[en] In 2018, the Beijing–Tianjin–Hebei (BTH) area launched the Blue Sky Protection Campaign (BSPC) to control atmospheric pollution. CO₂ emissions could be significantly reduced due to the co-effects of implementing the BSPC. This paper employs the Greenhouse Gas and Air Pollution Interactions and Synergies Asia model to quantitatively evaluate the CO₂ reductions when implementing the BSPC in the BTH region. The results indicate that CO₂ emissions can be reduced by 20.7 Mt (equivalently, a 19.7% reduction in the corresponding baseline scenario), 6.8 Mt (3.8%), and 80.2 Mt (9.2%) by 2020 for Beijing, Tianjin, and Hebei, respectively, as a co-benefit of the BSPC. By 2030, it is estimated that the CO₂ emission reductions will be 37.8 Mt (26.6%), 4.85 Mt (2.5%), and 69.9 Mt (8.6%) for Beijing, Tianjin, and Hebei, respectively. NO_x presents the highest co-effects with CO₂ in each region. From the key sector perspective, sectors of power and heating in Beijing, residential combustion in Tianjin, and industrial combustion in Hebei are the most important sector that presents the highest co-effects on CO₂ emission reductions due to the application of BSPC. We suggest that the implementation of BSPC, specifically the energy control measures in the power and heating, residential combustion, and industrial combustion sectors for Beijing, Tianjin, and Hebei, respectively, have high synergies and can simultaneously reduce CO₂ and other atmospheric emissions. The results contribute to city-level policymaking on facilitating air pollution control and climate change mitigation among different governmental departments. (paper)

[en] Highlights: • Implementation rates of 37 EEMs are quantified for China’s cement industry. • Energy Supply Cost Curves were implemented in the GAINS model. • The economic energy saving potential is 3.0 EJ and costs is $4.1 billion in 2030. • Energy efficiency would lead to large reductions in air pollution. • The co-benefits decrease average marginal costs of EEMs by 20%. - Abstract: China’s cement industry is the world’s largest and is one of the largest energy consuming, and GHG and air pollutant emitting industries. Actions to improve energy efficiency by best available technology can often bring co-benefits for climate change and air quality through reducing emissions of GHGs and air pollutants emission. In this study, the energy conservation supply curves (ECSC) combined with the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) was used to estimate the co-benefits of energy savings on CO_2 and air pollutants emission for implementing co-control options of energy efficiency measures and end-of-pipe options in the China’s cement industry for the period 2011–2030. Results show that there are large co-benefits of improving energy efficiency and reducing emissions of CO_2 and air pollutants for the China’s cement industry during the study period. The cost-effective energy saving potential (EEP1 scenario) and its costs is estimated to be 3.0 EJ and 4.1 billion $ in 2030. The technical energy savings potential (EEP2 scenario) and its costs amount to 4.2 EJ and 8.4 billion $ at the same time. Compared to the baseline scenario, energy efficiency measures can help decrease 5% of CO_2, 3% of PM, 15% of SO_2, and 12% of NOx emissions by 2030 in EEP1 scenario. If we do not consider costs (EEP2 scenario), energy efficiency measures can further reduce 3% of CO_2, 2% of PM, 10% of SO_2, and 8% of NOx by 2030. Overall, the average marginal costs of energy efficiency measures will decrease by 20%, from 1.48 $/GJ to 1.19 $/GJ, when taking into account avoided investments in air pollution control measures. Therefore, implementation of energy efficiency measures is more cost-effective than a solely end-of-pipe based policy. The plant managers and end users can consider using energy efficiency measures to reach new air pollutants emission standards in China’s cement industry

[en] Highlights: • Provincial disparities in energy use and emissions are quantified for China’s cement industry. • We describe emission mitigation impacts on EEMs with integrated assessment model. • We quantify the multiple benefits potential in China’s cement industry on provincial level. • Energy efficiency would lead to huge reductions in air pollution in all provinces. • We discuss uncertainty in relation to distribution of energy saving and emission reduction. - Abstract: China’s cement industry is the second largest energy consumer and key emitter of CO_2 and air pollutants. It accounts for 7% of total energy consumption in China and 15% of CO_2, 21% of PM, 4% SO_2 and 10% of NOx of total emissions, respectively. Provincial disparities in energy consumption and emissions of CO_2 and air pollutants in China’s cement industry are rarely quantified. In this study, an integrated assessment model including provincial energy conservation supply curves (ECSC) (which can shows the cost-effective and technical energy saving potential per province), the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model (which can be used to calculate air pollutant emissions), and ArcGIS (a geographical information system (GIS) with elaborated spatial functions) is developed and used to assess the potential of energy savings in terms of emission mitigation of CO_2 and air pollutants and multiple benefits of energy efficiency measures at the provincial level during the period 2011–2030. The results show significant heterogeneity across provinces in terms of potential of energy saving as well as emission mitigation of CO_2 and air pollutants (i.e. PM, SO_2, and NOx) in the next two decades. Seven provinces (i.e. Shandong, Sichuan, Jiangsu, Guangdong, Zhejiang, Henan, Hebei), six of which are located in the central- and east-China, account for 47% of the total energy saving potential, equivalent to 26% of baseline energy use in 2030. The energy efficiency measures can help decrease 38% of CO_2, 23% of SO_2, 33% of NOx, and 26% of PM emissions in these seven provinces by 2030. This indicates that the multiple benefits should be considered when local policy makers or end users make decisions whether to use energy efficiency measures to solve environmental issues

