Reduction Of Nitrogen Oxide Emissions Research Articles

Nonlinear effect of NOx concentration decrease on secondary aerosol formation in the Beijing-Tianjin-Hebei region: Evidence from smog chamber experiments and field observations

During the COVID-19 lockdown in the Beijing-Tianjin-Hebei (BTH) region in China, large decrease in nitrogen oxides (NOx) emissions, especially in the transportation sector, could not avoid the occurrence of heavy PM2.5 pollution where nitrate dominated the PM2.5 mass increase. To experimentally reveal the effect of NOx control on the formation of PM2.5 secondary components (nitrate in particular), photochemical simulation experiments of mixed volatile organic compounds (VOCs) under various NOx concentrations with smog chamber were performed. The proportions of gaseous precursors in the control experiment were comparable to ambient conditions typically observed in the BTH region. Under relatively constant VOCs concentrations, when the initial NOx concentration was reduced to 40% of that in the control experiment (labelled as NOx,0), the particle mass concentration was not significantly reduced, but when the initial NOx concentration decreased to 20 % of NOx,0, the mass concentration of particles as well as nitrate and organics showed a sudden decrease. A “critical point” where the mass concentration of secondary aerosol started to decline as the initial NOx concentration decreased, located at 0.2–0.4 NOx,0 (or 0.18–0.44 NO2,0) in smog chamber experiments. The oxidation capacity and solar radiation intensity played key roles in the mass concentration and compositions of the formed particles. In field observations in the BTH region in the autumn and winter seasons, the “critical point” exist at 0.15–0.34 NO2,0, which coincided mostly with the laboratory simulation results. Our results suggest that a reduction of NOx emission by >60% could lead to significant reductions of secondary aerosol formation, which can be an effective way to further alleviate PM2.5 pollution in the BTH region.

A sustainable model using RSM and MCDM techniques to evaluate performance and emission characteristics of a diesel engine fueled with diphenylamine antioxidant and CeO2 nanoparticle additive biodiesel blends

Overconsuming fossil fuels has worsened global warming and air pollution, requiring us to investigate alternate fuels for compression ignition engines. Biodiesel is a renewable fuel and environmentally favorable. Biodiesel's most significant disadvantage is increased nitrogen oxide (NOx) emissions. The intent of the present study was to examine the impact of antioxidant diphenylamine (DPA) and nanoparticle ceria (CeO2) additive inclusion in a B30 blend on engine performance and exhaust emission characteristics. For this study, diesel, Jatropha biodiesel (B30), 100 ppm of antioxidant diphenylamine (50 ppm) with ceria nanoparticle (50 ppm) is added to the B30 blend named as B30+DPA100 and antioxidant diphenylamine (50 ppm) with ceria nanoparticle (50 ppm) is added to the B30 blend named as B30+DPA50+CeO250 fuel blends has been used. A hybrid response surface methodology and multi-criteria decision-making techniques (entropy method, TOPSIS, and VIKOR) have been used to develop a sustainable model and find the optimal setting of input parameters in terms of ranking. From experimental findings, the inclusion of antioxidants (DPA) and nanoparticle (CeO2) at 50 ppm to B30 significantly reduced NOx emission. The brake-specific fuel consumption and NOx have been found reduced by 5.67% and 18.87%, respectively, for B30+DPA50+CeO250 as compared to B30. At the same time, brake thermal efficiency increased by 1.01%. The brake mean effective pressure and maximum cylinder pressure) have been found increased by 0.68% and reduced by 4.52%, respectively, for B30+DPA50+CeO250 as compared to B30. The alternative ranking of the input parameters has been found fuel injection pressure (300), compression ratio (17), and load (12) as Rank 1 for TOPSIS and VIKOR. Therefore, the B30+DPA50+CeO250 blend is appropriate for improving diesel engine performance and diminishing exhaust emissions.

