AUTHOR=Budde Sandeep , Chani Prabhjot Singh , Agrawal Sandeep TITLE=Sensitizing performance of air purifiers for the high-rise commercial buildings in urban core JOURNAL=Frontiers in Sustainable Cities VOLUME=6 YEAR=2025 URL=https://www.frontiersin.org/journals/sustainable-cities/articles/10.3389/frsc.2024.1469803 DOI=10.3389/frsc.2024.1469803 ISSN=2624-9634 ABSTRACT=

There are thousands of pollution monitoring stations which are recording the data 24×7, 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.