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Global warming and algal blooms have been two of the most pressing problems faced by the world today. In recent decades, numerous studies indicated that global warming promoted the expansion of algal blooms. However, research on how algal blooms respond to global warming is scant. Global warming coupled with eutrophication promoted the rapid growth of phytoplankton, which resulted in an expansion of algal blooms. Algal blooms are affected by the combined effects of global warming, including increases in temperatures, CO2 concentration, and nutrient input to aquatic systems by extreme weather events. Since the growth of phytoplankton requires CO2, they appear to act as a carbon sink. Unfortunately, algal blooms will release CH4, CO2, and inorganic nitrogen when they die and decompose. As substrate nitrogen increases from decompose algal biomass, more N2O will be released by nitrification and denitrification. In comparison to CO2, CH4 has 28-fold and N2O has 265-fold greenhouse effect. Moreover, algal blooms in the polar regions may contribute to melting glaciers and sea ice (will release greenhouse gas, which contribute to global warming) by reducing surface albedo, which consequently would accelerate global warming. Thus, algal blooms and global warming could form feedback loops which prevent human survival and development. Future researches shall examine the mechanism, trend, strength, and control strategies involved in this mutual feedback. Additionally, it will promote global projects of environmental protection combining governance greenhouse gas emissions and algal blooms, to form a geoengineering for regulating the cycles of carbon, nitrogen, and phosphorus. [ABSTRACT FROM AUTHOR]

Timely and accurately monitoring leaf nitrogen content (LNC) is essential for evaluating crop nutrition status. Currently, Unmanned Aerial Vehicles (UAV) imagery is becoming a potentially powerful tool of assessing crop nitrogen status in fields, but most of crop nitrogen estimates based on UAV remote sensing usually use single type imagery, the fusion information from different types of imagery has rarely been considered. In this study, the fusion images were firstly made from the simultaneously acquired digital RGB and multi-spectral images from UAV at three growth stages of rice, and then couple the selecting methods of optimal features with machine learning algorithms for the fusion images to estimate LNC in rice. Results showed that the combination with different types of features could improve the models' accuracy effectively, the combined inputs with bands, vegetation indices (VIs) and Grey Level Co-occurrence Matrices (GLCMs) have the better performance. The LNC estimation of using fusion images was improved more obviously than multispectral those, and there was the best estimation at jointing stage based on Lasso Regression (LR), with R2 of 0.66 and RMSE of 11.96%. Gaussian Process Regression (GPR) algorithm used in combination with one feature-screening method of Minimum Redundancy Maximum Correlation (mRMR) for the fusion images, showed the better improvement to LNC estimation, with R2 of 0.68 and RMSE of 11.45%. It indicates that the information fusion from UAV multi-sensor imagery can significantly improve crop LNC estimates and the combination with multiple types of features also has a great potential for evaluating LNC in crops. [ABSTRACT FROM AUTHOR]

Light and hydrodynamic force are important physical factors affecting growth of Microcystis. The most recent study found that green light has good effect in inhibiting growth of Microcystis. To understand the effect of mixing modes on Microcystis under the green light, we investigated the effects of continuous mixing and intermittent mixing on the abundance of Microcystis in Taihu Lake under field conditions. The study results found that abundance of Microcystis in control, intermittent mixing group, and continuous mixing group decreased 76.62%, 40.36%, and 95.18% on day 7 compared with that on day 1 in this experiment. At the end of the experiment, abundance percentages of diatoms and green algae to total phytoplankton abundance were 1.57% and 0.48% in control, 2.32% and 0.67% in intermittent mixing group, and 22.47% and 20.27% in continuous mixing group. The results indicated that continuous mixing favored the removal of Microcystis under green light conditions and was helpful for the growth of green algae and diatoms. The results provide a new approach for the control of Microcystis blooms. [ABSTRACT FROM AUTHOR]

Metal–organic framework materials(ZIF-9) were loaded on Sodium alginate/polyvinyl(PVA/SA) hydrogel by in situ growth method for adsorption of heavy metal Cu (II). The structure of hydrogels composited with MOFs and polymers was designed to improve the poor mechanical properties of natural polymer gel materials and the inconvenience of powdered MOFs materials in practical applications. The adsorption results showed that the optimum adsorption process of Cu (II) pH was 5.0. The adsorption kinetics and isotherm suggest that the adsorption process follows the Freundlich isotherm and the pseudo-second-order models. The experimental maximum adsorption capacity was 98.98 mg/g, 2.6 times and 1.5 times higher than ordinary SA and PVA/SA hydrogel spheres. Synthesized hydrogel spheres were characterized by FT-IR, SEM, XRD, and XPS, which confirmed that MOF materials have grown in situ on PVA/SA hydrogel spheres. More importantly, PVA/SA@ZIF-9 exhibited exceptional mechanical stability and showed excellent recycling capability in the cyclic adsorption process. [ABSTRACT FROM AUTHOR]

