Spatial Effects Research Articles

Dynamic Evolution of Multi-Scale Ecosystem Services and Their Driving Factors: Rural Planning Analysis and Optimisation

Rural areas provide ecosystem services (ESs) to urban metropolitan regions. These services are threatened by the constant pressure of urbanisation and new interest in rural development. This has heightened the conflict between environmental concerns and developmental needs, thereby presenting significant land management and rural planning challenges. Employing a quantitative measurement and optimisation framework, we investigate six representative ES variables to assess planning strategies that can address this contradiction. We used a suburban rural area around Nanjing, China, as our study area. We collected spatial data from 2005 to 2020 at two scales (village level and 500 m grid) to map ESs, quantify interactions (trade-offs and synergies among ES bundles), and identify the social, ecological, and landscape drivers of rural change. Based on this, rural planning strategies for optimising ESs at different scales have been proposed. Our findings include (1) spatial heterogeneity in the distribution of ESs, (2) the identification of seven synergistic and eight trade-off pairs among ESs, (3) a spatial scale effect in suburban rural areas, and (4) the spatial trade-offs/synergies of ESs exhibiting a ‘Matthew effect’. The identification of key trade-offs and synergistic ES pairs and the categorisation of ES bundles form the basis for a multi-scale hierarchical management approach for ESs in the region. By examining the commonalities and variations in drivers across diverse scales, we established connections and focal points for spatial planning. We use these findings to propose spatial planning and landscape policy recommendations for rural suburban areas on multiple scales. This study aims to provide a comprehensive and detailed spatial optimisation strategy for rural areas that can help contribute to their revitalisation.

Olfactory-trigeminal integration in the primary olfactory cortex.

Humans naturally integrate signals from the olfactory and intranasal trigeminal systems. A tight interplay has been demonstrated between these two systems, and yet the neural circuitry mediating olfactory-trigeminal (OT) integration remains poorly understood. Using functional magnetic resonance imaging (fMRI), combined with psychophysics, this study investigated the neural mechanisms underlying OT integration. Fifteen participants with normal olfactory function performed a localization task with air-puff stimuli, phenylethyl alcohol (PEA; rose odor), or a combination thereof while being scanned. The ability to localize PEA to either nostril was at chance. Yet, its presence significantly improved the localization accuracy of weak, but not strong, air-puffs, when both stimuli were delivered concurrently to the same nostril, but not when different nostrils received the two stimuli. This enhancement in localization accuracy, exemplifying the principles of spatial coincidence and inverse effectiveness in multisensory integration, was associated with multisensory integrative activity in the primary olfactory (POC), orbitofrontal (OFC), superior temporal (STC), inferior parietal (IPC) and cingulate cortices, and in the cerebellum. Multisensory enhancement in most of these regions correlated with behavioral multisensory enhancement, as did increases in connectivity between some of these regions. We interpret these findings as indicating that the POC is part of a distributed brain network mediating integration between the olfactory and trigeminal systems. PRACTITIONER POINTS: Psychophysical and neuroimaging study of olfactory-trigeminal (OT) integration. Behavior, cortical activity, and network connectivity show OT integration. OT integration obeys principles of inverse effectiveness and spatial coincidence. Behavioral and neural measures of OT integration are correlated.

Spatial effects of carbon pricing on transport equity

There is an ongoing process that greenhouse gas emissions of transport will be incorporated in the European Emissions Trading System. The cap-and-trade approach will result in substantial price increases for fossil fuels which will affect affordability of the transport systems. Within this paper the regressive effect on car-owning households is described in different area categories of the urban and rural region in Germany. Equal-per-household redistribution of the carbon revenue could reverse the regressive effect into a progressive effect. However, there is substantial variation within the different economic status groups leaving notable shares of households with a very low economic status without a positive net transfer. This share will be lowest in the metropolises of the urban region and highest in small-sized cities/village areas of the urban and rural region. Particularly in the latter area categories, these households may need temporary mobility allowances due to limited abatement options. Despite the environmental bonus, electric car-owning households still belong to groups of higher economic status, and public transport supply is limited, particularly in the small-sized cities/village areas of the urban and rural region.

