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Ecosystem disservices (EDS) is an important form of social-ecological interactions and can strongly influence people’s perception of nature. However, compare to ecosystem services (ES), current studies on EDS are still very limited especially from the perspective of classification and valuation. Here, we firstly proposed a function-based classification system to better explain the general effects of EDS. Then, we used Beijing, the capital of China, as a case study to value three common urban EDS (excessive decrease in water quantity, plant-related diseases and infrastructure damage) there. The results suggested that the total EDS value of Beijing was approximately 10.54 billion RMB/year in 2019, which equaled about 5.13% of the total value of five important ecosystem services (food and raw material production, climate regulation, environmental quality regulation, soil retention and ecotourism). The finding showed that although EDS caused considerable financial loss, the potential economic gains from ecosystem services could still greatly outweigh the loss and therefore supported the current urban greening expansion policy in Beijing. Our study attempted to promote the bridging of ecosystem services and disservices studies and call for more equal consideration of both ES and EDS to create more compressive and sustainable planning.
Shuyao Wu; Binbin V. Li; Shuangcheng Li. Classifying ecosystem disservices and valuating their effects - a case study of Beijing, China. Ecological Indicators 2021, 129, 107977 .
AMA StyleShuyao Wu, Binbin V. Li, Shuangcheng Li. Classifying ecosystem disservices and valuating their effects - a case study of Beijing, China. Ecological Indicators. 2021; 129 ():107977.
Chicago/Turabian StyleShuyao Wu; Binbin V. Li; Shuangcheng Li. 2021. "Classifying ecosystem disservices and valuating their effects - a case study of Beijing, China." Ecological Indicators 129, no. : 107977.
An increasing number of studies have linked ambient air pollution to chronic kidney disease (CKD) prevalence. However, its potential effect modification by urbanization has not been investigated. Based on data of 47,204 adults from the China National Survey of Chronic Kidney Disease (CKSCKD) dataset, night light satellite remote sensing data and high-resolution air pollution inversion products, the present cross-sectional study investigated the association between fine particulate matter <2.5 mm in diameter (PM2.5), nitrogen dioxide (NO2), night light index (NLI) and CKD prevalence in China, and the effect modification by urbanization characterized by administrative classification and NLI on the pollutant-health associations. Our results showed that a 10-μg/m3 increase in PM2.5 at 3-year moving average, a 10-μg/m3 increase in NO2 at 5-year moving average, and a 10-U increase in NLI at 5-year moving average were significantly associated with increased odds of CKD prevalence [OR = 1.24 (95 %CI:1.14, 1.35); OR = 1.12 (95 %CI:1.09, 1.15); OR = 1.05 (95 %CI:1.02, 1.07)]. Meanwhile, the pollutant-health associations were more apparent in medium-urbanized areas compared to low- and high-urbanized areas. For instance, a 10-μg/m3 increase in PM2.5 concentration at 2-year moving average was associated with increased odds of CKD in the areas with NLI level in the second [OR = 2.78 (95 %CI:1.77, 4.36)] and third quartiles [OR = 1.49 (95 %CI:1.14, 1.95)], compared to the lowest [OR = 0.96 (95% CI: 0.73, 1.26)] and highest [OR = 0.63 (95% CI: 0.39–1.02)] quartiles. PM2.5 and NO2 were associated with increased odds of CKD prevalence, especially in areas with medium NLI levels, suggesting the necessity of strengthening environmental management in medium-urbanized regions.
Ze Liang; Wanzhou Wang; Yueyao Wang; Lin Ma; Chenyu Liang; Pengfei Li; Chao Yang; Feili Wei; Shuangcheng Li; Luxia Zhang. Urbanization, ambient air pollution, and prevalence of chronic kidney disease: A nationwide cross-sectional study. Environment International 2021, 156, 106752 .
AMA StyleZe Liang, Wanzhou Wang, Yueyao Wang, Lin Ma, Chenyu Liang, Pengfei Li, Chao Yang, Feili Wei, Shuangcheng Li, Luxia Zhang. Urbanization, ambient air pollution, and prevalence of chronic kidney disease: A nationwide cross-sectional study. Environment International. 2021; 156 ():106752.
Chicago/Turabian StyleZe Liang; Wanzhou Wang; Yueyao Wang; Lin Ma; Chenyu Liang; Pengfei Li; Chao Yang; Feili Wei; Shuangcheng Li; Luxia Zhang. 2021. "Urbanization, ambient air pollution, and prevalence of chronic kidney disease: A nationwide cross-sectional study." Environment International 156, no. : 106752.
Deteriorating air quality is one of the most important environmental factors posing significant health risks to urban dwellers. Therefore, an exploration of the factors influencing air pollution and the formulation of targeted policies to address this issue are critically needed. Although many studies have used semi-parametric geographically weighted regression and geographically weighted regression to study the spatial heterogeneity characteristics of influencing factors of PM2.5 concentration change, due to the fixed bandwidth of these methods and other reasons, those studies still lack the ability to describe and explain cross-scale dynamics. The multi-scale geographically weighted regression (MGWR) method allows different variables to have different bandwidths, which can produce more realistic and useful spatial process models. By applying the MGWR method, this study investigated the spatial heterogeneity and spatial scales of impact of factors influencing PM2.5 concentrations in major Chinese cities during the period 2005–2015. This study showed the following: (1) Factors influencing changes in PM2.5 concentrations, such as technology, foreign investment levels, wind speed, precipitation, and Normalized Difference Vegetation Index (NDVI), evidenced significant spatial heterogeneity. Of these factors, precipitation, NDVI, and wind speed had small-scale regional effects, whose bandwidth ratios are all less than 20%, while foreign investment levels and technologies had medium-scale regional effects, whose bandwidth levels are 23% and 32%, respectively. Population, urbanization rates, and industrial structure demonstrated weak spatial heterogeneity, and the scale of their influence was predominantly global. (2) Overall, the change of NDVI was the most influential factor, which can explain 15.3% of the PM2.5 concentration change. Therefore, an enhanced protection of urban surface vegetation would be of universal significance. In some typical areas, dominant factors influencing pollution were evidently heterogeneous. Change in wind speed is a major factor that can explain 51.6% of the change in PM2.5 concentration in cities in the Central Plains, and change in foreign investment levels is the dominant influencing factor in cities in the Yunnan-Guizhou Plateau and the Sichuan Basin, explaining 30.6% and 44.2% of the PM2.5 concentration change, respectively. In cities located within the lower reaches of the Yangtze River, NDVI is a key factor, reducing PM2.5 concentrations by 9.7%. Those results can facilitate the development of region-specific measures and tailored urban policies to reduce PM2.5 pollution levels in different regions such as Northeast China and the Sichuan Basin.