Nutrients and hydrodynamic mixing are both important environmental factors affecting the growth of Microcystis. Effects of nutrient combined with hydrodynamic mixing in the dominance of Microcystis in phytoplankton community is unclear. Here we present data on the effects of hydrodynamic mixing (HM), nutrient addition (+ N + P), and hydrodynamic mixing combined nutrient addition (HM + N + P) on dominance of Microcystis in a microcosm experiments. Results showed that the average number of Microcystis in HM + N + P was 10.09, 3.79, and 1.95 times that of the control (9.19 × 106 cells L−1), + N + P, and HM group, respectively. Moreover, the mean colony sizes of Microcystis in HM + N + P group were 2.08, 1.91, and 1.21 times that of the control (24.42 μm), + N + P,HM group, respectively. Pseudanabaena limnetica replaced Microcystis as the dominant species in control, + N + P, and HM group at end of the experiment, with 82.21%, 90.65%, and 50.37% of total algae number, respectively. However, in HM + N + P group, Microcystis dominated throughout the experimental period, accounting for 73.56–94.67% of the total algae abundance. Results demonstrated that N and P combined with hydrodynamic mixing promoted abundance, colony size of Microcystis, which plays an important role in the dominance of Microcystis in phytoplankton community in natural ecosystems. [ABSTRACT FROM AUTHOR]

Trace element is one of the important factors affecting the growth of Microcystis. The effects of zinc (0.4 mg/L) and iron (2 mg/L) on the abundance of Microcystis in Lake Taihu were investigated under continuous turbulence and green light conditions in a microcosm experiment. The study results showed that the abundance of Microcystis in the zinc treatment and the iron treatment group was 8.30% and 214% of that in the control group at the end of the experiment, respectively. The proportion of Cyanobacteria in the total phytoplankton biomass in the control, iron treatment, and zinc treatment group decreased from 99.99% at the beginning of the experiment to 13%, 18%, and 1% at the end of the experiment, respectively. At the end of the microcosm experiment, the phytoplankton community was dominated by Bacillariophyta in the control group, accounting for 63%, but it was dominated by Chlorophyta in the zinc treatment and the iron treatment group, accounting for 89% and 42%, respectively. The study results showed that under green light and turbulence, 0.4 mg/L zinc remarkably decreased the abundance of Microcystis, but 2 mg/L iron effectively increased the number of Microcystis and other algae. This research results provided a new idea for controlling Microcystis blooms. [ABSTRACT FROM AUTHOR]

Hydrodynamic mixing is one of the important environment factors in determining phytoplankton community compositions. Here the influences of continuous hydrodynamic mixing on abundance, morphology, and dominance of Microcystis were investigated in microcosm and lab experiments. Our research results showed that Cyanophyta contributed 57.16% to the total biomass in control, but Chlorophyta was the dominant group in continuous hydrodynamic mixing (CHM) group, contributing 76.54% to the total biomass in the microcosm experiment. The average number of Microcystis in control was 1.95 folds in CHM group. However, the mean abundance of Scenedesmus quadricauda and Pseudanabaena limnetica in CHM was 2.47 and 2.97 folds in control. In the lab experiment, the average number of Microcystis flos-aquae in control was 2.97 folds in CHM group. The mean size of M. flos-aquae colony in control (34.65 μm) group were significantly bigger than that in the CHM (26.78 μm) group. This research results demonstrated that continuous hydrodynamic mixing weakened the dominance of Microcystis, but was beneficial for the others algae (S. quadricauda and P. limnetica) and is helpful in understanding the effect of hydrodynamic mixing on Microcystis blooms in freshwater ecosystem. [ABSTRACT FROM AUTHOR]

