Different Climate Zones In China Research Articles

Source tracing the bedroom bacteria across different climate zones in China during the heating season

Approximately 1/3 of people’s time is spent in bedrooms. Regulating the health implications arising from the bedroom bacterial community demands an in-depth understanding of both the bacterial composition and the influential factors. This study employed high-throughput 16S rRNA amplicon sequencing to characterize the bacterial community in 23 residential bedrooms across five climate zones in China. Our findings reveal that the bacterial richness and diversity were highest in the Hot-Summer-Cold-Winter (HSCW) zone, possibly due to its lowest indoor temperature during the heating season. Employing an advanced source tracing algorithm, we identified ventilation rate as the dominant factor affecting outdoor bacterial presence, with each additional air change per hour (ACH) increasing the outdoor bacterial abundance by 13.7%. The integumentary system was the largest contributor to the occupant-associated bacteria, particularly in the residences located in the Severe Cold and Cold zones. Our study provides valuable insights into the diverse bacterial communities in residential bedrooms across various climate zones in China, elucidating the key factors and sources that contribute to shaping these complex microbial ecosystems.

Spatial-temporal variation of water vapor scale height and its impact factors in different climate zones of China

Water vapor scale height reflects the vertical distribution of water vapor in the atmosphere, which is a vital parameter in tropospheric zenith wet delay (ZWD) modeling and GNSS meteorology. This study accurately calculated the long-term water vapor scale height using 89 radiosonde stations in China, analyzed the characteristics in temporal ad spatial variations and explored the impacts factors of the water vapor scale height from the perspective of the climate zones. The numerical results indicate that the water vapor scale height in China exhibits annual and semiannual variations with a rising-then-decreasing trend across the four seasons. A relatively larger value for the water vapor scale height were observed in the subtropical monsoon climate and the temperate continental climate zone, in which the values are greater than 2.35 km, while the values in temperate monsoon climate and the alpine plateau climate zone are relatively small. In addition, the water vapor scale height in different climate zones shows different trends, with a downward trend appeared in the subtropical monsoon climate and the alpine plateau climate zone, while an upward trend was observed in the temperate monsoon climate and the temperate continental climate zone. Furthermore, a positive correlation between water vapor scale height and temperature, pressure, and atmospheric precipitable water was found in China, with a varied degree of correlation in different climate zones.

The influence patterns of carbon flux in different climatic zones in China —Based on the complex network approach

Research on ecosystem carbon flux can provide important methodological and strategic support for climate change mitigation. The existing studies focus on the calculation of carbon flux, ignoring the intertwined effects between regions. The quantification and analysis of the interaction patterns of carbon flux is crucial for understanding the global carbon cycle process, forecasting and coping with climate change. In this study, carbon flux network model sequences are established based on complex network theory using carbon flux data spanning from December 1, 2005, to November 30, 2020. The time delay effect is introduced to accurately quantify the influence patterns of carbon flux within climate zones across China. The findings indicate that the probability distribution function of the link weights during the various seasons of each year exhibits a bimodal distribution with distinct positive and negative components. The delay probability distribution function reveals the significant impact of delay effects, which are especially pronounced and mostly significant long-term lag effects in nodes with negative weights. Further, the results of the interactions of carbon flux among climate zones demonstrate that changes in carbon flux in the plateau and southern temperate regions have either positive or negative impacts on other climate zones. Therefore, controlling carbon flux changes in these climatic zones can effectively optimize the distribution of carbon flux. The modeling framework and results presented in this paper provide useful insights for the regulation and distribution optimization of carbon flux in China.

