Real-world assessment of vehicle air pollutant emissions subset by vehicle type, fuel and EURO class: New findings from the recent UK EDAR field campaigns, and implications for emissions restricted zones

Mapping urban mobility using vehicle telematics to understand driving behaviour

Telematics data, primarily collected from on-board vehicle devices (OBDs), has been utilised in this study to generate a thorough understanding of driving behaviour. The urban case study area is the large metropolitan region of the West Midlands, UK, but the approach is generalizable and translatable to other global urban regions. The new approach of GeoSpatial and Temporal Mapping of Urban Mobility (GeoSTMUM) is used to convert telematics data into driving metrics, including the relative time the vehicle fleet spends idling, cruising, accelerating, and decelerating. The telematics data is also used to parameterize driving volatility and aggressiveness, which are key factors within road safety, which is a global issue. Two approaches to defining aggressive driving are applied and assessed, they are vehicle jerk (the second derivative of vehicle speed), and the profile of speed versus acceleration/deceleration. The telematics-based approach has a very high spatial resolution (15-150 m) and temporal resolution (2 h), which can be used to develop more accurate driving cycles. The approach allows for the determination of road segments with the highest potential for aggressive driving and highlights where additional safety measures could beneficially be adopted. Results highlight the strong correlation between vehicle road occupancy and aggressive driving.

Telematics data for geospatial and temporal mapping of urban mobility: Fuel consumption, and air pollutant and climate-forcing emissions of passenger cars

In this study, we use the approach of geospatial and temporal (GeoST) mapping of urban mobility to evaluate the speed-time-acceleration profile (dynamic status) of passenger cars. We then use a pre-developed model, fleet composition and real-world emission factor (EF) datasets to translate vehicles dynamics status into real-urban fuel consumption (FC) and exhaustive (CO2 and NOx) emissions with high spatial (15 m) and temporal (2 h) resolutions. Road transport in the West Midlands, UK, for 2016 and 2018 is the spatial and temporal scope of this study. Our approach enables the analysis of the influence of factors such as road slope, non-rush/rush hour and weed days/weekends effects on the characteristics of the transport environment. The results show that real-urban NOx EFs reduced by more than 14 % for 2016-18. This can be attributed to the increasing contribution of Euro 6 vehicles by 63 %, and the increasing contribution of diesel vehicles by 13 %. However, the variations in the real-urban FC and CO2 EFs are less significant (±2 %). We found that the FC estimated for driving under the NEDC (National European Driving Cycle) is a qualified benchmark for evaluating real-urban FCs. Considering the role of road slope increases the estimated real-urban FC, and NOx, and CO2 EFs by a weighted average of 4.8 %, 3.9 %, and 3.0 %, respectively. Time of travel (non-rush/rush hour or weed days/weekends) has a profound effect on vehicle fuel consumption and related emissions, with EFs increasing in more free-flowing conditions.

Diesel particulate filter regeneration mechanism of modern automobile engines and methods of reducing PM emissions: a review

Diesel particulate filter (DPF) is considered as an effective method to control particulate matter (PM) emissions from diesel engines, which is included in the mandatory installation list by more and more national/regional laws and regulations, such as CHINA VI, Euro VI, and EPA Tier3. Due to the limited capacity of DPF to contain PM, the manufacturer introduced a method of treating deposited PM by oxidation, which is called regeneration. This paper comprehensively summarizes the most advanced regeneration technology, including filter structure, new catalyst formula, accurate soot prediction, safe and reliable regeneration strategy, uncontrolled regeneration and its control methods. In addition, due to the change of working conditions in the regeneration process, the additional emissions during regeneration are discussed in this paper. The DPF is not only the aftertreatment device but also can be combined with diesel oxidation catalyst (DOC), selective catalytic reduction (SCR) and exhaust recirculation (EGR). In addition, the impact of DPF modification on the original system of some old models has been reasonably discussed in order to achieve emission targets.