Data‐ and Model‐Based Urban O3 Responses to NOx Changes in China and the United States

AbstractUrban air pollution continues to pose a significant health threat, despite regulations to control emissions. Here we present a comparative analysis of urban ozone (O3) responses to nitrogen oxide (NOx) changes in China and the United States (US) over 2015–2020 by integrating various data‐ and model‐based methods. The data‐based deep learning (DL) model exhibited good performance in simulating urban air quality: the correlation coefficients (R) of O3 daily variabilities with respect to independent O3 observations are 0.88 and 0.79 over N. China, 0.87 and 0.90 over S. China, and 0.87 and 0.49 over E. United States by the DL and GEOS‐Chem chemical transport models, respectively. Furthermore, the data‐based methods suggest volatile organic compound (VOC)‐limited regimes in urban areas over northern inland China and transitional regimes over eastern US urban areas; in contrast, GEOS‐Chem model suggests strong NOx‐limited regimes. Sensitivity analysis indicates that the inconsistent O3 responses are partially caused by the inaccurate representation of O3 precursor concentrations at the locations of urban air quality stations in the simulations, while the data‐based methods are driven by the variabilities in local O3 precursor concentrations and meteorological conditions. The O3 responses to NOx changes reported here provide a better understanding of urban O3 pollution; for example, reductions in NOx emissions are suggested to have resulted in an increase in surface O3 by approximately 7 ppb in the Sichuan Basin in 2014–2020.

Performance research and optimization of marine dual-fuel engine based on RSM and NSGA-II

ABSTRACT In order to improve the economic efficiency of the ship when sailing and reduce the engine optimization cost. We propose the Response Surface Methodology (RSM) combined with NSGA-II to optimize the engine parameters. First, a simulation model of a marine four-stroke dual-fuel engine is established in AVL-BOOST software. Then, control parameters such as engine speed, exhaust valve opening (EVO) and compression ratio (CR) are planned by design of experiments. The response surface model was established in Design-Expert software. The significant influence of control parameters on performance parameters was studied by analysis of variance (ANOVA). Finally, with the output power, indicated fuel consumption rate and nitrogen oxide emissions as the optimization objectives. Non-dominated Sequential Genetic Algorithm (NSGA-II) is used to optimize the parameters to improve engine performance and reduce emissions. The results show that the established response surface model has good prediction accuracy. The response surface model visualizes the mathematical relationship between the control parameters and the optimization targets. The ANOVA results show that engine speed, EVO and CR have significant effects on engine performance and emissions. The optimization results show that the engine speed is 793 rpm, the EVO is 145°CA, and the CR is 12.3. Compared to standard settings, the optimized data shows a 3.4% increase in power, a 0.3% reduction in ISFC, and a 6.2% reduction in nitrogen oxide (NOx) emissions. The combination of response surface analysis and NSGA-II algorithm to optimize engine performance and emissions is thereby a feasible method.

Impact of spatial scales of control measures on the effectiveness of ozone pollution mitigation in eastern China

Ozone (O3) pollution is becoming the primary air pollution issue with the large decrease in fine particulate concentrations in eastern China. The development of widely recognized policies for controlling O3 pollution episodes is urgent. This study aims to provide actionable and comprehensive suggestions for O3 control policy development, with an emphasis on the precursor emission reductions.Here, we compared the impacts of different spatial scale reductions on a widespread O3 pollution episode in eastern China by a state-of-the-art regional air quality model. We find that region-scale joint control (in >30 cities) is much more effective than city-scale sporadic reduction in reducing O3 concentration. Sporadic controls only reduce the maximum daily 8-h average (MDA8) O3 by ∼1 μg/m3 in the controlled city, whereas regional controls lead to a MDA8 O3 decrease of ∼8 μg/m3 in the controlled region. In addition, the emission reduction effectiveness increased by 2.6 times from <5 cities to >30 cities. Continuous reductions have a cumulative effect on the decrease of MDA8 O3, showing the strongest effects within 24 h and diminishing after 48 h, which underscores the importance of reducing emissions 24 h prior to an episode. Moreover, the effect of control measures on MDA8 O3 varies spatially depending on the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NOx) (VOCs/NOx). Both the reductions of VOC and NOx emissions have a positive effect on the decrease of MDA8 O3 in summer, but the effects of VOC reductions are 1.2 to 1.7 times higher than those of NOx reductions. The residential sector, due to its high VOCs/NOx emission ratio, exhibits the highest efficiency in the reduction of O3 concentrations. Our results highlight the importance of regional joint control and synergistic reduction of VOCs and NOx in eastern China.