The impact of intellectual property demonstration policies on carbon emission efficiency

Confronted with the concurrent challenges of economic advancement and environmental management, this study explores whether implementing Intellectual Property Demonstration Policies (IPDP) can be a covert force in enhancing carbon emission efficiency. Utilizing panel data from 280 prefecture-level cities in China over the period 2007–2019, we employ a quasi-natural experimental design, incorporating multiple-period difference-in-differences models, mediation effect models, and spatial Durbin difference-in-differences models to assess the impacts of IPDP on carbon emission efficiency, its mechanisms of action, and its spatial spillover effects. The regression results of the multi-period difference-in-differences model reveal a statistically significant enhancement in carbon emission efficiency due to IPDP, with an impact coefficient of 0.044. Through heterogeneity tests, it is observed that the influence of IPDP on carbon emission efficiency varies based on regional characteristics, carbon emission levels, and the extent of marketization. The mediation effect model demonstrates that IPDP enhances carbon emission efficiency by fostering green technological innovation and facilitating the transformation of industrial structures. Furthermore, the spatial Durbin difference-in-differences model illustrates that IPDP positively influences the carbon emission efficiency of neighboring regions, indicating favorable spatial spillover effects. Notably, the indirect effect coefficients in the geographical distance matrix, economic distance matrix, and economic-geographical nested matrix are calculated as 0.673, 0.250, and 0.386, respectively. These findings offer compelling theoretical and empirical support for strengthening the intellectual property framework to optimize its environmental impact.

Rational Design of the Spatial Effect in a Fe(II)/α‐Ketoglutarate‐Dependent Dioxygenase Reverses the Regioselectivity of C(sp3)−H Bond Hydroxylation in Aliphatic Amino Acids

AbstractThe hydroxylation of remote C(sp3)−H bonds in aliphatic amino acids yields crucial precursors for the synthesis of high‐value compounds. However, accurate regulation of the regioselectivity of remote C(sp3)−H bonds hydroxylation in aliphatic amino acids continues to be a common challenge in chemosynthesis and biosynthesis. In this study, the Fe(II)/α‐ketoglutarate‐dependent dioxygenase from Bacillus subtilis (BlAH) was mined and found to catalyze hydroxylation at the γ and δ sites of aliphatic amino acids. Crystal structure analysis, molecular dynamics simulations, and quantum chemical calculations revealed that regioselectivity was regulated by the spatial effect of BlAH. Based on these results, the spatial effect of BlAH was reconstructed to stabilize the transition state at the δ site of aliphatic amino acids, thereby successfully reversing the γ site regioselectivity to the δ site. For example, the regioselectivity of L‐Homoleucine (5 a) was reversed from the γ site (1 : 12) to the δ site (>99 : 1). The present study not only expands the toolbox of biocatalysts for the regioselective functionalization of remote C(sp3)−H bonds, but also provides a theoretical guidance for the precision‐driven modification of similarly remote C(sp3)−H bonds in complex molecules.

Rational Design of the Spatial Effect in a Fe(II)/α-Ketoglutarate-Dependent Dioxygenase Reverses the Regioselectivity of C(sp3)-H Bond Hydroxylation in Aliphatic Amino Acids.

The hydroxylation of remote C(sp3)-H bonds in aliphatic amino acids yields crucial precursors for the synthesis of high-value compounds. However, accurate regulation of the regioselectivity of remote C(sp3)-H bonds hydroxylation in aliphatic amino acids continues to be a common challenge in chemosynthesis and biosynthesis. In this study, the Fe(II)/α-ketoglutarate-dependent dioxygenase from Bacillus subtilis (BlAH) was mined and found to catalyze hydroxylation at the γ and δ sites of aliphatic amino acids. Crystal structure analysis, molecular dynamics simulations, and quantum chemical calculations revealed that regioselectivity was regulated by the spatial effect of BlAH. Based on these results, the spatial effect of BlAH was reconstructed to stabilize the transition state at the δ site of aliphatic amino acids, thereby successfully reversing the γ site regioselectivity to the δ site. For example, the regioselectivity of L-Homoleucine (5 a) was reversed from the γ site (1 : 12) to the δ site (>99 : 1). The present study not only expands the toolbox of biocatalysts for the regioselective functionalization of remote C(sp3)-H bonds, but also provides a theoretical guidance for the precision-driven modification of similarly remote C(sp3)-H bonds in complex molecules.

