Search

China's foreign capital R&D network has become a core component of the high-quality development of the national innovation ecosystem. Narrowing the spatial difference in the foreign R&D network is considered an essential strategy to improve China's holistic innovation capability. Previous studies only examined the internal factors of the system while mostly ignoring the quantitative analysis of the spatial differences diffusion. Based on the dissipative structure theory, the current paper demonstrates the construction of positive and negative entropy indexes of foreign capital R&D networks in China. Rested on a survey dataset of 340 foreign R&D institutions in 21 Chinese provinces from 2016 to 2017, this paper analyzes the spatial differences and driving factors of the innovation development of foreign capital R&D networks across the country using the Brusselator model. The results show that China's entire deviation degree of foreign capital R&D networks is small. Still, there are significant spatial differences in the deviation between the entropy value and the ideal status of dissipative structure in foreign R&D networks, with the minor deviation-value areas located in the eastern regions. In addition, the central and western regions where the late-mover layout of the foreign R&D network deviates are far from the ideal status. Among them, the western (i.e., Xi'an and Chengdu) foreign R&D network is significantly better than the central innovation performance. It is found that policy traction of talent advantage and intellectual property rights protection positively impact the negative entropy flow of foreign R&D networks in China, which becomes an influential driving force for the future system equilibrium. The paper concludes with several policy implications to guide China's innovation and ecological optimization of foreign capital R&D networks. [ABSTRACT FROM AUTHOR]

The development of urbanization has changed the original land cover and exacerbated the urban heat island effect, seriously affecting the sustainable development of the ecological environment. Research on urban heat island characteristics and land cover changes in five major urban agglomerations in China to provide a reference for preventing thermal environmental risks and urban agglomeration construction planning. This paper estimates the surface urban heat island intensity (SUHII) of the five major urban agglomerations in China from 2003 to 2019 based on Google Earth Engine (GEE) through the urban–rural dichotomy, analyzes their trends through the Sen + M–K trend analysis method, and combines the detrending rate matrix to analyze the impact of land cover type shift on urban heat island change. Research shows that (1) the land cover types of the five major urban agglomerations in China have changed considerably from 2003 to 2019, and all five major urban agglomerations in China experienced varying degrees of urban expansion. (2) The annual average value of SUHII decreases in Beijing-Tianjin-Hebei, Yangtze River Delta, and middle reaches of the urban agglomerations, while the annual average value of SUHII increases in Chengdu-Chongqing and Pearl River Delta urban agglomerations. (3) The spatial composition of land cover types in the five major urban agglomerations in China is highly spatially correlated with urban heat islands, with urban land and bare land urban heat islands being the most pronounced. (4) The land cover type shift has the most significant heat island impact on Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengdu-Chongqing urban agglomerations. (5) The land cover change (LCC) with an increasing trend in SUHII is mainly bare land converted to arable land, and water bodies, grassland, forest land, and arable land converted to urban land. [ABSTRACT FROM AUTHOR]

Bronchopneumonia is the most common infectious disease in children, and it seriously endangers children's health. In this paper, a deep neural network combining long short-term memory (LSTM) layers and fully connected layers was proposed to predict the prevalence of bronchopneumonia in children in Chengdu based on environmental factors and previous prevalence rates. The mean square error (MSE), mean absolute error (MAE), and Pearson correlation coefficient (R) were used to detect the performance of the deep learning model. The values of MSE, MAE, and R in the test dataset are 0.0051, 0.053, and 0.846, respectively. The results show that the proposed model can accurately predict the prevalence of bronchopneumonia in children. We also compared the proposed model with three other models, namely, a fully connected (FC) layer neural network, a random forest model, and a support vector machine. The results show that the proposed model achieves better performance than the three other models by capturing time series and mitigating the lag effect. [ABSTRACT FROM AUTHOR]

