Spatiotemporal Effects Research Articles

Spatio-temporal electrical grid emission factors effects on calculated GHG emissions of buildings in mixed-grid environments

This study compares the calculated greenhouse gas (GHG) emissions of buildings using two different methodologies in mixed-grid environments. Simulations were conducted using virtual models of 25 buildings and actual meteorological data over 2016–2018. The “Annual Method” using yearly average emission factors and the “Hourly Method” using consumption-based hourly emission factors were used to calculate GHG emissions. The study found that the hourly method provided a more accurate representation of GHG emissions, especially during peak grid demand. Furthermore, the study recommends using a zonal approach to building codes in terms of electrical grids similar to climate zones in current codes and standards while also prioritizing building types with the largest potential for emissions reductions. A case study in Ontario, Canada found that electrification via heat pump always results in GHG savings independent of year, building model, and city if keeping the calculation method the same between fuel-switching models. Future research is needed to improve the accuracy of GHG emissions calculations and understand the relationship between electrical load and GHG emissions.

Dynamic spatiotemporal ARCH models

ABSTRACT Geo-referenced data are characterised by an inherent spatial dependence due to geographical proximity. In this paper, we introduce a dynamic spatiotemporal autoregressive conditional heteroscedasticity (ARCH) process to describe the effects of (i) the log-squared time-lagged outcome variable, the temporal effect, (ii) the spatial lag of the log-squared outcome variable, the spatial effect, and (iii) the spatiotemporal effect on the volatility of an outcome variable. We derive a generalised method of moments (GMM) estimator based on the linear and quadratic moment conditions. We show the consistency and asymptotic normality of the GMM estimator. After studying the finite-sample performance in simulations, the model is demonstrated by analysing monthly log-returns of condominium prices in Berlin from 1995 to 2015, for which we found significant volatility spillovers.

Four shades of Airbnb and its impact on locals: A spatiotemporal analysis of Airbnb, rent, housing prices, and gentrification

Despite the growing amount of tourism literature examining short-term rentals, few studies have examined their economic impact on locals. This study is unique in that it elucidates Airbnb listings' heterogeneity and reflects spatiotemporal effects in the analysis of their impact on locals. The study revealed that Airbnb has different impacts on local housing markets by their characteristics. Furthermore, this study provides quantitative evidence delineating the relationship between Airbnb and gentrification. Overall, entire home listings by multi-unit hosts were found to exhibit the greatest impact on rent, housing value, and gentrification. The study findings provide practical implications for destinations to implement concrete strategies for balancing the positive and negative impacts of Airbnb.

Research on the dynamic characteristics of wind turbine gearboxes under the spatiotemporal inhomogeneous in the wake

In response to the problem of increasing fatigue load and frequent faults caused by the wake effect, the dynamic characteristics and fatigue life analysis of wind turbine gearbox under the Spatial-temporal non-uniformity of wake region were carried out in this paper. A rigid-flexible coupling model of gears transmission system for a 2 MW wind turbine was established. Based on the three-dimensional Station-temporal inhomogeneous wake model proposed in our previous work, the wind speed distribution of six typical locations in the wake region was obtained. Results show that, the spatiotemporal inhomogeneous effects of the wake expansion have great impact on the dynamic characteristics of the gearboxes for the downwind turbines located in different positions. Vibration energy representing the magnitude of impact energy during the operation of the gearbox is significantly higher under wake conditions than under upstream conditions; meanwhile, the gearbox vibration signal contains more impact component in the wake. The velocity deficit and increased turbulence intensity results in less intense but more complex vibration non-smoothness in the turbine transmission system. As the downwind distance downwind increases, the vibration frequency distribution of the transmission system at each moment is larger, but the vibration energy is reduced. Under the 3D spatiotemporal inhomogeneous effects of the wake expansion, the downstream turbine with staggered arrangement is less affected by wake and has a smoother vibration than the tandem arrangement. At the same downstream distance, the gear life is better in a tandem arrangement than in a staggered arrangement (a maximum value happens at the downstream distance of 6D). Research in this paper can provide references for the study of the dynamic characteristics of large wind turbine transmission systems under the wake effects as well as for the micro-siting of wind farms.