The impact of the digital economy on environmental pollution: a perspective on collaborative governance between government and Public

The rapid development of the digital economy is driving transformative changes in a multifaceted collaborative environmental governance system. From the perspective of collaborative governance between government and the public, this study employs double fixed-effects models, spatial econometric models, and instrumental variables methods to empirically explore how the digital economy influences environmental pollution, using panel data from 30 provinces in China spanning 2011 to 2022. The results demonstrate that the digital economy significantly lowers environmental pollution. The primary mechanism is through the government’s environmental governance behaviors, which are positively moderated by public environmental concerns, enhancing effectiveness. Additionally, the digital economy induces a spatial spillover effect on environmental pollution. This promotion of collaborative management between the government and the public is poised to become a pivotal direction in future environmental governance.

Tandem Proton Transfer in Carboxylated Supramolecular Polymer for Highly Efficient Overall Photosynthesis of Hydrogen Peroxide

Proton supply is as critical as O2 activation for artificial photosynthesis of H2O2 via two‐electron oxygen reduction reaction (2e‐ ORR). However, proton release via water dissociation is frequently hindered because of the sluggish water oxidation reaction (WOR), extremely limiting the efficiency of photocatalytic H2O2 production. To tackle this challenge, carboxyl‐enriched supramolecular polymer (perylene tetracarboxylic acid ‐ PTCA) is elaborately prepared by molecular self‐assembly for overall photosynthesis of H2O2. Interestingly, the interconversion between carboxyl as Brønsted acid and its conjugated base realizes rapid proton circulation. Through this efficient tandem proton transfer process, the spatial effect of photocatalytic reduction and oxidation reaction is greatly enhanced with reduced reaction barrier. This significantly facilitates 2e‐ photocatalytic ORR to synthesize H2O2 and in the meanwhile promotes 4e‐ photocatalytic WOR to evolve O2. Consequently, the as‐developed PTCA exhibits a remarkable H2O2 yield of 185.6 μM h‐1 in pure water and air atmosphere under visible light illumination. More impressively, an appreciable H2O2 yield of 78.6 μM h‐1 can be well maintained in an anaerobic system owing to in‐situ O2 generation by 4e‐ photocatalytic WOR. Our study presents a novel concept for artificial photosynthesis of H2O2 via constructing efficient proton transfer pathway to enable rapid proton circulation.

Spatial effects of shrub encroachment on wetland soil pH and salinity in the Yellow River Delta, China

Spatial effects of shrub encroachment on wetland soil pH and salinity in the Yellow River Delta, China

Spatial Nonlinear Effects of Street Vitality Constrained by Construction Intensity and Functional Diversity—A Case Study from the Streets of Shenzhen

As an important part of urban vitality, street vitality is an external manifestation of street economic prosperity and is affected by the built environment and the surrounding street vitality. However, existing research on the formation mechanism of street vitality focuses only on the built environment itself, ignoring the spatial spillover effect on street vitality. This study uses 5290 street segments in Shenzhen as examples. Utilizing geospatial and other multisource big data, this study creates spatial weight matrices at varying distances based on different living circle ranges. By combining the panel threshold model (PTM) and the spatial panel Durbin model (SPDM), this study constructs a spatial autoregressive threshold model to explore the spatial nonlinear effects of street vitality, considering various spatial weight matrices and thresholds of construction intensity and functional diversity. Our results show the following: (1) Street vitality exhibits significant spatial spillover effects, which gradually weaken as the living circle range expands (Moran indices are 0.178***, 0.160***, and 0.145*** for the 500 m, 1000 m, and 1500 m spatial weight matrices, respectively). (2) Construction intensity has a threshold, which is 0.1466 under spatial matrices of different distances. Functional diversity has two thresholds: 0.6832 and 2.2065 for the 500 m spatial weight matrix, and 0.6832 and 1.4325 for the 1000 m matrices, and 0.6832 and 1.2724 for 1500 m matrices. (3) As an international metropolis, street accessibility in Shenzhen has a significant and strong positive impact on its street vitality. This conclusion provides stakeholders with spatial patterns that influence street vitality, offering a theoretical foundation to further break down barriers to street vitality.

PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) MENGGUNAKAN PEMBOBOT KERNEL PADA KASUS TINGKAT PENGANGGURAN TERBUKA DI KALIMANTAN

AbstractUnemployment is one of the serious problems in Indonesia's economic development. This unemployment describes human resources that have not been utilized optimally, as a result of which people's productivity and income have not been maximized, this can also be one of the causes of poverty and other social problems. This study aims to find out the general picture of the open unemployment rate in the Kalimantan region, get the best model and factors that influence the open unemployment rate and illustrate it through thematic maps. The study began with testing assumptions and spatial effects then continued with testing global regression modeling and Geographically Weighted Regression. The weighting function used in this study is adaptive gaussian kernel. The variable that has a positive effect on the open unemployment rate in the Kalimantan region is population density. While the variable that negatively affects the open unemployment rate is the Labor Force Participation Rate. Keywords: Open Unemployment Rate, Kalimantan Island, Spatial, GWR

Collaborative management of environmental pollution and carbon emissions drives local green growth: An analysis based on spatial effects

Collaborative management of environmental pollution and carbon emissions (CMPC) has been a major policy instrument to promote Sustainable Development Goals (SDG) in recent years. However, the relationship between the benefits and drawbacks of this environmental management practice for green growth in and around a local area remains to be clarified. Using 30 provinces in China during 2001–2019 as the object of analysis, we assessed the efficiency of local CMPC practices using the nonradial directional distance function (NDDF) model, predicted local green growth using the frontier green complexity index (GCI), and empirically examined the spatial effects, locational heterogeneity, and threshold characteristics of the relationship using the spatial Durbin model and the panel threshold model. Our study finds that although efficient CMPC does drive local green growth, the promotion effect is nonlinear with decreasing marginal effect. This effect is particularly obvious in economically developed regions with higher CMPCs, which will absorb resources from neighboring regions and create a "siphoning" effect. It was found that local financial support and foreign direct investment (FDI) can radiate green growth to neighboring regions; therefore, CMPC practice needs to pay more attention to the effect of joint governance, supplemented by financial and foreign investment policy tools, to better promote the green transformation of local economy.

Examining the Impact of Urban Connectivity on Urban Innovation Efficiency: An Empirical Study of Yangtze River Delta in China

Innovation serves as a vital catalyst for sustainable urban development, with the enhancement of urban innovation efficiency representing a critical strategy to bolster cities’ innovative capacity. Rigorous scientific measurement of urban innovation efficiency and thorough investigation into the key factors influencing it are imperative for advancing urban innovation capacity. Despite this significance, prior research has largely overlooked the impact of urban connections on urban innovation efficiency. Therefore, this paper undertakes the task of measuring the innovation efficiency of 27 cities within China’s Yangtze River Delta (YRD) region using an improved DEA model, while also examining the associated influencing factors. The primary findings are as follows: (1) The comprehensive efficiency of the 27 cities in the YRD remains relatively low, with pure technical efficiency representing a notable constraint, while scale efficiency demonstrates higher overall performance. (2) The cities can be classified into four distinct categories: innovation-leading, innovation-optimizing, innovation-breaking, and innovation-improving cities. (3) The urban innovation efficiency within the YRD exhibits negative spatial spillover effects. (4) And notably, local economic and social characteristics such as human capital and degree of openness play a positive role in enhancing innovation efficiency in YRD cities. Conversely, factors such as economic foundation and government involvement exhibit negative contributions to innovation efficiency enhancement in YRD cities. Additionally, population mobility between cities is identified as a significant contributor to urban innovation efficiency. This study sheds light on the complex dynamics shaping urban innovation efficiency and underscores the importance of leveraging urban connections to bolster innovation capacity in the YRD and beyond.

Will structural adjustment and financial support affect low-carbon agricultural production in the Yellow River Basin?