Effect of carbonaceous components of biodiesel combustion particles on optical properties

This paper studies the influence of carbonaceous components on the optical properties of particulate matter (PM) in biodiesel combustion by conducting a bench test on an electronically controlled high-pressure common-rail diesel engine. In addition, the PM produced by the combustion of diesel oil, soybean oil methyl ester (SME), waste edible oil methyl ester (WME), and palm oil methyl ester (PME) was collected. The carbonaceous composition and optical properties of diesel and three biodiesel particulates were then analyzed. The obtained results showed that the ratio of organic carbon (OC) to total carbon (TC) in diesel PM was 0.25 and the ratio of OC/EC was 0.33. The OC to TC ratio of biodiesel PM was significantly greater than that of diesel PM, ranging between 0.59 and 0.65, with OC/EC values in the range of 1.44-1.86. The mass absorption cross-section (MAC) values of three kinds of biodiesel particles were all higher than those of diesel particles. When the incident laser wavelength increased, the difference of MAC values among four kinds of fuel particles gradually decreased. The MAC values of all the three biodiesel particles were higher than those of the diesel particles, and the difference between the MAC values of the four fuel particles gradually decreased with the increase of the incident laser wavelength. Afterwards, the "shell-core" model of particles was developed with 80 nm EC sphere as the core. At the two refractive indices, the scattering cross section, absorption cross section, and extinction cross section of the particles decrease with the increase of the incident light wavelength, and the scattering cross section, absorption cross section, and extinction cross section of the particles increase with the increase of the OC coating thickness.

Detecting high emitting vehicle subsets using emission remote sensing systems

It is often assumed that a small proportion of a given vehicle fleet produces a disproportionate amount of air pollution emissions. If true, policy actions to target the highly polluting section of the fleet could lead to significant improvements in air quality. In this paper, high-emitter vehicle subsets are defined and their contributions to the total fleet emission are assessed. A new approach, using enrichment factor in cumulative Pareto analysis is proposed for detecting high emitter vehicle subsets within the vehicle fleet. A large dataset (over 94,000 remote-sensing measurements) from five UK-based EDAR (emission detecting and reporting system) field campaigns for the years 2016-17 is used as the test data. In addition to discussions about the high emitter screening criteria, the data analysis procedure and future issues of implementation are discussed. The results show different high emitter trends dependent on the pollutant investigated, and the vehicle type investigated. For example, the analysis indicates that 23 % and 51 % of petrol and diesel cars were responsible for 80 % of NO emissions within that subset of the fleet, respectively. Overall, the contributions of vehicles that account for 80 % of total fleet emissions usually reduce with EURO class improvement, with the subset fleet emissions becoming more homogenous. The high emitter constituent was more noticeable for pollutant PM compared with the other gaseous pollutants, and it was also more prominent for petrol cars when compared to diesel ones.

Diesel-Biodiesel-Water Fuel Nanoemulsions for Direct Injection and Indirect Injection Diesel Engines: Performance and Emission Characteristics

An experimental research is assessed to examine the engine performance and exhaust emissions of direct injection (DI) and indirect injection diesel (IDI) engines fueled with petroleum diesel, biodiesel, and nanoemulsion fuel. The nanoemulsion fuel was produced using a hydrodynamic cavitation reactor. These three fuels were used to study the exhaust emissions, brake power, brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), and exhaust gas temperature at engine speeds ranging from 1100, 1400, 1700, 2000, and 2300 rpm with engine loads of 25, 50, and 75%. Furthermore, three fuels were burned in two types of combustion engines such as DI and IDI diesel engines under identical conditions. The finding showed that using DI and IDI engines influenced the magnitude of emissions as well as the performance with different speeds and loads. By comparing the performance of DI and IDI engines at a maximum engine load of 75%, the most concerning parameter among the efficiency of an engine of BTE of diesel, biodiesel, and nanoemulsion fuel from the DI engine was higher at 24.19, 24.83, and 20.76%, respectively, than that of the IDI engine at 2300 rpm engine speed. At the maximum load and speed of engines, the BSFC of diesel, biodiesel, and nanoemulsion fuel in the DI engine were 4.44, 23.73, and 20% lower than in the IDI engine, respectively. Emission results of the DI and IDI engines were analyzed at 75% load and 2300 rpm speed. The results demonstrated that emissions of NO _x from nanoemulsion fuel from the IDI engine was significantly reduced by 82.46% when the values were compared to the DI engine. In terms of CO emissions, the IDI engine emits significantly less than the DI diesel engine. The CO emissions of diesel, biodiesel, and nanoemulsion fuel in the IDI engine were 69.02, 28.95, and 48.75% lower than those in the DI engine, respectively. The studies conclude that the emissions from IDI engines clearly show that pollution from exhaust emissions can be reduced to a low level compared to the DI engine. However, when high-performance engines are considered, the DI engine is recommended rather than the IDI engine.

