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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.
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.
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.
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.