Analysis of temporal spatial distribution characteristics of PM<sub>2.5</sub> pollution and the influential meteorological factors using Big Data in Harbin, China

Luo, Yao; Liu, Shuo; Che, Lina; Yu, Yi

doi:10.1080/10962247.2021.1902423

Cited by 24 publications

(13 citation statements)

References 26 publications

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“…Pollution in southern cities is still dominated by vehicle emissions even in winter, while in Harbin, a cold-climate city, the heating emissions are even greater in winter. In terms of urban microclimate, temperature and wind speed are strongly negatively correlated with PM 2.5 concentration, while relative humidity is strongly positively correlated with PM 2.5 concentration, which is basically consistent with previous studies [4]. In terms of selecting research methods for PM 2.5 concentration prediction, some scholars have conducted prediction research on air pollution.…”

Section: Discussion and Urban Design Recommendationssupporting

confidence: 86%

“…PM 2.5 pollution is very serious in cold-climate cities of northeast China. In addition to common forms of urban air pollution such as long-distance transportation of pollutants and automobile exhaust emissions, winter heating and inversion layer aggravate the problem of declining urban air quality and frequent haze weather [3,4]. It is worth noting that the demand for wind and cold protection of cold-climate cities also forces the urban morphology design to be relatively simple and closed, which is not conducive to the dispersion of air pollutants [5].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Effects of Urban Morphology Parameters on PM2.5 Distribution in Northeast China Based on Gradient Boosted Regression Trees Method

et al. 2022

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The dispersion of urban pollutants is affected by the urban morphology parameters. The objective of this study was to investigate the correlation between PM2.5 distribution and urban morphology parameters in a cold-climate city in China. Field measurements were performed to record the PM2.5 concentration and microclimate parameters at 25 points in a 10 km2 urban area in Harbin, China. It was found that the maximum difference of PM2.5 concentration among the measuring points at the same time could be up to 69.03 μg/m3. In this study, a geographic information system (GIS) was used to extract and screen the urban morphology parameter data under reasonable buffer radius, the gradient boosted regression trees model (GBRT) was used to carry out the prediction experiment of PM2.5 concentration and explore the nonlinear influence of urban morphology factors on PM2.5 concentration. In addition, random forest (RF), decision trees (DT), and multiple linear regression (MLR) models were selected to compare the prediction accuracy of the GBRT model. The results show that the GBRT model has the highest accuracy, with R2 reaching 0.981; building density (57%) and average building height (49%) were the two most significant factors affecting PM2.5 concentration.

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Section: Discussion and Urban Design Recommendationssupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Assessing the Effects of Urban Morphology Parameters on PM2.5 Distribution in Northeast China Based on Gradient Boosted Regression Trees Method

et al. 2022

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“…To a certain extent, the higher relative humidity promoted the absorption of moisture and clumping of fine PM. 23,24 Correlation analysis of NAI with respect to temperature and relative humidity Previous studies have shown that temperature and relative humidity have an important influence on the NAI concentration. 25 Therefore, based on the measured data under different weather conditions, a correlation analysis between NAI, temperature and relative humidity was carried out as shown in Table 2.…”

Section: Distributionmentioning

confidence: 99%

Spatiotemporal distribution of negative air ion and PM_2.5 in urban residential areas

Wang

Xia

Zhu

et al. 2022

Indoor and Built Environment

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Urban environments are characterised by high pollution levels, which adversely affect the physiology, psychology and behaviour of the urban residents. In this study, on-site measurements and air quality evaluations were performed in urban residential areas. The negative air ion (NAI) concentration, fine particulate matter (PM2.5) concentration, temperature and relative humidity were measured in different seasons. Both PM2.5 and the NAI concentrations changed significantly with seasons. The PM2.5 concentration was the highest in winter, intermediate in autumn and the lowest in summer, while the NAI concentration showed an opposite trend. The overall changes in NAI and PM2.5 concentrations showed a trend of double peaks and double valleys, and there was a substantial difference between rainy days versus sunny days. The NAI concentration was positively correlated with temperature and relative humidity, and the influence of relative humidity on NAI was greater than that of temperature. There were notable spatial differences in the intensity of impact by different pollution sources. Based on these results, suggestions were made for optimising the layout of residential buildings and the rationalisation of traffic networks, with the aim of increasing NAI concentrations and reducing PM2.5 concentrations. This would help reduce the pollution levels in urban residential areas.

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“…In recent years, Harbin, a megacity in Northeast China, has experienced severe and continuous haze conditions in winter, which has had serious impacts on the social economy, ecological environment, and human health [29,30] . The temperature in Harbin can range from below -30 °C in winter to > 35 °C in summer, so Harbin provides an ideal research area to study how the weather and air quality influence human exposure to atmospheric BFRs.…”

Section: Introductionmentioning

confidence: 99%

Factors affecting the levels and pathways of atmospheric brominated flame retardant uptake by humans in different weather conditions

Hu¹,

Zhong²,

Liu³

et al. 2023

J Environ Expo Assess

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The health risks posed by atmospheric brominated flame retardants (BFRs) have been widely studied, but there remains a lack of clarity about exposure differences between clear days and haze days. We sampled the total suspended particle (TSP) and gaseous BFRs on clear days in summer, clear days in winter, and haze days in winter in Harbin, China, to investigate the variations in the concentrations and intakes (dermal and inhalation) in the different weather conditions. The concentrations of atmospheric BFRs were highest on haze days in winter (185 pg/m3), followed by clear days in summer (158 pg/m3), and clear days in winter (79.2 pg/m3), and these concentrations were significantly correlated with the concentrations of TSP. The human intake in the different weather conditions followed the pattern of the BFR concentrations, and the human intake of atmospheric BFRs was dominated by inhalation. A comparison of the BFR levels showed that the human intake of gaseous and particulate BFRs varied in the three weather conditions and that the inhalation intake, but not the dermal intake, was influenced under high concentrations of gaseous BFRs with low molecular weight.

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Analysis of temporal spatial distribution characteristics of PM_2.5 pollution and the influential meteorological factors using Big Data in Harbin, China

Cited by 24 publications

References 26 publications

Assessing the Effects of Urban Morphology Parameters on PM2.5 Distribution in Northeast China Based on Gradient Boosted Regression Trees Method

Assessing the Effects of Urban Morphology Parameters on PM2.5 Distribution in Northeast China Based on Gradient Boosted Regression Trees Method

Spatiotemporal distribution of negative air ion and PM_2.5 in urban residential areas

Factors affecting the levels and pathways of atmospheric brominated flame retardant uptake by humans in different weather conditions

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Analysis of temporal spatial distribution characteristics of PM2.5 pollution and the influential meteorological factors using Big Data in Harbin, China

Cited by 24 publications

References 26 publications

Assessing the Effects of Urban Morphology Parameters on PM2.5 Distribution in Northeast China Based on Gradient Boosted Regression Trees Method

Assessing the Effects of Urban Morphology Parameters on PM2.5 Distribution in Northeast China Based on Gradient Boosted Regression Trees Method

Spatiotemporal distribution of negative air ion and PM2.5 in urban residential areas

Factors affecting the levels and pathways of atmospheric brominated flame retardant uptake by humans in different weather conditions

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Analysis of temporal spatial distribution characteristics of PM_2.5 pollution and the influential meteorological factors using Big Data in Harbin, China

Spatiotemporal distribution of negative air ion and PM_2.5 in urban residential areas