Are Industrial Structure Adjustment and Technical Progress Conducive to Environmental Improvement?

China actively broadens its channels for environmental protection and limits pollutant emissions through industrial structure adjustment and technical progress. Based on panel data of 30 provinces in China from 2003 to 2017, this study investigated the effects of industrial structure adjustment and technical progress on environmental pollution using spatial Dubin models. The findings show the following. (1) As the economy develops, the situation of environmental pollution in various regions deteriorates; moreover, spatio-temporal dependence is an aspect of environmental pollution. (2) Industrial structure adjustment and technical progress are beneficial to environmental improvement. Furthermore, there are spillover effects in factors such as industrial structure and technical progress to varying degrees. Thus, this study suggests that the path of coupling between industrial structure and technical progress should be explored to establish a pollution filtering mechanism, thereby improving environmental quality.

Comprehensive Analysis of the Pollutant Characteristics of Gasoline Vehicle Emissions under Different Engine, Fuel, and Test Cycles

Vehicle exhaust emissions have seriously affected air quality and human health, and understanding the emission characteristics of vehicle pollutants can promote emission reductions. In this study, a chassis dynamometer was used to study the emission characteristics of the pollutants of two gasoline vehicles (Euro 5 and Euro 6) when using six kinds of fuels. The results show that the two tested vehicles had different engine performance under the same test conditions, which led to a significant difference in their emission characteristics. The fuel consumption and pollutant emission factors of the WLTC cycle were higher than those of the NEDC. The research octane number (RON) and ethanol content of fuels have significant effects on pollutant emissions. For the Euro 5 vehicle, CO and particle number (PN) emissions decreased under the WLTC cycle, and NOx emissions decreased with increasing RONs. For the Euro 6 vehicle, CO and NOx emissions decreased and PN emissions increased with increasing RONs. Compared with traditional gasoline, ethanol gasoline (E10) led to decreases in NOx and PN emissions, and increased CO emissions for the Euro 5 vehicle, while it led to higher PN and NOx emissions and lower CO emissions for the Euro 6 vehicle. In addition, the particulate matter emitted was mainly nucleation-mode particulate matter, accounting for more than 70%. There were two peaks in the particle size distribution, which were about 18 nm and 40 nm, respectively. Finally, compared with ethanol–gasoline, gasoline vehicles with high emission standards (Euro 6) are more suitable for the use of traditional gasoline with a high RON.

Assessment of meteorological settings on air quality modeling system - a proposal for UN-SDG and regulatory studies in non-homogeneous regions in Brazil

Air quality models are essential tools to meet the United Nations Sustainable Development Goals (UN-SDG) because they are effective in guiding public policies for the management of air pollutant emissions and their impacts on the environment and human health. Despite its importance, Brazil still lacks a guide for choosing and setting air quality models for regulatory purposes. Based on this, the current research aims to assess the combined WRF/CALMET/CALPUFF models for representing SO2 dispersion over non-homogeneous regions as a regulatory model for policies in Brazilian Metropolitan Regions to satisfy the UN-SDG. The combined system was applied to the Rio de Janeiro Metropolitan Region (RJMR), which is known for its physiographic complexity. In the first step, the WRF model was evaluated against surface-observed data. The local circulation was underestimated, while the prevailing observational winds were well-represented. In the second step, it was verified that all CALMET three meteorological configurations performed better for the most frequent wind speed classes, so that the largest SO2 concentrations errors occurred during light winds. Among the meteorological settings in WRF/CALMET/CALPUFF, the joined use of observed and modeled meteorological data yielded the best results for the dispersion of pollutants. This result emphasizes the relevance of meteorological data composition in complex regions with unsatisfactory monitoring given the inherent limitations of prognostic models and the excessive extrapolation of observed data that can generate distortions of reality. This research concludes with the proposal of the WRF/CALMET/CALPUFF air quality regulatory system as a supporting tool for policies in the Brazilian Metropolitan Regions in the framework of the UN-SDG, particularly in non-homogeneous regions where steady-state Gaussian models are not applicable.

Project and Development of a Reinforcement Learning Based Control Algorithm for Hybrid Electric Vehicles

Hybrid electric vehicles are, nowadays, considered as one of the most promising technologies for reducing on-road greenhouse gases and pollutant emissions. Such a goal can be accomplished by developing an intelligent energy management system which could lead the powertrain to exploit its maximum energetic performances under real-world driving conditions. According to the latest research in the field of control algorithms for hybrid electric vehicles, Reinforcement Learning has emerged between several Artificial Intelligence approaches as it has proved to retain the capability of producing near-optimal solutions to the control problem even in real-time conditions. Nevertheless, an accurate design of both agent and environment is needed for this class of algorithms. Within this paper, a detailed plan for the complete project and development of an energy management system based on Q-learning for hybrid powertrains is discussed. An integrated modular software framework for co-simulation has been developed and it is thoroughly described. Finally, results have been presented about a massive testing of the agent aimed at assessing for the change in its performance when different training parameters are considered.