In shallow lakes, wind wave turbulence alters underwater spectral composition, but the influence of this phenomenon on phytoplankton community structure is poorly understood. We used 100L mesocosms to investigate the influence of light quality on a natural phytoplankton community collected from Taihu Lake in China. The communities in mesocosms were exposed to sunlight filtered for white, blue, green, and red light, while wave-making pumps simulated wind wave turbulence similar to Taihu Lake. Over the course of experiment, each filtered light reduced the total phytoplankton abundance compared to white light. The mean abundance of phytoplankton in controls was 1.72, 1.78, and 7.89 times of that in the red, blue, and green light treatments. Red, blue, and green light significantly promoted the growth of cyanobacteria, green algae, and diatoms, respectively, and induced successional change of the phytoplankton species under the tested conditions. The proportion of Microcystis to total phytoplankton abundance in controls and red light shifted from 87.09% at the beginning to 37.95% and 56.30% at the end of the experiment, respectively, and maintained its dominance, whereas Microcystis lost its dominance and was replaced by Scenedesmus (53.78%) and Synedra (53.18%) in the blue and green light, respectively. Given the process of how these phytoplankton compete in designated spectrum, exploring these influences could help provide new insights into the dominance formation of toxic cyanobacteria. [ABSTRACT FROM AUTHOR]

To obtain accurate spatially continuous reflectance from Unmanned Aerial Vehicle (UAV) remote sensing, UAV data needs to be integrated with the data on the ground. Here, we tested accuracy of two methods to inverse reflectance, Ground-UAV-Linear Spectral Mixture Model (G-UAV-LSMM) and Minimum Noise Fraction-Pixel Purity Index-Linear Spectral Mixture Model (MNF-PPI-LSMM). At wavelengths of 550, 660, 735 and 790 nm, which were obtained by UAV multispectral observations, we calculated the canopy abundance based on the two methods to acquire the inversion reflectance. The correlation of the inversion and measured reflectance values was stronger in G-UAV-LSMM than MNF-PPI-LSMM. We conclude that G-UAV-LSMM is the better model to obtain the canopy inversion reflectance. [ABSTRACT FROM AUTHOR]

Timely, nondestructive and effective determination of canopy nitrogen content provides an important reference value for real-time monitoring of total nitrogen status of apple trees. Different processing methods are used to mine hyperspectral information to estimate nitrogen content. However, the overprocessing or underprocessing of hyperspectral data leads to the underutilization of spectral information. The primary objective of this study was to establish a model for estimating the nitrogen content of apple tree canopy by red-edge parameters based on fractional differential. The Grunwald–Letnikov fractional difference algorithm was used to extract the red-edge parameters from the hyperspectral canopy data, so as to develop the support vector machine (SVM) and random forest (RF) models. The results showed that the correlation with nitrogen content can be enhanced by differential spectroscopy compared with the original spectrum. The spectral parameters such as red-edge peak area (Sr(α)) obtained by fractional differential and logarithmic transformation processing and the correlation coefficient with nitrogen content can reach 0.6 or greater. The R2 of SVM and RF models constructed with red-edge parameters reached 0.56 (RMSE was 1.51 for SVM) and 0.94 (RMSE was 0.84 for RF), respectively. The RPD greater than 2 indicates that both models could be used for nitrogen estimation, and the RF model has a better predictive effect (RPD was 2.17 for SVM, RPD was 2.43 for RF). It provides an effective method for real-time monitoring of apple canopy nitrogen status and provides theoretical and technical support for hyperspectral information mining and data processing. [ABSTRACT FROM AUTHOR]

Analysis of the canopy structure change and spectral response mechanism of rice under flooding stress is an important prerequisite for large-scale monitoring of rice flooding disasters. The leaf area index (LAI) was used as the characterization indicator. The response rule of the canopy spectrum to flooding stress intensity was analyzed. The sensitive spectral characteristic parameters were screened to construct the LAI spectral response model of rice under flooding stress. The results showed that the rice LAI under flooding stress decreased with an increase in waterlogging depth. The spectral reflectance of the rice canopy under flooding stress significantly changed in the near-infrared band and decreased with an increase in waterlogging depth. In 680–760 nm, the double peak in the first-order differential spectrum of the rice canopy was more obvious with advancement of the growth process and a multiple peak appeared during the late growth stage. The blueshift of the red edge parameters was the most obvious in the submerged top during the tillering stage. A power function regression model based on the ratio of the first-order differential spectral amplitude at 737 nm to 719 nm in the red edge range was the optimal LAI response model for rice under flooding stress. A field waterlogging experiment was used to simulate and analyze the influence of flooding on the rice canopy structure and the canopy spectral response rule, providing a reference for the subsequent analysis of rice growth and disaster loss assessment under flooding stress. [ABSTRACT FROM AUTHOR]

