Citizen participation and urban air pollution abatement: Evidence from environmental whistle-blowing platform policy in Sichuan China

Author(s):  
Xuan Leng ◽  
Shihu Zhong ◽  
Yankun Kang
2020 ◽  
Vol 13 (3) ◽  
pp. 1623-1634 ◽  
Author(s):  
Peter Wind ◽  
Bruce Rolstad Denby ◽  
Michael Gauss

Abstract. We present a computationally inexpensive method for individually quantifying the contributions from different sources to local air pollution. It can explicitly distinguish between regional–background and local–urban air pollution, allowing for fully consistent downscaling schemes. The method can be implemented in existing Eulerian chemical transport models and can be used to distinguish the contribution of a large number of emission sources to air pollution in every receptor grid cell within one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence, it can be used for time-critical operational services by providing scientific information as input for local policy decisions on air pollution abatement. The main limitation in its current version is that nonlinear chemical processes are not accounted for and only primary pollutants can be addressed. In this paper we provide a technical description of the method and discuss various applications for scientific and policy purposes.


2019 ◽  
Author(s):  
Peter Wind ◽  
Bruce Rolstad Denby ◽  
Michael Gauss

Abstract. We present a computationally inexpensive method for individually quantifying the contributions from different sources to local air pollution. It can explicitly distinguish between regional/background and local/urban air pollution, allowing fully consistent downscaling schemes. The method can be implemented in existing Eulerian chemical transport models and can be used to distinguish a large number of emission sources to air pollution in every receptor grid cell within one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence it can be used for time-critical operational services providing scientific information as input to local policy decisions on air pollution abatement. The main limitation in its current version is that only primary pollutants can be addressed. In this paper we provide a technical description of the method and discuss various applications for scientific and policy purposes.


2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.


2020 ◽  
Vol 1 (3) ◽  
pp. 100047 ◽  
Author(s):  
Donghai Liang ◽  
Liuhua Shi ◽  
Jingxuan Zhao ◽  
Pengfei Liu ◽  
Jeremy A. Sarnat ◽  
...  

Author(s):  
Nikolaos Sifakis ◽  
Maria Aryblia ◽  
Tryfon Daras ◽  
Stavroula Tournaki ◽  
Theocharis Tsoutsos

2021 ◽  
Vol 246 ◽  
pp. 118094
Author(s):  
Erik Velasco ◽  
Armando Retama ◽  
Miguel Zavala ◽  
Marc Guevara ◽  
Bernhard Rappenglück ◽  
...  

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