About Beijing
Beijing is one of the four ancient cities of China. The discovery of “Peking Man” in the area suggests inhabitation as early as 770,000 years ago. Historians date the city’s establishment to over 3,000 year ago. Since 221 BC, the city has played an important role provincially, and later nationally, and subsequently has been home to 34 Chinese emperors. Currently, Beijing is the capital of the People’s Republic of China (1949 – present). Since the 1980s the city has undergone rapid expansion. Growth was driven by the opening up of the Chinese economy and accompanied increases in per capita income and land area. For example, the built up area of the city increased from 184 km2 in 1973 to 1,210 km2 in 2005 and 16,410 km2 in 2020. The resident population grew from approximately 9 million in 1970 to 21.4 million today. Beijing, is currently at the forefront of the country’s economic development and a national service sector leader. It’s tertiary industry accounts for more than 80% of the total city GDP, which exceeds 523 billion USD and the GDP per capita exceeds US$19,000, which was well above the domestic average. Population and economic growth helped to induce large increases in energy use and GHG emissions. Annual emissions increased dramatically from the 1990s to reach 94 Mt in 2011, but have subsequently declined. By 2020 total annual GHG emissions were approximately 88 Mt. The national government has pledged to ensure that national CO2 emissions peak around 2030. They have also now included reaching carbon neutrality by 2060 (the “Dual Carbon” targets). One important method in achieving these goals is through meeting a series of carbon intensity (CI) targets. As the capital of the country, Beijing has the responsibility to take the lead in achieving “Dual Carbon” targets, so as to provide incentives and an example for the low-carbon transition in other cities.
Beijing Research Paper
Industrial transformation and residential sustainable
consumption for the promotion of low-carbon urbanization in
Beijing-Tianjin-Hebei region of China
Zhihui Li, Xiangzheng Deng, Chao Wang, Lu Peng
Introduction
This paper tackles three issues faced in greenhouse gas emissions research. 1) Environmental performance metrics such as CO2 emissions are usually calculated at the country or regional scale. Many indices neglect the inputs in the system and rather the emission outputs. 2) A common method called the data envelopment analysis (DEA) for measuring productivity efficiency has some shortcomings that could be improved upon. 3) The focus on CO2 emissions research has primarily fallen on industrial sectors, leaving gaps in residential consumption knowledge.
City Analysis
This paper was able to work with city level data from the Beijing-Tianjin-Hebei(BTH) region in China. The BTH region holds three provincial-level administrative areas: Beijing city, Tianjin city, and Hebei province. This region contains more than 110 million residents and a large GDP of greater than 8 trillion CNY. The data being used were derived from the Beijing Statistical Yearbook, Tianjin Statistical Yearbook, Hebei Economic Yearbook, and the China Statistical Yearbook.
Measuring TFCP and CMP
In this study the Debreu-Farrel efficiency was used as the framework of production efficiency for estimating carbon emission performance. This method tries to minimize undesirable outputs such as carbon emissions while maximized industrial outputs. These two outcomes are produced by the capital stock, labor force, and energy used also known as the production technology set. This helps derive the TFCP or production efficiency, which can be combined with CO2 emissions to calculate the CMP (carbon emission mitigation potential).
Residential Consumption
There are two ways carbon emissions can be calculated, the direct and indirect residential emissions. Direct emissions can be the result of cooking, heating, etc, while indirect emissions are comprised of the carbon emitted during the creation of products and services being consumed. This is calculated using the carbon emission per unit metric of gross product for each sector with the intermediate demand captured in the Leontief inverse matrix. Next the value is multiplied by the residential consumption per sector with another term that differentiates rural and urban residents.
Structural decomposition analysis can help explore the main factors in the change in emissions over time. It’s a popular method for economists to decompose or uncover main constituents that make up changes over time to an output value. Often times they can broken into scale effects, composition effects, and technical effects. In this example the researchers broke down household consumption into population size, consumption structure, and consumption level.
Findings
The total carbon emissions in the industrial sector in the BTH region increased from 542 million tons of CO2(MtC) in 2010 to 649 Mtc in 2016, this increase is about a 20% difference in 6 years. The Hebei region contributed the largest portion of this change compared to Tianjin which had minor increases and Beijing which decreased its emissions. In Beijing, the TFCP increased during this period, while Tianjin decreased slightly, but there were no clear findings about TFCP from Hebei.
For the residential sector, carbon emissions jumped from 257 MtC in 2002 to 673 MtC in 2012, which is a 150% increase. Hebei had the largest carbon emissions and urban areas accounted for more emissions compared to rural areas. The decomposition analysis showed that consumption level had the biggest effect on carbon emissions.
Conclusion
This study contributed to the growing literature of carbon emissions in an urban asian context, specifically by breaking down TFCP and CMP for 39 industrial sectors, but also in calculating direct and indirect emissions from residential consumption in the BTH region. While CO2 emission rose in both industrial and residential sectors, there are some positive findings from the study. For example, TFCP did rise for some areas, and this study also highlights sectors that could be taken into more careful consideration such as the manufacturing of non metallic mineral products, gast and water production, and mining and processing of ferrous metal ores. From a residential perspective, indirect emissions grew the most in the study period. The growth in residential consumption levels is worrying for the future of emission reduction, but the use of consumption structure could be a lever towards taming future emission output.