Feili Wei; Shuang Li; Ze Liang; Aiqiong Huang; Zheng Wang; Jiashu Shen; Fuyue Sun; Yueyao Wang; Huan Wang; Shuangcheng Li. Analysis of Spatial Heterogeneity and the Scale of the Impact of Changes in PM2.5 Concentrations in Major Chinese Cities between 2005 and 2015. Energies 2021, 14, 3232 .
AMA StyleFeili Wei, Shuang Li, Ze Liang, Aiqiong Huang, Zheng Wang, Jiashu Shen, Fuyue Sun, Yueyao Wang, Huan Wang, Shuangcheng Li. Analysis of Spatial Heterogeneity and the Scale of the Impact of Changes in PM2.5 Concentrations in Major Chinese Cities between 2005 and 2015. Energies. 2021; 14 (11):3232.
Chicago/Turabian StyleFeili Wei; Shuang Li; Ze Liang; Aiqiong Huang; Zheng Wang; Jiashu Shen; Fuyue Sun; Yueyao Wang; Huan Wang; Shuangcheng Li. 2021. "Analysis of Spatial Heterogeneity and the Scale of the Impact of Changes in PM2.5 Concentrations in Major Chinese Cities between 2005 and 2015." Energies 14, no. 11: 3232.
Analysis focused on sub-regional differentiation of vegetation greenness and their dominant drivers are needed to properly develop targeted strategies for sustainable management. In this study, we took China as a case study area, and analyzed the spatiotemporal heterogeneity of vegetation greenness and its strength of association with both environmental (topographical factors and hydrothermal conditions) and anthropogenic factors (land use type and population density) across six eco-geographic regions during 1982–2015. The whole period was divided into two periods by the turning point of 1998, after which China has implemented numerous forest protection projects. The attribution results based on the Geodetector method show the followings: (1) In China, precipitation is the dominant factor in landscape variation of Normalized Difference Vegetation Index (NDVI) with a strength of association of 85%. Additionally, precipitation is also the dominant factor in arid and semi-arid regions, including Northern semiarid (NS) region, Northwestern arid (NWA) region and Qinghai-Tibet Plateau (QTP) region. The dominant factors differ across diverse eco-geographic regions; for example, slope dominates in sub-tropical/tropical humid (STH) and middle temperate humid/sub-humid (MTH) regions. (2) Generally, the strength of association between vegetation and temperature decreases across China over the past 34 years, meaning that the limiting effect of temperature on the NDVI is weakened, similarly, the controlling effect of water conditions is also weakened. In contrast, the spatial association between anthropogenic factors and NDVI is enhanced. (3) The temporal dynamics of strength of association between factors and the NDVI differ in diverse periods and regions; for example, the strength of association between wind speed and NDVI decreased during 1982–1998, but increased during 1999–2015 in temperate humid/sub-humid (WTH) region; however, decreasing trends were revealed in the QTP region in both periods. Our study highlights that variation of NDVI is mainly attributed to climate change and land cover change. Generally, the limiting impact of hydrothermal conditions on NDVI weakens, and the controlling effect of human activity increases over time.
Huan Wang; Shijie Yan; Ze Liang; Kewei Jiao; Delong Li; Feili Wei; Shuangcheng Li. Strength of association between vegetation greenness and its drivers across China between 1982 and 2015: Regional differences and temporal variations. Ecological Indicators 2021, 128, 107831 .
AMA StyleHuan Wang, Shijie Yan, Ze Liang, Kewei Jiao, Delong Li, Feili Wei, Shuangcheng Li. Strength of association between vegetation greenness and its drivers across China between 1982 and 2015: Regional differences and temporal variations. Ecological Indicators. 2021; 128 ():107831.
Chicago/Turabian StyleHuan Wang; Shijie Yan; Ze Liang; Kewei Jiao; Delong Li; Feili Wei; Shuangcheng Li. 2021. "Strength of association between vegetation greenness and its drivers across China between 1982 and 2015: Regional differences and temporal variations." Ecological Indicators 128, no. : 107831.
The impact of extreme climate on natural ecosystems and socioeconomic systems is more serious than that of the climate’s mean state. Based on the data of 1698 meteorological stations in China from 2001 to 2018, this study calculated the 27 extreme climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). Through correlation analysis and collinearity diagnostics, we selected two representative extreme temperature indices and three extreme precipitation indices. The spatial scale of the impact of extreme climate on Normalized Difference Vegetation Index (NDVI) in China during the growing season from 2001 to 2018 was quantitatively analyzed, and the complexity of the dominant factors in different regions was discussed via clustering analysis. The research results show that extreme climate indices have a scale effect on vegetation. There are spatial heterogeneities in the impacts of different extreme climate indices on vegetation, and these impacts varied between the local, regional and national scales. The relationship between the maximum length of a dry spell (CDD) and NDVI was the most spatially nonstationary, and mostly occurred on the local scale, while the effect of annual total precipitation when the daily precipitation amount was more than the 95th percentile (R95pTOT) showed the greatest spatial stability, and mainly manifested at the national scale. Under the current extreme climate conditions, extreme precipitation promotes vegetation growth, while the influence of extreme temperature is more complicated. As regards intensity and range, the impact of extreme climate on NDVI in China over the past 18 years can be categorized into five types: the humidity-promoting type, the cold-promoting and drought-inhibiting compound type, the drought-inhibiting type, the heat-promoting and drought-inhibiting compound type, and the heat-promoting and humidity-promoting compound type. Drought is the greatest threat to vegetation associated with extreme climate in China.
