[Spatial and Temporal Scale Effects of Landscape Pattern on Riverine Nitrogen and Phosphorus Nutrients in the Qingshan Lake Watershed].

The influences of landscape pattern on water quality are dependent on spatial-temporal scales. However, the effects of landscape composition, landscape configuration, and landscape slope metrics on seasonal water quality at different spatial scales remain unclear. Based on the total nitrogen, total phosphorus, nitrate-N, and ammonium-N data from 26 sampling sites in the Qingshan Lake watershed, this study coupled landscape pattern analysis, redundancy analysis, and partial redundancy analysis to quantify the spatiotemporal scale effects of landscape pattern on riverine nitrogen （N） and phosphorus （P） concentrations. The results showed that： ① The explanatory ability of landscape pattern at the sub-watershed scale on riverine N and P concentrations was 6.8%-8.4% higher than that at the buffer scale, and this effect was more obvious in the dry season. ② At the sub-watershed scale, the percentage of forestland and the interspersion and juxtaposition degree of residential land had a greater influence on riverine N and P concentrations. At the buffer scale, the slope of farmland and residential land and the aggregation degree of forestland patches were the key factors affecting riverine N and P concentrations. ③ The contribution rate of landscape configuration to riverine N and P concentration variations （20.1%-36.5%） was the highest. The sensitivity of the effect of landscape configuration on riverine N and P concentrations to seasonal changes was the highest, and the effect of landscape slope on riverine N and P concentrations had the highest sensitivity to spatial scale changes. Therefore, landscape pattern-regulated non-point source pollution should be considered from a multi-scale perspective. These results can provide scientific basis for the formulation of landscape pattern optimization measures aiming at non-point source pollution control.

Vibration Analysis of Porous Cu-Si Microcantilever Beams in Fluids Based on Modified Couple Stress Theory.

The vibrations in functionally graded porous Cu-Si microcantilever beams are investigated based on physical neutral plane theory, modified coupled stress theory, and scale distribution theory (MCST&SDT). Porous microcantilever beams define four pore distributions. Considering the physical neutral plane theory, the material properties of the beams are computed through four different power-law distributions. The material properties of microcantilever beams are corrected by scale effects based on modified coupled stress theory. Considering the fluid driving force, the amplitude-frequency response spectra and resonant frequencies of the porous microcantilever beam in three different fluids are obtained based on the Euler-Bernoulli beam theory. The quality factors of porous microcantilever beams in three different fluids are derived by estimating the equation. The computational analysis shows that the presence of pores in microcantilever beams leads to a decrease in Young's modulus. Different pore distributions affect the material properties to different degrees. The gain effect of the scale effect is weakened, but the one-dimensional temperature field and amplitude-frequency response spectra show an increasing trend. The quality factor is decreased by porosity, and the degree of influence of porosity increases as the beam thickness increases. The gradient factor n has a greater effect on the resonant frequency. The effect of porosity on the resonant frequency is negatively correlated when the gradient factor is small (n<1) but positively correlated when the gradient factor is large (n>1).

Study on the Cross-Scale Effects of Microscopic Interactions and Mechanical Properties of Rigid Polyurethane Foam Driven by Negative-Temperature Environments.

In order to investigate the cross-scale effects of the interaction between the hard and soft segments of stiff polyurethane foam on the material's mesoscopic pore structure and macroscopic compression characteristics in various negative-temperature environments, this paper used molecular dynamics to calculate the interaction differences between hard and soft segments in different negative-temperature environments. The effects of various negative-temperature settings on the cell structure of stiff polyurethane foam were investigated using scanning electron microscopy and Image J software. Finally, macro experiments were used to determine the influence of a negative-temperature environment on the characteristics of stiff polyurethane foam (such as compressibility). The molecular simulation calculation results show that in a negative-temperature environment, decreasing temperature gradually increases the interaction between hard segment molecules and soft segment molecules, resulting in an increase in the molecules' modulus and cohesive energy density. The scanning electron microscope results reveal that a negative-temperature environment gradually increases the pore diameter of stiff polyurethane foam. The compression experiment findings demonstrate that, for the same service duration, the compressive strength in the -20 °C environment is 27.53% higher than that in the 0 °C environment. The study's findings reveal a microscopic mechanism for the following receiving alterations and toughness enhancement of rigid polyurethane foam throughout service in negative-temperature conditions.