A prospective study to evaluate CO2 emission mitigation strategies for highway transportation

Ranking as one of the largest mobility modes for passengers and freight, highway transportation globally accounts for huge amounts of fossil-based energy consumption and greenhouse gas emissions. Correspondingly, on-road transportation causes detrimental effects on air quality, climate change, and global warming, particularly over the short term. In order to prevent a further escalation of this detrimental environmental issue, long-term efficacious policies aimed at reducing the transportation-driven CO₂ emission should be urgently enacted and implemented on a global scale. Thus, this paper presents an exploratory study with the main objective of investigating the impact of four adopted mitigation scenarios that suggest switching to Euro 6 vehicle emission standards, increasing the average urban traffic speed limits, encouraging public transport, and increasing the proportion of hybrid electric vehicles. This study then compared and contrasted each strategy and its subgroups with a reference scenario projected for the year 2025. The evidence from this research showed that transition to Euro 6 compliant vehicles significantly decarbonizes the transportation sector, yet more vehicle electrification is required to achieve the Paris Climate Agreement targets. The results also indicate that by 2025, a 10% shift from passenger cars to public transport will decrease CO₂ emissions by 3%, whilst increasing the urban traffic speed by 10 km/h will yield a 1.38% CO₂ gas emission saving.

Long-Term In-Use NOx Emissions from London Buses with Retrofitted NOx Aftertreatment

Buses constitute a significant source of air pollutant emissions in cities. In this study, we present real-world NO_x emissions from 97 diesel-hybrid buses measured using on-board diagnostic systems over 44 months and 6.35 million km in London. Each bus had previously been retrofitted with a selective catalytic reduction (SCR) aftertreatment system to reduce emissions of nitrogen oxides (NO_x). On average, parallel hybrid (PH) and series hybrid (SH) buses emitted 3.80 g of NO_x/km [standard deviation (SD) of 1.02] and 2.37 g of NO_x/km (SD of 0.51), respectively. The SCR systems reduced engine-out emissions by 79.8% (SD of 5.0) and 87.2% (SD of 2.9) for the PHs and SHs, respectively. Lower ambient temperatures (0-10 °C) increased NO_x emissions of the PHs by 24.2% but decreased NO_x emissions of the SHs by 27.9% compared to values found at more moderate temperatures (10-20 °C). To improve emissions inventories, we provide new distance-based NO_x emissions factors for different ranges of ambient temperature. During the COVID-19 pandemic, the emissions benefits of reduced congestion were largely offset by more frequent route layovers leading to lower SCR temperatures and effectiveness. This study shows that continuous in-service measurements enable quantification of real-world vehicle emissions over a wide range of operations that complements conventional testing approaches.

Empirical estimation and analysis of total carbon emission quota based on carbon transfer-embedded import and export trade

Based on the input-output table and considering the terms of import and export trade at the national level, this paper calculates China's annual direct carbon emissions and total carbon emissions from 2005 to 2015. On the one hand, the actual direct carbon emissions and actual complete carbon emissions at the national level are calculated by MRIO model; on the other hand, according to the 5-year emission reduction targets set in the Eleventh Five-Year Plan and the outline document of the Twelfth Five-Year Plan, the emission reduction targets for each year are determined by equal distribution over the years. Hence, the annual carbon intensity emission reduction targets for 2006-2010 and 2011-2015 can be determined to be 4% and 3.4%, respectively, to calculate the target direct carbon emissions and target goal for complete carbon emissions. The smaller of the two is taken as the total quota. Taking 2015 as an example, the total direct carbon quota and complete carbon quota calculated are 87.87 million tons and 71.85 million tons, respectively, which is the total amount to be allocated for inter-provincial direct carbon quota and inter-provincial complete carbon quota. Findings of the study hold pivotal implications for policy development.

Quantitative of instantaneous BC emissions based on vehicle specific power from real-world driving diesel trucks in China

In-depth exploration of the potential links between instantaneous black carbon (BC) emissions and driving parameters from real-world diesel trucks (DTs) is a key step toward development of a highly flexible vehicle emissions estimation system. In this study, we conducted real-world measurements on 22 DTs with mainstream types and emission standards, and obtained instantaneous data of BC emissions and vehicle driving. Since vehicle specific power (VSP) is an excellent surrogate for engine load, we characterize the instantaneous BC emissions and VSP distributions, and then establish links between VSP and fuel consumption, VSP and BC emission rates, VSP and BC emission factors (EFs), respectively. We find that BC emission rates of China V light-duty DTs installed with diesel particulate filter (DPF) are significantly lower (2 to 3 orders of magnitude) than those with China III and China IV. Frequent acceleration and deceleration of vehicles maybe the main reason leads to high BC emissions. The distribution of VSP is mainly concentrated in the ranges of -30 to 35 kW/t in the scope of this study. We find that VSP and BC EFs did not show a consistent pattern for all tested DTs, and BC EFs present obvious fluctuations with the VSP variation. The average fuel-based BC EFs vary by factors of 2.27-8.25 from the lowest to highest EFs. Through a fitting of the third-order polynomial function, we finally quantify and provide fitting formulas of BC EFs and VSP under more detailed categorization. Our results can provide important data support for accurate quantification of BC EFs, and even emission inventory calculations.

