|Title||China Energy and Emissions Paths to 2030 (2nd Edition)|
|Year of Publication||2012|
|Authors||David Fridley, Nina Zheng, Nan Zhou, Jing Ke, Ali Hasanbeigi, William R Morrow, III, Lynn K Price|
|Tertiary Authors||Nina Khanna|
|Institution||Lawrence Berkeley National Laboratory|
|Keywords||China, China 2050, China Energy, China Energy Group, data, emissions, energy, Energy Analysis and Environmental Impacts Division, International Energy Department, modeling, scenarios|
After over two decades of staggering economic growth and soaring energy demand, China has started taking serious actions to reduce its economic energy and carbon intensity by setting short and medium-term intensity reduction targets, renewable generation targets and various supporting policies and programs. In better understanding how further policies and actions can be taken to shape China's future energy and emissions trajectory, it is important to first identify where the largest opportunities for efficiency gains and emission reduction lie from sectoral and end-use perspectives. Besides contextualizing China's progress towards reaching the highest possible efficiency levels through the adoption of the most advanced technologies from a bottom-up perspective, the actual economic costs and benefits of adopting efficiency measures are also assessed in this study.
This study presents two modeling methodologies that evaluate both the technical and economic potential of raising China's efficiency levels to the technical maximum across sectors and the subsequent carbon and energy emission implications through 2030. The technical savings potential by efficiency measure and remaining gap for improvements are identified by comparing a reference scenario in which China continues the current pace of with a Max Tech scenario in which the highest technically feasible efficiencies and advanced technologies are adopted irrespective of costs. In addition, from an economic perspective, a cost analysis of selected measures in the key industries of cement and iron and steel help quantify the actual costs and benefits of achieving the highest efficiency levels through the development of cost of conserved energy curves for the sectors.
The results of this study show that total annual energy savings potential of over one billion tonne of coal equivalent exists beyond the expected reference pathway under Max Tech pathway in 2030. CO2 emissions will also peak earlier under Max Tech, though the 2020s is a likely turning point for both emission trajectories. Both emission pathways must meet all announced and planned policies, targets and non-fossil generation targets, or an even wider efficiency gap will exist. The savings potential under Max Tech varies by sector, but the industrial sector appears to hold the largest energy savings and emission reduction potential. The primary source of savings is from electricity rather than fuel, and electricity savings are magnified by power sector decarbonization through increasing renewable generation and coal generation efficiency improvement. In order to achieve the maximum energy savings and emission reduction potential, efficiency improvements and technology switching must be undertaken across demand sectors as well as in the growing power sector.
Using the bottom-up conservation supply curve models for the cement industry, the cumulative cost-effective electricity savings potential for 2010-2030 is estimated to be 251 TWh, and the total technical electricity savings potential is 279 TWh. The cumulative cost-effective fuel savings potential is 4,326 PJ which is equivalent to the total technical potential. The CO2 emission reductions associated with the total fuel saving potential is 406 Mt CO2. For the steel industry, the cumulative cost-effective electricity savings potential for 2010-2030 is estimated to be 251 TWh, and the total technical electricity savings potential is 416 TWh. The cumulative cost-effective fuel savings potential is 11,999 PJ, and the total technical fuel saving potential is 12,139. The total potential savings from these measures confirm the magnitude of savings in the scenario models, and illustrate the remaining efficiency gap in the cement and iron and steel industries.