China Energy Databook -- User Guide and Documentation, Version 7.0

Fridley, David; Aden, Nathaniel; Lu, Hongyou; Zheng, Nina

doi:10.2172/941686

Cited by 8 publications

(10 citation statements)

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“…There are three sets of EFs in the NDRC data, corresponding to three tiers of fuel classifications, four sets in NC and two sets in UN. We combined these 12 sets of EFs with two sets of energy statistics derived from national and provincial data 6,36 . This yielded 24 possible inventories for China's carbon emissions of fossil fuel combustion for 1997-2012 (Extended Data Table 1).…”

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confidence: 99%

Reduced carbon emission estimates from fossil fuel combustion and cement production in China

Liu

Guan

Wei

et al. 2015

Nature

1,284

639

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Nearly three-quarters of the growth in global carbon emissions from the burning of fossil fuels and cement production between 2010 and 2012 occurred in China. Yet estimates of Chinese emissions remain subject to large uncertainty; inventories of China's total fossil fuel carbon emissions in 2008 differ by 0.3 gigatonnes of carbon, or 15 per cent. The primary sources of this uncertainty are conflicting estimates of energy consumption and emission factors, the latter being uncertain because of very few actual measurements representative of the mix of Chinese fuels. Here we re-evaluate China's carbon emissions using updated and harmonized energy consumption and clinker production data and two new and comprehensive sets of measured emission factors for Chinese coal. We find that total energy consumption in China was 10 per cent higher in 2000-2012 than the value reported by China's national statistics, that emission factors for Chinese coal are on average 40 per cent lower than the default values recommended by the Intergovernmental Panel on Climate Change, and that emissions from China's cement production are 45 per cent less than recent estimates. Altogether, our revised estimate of China's CO2 emissions from fossil fuel combustion and cement production is 2.49 gigatonnes of carbon (2 standard deviations = ±7.3 per cent) in 2013, which is 14 per cent lower than the emissions reported by other prominent inventories. Over the full period 2000 to 2013, our revised estimates are 2.9 gigatonnes of carbon less than previous estimates of China's cumulative carbon emissions. Our findings suggest that overestimation of China's emissions in 2000-2013 may be larger than China's estimated total forest sink in 1990-2007 (2.66 gigatonnes of carbon) or China's land carbon sink in 2000-2009 (2.6 gigatonnes of carbon)

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mentioning

confidence: 99%

Reduced carbon emission estimates from fossil fuel combustion and cement production in China

Liu

Guan

Wei

et al. 2015

Nature

1,284

639

View full text Add to dashboard Cite

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“…Inhalation values for each coal power plant are summed over total emissions from arbitrary energy demands in each power grid (EV use in this case), to estimate the impact per energy production. We include 14% generation and transmission losses, China’s average. , Total inhalation in county x is the sum of incremental inhalation from emissions from all coal power plants.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…We include 14% generation and transmission losses, China's average. 41,53 Total inhalation in county x is the sum of incremental inhalation from emissions from all coal power plants.…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

Environmental Justice Aspects of Exposure to PM_2.5 Emissions from Electric Vehicle Use in China

Cherry

Zhou

et al. 2015

Environ. Sci. Technol.

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Plug-in electric vehicles (EVs) in China aim to improve sustainability and reduce environmental health impacts of transport emissions. Urban use of EVs rather than conventional vehicles shifts transportation's air pollutant emissions from urban areas (tailpipes) to predominantly rural areas (power plants), changing the geographic distribution of health impacts. We model PM2.5-related health impacts attributable to urban EV use for 34 major cities. Our investigation focuses on environmental justice (EJ) by comparing pollutant inhalation versus income among impacted counties. We find that EVs could increase EJ challenge in China: most (~77%, range: 41-96%) emission inhalation attributable to urban EVs use is distributed to predominately rural communities whose incomes are on average lower than the cities where EVs are used. Results vary dramatically across cities depending on urban income and geography. Discriminant analysis reveals that counties with low income and high inhalation of urban EV emissions have comparatively higher agricultural employment rates, higher mortality rates, more children in the population, and lower education levels. We find that low-emission electricity sources such as renewable energy can help mitigate EJ issues raised here. Findings here are not unique to EVs, but instead are relevant for nearly all electricity-consuming technologies in urban areas.

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“…3 Automobile ownership increased more than an order of magnitude in one decade, from 3 cars per 1000 people in 1998 to at least 39 cars per 1000 people in 2009. 1,4 Encouraging motorized transportation is a national strategy for economic and social development in China. 5,6 This article's focus on electric vehicles (EVs: electric cars [e-cars] and electric two-wheelers including electric bicycles and light electric scooters [e-bikes]) in China is motivated in part by their unprecedented rise in popularity (Figure 1).…”

Section: ■ Introductionmentioning

confidence: 99%

Electric Vehicles in China: Emissions and Health Impacts

Cherry

Bechle

et al. 2012

Environ. Sci. Technol.

209

104

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E-bikes in China are the single largest adoption of alternative fuel vehicles in history, with more than 100 million e-bikes purchased in the past decade and vehicle ownership about 2× larger for e-bikes as for conventional cars; e-car sales, too, are rapidly growing. We compare emissions (CO(2), PM(2.5), NO(X), HC) and environmental health impacts (primary PM(2.5)) from the use of conventional vehicles (CVs) and electric vehicles (EVs) in 34 major cities in China. CO(2) emissions (g km(-1)) vary and are an order of magnitude greater for e-cars (135-274) and CVs (150-180) than for e-bikes (14-27). PM(2.5) emission factors generally are lower for CVs (gasoline or diesel) than comparable EVs. However, intake fraction is often greater for CVs than for EVs because combustion emissions are generally closer to population centers for CVs (tailpipe emissions) than for EVs (power plant emissions). For most cities, the net result is that primary PM(2.5) environmental health impacts per passenger-km are greater for e-cars than for gasoline cars (3.6× on average), lower than for diesel cars (2.5× on average), and equal to diesel buses. In contrast, e-bikes yield lower environmental health impacts per passenger-km than the three CVs investigated: gasoline cars (2×), diesel cars (10×), and diesel buses (5×). Our findings highlight the importance of considering exposures, and especially the proximity of emissions to people, when evaluating environmental health impacts for EVs.

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China Energy Databook -- User Guide and Documentation, Version 7.0

Cited by 8 publications

References 0 publications

Reduced carbon emission estimates from fossil fuel combustion and cement production in China

Reduced carbon emission estimates from fossil fuel combustion and cement production in China

Environmental Justice Aspects of Exposure to PM_2.5 Emissions from Electric Vehicle Use in China

Electric Vehicles in China: Emissions and Health Impacts

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China Energy Databook -- User Guide and Documentation, Version 7.0

Cited by 8 publications

References 0 publications

Reduced carbon emission estimates from fossil fuel combustion and cement production in China

Reduced carbon emission estimates from fossil fuel combustion and cement production in China

Environmental Justice Aspects of Exposure to PM2.5 Emissions from Electric Vehicle Use in China

Electric Vehicles in China: Emissions and Health Impacts

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Product

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Environmental Justice Aspects of Exposure to PM_2.5 Emissions from Electric Vehicle Use in China