Performance and Emission Analysis of Biodiesel Blends in a Low Heat Rejection Engine with an Antioxidant Additive: An Experimental Study.

The rapid depletion of crude oil and environmental degradation necessitate the search for alternative fuel sources for internal combustion engines. Biodiesel is a promising alternative fuel for compression ignition (CI) engines due to its heat content and combustion properties. Biodiesel blends are used in various vehicles and equipment, such as cars, trucks, buses, off-road vehicles, and oil furnaces. Biodiesel can reduce emissions from CI engines by up to 75% and improve engine durability due to its high lubricity. However, biodiesel has some drawbacks, including a performance reduction and increased nitrogen oxide emissions. Therefore, this study aims to investigate using environmentally available biodiesel in a low-heat rejection engine and an antioxidant additive to enhance the performance and reduce nitrogen oxide emissions. India currently has several biodiesel sources, including mango seed oil, mahua oil, and pongamia oil, which can be effectively utilized in CI engines by adding l-ascorbic acid. The experimental work involves a single-cylinder 4-stroke water-cooled direct injection CI engine with a power output of 5.2 kW. The engine's cylinder head, piston head, and valves are coated with lanthanum oxide using the plasma spray coating technique, with a thickness of 0.5 mm. The coated and uncoated engines are tested with different proportions of mahua oil, mango seed oil, and pongamia oil. The results show that the engine's performance is significantly improved compared to the baseline engine at all loads. Additionally, these biodiesels exhibit a notable reduction in nitrogen oxide emissions when combined with l-ascorbic acid.

Deep-learning-based reduced-order modeling to optimize recuperative burner operating conditions

This study analyzed a recuperative burner system that is critical for energy efficiency and pollutant reduction in the firing processes required in the manufacturing industries. We aimed to optimize the operating conditions of a recuperative burner using computational fluid dynamics (CFD) combined with a novel reduced-order deep-learning technique. The Reynolds-averaged Navier–Stokes model and finite-rate/eddy-dissipation models were used to generate reliable CFD simulation results considering four operating conditions (temperature and mass flow rate of air and fuel). We first validated the CFD model with two-dimensional axis-symmetric experimental burner results and created a proper orthogonal decomposition transformer model using large-scale snapshots of the CFD results and various operating conditions. Subsequently, a genetic algorithm was employed to find the optimal conditions for five different objective functions: fuel economy, decrease in carbon monoxide emissions, reduction in nitrogen oxide emissions, decrease in carbon dioxide production, and an all-encompassing view of the four objectives. Finally, by comparing our proposed approach with previous methods, we confirmed that the obtained optimal operating conditions improve the performance of the recuperative burner. This study provides an optimized framework for recuperative burners to reduce environmental pollution, with potential applications in many industries, such as ceramics, steel, and batteries.

