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Window opening behavior in residential buildings has important theoretical significance and practical value for improving energy conservation, indoor thermal comfort, and indoor air quality. Climate and cultural differences may lead to different window opening behavior by residents. Currently, research on residential window opening behavior in northwest China has focused on indoor air quality, and few probabilistic models of residential window behaviors have been established. Therefore, in this study, we focused on an analysis of factors influencing window opening behavior and the establishment of a predictive model for window opening behavior. Four typical residential buildings in different locations and building types in Xi'an were selected. The indoor and outdoor environments and window opening states were measured. Subsequently, a multivariate analysis of variance was used to determine the factors that had a significant effect on window opening behavior. Single- and multiparameter logistic regression models for window opening behavior were established. Of all the measured factors, we found that indoor temperature and CO2 concentration, outdoor temperature, and relative humidity had significant effects on window opening behavior, and indoor relative humidity and noise did not. Meanwhile, the temperature was positively correlated with the window opening probability, whereas indoor CO2 concentration and outdoor relative humidity were negatively correlated. The prediction accuracy of the multiparameter model was promising, at almost 75%, and the model can provide theoretical support for modelling residential buildings in Xi'an. [ABSTRACT FROM AUTHOR]

With the rapid development of new energy sources and the increasing proportion of electric vehicles (EVs) connected to the power grid in China, peak load regulation of power systems will face severe challenges. Therefore, in this study, we analyzed the relationship between the electricity consumption characteristics of EVs and the peak load regulation (PLR) mechanism of power systems, and we proposed an operation mode for virtual power plants with EVs to participate in the auxiliary service market and facilitate deep peak load regulation in the thermal power units. Based on the electricity demand‐side management theory and cost‐benefit analysis method, we constructed a decision model for economic deep peak load regulated operation (DPLR) of the auxiliary thermal power units in a virtual power plant with EVs, aiming to optimize the operation efficiency. The case study showed that a virtual power plant that included EVs can effectively reduce the total PLR cost of the system and the peak valley difference of the net load as well as improve the economic benefits of the thermal power units. The results indicated that the virtual power plant had improved economic efficiency. Therefore, the results of this research can help improve the PLR capacity of the grid and significantly promote the consumption of intermittent renewable energy. [ABSTRACT FROM AUTHOR]

Biological traits analysis (BTA) can help identify the effect of various contaminants on functional trait composition of macrobenthos. However, the effects of bioavailable heavy metals on functional traits of macrobenthos communities remain to be examined. We sampled macrobenthos communities and assessed environmental variables over gradients of heavy metal pollution in Swan Lagoon, China. The RLQ and fourth-corner approaches were used to investigate the response of functional traits to heavy metal pollution. Our findings suggested that macrobenthic functional traits can be used to distinguish the effects of heavy metals and other environmental variables and isolate the corresponding species associated with heavy metal contamination. The macrobenthos at highly contaminated sites comprised taxa of sub-surface deposit-feeders, second-order opportunistic species, and tube-builders, mainly represented by the polychaeta Cirriformia tentaculata and Cirratulus chrysoderma. At less contaminated sites, indifferent species, species attached to seagrass, and crawlers were observed. The results confirm that BTA can provide new insights into the response of macrobenthic functional traits to heavy metal pollution in coastal lagoons. Image 1 • Macrobenthos functional trait responses to heavy metal pollution have rarely been assessed. • Functional traits can differentiate the effects of heavy metals and other environmental variables. • Heavy metal pollution may cause clear functional trait changes in macrobenthic communities. [ABSTRACT FROM AUTHOR]

This study was performed to determine the distribution and chemical fractions of five heavy metals (Cd, Cr, Cu, Pb, and Zn) in sediment from three sampling areas in Swan Lagoon, and their relation to the physiochemical properties of sediment were explored. The results revealed that Cd in sediment from the sand part (SP), muddy sand part (MSP) and sand muddy part (SMP) were potentially highly susceptible and bioavailable since the exchangeable fractions were 21.0%, 27.4%, and 32.1%, respectively, of the total concentrations. A portion of Pb and Zn were observed as reducible fractions owing to their affinity to Fe-Mn; they were able to complex with Fe-Mn oxides and oxyhydroxides in the sediment. A large amount of Cu in the oxidizable fraction may be due to the fact that Cu can easily form stable complexes with organic matter. Cr was overwhelmingly found in the residual fraction, suggesting that Cr was strongly bound in mineral lattices. Enrichment factors (EF) indicated that Cd in three sampling areas suffered severe enrichment, whereas other metals were present in only minor amounts. In addition, Cd may pose a medium to high risk in the MSP and SMP based on risk assessment codes. According to the mean probable effects level quotient, the samples from the MSP and SMP had a 21% probability of toxicity. The multivariate statistical analysis suggested that sediment texture (d0.5, sand and silt), Fe-Mn, and the total organic carbon (TOC) influenced the distribution of the studied metals and their chemical fractions. [ABSTRACT FROM AUTHOR]

