Prediction of local particle pollution level based on artificial neural network

Citizens eager to know the local pollution level to prevent from air pollution. The real-time measurement for everywhere is a very expensive way, a statistical model based on artificial neural network is applied in this research. This model can estimate particle pollution level with some influencing factors, including background pollution level, weather conditions, urban morphology and local pollution sources. The monitoring from regulatory monitoring sites is considered as the background level. The field measurements of 20 locations are conducted to feed the output layer of ANN model. The average relative error of prediction compared with measurement is 9.24% for PM10 and 18.90% for PM2.5

Indoor thermal environments in Chinese residential buildings responding to the diversity of climates

China has a diversity of climates and a unique historic national heating policy which greatly affects indoor thermal environment and the occupants’ thermal response. This paper quantitatively analyzes the data from a large-scale field study across the country conducted from 2008 to 2011 in residential buildings. The study covers nine typical cities located in the five climate zones including Severe Cold (SC), Cold (C), Hot Summer and Cold Winter (HSCW), Hot Summer and Warm Winter (HSWW) and Mild (M) zones. It is revealed that there exists a large regional discrepancy in indoor thermal environ- ment, the worst performing region being the HSCW zone. Human’s long-term climate adaptation leads to wider range of acceptable thermal comfort temperature. Different graphic comfort zones with accept- able range of temperature and humidity for the five climate zones are obtained using the adaptive Predictive Mean Vote (aPMV) model. The results show that occupants living in the poorer thermal environments in the HSCW and HSWW zones are more adaptive and tolerant to poor indoor conditions than those living in the north part of China where central heating systems are in use. It is therefore recommended to develop regional evaluation standards of thermal environments responding to climate characteristics as well as local occupants’ acclimatization and adaptation in order to meeting dual targets of energy conservation and indoor thermal environment improvement

Exploring the “black box” of thermal adaptation using information entropy

Thermal adaptation has been interpreted well by behavioral, physiological, and psychological factors, but the mechanism and interaction between the three factors remain in the “black box”. This paper aims to apply the theory of general system and information entropy to investigate the quantitative relationships of the three thermal adaptation processes. Based on the database from the field survey and laboratory experiments conducted in the hot summer and cold winter climate zone of China, three typical adaptive indices: clothing insulation (Clo), thermal sensation votes (TSV) and sensory nerve conduction velocity (SCV) were selected to calculate Clo entropy, TSV entropy, SCV entropy and total entropy. The regression models were developed between these entropies and the indoor air temperature to quantify the weights of the three adaptive categories. The models were used to compare the differences between China and Pakistan as well as between adaptive approaches and climate chamber experiments. The thermal comfort and acceptable temperature ranges were obtained using the entropy models. Our findings propose a new perspective using entropy to quantify the behaviorally, physiologically, and psychologically adaptive approaches, which contribute to a better understanding of opening the “black box” of thermal adaptation

An investigation on energy consumption of public buildings in Chongqing, China

Global climate change is one of the most important environmental issues that human have ever faced. China is taking an active role in reducing carbon dioxide emission in order to alleviate the climate change process. Building sectors contribute for 30% of carbon emission and 27.5% of total energy consumption in China. There is an urgent need for improving building energy efficiency to achieve carbon reduction. New buildings are legislated by national standards and regulations to secure a relatively high level of energy efficiency. However, the diversity of architectural design, system operation and management make it a big challenging to achieve energy efficiency in existing buildings. Existing researches have already investigated the building retrofit technologies and strategies. However, information on the current building stocks is even more important due to its impact in decision makings of retrofit strategies. This paper investigates the energy consumption of public buildings in Chongqing, China. Building energy consumption data collected from Chongqing public building energy consumption monitoring platform was analyzed by SPSS software. The data collection and analysis are focused on governmental office, general office, hotel buildings and shopping mall. Statistical hypothesis test, using log-normal P-P plot and Shapiro–Wilk test, reveals that the annual energy consumption densities of these types of building are log-normal distributed

Hybrid Uncertain Analysis for Exterior Acoustic Field Prediction with Interval Random Parameters

For exterior acoustic field problems that lack sufficient information to construct precise probability distributions, an interval random model is introduced to deal with the uncertain parameters. In the interval random model, the probability variables are employed to treat the uncertain parameters, whereas some distribution parameters of random variables are modeled as interval variables instead of precise values. Based on the interval random model, the interval random finite element equation for exterior acoustic fields is established and a hybrid uncertain analysis method is presented to solve the exterior acoustic field problem with interval random variables. In the presented method, by temporarily neglecting the uncertainties of interval variables, a first-order stochastic perturbation method is adopted to calculate the expectation and the variance of the response vector. According to the monotonicity of the expectation and variance of the response vector with respect to the interval variables, the lower and upper bounds of the expectation and variance of the response vector can be calculated by the vertex method. In addition, in order to ensure accuracy of the proposed method, the subinterval technique is introduced and investigated. The numerical example of a square flexible shell model is presented to demonstrate the effectiveness of the proposed method.</jats:p

A multidimensional model for green building assessment: a case study of a highest-rated project in Chongqing

Green building is an inevitable trend in the construction industry which deeply affects the social development of the economy, environment and a series of industries. There is practical significance for the multidimensionally balanced development of green buildings. A model for multi-objective assessment of green building is devel-oped under three dimensions: Objective, Professional and Time (OPT) according to the green building definition. The OPT coordinate system was built up based on the scoring centroid system of both the China Green Building Labelling scheme (GBL) and the Singapore Green Mark (GM) by the introduction of the Coefficient of Varia-tion and Moment of Inertia. Both these frameworks are restructured based on a case study of a practical project in Chongqing which had achieved the highest GBL and GM awards. Results show that GBL distributes its scores more evenly while GM concentrates on energy saving with greater diversity in land supply and building oper-ations (normalized coefficients of variation of 0.435 and 0.350). The project’s com-pliance coefficients are 1.27 and 0.31 under GBL and GM respectively indicating its higher degree of compliance with the GM framework. The developed model provides multitarget-oriented guidelines for green building design, assessment and stand-arddevelopment