The development of reliable anthropogenic emission inventories is essential for both understanding the sources of air pollution and designing effective air-pollution-control measures in China. However, it is challenging to quantify emissions in China accurately, given the variety of contributing sources, the complexity of the technology mix and the lack of reliable measurements. Over the last two decades, tremendous efforts have been made to improve the accuracy of emission inventories, and significant improvements have been realized. More reliable statistics and survey-based data have been used to reduce the uncertainties in activity rates and technology distributions. Local emission factors and source profiles covering various sources have been measured and reported. Based on these local databases, improved emission inventory models have been developed for power plants, large industrial plants and the residential, transportation and agricultural sectors. In this paper, we review the progress that has been made in developing inventories of anthropogenic emissions in China. We first highlight the major updates that have been made to emission inventory models and the underlying data by source category. We then summarize the sector-based estimates of emissions of different species contained in current inventories. The progress that has been made in the development of model-ready emissions is also presented. Finally, we suggest future directions for further improving the accuracy of emission inventories in China.

Nitrogen oxides (NO_x) are key pollutants for the improvement of ambient air quality. Within this study we estimated the historical NO_x emissions in China for the period 1995–2010, and calculated future NO_x emissions every five years until 2030 under six emission scenarios. Driven by the fast growth of energy consumption, we estimate the NO_x emissions in China increased rapidly from 11.0 Mt in 1995 to 26.1 Mt in 2010. Power plants, industry and transportation were major sources of NO_x emissions, accounting for 28.4%, 34.0%, and 25.4% of the total NO_x emissions in 2010, respectively. Two energy scenarios, a business as usual scenario (BAU) and an alternative policy scenario (PC), were developed to project future energy consumption. In 2030, total energy consumption is projected to increase by 64% and 27% from 2010 level respectively. Three sets of end-of-pipe pollution control measures, including baseline, progressive, and stringent control case, were developed for each energy scenario, thereby constituting six emission scenarios. By 2030, the total NO_x emissions are projected to increase (compared to 2010) by 36% in the baseline while policy cases result in reduction up to 61% in the most ambitious case with stringent control measures. More than a third of the reduction achieved by 2030 between least and most ambitious scenario comes from power sector, and more than half is distributed equally between industry and transportation sectors. Selective catalytic reduction dominates the NO_x emission reductions in power plants, while life style changes, control measures for industrial boilers and cement production are major contributors to reductions in industry. Timely enforcement of legislation on heavy-duty vehicles would contribute significantly to NO_x emission reductions. About 30% of the NO_x emission reduction in 2020 and 40% of the NO_x emission reduction in 2030 could be treated as the ancillary benefit of energy conservation. Sensitivity analysis was conducted to explore the impact of key factors on future emissions.

This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.