Shuang Li; Feili Wei; Zheng Wang; Jiashu Shen; Ze Liang; Huan Wang; Shuangcheng Li. Spatial Heterogeneity and Complexity of the Impact of Extreme Climate on Vegetation in China. Sustainability 2021, 13, 5748 .
AMA StyleShuang Li, Feili Wei, Zheng Wang, Jiashu Shen, Ze Liang, Huan Wang, Shuangcheng Li. Spatial Heterogeneity and Complexity of the Impact of Extreme Climate on Vegetation in China. Sustainability. 2021; 13 (10):5748.
Chicago/Turabian StyleShuang Li; Feili Wei; Zheng Wang; Jiashu Shen; Ze Liang; Huan Wang; Shuangcheng Li. 2021. "Spatial Heterogeneity and Complexity of the Impact of Extreme Climate on Vegetation in China." Sustainability 13, no. 10: 5748.
Urban form studies on urban heat island (UHI) are mostly from the microscale perspective of thermodynamics or fluid mechanics, lacking of consideration of the impact of urban form on traffic behavior or air pollution, which is also proved to be influential on nighttime urban thermal environment. The objective of this paper is to quantitatively reveal the mediating role of air pollution in the impacts of urban form on nighttime UHI intensity based upon an empirical research of 150 cities of China. We constructed multivariate regression models, structural equation models and scenario simulations to verify and predict the mediating effect of air pollution. Results showed that the fractal dimension of urban planar shape almost all influences UHI intensity through air pollution. The mediating effect related to urban continuity and urban elongation also accounts for 25-28% and 33-40% of the total effect, respectively. Controlling urban population density can play an important role on UHI mitigation, but optimization of urban geometry can bring co-benefits on urban air and thermal environments. For the purpose of improving urban thermal environment, we advocate the proper elongation and decentralization of urban form, and control urban sprawl disorderly, especially in cities with severe air pollution.
Ze Liang; Jiao Huang; Yueyao Wang; Feili Wei; Shuyao Wu; Hong Jiang; Xuliang Zhang; Shuangcheng Li. The Mediating Effect of Air Pollution in the Impacts of Urban Form on Nighttime Urban Heat Island Intensity. Sustainable Cities and Society 2021, 102985 .
AMA StyleZe Liang, Jiao Huang, Yueyao Wang, Feili Wei, Shuyao Wu, Hong Jiang, Xuliang Zhang, Shuangcheng Li. The Mediating Effect of Air Pollution in the Impacts of Urban Form on Nighttime Urban Heat Island Intensity. Sustainable Cities and Society. 2021; ():102985.
Chicago/Turabian StyleZe Liang; Jiao Huang; Yueyao Wang; Feili Wei; Shuyao Wu; Hong Jiang; Xuliang Zhang; Shuangcheng Li. 2021. "The Mediating Effect of Air Pollution in the Impacts of Urban Form on Nighttime Urban Heat Island Intensity." Sustainable Cities and Society , no. : 102985.
Based on the indicators of more than 3000 cities in China, this study shows that the relationship between the urban form and surface urban heat island intensity (SUHII) demonstrates seasonal and diurnal variations, and also changes along urban development and elevation gradients. SUHIIs show seasonal and diurnal change patterns along urban development and elevation gradients, but there is no obvious change trend along temperature and humidity gradients. Among them, the seasonal variation of the SUHII went up about 0.4 ℃ from the first level of urban development to the highest level, while the diurnal variation of the SUHII decreased by 0.4 °C. With urban development, the correlations between the anthropogenic heat flux (AHF), population density (POPDEN) and morphological continuity (CONTIG) with the SUHII of summer days, summer nights and winter nights continued to be enhanced, with the correlation coefficients (β) increased by about 0.3. The effect of area size (AREA) became more influential on the SUHII of summer days and nights, but its effect on the SUHII of winter nights increased first and then decreased along the urban development gradient. With the increase of elevation, the correlations of the AHF, POPDEN, AREA, CONTIG and summer day and night SUHII were gradually reduced (β decreased by about 0.4), but their impact on the SUHII of winter nights was gradually enhanced (β increased by about 0.2 to 0.3). Along temperature and humidity gradients, the positive effect of POPDEN on the summer SUHII decreased gradually (β decreased by about 0.3). However, the enhancement effects of the AHF, AREA, CONTIG and POPDEN on the SUHII of winter nights increased generally (β increased by about 0.2). According to the Random Forest model, for the SUHIIs at night, the relative importance (RI) of urban form factors was greater, while for the SUHIIs of daytime, the RIs of natural factors were greater. The contribution of the urban form to the seasonal variation of the SUHII is similar to that of natural factors, but their contribution to diurnal variation is lower. Our results suggest that it is more necessary to control the urban scale, avoid excessive urban agglomeration and reasonably control the anthropogenic heat emission in more developed and low altitude cities to reduce their summer heat exposure.
Lin Ma; Yueyao Wang; Ze Liang; Jiaqi Ding; Jiashu Shen; Feili Wei; Shuangcheng Li. Changing Effect of Urban Form on the Seasonal and Diurnal Variations of Surface Urban Heat Island Intensities (SUHIIs) in More Than 3000 Cities in China. Sustainability 2021, 13, 2877 .
AMA StyleLin Ma, Yueyao Wang, Ze Liang, Jiaqi Ding, Jiashu Shen, Feili Wei, Shuangcheng Li. Changing Effect of Urban Form on the Seasonal and Diurnal Variations of Surface Urban Heat Island Intensities (SUHIIs) in More Than 3000 Cities in China. Sustainability. 2021; 13 (5):2877.
