Showing papers by "Xiaodong Yang published in 2021"

Analysis of the Impacts of Economic Growth Targets and Marketization on Energy Efficiency: Evidence from China

Abstract: OEnergy efficiency is a vital factor to promote sustainable development. In this paper, the directional distance function–global Malmquist–Luenberger model (DDF-GML) is applied to measure the energy efficiency levels of 30 provinces in China from 2000 to 2017. Simultaneously, the impacts of the economic growth targets and marketization on energy efficiency are empirically tested using the generalized system moment estimation (SYS-GMM) and mediation effect model. The statistical results reveal that energy efficiency is on the rise every year as a whole. Mediated by marketization, economic growth targets inhibit energy efficiency by distorting marketization. Moreover, there is significant regional heterogeneity in the impacts of economic growth targets on energy efficiency. The inhibition effect of economic growth targets on energy efficiency in the eastern region is greater than in the central and western regions. The above empirical results are determined to be robust through testing.

Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location.

Abstract: The purpose of this study is to investigate whether the relationship between meteorological factors (i.e., daily maximum temperature, minimum temperature, average temperature, temperature range, relative humidity, average wind speed and total precipitation) and COVID-19 transmission is affected by season and geographical location during the period of community-based pandemic prevention and control. COVID-19 infected case records and meteorological data in four cities (Wuhan, Beijing, Urumqi and Dalian) in China were collected. Then, the best-fitting model of COVID-19 infected cases was selected from four statistic models (Gaussian, logistic, lognormal distribution and allometric models), and the relationship between meteorological factors and COVID-19 infected cases was analyzed using multiple stepwise regression and Pearson correlation. The results showed that the lognormal distribution model was well adapted to describing the change of COVID-19 infected cases compared with other models (R2 > 0.78; p-values < 0.001). Under the condition of implementing community-based pandemic prevention and control, relationship between COVID-19 infected cases and meteorological factors differed among the four cities. Temperature and relative humidity were mainly the driving factors on COVID-19 transmission, but their relations obviously varied with season and geographical location. In summer, the increase in relative humidity and the decrease in maximum temperature facilitate COVID-19 transmission in arid inland cities, while at this point the decrease in relative humidity is good for the spread of COVID-19 in coastal cities. For the humid cities, the reduction of relative humidity and the lowest temperature in the winter promote COVID-19 transmission.

Does Low-Carbon City Pilot Policy Alleviate Urban Haze Pollution? Empirical Evidence from a Quasi-Natural Experiment in China.

Abstract: As a comprehensive environmental regulation, the low-carbon city pilot policy (LCCP) may have an impact on haze pollution. The evaluation of the effectiveness of LCCP on haze pollution is greatly significant for air pollution prevention and control. Taking LCCP as the starting point, in this study we constructed DID, PSM-DID, and intermediary effect models to empirically test the impact and mechanism of LCCP on haze pollution, based on the panel data of 271 cities in China from 2005 to 2018. The findings show that (1) LCCP has significantly reduced the urban haze pollution, and the average annual concentration of PM2.5 in pilot cities decreased by 14.29%. (2) LCCP can inhibit haze pollution by promoting technological innovation, upgrading the industrial structure, and reducing energy consumption. Among these impacts, the effect of technological innovation is the strongest, followed by industrial structure, and energy consumption. (3) LCCP has significantly curbed the haze pollution of non-resource dependent cities, Eastern cities, and large cities, but exerted little impact on resource-dependent cities, Central and Western regions, and small and medium-sized cities. (4) LCCP has a spatial spillover effect. It can inhibit the haze pollution of adjacent cities through demonstration and warning effects. This study enriches the relevant research on LCCP and provides empirical support and policy enlightenment for pollution reduction.

Assessing the Impact of the National Sustainable Development Planning of Resource-Based Cities Policy on Pollution Emission Intensity: Evidence from 270 Prefecture-Level Cities in China

Abstract: The question of how to achieve the sustainable development of resource-based cities has been a major concern for the whole world. In response, the Chinese government has introduced the National Sustainable Development Planning of Resource-Based Cities Policy (SDPRP) to address sustainable development issues in resource-based cities. However, few studies have evaluated the environmental effects of the implementation of the SDPRP. Therefore, difference-in-differences (DID) and mediation effect models were applied to investigate the impact of the SDPRP on pollution emission intensity using balanced panel data for 270 prefecture-level cities in China from 2003 to 2018. The statistical results reveal that the SDPRP significantly reduced pollution emission intensity. Robustness test results showed that the conclusions are robust. Furthermore, the inhibitory effect of the SDPRP on pollution emission intensity increased year after year. We also found that the SDPRP can reduce pollution emission intensity by facilitating technological innovation, accelerating digital transformation, and improving human capital level, in which the role of human capital is stronger, while the role of digital transformation is weaker. The heterogeneity results suggest that compared with mature resource-based cities, the SDPRP had a stronger inhibitory effect on the pollution emission intensity in declining resource-based cities. However, the impact of the SDPRP on pollution emission intensities in growing resource-based cities was significant, while it was not significant in regenerative resource-based cities. Similarly, the SDPRP had a significantly greater inhibitory effect on pollution emission intensity in megacities than in large cities, while it increased the pollution emission intensity in small- and medium-sized cities.

