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Reducing Air Pollution in Smart and Sustainable Future Cities

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 9564

Special Issue Editors


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Guest Editor
School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China
Interests: indoor air quality; particulate matter; human response; ventilation; sustainable city; energy efficiency
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China
Interests: phase change material preparation and energy storage; low carbon energy supply and performance improvement in buildings; healthy built environment construction; renewable energy utilization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With rapid economic development, population growth, and increased mobility, the problem of air pollution in cities is becoming increasingly serious, significantly impacting people's quality of life and the sustainable development of cities. The main pollutants are particulate matter, sulfur dioxide, nitrogen oxides, carbon monoxide, lead and ozone, and volatile organic compounds in atmospheric environment. They are emitted into the atmosphere through various natural and anthropogenic means, such as transportation, industrial production, pollution of construction and living, and open burning. Smart and sustainable future cities are innovative cities that use information and communication technology and other means to improve the quality of life, the efficiency of city operations and services, and competitiveness. A variety of high-technology means are integrated in smart cities to reduce pollution levels and carbon dioxide emissions, and to protect natural resources within the city. Air pollution control methods will be important to urban sustainability. This Special Issue aims to show the variety and relevance of recent developments and research in the field of related reduction of air pollutants in cities.

Dr. Jianlin Ren
Prof. Dr. Xiangfei Kong
Guest Editors

Manuscript Submission Information

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Keywords

  • environmental issues
  • energy-saving potential
  • effects of air pollutants
  • intelligent methods for air pollutant removal
  • air quality
  • artificial intelligence
  • smart ventilation
  • health outcome
  • COVID-19
  • urban sustainability

Published Papers (5 papers)