Chicago/Turabian StyleLin Ma; Yueyao Wang; Ze Liang; Jiaqi Ding; Jiashu Shen; Feili Wei; Shuangcheng Li. 2021. "Changing Effect of Urban Form on the Seasonal and Diurnal Variations of Surface Urban Heat Island Intensities (SUHIIs) in More Than 3000 Cities in China." Sustainability 13, no. 5: 2877.
Ecosystem service is widely acknowledged as a mainstream and valuable concept for the sustainability-oriented decision-makings on meeting the fundamental needs for improving human well-being and addressing the critical challenges such as food scarcity, land degradation, climate warming, biodiversity loss, flood risk and population pressure. Different ecosystem services arise through combinations of social-ecological drivers and interact with each other across scales. Essential to design effective policy interventions toward achieving sustainability is clarifying the relationships among ecosystem services and the underlying drivers at different scales. Therefore, this study analysed the spatial patterns and relationships of six ecosystem service supplies and examined their responses to ten social-ecological drivers at three spatial scales in the Beijing-Tianjin-Hebei region in 2015. Our results revealed differences in ecosystem service spatial pattern robustness across scales. The trade-offs and synergies between ecosystem services changed less in direction and more in strength at the three scales. The relationships between the provisioning service and the other ecosystem services were mostly antagonistic, and those between the regulating services and cultural service were predominately synergistic. Different types of ecosystem service bundles comprising different abundances of services were detected, and reconfiguration of ecosystem service bundles occurred as the scale changed. The directions of social-ecological drivers’ impacts varied across ecosystem services, and the magnitudes of social-ecological drivers’ impacts on the services varied at different scales. Across the three spatial scales, the most influential driver of ecosystem services was the normalized difference vegetation index, to which different ecosystem services responded diversely and non-linearly. Our results advocated the multiscale assessment of ecosystem services and social-ecological drivers and emphasized the necessity of embracing scale dependency in the hierarchical governance of ecosystem services.
Jiashu Shen; Shuangcheng Li; Laibao Liu; Ze Liang; Yueyao Wang; Huan Wang; Shuyao Wu. Uncovering the relationships between ecosystem services and social-ecological drivers at different spatial scales in the Beijing-Tianjin-Hebei region. Journal of Cleaner Production 2020, 290, 125193 .
AMA StyleJiashu Shen, Shuangcheng Li, Laibao Liu, Ze Liang, Yueyao Wang, Huan Wang, Shuyao Wu. Uncovering the relationships between ecosystem services and social-ecological drivers at different spatial scales in the Beijing-Tianjin-Hebei region. Journal of Cleaner Production. 2020; 290 ():125193.
Chicago/Turabian StyleJiashu Shen; Shuangcheng Li; Laibao Liu; Ze Liang; Yueyao Wang; Huan Wang; Shuyao Wu. 2020. "Uncovering the relationships between ecosystem services and social-ecological drivers at different spatial scales in the Beijing-Tianjin-Hebei region." Journal of Cleaner Production 290, no. : 125193.
At the city scale, the diurnal and seasonal variations in the relationship between urban form and the urban heat island effect remains poorly understood. To address this deficiency, we conducted an empirical study based on data from 150 cities in the Jing-Jin-Ji region of China from 2000 to 2015. The results derived from multiple regression models show that the effects of urban geometric complexity, elongation, and vegetation on urban heat island effect differ among different seasons and between day and night. The impacts of urban geometric factors and population density in summer, particularly those during the daytime, are significantly larger than those in winter. The influence of urban area and night light intensity is greater in winter than in summer and is greater during the day than at night. The effect of NDVI is greater in summer during the daytime. Urban vegetation is the factor with the greatest relative contribution during the daytime, and urban size is the dominant factor at night. Urban geometry is the secondary dominant factor in summer, although its contribution in winter is small. The relative contribution of urban geometry shows an upward trend at a decadal time scale, while that of vegetation decreases correspondingly. The results provide a valuable reference for top-level sustainable urban planning.
Ze Liang; Yueyao Wang; Jiao Huang; Feili Wei; Shuyao Wu; Jiashu Shen; Fuyue Sun; Shuangcheng Li. Seasonal and Diurnal Variations in the Relationships between Urban Form and the Urban Heat Island Effect. Energies 2020, 13, 5909 .
AMA StyleZe Liang, Yueyao Wang, Jiao Huang, Feili Wei, Shuyao Wu, Jiashu Shen, Fuyue Sun, Shuangcheng Li. Seasonal and Diurnal Variations in the Relationships between Urban Form and the Urban Heat Island Effect. Energies. 2020; 13 (22):5909.
Chicago/Turabian StyleZe Liang; Yueyao Wang; Jiao Huang; Feili Wei; Shuyao Wu; Jiashu Shen; Fuyue Sun; Shuangcheng Li. 2020. "Seasonal and Diurnal Variations in the Relationships between Urban Form and the Urban Heat Island Effect." Energies 13, no. 22: 5909.
