引用本文: | 李舒惠,曹闪闪,杨依,程丹阳,樊林平,刘敏.2023.长三角地区2000 — 2019年黑碳排放核算及其不确定性[J].地球环境学报,14(1):86-97, 109 |
| LI Shuhui, CAO Shanshan, YANG Yi, CHENG Danyang, FAN Linping, LIU Min.2023.Accounting and uncertainty analysis of black carbon emissions in the Yangtze River Delta from 2000 to 2019[J].Journal of Earth Environment,14(1):86-97, 109 |
|
摘要: |
基于国家能源活动统计资料,使用排放因子法建立了长三角地区2000—2019年黑碳排放清单,并利用Monte Carlo方法量化排放因子对黑碳排放核算的影响及不确定性。研究结果表明:(1)近20 a长三角地区总黑碳排放量由10.72×107 kg(2000年)增加至12.54×107 kg(2019年),增长了16.98%;黑碳排放源结构发生显著变化,2000年居民生活是长三角地区最主要的黑碳排放源(占42.2%);自2006年开始工业逐渐成为研究区最主要的黑碳排放源,2019年工业排放占长三角地区黑碳排放总量的63.2%。(2)长三角地区黑碳排放存在明显的空间分异。总体而言,江苏省黑碳排放总量和人均黑碳排放强度居长三角地区首位,安徽省单位GDP黑碳排放最高,上海市单位面积黑碳排放强度最高,而浙江省人均和单位面积黑碳排放强度最低。(3)考虑黑碳排放核算过程中排放因子的取值差异,2019年长三角地区黑碳排放总量为7.13×107—14.49×107 kg(95%置信区间),相对不确定性为−33.50%—35.11%。工业排放因子是长三角黑碳排放核算不确定性的主要贡献者。 |
关键词: 黑碳 排放清单 不确定性 长三角地区 |
DOI:10.7515/JEE222041 |
CSTR:32259.14.JEE222041 |
分类号: |
基金项目:国家自然科学基金项目(41977399) |
英文基金项目:National Natural Science Foundation of China (41977399) |
|
Accounting and uncertainty analysis of black carbon emissions in the Yangtze River Delta from 2000 to 2019 |
LI Shuhui, CAO Shanshan, YANG Yi, CHENG Danyang, FAN Linping, LIU Min
|
1. Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
2. Institute of Eco-Chongming (IEC), East China Normal University, Shanghai 202162, China
|
Abstract: |
Background, aim, and scope Black carbon (BC) is a greenhouse gas with a warming benefit second only to that of CO2. This has an impact on regional climate change and human health. The aim of this study was to examine the BC emission inventory and its uncertainty in the Yangtze River Delta (YRD), one of the fastest growing economies in China, and to provide a scientific basis for reducing BC emissions and achieving emission reduction targets in the YRD. Materials and methods Based on the latest energy statistics and domestically measured emission factors, a BC emission inventory in the YRD from 2000 to 2019 was established. The Monte Carlo method was used to analyze the uncertainty of the BC emission inventory, focusing on the influence of the value difference of emission factor values on the BC emission accounting. The key factors that had a significant effect on the uncertainty of the accounting results were identified and an objectively confidence interval of the BC emission in the YRD was provided. Results The results showed that: (1) the total BC emissions in the YRD increased from 10.72×107 kg to 12.54×107 kg from 2000 to 2019. In 2000, residences were the largest source of BC emissions in the YRD, accounting for 42.2% of the total BC emissions. Emissions from industrial sources became the largest source of BC emissions after 2006 and accounting for 63.2% of total BC emissions in 2019. (2) BC emissions in the YRD showed noticeable spatial differentiation. The total BC emissions and BC emission intensity per capita in Jiangsu Province were ranked first. (3) The 95% confidence interval of total BC emissions in the YRD in 2019 was 7.13×107—14.49×107 kg. The relative uncertainty caused by the emission factor was −33.50%—35.11%, in which industrial sources were the main contributors to the uncertainty of BC emission uncertainty. Discussion (1) Significant changes have occurred in the structure of the BC emissions sources from 2000 to 2019. Owing to the rapid development of urban industries, the contribution of BC emissions from industrial sources has increased. In addition, with the popularization of natural gas energy, the contribution of BC from residential coal combustion in the YRD has significantly reduced. (2) The spatial distribution of BC emissions in the YRD was uneven and closely related to energy consumption, economy, and population density. The cities of Shanghai, Hefei, Fuyang, Xuzhou, and Nanjing had the highest BC emissions, which was related mostly to industrial development and energy consumption. The BC emissions per unit GDP decreased significantly in 2019 in all provinces, indicating that the development of the YRD relied less on energy-intensive industries. (3) The uncertainty of BC emissions was larger than that of other greenhouse gases because the current methods for assessing BC emissions are not as mature or reliable as those for CH4 and CO2. Differences in uncertainty calculations between inventories may also arise from differences in calculation methods and coefficients of variation. Conclusions Based on the emission inventory, the economy in the YRD is improving its dependence on energy-intensive industries; however, focus on controlling industrial and transportation sources is still required to reduce BC emissions. Recommendations and perspectives Future studies are required to analyze the uncertainties caused by emission control technologies. |
Key words: black carbon emission inventory uncertainty the Yangtze River Delta |