13 research outputs found

    Input Digitization of the Manufacturing Industry and Carbon Emission Intensity Based on Testing the World and Developing Countries

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    Facing the increasingly deteriorating climate, carbon emission reduction has become a global consensus. In particular, as an industry with very serious pollution emissions, the manufacturing industry is under enormous pressure to reduce environmental consumption. At the same time, against the background of rapid digitization development, the production and organization of the manufacturing industry have greatly changed, which also provides new research ideas for global carbon emission reduction. Based on the panel data of 40 major economies in the world, this paper calculates the degree of input digitization of the manufacturing industry using the input–output method and constructs a triple fixed effect model to analyze the impact of manufacturing’s input digitization on its carbon emission intensity from the perspective of the world and developing countries. The research finds that, first, on the global level, input digitization significantly reduces the carbon emission intensity of manufacturing, and the effect of carbon reduction increases gradually over time, with a noticeable industry spillover effect. Second, the test results from developing countries show that the relationship between digital input from developed countries and manufacturing’s carbon intensity in developing countries presents an inverted U shape. Third, heterogeneity analysis shows that digital input has the most obvious effect on carbon reduction in the pollution-intensive manufacturing sector. Tracking the sources of digital input, it is found that digital input from high-tech economies has the most obvious effect on carbon reduction. The paper takes the lead in clarifying the impact of digitization on carbon emissions from the manufacturing sector, expands the existing research on the digital economy and the environment, and also makes a theoretical contribution to global carbon emission reduction

    Geometric Shape Induced Small Change of Seebeck Coefficient in Bulky Metallic Wires

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    In this paper, we report the results of slight changes in the thermopower of long W, Mo, Zn, Cu, brass, and Ti wires, that resulted from changes in the wire’s diameter or cross-sectional area. The samples used in the tests had a round shape with a diameter that ranged from tens of micron to 2 mm, which was much larger than the corresponding mean free paths of these materials. Nevertheless, a small change in thermopower, at the order of 1–10 nV/K, was repeatedly observed when the wire diameter was changed, or when the cross-sectional area of the wire was altered by mechanical methods, such as grinding or splitting. The results are consistent with previous observations showing that the thermopower in metallic thin film stripes changes with their width, from 100 μm to as little as 70 nm, implying a universal, geometric-boundary-related size effect of thermopower in metal materials, that occurs at the nanometer scale and continuously decreases all the way to the millimeter scale. This effect could be applied in the manufacturing of high-temperature sensors with simple structures

    Real-Time Two-Dimensional Mapping of Relative Local Surface Temperatures with a Thin-Film Sensor Array

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    Dynamic mapping of an object’s local temperature distribution may offer valuable information for failure analysis, system control and improvement. In this letter we present a computerized measurement system which is equipped with a hybrid, low-noise mechanical-electrical multiplexer for real-time two-dimensional (2D) mapping of surface temperatures. We demonstrate the performance of the system on a device embedded with 32 pieces of built-in Cr-Pt thin-film thermocouples arranged in a 4 × 8 matrix. The system can display a continuous 2D mapping movie of relative temperatures with a time interval around 1 s. This technique may find applications in a variety of practical devices and systems

    Additional file 1: Figure S1. of Performance of Nano-Submicron-Stripe Pd Thin-Film Temperature Sensors

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    The red lines are the isothermal lines for the expected temperature distribution on the substrate surface. The sensors in the testing array are numbered the same series numbers from 1 to 9 as that in the main text (DOC 363 kb)

    Drivers of improved PM2.5 air quality in China from 2013 to 2017

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    From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population-weighted annual mean PM2.5 concentrations decreased from 61.8 (95%CI: 53.3-70.0) to 42.0 mu g/m(3) (95% CI: 35.7-48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9-7.1), 4.4- (95% CI: 3.84.9), 2.8- (95% CI: 2.5-3.0), and 2.2- (95% CI: 2.0-2.5) mu g/m(3) declines in the national PM2.5 concentration in 2017, respectively, and further reduced PM2.5-attributable excess deaths by 0.37 million (95% CI: 0.35-0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China's recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries
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