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With the rapid development of the Internet of Things (IoT) in the 5G age, the construction of smart cities around the world consequents on the exploration of carbon reduction path based on IoT technology is an important direction for global low carbon city research. Carbon dioxide emissions in small cities are usually higher than that in large and medium cities. However, due to the huge difference in data environment between small cities and Medium-large sized cities, the weak hardware foundation of the IoT, and the high input cost, the construction of a small city smart carbon monitoring platform has not yet been carried out. This paper proposes a real-time estimate model of carbon emissions at the block and street scale and designs a smart carbon monitoring platform that combines traditional carbon control methods with IoT technology. It can exist long-term data by using real-time data acquired with the sensing device. Therefore, the dynamic monitoring and management of low-carbon development in small cities can be achieved. The contributions are summarized as follows: (1) Intelligent thermoelectric systems, industrial energy monitoring systems, and intelligent transportation systems are three core systems of the monitoring platform. Carbon emission measurement methods based on sample monitoring, long-term data, and real-time data have been established, they can solve the problem of the high cost of IoT equipment in small cities. (2) Combined with long-term data, the real-time correction technology, they can dispose of the matter of differences in carbon emission measurement under diverse scales. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [ABSTRACT FROM AUTHOR]

This paper constructs a model to accurately estimate the urban CO2 emissions in 2000, 2005, and 2013 in China, using the combined data of DMSP/OLS nighttime light data and the provincial energy statistical yearbook data. We calculate and analyze the growth of urban built-up areas and carbon emissions in different time periods both all over the country and the four economic zones in China. It was shown a good fitting relationship between urban growth and carbon emissions, with the R2 at 0.6188 in 2000, 0.7132 in 2005, and 0.7195 in 2013. The growth rate of developed land area was 13.4% from 2000 to 2005 and 15.9% from 2005 to 2013. During the same period, CO2 emissions had been increasing as well, at an average annual growth rate of 12.2% from 2000 to 2005 and 6.5% from 2005 to 2013. From a spatial point of view, carbon emissions are far greater in the eastern region of China than in western China. The carbon emissions are the highest in major metropolitan cities such as Beijing, Shanghai, and Guangzhou. Per capita carbon emissions are also higher in eastern China, which is consistent with the people's higher living standards. In some cities with large energy and heavy industry concentrations, especially in the northeastern and western regions, the growth rate of carbon emissions has risen faster than in other cities. [ABSTRACT FROM AUTHOR]