To study the indoor air qualities（IAQ）of large commercial office buildings in Hunan province of China and the corresponding improvement methods,the IAQ of a large commercial office building in Changsha in July,2008,...To study the indoor air qualities（IAQ）of large commercial office buildings in Hunan province of China and the corresponding improvement methods,the IAQ of a large commercial office building in Changsha in July,2008,is investigated.A questionnaire survey and field tests are used to collect data.According to the data of twelve rooms in this building,objective evaluation and the subjective evaluation of the IAQ are obtained.Almost all of the environmental parameters in these rooms basically meet the standards of the objective evaluation.But the average concentration of carbon dioxide in most rooms cannot reach the value of the cleanliness standards,1 255 mg/m^3.The average acceptability of the IAQ in these rooms is 71%,which is lower than the value of the ASHRAE 55—1992 standards,80%.The proper increase in the wind speed and the indoor fresh air supply can greatly improve the objective evaluation and the subjective evaluation of the IAQ.展开更多
Increasing incidents of indoor air quality(IAQ) related complaints lead us to the fact that IAQ has become a significant occupational health and environmental issue. However, how to effectively evaluate IAQ under diff...Increasing incidents of indoor air quality(IAQ) related complaints lead us to the fact that IAQ has become a significant occupational health and environmental issue. However, how to effectively evaluate IAQ under different scale of multiple indicators is still a challenge. The traditional single-indicator method is subjected to uncertainties in assessing IAQ due to different subjectivity on good or bad quality and scalar differences of data set. In this study, a multilevel integrated weighted average IAQ method including initial walking through assessment(IWA) and two-layers weighted average method are developed and applied to evaluate IAQ of the laboratory building at the University of Regina in Canada. Some important chemical parameters related to IAQ in terms of volatile organic compounds(VOCs), methanol(HCHO), carbon dioxide(CO2), and carbon monoxide(CO) are evaluated based on 5 months continuous monitoring data. The new integrated assessment result can not only indicates the risk of an individual parameter, but also able to quantify the overall IAQ risk on the sampling site. Finally, some recommendations based on the result are proposed to address sustainable IAQ practices in the sampling area.展开更多
From the view of both objective and subjective factors,the indoor air quality(IAQ)evaluation was considered.Carbon dioxide(CO2)and formaldehyde(HCHO)were selected as the typical contaminants of indoor air,and the eval...From the view of both objective and subjective factors,the indoor air quality(IAQ)evaluation was considered.Carbon dioxide(CO2)and formaldehyde(HCHO)were selected as the typical contaminants of indoor air,and the evaluation method of logarithmic index was adopted as the evaluation means of IAQ.Then the recommended limits(RL)of typical contaminants CO2 and HCHO were given through analysis and calculation.The limits of CO2 and HCHO in Indoor Air Quality Standard of China or other existing standards probably correspond to the level of PD=25(%).The result shows that the existing standards fail to meet the requirement of the definition of "acceptable indoor air quality",that is to say,less than 20% of the people express dissatisfaction.When PD=20%,RL of CO2 and HCHO are 728×10-6 and 0.068×10-6 respectively,which are stricter than the limits in the existing standards.The method proposed in this paper is applicable to 13.1%≤PD≤86.7%.展开更多
Air quality has a significant relationship with our life. Residents are concerned with the environment issue of Chongqing, which used to be one of major industrial cities in China. We choose the air quality of Chongqi...Air quality has a significant relationship with our life. Residents are concerned with the environment issue of Chongqing, which used to be one of major industrial cities in China. We choose the air quality of Chongqing as the research object, valued by choice experiment model with designed questionnaires, to discuss the best approach of improving the air quality. Firstly, the paper introduces the representative methods of the stated preferences: CVM and choice experiment(CE). The choice experiment(CE) could be designed in a series of situations with many different attributes to test the relative values among the attributes, which are the evidences of ranking importance of the attributes. Because the improvement of air quality is affected by multiple factors, the technique is better at valuing the economical impacts. Once the attributes and levels are decided, profiles and choice sets can be designed. We can also collect data through questionnaires and use the conditional logit model to evaluate the improvement of air quality in Chongqing. The result shows the relative importance of the elements selected to evaluate the improvement of urban air quality. In a word, this research has important practical value to better the air quality.展开更多
The present building facility management status in China resulted in many problems such as high energy consumption,failure of automation control,services failure and poor indoor air quality.Based on questionnaires and...The present building facility management status in China resulted in many problems such as high energy consumption,failure of automation control,services failure and poor indoor air quality.Based on questionnaires and interviews to professional engineers and building users,a comprehensive evaluation index system was established on facility management of high-rise office buildings.A Fuzzy AHP based upon hierarchy criteria system was established.A Fuzzy AHP Evaluation Model on Facility Management System was set up;α-cut analysis was introduced and incorporated with expert knowledge together,which made up the optimism index λ.The fuzzy optimum crisp weight of each criterion was resulted from data-mining.Case investigations were processed in high-rise office buildings in Shenyang.The results illustrated that indoor air quality,thermal comfort and life cycle cost were the most important indexes in the evaluation of Facility Management System of high rise office buildings.Residents in high-rise buildings in Shenyang pay less attention to maintenance management and environment protection.By comparison with the analysis result of Export Choice,Fuzzy AHP-based evaluation model could act as a scientific reference for the establishment of governmental standards in facility management area in building.展开更多
The built environment sector is responsible for almost one-third of the world’s final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impa...The built environment sector is responsible for almost one-third of the world’s final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.展开更多
基金The National Natural Science Foundation of China(No.50878078)
文摘To study the indoor air qualities（IAQ）of large commercial office buildings in Hunan province of China and the corresponding improvement methods,the IAQ of a large commercial office building in Changsha in July,2008,is investigated.A questionnaire survey and field tests are used to collect data.According to the data of twelve rooms in this building,objective evaluation and the subjective evaluation of the IAQ are obtained.Almost all of the environmental parameters in these rooms basically meet the standards of the objective evaluation.But the average concentration of carbon dioxide in most rooms cannot reach the value of the cleanliness standards,1 255 mg/m^3.The average acceptability of the IAQ in these rooms is 71%,which is lower than the value of the ASHRAE 55—1992 standards,80%.The proper increase in the wind speed and the indoor fresh air supply can greatly improve the objective evaluation and the subjective evaluation of the IAQ.
