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Ground and satellite observations show that air pollution regulations in the United States (US) have resulted in substantial reductions in emissions and corresponding improvements in air quality over the last several decades. However, large uncertainties remain in evaluating how recent regulations affect different emission sectors and pollutant trends. Here we show a significant slowdown in decreasing US emissions of nitrogen oxides (NOₓ) and carbon monoxide (CO) for 2011–2015 using satellite and surface measurements. This observed slowdown in emission reductions is significantly different from the trend expected using US Environmental Protection Agency (EPA) bottom-up inventories and impedes compliance with local and federal agency air-quality goals. We find that the difference between observations and EPA’s NOₓ emission estimates could be explained by: (i) growing relative contributions of industrial, area, and off-road sources, (ii) decreasing relative contributions of on-road gasoline, and (iii) slower than expected decreases in on-road diesel emissions.

China started to implement comprehensive measures to mitigate traffic pollution at the end of 1990s, but the comprehensive effects, especially on ambient air quality and public health, have not yet been systematically evaluated. In this study, we analyze the effects of vehicle emission control measures on ambient air pollution and associated deaths attributable to long-term exposures of fine particulate matter (PM2.5) and O₃ based on an integrated research framework that combines scenario analysis, air quality modeling, and population health risk assessment. We find that the total impact of these control measures was substantial. Vehicular emissions during 1998–2015 would have been 2–3 times as large as they actually were, had those measures not been implemented. The national population-weighted annual average concentrations of PM2.5 and O₃ in 2015 would have been higher by 11.7 μg/m³ and 8.3 parts per billion, respectively, and the number of deaths attributable to 2015 air pollution would have been higher by 510 thousand (95% confidence interval: 360 thousand to 730 thousand) without these controls. Our analysis shows a concentration of mortality impacts in densely populated urban areas, motivating local policymakers to design stringent vehicle emission control policies. The results imply that vehicle emission control will require policy designs that are more multifaceted than traditional controls, primarily represented by the strict emission standards, with careful consideration of the challenges in coordinated mitigation of both PM2.5 and O₃ in different regions, to sustain improvement in air quality and public health given continuing swift growth in China’s vehicle population.

Traffic-related sources have been recognized as a significant contributor of particulate matter particularly within major cities. Exhaust and non-exhaust traffic-related sources are estimated to contribute almost equally to traffic-related PM₁₀emissions. Non-exhaust particles can be generated either from non-exhaust sources such as brake, tyre, clutch and road surface wear or already exist in the form of deposited material at the roadside and become resuspended due to traffic-induced turbulence. Among non-exhaust sources, brake wear can be a significant particulate matter (PM) contributor, particularly within areas with high traffic density and braking frequency. Studies mention that in urban environments, brake wear can contribute up to 55 % by mass to total non-exhaust traffic-related PM₁₀emissions and up to 21 % by mass to total traffic-related PM₁₀emissions, while in freeways, this contribution is lower due to lower braking frequency. As exhaust emissions control become stricter, relative contributions of non-exhaust sources—and therefore brake wear—to traffic-related emissions will become more significant and will raise discussions on possible regulatory needs. The aim of the present literature review study is to present the state-of-the-art of the different aspects regarding PM resulting from brake wear and provide all the necessary information in terms of importance, physicochemical characteristics, emission factors and possible health effects.

Biodiesels have gained much popularity because they are cleaner alternative fuels and they can be used directly in diesel engines without modifications. In this paper, a brief review of the key studies pertaining to the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends, exhaust aftertreatment systems, and low-temperature combustion technology is presented. In general, most biodiesel blends result in a significant decrease in carbon monoxide and total unburned hydrocarbon emissions. There is also a decrease in carbon monoxide, nitrogen oxide, and total unburned hydrocarbon emissions while the engine performance increases for diesel engines fueled with biodiesels blended with nano-additives. The development of automotive technologies, such as exhaust gas recirculation systems and low-temperature combustion technology, also improves the thermal efficiency of diesel engines and reduces nitrogen oxide and particulate matter emissions.

This article deals with a unique, new powertrain diagnostics platform at the level of a large number of EU25 inspection stations. Implemented method uses emission measurement data and additional data from significant sample of vehicles. An original technique using machine learning that uses 9 static testing points (defined by constant engine load and constant engine speed), volume of engine combustion chamber, EURO emission standard category, engine condition state coefficient and actual mileage is applied. An example for dysfunction detection using exhaust emission analyses is described in detail. The test setup is also described, along with the procedure for data collection using a Mindsphere cloud data processing platform. Mindsphere is a core of the new Platform as a Service (Paas) for data processing from multiple testing facilities. An evaluation on a fleet level which used quantile regression method is implemented. In this phase of the research, real data was used, as well as data defined on the basis of knowledge of the manifestation of internal combustion engine defects. As a result of the application of the platform and the evaluation method, it is possible to classify combustion engine dysfunctions. These are defects that cannot be detected by self-diagnostic procedures for cars up to the EURO 6 level.

Increasing environmental concern, human health and the continuous upgradation in the stringent standards of vehicular emissions have shown much interest in cleaner diesel fuels. Out of various strategies to mitigate the diesel engine emissions, use of water blended diesel in the form of emulsion has grabbed sufficient attention of the fuel research community. Various researches have shown that water-emulsified diesel has sufficient potential to improve the engine performance simultaneously with a significant reduction in the levels of nitrogen oxides (NO x ) and particulate matter (PM) emissions. Micro-explosion phenomenon of combustion in emulsion fuel helps to provide efficient and complete combustion which in turn improves brake thermal efficiency. The current study presents a comprehensive review of the usage of water-emulsified diesel fuel in CI engines. Focusing on the performance, combustion, and emission analysis, it also talks in detail about the principle and the chemistry involved in making of a stable and homogeneous water–diesel emulsion compatible for CI engine. The literature survey concludes two crucial points. First, the water-blended diesel emulsion serves as an economical, fuel efficient, and cleaner combustion technology. Second, the optimum blend ratio, emulsifier quantity, and proper process differs in almost all the research papers and hence needed to be standardized.