[en] In China, industrial energy use accounts for two thirds of total energy consumption, and this is expected to remain the same in the medium and long-term. China has embarked on a path towards more sustainable energy use to meet domestic (e.g. air quality) and global needs (e.g. climate change), and to sustain its economic welfare. However, most energy-economy models for China have shown limitations to evaluate policy instruments and technology diffusion in industries, in relation to the multiple policy goals. In this paper, the advantages and weaknesses of 19 current energy models for China are evaluated, including important co-benefits as reduced air pollutant emissions. Results show that the co-benefits of energy use and emission policies are rarely modeled on industrial level. Based on the critical assessment of the state-of-the-art energy models, we develop recommendations for modeling industrial energy use, with an emphasis on improved incorporation of (economic, environmental and energy) policy effects, technology representation, co-benefit modeling, and uncertainty analysis. - Highlights: • This study evaluates 19 the state-of-the-art energy models on different level. • The co-benefits of different policies are rarely reported in energy models. • Technology plays a key role in models when assessing the co-benefits. • The integrated models provide a better understanding to evaluate the co-benefits. • The directions to improve the accuracy of the current energy models are presented.

[en] Denitrifying bioelectrochemical system provided an alternative technology for nitrogen removal, even power recovery from wastewater, and its nitrogen removal performance and intermediate accumulation were affected by the extracellular electron transfer modes and rate-limiting steps in denitrifying biocathodes. In the current study, the extracellular electron transfer modes and rate-limiting steps for nitrate reduction and nitrite reduction of denitrifying biocathode were investigated through cyclic voltammetry. When the cathode potential swept from 0.003 to − 0.897 V (vs. Ag/AgCl), denitrifiers were indispensable for electrochemical denitrification. Three peak potentials were found in the cyclic voltammogram of denitrifying biocathode, where E₁ (− 0.471 to − 0.465 V) and E₂ (− 0.412 to − 0.428 V) represented respectively nitrate reduction and nitrite oxidation while E₃ (− 0.822 to − 0.826 V) represented nitrite reduction. Nitrate reduction involved the direct electron transfer mode while nitrite reduction involved the mediated electron transfer mode. Intracellular catalytic reaction was the rate-limiting step for nitrate reduction, independent on the electrochemical activity of denitrifying biocathode and the nitrate supply. The nitrate supply posed an effect on the rate-limiting step for nitrite reduction. The mediator transfer was the rate-limiting step for nitrite reduction in the absence of nitrate. But both mediator transfer and intracellular catalytic reaction became the rate-limiting steps for nitrite reduction in the presence of sufficient nitrate.

[en] Relaxation oscillation spectrums of orthogonally polarized modes versus the direction of pump polarization is observed. Unlike previous reports that the anti-phase relaxation peaks are compensated totally, in most cases, they can still be observed in total intensity fluctuation spectrum. An anisotropic rate equation model for orthogonally polarized states Nd:YAG microchip laser is developed to account for the experimental observations. Anisotropic gain and loss are included to explain the polarization dynamics. (paper)