Spatial-Temporal Changes and Driving Force Analysis of Green Space in Coastal Cities of Southeast China over the Past 20 Years

Abstract: The purpose of this study is to reveal the spatial-temporal change and driving factors of green space in coastal cities of southeast China over the past 20 years. A supervised classification method combining support vector machines (SVMs) and visual interpretation was used to extract the green space from Landsat TM/OLI imageries from 2000–2020. The landscape pattern index was used to calculate geospatial information of green space and analyze their spatial-temporal changes. The hierarchical partitioning analysis was then used to determine the influences of anthropogenic and geographic environmental factors on the spatial-temporal changes in green space. The results indicated that the total area of green space remained constant over the past 20 years in coastal cities of southeast China (1% reduction). The spatial change of green space mainly occurred in the area near the ocean and the southern region. 41.37% of forest land was transferred from cultivated land, while 44.56%, 41.83%, 43.20%, 46.31%, 41.98% and 40.20% of shrub land, sparse woodland, other woodland, high-coverage grassland, moderate-coverage grassland and low-coverage grassland were transferred from forest land. The number of patches, patch density, edge density, landscape shape index and Shannon’s diversity index increased from 2000–2015, and then decreased to the minimum in 2020, while largest patch index continued to decline from 2000–2020. The contribution of anthropogenic factors (0.53–0.61) on the spatial-temporal changes of green space continually increased over the past 20 years, which was also higher than geographical environment factors (0.39–0.41). Our study provides a new perspective to distinguish the impact of anthropogenic activities and geographical environmental factors on the change of green space area, thereby providing a theoretical support for the construction and ecological management of green space.

Influence of soil microorganisms and physicochemical properties on plant diversity in an arid desert of Western China

Abstract: Soil microorganisms and physicochemical properties are considered the two most influencing factors for maintaining plant diversity. However, the operational mechanisms and which factor is the most influential manipulator remain poorly understood. In this study, we examine the collaborative influences of soil physicochemical properties (i.e., soil water, soil organic matter (SOM), salinity, total phosphorus and nitrogen, pH, soil bulk density and fine root biomass) and soil microorganisms (fungi and bacteria) on plant diversity across two types of tree patches dominated by big and small trees (big trees: height ≥ 7 m and DBH ≥ 60 cm; small trees: height ≤ 4.5 m and DBH ≤ 20 cm) in an arid desert region. Tree patch is consists of a single tree or group of trees and their accompanying shrubs and herbs. It was hypothesized that soil physicochemical properties and microorganisms affect plant diversity but their influence differ. The results show that plant and soil microbial diversity increased with increasing distances from big trees. SOM, salinity, fine root biomass, soil water, total phosphorus and total nitrogen contents decreased with increasing distance from big trees, while pH and soil bulk density did not change. Plant and soil microbial diversity were higher in areas close to big trees compared with small trees, whereas soil physicochemical properties were opposite. The average contribution of soil physicochemical properties (12.2%–13.5%) to plant diversity was higher than microbial diversity (4.8%– 6.7%). Salinity had the largest negative affect on plant diversity (24.7%–27.4%). This study suggests that soil fungi constrain plant diversity while bacteria improve it in tree patches. Soil physicochemical properties are the most important factor modulating plant diversity in arid desert tree patches.

