The Paris Agreement requires a drastic reduction of global carbon emissions towards the net zero transition by mid-century, based on the large-scale transformation of the global energy system and ...major emitting sectors. Aviation and shipping emissions are not on a trajectory consistent with Paris goals, driven by rapid activity growth and the lack of commercial mitigation options, given the challenges for electrification of these sectors. Large-scale models used for mitigation analysis commonly do not capture the specificities and emission reduction options of international shipping and aviation, while bottom-up sectoral models do not represent their interlinkages with the entire system. Here, I use the global energy system model PROMETHEUS, enhanced with a detailed representation of the shipping and aviation sector, to explore transformation pathways for these sectors and their emission, activity, and energy mix impacts. The most promising alternative towards decarbonizing these sectors is the large-scale deployment of low-carbon fuels, including biofuels and synthetic clean fuels, accompanied by energy efficiency improvements. The analysis shows that ambitious climate policy would reduce the trade of fossil fuels and lower the activity and the mitigation effort of international shipping, indicating synergies between national climate action and international transport.
Currently, Tangshan confronts the dual challenge of elevated carbon emissions and substantial pollution discharge from the iron and steel industries (ISIs). While significant efforts have been made ...to mitigate air pollutants and carbon emissions within the ISIs, there remains a gap in comprehending the control of carbon emissions, air pollutant emissions, and their contributions to air pollutant concentrations at the enterprise level. In this study, we devised the Air Pollutant and Carbon Emission and Air Quality (ACEA) model to identify enterprises with noteworthy air pollution and carbon emissions, as well as substantial contributions to air pollutant concentrations. We constructed a detailed inventory of air pollutants and CO2 emissions from the iron and steel industry in Tangshan for the year 2019. The findings reveal that in 2019, Tangshan emitted 5.75 × 104 t of SO2, 13.47 × 104 t of NOx, 3.55 × 104 t of PM10, 1.80 × 104 t of PM2.5, 5.79 × 106 t of CO and 219.62 Mt of CO2. The ACEA model effectively pinpointed key links between ISI enterprises emitting air pollutants and carbon dioxide, notably in pre-iron-making processes (coking, sintering, pelletizing) and the Blast furnace. By utilizing the developed air pollutant emission inventory, the CALPUFF model assessed the impact of ISI enterprises on air quality in the Tangshan region. Subsequently, we graded the performance of air pollutant and CO2 emissions following established criteria. The ACEA model successfully identified eight enterprises with significant air pollution and carbon emissions, exerting notable influence on air pollutant concentrations. Furthermore, the ACEA outcomes offer the potential for enhancing regional air quality in Tangshan and provide a scientific instrument for mitigating air pollutants and carbon emissions. The effective application of the ACEA model in Tangshan’s steel industry holds promise for supporting carbon reduction initiatives and elevating environmental standards in other industrial cities across China.
The aim of this study was to compare and evaluate the production of exhaust emissions from a vehicle with a petrol engine with the Euro 4 emission standard and powered by petrol and LPG (liquefied ...petroleum gas). The paper presents new possibilities for monitoring exhaust emissions using an exhaust gas analyzer. At the same time, it points out the topicality and significance of the issue in the monitored area. It examines the impact of a change in fuel on emissions. This change is monitored in various areas of vehicle operation. Measurements were performed during real operation, which means that the results are fully usable and applicable in practice. The driving simulation as well as the test conditions correspond to the RDE (Real Driving Emissions) test standard. A commercially available car was first selected to perform the tests, which was first measured in the original configuration (petrol drive). Based on real-time RDE driving tests, it is possible to determine the number of exhaust emissions. Subsequently, the same measurements were performed with the same vehicle, but the vehicle’s propulsion was changed to LPG. The vehicle was equipped with an additional system that allowed the vehicle to be powered by LPG. The results from the individual driving tests allowed the determination of the exhaust emissions. Emissions of CO (carbon monoxide), CO2 (carbon dioxide), HC (hydrocarbons), and NOx (nitrogen oxides) were monitored as a matter of priority. Through the driving tests, it was found that the gasoline combustion produced higher CO (1.926 g/km) and CO2 (217.693 g/km) emissions compared to the combustion of liquefied gas, where the concentration of the CO emissions was 1.892 g/km and that of the CO2 emissions was 213.966 g/km. In contrast, the HC (0.00397 g/km) and NOx (0.03107 g/km) emissions were lower when petrol was burned. During LPG combustion, the HC emissions reached 0.00430 g/km, and the NOx emissions reached 0.05134 g/km. At the end of the research, the authors compared the emissions determined by real driving (in g/km) with the emission values produced by the emission standard EURO 4 and the certificate of conformity (COC). Practical measurements showed that the vehicle produced excessive amounts of CO when burning gasoline. This production is 0.926 g/km higher and 0.892 g/km higher when burning LPG compared to the limit set by the Euro 4 Emission Standard. The difference is even greater than the limit value stated in the COC document. For other substances, the monitored values are in the norm and are even far below the permitted value
This study examines the association between tourism development, technology innovation, and carbon emissions by simultaneously testing Environment Kuznets Curve (EKC) hypothesis in China. The study ...develops and uses a novel composite index of tourism development and technology innovation. Utilizing quarterly data from 1995Q1 to 2017Q4, the study employs QARDL (Quantile Autoregressive Distributive Lag) approach and Granger causality‐in‐quantiles. The outcome of the study reveals that the observed relationship is quantile‐dependent, which may disclose misleading results in previous studies using traditional linear methodologies (such as OLS/ARDL) that address the averages. Primarily, the findings indicate that tourism development (TOR) and technology innovation (TII) significantly mitigate the level of carbon dioxide emissions (CO2) in the long run at lower‐higher (0.05–0.95) emissions quantiles and higher‐highest (0.7–0.95) emissions quantiles, respectively. Economic growth (GDP) and globalization (GLO) exert a positive asymmetric influence on CO2 only at lower‐medium (0.05–0.40) emissions quantiles and medium‐higher emissions quantiles (0.50–0.95), respectively. In the short run, TII, and GDP2 possess an insignificant impact across all emissions levels, while TOR shows a positive influence on CO2 only at lowest‐lower (0.05–0.20) emissions quantiles. The study confirms the presence of the EKC hypothesis at lower‐higher (0.05–0.70) emissions quantiles in the long run. Moreover, the outcomes of Granger causality in quantiles confirm asymmetric bidirectional quantile causality between TOR, TII, GLO, and CO2, while a unidirectional causality running from GDP to CO2. The results recommend that the Chinese government should implement integrated “tourism‐technology” policies based on the asymmetric emissions‐reduction effects of tourism and technology innovation in the long run.
Methane (CHsub.4) is an important greenhouse as well as a chemically active gas. Accurate monitoring and understanding of its spatiotemporal distribution are crucial for effective mitigation ...strategies. Nowadays, satellite measurements are widely used for CHsub.4 studies. Here, we use the CHsub.4 products from four commonly used satellites (GOSAT, TROPOMI, ARIS, and IASI) during the period from 2018 to 2020 to investigate the spatiotemporal variations of CHsub.4 in China. In spite of the same target (CHsub.4) for the four satellites, differences among them exist in terms of the instrument, spectrum, and retrieval algorithm. The GOSAT and TROPOMI CHsub.4 retrievals use shortwave infrared spectra, with a better sensitivity near the surface, while the IASI and AIRS CHsub.4 retrievals use thermal infrared spectra, showing a good sensitivity in the mid–upper troposphere but a weak sensitivity in the lower troposphere. The GOSAT and TROPOMI observe high CHsub.4 concentrations in the east and south and low concentrations in the west and north, which is highly related to the CHsub.4 emissions. The IASI and AIRS show a more uniform CHsub.4 distribution over China, which reflects the variation of CHsub.4 at a high altitude. However, a large discrepancy is observed between the IASI and AIRS despite using a similar retrieval band, e.g., significant differences in the seasonal variations of CHsub.4 are observed between the IASI and AIRS across several regions in China. This study highlights the CHsub.4 differences observed by the four satellites in China, and caution must be taken when using these satellite products.
