The changing carbon content of coal consumed in China between 2002 and 2012 is quantified using information from the power sector. The carbon content decreased by 7.7% over this interval, the decrease particularly pronounced between 2007 and 2009. Inferences with respect to the changing carbon content of coal and the oxidation rate for its consumption, combined with the recent information on coal use in China, are employed to evaluate the trend in emissions of CO2. Emissions are estimated to have increased by 158% between 2002 and 2012, from 3.9 Gt y-1 to 9.2 Gt y-1. Our estimated emissions for 2005 are notably consistent with data reported by China in its “Second National Communication” to the UN (NDRC, 2012) and significantly higher than the estimation published recently in Nature. The difference is attributed, among other factors, to the assumption of a constant carbon content of coal in the latter study. The results indicate that CO2 emissions of China in 2005 reported by Second National Communication are more reliable to serve as the baseline for China's future carbon commitments (e.g. those in Paris Agreement of the UNFCCC). Discrepancies between national and provincial statistics on coal production and consumption are investigated and attributed primarily to anomalous reporting on interprovincial trade in four heavily industrialized provinces.
Among biomass energy technologies which are treated as the promising way to mitigate critical energy crisis and global climate change, biomass gasification plays a key role given to its gaseous fuels especially syngas for distributed power plant. However, a system analysis for the energy saving and greenhouse gas emissions abatement potentials of gasification system has been directed few attentions. This study presents a system analysis that combines process and input-output analyses of GHG emissions and energy costs throughout the full chain of activities associated with biomass gasification. Incorporating agricultural production, industrial process and wastewater treatment which is always ignored, the energy inputs in life cycle are accounted for the first commercial biomass gasification power plant in China. Results show that the non-renewable energy cost and GHG emission intensity of the biomass gasification system are 0.163 MJ/MJ and 0.137 kg CO2-eq/MJ respectively, which reaffirm its advantages over coal-fired power plants in clean energy and environmental terms. Compared with other biomass energy processes, gasification performs well as its non-renewable energy cost and CO2 intensity are in the central ranges of those for all of these technologies. Construction of the plant is an important factor in the process’s non-renewable energy consumption, contributing about 44.48% of total energy use. Wastewater treatment is the main contributor to GHG emissions. The biomass gasification and associated wastewater treatment technologies have critical influence on the sustainability and renewability of biomass gasification. The results provide comprehensive analysis for biomass gasification performance and technology improvement potential in regulating biomass development policies for aiming to achieve sustainability globally.
Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM≤2.5 micrometers in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.
Current Chinese policy promotes the development of both electricity-propelled vehicles and carbon-free sources of power. Concern has been expressed that electric vehicles on average may emit more CO2 and conventional pollutants in China. Here, we explore the environmental implications of investments in different types of electric vehicle (public buses, taxis and private light-duty vehicles) and different modes (fast or slow) for charging under a range of different wind penetration levels. To do this, we take Beijing in 2020 as a case study and employ hourly simulation of vehicle charging behaviour and power system operation. Assuming the slow-charging option, we find that investments in electric private light-duty vehicles can result in an effective reduction in the emission of CO2 at several levels of wind penetration. The fast-charging option, however, is counter-productive. Electrifying buses and taxis offers the most effective option to reduce emissions of NOx, a major precursor for air pollution.
Deploying high penetration of variable renewables represents a critical pathway for deep decarbonizing the power sector. The conflict between their temporal variability and limited system flexibility has been largely ignored currently at planning stage. Here we present a novel capacity expansion model optimizing investment decisions and full-year, hourly power balances simultaneously, with considerations of storage technologies and policy constraints, such as carbon tax and renewable portfolio standards (RPS). Based on a computational efficient modeling formulation, all flexibility constrains (ramping, reserve, minimum output, minimal online/offline time) for the 8760-hour duration are incorporated. The proposed model is applied to the northwestern grid of China to examine the optimal composition and distribution of power investments with a wide range of renewable targets. Results indicate that the cost can increase moderately towards 45% of RPS, when properly designing the generation portfolio: prioritizing wind investments, distributing renewable investments more evenly and deploying more flexible mid-size coal and gas units. Reaching higher penetrations of renewables is expensive and the reductions of storage costs are critically important for an affordable low-carbon future. RPS or carbon taxes to reach a same target of emission reduction in China will result in similar overall costs but different generation mixes.
To evaluate the effectiveness of national air pollution control policies, the emissions of SO2, NOX, CO and CO2 in China are estimated using bottom-up methods for the most recent 15-year period (2000–2014). Vertical column densities (VCDs) from satellite observations are used to test the temporal and spatial patterns of emissions and to explore the ambient levels of gaseous pollutants across the country. The inter-annual trends in emissions and VCDs match well except for SO2. Such comparison is improved with an optimistic assumption in emission estimation that the emission standards for given industrial sources issued after 2010 have been fully enforced. Underestimation of emission abatement and enhanced atmospheric oxidization likely contribute to the discrepancy between SO2 emissions and VCDs. As suggested by VCDs and emissions estimated under the assumption of full implementation of emission standards, the control of SO2 in the 12th Five-Year Plan period (12th FYP, 2011–2015) is estimated to be more effective than that in the 11th FYP period (2006–2010), attributed to improved use of flue gas desulfurization in the power sector and implementation of new emission standards in key industrial sources. The opposite was true for CO, as energy efficiency improved more significantly from 2005 to 2010 due to closures of small industrial plants. Iron & steel production is estimated to have had particularly strong influence on temporal and spatial patterns of CO. In contrast to fast growth before 2011 driven by increased coal consumption and limited controls, NOX emissions decreased from 2011 to 2014 due to the penetration of selective catalytic/non-catalytic reduction systems in the power sector. This led to reduced NO2 VCDs, particularly in relatively highly polluted areas such as the eastern China and Pearl River Delta regions. In developed areas, transportation is playing an increasingly important role in air pollution, as suggested by the increased ratio of NO2 to SO2 VCDs. For air quality in mega cities, the inter-annual trends in emissions and VCDs indicate that surrounding areas are more influential in NO2 level for Beijing than those for Shanghai.
