Impacts of urbanization and air pollution on building energy demands — Beijing case study

Xu, Xiaoyu; González, Jorge E.; Shen, Shuanghe; Miao, Shiguang; Dou, Junxia

doi:10.1016/j.apenergy.2018.04.120

Cited by 84 publications

(35 citation statements)

References 35 publications

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“…The research of Azimi et al (2018) indicated that coal consumption, power generation, power intensity of GDP, and per capita GDP were four urban development drivers of per capita SO 2 emissions, and the intensity of gasoline consumption, proportion of gasoline vehicles, vehicle use in urban populations, and urbanization rate were the four urban development drivers of per capita NO x in China [18]. In addition, topography, climate, industrial structure, population size and density, GDP, GDP of secondary industry, energy consumption, size of urban area, and transportation could also make great contributions to air pollution in a country or region [36][37][38][39][40][41]. However, only a single air pollution driving factor, or a few factors, were discussed in these studies, leading to some limitations on their conclusions.…”

Section: Driving Forcesmentioning

confidence: 99%

“…First, unprecedented urbanization aggravated the sharp depletion of energy and resources, which then increased air pollutant emissions [18,[42][43][44][45][46]. Even worse, the urban heat island effect not only affects the energy demand for cooling and heating, but also hampers air pollutant diffusion to a great extent [41,46]. Therefore, the air quality in the 17 municipalities of Henan province deteriorated in recent years (Figure 2).…”

Section: Urban Development and Population Growth Potentialmentioning

confidence: 99%

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A Study of the Socioeconomic Forces Driving Air Pollution Based on a DPSIR Model in Henan Province, China

et al. 2019

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The 3D spatiotemporal distribution (spatial and annual-month-daily temporal) features of the air quality index (AQI), air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3-8h), and air pollution risks (R) from 2003 to 2018 were investigated to understand the severity of air pollution in Henan province. The multiyear ascending trends for AQI and R values, with a peak in 2015, were observed in 2003 to 2018 since the annual population-weighted average concentrations of PM2.5, PM10, NO2, and O3-8h were always higher than the CAAQs II from 2013 to 2017 in Henan province. Changes in the monthly moving average AQI values in Henan province conformed to a U-shaped pattern, with the highest values in the winter (from December to February) and the lowest in the summer (from June to August). Triple peaks for AQI values of 8:00‒10:00 a.m., 6:00‒8:00 p.m., and 2:00‒4:00 p.m. in the representative municipalities corresponded with the morning and evening traffic tendencies and photochemical process. A spatial analysis indicated that there were decreasing trends for air pollution from northwest to southeast in Henan province. Data on 48 concrete parameters were collected from 2003 to 2017 to construct a driving force‒pressure‒state‒influence‒response (DPSIR) model for assessing the socioeconomic forces driving air pollution in this province. It was the too-rapid growth of the driving force index (DFI), induced by urban development and population growth (UDPG), economic growth and change of industrial structure (EGCIS), and energy consumption growth and structure change (ECGSC), that led to a direct increase in the atmospheric pollution burden, i.e., total emissions from air pollution and industrial emissions, which are linearly correlated to values of UDPG and ECGSC, respectively (p < 0.05). Furthermore, the prediction models for AQI and R values in Henan province, with the growth rates being 4.251 DFI−1 and 0.0816 DFI−1, respectively, were simulated by multiple linear regression analysis. Therefore, the integrated risks of air pollution in Henan province were originally driven by DFI.

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Section: Driving Forcesmentioning

confidence: 99%

Section: Urban Development and Population Growth Potentialmentioning

confidence: 99%

A Study of the Socioeconomic Forces Driving Air Pollution Based on a DPSIR Model in Henan Province, China

et al. 2019

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“…Figure 4 to Figure 6 show the average indoor temperature during summer, average daily range, and summer maximum temperature over 60 years in different cities. Except for global climate change, urbanization and urban heat island (Xu et al, 2018) may also contribute to the rising trend.…”

Section: Indoor Thermal Environment In Different Cities Across 60 Yearsmentioning

confidence: 99%

A novel approach for selecting typical hot-year (THY) weather data

et al. 2019

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The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.

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“…The aforementioned urban complexity trap and absorb the heat from escaping into the open space, thus creating a steep temperature gradient between urban and rural areas at nights [7]. Upon intensification, UHIs induce deleterious impacts on anthropogenic energy emissions [8], thermal comfort levels [9], air quality [10], biodiversity [11] and public health [12].…”

Section: Introductionmentioning

confidence: 99%

Spatial characteristics of open park spaces and perceived warmness in a tropical city

Hanif

Fong

Ramakreshnan

et al. 2020

Preprint

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Background: Rapid urbanization in Kuala Lumpur Metropolitan City (KLMC) has resulted in urban heat island (UHI) effect that deteriorated public health of the urban dwellers. In a motive of identifying the heat sources, this study reported the perceived warmness and the characteristics of Open Park Spaces (OPS) that induce the reported warmness of the surrounding environment in Kuala Lumpur Metropolitan City (KLMC), a tropical city of Malaysia.Methods: A cross sectional survey using structured questionnaires is conducted on randomly clustered respondents in selected localities of KLMC from January to May, 2018. Pearson correlation is performed to examine the relationship between perceived characteristics of OPS and perceived warmness of the surrounding environment according to three time slots of a day.Results: The outcomes demonstrated that respondents felt warm during nights (89%) compared to morning (75%) and afternoon (87%). Meanwhile, the existing OPS are reported to be equipped with a mix of biodiversity such as birds, rodents and insects (89%), a mix of natural plants and animal populations (88%), water bodies (88%), variety of plants (86%), well-maintained grass surfaces (80%), ornamental flowers (79%) as well as wooded pasture (78%) in their neighbourhood. As the maximum warming sensation is reported to be felt at nights, especially in the presence of water bodies (r= 0.318, p<0.01) and wooded pasture (r= 0.222, p<0.01) in the vicinity, the integration of heat ameliorators across the existing water bodies and wood pasture deemed essential to reduce the surrounding heat impacts.Conclusion: The findings of this preliminary investigation are useful for urban designers and policy makers to make tacit evidence-based decisions.

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Impacts of urbanization and air pollution on building energy demands — Beijing case study

Cited by 84 publications

References 35 publications

A Study of the Socioeconomic Forces Driving Air Pollution Based on a DPSIR Model in Henan Province, China

A Study of the Socioeconomic Forces Driving Air Pollution Based on a DPSIR Model in Henan Province, China

A novel approach for selecting typical hot-year (THY) weather data

Spatial characteristics of open park spaces and perceived warmness in a tropical city

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