In this work, the traffic characteristics and emissions of air pollutants were predicted for two vehicle classifications (passenger cars and trucks) at the national highway in Kyoto City, Japan. ...Traffic characteristic information (traffic volume, travel speed, and degree of congestion) was estimated based on the digitised data collected by the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) of Japan. A vehicle emission model, known as the computer program to calculate emissions from road transport (COPERT), was utilised to compute the emission factors (EFs) and total emissions of air pollutants in terms of exhaust particulate matter (PM
Exh
), benzene (C
6
H
6
), carbon monoxide (CO), and nitrogen oxide (NO
x
). Input variables, such as fuel data, activity data, driving conditions, and meteorological conditions, are needed. The findings revealed that the pollutant emissions reached the higher values over the slower travel speed phase. Road no. 1 with the most congested road segment has intensified vehicle numbers, and the slowest traffic flow movement exposed a greater magnitude of pollutant emissions. C
6
H
6
and CO emissions are obviously more emitted from the passenger cars whereas the trucks are responsible for the greater emission of NO
x
and PM
Exh
. The EFs of pollutants were compared with the Japanese Emission Standards through JE05 and JC08 chassis dynamometer test cycles. The estimated EFs showed inconsistency with the EFs derived from the test cycles. These results may be deployed as the input in air quality dispersion modelling in urban areas for designing the air pollution abatement strategy.
In the context of phase 5 of the Coupled Model Intercomparison Project, most climate simulations use prescribed atmospheric CO₂ concentration and therefore do not interactively include the effect of ...carbon cycle feedbacks. However, the representative concentration pathway 8.5 (RCP8.5) scenario has additionally been run by earth system models with prescribed CO₂ emissions. This paper analyzes the climate projections of 11 earth system models (ESMs) that performed both emission-driven and concentration-driven RCP8.5 simulations. When forced by RCP8.5 CO₂ emissions, models simulate a large spread in atmospheric CO₂; the simulated 2100 concentrations range between 795 and 1145 ppm. Seven out of the 11 ESMs simulate a larger CO₂ (on average by 44 ppm, 985 ± 97 ppm by 2100) and hence higher radiative forcing (by 0.25 W m−2) when driven by CO₂ emissions than for the concentration-driven scenarios (941 ppm). However, most of these models already overestimate the present-day CO₂, with the present-day biases reasonably well correlated with future atmospheric concentrations’ departure from the prescribed concentration. The uncertainty in CO₂ projections is mainly attributable to uncertainties in the response of the land carbon cycle. As a result of simulated higher CO₂ concentrations than in the concentration-driven simulations, temperature projections are generally higher when ESMs are driven with CO₂ emissions. Global surface temperature change by 2100 (relative to present day) increased by 3.9° ± 0.9°C for the emission-driven simulations compared to 3.7° ± 0.7°C in the concentration-driven simulations. Although the lower ends are comparable in both sets of simulations, the highest climate projections are significantly warmer in the emission-driven simulations because of stronger carbon cycle feedbacks.
Natural gas is seen by many as the future of American energy: a fuel that can provide energy independence and reduce greenhouse gas emissions in the process. However, there has also been confusion ...about the climate implications of increased use of natural gas for electric power and transportation. We propose and illustrate the use of technology warming potentials as a robust and transparent way to compare the cumulative radiative forcing created by alternative technologies fueled by natural gas and oil or coal by using the best available estimates of greenhouse gas emissions from each fuel cycle (i.e., production, transportation and use). We find that a shift to compressed natural gas vehicles from gasoline or diesel vehicles leads to greater radiative forcing of the climate for 80 or 280 yr, respectively, before beginning to produce benefits. Compressed natural gas vehicles could produce climate benefits on all time frames if the well-to-wheels CH4 leakage were capped at a level 45–70% below current estimates. By contrast, using natural gas instead of coal for electric power plants can reduce radiative forcing immediately, and reducing CH4 losses from the production and transportation of natural gas would produce even greater benefits. There is a need for the natural gas industry and science community to help obtain better emissions data and for increased efforts to reduce methane leakage in order to minimize the climate footprint of natural gas.
PDF
