liang wang

liang wang


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 February 2020 in Processes
Verified
Journal Article
Open access
PDF file
BYBi Yangang
Bi Yangang
ZTZhi Tan
Zhi Tan
LWliang wang
liang wang
WLWusong Li
Wusong Li
CLCongcong Liu
Congcong Liu
XJXinru Jia
Xinru Jia
Polymer flooding emulsions and microemulsions caused by tertiary oil recovery technologies are harmful to the environment due to their excellent stability. Two cationic hyperbranched polyamidoamines (H-PAMAM), named as H-PAMAM-HA and H-PAMAM-ETA, were obtained by changing the terminal denotation agents to H-PAMAM, which was characterized by 1H NMR, FT-IR, and amine possession, thereby confirmed the modification. Samples (300 mg/L) were added to the polymer flooding emulsion (1500 mg/L oil concentration) at 30 °C for 30 min and the H-PAMAM-HA and H-PAMAM-ETA were shown to perform at 88% and 91% deoil efficiency. Additionally, the increased settling time and the raised temperature enhanced performance. For example, an oil removal ratio of 97.7% was observed after dealing with the emulsion for 30 min at 60 °C, while 98.5% deoil efficiency was obtained after 90 min at 45 °C for the 300 mg/L H-PAMAM-ETA. To determine the differences when dealing with the emulsion, the interfacial tension, ζ potential, and turbidity measurements were fully estimated. Moreover, diametrically different demulsification mechanisms were found when the samples were utilized to treat the microemulsion. The modified demulsifiers showed excellent demulsification efficiency via their obvious electroneutralization and bridge functions, while the H-PAMAM appeared to enhance the stability of the microemulsion.

1 January 2020 in Ciência Rural
Verified
Journal Article
Open access
PDF file
XYXu Yanlin
Xu Yanlin
LZLi Zijun
Li Zijun
LWliang wang
liang wang
Based on the panel data of 134 counties (cities and districts) from 1998 to 2017, the temporal-spatial variation characteristics and influencing factors of agricultural eco-efficiency in Shandong Province were analyzed by using various methods, such as the super-efficiency SBM (slacks-based measure) model considering undesired output and the STIRPAT (stochastic impacts by regression on population, affluence, and technology) model, which helps clarify the improvements needed for agricultural eco-efficiency and provides a basis for the development of ecological agriculture in Shandong Province. Results showed the following: (1) During 1998-2017, the agricultural eco-efficiency of Shandong Province showed a fluctuating increasing tendency, but the overall efficiency value wasrelatively low. (2) The agricultural eco-efficiency of Shandong Province had a significant regional disparity, and its spatial agglomeration gradually weakened. The spatial distribution had a sporadic distribution of high value areas at first and then gradually formed the “low-high-low-high” zonal distribution from west to east. (3) The net income per capita of farmers and the added value of the primary industry had a significantly positive correlation with the agricultural eco-efficiency of Shandong Province, while the mechanization level, the planting area per capita, the level of financial support to agriculture and the planting structure exhibited a mainly negative correlation with the agricultural eco-efficiency of Shandong Province. Moreover, the added value of the primary industry and the financial support to agriculture in the 0.75 quantile had no significant influence on the agricultural eco-efficiency of Shandong Province, and the planting structure in the 0.25 and 0.75 quantiles also had no significant influence.

30 April 2024 in Plants
Verified
Journal Article
Open access
PDF file
KXKunlun Xiang
Kunlun Xiang
QGQian Guo
Qian Guo
BZBeibei Zhang
Beibei Zhang
JWJiaming Wang
Jiaming Wang
NJNing Jin
Ning Jin
Jie ZhaoJie Zhao
Jie Zhao
During the period preceding the vegetation growing season (GS), temperature emerges as the pivotal factor determining phenology in northern terrestrial ecosystems. Despite extensive research on the impact of daily mean temperature (Tmean) during the preseason period, the influence of diurnal temperature range (DTR) on vegetation photosynthetic phenology (i.e., the impact of the plant photosynthetic cycle on seasonal time scale) has largely been neglected. Using a long-term vegetation photosynthetic phenology dataset and historical climate data, we examine vegetation photosynthetic phenology dynamics and responses to climate change across the mid–high latitudes of the Northern Hemisphere from 2001 to 2020. Our data reveal an advancing trend in the start of the GS (SOS) by −0.15 days per year (days yr−1), affecting 72.1% of the studied area. This is particularly pronounced in western Canada, Alaska, eastern Asia, and latitudes north of 60°N. Conversely, the end of the GS (EOS) displays a delaying trend of 0.17 days yr−1, impacting 62.4% of the studied area, especially northern North America and northern Eurasia. The collective influence of an earlier SOS and a delayed EOS has resulted in the notably prolonged length of the GS (LOS) by 0.32 days yr−1 in the last two decades, affecting 70.9% of the studied area, with Eurasia and western North America being particularly noteworthy. Partial correlation coefficients of the SOS with preseason Tmean, DTR, and accumulated precipitation exhibited negative values in 98.4%, 93.0%, and 39.2% of the study area, respectively. However, there were distinct regional variations in the influence of climate factors on the EOS. The partial correlation coefficients of the EOS with preseason Tmean, DTR, and precipitation were positive in 58.6%, 50.1%, and 36.3% of the region, respectively. Our findings unveil the intricate mechanisms influencing vegetation photosynthetic phenology, holding crucial significance in understanding the dynamics of carbon sequestration within terrestrial ecosystems amidst climate change.

