (GIS) usually takes three approaches: loose coupling, tight coupling, and full coupling. However, this paper adopted a special loose coupling approach—case-based reasoning (CBR) to develop an integrated decision support system. This was characterized by invoking the case base stored in the GIS platform as the output of the model. The fused capability of model’s water quality predication and strong spatial data processing analysis of GIS can be realized at the same time by integration. The functionality of the integrated system was illustrated through a case study of Chaohu, a medium-sized city in China, which includes case retrieval, result interpretation, and the visual display in the GIS platform. Results verified the feasibility and operability of the developed method. As a useful tool, the integrated decision support system makes it simpler and more convenient for decision makers to make decisions efficiently and quickly.

Chlorpyrifos is a widely used organophosphate insecticide and ubiquitously detected in the environment. However, little attention has been paid to its endocrine disrupting effect to non-target organisms. In the present study, zebrafish was exposed to 13 and 65 μg/L of chlorpyrifos for 7 and 10 days to determine the induced neurotoxicity and the alteration of thyroid metabolism. The 120 h LC50 and LC10 of chlorpyrifos was estimated as 1.35 mg/L and 0.62 mg/L based on the acute embryo toxicity assay, respectively. The acetylcholinesterase (AChE) inhibitory was detected by 13 μg/L chlorpyrifos and could be reversed by the co-exposure of 100 and 1000 μg/L anticholinergic agent atropine. For thyroid hormone level, 13 and 65 μg/L of chlorpyrifos induced increased free T3 levels in 10 dpf (days post-fertilization). The expression of thyroid related genes in 7 and 10 dpf exposed zebrafish were measured by the quantitative Real-Time PCR (qRT-PCR) assay. The mRNA expression of tshba, thrb, crhb, ttr, tpo, ugt1ab and slc5a5 had significant change. However, the alterations of thyroid hormone and mRNA expression could be partly rescued by the addition of atropine. The molecular docking of chlorpyrifos and T3 to the thyroid receptor β in zebrafish using homology modelling and CDOCKER procedures shown weaker binding ability of chlorpyrifos compared to T3. Therefore, we concluded that the disturbance of thyroid signaling in zebrafish might arise from the developmental neurotoxicity induced by chlorpyrifos.

A simple and fast high-performance liquid chromatography (HPLC) fingerprint method combining reference standard extract for the identification of bilberry extract was developed and validated. Six batches of bilberry extract collected from different manufactures were used to establish the HPLC fingerprint. Other berry extracts&mdash, such as blueberry extracts, mulberry extracts, cranberry extracts, and black rice extracts&mdash, were also analyzed for their HPLC chromatograms. The fingerprints of five batches of bilberry extract showed high similarities, while one batch was distinguished from others. Additionally, the content of anthocyanin Cyanidin-3-O-glucoside (Cy-3-glc) in each berry extract was analyzed and compared. The results indicate that this HPLC fingerprint method, combining reference standard extracts, could be used for the authentication and quality control of bilberry extracts.

In this paper, a hybrid neural network (HNN) that combines a convolutional neural network (CNN) and long short-term memory neural network (LSTM) is proposed to extract the high-level characteristics of materials for critical temperature (Tc) prediction of superconductors. Firstly, by obtaining 73,452 inorganic compounds from the Materials Project (MP) database and building an atomic environment matrix, we obtained a vector representation (atomic vector) of 87 atoms by singular value decomposition (SVD) of the atomic environment matrix. Then, the obtained atom vector was used to implement the coded representation of the superconductors in the order of the atoms in the chemical formula of the superconductor. The experimental results of the HNN model trained with 12,413 superconductors were compared with three benchmark neural network algorithms and multiple machine learning algorithms using two commonly used material characterization methods. The experimental results show that the HNN method proposed in this paper can effectively extract the characteristic relationships between the atoms of superconductors, and it has high accuracy in predicting the Tc.

