Y. Zhao, LP Qiu, RY Xu, FJ Xie, Q. Zhang, YY Yu, C.P. Nielsen, HX Qin, H.K. Wang, XC Wu, WQ Li, and J. Zhang. 2015. “
Advantages of city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China.” Atmospheric Chemistry and Physics, 15, Pp. 12623-12644.
Publisher's VersionAbstractWith 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.
Yanxia Zhang, Haikun Wang, Sai Liang, Ming Xu, Qiang Zhang, Hongyan Zhao, and Jun Bi. 2015. “
A dual strategy for controlling energy consumption and air pollution in China's metropolis of Beijing.” Energy, 81, 1 March, Pp. 294-303.
Publisher's VersionAbstract
It is critical to alleviate problems of energy and air pollutant emissions in a metropolis because these areas serve as economic engines and have large and dense populations. Drivers of fossil fuel use and air pollutants emissions were analyzed in the metropolis of Beijing during 1997-2010. The analyses were conducted from both a bottom-up and a top-down perspective based on the sectoral inventories and structural decomposition analysis (SDA). From a bottom-up perspective, the key energy-intensive industrial sectors directly caused the variations in Beijing's air pollution by means of a series of energy and economic policies. From a top-down perspective, variations in production structures caused increases in most materials during 2000-2010, but there were decreases in PM10 and PM2.5 emissions during 2005-2010. Population growth was found to be the largest driver of energy consumption and air pollutant emissions during 1997-2010. This finding suggests that avoiding rapid population growth in Beijing could simultaneously control energy consumption and air pollutant emissions. Mitigation policies should consider not only the key industrial sectors but also socioeconomic drivers to co-reduce energy consumption and air pollution in China's metropolis.
Yu Deng, Shenghe Liu, Jianming Cai, Xi Lu, and Chris P Nielsen. 2015. “
Spatial pattern and evolution of Chinese provincial population: Methods and empirical study.” Journal of Geographical Sciences, 25, 12, Pp. 1507-1520.
Publisher's VersionAbstract
China has been experiencing an unprecedented urbanization process. In 2011, China’s urban population reached 691 million with an urbanization rate of 51.27%. Urbanization level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the total fertility rate of China’s population is declining due to the combined effect of economic growth, environmental carrying capacity, and modern social consciousness. The Chinese government has loosened its “one-child policy” gradually by allowing childbearing couples to have the second child as long as either of them is from a one-child family. In such rapidly developing country, the natural growth and spatial migration will consistently reshape spatial pattern of population. An accurate prediction of the future spatial pattern of population and its evolution trend are critical to key policy-making processes and spatial planning in China including urbanization, land use development, ecological conservation and environmental protection. In this paper, a top-down method is developed to project the spatial distribution of China’s future population with considerations of both natural population growth at provincial level and the provincial migration from 2010 to 2050. Building on this, the spatial pattern and evolution trend of Chinese provincial population are analyzed. The results suggested that the overall spatial pattern of Chinese population will be unlikely changed in next four decades, with the east area having the highest population density and followed by central area, northeast and west area. Four provinces in the east, Shanghai, Beijing, Tianjin and Jiangsu, will remain the top in terms of population density in China, and Xinjiang, Qinghai and Tibet will continue to have the lowest density of population. We introduced an index system to classify the Chinese provinces into three categories in terms of provincial population densities: Fast Changing Populated Region (FCPR), Low Changing Populated Region (LCPR) and Inactive Populated Region (IPR). In the FCPR, China’s population is projected to continue to concentrate in net immigration leading type (NILT) area where receives nearly 99% of new accumulated floating population. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while the population density in Guangdong will keep increasing until 2035. Net emigration leading type (NELT) area will account for 75% of emigration population, including Henan, Anhui, Chongqing and Hubei. Natural growth will play a dominant role in natural growth leading type area, such as Liaoning and Shandong, because there will be few emigration population. Due to the large amount of moving-out labors and gradually declining fertility rates, population density of the LCPR region exhibits a downward trend, except for Fujian and Hainan. The majority of the western provinces will be likely to remain relatively low population density, with an average value of no more than 100 persons per km2.