Actual Emission Research Articles

Deep Learning to Evaluate US NOx Emissions Using Surface Ozone Predictions

AbstractEmissions of nitrogen oxides (NOx = NO + NO2) in the United States have declined significantly during the past three decades. However, satellite observations since 2009 indicate total column NO2 is no longer declining even as bottom‐up inventories suggest continued decline in emissions. Multiple explanations have been proposed for this discrepancy including (a) the increasing relative importance of nonurban NOx to total column NO2, (b) differences between background and urban NOx lifetimes, and (c) that the actual NOx emissions are declining more slowly after 2009. Here, we use a deep learning model trained by NOx emissions and surface observations of ozone to assess consistency between the reported NOx trends between 2005 and 2014 and observations of surface ozone. We find that the satellite‐derived trends best reproduce ozone in low NOx emission (background) regions. The 2010–2014 trend from older satellite‐derived emission estimates produced at low spatial resolution results in the largest bias in surface ozone in regions with high NOx emissions, reflecting the blending of urban and background NOx in these low‐resolution top‐down analyses. In contrast, the trend from higher resolution satellite‐based estimates, which are more capable of capturing the urban emission signature, is in better agreement with ozone in high NOx emission regions, and is consistent with the trend based on surface observations of NO2. Our results confirm that the satellite‐derived trends reflect anthropogenic and background influences.

Modeling and Analysis of Acoustic Emission Generated by Fatigue Cracking

The acoustic emission (AE) method is a popular and well-developed method for passive structural health monitoring of metallic and composite structures. The current study focuses on the analysis of one of its processes, sound source or signal propagation. This paper discusses the principle of plate wave signal sensing using piezoelectric transducers, and derives an analytical expression for the response of piezoelectric transducers under the action of stress waves, to obtain an overall mathematical model of the acoustic emission signal from generation to reception. The acoustic emission caused by fatigue crack extension is simulated by a finite element method, and the actual acoustic emission signal is simulated by a pencil lead break experiment. The results predicted by the mathematical model are compared with the experimental results and the simulation results, respectively, and show good agreement. In addition, the presence of obvious S0 mode Lamb waves is observed in the simulation results and experimental results, which further verifies the correctness of the analytical model prediction.

How social movements contribute to staying within the global carbon budget: Evidence from a qualitative meta-analysis of case studies

Despite renewed efforts to combat climate change, it remains uncertain how economies will achieve emission reduction by 2050. Among different decarbonisation strategies, knowledge about the potential role and contributions of social movements to curbing carbon emissions has been limited. This study aims to shed light on the diverse contributions of social movements to staying within the global carbon budget, as well as on the specific outcomes and strategies employed in protests against hydrocarbon activities. For this purpose, we conduct a systematic literature review of 57 empirical cases of social movements contesting fossil fuel projects in 29 countries. Based on an exploratory approach, we identify a series of different movement strategies and a range of qualitative contributions that support staying within the carbon budget. These include raising awareness of risks and strategies, enhancing corporate responsibility, being informed about policy changes, laws and regulations, fostering just energy transitions, energy democracy, divestment, alternative market solutions, and forcing the postponement or cancellation of targeted hydrocarbon activities. While the institutional means are widely used and seem to support policy change and regulation, these strategies are not used to deliver awareness or postponement outcomes. Similarly, while movements tend to rely on civil disobedience to stop hydrocarbon projects in the short term, they rely on multiple strategies to cancel them in the longer term. Our study also indicates significant knowledge gaps in the literature, particularly, cases in Africa and Central Asia, women's participation in these movements, in addition to more quantitative assessments of the actual emissions reduced by social movements.