Ecosystem services (ESs), as important indicators for ecosystem conditions, are always interacted complexly, however, the underlying mechanisms remain not fully understood. The Beijing-Tianjin-Hebei (BTH) region is a typical example of this complexity and is one of the most populous regions globally. In this study, we take the BTH region as the study area and try to identify the spatiotemporally complex relationships and dominant drivers of ESs, by utilizing multiple methods: Pearson correlation analysis, partial correlation analysis and the GeoDetector method. Three critically important ESs: soil erosion, water yield, and net primary production (NPP) are simulated for the period of 2000 to 2018. The results show that the Pearson correlation coefficient indicated a synergistic relationship between soil erosion and water yield and between water yield and NPP and a trade-off relationship between soil erosion and NPP, while the partial correlation analysis using the normalized difference vegetation index (NDVI) and precipitation as controlling factors showed that the relationships between soil erosion and water yield and between water yield and NPP were transformed to trade-offs. We confirmed that the drivers (especially the shared drivers and dominant drivers of each ecosystem service) played important roles in the direction of complex relationships; when different factors were involved in the relationships, the direction of positive or negative relationships may be diverse. Furthermore, the slope (q = 0.32), precipitation (q = 0.42) and NDVI (q = 0.72) were the dominant factors for soil erosion, water yield and NPP, respectively. The power of determinants for ESs showed high spatial heterogeneity in different geomorphological types due to differences in each type of inner characteristic; for example, the q value of slope for soil erosion decreased with increasing mountain relief, but the q value of NDVI increased. In addition, the trade-off degree among the three ESs was spatially heterogeneous; in mountainous areas the trade-off scores were much higher than those in relatively flat areas. Our general approaches and results provide useful references for researchers and policy makers to understand the mechanisms governing complex relationships among ESs and to manage ESs by manipulating these drivers to enhance synergies or weaken trade-offs.
Huan Wang; Laibao Liu; Le Yin; Jiashu Shen; Shuangcheng Li. Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018). Ecological Indicators 2020, 121, 107116 .
AMA StyleHuan Wang, Laibao Liu, Le Yin, Jiashu Shen, Shuangcheng Li. Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018). Ecological Indicators. 2020; 121 ():107116.
Chicago/Turabian StyleHuan Wang; Laibao Liu; Le Yin; Jiashu Shen; Shuangcheng Li. 2020. "Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)." Ecological Indicators 121, no. : 107116.
Urbanization has a significant impact on urban precipitation. Existing studies on precipitation pay more attention to the impact of natural and meteorological factors, and the research on the impact of urbanization on the spatial patterns of precipitation is still very deficient. Based on geographic detection, this study quantitatively analyzed the dominant, interaction, and sensitivity factors that affect precipitation changes in more than 150 urban units in Jing–Jin–Ji (Beijing–Tianjin–Hebei) during the process of urbanization. The research findings show the following: ① The dominant factors have seasonal differences in terms of the precipitation variation in Jing–Jin–Ji. The leading factors in summer were the change of radiation and relative humidity. The dominant factors in winter were the changes in radiation, relative humidity, and wind speed. On the annual scale, the dominant factors were the changes in relative humidity, aerosol optical depth, radiation, and wind speed. ② Whether in summer, in winter, or on the annual scale, urbanization can enhance the explanatory power of spatial variation of urban precipitation through interaction with natural/meteorological factors, and all the dominant interaction factors show a nonlinear enhancement trend. ③ The night light intensity and urban heat island can greatly amplify the explanatory power of other factors, thus becoming the most sensitive factor in urbanization precipitation changes. The above research can provide a theoretical basis for the formulation of urban climate policies and urban planning.
Feili Wei; Ze Liang; Yueyao Wang; Zhibin Huang; Huan Wang; Fuyue Sun; Shuangcheng Li. Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015. Sustainability 2020, 12, 7426 .
AMA StyleFeili Wei, Ze Liang, Yueyao Wang, Zhibin Huang, Huan Wang, Fuyue Sun, Shuangcheng Li. Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015. Sustainability. 2020; 12 (18):7426.
Chicago/Turabian StyleFeili Wei; Ze Liang; Yueyao Wang; Zhibin Huang; Huan Wang; Fuyue Sun; Shuangcheng Li. 2020. "Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015." Sustainability 12, no. 18: 7426.
China has set ambitious goals to cap its carbon emissions and increase low-carbon energy sources to 20% by 2030 or earlier. However, wind and solar energy production can be highly variable: the stability of single wind/solar and hybrid wind-solar energy and the effects of wind/solar ratio and spatial aggregation on energy stability remain largely unknown in China, especially at the grid cell scale. To address these issues, we analyzed the newly 2007–2014 hourly wind and solar data, which have higher resolution and quality than those used in previous research. The stability of single wind/solar energy production clearly increased as the wind/solar energy capacity factor increased, and there were significant functional relationships between single wind/solar energy stability and the wind/solar energy capacity factor. Highly stable wind energy was concentrated in eastern Inner Mongolia, northeastern China, and northern China while highly stable solar energy was concentrated in the Tibetan Plateau, Inner Mongolia, and northwestern China. Different wind/solar ratios affected the stability of hybrid wind-solar energy through a unimodal relationship, allowing us to produce a map of optimal wind/solar ratios throughout China in order to minimize the variability of hybrid wind-solar energy production. At the optimal wind/solar ratio, the most stable hybrid wind-solar energy was concentrated in eastern Inner Mongolia, northeastern China, and northern China. The variability of single and hybrid wind/solar energy decreased as the aggregated area size increased, especially for wind-dominated energy systems. These results have important practical applications: (a) using the optimal wind/solar ratio to install simple hybrid wind-solar energy systems locally; (b) prioritizing the deployment of large-scale wind farms or centralized solar photovoltaic stations in regions with high hybrid energy stability; and (c) strongly promoting regional cooperation, such as breaking inter-provincial power grid barriers, to reduce the variability of hybrid wind-solar energy production and thus operational costs.
Laibao Liu; Zheng Wang; Yang Wang; Jun Wang; Rui Chang; Gang He; Wenjun Tang; Ziqi Gao; Jiangtao Li; Changyi Liu; Lin Zhao; Dahe Qin; Shuangcheng Li. Optimizing wind/solar combinations at finer scales to mitigate renewable energy variability in China. Renewable and Sustainable Energy Reviews 2020, 132, 110151 .
AMA StyleLaibao Liu, Zheng Wang, Yang Wang, Jun Wang, Rui Chang, Gang He, Wenjun Tang, Ziqi Gao, Jiangtao Li, Changyi Liu, Lin Zhao, Dahe Qin, Shuangcheng Li. Optimizing wind/solar combinations at finer scales to mitigate renewable energy variability in China. Renewable and Sustainable Energy Reviews. 2020; 132 ():110151.