Based on the panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this manuscript measures the agricultural low-carbon production efficiency scientifically through the Super-SBM model. In addition, the deviation degree of agricultural industry is used as the index of structural adjustment. Finally, the spatial Durbin model is used to analyze the effect direction and degree of structural adjustment, financial support, and their synergistic effect on agricultural low-carbon production efficiency. The results show that ① the agricultural low-carbon production efficiency in the Yellow River Basin shows a trend of fluctuating downward and a spatial distribution pattern of "high in the east and low in the west". ② Structural adjustment in local region and adjacent areas has a significantly negative impact on agricultural low-carbon production, and the inhibitory effect in adjacent areas is more obvious, and the negative spatial spillover effect is strong. Financial support has a significantly positive impact on agricultural low-carbon production, but the spatial spillover effect of adjacent areas is not obvious. ③ By region, structural adjustment has a significantly negative impact on low-carbon agricultural production in the midstream and downstream regions, while financial support has a significantly positive impact on low-carbon agricultural production in the upstream region. The impact of control variables on agricultural low-carbon production varies from region to region. ④ The synergistic effect of structural adjustment and financial support in the whole and midstream region shows a significantly positive impact on agricultural low-carbon production, indicating that financial support has a certain correction effect on structural adjustment. The coefficient between the upstream and downstream regions is positive but not significant. The conclusions have important reference significance for promoting the ecological protection and high-quality development and agricultural low-carbon development in the Yellow River Basin.

Beta diversity of restored river dike grasslands is strongly influenced by uncontrolled spatio‐temporal variability

AbstractAimsUnderstanding the spatio‐temporal patterns of restoration outcomes is crucial to improve predictability of restoration. High beta diversity of species‐rich communities is sought because it increases overall biodiversity and improves ecosystem stability and multifunctionality. For predictive restoration, it is important to identify the significance of drivers like site characteristics but also uncontrolled factors such as spatial effects, historical factors, and year effects.LocationDikes at river Danube, SE Germany.MethodsWe studied dike grasslands 4–19 years after restoration over five years (2017–2021, 41 plots in 12 sites). We calculated beta diversity indices to describe spatial variation and temporal turnover, including their additive components ‘replacement’ and ‘nestedness’, or ‘gains’ and ‘losses’. We analysed the main drivers of beta diversity like local site characteristics, landscape, and historical factors.ResultsSpatial variation of the restored dike grasslands was dominated by the replacement component and showed no homogenisation despite a significant temporal turnover. The replacement drivers changed over time, although replacement was mainly affected by slope aspect and landscape factors. Historical factors were inconsistent over time, and no statistically clear drivers of nestedness were found. The dike grasslands exhibited a year‐to‐year turnover in species composition of 37 ± 11%. Gains and losses were balanced over time, although the ratio changed and was most pronounced on south‐facing slopes.ConclusionsThe restored grasslands exhibited spatial variation by site characteristics but also by spatial factors which were not controlled by restorations. Moreover, high non‐directional temporal turnover occurred, caused most likely by weather fluctuations, slightly varying management, and stochastic biotic dynamics. Thus, flexible targets are recommended for restoration monitoring, by defining a set of desired states within a certain range. Furthermore, the dominance of the replacement component of spatial variation should move the focus from defining one precise restoration approach to defining a set of possible methods which together would foster beta diversity.

Research on the spatio-temporal evolution and impact of China’s industrial green development from the perspective of digital economy--based on analysis of 279 cities in China

Empowering industrial green development with the digital economy represents a crucial approach to advancing the green transformation of China’s economy and achieving high-quality economic development. Based on panel data from 279 cities in China from 2011 to 2021, this article uses the spatial econometrics model and threshold effect model to explore the spatial effect and nonlinearity of digital economy (DE) on industrial green development (IGD). The results show that, both DE and IGD exhibit fluctuating upward trends in China. There exists stronger spatial linkage effect in the eastern coastal areas, but this effect is weaker in the central and western regions. Furthermore, DE has significantly promoted IGD, and the conclusion remains robust after a series of endogeneity and robustness tests. Additionally, the promotion of the DE for IGD is characterized by regional spillovers and non-linear dynamics. The research results can serve as a theoretical support and decision-making basis for China to enhance industrial green development, promote the construction of an ecological civilization, and implement sustainable development strategies.

