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[en] The design and metrological characteristics of a photometric gas analyzer for atmospheric sulfur dioxide that is equipped with adsorbing polymer films are considered. It is shown that the device can solve ecological and health safety issues and has small overall dimensions and power consumption.
[en] Highlights: • The Environmental Kuznets Curve (EKC) has been estimated at the national and the provincial level in China. • There exists aggregation bias in estimating the national level EKC for sulfur dioxide emission. • The local government should play more important role in environmental policy-making. - Abstract: Aggregation bias may lead to a wrongly estimated Environmental Kuznets Curve (EKC), and misguide the policy-makers. This paper aims to test the existence of aggregation bias in the Environmental Kuznets Curve with the sulfur dioxide (SO2) emission. The empirical methods robust to cross-sectional dependence and slope heterogeneity reveals that the estimation of SO2 EKC in China suffers from aggregation bias. The results with the disaggregate data cannot support the EKC estimated at the aggregate level. The finding of aggregation bias has several policy implications. First, the government should not be misled by the false relationship between the pollutant emission and the real GDP per capita at the aggregate level. Second, the local governments should play more important roles in making environmental protection policies since the more disaggregate data can mitigate the aggregation bias. To provide enough incentives to the local government, the Chinese national government should align the interests of the local governments with those of the national government. On the other hand, the findings indicate that China can stick to the policy of encouraging foreign direct investment, openness and financial development since they have not influenced the SO2 emission in China.
[en] Sulfur dioxide is a major air pollutant in the environment. Fortunately, the plant purification system can effectively reduce SO2 pollution. However, the effect mechanism of plant purification system for the dynamic evolution of SO2 remains incompletely clear. In this work, inspired by the “Boston ivy,” we successfully designed and constructed a semi-continuous plant system. Subsequently, based on the “vine-like plant” and the “island-like plant,” the semi-continuous plant system and the isolated plant system are selected as the models of plant purification system, respectively. The dynamic evolution of SO2 in the plant systems is investigated using the computational fluid dynamic (CFD) method. It is demonstrated that the dynamic evolution of SO2 is impacted by the plant structure and the flow path ((cg/lg) + (cl/ll)). In the semi-continuous plant system, the strong flow paths with gradually weakened fluctuation are restricted by this special plant structure, the length of flow paths are extended, and more SO2 can be dissolved. In the isolated plant system, the mild flow paths with linear relationship can easily pass through the plants, such that only a little SO2 is dissolved. Overall, the present study opens a new path into the dynamic evolution of SO2 pollution in the plant systems, which helps providing guidance for the designing of plant purification system.
[en] Highlights: • The impact of public opinion on haze pollution in China is investigated. • A dataset consisting of 109 prefecture-level Chinese cities is employed. • Public opinion has a positive effect on the environment only in the short run. • There is a time lag between the surge in public opinion and improved air quality. - Abstract: In recent years, serious smog and haze have shrouded vast areas of northern and eastern China, which has drawn broad attention at home and abroad. Although China is an authoritarian country with strict media control, public opinion may still affect air quality by putting pressure on the local and central governments to enhance environmental protections. In this paper, the impact of public opinion on air quality in China is for the first time quantitatively examined. Specifically, the monthly average levels of the Air Quality Index (AQI) and the concentrations of several main air pollutants, such as PM2.5, PM10 and SO2, are utilized as indicators for air quality. Using a dataset consisting of 109 prefecture-level Chinese cities for the period between November 2013 and October 2016, the estimation results indicate that air pollution significantly affects public opinion on air quality, and the surge in public opinion on air pollution occurs more frequently in the winter. Public opinion seems to have a positive effect on the environment only in the short run: air quality tends to improve two months after the surge in negative public opinion. In general, public opinion about air pollution helps to improve air quality in China.
[en] Focusing on the mechanism of foreign direct investment on environment, we attempt to build a series of hierarchical linear models to explore the impact of foreign direct investment on China’s sulfur dioxide (SO2) emissions by using the panel data of industrial sector in Chinese provinces from 2002 to 2013. The findings show that: Firstly, the industrial SO2 emission shows a slow downward trend. Secondly, 27.96% of the variations of SO2 emission intensity come from the differences between the provinces. Thirdly, foreign direct investment can explain 50.50% of the different changes in provincial SO2 emission intensity due to economic scale effect, structural effect, technological effect, and environmental regulation effect. Among them, the scale effect and technical effect are negatively correlated with SO2 emissions intensity, while structural and environmental regulation effects positively. Moreover, foreign direct investment can significantly inhibit the positive correlation of structural effect and weaken the negative correlation of technology effect on SO2 emission intensity, but do not have a significant impact on SO2 emission intensity by economic scale effect and environmental regulation effect.