Application of Murphy – Good Plot Parameters Extraction Method on Electron Emission from Carbon Fibers

The significance of the Fowler-Nordheim-type plots lies in the possibility of extracting useful and reliable physical parameters of the field electron emitters. This is achieved by the parameter's extraction methods. We report on the application of two parameters extraction methods on field emission data from bundles of carbon fibers (CFs) grouped in nickel tubes and operated inside a typical field emission microscope setup. These methods are the Murphy-Good plot and the conventional Fowler-Nordheim plot iterative method. The physical parameters include the area extraction parameter, the notional (actual) emission area, the formal area efficiency factor and the voltage conversion length. The results obtained from the two methods are discussed and compared to shed light on the controversial nature of these methods. The mechanism of field electron emission is analyzed based on the parameters extracted.

A new perspective for understanding actual anthropogenic heat emissions from buildings

The magnitude and timing of heat emissions from buildings can be substantially different than the corresponding energy consumption profile. Indeed, the definition of anthropogenic heat needs rethinking if our goal is to understand the role of buildings in heating of the urban environment, and to identify opportunities to reduce that heating. Here, we introduce a new definition of anthropogenic heat emissions from buildings. Specifically, we contend that a more useful definition must compare total sensible heat emissions from a building and its surrounding land with the emissions that would have been generated from the same land without a building. This definition includes convection from all building surfaces, heat emissions from the building air conditioning system, and infiltration/exfiltration of heat. It also considers shading of other buildings and the ground surface. The proposed framework is intended not to replace existing waste heat emissions approaches within atmospheric models, but rather to provide a separate approach for truly understanding the role of building construction, materials, and operations in affecting the urban environment. We implement this framework through urban building energy model simulations to estimate the actual hourly profiles of anthropogenic heat from an archetype office building of 3 different heights in four US cities in varied climate regions. In the summer season, 6 story buildings are responsible for a sensible heating of the environment that is three to four times the magnitude of their energy use. For 2 story buildings 62 to 69% of this sensible heating in summer is due to convection from the roof surface alone, while less than 29% is due to waste heat from air conditioning systems. So, the rooftop surface is twice as important as the building energy use in determining the extent to which a building warms the surrounding environment. These results demonstrate the flawed nature of thinking of anthropogenic heat from buildings solely from the perspective of energy use or emissions from heating and cooling equipment. The proposed framework is of crucial importance in understanding how buildings affect their surrounding thermal environments. Ultimately, it can inform strategies to mitigate heat emissions as it quantifies the role of façade and rooftop construction materials and their thermal and radiative properties.

Long-term PM2.5 source analyses in New York City from the perspective of dispersion normalized PMF

Receptor models like positive matric factorization (PMF) have been widely used in atmospheric studies for source identification and quantification. However, one of the issues with ambient air pollution data used in those analyses is that the concentrations result from a combination of emission/formation rates and meteorological dispersion. Dispersion normalized PMF (DN-PMF) was recently developed to reduce the influence of dilution on source resolution. Studies have shown its capability to better reflect actual emission rates and yield more interpretable results for hourly integrated ambient data for particulate matter and particle number size distributions. In this study, conventional and DN-PMF were used to deconvolute long-term 24-h integrated speciated PM2.5 data sets, for the first time, for three urban sites in the NYC metropolitan area. DN-PMF using 24-h integrated data does not provide much improvement over DN-PMF using hourly integrated data since averaging over 24 h loses the strong diel dispersion patterns. However, it provides improved seasonal patterns for different sources that are lost with conventional PMF results. DN-PMF implements necessary corrections to the conventional PMF approach, and makes better use of the chemical monitoring data that generally have lower time resolution.