An interpretable framework for modeling global solar radiation using tree-based ensemble machine learning and Shapley additive explanations methods

Machine learning techniques provide an effective and cost-efficient solution for estimating solar radiation for solar energy utilization. However, the reported machine learning-based solar radiation models fail to offer comprehensive explanations for their outputs. Therefore, this study aims to tackle this issue by developing machine learning models that are both accurate and interpretable. To achieve the objective, this study evaluated the performance of tree-based ensemble algorithms, using optimized combinations of model input parameters for different climate zones in China. The results showed that the extreme gradient boosting (XGBoost) models demonstrated the highest overall accuracy, model stability, and generalization ability. At the national scale, the developed XGBoost models yielded an average R2, MAE, and RMSE of 0.939, 1.226 MJ/m2, and 1.663 MJ/m2, respectively, showing significant improvements of 2.13–27.78% in RMSE compared to recently reported models. Most importantly, the state-of-the-art SHapley Additive exPlanations (SHAP) technique was integrated with the developed XGBoost models to enhance model interpretability in terms of global and local feature importance, as well as the interaction effects between model features. The results of the SHAP value analysis demonstrated the robustness of sunshine duration in modeling global solar radiation, revealing thresholds where its values undergo a shift from negative to positive effects on model output. SHAP interaction values illustrated the interaction effects among features in the developed solar radiation model, uncovering the model's complex non-linear relationships. Additionally, this study provided explanations for individual instances based on the SHAP method. Overall, this study provided an accurate, reliable, and transparent machine learning model and an enlightening framework for modeling global solar radiation at sites without observations.

Effectiveness of enhanced roof ventilation unit (ERU) based on venturi cap in different wind environments and new evaluation models: A numerical study

Reasonable building ventilation design can effectively improve indoor thermal comfort and reduce energy consumption. Therefore, an enhanced roof ventilation unit (ERU) was developed for this study, and its performance and influence law under various wind speeds and directions were explored through numerical simulation. Additionally, a new evaluation method for ERU was proposed through data fitting, and applicability was verified for different climate zones in China. The results showed that: (1) With a maximum difference of 3.11 °C, the ERU performed best in the N direction and poorest in the SW direction for indoor temperature. Furthermore, the impact of wind directions was more evident than wind speeds. (2) The wind speed affected the volume flow rate significantly in the NE direction (7.77 m3/s) and insignificantly not in the SE direction (0.32 m3/s). Nevertheless, the performance was the opposite in the NE and SE directions when the wind speed increased from 0.5 m/s (3) The air age performed best in the NE and worst in the SE directions. As wind speeds surpassed 2.0 m/s, the air age variation steadily stabilized in various wind directions. (4) The fitted equation for indoor temperature has applicability in typical cities in five climate zones, and the fitted equation for volume flow rate is applicable in four climate zones except the hot summer and warm winter zone. The study results can provide references for the ERU to improve indoor thermal ventilation, contributing to sustainable building energy efficiency.

Study on the Influence of the Application of Phase Change Material on Residential Energy Consumption in Cold Regions of China

As the impact of climate change intensifies, meeting the energy demand of buildings in China’s cold regions is becoming increasingly challenging, particularly in terms of cooling energy consumption. The effectiveness of integrating phase change material (PCM) into building envelopes for energy saving in China’s cold regions is unclear. The aim of this study is to assess the effectiveness of PCM integration in building enclosures for energy efficiency in these regions. The research monitored and recorded indoor temperature data from typical residential cases from May to September. This measured data was then used to validate the accuracy of EnergyPlus22-1 software simulation models. Subsequently, the calibrated model was utilized to conduct a comparative analysis on the effects of PCM on indoor temperatures and cooling energy consumption across these regions. The results of these comparative analyses indicated that PCM can alleviate indoor overheating to varying degrees in severe cold regions of China. Focusing on north-facing bedrooms, applying PCMs reduced the duration of overheating in non-air-conditioned buildings in severe cold regions of China by 136 h (Yichun), 340 h (Harbin), 356 h (Shenyang), and 153 h (Dalian). In terms of cooling energy consumption, the energy saved by applying PCMs ranged from 1.48 to 13.83 kWh/m2. These results emphasize that the performance of PCM varies with climate change, with the most significant energy-saving effects observed in severe cold regions. In north-facing bedrooms in Harbin, the energy-saving rate was as high as 60.30%. Based on these results, the study offers guidance and recommendations for feasible passive energy-saving strategies for buildings in severe cold and cold regions of China in the face of climate change. Additionally, it provides practical guidance for applying PCMs in different climatic zones in China.