Accurate estimation of crop biophysical and biochemical parameters during crop growing seasons is essential for improving site-specific management and yield estimation. The potential ability of fully polarimetric synthetic aperture radar (SAR) data in estimating above-ground biomass of oilseed rape was investigated in this study. The temporal profile of different scattering intensity and polarimetric features during the entire growing season was identified with ground measurements. A polarimetric feature, relying on the polarimetric decomposition method, was put forward to estimate the biomass of oilseed rape. Validation results revealed great potential with a determination coefficient (R2) of 0.85, root mean squared error (RMSE) of 41.6 g/m2, and relative error (RE) of 28.5% for dry biomass, and an R2 of 0.76, RMSE of 527.4 g/m2 and RE of 28.6% for fresh biomass. Moreover, the use of full polarization SAR data was compared with single and dual polarization SAR data. The results suggest that when full polarization SAR data is available, a simpler model, higher saturation point and better accuracy can be achieved in biomass estimation of oilseed rape, which highlights the importance and value of polarimetry information in quantitative crop monitoring. This study provides guidelines for in-season monitoring of crop growth parameters with SAR data, which further improves crop monitoring capability in adverse weather conditions. [ABSTRACT FROM AUTHOR]

The main objective of this research was to examine the feasibility of Multi-GNSS precise point positioning (PPP) in precision agriculture (PA) through a series of experiments with different working modes (i.e. stationary and moving) under different observation conditions (e.g. open sky, with buildings or with canopy). For the stationary test carried out in open space in the UK, the positioning accuracy achieved was 13.9 mm in one dimension by a PPP approach, and the repeatability of positioning results was improved from 19.0 to 6.0 mm by using Multi-GNSS with respect to GPS only. For the moving test carried out in similar location in the UK, almost the same performance was achieved by GPS-only and by Multi-GNSS PPP. However, for a moving experiment carried out in China with obstruction conditions, Multi-GNSS improved the accuracy of baseline length from 126.0 to 35.0 mm and the repeatability from 110.0 mm to 49.0 mm, The results suggested that the addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing improved the positioning repeatability, while a positioning accuracy was achieved at about 20 mm level in the horizontal direction with an improvement against the GPS-only PPP results. In space-constrained and harsh environments (e.g. farms surrounded with dense trees), the availability and reliability of precise positioning decreased dramatically for the GPS-only PPP results, but limited impacts were observed for Multi-GNSS PPP. In addition, compared to real time kinematic (RTK) GNSS, which is currently most commonly used for high precision PA applications, similar accuracy has been achieved by PPP. In contrast to RTK GNSS, PPP can provide high accuracy positioning with higher flexibility and potentially lower capital and running costs. Hence, PPP might be a great opportunity for agriculture to meet the high accuracy requirements of PA in the near future. [ABSTRACT FROM AUTHOR]

Water productivity (WP) is a key element of agricultural water management in agricultural irrigated regions. The objectives of this study were: (i) to estimate biomass of winter wheat using spectral indices; (ii) integrate the estimation of biomass data with the AquaCrop model using a lookup table for higher accuracy biomass simulation; (iii) show estimation accuracy of the data assimilation method in yield and WP. Spectral variables and concurrent biomass, yield and WP of samples were acquired at the Xiaotangshan experimental site in Beijing, China, during the 2008/2009, 2009/2010, 2010/2011 and 2011/2012 winter wheat growing seasons. The results showed that all spectral indices had a highly significant relationship with biomass, especially normalized difference matter index, with R and RMSE values of 0.84 and 1.43 t/ha, respectively. Simulation of biomass and yield by the AquaCrop model were in good agreement with the measured biomass and yield of winter wheat. The results showed that the data assimilation method (R = 0.79 and RMSE = 0.12 kg/m) could be used to estimate WP. The result indicated that the AquaCrop model could be used to estimate yield and WP with the aid of remote sensing for improving agricultural water resources management. [ABSTRACT FROM AUTHOR]

