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Abstract: Emission from motor vehicles is the most important source of polycyclic aromatic hydrocarbons (PAHs) in urban areas. Emission factors of individual PAHs for motor vehicles reported in the literature varied 4 to 5 orders of magnitude, leading to high uncertainty in emission inventory. In this study, key factors affecting emission factors of PAHs (EFPAH) for motor vehicles were evaluated quantitatively based on thousands of EFPAH measured in 16 countries for over 50 years. The result was used to develop a global emission inventory of PAHs from motor vehicles. It was found that country and vehicle model year are the most important factors affecting EFPAH, which can be quantified using a monovariate regression model with per capita gross domestic production (purchasing power parity) as a sole independent variable. On average, 29% of variation in log-transformed EFPAH could be explained by the model, which was equivalent to 90% reduction in overall uncertainty on arithmetic scale. The model was used to predict EFPAH and subsequently PAH emissions from motor vehicles for various countries in the world during a period from 1971 to 2030. It was estimated that the global emission reached its peak value of approximate 101 Gg in 1978 and decreased afterwards due to emission control in developed countries. The annual emission picked up again since 1990 owing to accelerated energy consumption in China and other developing countries. With more and more rigid control measures taken in the developing world, global emission of PAHs is currently passing its second peak. It was predicted that the emission would decrease from 77 Gg in 2010 to 42 Gg in 2030. [Copyright &y& Elsevier]

Published emission factors (EFs) often vary significantly, leading to high uncertainties in emission estimations. There are few reliable EFs from field measurements of residential wood combustion in China. In this study, 17 wood fuels and one bamboo were combusted in a typical residential stove in rural China to measure realistic EFs of particulate matter (PM), organic carbon (OC), and elemental carbon (EC), as well as to investigate the influence of fuel properties and combustion conditions on the EFs. Measured EFs of PM, OC, and SC (EFPM, EFOC and EFEC respectively) were in the range of 0.38-6.4, 0.024-3.0, and 0.039-3.9 gJkg (dry basis), with means and standard derivation of 2.2 ± 1.2, 0.62 ± 0.64, and 0.83 ± 0.69 g/kg respectively. Shrubby biomass combustion produced higher EFs than tree woods, and both species had lower EFs than those of indoor crop residue burning (p <005). Significant correlations between EFPM, EFOC, and EFEC were expected. By using a nine-stage cascade impactor, it was shown that size distributions of PM emitted from tree biomass combustions were unimodal with peaks at a diameter less than 0.4 μm (PM0,4), much finer than the PM from indoor crop residue burning. Approximately 79.4% of the total PM from tree wood combustion was PM with a diameter less than 2.1 μm (PM2.1). PM size distributions for shrubby biomasses were slightly different from those for tree fuels. On the basis of the measured EFs, total emissions of PM, OC, and EC from residential wood combustion in rural China in 2007 were estimated at about 303, 75.7, and 92.0 Gg. [ABSTRACT FROM AUTHOR]

Background: Quantifying CO2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO2 emissions. As the largest urbanized megalopolis region in northern China, the Beijing-Tianjin-Hebei (Jing-Jin-Ji, JJJ) region (population: 112.7 million) is under considerable pressure to reduce carbon emissions. Despite the several emission inventories covering the JJJ region, a comprehensive evaluation of the CO2 emissions at the prefectural city scale in JJJ is still limited, and this information is crucial to implementing mitigation strategies. Results: Here, we collected and analyzed 8 published emission inventories to assess the emissions and uncertainty at the JJJ city level. The results showed that a large discrepancy existed in the JJJ emissions among downscaled country-level emission inventories, with total emissions ranging from 657 to 1132 Mt CO2 (or 849 ± 214 for mean ± standard deviation (SD)) in 2012, while emission estimates based on provincial-level data estimated emissions to be 1038 and 1056 Mt. Compared to the mean emissions of city-data-based inventories (989 Mt), provincial-data-based inventories were 6% higher, and national-data-based inventories were 14% lower. Emissions from national-data-based inventories were 53–75% lower in the high-emitting industrial cities of Tangshan and Handan, while they were 47–160% higher in Beijing and Tianjin than those from city-data-based inventories. Spatially, the emissions pattern was consistent with the distribution of urban areas, and urban emissions in Beijing contributed 50–70% of the total emissions. Higher emissions from Beijing and Tianjin resulted in lower estimates of prefectural cities in Hebei for some national inventories. Conclusions: National-level data-based emission inventories produce large differences in JJJ prefectural city-level emission estimates. The city-level statistics data-based inventories produced more consistent estimates. The consistent spatial distribution patterns recognized by these inventories (such as high emissions in southern Beijing, central Tianjin and Tangshan) potentially indicate areas with robust emission estimates. This result could be useful in the efficient deployment of monitoring instruments, and if proven by such measurements, it will increase our confidence in inventories and provide support for policy makers trying to reduce emissions in key regions. [ABSTRACT FROM AUTHOR]