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Research

17 pages, 5268 KiB  
Article
Analysis of Thermal Insulation Thickness for a Container House in the Yanqing Zone of the Beijing 2022 Olympic and Paralympic Winter Games
by Yurou Tong, Hui Yang, Li Bao, Baoxia Guo, Yanzhuo Shi and Congcong Wang
Int. J. Environ. Res. Public Health 2022, 19(24), 16417; https://doi.org/10.3390/ijerph192416417 - 7 Dec 2022
Cited by 1 | Viewed by 1268
Abstract
A large number of temporary housings (THs) were used in the Yanqing zone of the Beijing 2022 Olympic and Paralympic Winter Games. Taking a kind of container house (CH) used in Yanqing zone as a model, the objective of this paper is to [...] Read more.
A large number of temporary housings (THs) were used in the Yanqing zone of the Beijing 2022 Olympic and Paralympic Winter Games. Taking a kind of container house (CH) used in Yanqing zone as a model, the objective of this paper is to analyze the effect of insulation thickness on heating energy consumption and corresponding carbon emission. The effect of service life of THs on economic thickness was also discussed. The simulation model was developed using EnergyPlus and the heating energy consumption with different insulation materials was simulated based on the meteorological parameters of the top of Xiaohaituo Mountain (2177.5 m) and the Olympic/Paralympic Village (950 m) in Yanqing zone. In the simulation process, the thermal insulation performance of the CH was enhanced with reference to the requirements of GB/T 51350-2019 Technical Standard for Nearly Zero Energy Buildings (NZEB) on one hand. Additionally, the insulation performance was evaluated in terms of payback period and carbon emission. On the other hand, the economic thickness of different insulation materials (rock wool (RW), extruded polystyrene (XPS), polyurethane (PU)) and the high performance vacuum insulation panel (HVIP)) for different service lives of CH was studied. Results show that the U-values of the envelope meeting the NZEB standard can decrease approximately 21.4–32.8% of the heating energy consumption, compared with the original envelope. When the service life of CH is extended to 20 years, the carbon emission is reduced by 18.5% and 29.5%. The payback period of HVIP is longest, up to 31.4 a, and the results of economic thickness show that when the service life of the CH ranges from 1 year to 20 years, the economic thickness range of RW is 47–235 mm, XPS is 41–197 mm, PU is 33–149 mm and HVIP is 4–18 mm at the altitude of 2177.5 m. At the altitude of 950 m, the economic thickness range of RW is 28–158 mm, XPS is 26–131 mm, PU is 25–118 mm, and HVIP is 2–12 mm. From an economic point of view, the service life of a CH has a significant impact on the choice of insulation thickness. Full article
(This article belongs to the Special Issue Reducing Air Pollution in Smart and Sustainable Future Cities)
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16 pages, 5277 KiB  
Article
Measuring the Air Quality Using Low-Cost Air Sensors in a Parking Garage at University of Minnesota, USA
by Andres Gonzalez, Adam Boies, Jacob Swanson and David Kittelson
Int. J. Environ. Res. Public Health 2022, 19(22), 15223; https://doi.org/10.3390/ijerph192215223 - 18 Nov 2022
Cited by 4 | Viewed by 2410
Abstract
The concentration of air pollutants in underground parking garages has been found to be higher compared to ambient air. Vehicle emissions from cold starts are the main sources of air pollution in underground parking garages. Eight days of measurements, using low-cost air sensors, [...] Read more.
The concentration of air pollutants in underground parking garages has been found to be higher compared to ambient air. Vehicle emissions from cold starts are the main sources of air pollution in underground parking garages. Eight days of measurements, using low-cost air sensors, were conducted at one underground parking garage at the University of Minnesota, Minneapolis. The CO, NO, NO2, and PM2.5 daily average concentrations in the parking garage were measured to be higher, by up to more than an order of magnitude, compared to the ambient concentration. There is positive correlation between exit traffic flow and the air concentrations in the parking garage for lung deposited surface area (LDSA), CO2, NO, and CO. Fuel specific emission factors were calculated for CO, NO, and NOx. Ranging from 25 to 28 g/kgfuel for CO, from 1.3 to 1.7 g/kgfuel for NO, and from 2.1 to 2.7 g/kgfuel for NOx. Regulated emissions were also calculated for CO and NOx with values of 2.4 to 2.9 and 0.19 to 0.25 g/mile, respectively. These emissions are about 50% higher than the 2017 U.S. emission standards for CO and nearly an order magnitude higher for NOx. Full article
(This article belongs to the Special Issue Reducing Air Pollution in Smart and Sustainable Future Cities)
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16 pages, 12294 KiB  
Article
Stratum Ventilation: Enabling Simultaneous Energy Conservation and Air Purification in Subway Cars
by Yanhui Mao, Shengxu Wang, Jianzhou Liang, Saiqin Mao, Yukun Han and Shengquan Zhang
Int. J. Environ. Res. Public Health 2022, 19(21), 14521; https://doi.org/10.3390/ijerph192114521 - 5 Nov 2022
Viewed by 1642
Abstract
The supply of fresh air for underground rail transit systems is not as simple as opening windows, which is a conventional ventilation (CV) measure adopted in aboveground vehicles. This study aims to improve contaminant dilution and air purification in subway car ventilation systems [...] Read more.
