Characteristics of NOX and NH3 emissions from in-use heavy-duty diesel vehicles with various aftertreatment technologies in China

Characteristics of inland ship and the effect of combined diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) aftertreatment system on their pollutant emissions

Inland ships, often overlooked, are major sources of air pollution, especially near populated areas. This study aims to characterize emissions from inland ships and evaluate the effectiveness of Diesel Oxidation Catalyst (DOC) and Diesel Particulate Filter (DPF) systems in reducing pollutants across various operational loads. Emission factors (EFs) of PM and CO2 in raw exhaust, untreated by DOC+DPF, increase with engine load, reaching 9.21 g kg-fuel-1 and 3060 g kg-fuel-1 at 75% load, respectively. Conversely, the EFs of CO and volatile organic compounds (VOCs) in raw exhaust decreased with higher engine load, with averages of 12.7±10.9 g kg-fuel-1 and 2.46±1.52 g kg-fuel-1, respectively. Additionally, oxygenated VOCs (OVOCs) made up more than 43.3±15.9% of total VOCs, with formaldehyde and acetaldehyde being the most prevalent species, contributing 55.9-75.3% of OVOCs. Ozone formation potential (OFP) was primarily driven by OVOCs, with EFs of 4.84±5.44 g O3 kg-fuel-1 while secondary organic aerosol formation potential (SOAFP) was dominated by aromatics, with EFs of 0.742±0.365 g SOA kg-fuel-1. The DOC+DPF installation reduced PM by 92.1%, CO by 100%, and VOCs by 84.1% at the highest load. Additionally, they reduced OVOCs by 65.8±6.62 % and aromatics by 74.9±12.5%, further lowering OFP and SOAFP. The NO conversion increased with engine load, but NO2 was generated, resulting in a low total NOx conversion efficiency of 11.7-13.2%. This study highlights the effectiveness of DOC+DPF system at higher loads in reducing PM, CO, and VOC emissions from inland ships, providing insights for future air quality improvement and global studies on aftertreatment systems.

Unraveling Reactive Nitrogen Emissions in Heavy-Duty Diesel Vehicles across Evolving Standards and Cheating Tactics

Reactive nitrogen (Nr) emissions significantly affect air quality and the nitrogen cycle in ecosystems. Heavy-duty diesel vehicles (HDDVs), as major sources of these emissions, exhibit complex emission characteristics because of the combined effects of different driving conditions and aftertreatment technologies. This study first investigated the emission factors (EFs) of Nr species, including NO, NO2, HONO, N2O, and NH3, from HDDVs under different emission standards (China IV/V/VI) and cheating strategies, with a particular focus on the impact of selective catalytic reduction (SCR) systems. Vehicles employing water injection cheating present NO, NO2, and HONO EFs that are consistent with the China III standards, significantly undermining the effectiveness of Nr emission control. The evolution of SCR technology in China IV, V, and VI standards has generally led to substantial reductions in NO, NO2, and HONO emissions, yet the integration of ammonia slip catalysts (ASC) systems in China VI vehicles presents new challenges. While ASCs have successfully reduced NH3 slip to an average of 17 ± 12 mg/km, they have also caused a 6-13-fold increase in N2O emissions compared with those of China IV and V vehicles, reaching levels of 205 ± 85 mg/km. Additionally, China VI vehicles exhibit a marked increase in the HONO/NOx ratio, which increases from 0.9% in China V to 4.6%. These increases are attributed to high-temperature oxidation of NH3 within the ASC catalyst, leading to undesirable byproducts. The temporal dynamics of Nr emissions under real-world driving conditions further reveal that the effectiveness of aftertreatment technologies and their selectivity toward byproducts vary depending on the driving mode. This variability underscores the need for further optimization of the SCR and ASC technologies to balance the control of all the reactive nitrogen species effectively.