Acceleration of premixed H[formula omitted]-Air-Steam flames when accounting for thermal radiation

Diluting hydrogen flames with steam can increase flame stability and reduce nitrogen oxide emissions. While the effects of dilution on the flame characteristics due to variations in chemistry or transport properties have been well investigated, this is not the case for those related to thermal radiation. Thermal radiation is indeed often neglected in free flame simulations. However, it can be critical in diluted flames in which participating species are present in the fresh gases. This study explores thermal radiation’s impact on H2-Air flames diluted with steam through 1D laminar flame computations. To this end, a reactive fluid solver is coupled with a semi-analytical thermal radiation code. Both the grey gas approximation, for a preliminary understanding, and the more accurate CK narrow-band model, for detailed simulations that account for spectral-dependent gas properties, are used. The combustion numerical setup is validated against literature results. Three main thermal radiation effects are highlighted: a preheating of the fresh gases, an increased laminar flame speed, and a decreased temperature in the burnt gases. It is found that domain length considerably affects this preheating and flame speed, which can then affects laminar burning velocity measurements. It is shown that thermal radiation and combustion can often be decoupled and that a preheated adiabatic flame can recover the main characteristics of the corresponding radiative flame. The increase of the laminar flame speed by thermal radiation is reported for a wide range of equivalence ratios, dilution levels, and pressures. The observed acceleration is especially significant for lean and very lean flames which can be up to 500% faster when considering thermal radiation.

Application of high-frequency water injection for the performance improvement of waste-heat-recovery boilers

It has been discussed that injecting water into the intake air can increase thermal efficiency and reduce NOx emissions simultaneously in waste-heat-recovery boilers (WHRB). To increase the evaporation rate of the injected water and recover more thermal energy through the heat exchanger, the water injection amount needs to be controlled properly and droplets in the spray need to be distributed homogeneously with the smallest droplets possible. To achieve this, this study introduces a high-frequency injection strategy that can generate strong in-nozzle turbulence, thus promoting spray atomization and supplying continuous water to the heat exchanger. Three different injection frequencies are applied to investigate water spray characteristics. The water spray structure is visualized using the Mie-scattering technique, and the droplet size is measured using the laser diffraction method. In addition, practical boiler tests are performed to confirm the effect of the high-frequency water injection on the boiler performance. The experimental results showed that the mean droplet size decreased, and the spatial and temporal homogeneity of the spray distribution was improved as the injection frequency increased. As a result of the higher water injection frequency, the evaporation rate and thermal efficiency of the boiler increased, and nitrogen oxide (NOx) emissions decreased.

Detailed assessment of exhaust emissions in a diesel engine running with low-carbon fuels via FTIR spectroscopy

Low-carbon fuels have been proposed as alternatives that can help with the transition to a sustainable and decarbonized transport sector. This study examines the potential of four different fuel blends with different renewable content to reduce pollutant emissions by evaluating both regulated and unregulated emissions produced by their combustion in a light-duty compression ignition engine. The study distinguishes between two measurement conditions: drop-in and optimized calibration. The drop-in calibration represents the operation of low-carbon fuels using baseline injection settings, while the optimized calibration involves a specific approach to reduce nitrogen oxide emissions. Unregulated emissions were measured using a Fourier Transform Infrared analyzer, which recorded various substances, including aldehydes (acetaldehyde, formaldehyde), saturated hydrocarbons (ethylene, propylene, 1,3 butadiene, and isobutylene), unsaturated hydrocarbons (methane and ethane), aromatics (benzene and toluene), and the greenhouse gas nitrous oxide (N2O). Results indicated that aldehyde production is not affected at low-load operation for fuels with higher oxygen content, but instead, the use of diesel from vegetable origin in the fuel blend could lead to slight increases in this species. On the other hand, the production of saturated hydrocarbons was impacted by the cylinder temperature and combustion duration, being the oxygenated fuels with longer combustion durations at low-load, which reported reductions, but at mid-load, this effect is mitigated. In addition, the production of aromatics and unsaturated hydrocarbon emissions were assessed as soot precursors. The production rate of these species was higher when the calibration was applied due to the reductions in NOx and increases in soot emissions. Lastly, the results of N2O emissions showed slight decreases in the combustion of oxygenated fuels when using the drop-in calibration, but these emissions returned to similar diesel levels when applying the optimized calibration. Overall, the results of the investigation show the potential of these LCFs to meet the regulations but also not sacrificing the emissions performance of unregulated species.