Experimental investigation on dynamic deformation characteristics of the overlying strata in backfilling strip mining at different time scales.

The dynamic subsidence disaster caused by underground mining of coal resources is a complex spatiotemporal process, which is a common disaster in mining areas. The backfilling strip mining technology is a green and sustainable coal mining method, which has been commonly used to reduce the subsidence disaster of the overlying strata and protect surface buildings. The transient deformation is the main reason of surface buildings damage; therefore, in this study, the similar material model was used to research dynamic deformation characteristics of the overlying strata in backfilling strip mining at different time scales, and the optical image method was employed to monitor and obtain the movement data of the overlying strata automatically. The data analysis shows that there is a time-scale effect in mining subsidence. The deformation of the overlying strata increases instantaneously at a certain time under the monitoring of small time scale, and this phenomenon gradually disappears as time scales increase. According to the subsidence velocity of small time scale, the subsidence state of the overlying strata can be further divided into the abrupt subsidence state and the gentle subsidence state. This is really significant for promoting the development of the backfilling strip mining technology and preventing the damage of surface buildings.

Spatial difference on nitrogen removal in the water based on different resolutions for Sanhuanpao wetland, Northeast China.

The research on the deviations caused by different resolutions is relevant to the study of spatial scale effects. In 2018, spatial interpolations were performed using the removal ratios of the TN, NH4-N, and NO3-N of the layers of different resolutions, respectively. Based on the mean and the standard deviation, the area, shape, and position were obtained for four levels related to the removal ratios of the three nitrogen forms. The linear and 6th function fitting methods were used to reveal the differences in nitrogen removal in wetland water at different spatial resolutions. The results showed that a resolution of 25 times the original was the key scale of the spatial effects. Due to the fact that 52 of the 72 functions did not reach a significant level (P < 0.05), the spatial scale effect of the nitrogen removal was mainly characterized by disorderly fluctuations. The results have a certain extrapolation value for the analysis of spatial scale effects. PRACTITIONER POINTS: The resolution difference was not sufficient to change the spatial pattern of the geographic phenomena. The resolution of 25 times the original was the important scale for determining spatial effects. When studying the spatial scale effects caused by differences in resolution, it was necessary to comprehensively consider various resolutions.

Mechanics of Small-Scale Spherical Inclusions Using Nonlocal Poroelasticity Integrated with Light Gradient Boosting Machine.

Detecting inclusions in materials at small scales is of high importance to ensure the quality, structural integrity and performance efficiency of microelectromechanical machines and products. Ultrasound waves are commonly used as a non-destructive method to find inclusions or structural flaws in a material. Mathematical continuum models can be used to enable ultrasound techniques to provide quantitative information about the change in the mechanical properties due to the presence of inclusions. In this paper, a nonlocal size-dependent poroelasticity model integrated with machine learning is developed for the description of the mechanical behaviour of spherical inclusions under uniform radial compression. The scale effects on fluid pressure and radial displacement are captured using Eringen's theory of nonlocality. The conservation of mass law is utilised for both the solid matrix and fluid content of the poroelastic material to derive the storage equation. The governing differential equations are derived by decoupling the equilibrium equation and effective stress-strain relations in the spherical coordinate system. An accurate numerical solution is obtained using the Galerkin discretisation technique and a precise integration method. A Dormand-Prince solution is also developed for comparison purposes. A light gradient boosting machine learning model in conjunction with the nonlocal model is used to extract the pattern of changes in the mechanical response of the poroelastic inclusion. The optimised hyperparameters are calculated by a grid search cross validation. The modelling estimation power is enhanced by considering nonlocal effects and applying machine learning processes, facilitating the detection of ultrasmall inclusions within a poroelastic medium at micro/nanoscales.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

Agricultural practices and ditch size drive microbial community assembly and mediate N- and P-transformation in multistage drainage networks of paddy fields: Insights from a large-scale irrigation district in eastern China.

