Assessing the ecosystem services of various types of urban green spaces based on i-Tree eco

Urban green spaces play a crucial role in maintaining urban ecosystem sustainability by providing numerous ecosystem services. How to quantify and evaluate the ecological benefits and services of urban green spaces remains a hot topic currently, while the evaluation is barely applied or implemented in urban design and planning. In this study, super-high-resolution aerial images were used to acquire the spatial distribution of urban green spaces; a modified pre-stratified random sampling method was applied to obtain the vegetation information of the four types of urban green spaces in Luohe, a common plain city in China; and i-Tree Eco model was further used to assess the vegetation structure and various ecosystem services including air quality improvement, rainfall interception, carbon storage, and sequestration provided by four types of urban green spaces. The modeling results reveal that there were about 1,006,251 trees in this area. In 2013, all the trees in these green spaces could store about 54,329 t of carbon, sequester about 4973 t of gross carbon, remove 92 t of air pollutants, and avoid 122,637 m3 of runoff. The study illustrates an innovative method to reveal different types of urban green spaces with distinct ecosystem service productivity capacity to better understand their various roles in regulating the urban environment. The results could be used to assist urban planners and policymakers to optimize urban green space structure and composition to maximize ecosystem services provision

Comparing human activity density and green space supply using the Baidu Heat Map in Zhengzhou, China

Rapidly growing cities often struggle with insufficient green space, although information on when and where more green space is needed can be difficult to collect. Big data on the density of individuals in cities collected from mobile phones can estimate the usage intensity of urban green space. Taking Zhengzhou\u27s central city as an example, we combine the real-time human movement data provided by the Baidu Heat Map, which indicates the density of mobile phones, with vector overlays of different kinds of green space. We used the geographically weighted regression (GWR) method to estimate differentials in green space usage between weekdays and weekends, utilizing the location and the density of the aggregation of people with powered-up mobile phones. Compared with weekends, the aggregation of people in urban green spaces on workdays tends to vary more in time and be more concentrated in space, while the highest usage is more stable on weekends. More importantly, the percentage of weekday green space utilization is higher in small parks and green strips in the city, with the density increasing in those small areas, while the green space at a greater distance to the city center is underutilized. This study validates the potential of applying Baidu Heat Map data to provide a dynamic perspective of green space use, and highlights the need for more green space in city centers

Hydrological effects of urban green space on stormwater runoff reduction in Luohe, China

This paper reveals the role of urban green space (UGS) in regulating runoff and hence on urban hydrological balance. The modeling software i-Tree Hydro was used to quantify the effects of UGS on surface runoff regulation and canopy interception capacity in four simulated land-cover scenarios. The results showed that the existing UGS could mitigate 15,871,900 m3 volume of runoff (accounting for 9.85% of total runoff) and intercept approximately 9.69% of total rainfall by the vegetation canopy. UGS in midterm goal and final goal scenarios could retain about 10.74% and 10.89% of total rainfall that falls onto the canopy layer, respectively. The existing UGS in the Luohe urban area had a positive but limited contribution in runoff regulation, with similar responses in future scenarios with increased UGS coverage. UGS rainfall interception volume changed seasonally along with changing leaf area index (LAI) and precipitation, and the interception efficiency was distinctly different under various rain intensities and durations. The UGS had a relatively high interception performance under light and long duration rain events but performed poorly under heavy and short rain events due to limited surface storage capacities. Our study will assist urban planners and policy-makers regarding UGS size and functionality in future planning in Luohe, particularly regarding future runoff management and Sponge City projects

An effective route to the additive manufacturing of a mechanically gradient supramolecular polymer nanocomposite structure

3D Printing techniques are additive methods of fabricating parts directly from computer-aided designs. Whilst the clearest benefit is the realisation of geometrical freedom, multi-material printing allows the introduction of compositional variation and highly tailored product functionality. The paper reports a proof-of-concept additive manufacturing study to deposit a supramolecular polymer and a complementary organic filler to form composites with gradient composition to enable spatial distribution of mechanical properties and functionality by tuning the number of supramolecular interactions. We use a dual-feed extrusion 3D printing process, with feed stocks based on the supramolecular polymer and its organic composite, delivered at ratios predetermined. This allows for production of a graded specimen with varying filler concentration that dictates the mechanical properties. The printed specimen was inspected under dynamic load in a tensile test using digital image correlation to produce full-field deformation maps, which showed clear differences in deformation in regions with varying compositions, corresponding to the designed-in variations. This approach affords a novel method for printing material with graded mechanical properties which are not currently commercially available or easily accessible, however, the method can potentially be directly translated to the generation of biomaterial-based composites featuring gradients of mechanical properties

