Emissions of nitrogen oxides (NOx) are a dominant contributor to ambient nitrogen dioxide (NO2) concentrations, but the quantitative relationship between them at an intracity scale remains elusive. The Chengdu 2021 FISU World University Games (July 22 to August 10, 2023) was the first world-class multisport event in China after the COVID-19 pandemic which led to a substantial decline in NOx emissions in Chengdu. This study evaluated the impact of variations in NOx emissions on NO2 concentrations at a fine spatiotemporal scale by leveraging this event-driven experiment. Based on ground-based and satellite observations, we developed a data-driven approach to estimate full-coverage hourly NO2 concentrations at 1 km resolution. Then, a random-forest-based meteorological normalization method was applied to decouple the impact of meteorological conditions on NO2 concentrations for every grid cell, the resulting data were then compared with the timely bottom-up NOx emissions. The SHapley-Additive-exPlanation (SHAP) method was employed to delineate the individual contributions of meteorological factors and various emission sources to the changes in NO2 concentrations. According to the full-coverage meteorologically normalized NO2 concentrations, a decrease in NOx emissions and favorable meteorological conditions accounted for 80 % and 20 % of the NO2 reduction, respectively, across Chengdu city during the control period. Within the strict control zone, a 30 % decrease in the meteorologically normalized NO2 concentrations was observed during the control period. The normalized NO2 concentrations demonstrated a strong correlation with NOx emissions (R = 0.96). Based on the SHAP analysis, traffic emissions accounted for 73 % of the reduction in NO2 concentrations, underscoring the significance of traffic control measures in improving air quality in urban areas. This study provides insights into the relationship between NO2 concentrations and NOx emissions using real-world data, which implies the substantial benefits of vehicle electrification for sustainable urban development.

With stringent regulations of internal combustion engine on reducing CO2 emission, ammonia has been used as an alternative fuel. Investigating how engine-related performance is affected by partial ammonia replacement of diesel fuel is essential for understanding the combustion. Therefore, in this study, a three-dimensional numerical simulation model is developed for the burning of two fuels of diesel and ammonia based on relevant parameters (i.e., compression ratio, load, ammonia energy fraction, etc.) in a lab-made diesel engine. The consequences of load and compression proportion on combustion and pollutant emissions are investigated for ammonia energy fractions between 50% and 90%. When the ammonia portion rises, the increased ammonia equivalent ratio causes ammonia to move away from the dilute combustion boundary and accelerates the combustion rate of ammonia. An increase in compression ratio significantly increases the specified thermal performance and combustion efficacy. When the compression ratio is 16, as the ammonia energy fractions increases, due to the increase in the proportion of ammonia, that is, the proportion of nitrogen atoms increases, more NOx is generated during the combustion process. When the ammonia substitution rate is 90%, as the compression ratio increases, the cylinder pressure and temperature increase. The combustion efficiency of ammonia increases, generating more NOx and NOx emissions can reach 0.66 mg/m3. At a compression ratio of 18, the NOx emissions can reach 1.59 mg/m3. However, under medium and low load conditions, as the ammonia fraction increases, the total energy of fuel decreases, and the combustion efficiency of ammonia decreases, resulting in a decrease in the heat released during combustion and a decrease in NOx emissions. When the ammonia substitution rate is 90% and the load is 25%, NOx emissions reach 0.1 mg/m3. This research provides theoretical suggestions for the profitable and use ammonia fuel in internal combustion engines in a clean manner.

Accurate estimates of fossil fuel CO2 (FFCO2) emissions are of great importance for climate prediction and mitigation regulations but remain a significant challenge for accounting methods relying on economic statistics and emission factors. In this study, we employed a regional data assimilation framework to assimilate in situ NO2 observations, allowing us to combine observation-constrained NOx emissions coemitted with FFCO2 and grid-specific CO2-to-NOx emission ratios to infer the daily FFCO2 emissions over China. The estimated national total for 2016 was 11.4 PgCO2·yr-1, with an uncertainty (1σ) of 1.5 PgCO2·yr-1 that accounted for errors associated with atmospheric transport, inversion framework parameters, and CO2-to-NOx emission ratios. Our findings indicated that widely used \"bottom-up\" emission inventories generally ignore numerous activity level statistics of FFCO2 related to energy industries and power plants in western China, whereas the inventories are significantly overestimated in developed regions and key urban areas owing to exaggerated emission factors and inexact spatial disaggregation. The optimized FFCO2 estimate exhibited more distinct seasonality with a significant increase in emissions in winter. These findings advance our understanding of the spatiotemporal regime of FFCO2 emissions in China.