In the 21st Conference of the Parties to the UNFCCC held in Paris in December 2015, China pledged to peak its carbon emissions and increase non-fossil energy to 20% by 2030 or earlier. Expanding renewable capacity, especially wind power, is a central strategy to achieve these climate goals. Despite greater capacity for wind installation in China compared to the US (145.1 versus 75.0 GW), less wind electricity is generated in China (186.3 versus 190.9 TWh). Here, we quantify the relative importance of the key factors accounting for the unsatisfactory performance of Chinese wind farms. Different from the results in earlier qualitative studies, we find that the difference in wind resources explains only a small fraction of the present China-US difference in wind power output (17.9% in 2012); the curtailment of wind power, differences in turbine quality, and delayed connection to the grid are identified as the three primary factors (respectively 49.3%, 50.2%, and 50.3% in 2012). Improvements in both technology choices and the policy environment are critical in addressing these challenges.
With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM2.5) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions.
Development of shale gas resources is expected to play an important role in China's projected transition to a low-carbon energy future. The question arises whether the availability of water could limit this development. The paper considers a range of scenarios to define the demand for water needed to accommodate China's projected shale gas production through 2020. Based on data from the gas field at Fuling, the first large-scale shale gas field in China, it is concluded that the water intensity for shale gas development in China (water demand per unit lateral length) is likely to exceed that in the US by about 50%. Fuling field would require a total of 39.9–132.9 Mm3 of water to achieve full development of its shale gas, with well spacing assumed to vary between 300 and 1000 m. To achieve the 2020 production goal set by Sinopec, the key Chinese developer, water consumption is projected to peak at 7.22 Mm3 in 2018. Maximum water consumption would account for 1% and 3%, respectively, of the available water resource and annual water use in the Fuling district. To achieve China's nationwide shale gas production goal set for 2020, water consumption is projected to peak at 15.03 Mm3 in 2019 in a high-use scenario. It is concluded that supplies of water are adequate to meet demand in Fuling and most projected shale plays in China, with the exception of localized regions in the Tarim and Jungger Basins.
Accommodating variable wind power poses a critical challenge for electric power systems that are heavily dependent on combined heat and power (CHP) plants, as is the case for north China. An improved unit-commitment model is applied to evaluate potential benefits from pumped hydro storage (PHS) and electric boilers (EBs) in West Inner Mongolia (WIM), where CHP capacity is projected to increase to 33.8 GW by 2020. A business-as-usual (BAU) reference case assumes deployment of 20 GW of wind capacity. Compared to BAU, expanding wind capacity to 40 GW would allow for a reduction in CO2 emissions of 33.9 million tons, but at a relatively high cost of US$25.3/ton, reflecting primarily high associated curtailment of wind electricity (20.4%). A number of scenarios adding PHS and/or EBs combined with higher levels of wind capacity are evaluated. The best case indicates that a combination of PHS (3.6 GW) and EBs (6.2 GW) together with 40 GW of wind capacity would reduce CO2 emissions by 43.5 million tons compared to BAU, and at a lower cost of US$16.0/ton. Achieving this outcome will require a price-incentive policy designed to ensure the profitability of both PHS and EB facilities.
With most eastern Chinese cities facing major air quality challenges, there is a strong need for city-scale emission inventories for use in both chemical transport modeling and the development of pollution control policies. In this paper, a high-resolution emission inventory of air pollutants and CO2 for Nanjing, a typical large city in the Yangtze River Delta, is developed incorporating the best available information on local sources. Emission factors and activity data at the unit or facility level are collected and compiled using a thorough onsite survey of major sources. Over 900 individual plants, which account for 97% of the city's total coal consumption, are identified as point sources, and all of the emission-related parameters including combustion technology, fuel quality, and removal efficiency of air pollution control devices (APCD) are analyzed. New data-collection approaches including continuous emission monitoring systems and real-time monitoring of traffic flows are employed to improve spatiotemporal distribution of emissions. Despite fast growth of energy consumption between 2010 and 2012, relatively small inter-annual changes in emissions are found for most air pollutants during this period, attributed mainly to benefits of growing APCD deployment and the comparatively strong and improving regulatory oversight of the large point sources that dominate the levels and spatial distributions of Nanjing emissions overall. The improvement of this city-level emission inventory is indicated by comparisons with observations and other inventories at larger spatial scale. Relatively good spatial correlations are found for SO2, NOX, and CO between the city-scale emission estimates and concentrations at 9 state-opertated monitoring sites (R = 0.58, 0.46, and 0.61, respectively). The emission ratios of specific pollutants including BC to CO, OC to EC, and CO2 to CO compare well to top-down constraints from ground observations. The inter-annual variability and spatial distribution of NOX emissions are consistent with NO2 vertical column density measured by the Ozone Monitoring Instrument (OMI). In particular, the Nanjing city-scale emission inventory correlates better with satellite observations than the downscaled Multi-resolution Emission Inventory for China (MEIC) does when emissions from power plants are excluded. This indicates improvement in emission estimation for sectors other than power generation, notably industry and transportation. High-resolution emission inventory may also provide a basis to consider the quality of instrumental observations. To further improve emission estimation and evaluation, more measurements of both emission factors and ambient levels of given pollutants are suggested; the uncertainties of emission inventories at city scale should also be fully quantified and compared with those at national scale.