Influence of alumina nanoparticles additives into biofuel (water hyacinth)‐diesel mixture on diesel engine performance and emissions

AbstractThe using diesel and biodiesel blends as a fuel has been a recent field of study especially with nanoparticles additives. The addition of alumina nanoparticles to biodiesel was verified to reduce emissions, while engine performance was not given great attention to evaluate the effect of blending alumina nanoparticles with the diesel and biodiesel mixture on the performance characteristics of the diesel engine. Then performance and emission tests were carried out by using different fuel samples in a single cylinder diesel engine. The brake thermal efficiency for the alumina nanoparticles (50 ppm, 100 ppm) and biodiesel blends were lower than that of biofuel (D80B20) blends, it was decreased by 2.5 %, 6.05 % respectively as compared to the blend (D80B20). The rate of carbon monoxide emissions for the two biodiesel and alumina blends were lower than that of the biodiesel blend (D80B20) and the best reduction was for the blend (D80B20N50) and was 76.3 % as compared with the biodiesel blend (D80B20). Also, the nitrogen oxides emissions for all the blends with nanoparticles were lower than that of the blend D80B20 due to shortened ignition delay and less fuel was added during the combustion which lead to reduction in nitrogen oxides emissions.

THERMOPHYSICAL AND ENVIRONMENTAL ASSESSMENT OF NATURAL GAS UTILIZATION IN THE RECONSTRUCTION OF A PULVERIZED COAL-FIRED BOILER

Link for citation: Maltsev K.I., Gil A.V., Abramov N.V., Puzyrev S.A. Thermophysical and environmental assessment of natural gas utilization in the reconstruction of a pulverized coal-fired boiler. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 8, рр. 30-38 In Rus. The relevance of the investigation is caused by the need to assess the completeness of fuel combustion, harmful emissions, and temperature stress of the screen surfaces of a pulverized coal-fired boiler during its reconstruction for natural gas combustion. Currently, the conversion of solid fuel combustion installations to natural gas is highly relevant due to significantly lower emissions of carbon compounds. The main aim of this research is to study the physicochemical processes in the combustion chamber at various loads with flammable natural gas combustion and evaluate the effectiveness of combustion organization during the reconstruction of a pulverized coal-fired boiler. Objects: combustion chamber of a boiler unit with a steam capacity of 210 t/h, burners, parameters of the combustion chamber environment Methods: comparison of results obtained from analytical thermal calculations and numerical modeling. The numerical simulation of gas flare combustion was performed using the ANSYS Fluent software package. Reynolds Averaged Navier–Stokes approaches based on averaging the Navier–Stokes equations over the Reynolds number with additional equations for the turbulent kinetic energy k and the rate of turbulent kinetic energy dissipation ε were applied to describe the turbulent flow. Results. A numerical study of the physicochemical processes in the combustion chamber of a boiler unit was conducted after its reconstruction for natural gas combustion. Dependencies of temperature level changes, hydrodynamics, and concentrations of combustion products components in the volume of the combustion chamber at various loads were obtained. It was found that high-temperature combustion products are redistributed towards the front and rear walls, resulting in the formation of zones in the wall layer with a significant temperature gradient. The nozzles of the tertiary air contribute to the reduction of nitrogen oxide emissions in the combustion chamber by suppressing their formation due to oxygen deficiency in the combustion zone, as well as by lowering the temperature of the flame in the oxidizing zone.