The ultrashort pulse laser ablation model of silicon based on the generalized thermoelastic theory with spatio-temporal nonlocal effect

The present work is devoted to establishing the ultrashort pulse laser ablation generalized thermoelastic model with spatio-temporal nonlocal effect and investigating the transient responses of the process of silicon ablated by the picosecond pulse laser. The research is divided into three cases. 1) The solid silicon before the target surface melting is studied, and the transient responses of the final state of this case are taken as the initial conditions of the Case Two. 2) The liquid silicon after the target surface melting is researched, and the heat flux taken away by vaporization is considered in the boundary condition. 3) The solid silicon after the target surface melting is discussed, and the moving solid-liquid interface is regarded as the coordinate origin. The coupled governing equations containing spatial nonlocal parameter, time delay factor, and kernel function are established and solved by the Laplace transform together with its numerical inversion. The melting time and depth of target are emphatically discussed. The temperature, displacement and stress with different laser intensity, spatial nonlocal parameter, time delay factor, kernel function as well as time are obtained and illustrated graphically.

Government land control approach, industrial agglomeration, and urban air quality: Analysis based on spatial spillovers and threshold effects

Local government intervention in industrial land concessions has contributed significantly to the country's miraculous growth during the past four decades, but there are concerns about its environmental impact. Assessing the model's impact on the Air Quality Index (AQI) is critical for China as it focuses, now, on sustainable development. We examine the spatiotemporal effects and pathways of land use regulation by local governments in China on air quality index. The data used are real-time air quality data and land transaction micro data of 282 cities from 2015 to 2020. The results demonstrate that local government use controls have a favorable impact on the AQI in the city and its surrounding areas. Land intervention attracted capital from low-tech and high-polluting industries to their more aggressive locations, triggering “bottom-up competition” in the industrial structure through the industrial aggregation effect. The study also found structural breakpoints in the model's industrial agglomeration effect. There are two structural breakpoints in the national region; the model's impact on AQI increases significantly after exceeding each structural breakpoint. At the sub-regional level, there are two structural breakpoints in the industrial agglomeration effect of the eastern and western cities; both weaken after exceeding the second structural breakpoint. There is one structural breakpoint in the central cities; after exceeding it, the model's impact on AQI increases.

618 Environmental exposures and spatiotemporal effects that characterize rapid lung function decline in a Midwest U.S. cystic fibrosis cohort

618 Environmental exposures and spatiotemporal effects that characterize rapid lung function decline in a Midwest U.S. cystic fibrosis cohort

Rapid eye movement sleep affects interictal epileptic activity differently in mesiotemporal and neocortical areas.

Rapid eye movement (REM) sleep reduces the rate and extent of interictal epileptiform discharges (IEDs). Breakthrough epileptic activity during REM sleep is therefore thought to best localize the seizure-onset zone (SOZ). We utilized polysomnography combined with direct cortical recordings to investigate the influences of anatomical locations and the time of night on the suppressive effect of REM sleep on IEDs. Forty consecutive patients with drug-resistant focal epilepsy underwent combined polysomnography and stereo-electroencephalography during presurgical evaluation. Ten-minute interictal epochs were selected 2 h prior to sleep onset (wakefulness), and from the first and second half of the night during non-REM (NREM) sleep and REM sleep. IEDs were detected automatically across all channels. Anatomic localization, time of night, and channel type (within or outside the SOZ) were tested as modulating factors. Relative to wakefulness, there was a suppression of IEDs by REM sleep in neocortical regions (median=-27.6%), while mesiotemporal regions showed an increase in IEDs (19.1%) (p=0.01; d=0.39). This effect was reversed when comparing the regional suppression of IEDs by REM sleep relative to NREM sleep (-35.1% in neocortical; -58.7% in mesiotemporal) (p<0.001; d=0.39). Across all patients, no clinically relevant novel IED regions were observed in REM sleep versus NREM or wakefulness based on our predetermined thresholds (4 IEDs/min in REM, 0 IEDs/min in NREM and W). Finally, there was a reduction in IEDs in late (NREM: 1.08/min; REM: 0.61/min) compared to early sleep (NREM: 1.22/min; REM: 0.69/min) for both NREM (p<0.001; d=0.21) and REM (p=0.04; d=0.14). Our results demonstrate a spatiotemporal effect of IED suppression by REM sleep relative to wakefulness in neocortical, but not mesiotemporal regions, and in late versus early sleep. This suggests the importance of considering sleep stage interactions and the potential influences of anatomical locations when using IEDs to define the epileptic focus.