Does Green Credit Policy Move the Industrial Firms Toward a Greener Future? Evidence From a Quasi-Natural Experiment in China

How to utilize financial instrument to deal with environmental issues has been a focal topic. Taking the introduction of green credit program as a “quasi-natural experiment,” the propensity score matching and difference-in-difference approach (PSM-DID) are used to investigate the impact of the green credit policy implemented by Chinese government on firm-level industrial pollutant emissions. The estimation results indicate that the green credit policy significantly reduces corporate sulfur dioxide emissions. Heterogeneity analysis shows this impact is more pronounced for large-scale enterprises and enterprises located in the eastern region. The estimated mediation models reveal that after the implementation of the green credit policy, reduction in sulfur dioxide emissions can be attribute to the increased environmental investment and improved energy consumption intensity. Moreover, the green credit policy is also significantly effective in mitigating the discharge of other common industrial pollutants. Our findings highlight the importance of green credit policies in achieving greener industrial production and more sustainable economic development.

Formation of Organic Sulfur Compounds through SO₂ Initiated Photochemistry of PAHs and DMSO at the Air-Water Interface

The presence of organic sulfur compounds (OSs) at the water surface, acting as organic surfactants, may influence the air-water interaction and contribute to new particle formation in the atmosphere. However, the impact of ubiquitous anthropogenic pollutant emissions, such as SO2 and polycyclic aromatic hydrocarbons (PAHs) on the formation of OSs at the air-water interface still remains unknown. Here, we observe large amounts of OSs formation in presence of SO2, upon irradiation of aqueous solutions containing typical PAHs such as pyrene (PYR), fluoranthene (FLA), and phenanthrene (PHE), as well as dimethylsulfoxide (DMSO). We observe rapid formation of several gaseous OSs from light-induced heterogeneous reactions of SO2 with either DMSO or a mixture of PAHs/DMSO, and some of these OSs (e.g. methanesulfonic acid) are well established secondary organic aerosol (SOA) precursors. A myriad of OSs and unsaturated compounds are produced and detected in the aqueous phase. The tentative reaction pathways are supported by theoretical calculations of the reaction Gibbs energies. Our findings provide new insights into potential sources and formation pathways of OSs occurring at the water (sea, lake, river) surface, that should be considered in future model studies to better represent the air-water interaction and SOA formation processes.

The stabilized methane–air counterflow flame into a plus-shaped chamber with platinum catalyst–coated walls: An emission estimation

Analysis of unsteady CH4/Air counterflow premixed flame into a newly designed plus-shaped channel is investigated in this study. The main objective is to explore the impact of platinum catalytic–coated walls of the combustion chamber on the flame characteristics and pollutant emissions. The OpenFOAM platform is used as a numerical simulation tool to investigate the effects of various equivalence ratios, from the range of lean to rich flames, and passing the reaction time on the counterflow flame characteristics and pollutant emissions of a plus-shaped chamber with the platinum catalyst–coated wall. Results show that the integrated temperature over the proposed geometry with platinum surfaces increases by 18% compared to the non-catalytic case. The numerical simulation revealed that presence of the platinum catalyst on the wall of the chamber has significant impact on reducing the pollutant emissions. This is evident as a 99.5% decrease on NO2 emission and a 58% reduction on CO2 formation are found.

CFD Analysis of a Large Marine Engine Scavenging Process

The scavenging process is an important part of the two-stroke engine operation. Its efficiency affects the global engine performance such as power, fuel consumption, and pollutant emissions. Slow speed marine diesel engines are uniflow scavenged, which implies inlet scavenging ports on the bottom of the liner and an exhaust valve on the top of the cylinder. A CFD model of such an engine process was developed with the OpenFOAM software tools. A 12-degree sector of the mesh was used corresponding to one of the 30 scavenging ports. A mesh sensitivity test was performed, and the cylinder pressure was compared to experimental data for the analyzed part of the process. The scavenging performances were analyzed for real operation parameters. The influence of the scavenge air pressure and inlet ports geometric orientation was analyzed. The scavenging process is analyzed by means of a passive scalar representing fresh air in the cylinder. Isosurfaces that show the concentration of fresh air were presented. The variation of oxygen and carbon dioxide with time and the axial and angular momentum in the cylinder were calculated. Finally, the scavenging performance for the various operation parameters was evaluated by means of scavenging efficiency, charging efficiency, trapping efficiency, and delivery ratio. It was found that the scavenging efficiency decreases with the engine load due to the shorter time for the process. The scavenging efficiency increases with the pressure difference between the exhaust and scavenging port, and the scavenging efficiency decreases with the increase in the angle of the scavenging ports. It was concluded that smaller angles than the industry standard of 20° could be beneficial to the scavenging efficiency. In the investigation, the charging efficiency ranged from 0.91 to over 0.99, the trapping efficiency ranged from 0.54 to 0.83, the charging efficiency ranged from 0.78 to 0.92, and the delivery ratio ranged from 1.21 to 2.03.