Spatial and Temporal Effect of Environmental Factors on the Length-Weight Relationship of the Bali Sardinella (Sardinella lemuru Bleeker, 1853) in Bali Strait Water

Spatial and Temporal Effect of Environmental Factors on the Length-Weight Relationship of the Bali Sardinella (Sardinella lemuru Bleeker, 1853) in Bali Strait Water

Optimal governance radius of environmental information disclosure policy: Evidence from China

s: Urban pollution governance requires the joint participation of government, society, and enterprises, with the environmental information disclosure policy serving as a novel tool to promote multi-stakeholder engagement. This study aims to delve into the impact of the environmental information disclosure policy on regional environmental quality by using data from Chinese cities. Through analysis, the study gets the following conclusions. Firstly, the environmental information disclosure policy not only effectively reduces urban environmental pollution but also exhibits an apparent spatial spillover effect. The impact of this policy on air pollution in neighboring cities shows an inverted U-shaped pattern of first rising and then falling, with the optimal radius of this external effect estimated at 250km. Secondly, the results of the mechanism test indicate that government regulatory efforts and clean industry alternatives are essential channels for curbing urban environmental pollution. Lastly, the heterogeneity test shows that the inhibitory effect of the environmental information disclosure policy on environmental pollution is more pronounced in civilized cities, cities in the “two control zones”, sulfur dioxide control zones, and cities with high Pollution Information Transparency Index scores.

Pilot free trade zones and low-carbon innovation: Evidence from listed companies in China

The impact of pilot free trade zones (PFTZs) on companies' low-carbon innovation is not yet studied. In response, this paper considers the establishment of PFTZs as a quasi-natural experiment, using panel data on China's A-share industrial listed companies for the period 2010–2021 and utilizing the entropy balancing difference-in-differences (EB-DID) model to examine PFTZs' impact on companies' low-carbon innovation. The results show that: (1) PFTZs significantly promote companies' low-carbon innovation in pilot cities through the “promoting R&D effect” and the “environmental governance effect”; (2) Foreign capital positively moderates PFTZs' impact on companies' low-carbon innovation; (3) PFTZs' policy effect is characterized by spatial heterogeneity. The paper thus suggests that the government should improve the construction plans of PFTZs to ensure alignment with low-carbon development goals. Moreover, the government should also provide appropriate subsidies for low-carbon technology R&D to encourage innovation, implement advanced institutional systems to facilitate local companies' low-carbon transition, attract high-quality foreign investments to drive the inflow of innovation elements, and optimize the geographical distribution of PFTZs to maximize the spatial spillover effect.

Preparation and Performance Evaluation of a New Type of Polyethylene-vinyl Acetate/Polystyrene Microsphere Composite Pour Point Depressant for Waxy Crude Oil.

Polymer/inorganic nanocomposite pour point depressant (PPD) is a research hotspot in the field of waxy crude oil pipelining. However, the inorganic nanoparticles need to be organically modified to improve their organic compatibility, and the inorganic nanoparticles are harmful to crude oil refining. In this work, organic PSMS with an average size of 1.4 μm was first synthesized by dispersion polymerization. Then, a new type of EVA/PSMS composite PPD was prepared by melt blending. The effects of the PSMS, EVA PPD, and composite PPD on the pour point, rheological properties, and wax precipitating properties of a specific waxy crude oil were investigated. It was found that adding 50-200 ppm of PSMS alone slightly improves the crude oil rheology through a spatial hindrance effect, while adding 20 ppm of EVA PPD greatly improves the crude oil rheology by modifying the wax crystal morphology. Compared with EVA PPD, adding 20 ppm composite PPD improves the crude oil rheology further, and the rheological improving ability first enhances and then weakens with increasing the PSMS content in the composite PPD (0-10 wt %). At the PSMS content in the composite PPD 5 wt %, the EVA/PSMS 5% composite PPD makes the wax crystal aggregates more compact, thus showing the strongest rheological improving ability. The EVA molecules could adsorb on the PSMS and form the composite particles, which further regulate the wax crystal morphology and then improve the crude oil rheology further.