Impacts of emergency health protection measures upon air quality, traffic and public health: evidence from Oxford, UK

Emergency responses to the COVID-19 pandemic led to major changes in travel behaviours and economic activities in 2020. Machine learning provides a reliable approach for assessing the contribution of these changes to air quality. This study investigates impacts of health protection measures upon air pollution and traffic emissions and estimates health and economic impacts arising from these changes during two national 'lockdown' periods in Oxford, UK. Air quality improvements were most marked during the first lockdown with reductions in observed NO₂ concentrations of 38% (SD ± 24.0%) at roadside and 17% (SD ± 5.4%) at urban background locations. Observed changes in PM_2.5, PM₁₀ and O₃ concentrations were not significant during first or second lockdown. Deweathering and detrending analyses revealed a 22% (SD ± 4.4%) reduction in roadside NO₂ and 2% (SD ± 7.1%) at urban background with no significant changes in the second lockdown. Deweathered-detrended PM_2.5 and O₃ concentration changes were not significant, but PM₁₀ increased in the second lockdown only. City centre traffic volume reduced by 69% and 38% in the first and second lockdown periods. Buses and passenger cars were the major contributors to NO₂ emissions, with relative reductions of 56% and 77% respectively during the first lockdown, and less pronounced changes in the second lockdown. While car and bus NO₂ emissions decreased during both lockdown periods, the overall contribution from buses increased relative to cars in the second lockdown. Sustained NO₂ emissions reduction consistent with the first lockdown could prevent 48 lost life-years among the city population, with economic benefits of up to £2.5 million. Our findings highlight the critical importance of decoupling emissions changes from meteorological influences to avoid overestimation of lockdown impacts and indicate targeted emissions control measures will be the most effective strategy for achieving air quality and public health benefits in this setting.

Long-term trends in nitrogen oxides concentrations and on-road vehicle emission factors in Copenhagen, London and Stockholm

Road transport is the main anthropogenic source of NOx in Europe, affecting human health and ecosystems. Thus, mitigation policies have been implemented to reduce on-road vehicle emissions, particularly through the Euro standard limits. To evaluate the effectiveness of these policies, we calculated NO₂ and NOx concentration trends using air quality and meteorological measurements conducted in three European cities over 26 years. These data were also employed to estimate the trends in NOx emission factors (EF_NOx, based on inverse dispersion modeling) and NO₂:NOx emission ratios for the vehicle fleets under real-world driving conditions. In the period 1998-2017, Copenhagen and Stockholm showed large reductions in both the urban background NOx concentrations (-2.1 and -2.6% yr^-1, respectively) and EF_NOx at curbside sites (68 and 43%, respectively), proving the success of the Euro standards in diminishing NOx emissions. London presented a modest decrease in urban background NOx concentrations (-1.3% yr^-1), while EF_NOx remained rather constant at the curbside site (Marylebone Road) due to the increase in public bus traffic. NO₂ primary emissions -that are not regulated- increased until 2008-2010, which also reflected in the ambient concentrations. This increase was associated with a strong dieselization process and the introduction of new after-treatment technologies that targeted the emission reduction of other species (e.g., greenhouse gases or particulate matter). Thus, while regulations on ambient concentrations of specific species have positive effects on human health, the overall outcomes should be considered before widely adopting them. Emission inventories for the on-road transportation sector should include EF_NOx derived from real-world measurements, particularly in urban settings.

