Exploring spatiotemporal patterns of PM2.5 in China based on ground-level observations for 190 cities

Zhang, Haifeng; Wang, Zhaohai; Zhang, Wenzhong

doi:10.1016/j.envpol.2016.06.009

Cited by 105 publications

(57 citation statements)

References 72 publications

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“…Numerous studies have been conducted on PM 2.5 , mainly focused on the spatial and temporal distribution [5,6,7,8,9,10], source apportionment [11,12,13,14], health effects [15,16,17,18], and estimation [19,20,21,22]. Studies have shown that at the macro-scale, PM 2.5 pollution is significantly influenced by meteorological conditions [23,24,25,26]; at the micro-scale, PM 2.5 pollution is strongly related to the land use pattern [27,28,29,30].…”

Section: Introductionmentioning

confidence: 99%

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

Yang

Cai

Liang

2017

IJERPH

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Fine particulate matter (PM2.5) pollution has become one of the greatest urban issues in China. Studies have shown that PM2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM2.5 pollution in urban areas.

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Section: Introductionmentioning

confidence: 99%

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

Yang

Cai

Liang

2017

IJERPH

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“…Recent studies have suggested that airborne pollutants, PM 2.5 in particular, are closely related to cardiovascular disease-related mortality (Garrett and Casimiro, 2011;Li et al, 2015a;Lanzinger et al, 2015), emergency room visits and all-year non-accidental mortality (Pasca et al, 2014). Due to its strong negative influences on public health, scholars have been working towards a better understanding of sources (Guo et al, 2012;Zhang et al, 2013Zhang et al, , 2016Gu et al, 2014;Cao et al, 2014), characteristics (Wei et al, 2012;Zhang et al, 2013;Hu et al, 2015;F. Zhang et al, 2015;Zhen et al, 2016) and seasonal variations (Cao et al, 2012;Shen et al, 2014;Yang and Christakos, 2015;Chen et al, 2015; of PM 2.5 .…”

Section: Introductionmentioning

confidence: 99%

Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective

et al. 2018

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Abstract. With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM 2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM 2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM 2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM 2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM 2.5 concentrations are high, meteorological influences on PM 2.5 concentrations are strong. The dominant meteorological influence for PM 2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM 2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM 2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM 2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM 2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

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“…Moreover, fewer independent points will be enough at the area with low PM 2.5 concentration. High concentration of PM 2.5 was found in three areas of China: (1) the North China Plain including two of China's four municipalities, Beijing and Tianjin, southern Hebei Province, western Shandong Province, and northern Henan province; (2) the Northeast China Plain; and (3) the Taklimakan desert (e.g., [3,4]). Therefore, grid points in the above-mentioned high concentration area are selected as independent points from each 5 ∘ ×5 ∘ area.…”

Section: Independent Point Schemementioning

confidence: 99%

Application of Surface Spline Interpolation Method in Parameter Estimation of a PM_2.5 Transport Adjoint Model

Zhang

2018

Mathematical Problems in Engineering

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A new method for the estimation of initial conditions (ICs) in a PM 2.5 transport adjoint model is proposed in this paper. In this method, we construct the field of ICs by interpolating values at independent points using the surface spline interpolation. Compared to the traditionally used linear interpolation, the surface spline interpolation has an advantage for reconstructing continuous smooth surfaces. The method is verified in twin experiments, and the results indicate that this method can produce better inverted ICs and less simulation errors. In practical experiments, simulation results show good agreement with the ground-level observations during the 22nd Asia-Pacific Economic Cooperation summit period, demonstrating that the new method is effective in practical application fields.

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Exploring spatiotemporal patterns of PM2.5 in China based on ground-level observations for 190 cities

Cited by 105 publications

References 72 publications

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective

Application of Surface Spline Interpolation Method in Parameter Estimation of a PM_2.5 Transport Adjoint Model

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Exploring spatiotemporal patterns of PM2.5 in China based on ground-level observations for 190 cities

Cited by 105 publications

References 72 publications

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

Understanding meteorological influences on PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations across China: a temporal and spatial perspective

Application of Surface Spline Interpolation Method in Parameter Estimation of a PM2.5 Transport Adjoint Model

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Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective

Application of Surface Spline Interpolation Method in Parameter Estimation of a PM_2.5 Transport Adjoint Model