The supply of fresh air for underground rail transit systems is not as simple as opening windows, which is a conventional ventilation (CV) measure adopted in aboveground vehicles. This study aims to improve contaminant dilution and air purification in subway car ventilation systems and the safety of rail transit post-coronavirus disease pandemic era. We designed an air conditioning (AC) terminal system combined with stratum ventilation (SV) to enable energy consumption reduction for subway cars. We experimentally tested the effectiveness of a turbulence model to investigate ventilation in subway cars. Further, we compared the velocity fields of CV and SV in subway cars to understand the differences in their airflow organizations and contaminant removal efficiencies, along with the energy savings of four ventilation scenarios, based on the calculations carried out using computational fluid dynamics. At a ventilation flow rate of 7200 m3/h, the CO2 concentration and temperature in the breathing areas of seated passengers were better in the SV than in the CV at a rate of 8500 m3/h. Additionally, the energy-saving rate of SV with AC cooling was 14.05%. The study provides new ideas for reducing the energy consumption of rail transit and broadens indoor application scenarios of SV technology. Full article
(This article belongs to the Special Issue Reducing Air Pollution in Smart and Sustainable Future Cities)
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27 pages, 6352 KiB  
Article
Heating Control Strategy Based on Dynamic Programming for Building Energy Saving and Emission Reduction
by Haosen Qin, Zhen Yu, Tailu Li, Xueliang Liu and Li Li
Int. J. Environ. Res. Public Health 2022, 19(21), 14137; https://doi.org/10.3390/ijerph192114137 - 29 Oct 2022
Cited by 5 | Viewed by 1741
Abstract
Finding the optimal balance between end-user’s comfort, lifestyle preferences and the cost of the heating, ventilation and air conditioning (HVAC) system, which requires intelligent decision making and control. This paper proposes a heating control method for HVAC based on dynamic programming. The method [...] Read more.
Finding the optimal balance between end-user’s comfort, lifestyle preferences and the cost of the heating, ventilation and air conditioning (HVAC) system, which requires intelligent decision making and control. This paper proposes a heating control method for HVAC based on dynamic programming. The method first selects the most suitable modeling approach for the controlled building among three machine learning modeling techniques by means of statistical performance metrics, after which the control of the HVAC system is described as a constrained optimization problem, and the action of the controller is given by solving the optimization problem through dynamic programming. In this paper, the variable ‘thermal energy storage in building’ is introduced to solve the problem that dynamic programming is difficult to obtain the historical state of the building due to the requirement of no aftereffect, while the room temperature and the remaining start hours of the Primary Air Unit are selected to describe the system state through theoretical analysis and trial and error. The results of the TRNSYS/Python co-simulation show that the proposed method can maintain better indoor thermal environment with less energy consumption compared to carefully reviewed expert rules. Compared with expert rule set ‘baseline-20 °C’, which keeps the room temperature at the minimum comfort level, the proposed control algorithm can save energy and reduce emissions by 35.1% with acceptable comfort violation. Full article
(This article belongs to the Special Issue Reducing Air Pollution in Smart and Sustainable Future Cities)
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21 pages, 5043 KiB  
Article
Effects of Return Air Inlets’ Location on the Control of Fine Particle Transportation in a Simulated Hospital Ward
by Jianlin Ren, Shasha Duan, Leihong Guo, Hongwan Li and Xiangfei Kong
Int. J. Environ. Res. Public Health 2022, 19(18), 11185; https://doi.org/10.3390/ijerph191811185 - 6 Sep 2022
Cited by 6 | Viewed by 1538
Abstract
The COVID-19 pandemic has made significant impacts on public health, including human exposure to airborne pathogens. In healthcare facilities, the locations of return air vents in ventilation systems may have important effects on lowering airborne SARS-CoV-2 transmission. This study conducted experiments to examine [...] Read more.
The COVID-19 pandemic has made significant impacts on public health, including human exposure to airborne pathogens. In healthcare facilities, the locations of return air vents in ventilation systems may have important effects on lowering airborne SARS-CoV-2 transmission. This study conducted experiments to examine the influence of different return air vents’ heights (0.7 m, 1.2 m, and 1.6 m) on the particle removal effects in a simulated patient ward. Three different ventilation systems were examined: top celling air supply-side wall return (TAS), underfloor air supply-side wall return (UFAS) and side wall air supply-side wall return (SAS). CFD simulation was applied to further study the effects of return air inlets’ heights (0.3 m, 0.7 m, 1.2 m, 1.6 m, and 2.0 m) and air exchange rates. The technique for order of preference by similarity to ideal solution (TOPSIS) analysis was used to calculate the comprehensive scores of 60 scenarios using a multi-criterion method to obtain the optimal return air inlets’ heights. Results showed that for each additional 0.5 m distance in most working conditions, the inhalation fraction index of medical staff could be reduced by about 5–20%. However, under certain working conditions, even though the distances between the patients and medical personnel were different, the optimal heights of return air vents were constant. For TAS and UFAS, the optimal return air inlets’ height was 1.2 m, while for SAS, the best working condition was 1.6 m air supply and 0.7 m air return. At the optimum return air heights, the particle decay rate per hour of SAS was 75% higher than that of TAS, and the rate of particle decay per hour of SAS was 21% higher than that of UFAS. The location of return air inlets could further affect the operating cost-effectiveness of ventilation systems: the highest operating cost-effectiveness was 8 times higher than the lowest one. Full article
(This article belongs to the Special Issue Reducing Air Pollution in Smart and Sustainable Future Cities)
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