Applicability and improvement of different potential evapotranspiration models in different climate zones of China

BackgroundAccurate estimation of potential evapotranspiration (PET) is the key for studying land-air interaction hydrological processes. Several models are used to estimate the PET based on standardized meteorological data. Although combination-based models have the highest level performance estimation of PET, they require more meteorological data and may therefore be difficult to apply in areas lacking meteorological observation data.ResultsThe results showed significant differences in the spatial trends of PET calculated by different models in China, the Doorenbots–Pruitts model revealed the highest PET (1902.6 mm), and the Kuzmin model revealed the lowest PET (349.6 mm), with the largest difference being 5.5 times. The Romanenko and the Rohwer models were the recommended temperature-based and aerodynamic-based models. On the other hand, the Abtew model was more suitable for arid and semi-arid regions, while the Priestley–Taylor model was more suitable for humid regions. Combination-based models revealed ideal calculation accuracies, among which the Penman–Monteith model was the best option for PET calculation.ConclusionsThe accuracy range of Romanenko, Rohwer, Abten, Priestley Taylor, and Penman Monteith models improved in MPZ and TCZ is higher than that improved in TMZ and SMZ. This does not mean that the improved models have higher accuracy in MPZ and TCZ than in TMZ and SMZ. On the contrary, the original model performed poorly in MPZ and TCZ, so the improved accuracy was relatively large. The unimproved model was already more suitable in TMZ and SMZ, so the improved accuracy was relatively small. Therefore, regional calibration of the PET models can improve the accuracy and applicability of PET calculation, providing a reference for studying hydrological processes in different climatic zones.

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants’ thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants’ comfort.

Influence of Different Forms on BIPV Gymnasium Carbon-Saving Potential Based on Energy Consumption and Solar Energy in Multi-Climate Zones

In this study, the influence of the gymnasium building form on energy consumption and photovoltaic (PV) potential was investigated to address its high energy consumption and carbon emissions issues. Five cities in different climate zones in China (Harbin, Beijing, Shanghai, Guangzhou, and Kunming) were selected as case study environments to simulate and calculate the energy use intensity (EUI), photovoltaic power generation potential (PVPG), and CO2 emission (CE) indicators for 10 typical gymnasium building forms, while also assessing the impact of building orientation. This study found that changes in gymnasium building orientation can cause a 0.5–2.5% difference in EUI under the five climatic conditions, whereas changes in building form can cause a 1.9–6.4% difference in EUI. After integrating a building-integrated photovoltaic (BIPV) system on the roof, changes in building orientation and form can lead to a 0–14.4% and 7.6–11.1% difference in PVPG and a 7.8–68.1% and 8.7–72.0% difference in CE. The results demonstrate that both the choice of form and orientation contribute to a reduction in carbon emissions from BIPV gymnasiums, with the rational choice of form having a higher potential for carbon savings than orientation. These research findings can guide the initial selection of gymnasium designs to pursue low-carbon goals.

Urban 2D and 3D morphology and the pattern of ozone pollution: a 68-city study in China

