Effect of current emission abatement strategies on air quality improvement in China:A case study of Baotou,a typical industrial city in Inner Mongolia

The national Air Pollution Prevention and Control Action Plan required significant decreases in PM_（2.5） levels over China.To explore more effective emission abatement strategies in industrial cities,a case study was conducted in Baotou to evaluate the current national control measures.The total emissions of SO_2,NO_X,PM_（2.5） and NMVOC（non-methane volatile organic compounds） in Baotou were 211.2 Gg,156.1 Gg,28.8 Gg,and 48.5 Gg,respectively in 2013,and they would experience a reduction of 30.4%,26.6%,15.1%,and 8.7%,respectively in 2017 and 39.0%,32.0%,24.4%,and 12.9%,respectively in2020.The SO_2,NO_Xand PM_（2.5） emissions from the industrial sector would experience a greater decrease,with reductions of 37%,32.7 and 24.3%,respectively.From 2013 to 2020,the concentrations of SO_2,NO_2,and PM_（2.5） are expected to decline by approximately 30%,10% and 14.5%,respectively.The reduction rate of SNA（sulfate,nitrate and ammonium）concentrations was significantly higher than that of PM_（2.5） in 2017,implying that the current key strategy toward controlling air pollutants from the industrial sector is more powerful for SNA.Although air pollution control measures implemented in the industrial sector could greatly reduce total emissions,constraining the emissions from lower sources such as residential coal combustion would be more effective in decreasing the concentration of PM_（2.5） from 2017 to 2020.These results suggest that even for a typical industrial city,the reduction of PM_（2.5） concentrations not only requires decreases in emissions from the industrial sector,but also from the low emission sources.The seasonal variation in sulfate concentration also showed that emission from coal-burning is the key factor to control during the heating season.

A NON-LINEAR MODEL FOR ESTIMATING THE COST OF ACHIEVING EMISSION REDUCTION TARGETS:THE CASE OF THE U.S.,CHINA AND INDIA

With the world talking about climate change, the United States （U.S.）, China and India have announced their carbon emission reduction targets. For these three countries to achieve their targets, significant questions arise, shch as what will be the annual emission reduction efforts to achieve those targets, how much it would cost and what would be the economic effects. This paper puts the carbon intensity reduction targets of China and India together with the absolute emission reduction target of the U.S. into the same non-linear model to quantitatively study the optimal emission control strategies and associated total cost for achieving those targets by the year 2020, and estimate and compare the minimized total costs of the three countries to reach their targets. Our results show that the total cost for the U.S. to achieve its emission reduction target is greater than those of China and India in terms of absolute amount. However, in terms of proportion of total cost to GDP, China and India＇s ratios are significantly greater than that of the U.S., indicating that for the developing countries such as China and India, the achievement of emission reduction targets needs relatively greater effort.

Enhancement of the polynomial functions response surface model for real-time analyzing ozone sensitivity

Quantification of the nonlinearities between ambient ozone(O3)and the emissions of nitrogen oxides(NOx)and volatile organic compound(VOC)is a prerequisite for an effective O3 control strategy.An Enhanced polynomial functions Response Surface Model(Epf-RSM)with the capability to analyze O3-NOx-VOC sensitivities in real time was developed by integrating the hill-climbing adaptive method into the optimized Extended Response Surface Model(ERSM)system.The Epf-RSM could single out the best suited polynomial function for each grid cell to quantify the responses of O3 concentrations to precursor emission changes.Several comparisons between Epf-RSM and pf-ERSM(polynomial functions based ERSM)were performed using out-of-sample validation,together with comparisons of the spatial distribution and the Empirical Kinetic Modeling Approach diagrams.The comparison results showed that Epf-RSM effectively addressed the drawbacks of pf-ERSM with respect to overfitting in the margin areas and high biases in the transition areas.The O3 concentrations predicted by Epf-RSM agreed well with Community Multi-scale Air Quality simulation results.The case study results in the Pearl River Delta and the north-western area of the Shandong province indicated that the O3 formations in the central areas of both the regions were more sensitive to anthropogenic VOC in January,April,and October,while more NOx-sensitive in July.