We investigated the dynamics and factors influencing the N uptake capacity in two sub-root systems of maize seedlings under partial N stress. Maize seedlings were grown in split-root containers containing nutrient solutions. Two N application conditions prior to partial N stress (full-strength N (4.0 mM): CP; N stress: SP) were considered. Thus, two experiments were conducted: (A) four treatments: CPNc, CPN2, CPN1 and CPN0, in which half of the root system was exposed to 4.0 mM, 2 mM, 1 mM and 0 mM N (CPNc–c, CPN2–2, CPN1–1 and CPN0–0), respectively, and the other half received full-strength N (CPNc–c, CPN2–c, CPN1–c and CPN0–c); (B) four treatments: SPNc, SPN2, SPN1 and SPN0, in which both sub-root systems received 4.0 mM, 2 mM, 1 mM and 0 mM N for 6 days, respectively, after which half of the root system was maintained at original N level (SPNc–c, SPN2–2, SPN1–1 and SPN0–0) and the other half received full-strength N (SPNc–c, SPN2–c, SPN1–c and SPN0–c). At 0.25 days after treatment (DAT), CPN2–c and CPN1–c enhanced N inflow rates (Iroot), whereas CPN0–c decreased it by 27.3% compared with CPNc–c, Iroot in CPN2–c, CPN1–c and CPN0–c was uniformly enhanced at 1 DAT, but were only enhanced in CPN0–c at 5 DAT compared with CPNc–c. In contrast, SPN1–c had a significantly increased Iroot by 10.52% compared with SPNc–c, although other treatments showed a negative effect on Iroot at 0.25 DAT. At 1 and 5 DAT, Iroot in SPN2–c, SPN2–2, SPN1–c, SPN1–1 and SPN0–c were significantly lower than that in SPNc–c. Furthermore, CP significantly enhanced Iroot in non-stressed sub-roots compared with SP. Additionally, CPN2 improved shoot dry mass and N use efficiency even under SPN2. Thus, N uptake capacity in each sub-root zone varied not only depending on the severity and duration of the N stress, but was also related to the N status prior to partial N stress. Moreover, the occurrence and disappearance of the root compensatory effect were delayed with increasing N stress severity. A higher compensatory effect developed following CP, even under CPN0.

To understand the functions of Populus euphratica CPD (PeCPD) and DWF4 (PeDWF4), the responses to exogenous phytohormone in Arabidopsis-PeCPD and -PeDWF4 transgenic lines (PeCPD-TL and PeDWF4-TL) and corresponding wild type (WT) seedlings were investigated. Results showed that all of PeCPD-TL, PeDWF4-TL and WT seedlings cultured on the mediums containing 2,4-dichlorophenoxyacetic acid (2,4-D) + 6-benzylaminopurin (6-BA) or 2,4-D + 6-BA + brassinolide (BL) could be dedifferentiated to callus with 100% frequency, but they displayed strong differences in callus formation sites, callus growth rates (CGRs) and tissue dedifferentiation degrees. On the medium containing 2,4-D alone, the seedlings of all the plants could formed callus, but callus formation times (CFTs) were delayed, and callus formation rates (CFRs) were differentially decreased. After adding lower concentrations of BL, their CFRs were all restored to 100%, but tissue dedifferentiation degrees were obviously lower than these on the mediums with 2,4-D + 6-BA or 2,4-D + 6-BA + BL. On the mediums containing 6-BA or 6-BA + BL, the seedlings of all the plants failed to produce callus. Semi-quantitative RT-PCR analysis also showed that the transcription levels of PeCPD, PeDWF4, AtCPD and AtDWF4 in PeCPD-TL, PeDWF4-TL and WT were evidently different. These results suggest that PeCPD and PeDWF4 play similar but not exactly the same roles in the regulation of callus morphogenesis of Arabidopsis seedlings, and that BL can partially replace the role of cytokinin to induce callus formation through interacting with auxin.

In this study, we analyzed the meteorological processes associated with 2018 tropical cyclone No. 14, “Yagi.” TC Yagi continued moving northeastward after losing its numerical designation from the National Meteorological Center of the China Meteorological Administration (CMA) because of weakening and then restrengthened when it moved over the Bohai Sea, inducing an ocean gale on 14-15 August 2018. The results of our investigation revealed that the continued northeastward movement of Yagi on 14 August was related to the divergence of the upper-level westerly jet stream, the northward shift of the subtropical high in the midtroposphere, as well as the steering flow and asymmetrical air flow around the disturbance itself in the lower troposphere. The enhancement of Yagi over the Bohai Sea on the night of 14 August was related to the decrease of friction over the ocean and the increase of diabatic heating from the sea surface flux. The wind speed increased to a maximum when the depression moved over the Bohai Sea, an occurrence that was not only due to the enhancement of the cyclone itself but also due to the flow of cold air from high latitudes along the north side of the Bohai Sea. The behavior of the cold air was related to the shift of the convergence zone in the upper-level westerly jet at 200 hPa, long-wave troughs and ridges at 500 hPa, and terrain effects. Thus, the gale development in the Bohai Sea was due to both the enhancement of tropical cyclone Yagi after it moved over the ocean and the flow of cold air from high latitudes.