ContextAir pollution significantly impacts urban sustainable development and public health. Urban ozone pollution (UOP) is currently one of the most challenging tasks for urban air pollution control, and is possibly linked to urban morphology. However, the effect of urban two-dimensional (2D) (coverage or density, etc.) and three-dimensional (3D) (density + height, etc.) morphology on the UOP concentration remains unclear.ObjectivesThe objective of this study was to explore the influence of urban morphology on UOP concentration and provide useful information to control urban air pollutants.MethodsFirst, based on building height and remotely sensed UOP data from 68 Chinese cities, the general spatial pattern of urban 3D morphology and UOP was detected across different climate zones in China. Then, this study used variance decomposition to investigate the contribution of 2D and 3D urban morphology to UOP in China.ResultsThe study showed that China's urban morphology was dominated by Medium Rise & Medium Density (MRMD). Large cities had higher UOP levels in summer, especially for the urban morphology with Low Rise & High Density (LRHD). Further, UOP concentrations were substantially higher in the southern temperate zone than in other climatic zones. Anthropogenic factors (rather than natural factors) were always the dominant factors influencing UOP across different seasons; specifically, urban 2D and 3D morphology can explain 40% of UOP variation. The effects of urban 3D and 2D morphologies on UOP concentrations varied seasonally. Urban 2D morphology dominated in spring, whereas 3D morphology dominated in winter.ConclusionsOur study elucidates the effect of urban morphology on UOP and provides insights for sustainable urban development.

Collaborative Optimized Design of Glazing Parameters and PCM Utilization for Energy-Efficient Glass Curtain Wall Buildings

Glass curtain walls (GCWs) have become prevalent in office buildings, owing to their lightweight and modular characteristics. However, their lower thermal resistance, compared to opaque walls, results in increased energy consumption. Incorporating phase-change materials (PCMs) provides a viable solution through which to address the susceptibility of GCWs to external conditions, thus enhancing thermal performance and mitigating energy concerns. This study delves into the influences of the glazing solar heat gain coefficient (SHGC), the glazing heat transfer coefficient (U-value), and PCM thickness on the energy performance of buildings. Using Design Builder (DB) software version 6.1.0.006, a multi-story office building was simulated in different climatic zones in China, covering the climatic characteristics of severe cold, cold, hot summer and warm winter, cold summer and winter, and mild regions. The simulation results quantitatively elucidated the effects of the glazing parameters and the number of PCMs on thermal regulation and energy consumption. A sensitivity analysis identified the glazing SHGC as the most influential factor in energy consumption. Additionally, by employing Response Surface Methodology (RSM), the researchers aimed to achieve a balance between minimal building energy consumption and economic cost, ultimately determining an optimal design solution. The results demonstrated significant energy savings, ranging from 20.16% to 81.18%, accompanied by economic savings, ranging from 15.78% to 79.54%, across distinct climate zones in China.

Climatic applicability of indirect evaporative cooling strategies for data centers in China

Modern digital developments have propelled data center (DC) to prominence, with the cooling requirement being an important driver of its energy consumption. This study explores the climate application potential of indirect evaporative cooling (IEC) technology, which utilizes water evaporation for cooling. The IEC technology is considered as a promising avenue for energy-efficient DC cooling system. This study reveals essential insights for optimizing DC cooling performance by analyzing different IEC operation modes, including dry mode, wet mode, and cascading hybrid mode. The selection of operation mode is closely related to climatic conditions, DC working conditions, and IEC cooling efficiency. Higher DC supply air temperatures extend dry mode cooling hours and decrease cascading hybrid mode hours. It enhances energy savings through better utilization of natural free cooling resources. Elevating IEC cooling efficiency expands dry mode cooling hours while reducing reliance on mechanical cooling, contributing to improved power usage effectiveness (PUE) and energy conservation. The analysis is based on a typical data center and considers representative cities in different climate zones of China, emphasizing the importance of reducing the PUE and energy consumption of the DC by adjusting the DC supply air temperature and improving the IEC cooling efficiency. This work provides a useful reference for customizing DC cooling strategies according to various climate differences, optimizing energy efficiency and promoting sustainable development.