Wind waves are responsible for some of the spatio-temporal gradients observed in the biotic and abiotic variables in large shallow lakes. However, their effects on the phytoplankton community composition are still largely unexplored especially in freshwater systems such as lakes. In this paper, using field observations and mesocosm bioassay experiments, we investigated the impact of turbulence generated by wind waves on the phytoplankton community composition (especially on harmful cyanobacteria) in Lake Taihu, a large, shallow eutrophic lake in China. The composition of the phytoplankton community varied with the intensity of wind waves in the different areas of the lake. During summer, when wind waves were strong in the central lake, diatoms and green algae seemed to dominate while harmful cyanobacteria dominated in the weakly influenced Meiliang Bay. Turbulence bioassays also showed that diatoms and green algae were favoured by turbulent mixing. The critical time for the shift of the phytoplankton community composition was approximately 10 days under turbulent conditions. However, short-term (6 days) turbulence is rather beneficial for the dominance of cyanobacteria. This study suggests that the duration of wind events and their associated hydrodynamics are key factors to understanding the temporal and spatial changes of phytoplankton communities. [ABSTRACT FROM AUTHOR]

In most cases, statistical models for monitoring the disease severity of yellow rust are based on hyperspectral information. The high cost and limited cover of airborne hyperspectral data make it impossible to apply it to large scale monitoring. Furthermore, the established models of disease detection cannot be used for most satellite images either because of the wide range of wavelengths in multispectral images. To resolve this dilemma, this paper presents a novel approach by constructing a spectral knowledge base (SKB) of diseased winter wheat plants, which takes the airborne images as a medium and links the disease severity with band reflectance from environment and disaster reduction small satellite images (HJ-CCD) accordingly. Through a matching process with a SKB, we estimated the disease severity with a disease index (DI) and degrees of disease severity. The proposed approach was validated against both simulated data and field surveyed data. Estimates of DI (%) from simulated data were more accurate, with a coefficient of determination ( R) of 0.9 and normalized root mean square error (NRMSE) of 0.2. The overall accuracy of classification reached 0.8, with a kappa coefficient of 0.7. Validation of the estimates against field measurements showed that there were some errors in the DI value with the NRMSE close to 0.5. The result of the classification was more encouraging with an overall accuracy of 0.77 and a kappa coefficient of 0.58. For the matching process, Mahalanobis distance performed better than the spectral angle (SA) in all analyses in this study. The potential of SKB for monitoring the incidence and severity of yellow rust is illustrated in this study. [ABSTRACT FROM AUTHOR]

The general population has a pessimistic view of low back pain (LBP), and evidence-based information has been used to positively influence LBP beliefs in previously reported mass media studies. However, there is a lack of randomized trials investigating whether LBP beliefs can be modified in primary prevention settings. This cluster randomized clinical trial investigated the effect of an evidence-based psychosocial educational program (PSEP) on LBP beliefs for soldiers completing military training. A military setting was selected for this clinical trial, because LBP is a common cause of soldier disability. Companies of soldiers (n = 3,792) were recruited, and cluster randomized to receive a PSEP or no education (control group, CG). The PSEP consisted of an interactive seminar, and soldiers were issued the Back Book for reference material. The primary outcome measure was the back beliefs questionnaire (BBQ), which assesses inevitable consequences of and ability to cope with LBP. The BBQ was administered before randomization and 12 weeks later. A linear mixed model was fitted for the BBQ at the 12-week follow-up, and a generalized linear mixed model was fitted for the dichotomous outcomes on BBQ change of greater than two points. Sensitivity analyses were performed to account for drop out. BBQ scores (potential range: 9-45) improved significantly from baseline of 25.6 +/- 5.7 (mean +/- SD) to 26.9 +/- 6.2 for those receiving the PSEP, while there was a significant decline from 26.1 +/- 5.7 to 25.6 +/- 6.0 for those in the CG. The adjusted mean BBQ score at follow-up for those receiving the PSEP was 1.49 points higher than those in the CG (P < 0.0001). The adjusted odds ratio of BBQ improvement of greater than two points for those receiving the PSEP was 1.51 (95% CI = 1.22-1.86) times that of those in the CG. BBQ improvement was also mildly associated with race and college education. Sensitivity analyses suggested minimal influence of drop out. In conclusion, soldiers that received the PSEP had an improvement in their beliefs related to the inevitable consequences of and ability to cope with LBP. This is the first randomized trial to show positive influence on LBP beliefs in a primary prevention setting, and these findings have potentially important public health implications for prevention of LBP. [ABSTRACT FROM AUTHOR]