Direct observations of NOxemissions over the San Joaquin Valley using airborne flux measurements during RECAP-CA 2021 field campaign

Abstract. Nitrogen oxides (NOx) are principle components of air pollution and serve as important ozone precursors. As the San Joaquin Valley (SJV) experiences some of the worst air quality in the United States, reducing NOx emissions is a pressing need, yet quantifying current emissions is complicated due to a mixture of mobile and agriculture sources. We performed airborne eddy covariance flux measurements during the Re-Evaluating the Chemistry of Air Pollutants in California (RECAP-CA) field campaign in June 2021. Combining footprint calculations and land cover statistics, we disaggregate the observed fluxes into component fluxes characterized by three different land cover types. On average, we find emissions of 0.95 mg N m−2 h−1 over highways, 0.43 mg N m−2 h−1 over urban areas, and 0.30 mg N m−2 h−1 over croplands. The calculated NOx emissions using flux observations are utilized to evaluate anthropogenic emissions inventories and soil NOx emissions schemes. We show that two anthropogenic inventories for mobile sources, EMFAC (EMission FACtors) and FIVE (Fuel-based Inventory for Vehicle Emissions), yield strong agreement with emissions derived from measured fluxes over urban regions. Three soil NOx schemes, including the MEGAN v3 (Model of Emissions of Gases and Aerosols from Nature), BEIS v3.14 (Biogenic Emission Inventory System), and BDISNP (Berkeley–Dalhousie–Iowa Soil NO Parameterization), show substantial underestimates over the study domain. Compared to the cultivated soil NOx emissions derived from measured fluxes, MEGAN and BEIS are lower by more than 1 order of magnitude, and BDISNP is lower by a factor of 2.2. Despite the low bias, observed soil NOx emissions and BDISNP present a similar spatial pattern and temperature dependence. We conclude that soil NOx is a key feature of the NOx emissions in the SJV and that a biogeochemical-process-based model of these emissions is needed to simulate emissions for modeling air quality in the region.

Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals

Remote sensing data from the Ozone Monitoring Instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI) play important roles in estimating surface nitrogen dioxide (NO2), but few studies have compared their differences for application in surface NO2 reconstruction. This study aims to explore the effectiveness of incorporating the tropospheric NO2 vertical column density (VCD) from OMI and TROPOMI (hereafter referred to as OMI and TROPOMI, respectively, for conciseness) for deriving surface NO2 and to apply the resulting data to revisit the spatiotemporal variations in surface NO2 for Beijing over the 2005–2020 period during which there were significant reductions in nitrogen oxide emissions. In the OMI versus TROPOMI performance comparison, the cross-validation R2 values were 0.73 and 0.72, respectively, at 1 km resolution and 0.69 for both at 100 m resolution. The comparisons between satellite data sources indicate that even though TROPOMI has a finer resolution it does not improve upon OMI for deriving surface NO2 at 1 km resolution, especially for analyzing long-term trends. In light of the comparison results, we used a hybrid approach based on machine learning to derive the spatiotemporal distribution of surface NO2 during 2005–2020 based on OMI. We had novel, independent passive sampling data collected weekly from July to September of 2008 for hindcasting validation and found a spatiotemporal R2 of 0.46 (RMSE = 7.0 ppb). Regarding the long-term trend of surface NO2, the level in 2008 was obviously lower than that in 2007 and 2009, as expected, which was attributed to pollution restrictions during the Olympic Games. The NO2 level started to steadily decline from 2015 and fell below 2008's level after 2017. Based on OMI, a long-term and fine-resolution surface NO2 dataset was developed for Beijing to support future environmental management questions and epidemiological research.

Engine preheating under real-world subfreezing conditions provides less than expected benefits to vehicle fuel economy and emission reduction for light-duty vehicles