Agricultural drainage ditches (ADDs) are ubiquitous and regarded as active zones for biogeochemical reactions and microbe-mediated pollutant removal. However, little is known about the microbial distribution and community assembly in ADDs. Here, a typical large-scale irrigation district, including five orders of farmland drainage systems (namely field, sublateral, head, branch, and trunk ditches that could efficiently remove excess water from paddy fields to downstream water bodies), was selected to investigate the ecological processes of microbial communities and N- and P-transformation processes in multistage ditches. We found that scale effects drove distinct environmental gradients and microbial community dissimilarities and that the five ordered ditches were grouped into three clusters (field vs. sublateral vs. head, branch, and trunk ditches). Specifically, the microbial communities in the field ditches located adjacent to the paddy fields were strongly selected by agricultural fertilization and irrigation drainage, enriching salt-tolerant microbes with high nitrification and inorganic P solubilization capabilities. In comparison, the sublateral ditches showed the highest removal performance for total nitrogen (13.28-55.80%) and total phosphorus (9.06-65.07%) during the growth of rice, which was mainly attributed to the enrichment of versatile microbiota (e.g., C39, Nitrospira, and Novosphingobium) as a result of the increased stochastic processes driven by the low redox potential. Notably, the specific gene (i.e., hzsB) for anaerobic ammonium oxidation in sublateral ditches was 1-2 orders of magnitude higher than in adjacent ditches, further contributing to N loss. As field water was discharged into the large-sized head, branch, and trunk ditches, the nutrient levels decreased sharply. At the same time, deterministic processes gained more importance (∼82%), leading to the flourishing of Synechococcus and increasing the potential risk of eutrophication. Overall, the microbial communities in multistage ADDs were co-shaped by agricultural practices and ditch size, which further governed the N and P removal performance. These results provide unique insights into microbiota assembly patterns and dynamics in multistage ADDs and important ecological knowledge for controlling agricultural non-point source pollutants by managing of small-sized ditches.

The Scale Effects of Organometal Halide Perovskites.

Organometal halide perovskites have achieved great success in solution-processed photovoltaics. The explorations quickly expanded into other optoelectronic applications, including light-emitting diodes, lasers, and photodetectors. An in-depth analysis of the special scale effects is essential to understand the working mechanisms of devices and optimize the materials towards an enhanced performance. Generally speaking, organometal halide perovskites can be classified in two ways. By controlling the morphological dimensionality, 2D perovskite nanoplatelets, 1D perovskite nanowires, and 0D perovskite quantum dots have been studied. Using appropriate organic and inorganic components, low-dimensional organic-inorganic metal halide hybrids with 2D, quasi-2D, 1D, and 0D structures at the molecular level have been developed and studied. This provides opportunities to investigate the scale-dependent properties. Here, we present the progress on the characteristics of scale effects in organometal halide perovskites in these two classifications, with a focus on carrier diffusion, excitonic features, and defect properties.

Effects of environmental factors on the river water quality on the Tibetan Plateau: a case study of the Xoirong River, China.