Both academics and policymakers regard publicly planned logistics nodes (PPLN) as a potential measure to promote logistics agglomeration and mitigate environmental damage caused by logistics activities. However, such measure may lead to non-linear carbon emission effect from the perspective of agglomeration economy, and empirical evidences are yet to be found to verify this inference. This paper uses DID method and mediating effect models to explore the effects and mechanisms of PPLN on CO2 emissions with panel data from 2000 to 2017 in Chengdu, China. Our findings show that PPLN promotes the agglomeration of both small and large-scale logistics enterprises and increases carbon emissions. In addition, the agglomeration of large-scale logistics enterprises can reduce carbon emissions; the opposite is true for smaller ones. Despite the continuous diminishing of the carbon emission increase, the emission-reduction effect has not been achieved through PPLN operations. Based on the results, the study recommends that the government should appropriately determine the location and scale of PPLN, advocate green construction and industrial upgrading, and adopt differentiated regulatory and incentive measures for enterprises. Logistics enterprises can increase their investment in green technologies and strengthen cooperation with their customers. [ABSTRACT FROM AUTHOR]

Heat action plans should be urgently formulated to enable urban managers, planners, and designers to take appropriate actions for mitigation and adaptation. However, few studies have been conducted to investigate the societal needs and knowledge gaps regarding heat mitigation and adaptation. To address such research gaps, this paper presents an empirical study of 574 questionnaires in Chengdu, China, to explore heat-related impacts, public responses, and driving mechanisms. The results indicated that outdoor activities and work/study were more sensitive to extreme heat than transportation, sleep/rest, and diet. Heat-related impacts on physiological health were at the same level as those on psychological health, where digestive system illness and emotional irritability were the most prevalent physiological and psychological symptoms. Respondents' knowledge of heat-related threats, adaptation awareness, and adaptation knowledge were insufficient, compared with heat severity. The payment willingness among the respondents was not strong and payment amount was not high. Poorer, healthier, and the less affected in outdoor activities were positive groups in payment willingness, while the group which experienced heat-related impacts on outdoor activities could pay more compared with other groups. Overall, these results help to shape the main contents of heat action plans. [ABSTRACT FROM AUTHOR]

Urban ecosystem has become a critical part of ecological security and draws much attention worldwide. It is both a result of natural ecological system development, and also an inevitable outcome of human ecological system development within a certain stage, with the objective of identifying the possible improvement space for unban ecological security evaluation from complex system perspective. Based on the brittle structure model and set pair theory, this paper firstly explored the main research methods of urban ecological security theory and its characteristics, then conducted a theory of complex system brittleness to analyze the urban ecological security brittle factors, brittle primitives, and brittle structure. Furthermore, it conducted a model of urban ecological system brittleness correlation entropy together with a set pair analysis method to discuss its brittleness. And finally, an ecological safety evaluation has been presented based on the empirical case in Chengdu City of China. The theoretical and empirical analysis shows that the brittle correlation entropy of natural subsystem in urban ecological security is the biggest one. The risks from natural subsystem collapse can easily trigger the brittleness of the entire urban system. The corresponding maximum brittle fluctuation entropy is from economic subsystem; it has a largest impact on the entropy change of urban ecosystem. The way of reducing the uncertainty of urban ecological risks is to lower difference degree coefficient in the system. Relevant decision makers should consider to reduce the increasing degree of entropy and eliminate the fluctuation of the brittle factors. Thus, the threats or risks of urban ecological system can be within the acceptable range and under control. An integrated system management combing with brittleness characters of natural, economics, and social subsystem is necessary. It is helpful for the ecological security construction. [ABSTRACT FROM AUTHOR]

Air quality prediction plays an important role in preventing air pollution and improving living environment. For this prediction, many indicators can be employed to reflect the air quality, among which air quality index (AQI) is the most commonly used. However, existing methods are relatively simple and the corresponding prediction accuracy needs to be improved. Particularly, the prediction accuracy is affected by the parameter selection of methods, and the corresponding optimization problems are usually non-convex and multi-modal. Therefore, based on long short-term memory (LSTM) neural network with improved jellyfish search optimizer (IJSO), a novel hybrid model denoted by IJSO-LSTM is proposed to predict AQI for Chengdu. In order to evaluate the optimizing ability of IJSO, other variants of jellyfish search optimizer as well as other state-of-the-art meta-heuristic algorithms are applied to optimize the hyperparameters of LSTM neural network for comparison, and the results confirm that IJSO is more suitable for optimizing LSTM neural network. In addition, compared with other well-known models, the results demonstrate IJSO-LSTM has higher prediction accuracy with root-mean-square error, mean absolute error, and mean absolute percentage error controlling below 4, 3, and 4%, respectively. [ABSTRACT FROM AUTHOR]