Various techniques are used to reduce harmful pollutants such as NOX emissions from ships. Selective catalyst reduction (SCR) systems are the most effective technique used to reduce NOX emissions. In this study, the effects of an SCR reactor on NOX emissions and performance in high-pressure selective catalytic reduction (HP-SCR) systems were investigated numerically. In numerical studies, the effects of SCR system diameter, output form, catalyst activation energy, mixing zone length, and location were investigated as parametric, and the most suitable system geometry was determined. The effects of geometric parameters and catalyst type on emission and performance such as NOX reduction, NH3 slip, velocity, and pressure loss were investigated. It was determined that with increasing system diameter, whereas the NOX reduction performance increased depending on exhaust velocity, the pressure drop decreased, and the most suitable system diameter was determined as 780 mm. Furthermore, the obtained results showed that the performance of NOX reduction decreased after 2 × 106 kJ/kmol activation energy, and the most suitable SCR output form was conical geometry. In terms of the environment, this study will contribute to achieving the UN Sustainable Development Goals such as climate action (SDG 13).

An oxygen-rich and low NOx burner integrated with liquefied natural gas (LNG) was proposed to address unstable combustion and high NOx emissions from a 330 MW subcritical boiler under ultra-low load operation in China. To assess the effectiveness of the retrofit, Chemkin and Fluent softwares were utilized to construct a new NOx model and calculate NOx generation, based on the combustion of pulverized coal gas and LNG. Further, an eddy dissipation concept (EDC) model, which can reflect detailed chemical reactions, was applied to calculate gas-phase reactions in the furnace. The results showed that when performing the deep peak shaving after the retrofit, the combustion in the furnace was stable under 50% or more load, and NOx emission level at the furnace outlet was lower than 350 mg/m3 (6% O2 content, dry basis). Under 25% load, the oxygen-rich burner integrated with LNG was applied, and the pulverized coal flow entered the furnace in a state of high-intensity combustion, which effectively promoted the stability of combustion in the furnace. The reductive combustion state with reductive free radicals generated by LNG decomposition inhibited NOx formation. Consequently, NOx emissions from the furnace outlet decreased from 380 mg/m3 to 316 mg/m3.

Reducing the differences between real-world and certificated NOx emission levels is an important element of in-use emission surveillance programs. Therefore, investigating the characteristics of the vehicles which have much higher NOx emissions (i.e., high-emitters) and determining a reasonable cut-off point to identify high-emitters with a low false detection rate is important. In this study, six diesel trucks were tested under different aftertreatment conditions. The results showed that the discrepancies of fuel-specific NOx emissions between vehicles with functioning and tampered selective catalytic reduction (SCR) systems occur mainly from medium- to high-speed modes. This is because the SCR systems were at low conversion efficiencies when the exhaust temperature was low, including cold-start and urban creep conditions. By using binary classification, we selected fuel-specific NOx cut-off points for high-emitters from China V and China VI diesel trucks. The false detection rate of high-emitters can decrease by 33 % and 95 %, if only NOx emissions from medium- to high-speed modes were used for the chosen cut-off points, respectively. This work highlights the importance of in-use emission compliance programs. It also suggests that high-emitters can be more accurately identified at medium- to high-speed modes if using instantaneous emission data.

This study investigates the long-term trends of ambient ultrafine particles (UFPs) and associated airborne pollutants in the Los Angeles Basin from 2007 to 2022, focusing on the indirect effects of regulations on UFP levels. The particle number concentration (PNC) of UFPs was compiled from previous studies in the area, and associated co-pollutant data, including nitrogen oxides (NOx), carbon monoxide (CO), elemental carbon (EC), organic carbon (OC), and ozone (O3), were obtained from the chemical speciation network (CSN) database. Over the study period, a general decrease was noted in the PNC of UFPs, NOx, EC, and OC, except for CO, the concentration trends of which did not exhibit a consistent pattern. UFPs, NOx, EC, and OC were positively correlated, while O3 had a negative correlation, especially with NOx. Our analysis discerned two distinct subperiods in pollutant trends: 2007-2015 and 2016-2022. For example, there was an overall decrease in the PNC of UFPs at an annual rate of -850.09 particles/cm3/year. This rate was more pronounced during the first sub-period (2007-2015) at -1814.9 particles/cm3/year and then slowed to -227.21 particles/cm3/year in the second sub-period (2016-2023). The first sub-period (2007-2015) significantly influenced pollutant level changes, exhibiting more pronounced and statistically significant changes than the second sub-period (2016-2022). Since 2016, almost all primary pollutants have stabilized, indicating a reduced impact of current regulations, and emphasizing the need for stricter standards. In addition, the study included an analysis of Vehicle Miles Traveled (VMT) trends from 2007 to 2022 within the Los Angeles Basin. Despite the general increase in VMT, current regulations and cleaner technologies seem to have successfully mitigated the potential increase in increase in PNC. Overall, while a decline in UFPs and co-pollutant levels was observed, the apparent stabilization of these levels underscores the need for more stringent regulatory measures and advanced emission standards.