Rapid estimation of crop nitrogen (N) status is helpful for achieving precise N fertilizer management, so as to promote the collaborative improvement of yield, quality and N use efficiency. To establish a method for rapidly estimating N status of apple-trees based on hyperspectral remote sensing, a field experiment on apple trees with four levels of N application were conducted in Luochuan, Yan'an, China in 2018 and 2019. Hyperspectral data at apple tree canopy scale were obtained at different phenological stages. The outliers in the dataset were detected by Monte-Carlo cross-validation (MCCV). A total of 15 forms of spectral data were analyzed, including the raw spectrum (RS), Savitzky-Golay (SG) smoothing, normalization by the mean (NME), standard normal transformation (SNV), multiplicative scatter correction (MSC) and their combination with the first-order derivative (FD) or second-order derivative (SD). The results showed that SNV-FD was the best preprocessing method for apple tree canopy spectral data on the Loess Plateau. For SNV-FD data, competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA), random frog (Rfrog), and partial least squares (PLS) were used to extract feature variables. The feature wavelengths extracted by CARS, SPA and Rfrog were widely distributed in visible and near-infrared (VIS/NIR) range. The feature variables extracted by PLS were fewer, but had a strong interpretation. Based on these feature variables, linear and nonlinear models including partial least squares regression (PLSR), support vector machine (SVM), back-propagation artificial neural network (BPANN), extreme learning machine (ELM) and random forest (RF), were used to establish the prediction model. Among all the models, four nonlinear modeling methods were superior to the linear method. The model by Rfrog-ELM achieved the best results (R2P = 0.843, RMSEP = 2.461 g·kg−1, RPD = 2.508). This study demonstrated that the combination of SNV-FD, Rfrog and ELM was feasible and reliable for estimating the leaf N content in apple-trees on the Loess Plateau, China.

The two most important aspects of material research using deep learning (DL) or machine learning (ML) are the characteristics of materials data and learning algorithms, where the proper characterization of materials data is essential for generating accurate models. At present, the characterization of materials based on the molecular composition includes some methods based on feature engineering, such as Magpie and One-hot. Although these characterization methods have achieved significant results in materials research, these methods based on feature engineering cannot guarantee the integrity of materials characterization. One possible approach is to learn the materials characterization via neural networks using the chemical knowledge and implicit composition rules shown in large-scale known materials. This article chooses an adversarial method to learn the composition of atoms using the Generative Adversarial Network (GAN), which makes sense for data symmetry. The total loss value of the discriminator on the test set is reduced from 4.1e13 to 0.3194, indicating that the designed GAN network can well capture the combination of atoms in real materials. We then use the trained discriminator weights for material characterization and predict bandgap, formation energy, critical temperature (Tc) of superconductors on the Open Quantum Materials Database (OQMD), Materials Project (MP), and SuperCond datasets. Experiments show that when using the same predictive model, our proposed method performs better than One-hot and Magpie. This article provides an effective method for characterizing materials based on molecular composition in addition to Magpie, One-hot, etc. In addition, the generator learned in this study generates hypothetical materials with the same distribution as known materials, and these hypotheses can be used as a source for new material discovery.

Faced with the scarcity of water resource and irrational fertilizer use, it is highly important to supply plants with water and fertilizer at desiderated stages to improve yield with high water use efficiency (WUE). A pot experiment was conducted to investigate the effects of growth stage-specific water deficiency and potassium (K) fertilization on tomato yield and WUE. The entire growing season of tomato was divided into 5 stages: vegetative growth stage (VG), flowering and fruit setting stage (FS), early fruit growth stage (FG), fruit development stage (FD) and fruit maturity stage (FM). Three soil moisture (W) and three K fertilization levels were set up. W levels included W1, W2 and W3, indicating that soil water was maintained at 60-70% field capacity, 70-80% field capacity, and 80-90% field capacity, respectively. K levels included K1, K2 and K3, indicating that 0 g K2O per kg soil, 0.46 g K2O per kg soil and 0.92 g K2O per kg soil was applied. All combinations of the three W and three K levels were solely imposed at each of the five growth stages, for other four stages, plants were watered to 80-90% field capacity without K fertilizer (W3K1). The permanent W3K1 over the entire growth stage was taken as control (CK). The results showed that W deficiency imposed at all stages significantly affected tomato yield (P