Legal restrictions on vehicle engine exhaust gas emission control do not always go hand in hand with an actual reduction in the emissions of toxins into the atmosphere. Moreover, the methods currently used to measure exhaust gas emissions do not give unambiguous results on the impact of the tested gases on living organisms. The method used to assess the actual toxicity of gases, BAT-CELL Bio-Ambient-Tests using in vitro tests, takes into account synergistic interactions of individual components of a mixture of gases without the need to know its qualitative and quantitative composition and allows for determination of the actual toxicity of the gas composition. Using the BAT-CELL method, exhaust gases from passenger vehicles equipped with spark-ignition engines complying with the Euro 3 and Euro 6 emission standards were tested. The results of toxicological tests were correlated with the results of chromatographic analysis. It was shown that diverse qualitative composition of the mixture of hydrocarbons determining the exhaust gases toxicity may decrease the percentage value of cell survival. Additionally, it was proven that the average survival of cells after exposure to exhaust gases from tested vehicles meeting the more restrictive Euro 6 standard was lower than for vehicles meeting the Euro 3 standard thus indicating the higher toxicity of exhaust gases from newer vehicles.

The establishment of a non-road construction machinery emission inventory forms the basis for the analysis of pollutant emission characteristics and for the formulation of control policy. We analyzed and investigated data on populations, emission factors, and activity levels for the construction machinery in Tianjin to estimate an emission inventory. Finally, a variety of emission reduction scenarios were used to simulate emission reductions and propose the most effective control policy. The results show that total emissions of CO, HC, NOx, PM 10 , and PM 2.5 from non-road construction machinery in Tianjin of 2018 reached 4180.78, 951.44, 5833.85, 383.92, and 365.70 t, respectively. Forklifts, excavators, and loaders were the three most important emission sources in Tianjin. There are clear differences in the emissions of different districts. Large machinery emissions were mainly distributed across the Binhai New Area, which includes high volumes of port machinery and tractors in Tianjin Port. Based on various emission reduction scenarios, the effect of emission reductions is estimated. The IAD affected the reduction of CO and HC emissions with RR values of 17.6% and 17.3%, respectively, while EMO affected the mitigation of PM 10 and PM 2.5 emissions and RR values by 18.0% and 18.4%, respectively. The emission reduction control policy for non-road construction machinery is proposed, including the accelerated updating of non-road machinery emission standards; integrating diesel engine research and development institutions to accelerate the development of vehicle after-treatment technology; and establishing a cooperation mechanism for scientific research institutes, government departments, and enterprises in the control of non-road mobile machinery emissions.

Particulate matter (PM), and in particular ultrafine particles, have a negative impact on human health. The contribution of vehicle PM emissions to air pollution is typically quantified with emission inventories, which need vehicle emission factors as input. Heavy-duty vehicles, although they represent a small percentage of the vehicle population in nearly every major country, contribute the majority of the on-road PM emissions. However, the published data of modern heavy-duty vehicle emissions are scarce, and for the newest Euro VI technologies, almost non-existent. The main objective of this paper is to present Solid Particle Number (SPN) emission factors from Euro VI heavy-duty vehicles using diesel, Compressed Natural Gas (CNG), or Liquefied Natural Gas (LNG). Urban, rural and motorway (highway) emissions were determined on the road at various European cities using SPN Portable Emission Measurement Systems (PEMS). Additional tests on a heavy-duty chassis dynamometer showed that the solid sub-23 nm fraction, which is not covered at the moment in the European regulation, is high, especially for CNG engines. The significant contribution of regeneration events and the effect of ambient temperature and engine cold-start on particle emissions were also discussed.

In order to scientifically evaluate the characteristics and impact outcomes of transportation carbon emissions, this paper uses the panel statistics of 286 cities to measure transportation carbon emissions and analyze their spatial correlation characteristics. Afterwards, primarily based on the current research, a system of indicators for the impact factors of transportation carbon emissions was established. After that, ordinary least squares regression, geographically weighted regression, and multiscale geographically weighted regression models were used to evaluate and analyze the data, and the outcomes of the multiscale geographically weighted regression model were selected to analyze the spatial heterogeneity of the elements influencing transportation carbon emissions. The effects exhibit that: (1) The spatial characteristics of China's transportation carbon emissions demonstrate that emissions are high in the east, low in the west, high in the north, and low in the south, with high-value areas concentrated in the central cities of Beijing-Tianjin-Hebei, the Yangtze River Delta, the Guangdong-Hong Kong-Macao region, and the Chengdu-Chongqing regions, and the low values concentrated in the Western Sichuan region, Yunnan, Guizhou, Qinghai, and Gansu. (2) The spatial heterogeneity of transportation carbon emissions is on the rise, but the patten of local agglomeration is obvious, showing a clear high-high clustering, and the spatial distribution of high-high agglomeration and low-low agglomeration is positively correlated, with high-high agglomeration concentrated in the eastern region and low-low agglomeration concentrated in the western region. (3) The effects of three variables-namely, GDP per capita, vehicle ownership, and road mileage-have a predominantly positive effect on transportation carbon emissions within the study area, while another three variables-namely, constant term, population density, and number of people employed in transportation industry-have different mechanisms of influence in different regions. Constant term, vehicle ownership, and road mileage have greater impacts on transportation carbon emissions.