文摘Increasing incidents of indoor air quality(IAQ) related complaints lead us to the fact that IAQ has become a significant occupational health and environmental issue. However, how to effectively evaluate IAQ under different scale of multiple indicators is still a challenge. The traditional single-indicator method is subjected to uncertainties in assessing IAQ due to different subjectivity on good or bad quality and scalar differences of data set. In this study, a multilevel integrated weighted average IAQ method including initial walking through assessment(IWA) and two-layers weighted average method are developed and applied to evaluate IAQ of the laboratory building at the University of Regina in Canada. Some important chemical parameters related to IAQ in terms of volatile organic compounds(VOCs), methanol(HCHO), carbon dioxide(CO2), and carbon monoxide(CO) are evaluated based on 5 months continuous monitoring data. The new integrated assessment result can not only indicates the risk of an individual parameter, but also able to quantify the overall IAQ risk on the sampling site. Finally, some recommendations based on the result are proposed to address sustainable IAQ practices in the sampling area.
文摘From the view of both objective and subjective factors,the indoor air quality(IAQ)evaluation was considered.Carbon dioxide(CO2)and formaldehyde(HCHO)were selected as the typical contaminants of indoor air,and the evaluation method of logarithmic index was adopted as the evaluation means of IAQ.Then the recommended limits(RL)of typical contaminants CO2 and HCHO were given through analysis and calculation.The limits of CO2 and HCHO in Indoor Air Quality Standard of China or other existing standards probably correspond to the level of PD=25(%).The result shows that the existing standards fail to meet the requirement of the definition of "acceptable indoor air quality",that is to say,less than 20% of the people express dissatisfaction.When PD=20%,RL of CO2 and HCHO are 728×10-6 and 0.068×10-6 respectively,which are stricter than the limits in the existing standards.The method proposed in this paper is applicable to 13.1%≤PD≤86.7%.
文摘Air quality has a significant relationship with our life. Residents are concerned with the environment issue of Chongqing, which used to be one of major industrial cities in China. We choose the air quality of Chongqing as the research object, valued by choice experiment model with designed questionnaires, to discuss the best approach of improving the air quality. Firstly, the paper introduces the representative methods of the stated preferences: CVM and choice experiment(CE). The choice experiment(CE) could be designed in a series of situations with many different attributes to test the relative values among the attributes, which are the evidences of ranking importance of the attributes. Because the improvement of air quality is affected by multiple factors, the technique is better at valuing the economical impacts. Once the attributes and levels are decided, profiles and choice sets can be designed. We can also collect data through questionnaires and use the conditional logit model to evaluate the improvement of air quality in Chongqing. The result shows the relative importance of the elements selected to evaluate the improvement of urban air quality. In a word, this research has important practical value to better the air quality.
文摘The present building facility management status in China resulted in many problems such as high energy consumption,failure of automation control,services failure and poor indoor air quality.Based on questionnaires and interviews to professional engineers and building users,a comprehensive evaluation index system was established on facility management of high-rise office buildings.A Fuzzy AHP based upon hierarchy criteria system was established.A Fuzzy AHP Evaluation Model on Facility Management System was set up;α-cut analysis was introduced and incorporated with expert knowledge together,which made up the optimism index λ.The fuzzy optimum crisp weight of each criterion was resulted from data-mining.Case investigations were processed in high-rise office buildings in Shenyang.The results illustrated that indoor air quality,thermal comfort and life cycle cost were the most important indexes in the evaluation of Facility Management System of high rise office buildings.Residents in high-rise buildings in Shenyang pay less attention to maintenance management and environment protection.By comparison with the analysis result of Export Choice,Fuzzy AHP-based evaluation model could act as a scientific reference for the establishment of governmental standards in facility management area in building.
基金supported by the Department of Architecture and Built Environment,University of Nottingham,and the PhD studentship from EPSRC,Project References:2100822(EP/R513283/1).
文摘The built environment sector is responsible for almost one-third of the world’s final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.