Differential spatiotemporal gait effects with frequency and dopaminergic modulation in STN-DBS.

The spatiotemporal gait changes in advanced Parkinson's disease (PD) remain a treatment challenge and have variable responses to L-dopa and subthalamic deep brain stimulation (STN-DBS). The purpose of this study was to determine whether low-frequency STN-DBS (LFS; 60 Hz) elicits a differential response to high-frequency STN-DBS (HFS; 180 Hz) in spatiotemporal gait kinematics. Advanced PD subjects with chronic STN-DBS were evaluated in both the OFF and ON medication states with LFS and HFS stimulation. Randomization of electrode contact pairs and frequency conditions was conducted. Instrumented Stand and Walk assessments were carried out for every stimulation/medication condition. LM-ANOVA was employed for analysis. Twenty-two PD subjects participated in the study, with a mean age (SD) of 63.9 years. Significant interactions between frequency (both LFS and HFS) and electrode contact pairs (particularly ventrally located contacts) were observed for both spatial (foot elevation, toe-off angle, stride length) and temporal (foot speed, stance, single limb support (SLS) and foot swing) gait parameters. A synergistic effect was also demonstrated with L-dopa and both HFS and LFS for right SLS, left stance, left foot swing, right toe-off angle, and left arm range of motion. HFS produced significant improvement in trunk and lumbar range of motion compared to LFS. The study provides evidence of synergism of L-dopa and STN-DBS on lower limb spatial and temporal measures in advanced PD. HFS and LFS STN-DBS produced equivalent effects among all other tested lower limb gait features. HFS produced significant trunk and lumbar kinematic improvements.

Multidimensional Spatial Driving Factors of Urban Vitality Evolution at the Subdistrict Scale of Changsha City, China, Based on the Time Series of Human Activities

Urban vitality is an important reflection of a city’s development potential and urban quality. This study used exploratory spatio-temporal big data such as social media check-ins to portray the spatio-temporal evolution of urban vitality at the subdistrict scale in Changsha, a city in central China, from 2013 to 2021, finding that urban vitality in Changsha exhibited central agglomeration and outward circling expansion over time, and then we used Geodetector and spatial regression analyses to explain the interactive effects and spatio-temporal heterogeneity of the spatial elements of subdistrict form, subdistrict function, and subdistrict economy on urban vitality. The results show the following: (1) The subdistrict form and subdistrict function dimensions had a significant effect on urban vitality, and the effect of the economic dimension of the subdistrict was not significant. (2) The interaction effect of the density of entertainment and leisure facilities and the density of business office facilities in subdistrict function was the dominant factor in the change of urban vitality. (3) Under the spatio-temporal effect, land use diversity and park facility density had the strongest positive effect on urban vitality; road density and shopping facility density had the weakest effect. The study aimed to provide a reference for the optimization and allocation of spatial elements of subdistricts in sustainable urban development and urban renewal, in order to achieve the purpose of urban vitality creation and enhancement.

Untangling the effects of climate variation and human interference on grassland dynamics in North China

AbstractClimatic and anthropogenic disturbances play pivotal roles in shaping the dynamics of grassland. Quantifying their impacts on grassland variation is essential to ensure sustainable grassland management. In this study, we employed the Thornthwaite Memorial and Carnegie–Ames–Stanford‐approach (CASA) models to investigate the spatiotemporal effects of these two variables on grassland variation in northern China from 2000 to 2016, using the net primary productivity (NPP) as a measure. Our findings reveal that approximately 25.92% of the grassland in northern China experienced degradation, while restored grasslands occupied 45% of the total grassland area. The average grassland actual NPP (ANPP) and human‐induced NPP decreased at rates of −0.60 and −5.62 gC m−2 a−1, respectively. Conversely, potential NPP exhibited an upward trend with an average increase of 2.27 gC m−2 a−1. Furthermore, grassland ANPP showed a projected increase in most parts of northern China. Climate change emerged as the primary driver for grassland restoration in Xinjiang, Qinghai, and Inner Mongolia, leading to an increase of 21582.79 Gg C in grassland NPP. In contrast, human activities were the dominant catalysts for grassland degradation, resulting in a reduction of 51932.3 Gg C in grassland NPP. Human‐induced grassland degradation was ubiquitous in northwest and northeast China. With the exception of slope grassland, climate change primarily influenced the restoration of most grassland types, while human activities were the primary cause of degradation. Our analysis indicated a strong correlation between temperature and grassland degradation, while precipitation played a pivotal role in grassland restoration in northern China. Human interference demonstrated both positive and negative impacts on grassland changes. In conclusion, the increase in precipitation and the implementation of ecological restoration plans have effectively promoted the restoration of grasslands in northern China.