Climate, topography, and landscape patterns affect river water quality through processes that influence non-point source pollution. However, little is known about the response of the water quality of rivers on China's Tibetan Plateau to these environmental factors. Based on the water quality parameters data of the Xoirong River on the Tibetan Plateau in western China, the redundancy analysis and variation partitioning analysis were adopted to determine the main influencing factors affecting river water quality and their spatial scale effects. The major water pollutants were further analyzed using the partial least square-structural equation modeling (PLS-SEM). Another mountainous river with a similar latitude, the same stream order, and low anthropogenic disturbance in central China, the Jinshui River, was also selected for comparative discussion. The results indicated that the overall river water quality on the Tibetan Plateau was superior to that of the Jinshui River. At the catchment scale, the cumulative explanatory powers of the influencing factors of both rivers were greatest. Landscape composition and configuration were the determinant factors for the overall water quality of the two rivers, while the river on the Tibetan Plateau was also significantly affected by climatic and topographical factors. Regarding the main water quality issue, i.e., total nitrogen, agricultural production activities might be the main cause of the river on the Tibetan Plateau. This study unveiled that the river water quality on the Tibetan Plateau is sensitive to climate and topography through comparative studies.

Effectiveness of landscape indicators for explaining the variability of benthic macro-invertebrates in urban streams.

Landscape indicators - measures of land use and land cover - are widely used as proxies for monitoring urban stream conditions, particularly for benthic invertebrates which are often negatively impacted by watershed urbanization. However, multi-scale and nonlinear relationships between benthic macroinvertebrates and landscape configuration derived from fine spatial resolution land cover are not well explored. Here, we developed a series of landscape indicators and assessed their effectiveness in explaining the variability of benthic macroinvertebrate communities in 63 streams across the Greater Vancouver Region in British Columbia, Canada. We asked: 1) How effective are multi-scale landscape indicators in explaining the variability of instream benthic macroinvertebrates? 2) Does the explanatory power of landscape indicators vary at different spatial scales? 3) Do different urban forest classification schemes and their spatial configurations impact the explanatory power of landscape indicators? We developed high spatial resolution (5-m) landscape indicators and evaluated their utility in statistical models explaining taxa richness, instream benthic indices of biological integrity (B-IBI), % Ephemeroptera, Plecoptera, and Trichoptera (EPT), and % Oligochaetes. For all benthic responses, landscape indicators measured at the watershed scale explained 5-25% more variation than riparian-based indicators. Combining indicators mapped at multiple scales further improved the explanatory power of landscape indicators for % EPT and % Oligochaetes, ultimately explaining over 70% of the variability of benthic macro-invertebrates in streams. Distinguishing deciduous and coniferous forest types improved the explanatory power of landscape indicators in a riparian model for B-IBI by 10%. When considering the spatial arrangement of land cover, patch density of forests in the surrounding watersheds of stream explained as much as 47% of the variability in % Oligochaetes. Our results highlight the importance of investigating nonlinear relationships between benthic macroinvertebrates and landscape configuration. This monitoring approach is transferable across cities interested in maintaining the ecological health of urban streams while supporting urban expansion and growth.

Shape Memory Alloy (SMA) Actuators: The Role of Material, Form, and Scaling Effects.

Shape memory alloys (SMAs) are smart materials that are widely used to create intelligent devices because of their high energy density, actuation strain, and biocompatibility characteristics. Given their unique properties, SMAs are found to have significant potential for implementation in many emerging applications in mobile robots, robotic hands, wearable devices, aerospace/automotive components, and biomedical devices. Here, the state-of-the-art of thermal and magnetic SMA actuators in terms of their constituent materials, form, and scaling effects are summarized, including their surface treatments and functionalities. The motion performance of various SMA architectures (wires, springs, smart soft composites, and knitted/woven actuators) is also analyzed. Based on the assessment, current challenges of SMAs that need to be addressed for their practical application are emphasized. Finally, how to advance SMAs by synergistically considering the effects of material, form, and scale is suggested.

Simulation of land use trends and assessment of scale effects on ecosystem service values in the Huaihe River basin, China.