Determination of local traffic emission and non-local background source contribution to on-road air pollution using fixed-route mobile air sensor network

Traffic-related air pollutants are major contributors to deteriorating urban air quality and pose a serious threat to pedestrians. From both a scientific and a regulatory standpoint, it is important and challenging to understand the contributions of local and non-local sources to accurately apportion specific sources such as traffic emissions contribution to on-road and near-road microenvironment air quality. In this study, we deployed mobile sensors on-board buses to monitor NO, NO₂, CO and PM_2.5 along ten important routes in Hong Kong. The measurements include two seasons: April 2017 and July 2017. Two types of baseline extraction methods were evaluated and applied to separate local and background concentrations. The results show NO and NO₂ are locally dominated air pollutants in spring, constituting 72%-84% and 58%-71%, respectively, with large inter-road variation. PM_2.5 and CO largely arise from background sources, which contribute 55%-65% and 73%-79% respectively. PM_2.5 displays a homogeneous spatial pattern, and the contributions show seasonal change, decreasing during summer. Regional transport pollution is the primary contributor during high pollution episodes. Isolated vehicle plumes show highly skewed concentration distributions. There are characteristic polluted segments on routes and they are most evident at rush hours. The most polluted road segments (top 10%) cluster at tunnel entrances and congested points. Some of these polluted locations were observed in Hong Kong's Low Emission Zones and suggest limitations to the existing control strategies, which only address larger buses. Our work gives new insights in the importance of regional cooperation to improve background air pollution combined with local control strategies to improve roadside air quality in Hong Kong.

Emissions and light absorption of carbonaceous aerosols from on-road vehicles in an urban tunnel in south China

With changing numbers, compositions, emission standards and fuel quality of on-road vehicles, it is imperative to accordingly characterize and update vehicular emissions of carbonaceous aerosols for better understanding their health and climatic effects. In this study, a 7-day field campaign was conducted in 2019 in a busy urban tunnel (>30,000 vehicles day^-1) in south China with filter-based aerosol samples collected every 2 h at both the inlet and the outlet for measuring carbonaceous aerosols and their light absorbing properties. Observed fleet average emission factor (EF) of total carbon (TC) was 13.4 ± 8.3 mg veh^-1 km^-1, and 17.4 ± 11.3 mg veh^-1 km^-1 if electric and LPG-driven vehicles were excluded; and fleet average EF of organic carbon (OC) and elemental carbon (EC) was 8.5 ± 6.6 and 4.9 ± 2.6 mg veh^-1 km^-1 (11.0 ± 8.8 and 6.3 ± 3.6 mg veh^-1 km^-1 if excluding electric and LPG vehicles), respectively. Regression analysis revealed an average TC-EF of 319.8 mg veh^-1 km^-1 for diesel vehicles and 2.1 mg veh^-1 km^-1 for gasoline vehicles, and although diesel vehicles only shared ~4% in the fleet compositions, they still dominate on-road vehicular carbonaceous aerosol emissions due to their over 150 times higher average TC-EF than gasoline vehicles. Filter-based light absorption measurement demonstrated that on average brown carbon (BrC) could account for 19.1% of the total carbonaceous light absorption at 405 nm, and the average mass absorption efficiency of EC at 635 nm and that of OC at 405 nm were 5.2 m² g^-1 C and 1.0 m² g^-1 C, respectively.

A comparison of light-duty vehicles' high emitters fractions obtained from an emission remote sensing campaign and emission inspection program for policy recommendation

Urban transportation is one of the leading causes of air pollution in big cities. In-use emissions of vehicles are higher than the emission control certification levels. The current study uses a roadside remote sensing emission monitoring campaign to investigate (a) fraction of high emitters in the light-duty vehicle (LDV) fleet and their contributions to the total emissions, (b) emission inspection (I/M) programs' effectiveness, and (c) alternate fuel (natural gas) encouragement policy. LDVs consist of passenger or freight transport vehicles with four wheels equivalent to classes M1 and N1 of European union vehicle classifications. The motivation is to assess the current emission inspection program's success rate and study the impact of the increased natural gas vehicle market share policy. It is also meant to present and validate remote sensing as a possible backup method to the current I/M program. The emission remote sensing campaign was conducted to measure emissions of CO, HC, and NO of the LDV fleet. Fleet age, engine size, and fuel type (gasoline or natural gas) were extracted and correlated with emissions. It was found that CO and HC emissions are five times higher for cars more than fifteen years old of age compared to those less than five years old. Analyses of high-emitters showed that almost 20% of the fleet were high-emitters and responsible for roughly half of CO, HC, and NO emissions. The correlation between the I/M program and the remote sensing to identify high-emitters was weak. Which indicates the need for an improved I/M program. It shows that even a limited remote sensing campaign is beneficial as a complementary monitoring tool to the I/M program. The study showed the same fraction of high-emitters in natural gas (methane) vehicles, despite the national policies to increase natural gas vehicle fraction in the market for reduced emissions.