Exploring the coupling coordination of urban ecological resilience and new-type urbanization: The case of China’s Chengdu–Chongqing Economic Circle

Reviewing the coupling coordination between urban ecological resilience (UER) and new-type urbanization (NU) has gradually become a necessary condition for understanding the structure and service patterns of urban ecological systems. Discussion on the temporal and spatial coordination evolution in UER and NU in urban agglomerations with different characteristics is beneficial for understanding the operational mechanisms of urban ecosystems. This work constructs a novel evaluation framework for the coupling coordination process between UER and NU, and scientifically measures the performance of each indicator using the entropy method and CRITIC method. By using the coupling coordination degree (CCD) model, this paper explores the spatio-temporal effects of the relationship between UER and NU, which has narrowed the cognitive gap. Using the Chengdu–Chongqing Economic Circle in China as an example, the validity and practicality of the framework are verified. The results show that the CCD between UER and NU generally shows a rapid growth trend with time and tends to be balanced; and the development patterns of CCD in urban agglomerations show significant spatial differences influenced by factors such as location advantage, natural resources, and human social activities. These results and findings can provide decision-making information reference for urban ecological system services, urban livability, and government planning.

Effects of climate change and variability on large pelagic fish in the Northwest Atlantic Ocean: implications for improving climate resilient management for pelagic longline fisheries

Climate change influences marine environmental conditions and is projected to increase future environmental variability. In the North Atlantic, such changes will affect the behavior and spatiotemporal distributions of large pelagic fish species (i.e., tunas, billfishes, and sharks). Generally, studies on these species have focused on specific climate-induced changes in abiotic factors separately (e.g., water temperature) and on the projection of shifts in species abundance and distribution based on these changes. In this review, we consider the latest research on spatiotemporal effects of climate-induced environmental changes to HMS’ life history, ecology, physiology, distribution, and habitat selection, and describe how the complex interplay between climate-induced changes in biotic and abiotic factors, including fishing, drives changes in species productivity and distribution in the Northwest Atlantic. This information is used to provide a baseline for investigating implications for management of pelagic longline fisheries and to identify knowledge gaps in this region. Warmer, less oxygenated waters may result in higher post-release mortality in bycatch species. Changes in climate variability will likely continue to alter the dynamics of oceanographic processes regulating species behavior and distribution, as well as fishery dynamics, creating challenges for fishery management. Stock assessments need to account for climate-induced changes in species abundance through the integration of species-specific responses to climate variability. Climate-induced changes will likely result in misalignment between current spatial and temporal management measures and the spatiotemporal distribution of these species. Finally, changes in species interactions with fisheries will require focused research to develop best practices for adaptive fisheries management and species recovery.

Spatiotemporal-aware machine learning approaches for dissolved oxygen prediction in coastal waters

Coastal waters face increasing threats from hypoxia, which can have severe consequences for marine life and fisheries. This study aims to develop a machine learning approach for hypoxia monitoring by investigating the effectiveness of four tree-based models, considering spatiotemporal effects in model prediction, and adopting the SHapley Additive exPlanations (SHAP) approach for model interpretability, using the long-term climate and marine monitoring dataset in Tolo Harbour (Zone 1) and Mirs Bay (Zone 2), Hong Kong. The LightBoost model was found to be the most effective for predicting dissolved oxygen (DO) concentrations using spatiotemporal datasets. Considering spatiotemporal effects improved the model's bottom DO prediction performance (R2 increase 0.30 in Zone1 and 0.68 in Zone 2), although the contributions from temporal and spatial factors varied depending on the complexity of physical and chemical processes. This study focused not only on error estimates but also on model interpretation. Using SHAP, we propose that hypoxia is largely influenced by hydrodynamics, but anthropogenic activities can increase the bias of systems, exacerbating chemical reactions and impacting DO levels. Additionally, the high relative importance of silicate (Zone 1:0.11 and Zone 2: 0.19) in the model suggests that terrestrial sources, particularly submarine groundwater discharge, are important factors influencing coastal hypoxia. This is the first machine learning effort to consider spatiotemporal effects in four dimensions to predict DO concentrations, and we believe it contributes to the development of a forecasting tool for alarming hypoxia, combining real-time data and machine learning models in the near future.