Chicago/Turabian StyleLaibao Liu; Zheng Wang; Yang Wang; Jun Wang; Rui Chang; Gang He; Wenjun Tang; Ziqi Gao; Jiangtao Li; Changyi Liu; Lin Zhao; Dahe Qin; Shuangcheng Li. 2020. "Optimizing wind/solar combinations at finer scales to mitigate renewable energy variability in China." Renewable and Sustainable Energy Reviews 132, no. : 110151.
Climate change and urbanization are the two major drivers that can alter vegetation growth processes in the urban environment. However, the effects of these two drivers on the continuous vegetation dynamics in the urban environments are not well understood, especially at a high spatial resolution. This study identified the urban fringe zones and explored the spatiotemporal variations of vegetation dynamics (Normalized Difference Vegetation Index) and the mechanisms underlying these variations in the urban core areas and urban fringe zones of China during 2001–2013. The results suggested that from 2000 to 2013, rapid urbanization regions in Yangtze River Delta experienced a high probability of vegetation degradation. However, some rapid urbanization areas in other parts of China did not undergo such sharp vegetation degradation. We demonstrated that about 63% of the vegetated areas in urban environments showed increasing trends, and the greening trend in the urban core areas was higher than that of urban fringe regions. Furthermore, the relative contributions of climate change, urbanization, and other factors to vegetation variation in the urban area were 33%, 24%, and 43%, respectively. The contribution of urbanization was higher in urban fringe zones than in urban core areas, while the climate change and residual factors were both higher in urban core areas. Our results verified that the urbanization process would not necessarily result in large-scale vegetation degradation. The vegetation in urban environments was mainly determined by climatic variables rather than urbanization. Based on these findings, we propose that the development of fringe areas outside the urban core areas should be avoided as much as possible to effectively mitigate vegetation degradation and the positive influences of urbanization on vegetation growth through effective urban landscape planning should be encouraged.
Delong Li; Shuyao Wu; Ze Liang; Shuangcheng Li. The impacts of urbanization and climate change on urban vegetation dynamics in China. Urban Forestry & Urban Greening 2020, 54, 126764 .
AMA StyleDelong Li, Shuyao Wu, Ze Liang, Shuangcheng Li. The impacts of urbanization and climate change on urban vegetation dynamics in China. Urban Forestry & Urban Greening. 2020; 54 ():126764.
Chicago/Turabian StyleDelong Li; Shuyao Wu; Ze Liang; Shuangcheng Li. 2020. "The impacts of urbanization and climate change on urban vegetation dynamics in China." Urban Forestry & Urban Greening 54, no. : 126764.
There have been debates and a lack of understanding about the complex effects of urban-scale urban form on air pollution. Based on the remotely sensed data of 150 cities in the Beijing-Tianjin-Hebei agglomeration in China from 2000 to 2015, we studied the effects of urban form on fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations from multiple perspectives. The panel models show that the elastic coefficients of aggregation index and fractal dimension are the highest among all factors for the whole region. Population density, aggregation index, and fractal dimension have stronger influences on air pollution in small cities, while area size demonstrates the opposite effect. Population density has a stronger impact on medium/high-elevation cities, while night light intensity (NLI), fractal dimension, and area size show the opposite effect. Low road network density can enlarge the influence magnitude of NLI and population density. The results of the linear regression model with multiplicative interactions provide evidence of interactions between population density and NLI or aggregation index. The slope of the line that captures the relationship between NLI on PM2.5 is positive at low levels of population density, flat at medium levels of population density, and negative at high levels of population density. The study results also show that when increasing the population density, the air pollution in a city with low economic and low morphological aggregation degrees will be impacted more greatly.
Ze Liang; Feili Wei; Yueyao Wang; Jiao Huang; Hong Jiang; Fuyue Sun; Shuangcheng Li. The Context-Dependent Effect of Urban Form on Air Pollution: A Panel Data Analysis. Remote Sensing 2020, 12, 1793 .
AMA StyleZe Liang, Feili Wei, Yueyao Wang, Jiao Huang, Hong Jiang, Fuyue Sun, Shuangcheng Li. The Context-Dependent Effect of Urban Form on Air Pollution: A Panel Data Analysis. Remote Sensing. 2020; 12 (11):1793.
Chicago/Turabian StyleZe Liang; Feili Wei; Yueyao Wang; Jiao Huang; Hong Jiang; Fuyue Sun; Shuangcheng Li. 2020. "The Context-Dependent Effect of Urban Form on Air Pollution: A Panel Data Analysis." Remote Sensing 12, no. 11: 1793.
More than 3000 cities in China were used to study the effect of urbanization and local climate variability on urban vegetation across different geographical and urbanization conditions. The national scale estimation shows that China’s urban vegetation depicts a trend of degradation from 2000 to 2015, especially in developed areas such as the Yangtze River Delta. According to the panel models, the increase of precipitation (PREC), solar radiation (SRAD), air temperature (TEMP), and specific humidity (SHUM) all enhance urban vegetation, while nighttime light intensity (NLI), population density (POPDEN), and fractal dimension (FRAC) do the opposite. The effects change along the East–West gradient; the influences of PREC and SHUM become greater, while those of TEMP, SRAD, NLI, AREA, and FRAC become smaller. PREC, SHUM, and SRAD play the most important roles in Northeast, Central, and North China, respectively. The role of FRAC and NLI in East China is much greater than in other regions. POPDEN remains influential across all altitudes, while FRAC affects only low-altitude cities. NLI plays a greater role in larger cities, while FRAC and POPDEN are the opposite. In cities outside of the five major urban agglomerations, PREC has a great influence while the key factors are more diversified inside.
Ze Liang; Yueyao Wang; Fuyue Sun; Hong Jiang; Jiao Huang; Jiashu Shen; Feili Wei; Shuangcheng Li. Exploring the Combined Effect of Urbanization and Climate Variability on Urban Vegetation: A Multi-Perspective Study Based on More than 3000 Cities in China. Remote Sensing 2020, 12, 1328 .