The next challenge in emissions control for heavy-duty diesel vehicles: From NOx to N2O

Vehicle emissions are a major source of greenhouse gases globally. Dual selective catalytic reduction (SCR), an advanced version of single SCR, is crucial under stricter nitrogen oxide (NOx) emission standards for heavy-duty diesel vehicles (HDDVs). However, the emission characteristics of nitrous oxide (N2O), a byproduct of SCR and a potent greenhouse gas, remain unclear. This study investigates the N2O emissions from HDDVs equipped with single or dual SCR systems using heavy-duty chassis dynamometers under various ambient temperatures, altitudes, and loading masses. The results showed that the brake-specific emissions (EFb) of N2O from HDDVs with single and dual SCRs were 76.28-269.65 mg/kWh and 147.50-170.22 mg/kWh, respectively. Notably, the dual SCR-equipped HDDV emitted 6-22 times more N2O than NOx under all tested conditions. As ambient temperature increased from -10 °C to 25 °C and from 25 °C to 40 °C, the average distance-based emission factors (EFd) of N2O for the single SCR-equipped HDDV increased by 87.73% and 48.26%, respectively. However, the variation was not significant for the dual SCR-equipped HDDV. Under half- and full-load conditions, the average EFd of N2O for the single SCR-equipped HDDV increased by 47.57% and 110.92%, respectively, compared to those without loading. Similarly, N2O emissions for dual SCR-equipped HDDV increased by 41.40% and 65.37% under the same loading variations. As altitude increased from 0 m to 3000 m, the average EFd of N2O for the single SCR-equipped HDDV decreased by 64.31%. Additionally, N2O emissions were significantly affected by SCR temperature, engine power, and nitric oxide (NO)/nitrogen dioxide (NO2) ratio. These findings are crucial for setting future greenhouse gas limits of HDDVs and informing carbon reduction strategies.

Clarifying the impact of engine operating parameters of heavy-duty diesel vehicles on NOx and CO2 emissions using multimodal fusion methods

The issue of air pollution from transportation sources remains a major concern, particularly the emissions from heavy-duty diesel vehicles, which pose serious threats to ecosystems and human health. China VI emission standards mandate On-Board Diagnostics (OBD) systems in heavy-duty diesel vehicles for real-time data transmission, yet the current data quality, especially concerning crucial parameters like NOx output, remains inadequate for effective regulation. To address this, a novel approach integrating Multimodal Feature Fusion with Particle Swarm Optimization (OBD-PSOMFF) is proposed. This network employs Long Short-Term Memory (LSTM) networks to extract features from OBD indicators, capturing temporal dependencies. PSO optimizes feature weights, enhancing prediction accuracy. Testing on 23 heavy-duty vehicles demonstrates significant improvements in predicting NOx and CO2 mass emission rates, with mean squared errors reduced by 65.205 % and 70.936 % respectively compared to basic LSTM models. This innovative multimodal fusion method offers a robust framework for emission prediction, crucial for effective vehicle emission regulation and environmental preservation.

Characterization of on-road nitrogen oxides and black carbon emissions from high emitters of heavy-duty diesel vehicles in China

Heavy-duty diesel vehicles (HDDVs) significantly contribute to atmospheric nitrogen oxides (NOX) and black carbon (BC), with high emitters within the HDDV fleet impacting the total emissions. However, emission patterns and contributions of high emitters are rarely explored from a fleet-perspective. We investigated NOX and BC emission factors (EFs) from 1925 HDDVs in Shenzhen by the plume-chasing method, and found that the fleet-average EFs decreased with stricter emission standards. Unexpectedly, the average NOX EF for the China IV fleet was comparable with that for the China III fleet due to possible ineffective aftertreatment in high-emitter sectors of China IV HDDVs. Decreasing trend in average NOX EF since 2017 reflected the effective emission controls by the implementation of China V standard. Besides, semi-trailer tractors exhibited a higher incidence of NOX over-emissions, whereas BC high emitters were more pronounced in box trucks. Total NOX and BC emissions from HDDVs in Shenzhen were revisited, reaching 54.0 and 1.1 Gg·yr-1, with updated NOX EF correcting a 26.2 % underestimation in national guidelines. Notably, eliminating high emitters yields greater emission reduction benefits than merely retiring old HDDVs, with BC reduction outpacing NOX. This study provides new insights into the implementation of targeted emission reduction measures for HDDVs.