Sampling origins and directions affect the minimum sampling area in forest plots

AbstractQuestionsThe minimum sampling area (minimum area) is the smallest space that reflects species composition and characteristics of a plant community. The quantitative concept of minimum area is often estimated using species–area relationships (SARs) and has become the classical foundation for managing protected areas. However, sampling designs to determine the minimum area in different forest types have not been systematically evaluated.LocationChina.MethodsWe used tree census data from three forest dynamic plots, each with a size of 25–60 ha, in different climatic zones in China to determine the minimum areas of woody plants and to analyze the effects of species richness and topographic heterogeneity on the minimum areas by changing sampling origin and direction.ResultsWe found that mainly sampling design affects the estimation of woody plant species richness and required minimum area in different forest types. The estimated size of the minimum areas required was several hectares and varied significantly with sampling origin and direction, and showed a difference of approximately 1.5–2 times in the forest plots. Topographic heterogeneity significantly affected the minimum area through changes in species composition.ConclusionsSampling origin and direction should be considered when using SARs to estimate the minimum area and species diversity in communities. Such a comprehensive approach of sampling can contribute to a better understanding of vegetation characteristics and the minimum area required for a conservation census in heterogeneous environments.

Parametric study and sensitivity analysis on thermoelectric energy generation of building integrated photovoltaic facades in various climatic zones of China

Building Integrated Photovoltaic facades (BIPV facades) represent state-of-the-art building envelope systems generating both electrical and thermal energy. While previous research predominantly focused on electricity generation, this study investigated impact of important design parameters on all useful thermoelectric energy, including electricity, air heat gains, and indoor heat dissipation. A novel BIPV facade model has been developed in TRNSYSvalidated by extensive long-term experimental data. Through numerical simulations conducted across different climatic zones in China, parameters impact regularities were investigated with sensitivity analysis. Results revealed that influence of parameters on electricity generation is relatively modest, with sensitivity indices ranging from 0 % to 2.4 %. BIPV facade height and building insulation U-value impact demonstrate monodirectional linear pattern, while air channel width impact exhibits extremums. For all climatic zones, both electricity generation and air heat gains are most sensitive to air channel width, with sensitivity index ranging from 1.2 % to 2.4 % and 38.3 %–42.3 %, respectively. Sensitivity index of indoor heat gains to air channel width decreases from 51.2 % to 20.9 % from north to south, while sensitivity to building insulation U-value increases from 23.8 % to 85.3 %. Research provides innovative perspective on the design of BIPV facades for comprehensive thermoelectric energy utilization with design parameter priority clarified.

Effect of the spatial form of outpatient buildings on energy consumption in different climate zones in China.

Under the influence of global epidemics and the need for urban expansion, many outpatient buildings have been rapidly constructed, but the problem of high energy consumption has been neglected. There is a lack of research on the impact of outpatient building forms on energy consumption in different climate zones. Many studies have demonstrated that the energy consumption of a given building can be greatly reduced by adopting a reasonable spatial form design at the early stages of design. Therefore, if architects choose a reasonable spatial form, this could effectively reduce energy consumption. In this study, outpatient building cases in China were summarized, and three typical spatial forms were proposed: the centralized, corridor, and courtyard forms. The DesignBuilder tool was used to simulate and analyse the typical building energy consumption in different climate zones. The results showed that the corridor form (southwards) should be chosen in the severe cold zone, the centralized form (southwards) should be chosen in the cold zone and the hot summer and cold winter zone, the centralized form (northwards) should be chosen in the hot summer and warm winter zone, and the centralized or corridor form can be chosen in the warm zone. The results of this study could provide a reference for energy-efficient design of outpatient buildings in China and other regions with similar conditions and could help architects quickly select reasonable spatial forms at the early stages of design.