AMA StyleZe Liang, Yueyao Wang, Fuyue Sun, Hong Jiang, Jiao Huang, Jiashu Shen, Feili Wei, Shuangcheng Li. Exploring the Combined Effect of Urbanization and Climate Variability on Urban Vegetation: A Multi-Perspective Study Based on More than 3000 Cities in China. Remote Sensing. 2020; 12 (8):1328.
Chicago/Turabian StyleZe Liang; Yueyao Wang; Fuyue Sun; Hong Jiang; Jiao Huang; Jiashu Shen; Feili Wei; Shuangcheng Li. 2020. "Exploring the Combined Effect of Urbanization and Climate Variability on Urban Vegetation: A Multi-Perspective Study Based on More than 3000 Cities in China." Remote Sensing 12, no. 8: 1328.
Understanding the relationships among multiple ecosystem services (ESs) is crucial for the sustainability of natural capital and ESs. The objective of this paper was to explore the antagonistic and synergistic relationships among ESs in their respective ESs bundles (ESBs) from the perspectives of heterogeneity and nonlinearity. Six ESs were quantified using different models, and the relationships among ESs were analysed by combining spatial mapping and statistical methods in the Beijing-Tianjin-Hebei (BTH) urban agglomeration. Our results showed that the spatially concordant supply of regulating services and cultural services decreased from northwest to southeast, whereas the delivery of provisioning services exhibited a distinct spatial pattern and decreased from southeast to northwest in the region. Different combinations of ecosystems provided seven types of ESBs with different compositions and quantities of ESs. The trade-offs and synergies among the ESs in the different ESBs had similarities and differences in both the types of ESs and their intensities. The provisioning service was synergistic with the other ESs in some ESBs, and the relationships among the regulating services and among the regulating services and the cultural service could be antagonistic in other ESBs. Within each ESB, the trade-offs and synergies among the bundled ESs showed spatially heterogeneous changes across the simplified landscapes, and the provision of the involved ESs displayed different nonlinear responses along the productivity gradients. There were different all-win and zero-sum exceptions for the trade-offs involving different ESs in each ESB, with the former indicating the possibilities of mitigating trade-offs and the latter demonstrating the detrimental effects of severe trade-offs. According to our findings, we suggested that the features of ES delivery and their relationships should be considered to ensure the effectiveness, efficiency and equity of the spatially targeted management of natural capital and ESs.
Jiashu Shen; Shuangcheng Li; Ze Liang; Laibao Liu; Delong Li; Shuyao Wu. Exploring the heterogeneity and nonlinearity of trade-offs and synergies among ecosystem services bundles in the Beijing-Tianjin-Hebei urban agglomeration. Ecosystem Services 2020, 43, 101103 .
AMA StyleJiashu Shen, Shuangcheng Li, Ze Liang, Laibao Liu, Delong Li, Shuyao Wu. Exploring the heterogeneity and nonlinearity of trade-offs and synergies among ecosystem services bundles in the Beijing-Tianjin-Hebei urban agglomeration. Ecosystem Services. 2020; 43 ():101103.
Chicago/Turabian StyleJiashu Shen; Shuangcheng Li; Ze Liang; Laibao Liu; Delong Li; Shuyao Wu. 2020. "Exploring the heterogeneity and nonlinearity of trade-offs and synergies among ecosystem services bundles in the Beijing-Tianjin-Hebei urban agglomeration." Ecosystem Services 43, no. : 101103.
There is an increasing demand for urban form optimization to mitigate urban heat island (UHI) effect under the background of global climate change and urbanization. However, there is still a lack of understanding about how the relationship between urban form and UHI intensity changes under diverse urbanization contexts. This study aims to show the change patterns of the relationship between urban form and UHI intensity along the urban development gradient based upon the investigation of a total of 150 urban areas in the Jing-Jin-Ji region in China in 2000, 2005, 2010 and 2015. We defined a comprehensive urban development index taking into account the size of urban area, population density and night light intensity to classify the different levels of urban development. A multi-model comparison was carried out to validate the results. We found that the increase in urban continuity, sprawling, scale and density all enhanced UHI effect at the regional scale. However, the relationship between urban form indicators and UHI intensity demonstrated two opposite patterns along the urban development gradient: population density, geometric complexity and continuity, and general vegetation index of a city were found to be increasingly influential, while night light intensity, geometric elongation and forest coverage presented declining influence. Finally, the study obtained an ascending contribution rate curve for urban geometry indicators, a convex curve for urban size indicators and a declining curve for urban vegetation. These changes along the urban development gradient may be closely related to the changes of the microclimate in cities due to land use, social and economic activities in different urban development stages. The findings can contribute to more appropriate and effective urban planning in countries and regions undergoing rapid urbanization as a valuable reference.
Ze Liang; Shuyao Wu; Yueyao Wang; Feili Wei; Jiao Huang; Jiashu Shen; Shuangcheng Li. The relationship between urban form and heat island intensity along the urban development gradients. Science of The Total Environment 2019, 708, 135011 .
AMA StyleZe Liang, Shuyao Wu, Yueyao Wang, Feili Wei, Jiao Huang, Jiashu Shen, Shuangcheng Li. The relationship between urban form and heat island intensity along the urban development gradients. Science of The Total Environment. 2019; 708 ():135011.
Chicago/Turabian StyleZe Liang; Shuyao Wu; Yueyao Wang; Feili Wei; Jiao Huang; Jiashu Shen; Shuangcheng Li. 2019. "The relationship between urban form and heat island intensity along the urban development gradients." Science of The Total Environment 708, no. : 135011.