Wood Fiber-Based Triboelectric Material with High Filtration Efficiency and Antibacterial Properties and Its Respiratory Monitoring in Mask

Self-powered wearable electronic products have rapidly advanced in the fields of sensing and health monitoring, presenting greater challenges for triboelectric materials. The limited surface polarity and structural defects in wood fibers restrict their potential as substitutes for petroleum-based materials. This study used bagasse fiber as the raw material and explored various methods, including functionalizing cellulose nanofibrils (CNFs) with polydopamine (PDA), in situ embedding of silver particles, filtration, and freeze-drying. These methods aimed to enhance the triboelectric output, antibacterial properties, and filtration properties of lignocellulosic materials. The Ag/PDA/CNF-based triboelectric nanogenerator (TENG) demonstrated an open-circuit voltage of 211 V and a short-circuit current of 18.1 μA. An aerogel prepared by freeze-drying the Ag/PDA/CNF material, combined with a polyvinylidene fluoride nanofiber structure fabricated by electrospinning, constitutes the TENG unit. A self-powered respiratory detection mask was created using this combination, achieving a filtration efficiency of 94.23% for 0.3 μm particles and an antibacterial rate exceeding 99%. In addition, it effectively responded to respiratory frequency signals of slow breathing, normal breathing, and shortness of breath, with the output electrical signal correlating with the respiratory frequency. This study considerably contributes to advancing wood fiber-based triboelectric materials as alternatives to petroleum-derived materials in self-powered wearable electronic products for medical applications.

Adaptive time-step unscented kalman filtering (ATS-UKF) based observer design for urea selective catalytic reduction (SCR) performance of diesel engines

To reduce the number of sensors in the SCR catalyst, state feedback and fault diagnosis information are provided. Firstly, a model based on the coupling of flow, heat transfer, and gas-solid phase catalytic reaction in the SCR system is investigated in this paper. The parabolic partial differential equations are simplified by the variable substitution method and the method of lines approach (MOL). The simplified system of equations is solved by backward differentiation formulas (BDF) with adaptive adjustment time step strategy. Meanwhile, the chemical reaction parameters are accurately calibrated per second using the Levenberg-Marquardt method. Secondly, the ATS-UKF is designed in this paper, and to ensure the synchronisation between the ATS-UKF and the SCR model calculations, the time step of solving the BDF by the SCR model is taken as the time step of propagating the sigma points. Two observation scenarios are assumed: (1) no downstream NH3 concentration sensor, ammonia coverage and downstream NH3 concentration are observed by ATS-UKF; (2) no downstream NOx sensor, ammonia coverage and downstream NOx concentration are observed by ATS-UKF. Finally, the paper carries out bench tests. In the first case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R². The mean absolute error (MAE) between the observed and experimental values of the ATS-UKF for the downstream NH3 concentration was 2.76 ppm. In the second case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R², and the MAE between the observed and experimental values of the ATS-UKF for the downstream NOx concentration was 1.53 ppm. ENVIRONMENTAL IMPLICATION: The Adaptive Time-Step Unscented Kalman Filtering (ATS-UKF) enhances urea Selective Catalytic Reduction (SCR) in diesel engines, improving environmental outcomes. This method minimizes sensor dependence, enabling more precise SCR system management and effective emission reduction. By advancing emission control technologies, ATS-UKF contributes to global air pollution mitigation efforts, supporting cleaner air and environmental sustainability. Its innovative approach in monitoring and predicting SCR performance marks a significant step towards eco-friendly diesel engine operation.