An interprovincial cooperative game model for air pollution control in China

The noncooperative air pollution reduction model (NCRM) that is currently adopted in China to manage air pollution reduction of each individual province has inherent drawbacks. In this paper, we propose a cooperative air pollution reduction game model (CRM) that consists of two parts: (1) an optimization model that calculates the optimal pollution reduction quantity for each participating province to meet the joint pollution reduction goal; and (2) a model that distribute the economic benefit of the cooperation (i.e., pollution reduction cost saving) among the provinces in the cooperation based on the Shapley value method. We applied the CRM to the case of SO₂ reduction in the Beijing–Tianjin–Hebei region in China. The results, based on the data from 2003–2009, show that cooperation helps lower the overall SO₂ pollution reduction cost from 4.58% to 11.29%. Distributed across the participating provinces, such a cost saving from interprovincial cooperation brings significant benefits to each local government and stimulates them for further cooperation in pollution reduction. Finally, sensitivity analysis is performed using the year 2009 data to test the parameters’ effects on the pollution reduction cost savings.

Implications: China is increasingly facing unprecedented pressure for immediate air pollution control. The current air pollution reduction policy does not allow cooperation and is less efficient. In this paper we developed a cooperative air pollution reduction game model that consists of two parts: (1) an optimization model that calculates the optimal pollution reduction quantity for each participating province to meet the joint pollution reduction goal; and (2) a model that distributes the cooperation gains (i.e., cost reduction) among the provinces in the cooperation based on the Shapley value method. The empirical case shows that such a model can help improve efficiency in air pollution reduction. The result of the model can serve as a reference for Chinese government pollution reduction policy design.     

Catalytic oxidation for air pollution control

Bench-scale experiments have been conducted to evaluate a series of titania-supported Pt-Pd (as oxides) catalysts in the presence and absence of MoO₃ and Fe₂O₃ additives for their effectiveness in the complete catalytic oxidation of volatile organic compounds (VOCs) in air likely to be found in waste gases. Under oxidizing conditions, all of the catalysts promoted the complete oxidation of VOCs to CO₂ and H₂O. 99 % Conversion was achieved with a C₂H₄-C₂H₆ gas mixture in air at temperatures between about 160–450 °C and at a space velocity of 20,000 h^?1. Oxidation activity for the titania supported catalysts were found to decrease in the order Pt-Pd-Mo-Fe > Pt-Pd-Mo > Pt-Pd-Fe > Pt-Pd. However, the addition of MoO₃ and Fe₂O₃ increase the catalyst activity and reduce the reaction temperature for the complete destruction. Ageing was also performed in order to study the stability of the most active catalyst. Pt-Pd-Mo-Fe (as oxides) on titania catalyst is effective in oxidizing a wide range of volatile organic compounds at relatively low temperatures (220–405 °C) and and at a space velocity of 40,000 h^?1 and is resistant to poisoning by halogenated and amine volatile organic compounds.     

A new detailed chemical model for indoor air pollution

A detailed chemical box model has been constructed based on a comprehensive chemical mechanism (the Master Chemical Mechanism) to investigate indoor air chemistry in a typical urban residence in the UK. Unlike previous modelling studies of indoor air chemistry, the mechanism adopted contains no simplifications such as lumping or the use of surrogate species, allowing more insight into indoor air chemistry than previously possible. The chemical mechanism, which has been modified to include the degradation reactions of key indoor air pollutants, contains around 15,400 reactions and 4700 species. The results show a predicted indoor OH radical concentration up to 4.0×10⁵ molecule cm⁻³, only a factor of 10–20 less than typically observed outdoors and sufficient for significant chemical cycling to take place. Concentrations of PAN-type species and organic nitrates are found to be important indoors, reaching concentrations of a few ppb. Sensitivity tests highlight that the most crucial parameters for modelling the concentration of OH are the light-intensity levels and the air exchange rate. Outdoor concentrations of O₃ and NO_X are also important in determining radical concentrations indoors. The reactions of ozone with alkenes and monoterpenes play a major role in producing new radicals, unlike outdoors where photolysis reactions are pivotal radical initiators. In terms of radical propagation, the reaction of HO₂ with NO has the most profound influence on OH concentrations indoors. Cycling between OH and RO₂ is dominated by reaction with the monoterpene species, whilst alcohols play a major role in converting OH to HO₂. Surprisingly, the absolute reaction rates are similar to those observed outdoors in a suburban environment in the UK during the summer. The results from this study highlight the importance of tailoring a model for its particular location and the need for future indoor air measurements of radical species, nitrated species such as PANs and organic nitrates, photolysis rates of key species over the range of wavelengths observed indoors and concurrent measurements of outdoor air pollutant concentrations.     