Six light-duty vehicles, both gasoline- and diesel-fueled, were driven a prescribed 13.8 km route in a real-world low-traffic environment under Finnish subfreezing winter conditions (−28 ... −10 °C). Cold starts, hot starts, and starts with different preheating strategies were used. Fuel consumption and emissions of particles and nitrogen oxides (NOx) were examined by a chasing method with a mobile laboratory. Both electric preheaters (0.3–1.2 kW) and fuel-operated auxiliary heaters (5 kW) were used in the experiments where a cold engine was preheated before starting. While most vehicles showed potential for reducing fuel consumption and emissions of particles (PM), black carbon (BC), and NOx during hot starts compared to subfreezing-cold starts, the benefits of preheating were relatively small and limited to only a few vehicles. The fuel consumption for the 13.8 km drive decreased less than 4% with one gasoline vehicle and one diesel vehicle by preheating. These two vehicles are both equipped with a fuel-operated auxiliary heater, and taking the fuel consumption of the heater during preheating into account leads to about 30% higher total fuel consumption, canceling the preheating benefit out. These two vehicles also showed the largest reductions in PM, BC, and NOx emissions achieved with preheating, e.g., the PM emission reductions being 72% (the gasoline vehicle) and 24% (the diesel vehicle). Whereas the NOx emission reduction for this gasoline vehicle was 41% when considering only the drive, it decreases to 15% when the NOx emissions from the auxiliary heater during preheating are also taken into account. High particle number (PN) emissions from all vehicles and NOx emissions from the diesel vehicles were detected. The PN emissions of particles larger than 23 nm were up to 2 orders of magnitude higher and the NOx emissions up to a factor of 21 higher than the corresponding limits in the European regulations for type-approval of new vehicles. The PN emissions did not depend on the start types; thus, no benefits to reduce them with preheating were detected. The limit-exceeding PN emissions are partially explained with the used measurement method for PN taking both nonvolatile and semivolatile particles into account, whereas the regulations take only the nonvolatile particles into account. The PM emissions were also observed to consist mostly of semivolatile material in most of the cases, organics being the main component of the semivolatile material.

Adaptation of Existing Vessels in Accordance with Decarbonization Requirements—Case Study—Mediterranean Port

This research investigates the application of photovoltaic (PV) systems on ship retrofits with the aim of reducing the emission of harmful gases. By using renewable energy resources, this research presents the potential for reducing greenhouse gas (GHG) emissions and improving energy efficiency in maritime operations, specifically within the Split coastal area. Overcoming the space restrictions on ships, an innovative design is presented to maximize the installation area for solar power. The research is conducted for several cases based on the IHOGA simulator, for all ship phases, and it aims to minimize fuel consumption by the diesel generators, thus emphasizing the use of renewable energy resources. A model with two operational modes is designed: Mode 1 allows surplus power to charge batteries or supply the port network, while Mode 2 covers power deficits from alternative sources. The implementation of renewables results in carbon dioxide (CO2) and nitrogen oxide (NOX) emission reductions. Furthermore, during the ship hotelling phase, the load is supplied entirely by batteries, resulting in zero emissions at the port.

Effects of integrated aftertreatment system on regulated and unregulated emission characteristics of non-road methanol/diesel dual-fuel engine

In order to ensure that output power, fuel economy and harmful emissions of non-road diesel engines meet the limit requirements, and reduce the dependence on fossil fuels, methanol/diesel dual-fuel combustion mode was conducted on an agricultural four-cylinder common-rail engine, and the effects of DOC + DPF + SCR aftertreatment system on overall performance and emission characteristics of dual-fuel mode were systematically investigated. Results show that dual-fuel mode can reduce both nitrogen oxide (NOx) and soot emissions, but increase nitrogen dioxide (NO2), methanol and formaldehyde (HCHO) emissions. With the increase of load, the conversion efficiency of diesel oxidation catalyst (DOC) to carbon hydrogen (HC), carbon monoxide (CO), methanol and HCHO emissions is continuously improved. DOC can increase NO2/NOx ratio for diesel mode, but reduce NO2/NOx ratio for dual-fuel mode. At full load, the average soot capture efficiency of diesel particulate filter (DPF) for dual-fuel engine is 98.84%, basically realizing zero soot emission, while the conversion efficiency of selective catalytic reduction (SCR) for NOx is 95.22%. The increase of methanol ratio can reduce NOx emissions and nitrous oxide (N2O) generation in SCR for dual-fuel mode. Under non-road steady cycle (NRSC), the maximum brake thermal efficiency (BTE) of diesel mode and dual-fuel mode are 39.4% and 41.0%, respectively. The regulation emissions of dual-fuel engine coupling with integrated DOC + DPF + SCR aftertreatment system can meet non-road Euro-V and US-Tier 4 emission standards.

Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain.

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.

Anthropogenic amplification of biogenic secondary organic aerosol production

Abstract. Biogenic secondary organic aerosols (SOAs) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability in observed organic aerosol (OA) in the southeast US, combined with a global chemistry–climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40 % of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability in surface OA. We hypothesize that the rest of the OA decreasing trend is largely due to a reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability in OA in this region. Extending to a centennial scale, our model shows that global SOA production increases by 36 % despite BVOC reductions from the preindustrial period to the present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models.

Response of PM2.5 and O3 to Emission Reductions in Nanjing Based on Random Forest Algorithm

High levels of fine particulate matter (PM2.5) and ozone (O3) in ambient air affect climate change and also endanger human health and ecosystems. Air pollution in Nanjing has been improving since the implementation of the "Air Pollution Prevention and Control Action Plan" in 2013. However, Nanjing still faces PM2.5 and O3 pollution. Evaluating the response of pollutant concentrations to the reductions in precursor emissions is helpful to obtain effective strategies of emission reduction to improve pollution levels. The sensitive simulations of emission perturbation in atmospheric chemistry models directly demonstrate the response of pollution to the reductions in emissions. Nevertheless, these sensitive simulations are limited in computing time and resources. The random forest algorithm was trained by using the simulation results of the atmospheric chemical transport model (GEOS-Chem) in 2015. The changes in daily PM2.5 and daily maximum eight-hour O3 (MDA8 O3) concentrations in Nanjing in 2019 were efficiently predicted under different reduction scenarios of anthropogenic emissions. The simulations showed that the seasonal average of ρ(PM2.5) in Nanjing would decrease by 2-4 μg·m-3 with the reduction in anthropogenic emissions of 10% in 2019 in China. In the case of controlling only local emissions in Nanjing, the concentrations of PM2.5 in Nanjing decreased significantly without local anthropogenic emissions. Additionally, the simulations showed that the annual average of ρ(PM2.5) in Nanjing could be lower than the national secondary limit (35 μg·m-3) when the anthropogenic emission reduction in China was higher than 20% in 2019. For ozone, the equal proportional emission reductions in nitrogen oxides (NOx) and volatile organic pollutants (VOCs) of O3 precursors in China likely led to the increase in seasonal average concentrations of O3 in Nanjing. For the proportional reduction of anthropogenic emissions by 10%-50% in China, the seasonal average of ρ(MDA8 O3) in Nanjing in 2019 would increase by 1-3 μg·m-3 in spring, 1-4 μg·m-3 in autumn, and 3-11 μg·m-3 in winter, respectively, compared with that in the base simulation. With the reduction in anthropogenic NOx emission by 10% and VOCs by 20%, the seasonal average of ρ(MDA8 O3) in Nanjing would decrease by 3-6 μg·m-3. On this basis, further increasing the proportion (30%) of VOCs emission reduction could reduce the annual average of ρ(MDA8 O3) in Nanjing by 7 μg·m-3. However, the annual average of ρ(MDA8 O3) of Nanjing in 2019 increased by 1 μg·m-3, with the local emission reduction of NOx by 10% and VOCs by 30%. Therefore, this showed that the key to alleviate ozone pollution in Nanjing is a reasonable control ratio of ozone precursor emissions and the implementation of regional joint prevention and control. In order to effectively reduce the O3 pollution in Nanjing, the emission reduction ratio of NOx and VOCs in China should be less than 1:2. The response of pollutant concentrations to reductions in precursor emissions were efficiently obtained by the random forest algorithm and GEOS-Chem model. The simulations would provide the scientific basis for the emission control strategy to alleviate air pollution.