Increasing water demand is exacerbating water shortages in water-scarce regions (such as India, China, and Iran). Effective water demand forecasting is essential for the sustainable management of water supply systems in watersheds. To alleviate the contradiction between water supply and demand in the basin, with water demand for economic growth as the main target, a hybrid moving autoregressive and deep neural network model (ARMA-DNN) was developed in this study, and four commonly used statistical indicators (MAE, RMSE, MSE, and R2) were selected to evaluate the performance of the model. Finally, the validity and practicality of the model were verified by taking the Minjiang River basin in China as an example. The results show that (a) the model can predict future water demand more accurately under the conditions of actual water consumption changes, (b) the ideal agricultural production in the Minjiang River Basin is predicted to be reached 2.26 × 109t in 2021, and (c) the highest industrial economic efficiency in Chengdu is 1.51 × 109yuan, while water satisfaction reaches 102%. This means that effective water demand forecasting can alleviate water demand conflicts under climate change conditions to a certain extent. At the same time, watershed managers can develop different water allocation schemes based on the prediction results of the hybrid ARMA-DNN model. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the association between relative humidity (RH) and various cause of mortality, and then quantify the RH-related mortality fraction of low and high RH under the assumption that causal effects exist. Daily cause-specific mortality counts from 2008 to 2011, and contemporaneous meteorological data in three Chinese cities were collected. Distributed lag nonlinear models were adopted to quantify the nonlinear and delayed effects of RH on mortality risk. Low and high RH were defined as RH lower or higher than the minimum mortality risk RH (MMRH), respectively. Corresponding RH-related mortality fractions were calculated in the explanatory analysis. From the three cities, 736,301 deaths were collected. RH (mean ± standard deviation) were 50.9 ± 20.0 for Beijing, 75.5 ± 8.6 for Chengdu, and 70.8 ± 14.6 for Nanjing. We found that low RH in Beijing and high RH (about 80–90%) in Chengdu was associated with increased all-cause mortality risk. Both low and high RH may increase the CVD mortality risk in Beijing. Both low and high (about 80–85%) RH may increase the COPD mortality risk in Chengdu. Low RH (about < 45%) was associated with increased diabetes mortality risk in Nanjing. Effects of extreme low and extreme high RH were delayed in these cities, except that extreme low effects on COPD mortality appeared immediately in Chengdu. The effects of extreme low RH are higher than that of the extreme high RH in Beijing and Nanjing, while contrary in Chengdu. Finally, under the causal effect assumption, 6.80% (95% eCI: 2.90, 10.73) all-cause mortality and 12.48% (95% eCI: 7.17, 16.80) CVD deaths in Beijing, 9.59% (95% eCI: 1.38, 16.88) COPD deaths in Chengdu, and 23.79% (95% eCI: 0.92, 387.93) diabetes mortality in Nanjing were attributable to RH. Our study provided insights into RH-mortality risk, helped draw relative intervention policies, and is also significant for future predictions of climate change effects under different scenarios. [ABSTRACT FROM AUTHOR]

Construction waste (CW) source reduction is a crucial strategy to address the sustainability issue of the construction industry. The economic benefit is a key factor affecting project decision-makers on whether to implement this strategy. However, limited studies analysed the cost–benefit of CW source reduction from a system dynamic perspective. Therefore, by considering the design and construction phase as a whole, this study constructed a system dynamics (SD) model based on the identification of the factors affecting the cost–benefit of CW source reduction to analyse the cost–benefit of CW source reduction. A residential building project in China's Chengdu was used for the study case. The results show that the net benefit of CW source reduction is positive, and BIM implementation, design for standard material size, and building material storage are the three strategies to effectively improve the economic benefits of CW source reduction. Furthermore, the best investment level of CW source reduction was also determined. This study provides a model which can be used to simulate the cost–benefit under different implementation levels of reduction strategies and different investment levels in advance, thereby providing a reference for project decision-makers to plan CW source reduction. [ABSTRACT FROM AUTHOR]