Incorporating dynamic schemes of canopy light extinction coefficient improves transpiration model performance for fruit plantations

The light extinction coefficient (C) describes the efficiency of light interception by a plant canopy, and is a key parameter commonly used to partition radiant energy between a vegetation canopy and the soil surface in several important transpiration models. The C has been observed to vary considerably in the field, but is often parametrized as a fixed constant value, resulting in large potential uncertainty in transpiration estimation. We hypothesized that C changes with leaf area index (LAI) and environments, and that accurate characterization of the C variation pattern would improve transpiration modelling. To test these hypotheses, the relationships between measured C and potential influencing factors were explored for three different fruit plantations in different climate zones in China. Based on these relationships, a new method was proposed to capture C dynamics that considered both LAI and environmental factors. Additionally, 16 C schemes (15 dynamic C schemes and one fixed C scheme) were individually embedded in the Penman-Monteith model, and comprehensive comparisons were made to determine the most effective C scheme for simulating transpiration based on a Bayesian framework. Results showed that C displayed clear variations across all sites, and that there were significant relationships of C with LAI and environmental factors. Compared with the model using a fixed C scheme, the model using the best dynamic C scheme significantly improved model performance by increasing estimation accuracy and decreasing model uncertainty. Specifically, the average coefficients of determination (R2) increased from 0.35 to 0.76, 0.82 to 0.85, and 0.90 to 0.93 for the orange orchard, the jujube orchard, and the grape greenhouse, respectively. Additionally, the average mean relative errors (MRE) decreased by 54.99%, 26.62%, and 13.95%, respectively, and the average uncertainty band widths (B) decreased by 46.81%, 21.74%, and 11.43%, respectively. Model performance improvement was more significant at sites with more serious environmental stresses. The results of our study emphasize the necessity for considering dynamic C patterns in water consumption estimation, particularly for regions facing severe abiotic stresses that are likely to occur in many regions under future climate conditions.

One-year dataset of hourly air quality parameters from 100 air purifiers used in China residential buildings

Household air purifiers have been widely used as an effective approach to improving indoor air quality. Air purifiers can automatically record indoor air quality parameters, providing valuable data resources for in-depth data-driven analysis. This work presents a one-year hourly indoor air quality dataset collected by household air purifiers in 100 residential homes in 18 provinces across 4 different climate zones in China. The data were collected from July 1, 2021, to July 1, 2022. The concentrations of formaldehyde, PM2.5, TVOC, temperature, relative humidity, on/off status and the airflow rate of air purifiers during operations were recorded hourly. The data were carefully screened with possibly missing values imputed using chained equation-based methods if any. The dataset provides a comprehensive and detailed picture of the indoor air quality in residential buildings, enabling evaluations on the cleaning effect of air purifiers, the impact of outdoor climate change on indoor air quality, and the future trends in indoor human behavior.

Assessing forecasting performance of daily reference evapotranspiration: A comparative analysis of updated temperature penman-monteith and penman-monteith forecast models

Accurate forecast of reference evapotranspiration (ET0) is essential for effective water resource management and efficient irrigation scheduling. The Penman-Monteith model (PM) recommended by FAO56 is widely used as the standard method for ET0 forecasting, but PM model application is often limited by the absence of forecasted meteorological variables, especially solar radiation (Rs). Previous studies have proposed two types of models based on temperature and sunshine duration to estimate Rs. However, there is currently a lack of comprehensive comparative analysis research to evaluate the performance and applicability of these two types of models combined with weather forecast data for ET0 forecasting using the PM model. To address this issue, we selected China as the research area, which has complex climate zones and an uneven distribution of water resources. The forecasting results of Rs from temperature-based models (M1–M8) and a sunshine duration-based model (M9) are input independently into the PM model for ET0 forecasting. The updated PM model is named PMTM1–PMTM8 and PMF, respectively. We conducted a comprehensive and analytical assessment of the updated PMTM1–PMTM8 model, the PMF model and the Hargreaves-Samani (HS) model in different climate zones of China. The results showed that the accuracy of the M1–M8 and the M9 for forecasting Rs decreased as the forecasting period increased. The accuracy of the M9 was higher than that of M1–M8 in the overall accuracy in the subtropical monsoon climate (SMZ). Both the updated PMTM1–PMTM8 and PMF models were utilized to evaluate the ET0 forecasting performance in all five zones. The PMTM3 model exhibited the highest accuracy, with RMSE and MAE ranges of 0.671–1.572 mm d−1 and 0.532–1.365 mm d−1, respectively. In contrast, the PMF model displayed RMSE and MAE ranges of 0.690–1.590 mm d−1 and 0.641–1.437 mm d−1, respectively. Compared to the PMF model, the updated PMTM1–PMTM5 model showed higher accuracy in forecasting ET0 in the plateau mountain climate, temperate continental climate, temperate monsoon climate, and tropical monsoon climatic zones, but was slightly less accurate in the SMZ. Moreover, both models outperformed the Hargreaves-Samani (HS) model in terms of ET0 forecasting accuracy. Specifically, the updated PMTM1–PMTM5 model demonstrated improved accuracy compared to the temperature-based model HS model across various climate zones, with reductions in RMSE and MAE ranging from 0.117 mm d−1 to 0.616 mm d−1and 0.012 mm d−1 to 0.450 mm d−1, respectively. Overall, the updated PMTM3 model was better than the PMF and thus this model was recommended for daily ET0 forecasting for the near-future at all climate regions across China.