Spatial non-stationarity effects of driving factors on soil respiration in an arid desert region

Abstract: Soil respiration (Rs) has significant spatial changes in terrestrial ecosystems, especially in arid areas where ecological factors and vegetation distribution have obvious patches. Despite growing interest regarding the variation of Rs and its driving factors, most studies have ignored the spatial heterogeneity in the relationship between Rs and driving factors. Sampling plots (100 m × 100 m) were arranged along a vertical transect from the river including the three habitat types of river bank (RB), transitional zone (TZ), and desert margin (DM) in arid area of northwest China. The Rs, soil microclimate (soil temperature and soil water content), and soil nutrients of different habitats were synchronously monitored. Geostatistics and geographically weighted regression (GWR) methods were used to evaluate the spatial variability of Rs and its relationship with driving factors. The mean value of Rs in RB (0.29 ± 0.25 μmol m−2 s−1) was significantly higher than that in TZ (0.18 ± 0.10 μmol m−2 s−1) and DM (0.12 ± 0.11 μmol m−2 s−1). The degree of spatial dependence of Rs in RB was higher than that in TZ, and the spatial structure of Rs was not detected in DM. The GWR model can clearly reflect significant spatial differences in the effects of driving factors on Rs. Soil microclimate, total nitrogen, and soil pH had a strong influence on the spatial variation of Rs in RB. Soil microclimate, ammonium nitrogen, nitrate nitrogen, available phosphorus, and organic matter had strong effects on the spatial variation of Rs in TZ, and soil microclimate, total phosphorus, and organic matter had stronger effects on the spatial variation of Rs in DM. The results indicate that the GWR model can reveal the complex spatial relationship between Rs and driving factors in detail, and provide a new direction for exploring the spatial heterogeneity of Rs.

Variability in plant trace element uptake across different crops, soil contamination levels and soil properties in the Xinjiang Uygur Autonomous Region of northwest China

Abstract: This study investigated contamination status of eight trace elements (As, Cd, Cr, Hg, Pb, Cu, Zn and Ni) in farmland soils and crops at 535 sites across the Xinjiang Uygur Autonomous Region, Northwest China. Land use types of the sampling sites included vegetable patch, grain field and orchard. Our experimental results indicated all farmland soils were considered as trace element contamination based on the Nemerow comprehensive pollution index (NCPI > 1). However, 91.97% of the crop samples were uncontaminated according to the Chinese Risk Control Standard. Soils from the vegetable patch showed higher pollution level comparison with that from grain field and orchard. Health risks for both non-carcinogenic and carcinogenic risks were calculated through crop ingestion exposure pathway. Grain samples showed highest health risks, followed by melon and fruit, and vegetables. The health risks of crops were mainly driven by Cr and Cd. Crop consumption may pose risks for children but not adults. The source of trace element contamination in the different farmland soils varied and may be attributed to the different agricultural activities. Plant type had a greater influence on the trace element accumulation in crops compared with soil trace element contents and physicochemical properties.

Impacts of socio-economic determinants, spatial distance and climate factors on the confirmed cases and deaths of COVID-19 in China.

Abstract: This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors.

Comparisons of random forest and stochastic gradient treeboost algorithms for mapping soil electrical conductivity with multiple subsets using Landsat OLI and DEM/GIS-based data at a type oasis in Xinjiang, China

Abstract: Accurate assessment of the spatial distribution and severity of soil salinization has long plagued local governments and researchers in the arid parts of Xinjiang Uygur Autonomous Region (XJUAR). T...

Relationship between Soil Fungi and Seedling Density in the Vicinity of Adult Conspecifics in an Arid Desert Forest

Abstract: Research Highlights: 1. Soil fungi have a higher influence on seedling density compared to soil environmental factors; 2. Host-specific pathogens and beneficial fungi affect seeding density via different influencing mechanisms. Background and Objectives: The growth and development of seedlings are the key processes that affect forest regeneration and maintain community dynamics. However, the influencing factors of seedling growth around their adult conspecifics are not clear in arid desert forests. Probing the intrinsic relations among soil fungi, soil environmental factors (pH, water content, salinity, and nutrition), and seedling density will improve our understanding of forest development and provide a theoretical basis for forest management and protection. Materials and Methods: Four experimental plot types, depending on the distance to adult conspecifics, were set in an arid desert forest. Soil environmental factors, the diversity and composition of the soil fungal community, and the seedlings’ density and height were measured in the four experimental plot types, and their mutual relations were analyzed. Results: Seedling density as well as the diversity and composition of the soil fungal community varied significantly among the four plot types (p < 0.05). Soil environmental factors, especially soil salinity, pH, and soil water content, had significant influences on the seedling density and diversity and composition of the soil fungal community. The contribution of soil fungi (72.61%) to the variation in seedling density was much higher than the soil environmental factors (27.39%). The contribution of detrimental fungi to the variation in seedling density was higher than the beneficial fungi. Conclusions: Soil fungi mostly affected the distribution of seedling density in the vicinity of adult conspecifics in an arid desert forest. The distribution of seedling density in the vicinity of adults was mainly influenced by the detrimental fungi, while the adults in the periphery area was mainly influenced by the beneficial fungi.