A multitude of epidemiological studies have demonstrated that both ambient temperatures and air pollution are closely related to health outcomes. However, whether temperature has modification effects on the association between ozone and health outcomes is still debated. In this study, three parallel time-series Poisson generalized additive models (GAMs) were used to examine the effects of modifying ambient temperatures on the association between ozone and mortality (including non-accidental, respiratory, and cardiovascular mortality) in Chengdu, China, from 2014 to 2016. The results confirmed that the ambient high temperatures strongly amplified the adverse effects of ozone on human mortality; specifically, the ozone effects were most pronounced at > 28 °C. Without temperature stratification conditions, a 10-μg/m3 increase in the maximum 8-h average ozone (O3–8hmax) level at lag01 was associated with increases of 0.40% (95% confidence interval [CI] 0.15%, 0.65%), 0.61% (95% CI 0.27%, 0.95%), and 0.69% (95% CI 0.34%, 1.04%) in non-accidental, respiratory, and cardiovascular mortality, respectively. On days during which the temperature exceeded 28 °C, a 10-μg/m3 increase in O3–8hmax led to increases of 2.22% (95% CI 1.21%, 3.23%), 2.67% (95% CI 0.57%, 4.76%), and 4.13% (95% CI 2.34%, 5.92%) in non-accidental, respiratory, and cardiovascular mortality, respectively. Our findings validated that high temperature could further aggravate the health risks of O3–8hmax; thus, mitigating ozone exposure will be brought into the limelight especially under the context of changing climate. [ABSTRACT FROM AUTHOR]

Despite the apparent improvement in air quality in recent years through a series of effective measures, the concentration of PM2.5 and O3 in Chengdu city remains high. And both the two pollutants can cause serious damage to human health and property; consequently, it is imperative to accurately forecast hourly concentration of PM2.5 and O3 in advance. In this study, an air quality forecasting method based on random forest (RF) method and improved ant colony algorithm coupled with back-propagation neural network (IACA-BPNN) are proposed. RF method was used to screen out highly correlated input variables, and the improved ant colony algorithm (IACA) was adopted to combine with BPNN to improve the convergence performance. Two datasets based on two different kinds of monitoring stations along with meteorological data were applied to verify the performance of this proposed model and compared with another five plain models. The results showed that the RF-IACA-BPNN model has the minimum statistical error of the mean absolute error, root mean square error, and mean absolute percentage error, and the values of R2 consistently outperform other models. Thus, it is concluded that the proposed model is suitable for air quality prediction. It was also detected that the performance of the models for the forecasting of the hourly concentrations of PM2.5 were more acceptable at suburban station than downtown station, while the case is just the opposite for O3, on account of the low variability dataset at suburban station. [ABSTRACT FROM AUTHOR]

As a policy tool for advancing ecological progress, the Grain to Green Program (GTGP) has been operating for 20 years and has played an important role in improving ecosystem service value. However, there are few studies on the trade-off/synergy changes in ecosystem services during the implementation of the GTGP and how to select the optimal scheme for regional ecological security based on these trade-offs. Thus, we took the Chengdu-Chongqing urban agglomeration (CCUA) in southwestern China as the study area and estimated the regional food production, carbon sequestration, water yield, soil conservation, and habitat quality services. Then, the trade-off/synergy relationships among ecosystem services were clarified, and the influential mechanism of the GTGP on trade-off changes was evaluated. Finally, different risk scenarios were generated and the regional ecological security zone was simulated under the principle of the best protection efficiency and the highest trade-off degree. The obtained results indicated that the trade-offs/synergies of regional ecosystem services changed significantly during the implementation of the GTGP. Among them, food production, water yield, and soil conservation have always had trade-offs, while carbon sequestration, soil conservation, and habitat quality have all had synergistic relationships. The relationships between carbon sequestration and water yield and food production changed from noncorrelated to trade-off/synergistic, and the relationships between habitat quality and food production and water yield were not obvious. The GTGP has been an important factor affecting the change of trade-off intensities. On the one hand, it has strengthened the synergistic relationships among carbon sequestration, soil conservation, and habitat quality; on the other hand, it increased the constraints of water resources on soil conservation and vegetation restoration. The scenarios with a decision risk coefficient of α = 1.6 were the most suitable, and the ecological security zone corresponding to this scenario was located in the northwestern region of the study area, with high carbon sequestration and habitat quality services. In the future, the intensity or direction of the GTGP should be adjusted to solve the conflicts among ecosystem services in other areas except the northwest region. [ABSTRACT FROM AUTHOR]