Increased ozone pollution alongside reduced nitrogen dioxide concentrations during Vienna's first COVID-19 lockdown: Significance for air quality management

BACKGROUND

Lockdowns amid the COVID-19 pandemic have offered a real-world opportunity to better understand air quality responses to previously unseen anthropogenic emission reductions.

METHODS AND MAIN OBJECTIVE

This work examines the impact of Vienna's first lockdown on ground-level concentrations of nitrogen dioxide (NO₂), ozone (O₃) and total oxidant (O_x). The analysis runs over January to September 2020 and considers business as usual scenarios created with machine learning models to provide a baseline for robustly diagnosing lockdown-related air quality changes. Models were also developed to normalise the air pollutant time series, enabling facilitated intervention assessment.

CORE FINDINGS

NO₂ concentrations were on average -20.1% [13.7-30.4%] lower during the lockdown. However, this benefit was offset by amplified O₃ pollution of +8.5% [3.7-11.0%] in the same period. The consistency in the direction of change indicates that the NO₂ reductions and O₃ increases were ubiquitous over Vienna. O_x concentrations increased slightly by +4.3% [1.8-6.4%], suggesting that a significant part of the drops in NO₂ was compensated by gains in O₃. Accordingly, 82% of lockdown days with lowered NO₂ were accompanied by 81% of days with amplified O₃. The recovery shapes of the pollutant concentrations were depicted and discussed. The business as usual-related outcomes were broadly consistent with the patterns outlined by the normalised time series. These findings allowed to argue further that the detected changes in air quality were of anthropogenic and not of meteorological reason. Pollutant changes on the machine learning baseline revealed that the impact of the lockdown on urban air quality were lower than the raw measurements show. Besides, measured traffic drops in major Austrian roads were more significant for light-duty than for heavy-duty vehicles. It was also noted that the use of mobility reports based on cell phone movement as activity data can overestimate the reduction of emissions for the road transport sector, particularly for heavy-duty vehicles. As heavy-duty vehicles can make up a large fraction of the fleet emissions of nitrogen oxides, the change in the volume of these vehicles on the roads may be the main driver to explain the change in NO₂ concentrations.

INTERPRETATION AND IMPLICATIONS

A probable future with emissions of volatile organic compounds (VOCs) dropping slower than emissions of nitrogen oxides could risk worsened urban O₃ pollution under a VOC-limited photochemical regime. More holistic policies will be needed to achieve improved air quality levels across different regions and criteria pollutants.

Real-World Contribution of Electrification and Replacement Scenarios to the Fleet Emissions in West Midland Boroughs, UK

This study reports the likely real-world effects of fleet replacement with electric vehicles (EVs) and higher efficiency EURO 6 vehicles on the exhaustive emissions of NOx, PM, and CO2 in the seven boroughs of the West Midlands (WM) region, UK. National fleet composition data, local EURO distributions, and traffic compositions were used to project vehicle fleet compositions for different roads in each borough. A large dataset of real-world emission factors including over 90,000 remote-sensing measurements, obtained from remote sensing campaigns in five UK cities, was used to parameterize the emission profiles of the studied scenarios. Results show that adoption of the fleet electrification approach would have the highest emission reduction potential on urban roads in WM boroughs. It would result in maximum reductions ranging from 35.0 to 37.9%, 44.3 to 48.3%, and 46.9 to 50.3% for NOx, PM, and CO2, respectively. In comparison, the EURO 6 replacement fleet scenario would lead to reductions ranging from 10.0 to 10.4%, 4.0 to 4.2%, and 6.0 to 6.4% for NOx, PM, and CO2, respectively. The studied mitigation scenarios have higher efficacies on motorways compared to rural and urban roads because of the differences in traffic fleet composition. The findings presented will help policymakers choose climate and air quality mitigation strategies.

Quantification of Non-Exhaust Particulate Matter Traffic Emissions and the Impact of COVID-19 Lockdown at London Marylebone Road

This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data were used to determine the traffic increment (roadside–background) and covered a range of meteorological conditions, seasons, and driving styles, as well as the influence of the COVID-19 “lockdown” on non-exhaust concentrations. Non-exhaust particulate matter (PM)10 concentrations were calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc), and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 “dilution approach”. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicate that non-exhaust emission factors were dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds, and meteorological conditions, as well as advanced source apportionment of the PM measurement data, were undertaken to enhance our understanding of these important vehicle sources.

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns

The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (O x = NO2 + O3) showed limited change, and PM2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.