Detrended seasonal relationships and impact of climatic factors combined with spatiotemporal effect on the prevalence of human brucellosis.

Human brucellosis (HB) is a seasonal and climate-affected infectious disease that is posing an increasing threat to public health and economy. However, most of the research on the seasonal relationships and impact of climatic factors on HB did not consider the secular trend and spatiotemporal effect related to the disease. We herein utilized long-term surveillance data on HB from 2008 to 2020 using sinusoidal models to explore detrended relationships between climatic factors and HB. In addition, we assessed the impact of such climatic factors on HB using a spatial panel data model combined with the spatiotemporal effect. HB peaked around mid-May. HB was significantly correlated with climatic factors with 1-5-month lag when the respective correlations reached the maximum across the different lag periods. Each 0.1 °C increase in temperature led to 0.5% decrease in the 5-month lag incidence of HB. We also observed a positive spatiotemporal effect on the disease. Our study provides a detailed and in-depth overview of seasonal relationships and impact of climatic factors on HB. In addition, it proposes a novel approach for exploring the seasonal relationships and quantifying the impacts of climatic factors on various infectious diseases.

The spatiotemporal effect of factor price distortion on capacity utilization in China’s iron and steel industry

Under the situation of global climate change and green transition, China’s iron & steel industry (ISI) faced great pressure to energy conservation and cut backward overcapacity. To explore the characteristics of overcapacity and inherent impacting factor of capacity utilization, the study focused on the relationship of incomplete input factor market and overcapacity. Based on provincial data from 2003 to 2019, the study estimated capacity utilization rate in China’s ISI sector, and further evaluated the impact of factor price distortion on capacity utilization rate and its spatiotemporal effect through dynamic spatial model. Firstly, the capacity utilization rate China’s ISI sector showed regional heterogeneity with an average level of 68%, and the capacity utilization rate would be promoted by previous capacity utilization rate and capacity utilization rate of neighbor provinces; Secondly, capital and energy price distortion showed significant negative effect on capacity utilization, while labor price distortion positively promoted capacity utilization; Thirdly, from the perspective of spatial effect, capital price distortion showed significantly negative effect on capacity utilization. Therefore, deepening factor market reform and reducing the intervention of local government would be effective way to improve capacity utilization and promote cleaning production.

Spatiotemporal response of concave VLS grating to ultra-short X-ray pulses.

In soft X-ray free-electron laser (FEL) beamlines, variable-line-spacing (VLS) gratings are often used as dispersive components of monochromators and spectrometers due to their combined dispersion and focusing properties. X-ray FEL pulses passing through the VLS grating can result in not only transverse focusing but also spatiotemporal coupling effects, such as pulse front tilt, pulse front rotation, and pulse stretching. In this paper, we present a theoretical study of the spatiotemporal response of concave VLS gratings to ultra-short X-ray pulses. The theoretical analysis indicates that the tilt angle of the non-zero diffraction orders varies with the propagation distance, and disappears at the focus, where the focal lengths and pulse stretching differ for different diffraction orders. The model demonstrates the pulse duration after the concave VLS grating is the convolution of the initial pulse duration and the stretching term induced by dispersion, while the beam size at the focus in x dimension is the convolution of the geometric scaling beam size and the dispersion term. This work provides a mathematical explanation for the spatiotemporal response of concave VLS grating to ultra-short X-ray pulses and offers valuable insights into the design of FEL grating monochromators, spectrometers, pulse compressors, and pulse stretchers.

Critical travelling waves of a vector-host disease model with spatio-temporal nonlocal effect

This paper is concerned with the existence of travelling wave solution (TWS) with critical speed c∗ for a nonlocal reaction–diffusion vector-host disease model. When the basic reproduction ratio R0 at the disease-free equilibrium is greater than one, we adopt the limiting arguments and contradictory approach to show the existence of critical TWS. Furthermore, it is observed that R0 at the final size of susceptible hosts and vectors is less than one, which indicates that the disease will not eventually break out.