Air pollution is a serious threat to ancient sites and cultural relicts. In this study, we collected indoor and outdoor PM2.5 samples and individual particles at the Exhibition Hall of Jinsha Site Museum in June 2020, and then the chemical components, sources, morphology, and mixing state of the fine particulate matter were analyzed. Our results show that the indoor and outdoor PM2.5 concentrations at the Exhibition Hall were 33.3±6.6 and 39.4±11.4 μg m−3, respectively. Although the indoor and outdoor concentrations of OC and EC were close, the proportion of secondary organic carbon in OC outdoor (33%) was higher than that indoor (27%). The PM2.5 was alkaline both indoors and outdoors, and the outdoor alkalinity was stronger than the indoor alkalinity. SNA (SO42−, NO3−, and NH4+) was the dominant component in the water-soluble inorganic ions; Na+, Mg2+, and Ca2+ were well correlated (R2> 0.9), and Cl− and K+ were also highly correlated (R2> 0.8). Enrichment factor analysis showed that Cu (indoor) and Cd were the main anthropogenic elements and that Cd was heavily enriched. Principal components analysis showed that the main sources of PM2.5 at Jinsha Site Museum were motor vehicles, dust, secondary sources, and combustion sources. The individual particles were classified as organic matter, S-rich, soot, mineral, and fly ash/metal particles, and most of these particles were internally mixed with each other. At last, we proposed pollution control measures to improve the air quality of museums and the preservation of cultural relicts. [ABSTRACT FROM AUTHOR]

This study aims to showcase the adaptability evaluation of human settlements in Chengdu with the use of 3S technology. Chengdu was selected as the research object; natural eco-environmental factors such as terrain fluctuations, temperature and humidity, vegetation type, land use, and vegetation cover were analyzed, together with human disturbance factors such as traffic and gross domestic product (GDP); and the index weights were calculated by analytic hierarchy process (AHP). The evaluation model of Chengdu's residential environment adaptability was constructed based on the analysis carried out by the 3S technology: projection transformation, remote sensing interpretation, information extraction, and analysis. The results of the analysis reflected the zoning and spatial distribution characteristics of Chengdu's residential environment adaptability, and show that (1) the adaptability index of Chengdu's human settlement environment is between 15.98 and 76.75, and the suitability of human settlement environment is seen gradually decreasing from the middle, where it is the highest, when moving to the west and to the east of Chengdu; (2) according to the present situation, the suitability index can be divided into high-grade suitable areas, relatively high-grade suitable areas, moderately suitable areas, and low suitable areas; (3) the correlation between the spatial distribution of Chengdu population and each index factor is as follows: per capita GDP > topographic relief > temperature and humidity > vegetation coverage > traffic network density > land use > hydrological factors; (4) there is a good correlation between Chengdu's human settlements suitability index and the present population density grid layer, and its correlation coefficient is 0.7326; and (5) the leading impact indicators of human settlements are different in different regions. The results show that the natural environmental conditions in Chengdu are superior and that the ecological environmental quality is relatively stable, but the human settlement suitability index is relatively low in the southeast and Longmenshan areas of Chengdu. [ABSTRACT FROM AUTHOR]

Three landfills are located in the eastern part of the Chengdu City, and two traffic tunnels pass beneath the south portion of landfill-1. The landfills have a simple leachate collection system without any bottom liner and impermeable wall, which causes a severe corrosion of the traffic tunnels from 175 to 250 m in the test section. In order to explore how the traffic tunnels impact the transport path of contaminants infiltrating from landfills, a groundwater flow model and a solute transport model were established in the present study. It was found that, after 16 years of operation, the traffic tunnels will accelerate the vertical migration of sulfate ions in the area between the tunnels. Furthermore, 64 water samples along the traffic tunnels were collected to test the concentration of the contaminants. According to the distribution mechanism of the measured concentrations in the traffic tunnels, a preliminary treatment plan was proposed to control the further corrosion of the tunnels and the spread of the contaminants. [ABSTRACT FROM AUTHOR]