Land use demand change in the Huaihe River basin (HRB) and ecosystem service values (ESVs) in watersheds are important for the sustainable development and use of land resources. This paper takes the HRB as the research object, and using remote sensing images of land use as the data source adopts the comprehensive evaluation analysis method of ESVs based on equivalent factors and sensitivity analysis of the performance characteristics of ESV changes of different land use types. The PLUS model is used to predict spatiotemporal land use change characteristics to 2030 combining inertial development, ecological development, and cultivated land development. The spatial distribution and aggregation of ESVs at each scale were also explored by analyzing ESVs at municipal, county, and grid scales. Considering also hotspots, the contribution of land use conversion to ESVs was quantified. The results showed that (1) from 2000 to 2020, cultivated land decreased sharply to 28,344.6875 km2, while construction land increased sharply to 26,914.563 km2, and the change of other land types was small. (2) The ESVs in the HRB were 222,019 × 1012 CNY in 2000, 235,015 × 1012 CNY in 2005, 234,419 × 1012 CNY in 2010, 229,885 × 1012 CNY in 2015, and 224,759 × 1012 CNY in 2020, with an overall fluctuation, first increasing and then decreasing. (3) The ESVs were 219,977 × 1012 CNY, 218,098 × 1012 CNY, 219,757 × 1012 CNY, and 213,985 × 1012 CNY under the four simulation scenarios of inertial development, ecological development, cultivated land development, and urban development, respectively. At different scales, the high-value areas decreased, and the low-value areas increased. (4) The hot and cold spots of ESV values were relatively clustered, with the former mainly clustered in the southeast region and the latter mainly clustered in the northwest region. The sensitivity of ecological value was lower than 1, while the ESV was inelastic to the ecological coefficient, and the results were plausible. The mutual conversion of cultivated land to water contributed the most to ESVs. Based on the multi-scenario simulation of land use in the HRB by the PLUS model, we identified the spatial distribution characteristics of ESVs at different scales, which can provide a scientific basis and multiple perspectives for the optimization of land use structure and socio-economic development decisions.

Scale effects of land use on river water quality: a case study of the Tuojiang River Basin, China.

Assessing the scale effects of land use on water quality is of great significance for effectively controlling nonpoint source (NPS) pollution in river basins. In this study, redundancy analysis (RDA) and stepwise multiple linear regression (SMLR) analysis were applied to assess the effects of land use on water quality across multiscales in the Tuojiang River Basin. All monitoring sections were classified into three groups according to the characteristics of land use and cluster analysis of water quality. Results showed that the improvement in water quality of rivers in the Tuojiang River Basin lies in the emphasis and protection of the small-scale scope. Concomitantly, the linkages between individual water quality parameter and land use were highly dependent on spatial scales and regional basis. For the upstream group A, urban land is the main source of COD and TN pollution, while industrial and rural residential land contributed the most to TP pollution. Water body exhibits favorable effects on ammonia nitrogen due to its absorption and degradation, together with the growth of phytoplankton within it. For group B in the middle-lower reaches, controlling the input of organic fertilizers in paddy field will effectively alleviate COD pollution. Increasing the proportion of grassland near the riparian zone can have a positive effect on TN and TP pollution. It should continue to strengthen the strict supervision of NH3-N concentration in wastewater discharge from industrial enterprises. Our results can provide important information for land use planning and making multiple scale measures for water quality conservation.

Land use and hydrological factors control concentrations and diffusive fluxes of riverine dissolved carbon dioxide and methane in low-order streams.