Effects of severity and duration of osmotic stress on partial root system were investigated on root hydraulic conductance (L p ) and growth in each sub-root system. The maize seedlings were raised in nutrient solution with the roots divided equally into two containers. At 12 days after transplanting, half of root system was subjected to osmotic stress of −0.2, −0.4 and −0.6 MPa using PEG 6000 added in the solution, and no PEG 6000 solution was taken as control (CK). L p and root growth in each sub-root system were measured at 0, 0.25, 0.5, 1, 3, 5, 7 and 9 days after treatment (DAT). Results show that compared to CK, −0.2 MPa treatment enhanced the hydraulic conductance per root area (L pr ) in non-stressed sub-root system by 12 % at 0.5 DAT. In −0.4 MPa treatment, L pr in non-stressed sub-root system was significantly increased at 9 DAT. But in −0.6 MPa treatment, significant decrease of 12–40 % was observed in non-stressed sub-root system during 0.5–3 DAT if compared to CK, indicating that the threshold of osmotic stress for the compensatory effect of water uptake in non-stressed sub-root system was between −0.2 and −0.4 MPa. In addition, the root area growth rate in non-stressed sub-root system was significantly higher than that in CK during 0.25–0.5, 1–3 and 5–7 DAT for −0.2, −0.4 and −0.6 MPa treatments, respectively. Similar trend also was observed for root length growth rate, indicating that osmotic stress could still stimulate the compensatory effect of root growth other than water uptake under partial root system. Moreover, the occurrence of such compensatory effect delayed with the increasing osmotic stress. Meanwhile, −0.2 MPa treatment had no significant effect on maize shoot growth but −0.4 and −0.6 MPa treatments inhibited shoot biomass accumulation, which resulted in higher root/shoot ratio in −0.4 and −0.6 MPa treatments. Thus root plasticity in hydraulic conductance and root growth in different root zones varied largely depending on the severity and duration of osmotic stress under partial root system.

In this paper, we investigate the observational direct radiation characteristics of several sandstorm events in Northwestern China (NWC). A simulating sensitivity experiment was designed to reduce the downward radiation in RegCM4 to investigate the climatic impacts and persistence of the direct radiation effect (DRE) from dust aerosols in sandstorms. The results show that dust aerosols in sandstorms can change the radiation heating rate of the atmosphere, heating the air in the middle and low troposphere and cooling Earth’s surface. The climate effects of continuous and intense sandstorms in April in NWC can reach downstream areas such as Southeast and Northeast China and can persist for months. The dust aerosols in sandstorms can enhance diabatic heating and moisture loss. Therefore, dust storms lead to the environment in NWC becoming warmer and dryer. Through analysis of the dust tracer total burden, we identified that the enhancement of the dust total burden in the arid region illustrated that the DRE of dust aerosol in sandstorm process can react with the dust emission, thus forming a self-feedback loop. The DRE can persist three months.

A field experiment was carried out to investigate the effects of different supply methods of nitrogen (N) fertilizer and irrigation on the spatial distribution and dynamics of soil NO3-N for maize (Zea mays L.) grown in northwest China in 2012 and 2014. In 2012, there were three irrigation methods: alternate furrow irrigation (AI), fixed furrow irrigation (FI) and conventional furrow irrigation (CI). Three N supply methods: alternate N supply (AN), fixed N supply (FN) and conventional N supply (CN), were applied at each irrigation method. In 2014, the fixed treatments were excluded. Soil NO3-N in horizontal direction was measured to 100 cm soil profile. For 2012, at filling stage, compared to CI, AI increased soil NO3-N concentration under the plant by 4.5 to 7.4% in 0-40 cm soil profile and decreased that by 9.9 to 14.4% in 40-80 cm for three N supply methods. NO3-N concentration between two sides of the ridge was comparable for AN and CN coupled with AI or CI. When compared to CI, AI reduced soil NO3-N concentration in 60-100 cm by 4.8 to 8.7% from 12 collars stage to maturity over different positions when coupled with CN. Soil residual NO3-N at maturityin 0-100 cm was the lowest in AI coupled with CN or AN. The 2014 experiment verified the above results. Therefore, alternate furrow irrigation coupled with conventional or alternate N supply brought an optimum spatial distribution of soil NO3-N during maize season, resulting in little soil residual NO3-N at maturity.

The particle size of apatite is one of the critical factors that influence the adsorption of heavy metals on apatite in the remediation of heavy metal contaminated soils using apatite. However, little research has been done evaluating the impact of different particle sizes of apatite on immobilization remediation of heavy metal polluted soils in field. In this study, the adsorption isothermal experiments of copper on three kinds of apatite was tested, and the field experiment by using different particle sizes apatite [nano-hydroxyapatite (NAP), micro-hydroxyapatite (MAP), ordinary particle apatite (OAP)] at a same dosage of 25.8 t/ha (1.16 %, W/W) was also conducted. Ryegrass was chosen as the test plant. The ryegrass biomass, the copper contents in ryegrass and the copper fractionations in soil were determined after field experiments. Results of adsorption experiments showed that the adsorption amounts of copper on OAP was the lowest among different particles. The adsorption amounts of copper on MAP was higher than NAP at high copper equilibrium concentration (>1 mmol L−1), an opposite trend was obtained at low copper concentration ( NAP > OAP, which was attributed to the high adsorption capacity of copper and the strong releasing of phosphate by MAP.