Supplementary data for "Application of the T-test and Virtual Fields Method to the Constitutive Response of Materials": T test supplementary data

Images, force data, processed DIC files for the experiments described in "Application of the T-test and Virtual Fields Method to the Constitutive Response of Materials

Tensile testing of polymers: Integration of digital image correlation, infrared thermography and finite element modelling

Tensile tests are often used as part of material characterisation strategies; however, the observed deformation is often complex, and it can be difficult to distinguish the underlying material behaviour from the structural response of the specimen. The objective of the research in this paper was to investigate whether a more accurate calibration of a material model could be obtained by considering not just the global behaviour of the specimen, but also the local strain-time response calculated from full-field displacement information obtained using digital image correlation. Tensile experiments were performed using ISO standard, flat, dog bone specimens. Optical and infra-red imaging were used to calculate full field displacement and temperature maps, and a finite element model of the experiment was produced. These were combined with compression test data from the same material to calibrate a constitutive model, which was shown to describe well the deformation and temperature rise in the specimen. The research demonstrates that it is insufficient to use force-displacement information from tensile experiments to calibrate, or validate, constitutive models of polymers. Further, it demonstrates a more applicable method, which could be further automated in the future

Tensile Testing of Polymers: Integration of Digital Image Correlation, Infrared Thermography and Finite Element Modelling

These data are the raw and processed data to support the paper: "Tensile testing of polymers: Integration of digital image correlation, infrared thermography and finite element modelling"

Experimentally simulating adiabatic behaviour: capturing the high strain rate compressive response of polymers using low strain rate experiments with programmed temperature profiles

Polymers are widely used in applications where they may be subjected to impact loading leading to high strain rate deformation. Plastic work on deformation generates heat in the material. At high strain rates, there is insufficient time for this heat to diffuse out of the material, leading to adiabatic conditions. This leads to post-yield thermal softening in the mechanical response, which modifies the material response and must be considered in Engineering design. In this paper, a novel technique is presented in which this adiabatic self-heating can be simulated experimentally at low strain rates using programmed temperature profiles. We show that, in some cases, these simulations can very accurately capture the mechanical response at higher rates, but in others, the replication is less accurate. This may give further insights into the thermodynamics of high strain rate polymer mechanics. This technique therefore enables a number of avenues of research: the work to heat conversion can be investigated systematically; diagnostic tools that are limited to low strain rates can be applied; and we can better understand material behaviour and thereby improve predictive models

Mechanical response of two different molecular weight polycarbonates at varying rates and temperatures

Polymers are widely used for lightweight design in industrial applications, such as helmets and car bumpers, where the most common causes of failure or damage are dynamic impact events. It is well known that the mechanical response of most polymers is highly dependent on the loading rate and temperature, and that it is not sufficient to use properties measured under static loads in the analysis of dynamic events. However, the time-temperature equivalence phenomenon offers the chance to predict high-rate performance using low-rate data. In this study, information about the constitutive behaviour of two different molecular weight polycarbonates, is obtained in low-rate experiments and then compared with the high-rate response. A master curve of storage modulus constructed from Dynamic Mechanical Analysis data is employed to understand the viscoelastic response under small-strain loading at various frequencies and temperatures. For the large-strain constitutive response, experiments at strain rates from 0.001 s-1 to 3000 s-1 are performed using a conventional crosshead device, hydraulic device, and split-Hopkinson pressure bar. Moreover, experiments at strain rates of 0.01 s-1 and temperatures from -60 to 120 °C are also performed, and the results are compared. This approach can distinguish ’constitutive’ rate dependence from the effects of specimen self-heating due to adiabatic heating under high-rate deformation. Meanwhile, the molecular weight effects on the mechanical response at varying rates and temperatures are also noted