Ideal thermochromic smart window in a south-facing office room of China considering daylighting and energy performance

ABSTRACT Thermochromic (TC) smart window which allows modulating the transmission of solar heat energy and sunlight in response to environmental conditions has great potential for improving the building energy and daylighting performance simultaneously. In this study, the multi-objective optimization method is used to determine the ideal optical properties of TC windows. Parametric assessment is firstly conducted to investigate the influence of several crucial parameters. Multi-objective optimization is then carried out by applying Non-dominated Sort Genetic Algorithm-III, maximizing daylight availability and building energy efficiency. Finally, the decision-making of the Pareto frontier is performed to achieve the ideal TC windows in 32 representative cities in different climatic zones of China. Results demonstrate that increasing the luminous transmittance at low-temperature and decreasing luminous transmittance modulation ability are beneficial to daylighting and energy performance. Lower solar transmittance at low-temperature contributes to building energy savings in Beijing, Shanghai, Guangzhou and Kunming, except for Harbin. Higher solar transmittance modulation ability is desired for building energy efficiency. The optimum value for the transition temperature is in the range of 23.67–38.85°C. The building energy consumption can be reduced by 13.01%, and the desired daylighting hours can be improved by 8.90%, relative to the clear double-glazed windows.

Vegetation response to changes in climate across different climate zones in China

Vegetation growth is sensitive to climate change. The complex climate types of China pose great challenges to the sustainable management of vegetation on global change. Therefore, this study used Enhanced Vegetation Index (EVI) as an indicator to explore the spatiotemporal dynamics of vegetation and their driving factors in different climatic zones of China to provide theoretical support for sustainable vegetation management in different climate zones in the future. The results showed that vegetation exhibited considerable clustering patterns in the country, with high and low values concentrated in the eastern and western regions, respectively. From 2001 to 2020, both at regional and pixel scales, vegetation in China showed a significant greening trend. EVI displayed a noticeable increase within temperate and subtropical areas. The only exception is observed in the eastern coastal area of the North China Plain and Yangtze River Delta region, which experienced evident degradation trend. During this period, China's climate showed an overall trend towards warming and humidification with drying trends observed mainly over the western regions. The impact of climate changes resulted in EVI dynamics that vary over time and space. The vegetation change in China was mainly derived by changes in precipitation and radiation rather than temperature, especially in temperate and subfrigid regions. Precipitation was the main driving factor for vegetation greening in tropical and temperate regions, while radiation and temperature were the dominant climate factor for vegetation greening in subfrigid and subtropical regions, respectively. When precipitation was no longer a limiting factor for vegetation growth, the effect of temperature or radiation increases. In addition, the positive impact of precipitation on plant growth in temperate regions was much greater than that of radiation and temperature, and this difference was much greater than in tropical, subtropical, and subfrigid regions.