China has experienced rapid social and economic development in the past 40 years. However, excessive consumption of fossil fuel energy has caused an energy shortage and led to severe environmental pollution. To achieve sustainable development, China is striving to transform its growth mode. Adopting renewable energy (RE) including solar photovoltaic (PV) power is an effective measure. How to promote the further development of solar PV power under the scenario of China's aspirational target of carbon peak by 2030 and 20% RE ratio in the energy mix remains a theme that need to be addressed. This paper analyzes the potential opportunities and challenges confronting solar PV power in China. The analysis covers the dimensions of political, economic, social, and technological (PEST). The results revealed a significant prospect for the further deployment of solar PV power in the coming decades. The aggressive estimated installed capacity of solar PV power is expected to reach 80+ GW annually. To successfully achieve the goal of 80+ GW, barriers that hinder the further development of solar PV power have to be eliminated. Suggestions for policymakers include maintaining enforceability and continuity of policies, favorable financial supports, mandatory RE quotas for all parties, and supporting fundamental R&D. Suggestions for the solar PV industry include full utilization of integrated applications, set up an after-sales service network, collaborative innovation among the industry chain, and engaging in storage and hydrogen technology. The findings are greatly beneficial for policymakers and the solar PV industry. [ABSTRACT FROM AUTHOR]

Exploring suitable maize straw-return measures is essential for the new double-cropping system of maize (Zea mays L.)–rice (Oryza sativa L.) rotation in the middle reaches of Yangtze River in China, which can increase crop yield by improving soil quality. In this study, four straw-return measures were evaluated by investigating the soil bulk density (BD), organic matter (OM), microbial community, and nutrients from 2016 to 2018. The four straw-return treatments were as follows: (1) no straw-return (CK), (2) only rice straw incorporated into the field (M0Ri), (3) both maize and rice straw incorporated to field (MiRi), and (4) maize straw mulched and rice straw incorporated into the field (MmRi). Compared to CK, two-season crop straw-return treatments changed soil microbial community composition, and increased soil total organic carbon (TOC) and dissolved organic carbon (DOC), microbial biomass carbon (MBC), mineralized nitrogen (Nmin), available phosphorus (P) and exchangeable potassium (K) in the 0–20 cm soil layer by 3.6%, 63.4%, 38.8%, 12.4%, 39.7%, and 21.6%, respectively, averaged across MmRi and MiRi treatments. In addition, MmRi and MiRi increased annual yield by 9.1% and 15.2% in 2017 and 11.7% and 12.9% compared to CK in 2018, respectively. MmRi exhibited superiority in the soil microbial community, enzyme activities, DOC, MBC, Nmin, available P, and exchangeable K in contrast to MiRi. We concluded that MmRi is the best measure to implement for straw-return in maize–rice rotation systems. [ABSTRACT FROM AUTHOR]

Water, energy, and food (WEF) are pivotal resources for the sustainable development of human society. Integrated assessment of the sustainable WEF nexus is essential to enhance resource efficiency and security, but there is a crucial gap to be filled in assessing the coupling relationship among sustainable WEF subsystems and improving multi-sectoral synergy. In this paper, a comprehensive indicator system for sustainable WEF nexus assessment was constructed based on theme-based frameworks and nexus thinking, and the combination weighting method based on game theory (GT-CW), the improved TOPSIS method based on gray relation degree (GRD-ITOPSIS), and the coupling coordination model were proposed for integrated assessment. The sustainability of WEF nexus in 30 regions of China from 2010 to 2019 was assessed and the spatiotemporal differences of the coupling coordination degree of sustainable WEF nexus were analyzed. The results revealed that the sustainability of WEF subsystems evidently affected the overall sustainability of regional WEF nexus. The change range of sustainable WEF nexus in different years was slightly lower than that of a single subsystem. The sustainability of WEF subsystems were highly coupled, and the WEF nexus in each region was within the coordinated development range. However, most eastern regions were at the intermediate coordinated development stage, and some western regions maintained at primary coordinated development stage for a long time. According to the results analysis, specific policy recommendations were proposed. The findings of this study can provide a useful reference for developing countries to improve resource management and promote sustainable development. [Display omitted] (1) Sustainable water-energy-food nexus in 30 regions of China was assessed. (2) Combination weighting method was optimized by game theory. (3) TOPSIS method was optimized by gray relation degree. (4) The synergy among WEF nexus were analyzed by coupling coordination degree. (5) The WEF nexus in each region was within the coordinated development range. [ABSTRACT FROM AUTHOR]

