Causation mechanism analysis for haze pollution related to vehicle emission in Guangzhou, China by employing the fault tree approach

Huang, Weiqing; Fan, Hongsong; Qiu, Yongfu; Cheng, Zhiyu; Xu, Pingru; Qian, Yu

doi:10.1016/j.chemosphere.2016.02.024

Cited by 32 publications

(13 citation statements)

References 24 publications

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“…On the other hand, the actual geographical distribution of urban functional zones is significant to satisfy the lifestyles of citizens and the availability of urban space regions [8]. The fine-scale urban functional zones division not only helps distinguish between working and living areas, but also copes with problems such as traffic congestion, air pollution and waste of land resources [9,10]. Hence, perceiving urban spatial structures accurately and identifying urban functional zones precisely are of great significance for the formulation of productive urban planning policies and regulations.…”

Section: Introductionmentioning

confidence: 99%

A New Remote Sensing Images and Point-of-Interest Fused (RPF) Model for Sensing Urban Functional Regions

Qing

Han³

et al. 2020

Remote Sensing

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For urban planning and environmental monitoring, it is essential to understand the diversity and complexity of cities to identify urban functional regions accurately and widely. However, the existing methods developed in the literature for identifying urban functional regions have mainly been focused on single remote sensing image data or social sensing data. The multi-dimensional information which was attained from various data source and could reflect the attribute or function about the urban functional regions that could be lost in some extent. To sense urban functional regions comprehensively and accurately, we developed a multi-mode framework through the integration of spatial geographic characteristics of remote sensing images and the functional distribution characteristics of social sensing data of Point-of-Interest (POI). In this proposed framework, a deep multi-scale neural network was developed first for the functional recognition of remote sensing images in urban areas, which explored the geographic feature information implicated in remote sensing. Second, the POI function distribution was analyzed in different functional areas of the city, then the potential relationship between POI data categories and urban region functions was explored based on the distance metric. A new RPF module is further deployed to fuse the two characteristics in different dimensions and improve the identification performance of urban region functions. The experimental results demonstrated that the proposed method can efficiently achieve the accuracy of 82.14% in the recognition of functional regions. It showed the great usability of the proposed framework in the identification of urban functional regions and the potential to be applied in a wide range of areas.

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Section: Introductionmentioning

confidence: 99%

A New Remote Sensing Images and Point-of-Interest Fused (RPF) Model for Sensing Urban Functional Regions

Qing

Han³

et al. 2020

Remote Sensing

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“…The core variables of energy application mainly include energy intensity, energy consumption structure, etc. [27][28][29] and the main variables of urban development include urbanization, vehicle use, and so on [30][31][32][33]. The significant relationship between these key variables and haze pollution has been scientifically and rigorously verified in the corresponding studies.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial–Temporal Heterogeneous Evolution of Haze Pollution in China as Deduced with the Use of Spatial Econometrics

et al. 2019

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Haze Pollution, consisting essentially of PM2.5 and PM10, has been arousing wide public concern home and abroad. It has become a universal urgency for atmospheric researchers, governments, organizations, institutions, and the general public to conduct corresponding actions. Therefore, this paper aims to explore the institutional distribution and the regional evolution trend of path characteristics of haze pollution in China under the spatial–temporal heterogeneity on the basis of spatial econometrics, by incorporating the spatial element into the framework of the Multiple Influencing Factors mechanism. The results show that it has been abating under the governance year by year, though with a decreasing intensity; the major polluted regions have been moving from the East to the central and western area; there is significant spatial autocorrelation among the highly polluted area, but the effective local regulations of les- polluted regions do not impact the neighboring regions correspondingly; among the impacting factors, industrial structure, energy intensity, and traffic pollution have a significant Positive Impact on haze pollution, and the level of urbanization has a Negative Impact, while economic growth and innovation performance have no significant Positive Impact and are both weak in promotion. This research, theoretically and practically, offers reference for the Chinese government to integrate regional effective systems into multiregional diversified environmental governance, so as to realize its Green Ecology Transformation Development Strategy.

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“…Large cities in China, such as Beijing, Shanghai and Guangzhou, have experienced frequent hazy weather because of the air pollution from vehicle emissions [11]. Data from the China National Environmental Monitoring Centre [12] show that Beijing experienced twelve days of heavy pollution and four days of severe pollution during the first half of 2017.…”

Section: Introductionmentioning

confidence: 99%

The Evolution of China’s New Energy Vehicle Industry from the Perspective of a Technology–Market–Policy Framework

Jian

Yang

et al. 2019

Sustainability

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Since air pollution and energy safety have become two worldwide concerns, New Energy Vehicles (NEVs) are one of the solutions to solve these problems. China has been taking action toward the NEV industry and has been successful. This paper aims to explore the evolution of the Chinese NEV industry. By using a three-dimensional model of technology, market and policy, we collected the national level policies from three NEV developmental stages based on the market sales. We found three reasons for its rising up in China: first, the NEV technical road has been directed by both the government and the market; second, the market has periodicity, so the prospective policies have been set ahead; and third, the government has transformed its role on time. Based on the resource endowment the industry has now, we can draw some inferences on its further development in the longitudinal direction.

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Causation mechanism analysis for haze pollution related to vehicle emission in Guangzhou, China by employing the fault tree approach

Cited by 32 publications

References 24 publications

A New Remote Sensing Images and Point-of-Interest Fused (RPF) Model for Sensing Urban Functional Regions

A New Remote Sensing Images and Point-of-Interest Fused (RPF) Model for Sensing Urban Functional Regions

Spatial–Temporal Heterogeneous Evolution of Haze Pollution in China as Deduced with the Use of Spatial Econometrics

The Evolution of China’s New Energy Vehicle Industry from the Perspective of a Technology–Market–Policy Framework

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