15 January 2024 in Plants
Verified
Journal Article
Open access
PDF file
XQXin Qi
Xin Qi
SLShuhua Liu
Shuhua Liu
SWShaoan Wu
Shaoan Wu
JWJian Wang
Jian Wang
JWJiaming Wang
Jiaming Wang
Jie ZhaoJie Zhao
Jie Zhao
The vegetation ecosystem in the southern hilly region of China (SHRC) plays a crucial role in the country’s carbon reservoir. Clarifying the dynamics of net primary productivity (NPP) in this area and its response to climate factors in the context of climate change is important for national forest ecology, management, and carbon neutrality efforts. This study, based on remote sensing and meteorological data spanning the period 2001 to 2021, aims to unveil the spatiotemporal patterns of vegetation productivity and climate factors in the southern hilly region, explore interannual variation characteristics of vegetation productivity with altitude, and investigate the response characteristics of NPP to various climate factors. The results indicate that from 2001 to 2021, the annual average NPP in the southern hilly region had a significant increasing trend of 2.13 ± 0.78 g m−2 a−1. The trend of NPP varies significantly with altitude. Despite a general substantial upward trend in vegetation NPP, regions at lower elevations exhibit a faster rate of increase, suggesting a diminishing difference in the NPP of different elevation ranges. The overall rise in average temperature has positive implications for the southern hilly region, while the impact of precipitation on vegetation NPP demonstrates noticeable spatial heterogeneity. Regions in which vegetation NPP is significantly negatively correlated with precipitation are mainly concentrated in the southern areas of Guangdong, Fujian, and Jiangxi provinces. In contrast, other regions further away from the southeastern coast tend to exhibit a positive correlation. Over the past two decades, there has been an asymmetry in the diurnal temperature variation in the SHRC, with the nighttime warming rate being 1.8 times that of the daytime warming rate. The positive impact of daytime warming on NPP of vegetation is more pronounced than the impact of nighttime temperature changes. Understanding the spatiotemporal patterns of NPP in the SHRC and the characteristics of its response to climate factors contributes to enhancing our ability to protect and manage vegetation resources amidst the challenges of global climate change.

YYyuanhe yu
yuanhe yu
LWliang wang
liang wang
JLJinkuo Lin
Jinkuo Lin
Zijun LiZijun Li
Zijun Li
Using typical counties in the Yimeng Mountain area of northern China as an example, this paper analyzed the household and agricultural input characteristics of different types of peasant households using survey data from 262 farm households. The target minimization of the total absolute deviations (MOTAD) model was applied to determine the optimal combinations in the allocation of agricultural input factors and production for different types of at-risk peasant households to obtain the ideal agricultural income. The relevant results are twofold. (1) The agricultural input behaviors of different types of peasant households vary significantly. The highest levels of agricultural land, labor, and yield-increasing and labor-saving inputs included I part-time peasant households (I PTPH), followed by full-time peasant households (FTPH), while the input levels of II part-time peasant households (II PTPH) and non-agricultural peasant households (NAPH) with higher levels of non-agricultural employment gradually decreased. In general, an increase in peasant households’ part-time employment revealed an inverted U-shaped trend in the agricultural input level, with a trajectory of I PTPH > FTPH > II PTPH > NAPH. (2) The current agricultural inputs and production combinations of different types of peasant households have room for improvement. It is necessary to adjust agricultural inputs and optimize production combinations to obtain target incomes. Overall, all types of peasant households must streamline labor inputs and increase capital inputs, except for I PTPH, for which capital inputs should be reduced. Following optimization, economic crops gradually replace grain crops, and the optimal agricultural incomes of peasant households will be improved. The study results provide practical policy insights for reducing agricultural production risks and improving agricultural production incomes.

25 October 2024 in Plants
Verified
Journal Article
Open access
PDF file
JLJinyue Liu
Jinyue Liu
Jie ZhaoJie Zhao
Jie Zhao
JHJunhao He
Junhao He
PZPengyi Zhang
Pengyi Zhang
FYFan Yi
Fan Yi
Zhenhong HuZhenhong Hu
Zhenhong Hu
Eurasian dryland ecosystems consist mainly of cropland and grassland, and their changes are driven by both natural factors and human activities. This study utilized the normalized difference vegetation index (NDVI), gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) to analyze the changing characteristics of vegetation activity in Eurasia over the past two decades. Additionally, we integrated the mean annual temperature (MAT), the mean annual precipitation (MAP), the soil moisture (SM), the vapor pressure deficit (VPD) and the terrestrial water storage (TWS) to analyze natural factors’ influence on the vegetation activity from 2003 to 2022. Through partial correlation and residual analysis, we quantitatively described the contributions of both natural and human factors to changes in vegetation activity. The results indicated an overall increasing trend in vegetation activity in Eurasia; the growth rates of vegetation greenness, productivity and photosynthetic capacity were 1.00 × 10−3 yr−1 (p < 0.01), 1.30 g C m−2 yr−2 (p < 0.01) and 1.00 × 10−3 Wm−2μm−1sr−1yr−1 (p < 0.01), respectively. Furthermore, we found that soil moisture was the most important natural factor influencing vegetation activity. Human activities were identified as the main driving factors of vegetation activity in the Eurasian drylands. The relative contributions of human-induced changes to NDVI, GPP and SIF were 52.45%, 55.81% and 74.18%, respectively. These findings can deepen our understanding of the impacts of current natural change and intensified human activities on dryland vegetation coverage change in Eurasia.