To determine whether China can achieve the commitment of reducing carbon emission intensity in 2030, a general regression neural network (GRNN) forecasting model based on improved fireworks algorithm (IFWA) optimization is constructed to forecast total carbon emissions (TCE) and carbon emissions intensity (CEI) in 2016–2040. Random forests (RF) method is used to select the important carbon emissions influencing factors to reduce data redundancy. The superiority of IFWA-GRNN forecasting model is verified by historical data from 1990 to 2015. The basic as usual (BAU), policy tightening (PT) and market allocation (ML) scenarios are set to forecast the TCE and CEI. The results show that under the BAU scenario, China's CEI reduction commitments in 2020 (40%–45%) can be achieved, but the commitment in 2030 (60%–65%) cannot be achieved. Under the PT and ML scenarios, China can achieve its CEI commitments in 2030, and the TCE will decrease gradually after reaching its peak in 2030. Under the existing macro development planning and policy intensity in China, there are still certain pressures to achieve CEI reduction targets. It is necessary to implement policy adjustment and market mechanism incentives for both energy supply and consumption, optimize power supply structure, promote electric energy substitution, and accelerate the construction of a unified national electricity market, carbon market, etc. Image 10939 • A hybrid carbon emissions forecasting model based on improved general regression neural network is proposed. • The influencing factors of carbon emissions is selected by random forests. • Basic as usual, policy tightening and market allocation scenarios are set, the carbon emission intensity will decrease by 54.7%, 63.4% and 60.8% in 2030 compared to 2005. [ABSTRACT FROM AUTHOR]

Seagrass systems are in decline, mainly due to anthropogenic pressures and ongoing climate change. Implementing seagrass protection and restoration measures requires accurate assessment of suitable habitats. Commonly, such assessments have been performed using single-algorithm habitat suitability models, nearly always based on low environmental resolution information and short-term species data series. Here we address eelgrass (Zoostera marina) meadows' large-scale decline (>80%) in Shandong province (Yellow Sea, China) by developing an ensemble habitat model (EHM) to inform eelgrass conservation and restoration strategies in the Swan Lake (SL). For this, we applied a weighted EHM derived from ten single-algorithm models including profile, regression, classification, and machine learning methods to generate a high-resolution habitat suitability map. The EHM was constructed based on the predictive performances of each model, by combining a series of present-absent eelgrass datasets from recent years coupled with oceanographic and sediment data. The model was cross-validated with independent historical datasets, and a final habitat suitability map for conservation and restoration was generated. Our EHM scheme outperformed all single models in terms of habitat suitability, scoring ∼0.95 for both true statistic skill (TSS) and area under the curve (AUC) performance criteria. Machine learning methods outperformed profile, regression and classification methods. Regarding model explanatory variables, overall, topographic characteristics such as depth (DEP) and seafloor slope (SSL) are the most significant factors determining the distribution of eelgrass. The EHM predicted that the overlapping area was almost 90% of the current eelgrass habitat. Using results from our EHM, a LOESS regression model for the relationship of the habitat suitability to both the biomass and density of Z. marina outperformed better than the classic Ordinary Least Squares regression model. The EHM is a promising tool for supporting eelgrass protection and restoration areas in temperate lagoons as data availability improves., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

Ticks, as obligate blood-sucking ectoparasites, attack a broad range of vertebrates and transmit a great diversity of pathogenic microorganisms. They are considered second only to mosquitoes as vectors of human disease, and the most important vector of pathogens of domestic and wild animals. Of the 117 described species in the Chinese tick fauna, 60 are known to transmit one or more diseases: 36 species isolated within China and 24 species isolated outside China. Moreover, 38 of these species carry multiple pathogens, indicating the potentially vast role of these vectors in transmitting pathogens. Spotted fever is the most common tick-borne disease, and is carried by at least 27 tick species, with Lyme disease and human granulocytic anaplasmosis ranked as the second and third most widespread tick-borne diseases, carried by 13 and 10 species, respectively. Such knowledge provides us with clues for the identification of tick-associated pathogens and suggests ideas for the control of tick-borne diseases in China. However, the numbers of tick-associated pathogens and tick-borne diseases in China are probably underestimated because of the complex distribution and great diversity of tick species in this country.