Sensitizing performance of air purifiers for the high-rise commercial buildings in urban core

被引:0
作者
Budde, Sandeep [1 ,2 ]
Chani, Prabhjot Singh [2 ]
Agrawal, Sandeep [1 ]
机构
[1] Univ Alberta, Sch Urban & Reg Planning, Urban Environm Observ, Edmonton, AB, Canada
[2] Indian Inst Technol IIT, Dept Architecture & Planning, Built Environm Lab, Roorkee, India
来源
FRONTIERS IN SUSTAINABLE CITIES | 2025年 / 6卷
关键词
air purifiers; urban air pollution; smart building guidelines; co-simulation mode; energy plus; ENERGY MANAGEMENT; POLLUTION; QUALITY; EXPOSURE; IMPACT;
D O I
10.3389/frsc.2024.1469803
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
There are thousands of pollution monitoring stations which are recording the data 24x7, the present research question is using this data to solve bring out a relationship between natural ventilation and air conditioning. Recently, WHO reported that 14 out of the top 15 most polluted cities are in India. Every year there is a loss of 6.2% to the global economy due to air pollution. The recent urban PM2.5 smog spread over the whole of north India covering about 50% of the country's population. This event has been increasing the use of air purifiers and affecting the building energy performance. Most air purifiers (PM 10 and PM 2.5) are energy-intensive but are not always equipped with sensors. In commercial buildings, air purifiers are operated based on publicly relayed pollution information. The air pollutants that infiltrate into buildings are based on leaks, cracks, quality of building construction and pressure differences. Since indoor pollution levels are less than outdoor pollution levels, usage of air purifiers based on outdoor information leads to overperformance and hence energy wastage. Therefore, there is a need for optimization in sensitizing the performance of air purifiers at the building level. This study intends to assess the role of building airtightness and air purifier automation in lessening the air purifiers' electricity consumption in urban areas. Transient building simulation tools do not account for infiltrated pollution levels directly. Virtually evaluating the energy savings through air purifier automation and the building's airtightness would not be a straightforward assessment. The following paper uses EnergyPlus Energy Management System Class along with air pollution data monitored to model and simulate the Business-as-usual (BAU) and proposed Automation scenarios.
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页数:10
相关论文
共 51 条
[21]   Status of indoor air pollution (IAP) through particulate matter (PM) emissions and associated health concerns in South Asia [J].
Junaid, Muhammad ;
Syed, Jabir Hussain ;
Abbasi, Naeem Akhtar ;
Hashmi, Muhammad Zaffar ;
Malik, Riffat Naseem ;
Pei, De-Sheng .
CHEMOSPHERE, 2018, 191 :651-663
[22]   Indoor air pollution levels in public buildings in Thailand and exposure assessment [J].
Klinmalee, Aungsiri ;
Srimongkol, Kasama ;
Oanh, Nguyen Thi Kim .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 2009, 156 (1-4) :581-594
[23]   Predictive control techniques for energy and indoor environmental quality management in buildings [J].
Kolokotsa, D. ;
Pouliezos, A. ;
Stavrakakis, G. ;
Lazos, C. .
BUILDING AND ENVIRONMENT, 2009, 44 (09) :1850-1863
[24]   Indoor air quality and energy management through real-time sensing in commercial buildings [J].
Kumar, Prashant ;
Martani, Claudio ;
Morawska, Lidia ;
Norford, Leslie ;
Choudhary, Ruchi ;
Bell, Margaret ;
Leach, Matt .
ENERGY AND BUILDINGS, 2016, 111 :145-153
[25]   Short-term effects of different PM2.5 ranges on daily all-cause mortality in Jinan, China [J].
Ma, Zhixiang ;
Meng, Xiangwei ;
Chen, Cai ;
Chao, Baoting ;
Zhang, Chuanzhen ;
Li, Wei .
SCIENTIFIC REPORTS, 2022, 12 (01)
[26]   ENERNET: Studying the dynamic relationship between building occupancy and energy consumption [J].
Martani, Claudio ;
Lee, David ;
Robinson, Prudence ;
Britter, Rex ;
Ratti, Carlo .
ENERGY AND BUILDINGS, 2012, 47 :584-591
[27]   PM2.5 pollution from household solid fuel burning practices in central India: 1. Impact on indoor air quality and associated health risks [J].
Matawle, Jeevan Lal ;
Pervez, Shamsh ;
Shrivastava, Anjali ;
Tiwari, Suresh ;
Pant, Pallavi ;
Deb, Manas Kanti ;
Bisht, Diwan Singh ;
Pervez, Yasmeen F. .
ENVIRONMENTAL GEOCHEMISTRY AND HEALTH, 2017, 39 (05) :1045-1058
[28]   Long-term analysis of the relationships between indoor and outdoor fine particulate pollution: A case study using research grade sensors [J].
Mendoza, Daniel L. ;
Benney, Tabitha M. ;
Boll, Sarah .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 776
[29]   Recognizing energy-related activities using sensors commonly installed in office buildings [J].
Milenkovic, Marija ;
Amft, Oliver .
4TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2013), THE 3RD INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2013), 2013, 19 :669-677
[30]  
Mineno H, 2010, CONSUM COMM NETWORK, P422