Temporal-spatial variation and regulatory mechanism of carbon budgets in territorial space through the lens of carbon balance: A case of the middle reaches of the Yangtze River urban agglomerations, China

As China’s largest cross-regional urban agglomerations, the middle reaches of the Yangtze River urban agglomerations (MRYRUA) possess both significant societal carbon source volume and ecological carbon sequestration capacity. Nevertheless, with the uncontrolled expansion of urban energy consumption activities and the industry migration from eastern coastal regions to inland cities, the carbon budget pattern of territorial space is increasingly unbalanced in the MRYRUA. To achieve low-carbon regulation, this study utilized land use and energy consumption data from 31 cities within the MRYRUA to establish a “carbon source-carbon sink” quantification and spatiotemporal exploration model, revealing the spatial-temporal variation of carbon budgets from 2005 to 2020. Furthermore, we developed a carbon balance indicator analysis system by employing the carbon offset rate (COR), carbon productivity (CP), Gini coefficient, ecological support coefficient (ESC), economic contribution coefficient (ECC), and functional zoning was performed. Finally, using the GM (1,1) model, we derived the carbon budget pattern for 2050 and explored the differentiated regulatory mechanisms under the carbon balance perspective. The results indicated that: (1) The MRYRUA’s territorial carbon budgets have increased annually, displaying a spatial distribution pattern with the highest values in the central region, followed by the northwest, and the lowest in the southeast near water bodies. The spatiotemporal differentiation effects manifest as an east–west axial development trend, with spatiotemporal clustering effects demonstrating a propensity for outward dispersion from the northern hot spot radiation core. (2) The MRYRUA’s COR has consistently remained below 10% and decreased annually, while the CP has shown a yearly increase at an accelerating rate. The ESC and ECC exhibit evident spatial heterogeneity among cities. In response to the carbon emission economic benefits and carbon sequestration ecological carrying capacity reflected by carbon balance indicators, each city was classified into low-carbon economic zones, carbon intensity control zones, carbon sink functional zones, and high-carbon optimization zones. (3) From 2020 to 2050, the polarization trend of the carbon budget pattern continues to intensify. Subsequently, we have established a differentiated territorial spatial carbon balance regulatory mechanism. This mechanism strengthens the leading role of low-carbon economic zones in the green low-carbon transition, moderately retains the carbon sink functional zones in the southeast with solid carbon fixation capabilities, and promotes the transition of the northern carbon intensity control zones and high-carbon optimization zones to low-carbon economic zones. The research findings provide a scientific basis for formulating territorial spatial planning policies from a carbon neutrality perspective.

Zone-Enhanced Spatio-Temporal Representation Learning for Urban POI Recommendation

Points-of-interest (POIs) recommendation plays a vital role in location-based social networks (LBSNs) by introducing unexplored POIs to consumers and has drawn extensive attention from academia and industry. Existing POI recommender systems usually learn fixed latent vectors to represent both consumers and POIs from historical check-ins and make recommendations under the spatio-temporal constraints. However, we argue that the existing works still suffer from the challenges of explaining consumers' complicated check-in actions. To this end, we first explore the interpretability of recommendations from the POI aspect, i.e., for a specific POI, its function usually changes over time, so representing a POI with a single fixed latent vector is not sufficient to describe the dynamic nature of POIs. Besides, check-in actions to a POI are also affected by the zone where it is located. In other words, the zone's embedding learned from POI distributions, road segments, and historical check-ins could be jointly utilized to enhance POI embeddings. Along this line, we propose a <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</b> ime-z <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</b> ne-space <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</b> OI embedding model ( <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ToP</b> ), which integrates multi-knowledge graphs and topic model to introduce not only spatio-temporal effects but also sentiment constraints into POI embeddings for strengthening interpretability of recommendation. Specifically, ToP learns multiple latent vectors for a POI in a different period with spatial constraints via knowledge graph learning. To add sentiment constraints, ToP jointly combines these vectors with the zone's representations learned by topic models to make explainable recommendations. ToP considers the time, space, and sentiment of POI in a unified embedding framework, which benefits the POI recommendations. Extensive experiments on real-world Changchun city datasets demonstrate that ToP achieves state-of-the-art performance in terms of common metrics and provides more insights for consumers' POI check-in actions.