We analyzed the impacts of land use/land cover types on carbon dioxide (CO2) and methane (CH4) concentration and diffusion in 1st to 4th Strahler order tributaries of the Longchuan River to the upper Yangtze River in China by using headspace equilibration method and CO2SYS program. Field sampling and measurements were conducted during the dry and wet seasons from 2017 to 2019. The average of calculated CO2 partial pressure (pCO2, mean ± SD: 2389 ± 3220 µatm) by CO2SYS program was 1.9-fold higher than the value (mean ± SD: 1230 ± 1440 µatm) 10 years ago in the Longchuan River basin, where the urban land area increased by a factor of 7 times. Further analysis showed that corrected pCO2 by headspace method and dissolved CH4 (dCH4) decrease as the stream order and flow velocity increase. The pCO2 and dCH4 in the wet season was lower than that in the dry season. The explanatory ability of land use types on the variation of corrected pCO2 and dCH4 was stronger at the reach scale than at the riparian and catchment scales in two seasons. Urban land at reach scale further showed much higher explanation on corrected pCO2 and dCH4 than cropland, grassland and forest land in the wet season. The Longchuan River emits approximately 112.5 kt CO2-C and 1.0 kt CH4-C per year, being 1.7-fold of the total lateral export of dissolved inorganic and dissolved organic carbon (68.3 kt C y-1). The findings highlight the scale effects of land use on the observed seasonality in dissolved carbon gases in low-order streams.

Influences of landscape pattern on water quality at multiple scales in an agricultural basin of western China.

Determining the associations between landscape pattern and river water quality and quantifying the abrupt change points of landscape metrics are vital to optimize landscape planning and improve basin water quality. This study took an agricultural basin in western China as a case study. River water quality of 61 sub-basin outlets were monitored during wet and dry seasons from 2020 to 2021. Landscape metrics were extracted at 100 m, 300 m, 500 m riparian buffer and sub-basin scales, respectively. Relationships between water quality and landscape pattern at multiple scales were explored by using redundancy analysis (RDA). Results showed that urban-related landscape metrics served as the primary contributor to degrade water quality during both seasons, followed by cropland-related metrics, which might be attributed to the increase of urban land and reduction of agricultural chemical fertilizer use. Landscape metrics could better explain the water quality variations during wet season than dry season. The explanatory abilities of landscape metrics to overall water quality appeared little difference among spatial scales during wet season, whereas landscape metrics within 100 m riparian buffer had much larger explanatory rate than other spatial scales during dry season. Results of abrupt change point analysis revealed that the abrupt change interval values (ACIVs) of percentage of urban land (PLANDurban) and the largest patch index of urban land (LPIurban) differed among COD, TN, and TP. The recommended threshold values of PLANDurban and LPIurban for COD, TN, and TP management were smaller than 11.0%, 2.5%, and 1.0%, respectively. When the PLANDurban or LPIurban exceeded 19.0%, the TN, TP, and COD pollution would all significantly accelerate. Therefore, a limit value of 19% of PLANDurban and LPIurban, respectively is put forward. From dry season to wet season, the ACIVs of PLANDurban and LPIurban for COD concentration increased, whereas they decreased for TN and TP concentrations. Our results can provide scientific insights into sustainable landscape planning and effective water quality protection in agricultural basins.

Managing landscape patterns at the riparian zone and sub-basin scale is equally important for water quality protection.

Widespread attention has been given to understanding the effect of the landscape pattern on river water quality. However, which spatial scale (riparian zone versus sub-basin) has the greater impact on water quality has long been controversial, since the key metrics that affect water quality varied with spatial scale. Thus, quantifying the spatial scale effects of key landscape metrics on water quality is critical to clarifying which scale of landscape pattern is more conducive to water quality conservation. Here, we adopted variation partitioning analysis (VPA) and random forest models to quantify the landscape pattern impact on water quality at northern Erhai Lake during the 2019 rainy season (early, mid, and late), and comprehensively analyze the key landscape metrics on different scales. The results revealed that the riparian zone and sub-basin scale landscape patterns explained similar water quality variations (difference only 0.9%) in the mid (August) and late rainy season (October), but exhibited a large difference (24.1%) during the early rainy season (June). Furthermore, rivers were primarily stressed by nitrogen pollution. Maintaining the Grassland_ED > 27.99 m/ha, Grassland_LPI > 4.19%, Farmland_LSI < 3.2 in the riparian zone, and Construction_ED < 1.69 m/ha, Construction_LSI < 2.46, Farmland_PLADJ < 89.0% at the sub-basin scale could significantly reduce the TN concentration in the stream. Meanwhile, managing of these metrics can effectively prevent rapid increases of TN in rivers. Moreover, due to the low phosphorus concentration in the rivers, none of the landscape metrics significantly explained the variation in TP. This study explored the spatial scale effect of landscape patterns on water quality and revealed the driving factors of nutrient variation. This study will provide a scientific basis for aquatic environmental management in plateau watersheds.