[en] Simplified assumptions regarding the relationship between per capita income and emissions are oftentimes utilized to generate future emission scenarios in integrated assessment models (IAMs). One such relationship is an environmental Kuznets curve (EKC), where emissions first increase, then decline with income growth. However, current knowledge about this relationship lacks the specificity needed for each sector and pollutant pairing, which is important for future emission scenarios. To fill this knowledge gap, we analyze the historical relationship between per capita income and emissions of SO2, CO2, and black carbon (BC) utilizing widely-used global, country-level emission inventories for the following four sectors: power, industry, residential, and transportation. Based on a modeling setup using long-term growth rates, emissions of SO2 from the power and industrial sectors, as well as CO2 from the industrial and the residential sectors, largely follow an EKC pattern. Income-emission trajectories for SO2 and CO2 from other sectors, and those for BC from all sectors, do not show an EKC, however. Results across different global inventories were variable, indicating that uncertainties within historical emission trajectories persist. Nonetheless, these results demonstrate that long-term income-emission trajectories of air pollutants are both sector and pollutant specific. Future reference trajectories of SO2 and BC from three IAMs show earlier estimates of turnover incomes and faster rates of emission declines when compared to historical data. Users of future emission scenarios derived using EKC assumptions should consider the underlying uncertainties in such projections in light of this historical analysis. (letter)
[en] Highlights: • A copula-based flexible-stochastic programming (CFSP) method is proposed. • CFSP can handle multiple uncertainties and reflect interaction of random variables. • It is applied to planning RES of the urban agglomeration of Beijing and Tianjin. • Scenarios of various joint- and individual constraint-violation levels are selected. • Results can provide in-depth analysis for identifying desired decision schemes. - Abstract: In this study, a copula-based flexible-stochastic programming (CFSP) method is developed for planning regional energy system (RES). CFSP can deal with multiple uncertainties expressed as interval values, random variables and fuzzy sets as well as their combinations employed to objective function and soft constraints. It can also reflect uncertain interactions among random variables through using copula functions even having different probability distributions and previously unknown correlations. Then, based on the developed CFSP approach, a CFSP-RES model is formulated for planning RES of the urban agglomeration of Beijing and Tianjin (China). Results disclose that uncertainties existed in the system components have significant effects on the outputs of decision variables and system cost, and the variation of system cost is reached 16.3%. Results also reveal that air pollutant emissions can be mitigated if the urban agglomeration can co-implement renewable energy development plans (REDP) over the planning horizon, with the reductive rates of [3.3, 7.6] % of sulfur dioxide (SO2), [2.7, 4.1] % of nitrogen oxides (NOx) and [7.0, 11.5] % of particulate matter (PM10). Compared to joint-probabilistic chance-constrained programming (JCP), the CFSP method is more effective for handling multiple random parameters associated with different probability distributions in which their correlations are unknown. Thus, it is not limited to some unjustified assumptions and can be applied to a wider range of problems than previous studies. The findings are helpful to explore the influence of interaction among random variables on modeling outputs and provide in-depth analysis for identifying desired decision schemes for planning RES.
[en] Highlights: • A compact and efficient gas reactor based on a point discharge microplasma (PD). • Gaseous oxidation reaction from H2S to SO2 with a high efficiency of 95%. • Chromatography-free and rapid speciation analysis for sulfide and sulfite. • Simple operation with PD on/off for sampling into a fluorescence spectrometer. - Abstract: A low temperature plasma integrating the merits of small size, simple operation and rich active particles has good performance in analytical chemistry. In this work, a point discharge microplasma was used as a reactor to facilitate the gaseous conversion reaction from H2S to SO2 with an excellent efficiency as high as 95%. By coupling this reactor with a fluorescence spectrometer, the speciation analysis of sulfide and sulfite was achieved in a simple, chromatographic separation-free, time-saving and practical way. Specifically, with the discharge off, only sulfite was quantified; with discharge on, both sulfide and sulfite were quantified; and with a simple subtraction, the speciation analysis could be easily attained. By the acidification process, a limit of detection of 7.7 µM by the proposed method was obtained for both sulfide and sulfite in aqueous medium, and this method was successfully utilized to analysis of real samples.
[en] Highlights: • A new hybrid dynamic input-output multi-objective optimized model is proposed. • Effects of industrial restructuring on energy saving and pollution reduction are investigated. • China can basically realize its goals of energy and environmental by industrial restructuring. - Abstract: The issue of achieving the twin goals of energy saving and pollution reduction by 2020 is important for transforming China's approach to economic growth. From the perspective of source control, this study investigates the impact of industrial structure adjustment on China's energy saving and pollution reduction goals by developing a new energy-environmental-economy model, integrating a dynamic input-output model and multi-objective model. The three best solutions are screened from the Pareto-optimal front conforming to decision-makers’ preferences. The results show that for China to successively achieve its set goals, it needs to modify and optimize the country's industrial structure. By optimizing its industrial structure, China's energy intensity of the three preferred solutions can be reduced by 17.7%, 17.0%, and 17.5% compared with 2015 levels, which helps to attain the target energy-saving goal. Emissions of COD, SO2, and NOx are significantly reduced; however, the reduction goal of NH3-N is barely realized. In the restructuring process, GDP can be maintained at 6.6–6.8% from 2013 to 2020. These findings could alleviate local governments’ concerns that implementation of stringent energy-saving and pollution-reduction mechanisms would harm their local economies.
[en] Highlights: • Adsorptions of di–, tri– and tetra–atomic gases on Sc–doped ZnO sodalite like cage were explored. • SO2 adsorbed on the Sc–ZnOSL is the most energetically preferred configuration. • Sc–ZnOSL tends to be used as N2O and SO2 gases detector by resistance measurement.