The reduction of various nitrogen oxide (NOx) emissions from diesel engines is an important environmental issue due to their negative impact on air quality and public health. Selective catalytic reduction (SCR) has emerged as an effective technology to mitigate NOx emissions, but predicting the performance of SCR systems remains a challenge due to the complex chemistry involved. In this study, we propose using DNN models to predict NOx emission reductions in SCR systems. Four types of datasets were created; each consisted of five variables as inputs. We evaluated the models using experimental data collected from a diesel engine equipped with an SCR system. Our results indicated that the deep neural network (DNN) model produces precise estimates for exhaust gas temperature, NOx concentration, and De-NOx efficiency. Moreover, inclusion of additional input features, such as engine speed and temperature, improved the prediction accuracy of the DNN model. The mean absolute error (MAE) values for these parameters were 3.1 °C, 3.04 ppm, and 3.65%, respectively. Furthermore, the R-squared coefficient of determination values for the estimates were 0.912, 0.983, and 0.905, respectively. Overall, this study demonstrates the potential of using DNNs to accurately predict NOx emissions from diesel engines and provides insights into the impact of input features on the performance of the model.

Real Drive Emission (RDE) test with Portable Emission Measurement System (PEMS) is a widely adopted way to assess vehicle emission compliance. However, the current NOx emissions calculation method stipulated in the China VI emission standard easily ignores the NOx emissions during cold start and low-power operation. To study the effect of cold start and low-power operation on the calculation of NOx emissions in the PEMS test, in this study, a China VI Heavy-Duty Vehicle (HDV) for urban use was used to conduct PEMS tests under various vehicle payload conditions. The data analysis results show that the increase in vehicle payload is beneficial to reducing the specific NOx emissions and passing the NOx emission compliance test because the increased payload improves the NOx conversion efficiency of the SCR system. Cold start duration has no obvious relationship with vehicle payload, accounting for only about 4∼6% in each test, but contributing more than 30% of NOx emissions. Due to the effect of the power threshold and the 90th cumulative percentile, the cold start data has little influence on the result of the NOx emissions assessment and the maximum variation of the NOx emissions result in this study is an 8% rise. For the HDV for urban use, the variation of the power threshold resulting from vehicle payload is small, no more than 2% in this study. The presence of the power threshold makes almost only the low-power operation in the second half of urban driving have an impact on the NOx emissions calculation, which may make more than 50% of NOx emissions in the PEMS test be neglected. The impact of the low-power operation on NOx emissions calculation result will be significantly enhanced if all windows are considered in the Moving Average Window (MAW) method. In the meantime, the degree of variation is closely related to the NOx emissions level during the first half of urban driving. The maximum deterioration of NOx emission assessment result can be more than 90% in this study.

Rapid depletion of fossil fuels required the development of alternate and sustainable fuel sources that could replace conventional fuel while having no negative environmental impact. Combining hydrogen induction with biodiesel ensures strict emission standards and lowers energy consumption compared to conventional fuels. In this study, the performance, emissions, and combustion of a CI engine for Syzygium cumini (B20) were assessed and compared to diesel fuel while using a fixed amount of hydrogen flow rate (6L/m). Throughout the experiment, an exhaust gas recirculation (EGR) technology of 10% and 20% and a constant engine speed of 1500 rpm at varying engine load circumstances were used. When hydrogen is added to B20, it decrease the emissions of carbon monoxide (CO), unburned hydrocarbons (UHC), brake thermal efficiency (BTE), and brake specific energy consumption (BSEC). At maximum load, the use of the EGR system decreased the exhaust gas temperature (EGT) by 13.4% and nitrogen oxide (NOX) emission by 25%, but it had a negative impact on BTE, BSEC, as well as other emission parameters including CO and UHC. Therefore, using hydrogen in dual fuel mode in a CI engine enhances performance and lowers exhaust emissions, while using the EGR approach reduces NOX emissions.