[en] Laser feedback interference is widely used for displacement measurement of non-cooperative targets due to its ultra-high sensitivity. However, by the same token, laser feedback interferometry (LFI) suffers from multi-channel optical feedback, which compromises measurement stability and accuracy. We perform both simulations and experiments to study the effect of dual-channel optical feedback on LFI systems based displacement measurement. Dual-channel optical feedback interference is the simplest and most representative form of multi-channel feedback interference. We evaluate system performance by varying $\mathrm{\alpha <!--\; ??\; -->},$ which is the ratio of feedback level in the primary channel to the one in the secondary channel. The results indicate that the measured displacement curve is a linear line superimposed with nonlinear periodic errors when the target in the primary channel moves linearly and the target in the secondary channel stays stationary. Whereas, the curve is a periodic curve instead of a linear one, for the case when the target in the secondary channel moves linearly while the one in the primary channel stays stationary. Furthermore, the amplitude and shape of the periodic curves also depend on the parameter $\mathrm{\alpha <!--\; ??\; -->}.$ When $\mathrm{\alpha <!--\; ??\; -->}$ is much less than 1, the displacement curve is sinusoidal, whereas the curve has a saw-tooth shape with larger amplitude for $\mathrm{\alpha <!--\; ??\; -->}$ close to 1. In view of this situation, a new displacement measurement method, counting the cycles of the periodic displacement curves, is proposed. The current work can provide theoretical and experimental suggestions for improving the performance of existing self-mixing interferometry systems, and implementing ones with multi-channel optical feedback channels. (paper)

[en] Support vector machine(SVM) got a good classification ability, but the recognition accuracy was easily affected by the value of the kernel parameters. Aiming at this problem, sparse autoencoder(SAE) has its unique advantages in dealing with complex structured data, so the combination of sparse autoencoder and support vector machine(SAE+SVM) was proposed on the fault identification of vehical automatic transmission. Firstly, eight indicators such as engine speed, throttle opening, water temperature and so on are collected from acquisition automobile automatic transmission under 3 running conditions. The data was used as input dataset of the sparse autoencoding model to extract the features. Then the features was used for the fault classification and identification based on support vector machine. Compared with using support vector machine only, the experiment results showed that the recognition accuracy based on the combination of sparse autoencoder and support vector machine(SAE+SVM) was less affected by the value of the kernel parameters and got better recognition accuracy. So the combination of sparse autoencoder and support vector machine can be better used in the real-time fault identification and diagnosis of automatic transmission. (paper)

[en] Highlights: • MFC can convert methane to electricity but face difficulties in startup. • Methane-fueled MFC was successfully started up in a short time of 53 d. • Mo/W facilitated both methane consumption and electricity generation. • 30 °C and pH 7 buffered by PBS were deemed as suitable operation parameters. • Formate-fed electroactive culture is a suitable inoculum of methane-fueled MFC. Methane gas is widespread in natural environments and anaerobic wastewater treatment sites, bringing the risk of the greenhouse effect and energy loss if left unmanaged. A methane-fueled microbial fuel cell (MFC) can convert methane to electricity under mild condition, but faced difficulties in startup. In this study, the new startup strategy and operation performance for methane-fueled MFCs were investigated. After the pre-cultivation of formate-acclimating electroactive culture, the methane-fueled MFC was successfully started up in a short time of 53 d. Increasing concentrations of molybdenum and tungsten in medium facilitated both methane consumption and electricity generation. Under the optimal condition (batch duration of 11 h, 30 °C, pH 7 buffered by phosphate buffer solution), the methane-fueled MFC achieved the maximum power density of 166 mW/m³, a coulomb production of 6.58 ± 0.07C/batch, a CE of 27.4 ± 0.4% and a methane consumption of 31.2 ± 0.3 μmol/batch. This work explored a suitable inoculum (formate-acclimating electroactive culture) for methane-fueled MFCs.

[en] Highlights: • An MFC was successfully started up using nitrite as cathodic electron acceptor. • The optimal HRT was deemed to be 8 h in this study. • The suitable temperature for power generation was found to be 20 °C. • The suitable temperature for pollutant removal was found to be 25 °C. • Free buffer led to 50% decrease of TN removal rate and power generation. - Abstract: The influences of hydraulic retention time, temperature and free buffer on the performance of short-cut denitrifying microbial fuel cell were investigated after it was successfully started up using nitrite as the cathodic electron acceptor. The results revealed that a power density of 8.3 ± 0.5 W m⁻³ NC was obtained after 15 days operation. The desirable hydraulic retention time was found in this study to be 8 h, with a COD removal rate of 2.117 ± 0.006 kg m⁻³ NC d⁻¹ and a total nitrogen removal rate of 0.041 ± 0.002 kg m⁻³ NC d⁻¹, respectively. It demonstrated that temperature had different effects on the electricity generation and pollutant removal performance of microbial fuel cell. The suitable temperature for power generation and pollutant removal was found to be 20 °C and 25 °C, respectively. Free buffer led to 50% decrease of both total nitrogen removal rate and power density of microbial fuel cell compared to that with phosphate buffer solution addition. The optimal total nitrogen removal rate obtained in the case with sodium azide addition (0.075 ± 0.008 kg m⁻³ NC d⁻¹) increased by 50% as compared to that without sodium azide addition. It suggested that abolishing oxygen or inhibiting nitrite oxidizing bacteria would favor nitrogen removal