Effect of multiple spatial scale characterization of land use on water quality.

Land use in uplands is an important factor affecting water quality in its respective catchment, and its influences at the different spatial scales and configurations warrant further investigation. Here, we selected 26 catchments in the upper Han River (China) and sampled the surface water at the outlet of each catchment in four seasons during 2019. Multivariate statistics were used to identify the relationships between land use characteristics in uplands and water quality in river system. The results indicated that chemical oxygen demand (CODMn); pH; dissolved oxygen; electrical conductivity; nutrient, i.e., NH4+-N, NO3--N; and dissolved phosphorus (DP) in rivers displayed significant seasonal variations. Stepwise regression revealed that landscape metrics such as patch density, landscape shape index, and splitting index were important factors influencing water quality in rivers regardless of their spatiality and seasonality. Urban was the most frequently chosen land-use type in the best prediction models, and forest area showed a negative correlation with water quality parameters in most cases for example, DP. Overall, the influence of land use on river water quality was slightly stronger at reach scale than at catchment and riparian scales. Also, nutrients (i.e., NH4+-N, NO3--N, and DP) in rivers were primarily impacted by the land use characteristic at catchment and riparian scales. Our results suggested that multi-scale explorations would help to achieve a fully understanding on the impacts of land use on river water quality.

Price and scale effects of China's carbon emission trading system pilots on emission reduction.

Constructing and adopting a county-level panel dataset containing carbon emission (CO2) and economic information between 2009 and 2017, this paper employs the continuous difference-in-differences (DID) model and is among the first to conduct an evaluation of the CO2 reduction effect of China's emission trading scheme (ETS) pilot markets from the dual perspectives of price and scale. The empirical results emerge that the increase of transaction price and the expansion of transaction volume in ETS pilots have a persistent and significant influence on CO2 reduction. Parallel to this, it is found the rising of transaction price in ETS can be effective on CO2 reduction by improving the energy structure transition, however, optimization of industrial structure and the development of ICT might be the essential channels driven by the expansion of transaction volume. Last, this paper identifies the synergistic effect on different sorts of contaminants and find it is more substantial to those with the gas state. This paper implies that the policymakers should fully excavate the market-oriented environmental regulation tools from transaction price and volume perspective of views for the well achieving the climate ambitions of carbon peak and neutrality.

Exploring the spatial scale effects of built environments on transport walking: Multi-Ethnic Study of Atherosclerosis.

We employed a longitudinal distributed lag modeling approach to systematically estimate how associations between built environment features and transport walking decayed with the increase of distance from home to built environment destinations. Data came from a cohort recruited from six U.S. cities (follow-up 2000-2010, N = 3913, baseline mean age 60). Built environment features included all walkable destinations, consisting of common and popular destinations for daily life. We also included two subsets frequent social destinations and food stores to examine if the spatial scale effects differed by varying density for different types of built environment destinations. Adjusted results found that increases in transport walking diminished when built environment destinations were farther, although distance thresholds varied across different types of built environment destinations. Higher availability of walking destinations within 2-km and frequent social destinations within 1.6-km were associated with transport walking. Food stores were not associated with transport walking. This new information will help policymakers and urban designers understand at what distances each type of built environment destinations influences transport walking, in turn informing the development of interventions and/or the placement of amenities within neighborhoods to promote transport walking. The findings that spatial scales depend on specific built environment features also highlight the need for methods that can more flexibly estimate associations between outcomes and different built environment features across varying contexts, in order to improve our understanding of the spatial mechanisms involved in said associations.