Both the clear effects and minimum aberration criteria are the important rules for the design selection. In this paper, it is proved that some $$2_{IV}^{m - p} $$ designs have weak minimum aberration, by considering the number of clear two-factor interactions in the designs. And some conditions are provided, under which a $$2_{IV}^{m - p} $$ design can have the maximum number of clear two-factor interactions and weak minimum aberration at the same time. Some weak minimum aberration $$2_{IV}^{m - p} $$ designs are provided for illustrations and two nonisomorphic weak minimum aberration $$2_{IV}^{13 - 6} $$ designs are constructed at the end of this paper. [ABSTRACT FROM AUTHOR]

Samples of Li4Ti5O12−y solid solutions are synthesized by one-step solid-state carbothermal reduction reaction using Li2CO3, anatase, and carbon black under a nitrogen atmosphere. The underlying formation mechanism that leads to Li4Ti5O12−y solid solutions is proposed. The formation mechanism of the Li4Ti5O12−y solid solution is investigated by in situ variable temperature X-Ray diffraction (VT-XRD) and thermogravimetric analysis/differential scanning calorimetry (TGA-DSC). First, some Ti4+ centers are converted to Ti3+ (TiO2-TiO2−x) because of the presence of carbon black. Secondly, Li2CO3 reacts with TiO2−x (anatase) to form Li2TiO3. Thirdly, Li2TiO3 reacts with TiO2−x to form the Li4Ti5O12−y solid solution, while anatase starts to transform into rutile at the same time. Rutile reacts with Li2TiO3 to form Li4Ti5O12−y at higher temperatures. The presence of Ti3+ not only improves the electrical conductivity but also improves the ionic conductivity. As a result, the as-prepared material exhibits good rate capability and cycling stability with 99.3% capacity retention after 200 cycles. [ABSTRACT FROM AUTHOR]

Plant height (PH) is a key factor in maize (Zea mays L.) yield, biomass, and plant architecture. We investigated the PH of diverse maize inbred lines (117 temperate lines, 135 tropical lines) at four growth stages using unmanned aerial vehicle high-throughput phenotypic platforms (UAV-HTPPs). We extracted PH data using an automated pipeline based on crop surface models and orthomosaic model. The correlation between UAV and manually measured PH data reached 0.95. Under temperate field conditions, temperate maize lines grew faster than tropical maize lines at early growth stages, but tropical lines grew faster at later growth stages and ultimately became taller than temperate lines. A genome-wide association study identified 68 unique quantitative trait loci (QTLs) for seven PH-related traits, and 35% of the QTLs coincided with those previously reported to control PH. Generally, different QTLs controlled PH at different growth stages, but eight QTLs simultaneously controlled PH and growth rate at multiple growth stages. Based on gene annotations and expression profiles, we identified candidate genes controlling PH. The PH data collected by the UAV-HTPPs were credible and the genetic mapping power was high. Therefore, UAV-HTPPs have great potential for use in studies on PH. [ABSTRACT FROM AUTHOR]

In order to solve the problem of plasticizers limited in alpine regions, in this paper, 1,6-hexanediol oleate (HD) was synthesized by a simple synthetic method using oleic acid and 1.6-hexanediol, and its epoxidation reaction was utilized to prepare a cold-resistant plasticizer (epoxidized 1,6-hexanediol oleate (EHD)) with excellent performances, which was structurally characterized by using Fourier transform infrared spectroscopy and 1HNMR. The properties of HD and EHD plasticized polyvinyl chloride (PVC) were tested and compared with dioctyl adipate (DOA). The results showed that the elongation at break, migration resistance and UV resistance of HD plasticized PVC films were slightly lower than those of DOA plasticized PVC films, but the temperature was 24.4 °C higher than that of DOA at 25% loss of mass, and the thermal stability was better; the epoxidized EHD plasticized PVC films showed 48.78% higher mechanical properties, 11.4 °C higher thermal stability at 25% loss of mass, higher migration resistance, compared with the DOA plasticized PVC films. The mechanical properties were 48.78% higher than those of DOA plasticized PVC films, the migration resistance was more stable in petroleum ether and anhydrous ethanol, and the UV resistance was better than that of DOA plasticized PVC films. Molecular dynamics simulations further verified the migration resistance of EHD/PVC in different solvents. In conclusion, EHD is suitable for low-temperature environments with excellent cold resistance, migration resistance and good stability. [ABSTRACT FROM AUTHOR]