A trajectory plume model for simulating air pollution transients

An air quality simulation model that is simple, yet capable of accurately estimating concentrations under unsteady meteorological conditions, has been developed. This trajectory plume model uses the Gaussian plume equation, but has an applicability that is approximately as wide as the Lagrangian puff model. The plume axis is represented by a series of straight-line plume segments. The performance of this model was evaluated by comparing it with other diffusion models. A comparison between simulation results using the present model and those using integrated puff and Eulerian diffusion models for three different metropolitan areas (one in Japan and two in the U.S.) has indicated that a simple trajectory plume model performs as well as the two other more complex models in simulating pollutant dispersion under complicated meteorological conditions such as those which occur during the transition period from a sea breeze to a land breeze.     

A systems approach to air pollution control

A preliminary study for the systematic investigation and the control of the pollution of the atmosphere over a wide region is considered and discussed.     

等离子体技术应用于气相污染物治理综述

近年来利用等离子体技术对气态污染物的氧化分解研究受到了广泛的关注.介绍了等离子体概念、分类及产生方法,简述了非平衡等离子体技术对气体污染物的降解原理,较全面地介绍了等离子体技术在脱硫、脱硝以及降解挥发性有机物(VOCs)等方面的研究.最后指出了今后等离子体处理废气的应用研究方向.     

工业点源大气污染扩散空间信息系统

开发了一个基于高斯扩散的大气污染扩散空间信息系统,用于模拟工业点源污染对区域大气质量的影响。该工业点源污染模型包括工业点源数据库、扩散参数、气象条件和大气质量评价4个主要数据库。用该模型计算上海市主要工业区的SO2排放,结果表明,该模型为模拟SO2污染扩散提供了一个有效便捷的方法。     

A spatial multicriteria model for determining air pollution at sample locations

Atmospheric pollution in urban centers has been one of the main causes of human illness related to the respiratory and circulatory system. Efficient monitoring of air quality is a source of information for environmental management and public health. This study investigates the spatial patterns of atmospheric pollution using a spatial multicriteria model that helps target locations for air pollution monitoring sites. The main objective was to identify high-priority areas for measuring human exposures to air pollutants as they relate to emission sources. The method proved to be viable and flexible in its application to various areas.

Implications:?Spatial multicriteria models provide a tool for air pollution management in urban areas. Analytic hierarchy process (AHP) modeling can help with the process of prioritizing monitoring site locations and minimizing costs.     

A Gaussian puff model with optimal interpolation for air pollution modelling assessment

A Gaussian plume model was modified to simulate the dispersion of non-reactive air pollutants under non-homogeneous wind conditions through a multi-puff approach. It was applied to the city of Lisbon and evaluated by comparison with measured sulphur dioxide data, showing a reasonable skill to estimate the transport and dispersion of pollutants under complex wind field and different atmospheric conditions. The modelling results were integrated with observed data, based on correlation functions determined from historical values, to obtain the improved analytical results by using optimal interpolation. A significant improvement over the predictions by the Gaussian puff model alone was achieved.