In northern high-latitude regions, amplified vegetation greening has been observed due to a larger warming rate than the rate at low latitudes. Similarly, on the Tibetan Plateau (TP), the warming rate is larger at high elevation than that at low elevation. Our results show that large discrepancies exist in the trends in the satellite-derived Normalized Difference Vegetation Index (NDVI) during 2000–2012, indicating the importance of using three satellite-derived NDVI datasets (Global Inventory Modeling and Mapping Studies, Moderate Resolution Imaging Spectroradiometer and SPOT) in the evaluation of vegetation activity on the TP. Based on three NDVI datasets, during 2000–2012, rising temperature drove the regional vegetation greening across the TP, but the vegetation greening rate contrasted with that of elevation-dependent warming. Here, with simultaneous use of climate observation data, we found that declining water availability with rising elevation may restrict and offset the positive effect of rising temperature on vegetation greening, resulting in the declining rate of vegetation greening as elevation increases on the TP. Our results highlight the significant influence of precipitation on elevation-dependent changes in vegetation activity in rapidly warming mountain ecosystems.
Laibao Liu; Yang Wang; Zheng Wang; Delong Li; Yatong Zhang; Dahe Qin; Shuangcheng Li. Elevation-dependent decline in vegetation greening rate driven by increasing dryness based on three satellite NDVI datasets on the Tibetan Plateau. Ecological Indicators 2019, 107, 105569 .
AMA StyleLaibao Liu, Yang Wang, Zheng Wang, Delong Li, Yatong Zhang, Dahe Qin, Shuangcheng Li. Elevation-dependent decline in vegetation greening rate driven by increasing dryness based on three satellite NDVI datasets on the Tibetan Plateau. Ecological Indicators. 2019; 107 ():105569.
Chicago/Turabian StyleLaibao Liu; Yang Wang; Zheng Wang; Delong Li; Yatong Zhang; Dahe Qin; Shuangcheng Li. 2019. "Elevation-dependent decline in vegetation greening rate driven by increasing dryness based on three satellite NDVI datasets on the Tibetan Plateau." Ecological Indicators 107, no. : 105569.
Urbanization brings significant changes to the urban food system. There is growing attention to food self-sufficiency in metropolitan areas for the concern of greenhouse gas (GHG) mitigation in food transportation. In China, grain self-sufficiency in metropolitan areas is also an important issue for grain security and involves coordination among contradictory policy goals. Based upon a comprehensive statistical analysis of 70 metropolitan areas in mainland China, we investigated the regional differences in the trends of grain self-sufficiency capacity in these areas from 1990 to 2015. The findings show a trend of decline in 3/4 of metropolitan areas, mainly located in the rapidly urbanizing eastern coastal areas and in the West. The increase of self-sufficiency mainly occurred in the North, in areas either specialized in grain production or originally low in grain self-sufficiency. The enlarging contradiction of decreasing supply and rising demand explained the sharp decrease in self-sufficiency, while the increase in self-sufficiency was due to the increase in supply. Land productivity contributed more significantly than land availability to supply change. There was a tradeoff between urban expansion (rather than economic growth) and grain production in metropolitan areas. Our results provide implications to future research and policy-making for grain production management in China’s metropolitan areas.
Jiao Huang; Ze Liang; Shuyao Wu; Shuangcheng Li. Grain Self-Sufficiency Capacity in China’s Metropolitan Areas under Rapid Urbanization: Trends and Regional Differences from 1990 to 2015. Sustainability 2019, 11, 2468 .
AMA StyleJiao Huang, Ze Liang, Shuyao Wu, Shuangcheng Li. Grain Self-Sufficiency Capacity in China’s Metropolitan Areas under Rapid Urbanization: Trends and Regional Differences from 1990 to 2015. Sustainability. 2019; 11 (9):2468.
Chicago/Turabian StyleJiao Huang; Ze Liang; Shuyao Wu; Shuangcheng Li. 2019. "Grain Self-Sufficiency Capacity in China’s Metropolitan Areas under Rapid Urbanization: Trends and Regional Differences from 1990 to 2015." Sustainability 11, no. 9: 2468.
Mountain ecosystems provide a variety of important ecosystem services (ESs) to humanity; however, the variation in multiple mountain ESs and the trade-off relationships among mountain ESs remain largely unknown. In this study, we took the Taihang Mountains as the study area and used the root mean square error (RMSE) method to quantify the trade-offs among multiple mountain ESs. Our results showed that net primary production (NPP), soil conservation (SC) and habitat quality (HQ) increased significantly with increasing elevation and vegetation cover fraction (VCF), whereas water yield (WY) did not. In addition, the trade-offs among different ES pairs had different sensitivities to changes in elevation, VCF and precipitation. As the elevation and VCF increased, the trade-offs between WY and NPP and WY and HQ increased significantly. As the precipitation increased, the trade-offs between SC and NPP, WY and NPP, HQ and SC, and WY and HQ all decreased significantly. In addition, the trade-offs among these four ESs were lowest in mid-elevation, high-VCF and low-mean annual precipitation (MAP) areas. This study could improve our current understanding of mountain ESs and help ES management for the Taihang Mountains.
Laibao Liu; Zheng Wang; Yang Wang; Yatong Zhang; Jiashu Shen; Dahe Qin; Shuangcheng Li. Trade-off analyses of multiple mountain ecosystem services along elevation, vegetation cover and precipitation gradients: A case study in the Taihang Mountains. Ecological Indicators 2019, 103, 94 -104.
AMA StyleLaibao Liu, Zheng Wang, Yang Wang, Yatong Zhang, Jiashu Shen, Dahe Qin, Shuangcheng Li. Trade-off analyses of multiple mountain ecosystem services along elevation, vegetation cover and precipitation gradients: A case study in the Taihang Mountains. Ecological Indicators. 2019; 103 ():94-104.
Chicago/Turabian StyleLaibao Liu; Zheng Wang; Yang Wang; Yatong Zhang; Jiashu Shen; Dahe Qin; Shuangcheng Li. 2019. "Trade-off analyses of multiple mountain ecosystem services along elevation, vegetation cover and precipitation gradients: A case study in the Taihang Mountains." Ecological Indicators 103, no. : 94-104.