Assessing the potential for unaccounted emissions from bioenergy and the implications for forests: The United States and global

AbstractDevelopment of the bioenergy sector is being actively pursued in many countries as a means to reduce climate change and fulfill international climate agreements such as the Paris Agreement. Although biomass for energy production (especially wood pellets) can replace carbon‐intensive fossil fuels, its net greenhouse gas impact varies, and the production of wood pellets can also lead to intensification in forest harvests and reduction of forest carbon stocks. Additionally, under specific conditions, emissions associated with imported biomass feedstocks may be omitted from national accounts, due to incompatibilities in accounting approaches. We assessed the risks and potential scale of emissions omitted from accounts (EOA) among key trading regions, focusing on the demand for wood pellets under different levels of climate mitigation targets. Our results suggest that the global production of wood pellets would grow from 38.9 to 120 Mton/year between 2019 and 2050 in a scenario that limits global mean temperature increase to 1.5°C above pre‐industrial levels. A large portion of this occurs in North America (36.8 Mton/year by 2050), Europe (47.6 Mton/year by 2050), and Asia (23.3 Mton/year by 2050). We estimate that in a 1.5°C scenario, global EOA associated with international trade of wood pellets has the potential to reach 23.81 MtCO2eq/year by 2030 and 69.52 MtCO2eq/year in 2050. Emissions resulting from European biomass energy production, based on wood pellet imports from the United States, may reach 11.68 MtCO2eq/year by 2030 and 33.57 MtCO2eq/year in 2050. The production of wood pellet feedstocks may also present a substantial carbon price arbitrage opportunity for bioenergy producers through a conjunction of two distinct GHG accounting rules. If this opportunity is realized, it could accelerate the growth of the bioenergy industry to levels that harm forests’ function as a carbon sink and omit actual emissions in national and global accounting frameworks.

A review and evaluation of nonroad diesel mobile machinery emission control in China

China's emission control for nonroad diesel mobile machinery (NDMM) must deal with a fast increase in stock as well as regulations that are two decades behind those for on-road vehicles. This study provides the first large-scale review and evaluation of China's NDMM policies, along with emission measurements and an investigation on diesel fuel quality. The sulfur contents of the investigated diesel declined from 430 ppm (median value) in 2011 to 6-8 ppm during the 2017-2018 period. The emission control of NOx and PM greatly improved with the shift from the China II to China IV standards, as demonstrated by engine tests and field NOx measurements. However, the NOx emission factors for non-type-approved engines were approximately twice the limits of the China II standards. Emission compliance based on bench tests was not sufficient to control actual emissions because the field-measured NOx emission factors of all machinery ranged from 24% to 225% greater than the respective emission limits for the engines. These circumstances adversely affected the effectiveness of the regulations and policies for China's emission control of NDMM. Nevertheless, the policies on new and in-use NDMM, as well as diesel fuel quality, prevented NOx and PM emissions amounting to 4.4 Tg and 297.8 Gg during the period 2008-2017, respectively. The emission management strategy contributed to enhancing the international competitiveness of China's NDMM industries by promoting advanced technologies. For effective NDMM emission control in the future, portable testing and noncontact remote supervision should be strengthened; also, the issue of noncompliant diesel should be addressed through rigorous control measures and financial penalties.

УДОСКОНАЛЕННЯ ДІЮЧОЇ СИСТЕМИ СПОСТЕРЕЖЕНЬ ЗА ЯКІСТЮ АТМОСФЕРНОГО ПОВІТРЯ В М. КИЄВІ У ВІДПОВІДНОСТІ ДО ВИМОГ ЄС

The paper is dedicated to the problems of the current system for atmospheric air quality monitoring which is operated by the national hydrometeorological service of Ukraine in Kyiv. The problems are discussed in the context of implementing the Directives of the European Parliament and the Council on ambient air quality. The improvement of the current monitoring system needs immediate solutions due to the nonconformity to modern requirements not only in Kyiv, but also on the entire Ukrainian territory. The study makes an attempt to define the main steps of network improvement and the optimization of air pollution measurement network using air pollution data from the archives of the Central Geophysical Observatory, pollutants’ emission, land-use/land cover and meteorological data for 2000-2019. We discuss main EU requirements for monitoring sites’ location, atmospheric air pollution and emission data. The analysis showed the necessity for preliminary urban field measurements before the establishment of monitoring sites. Depending on the wind regime, the new measurement network must take into account the prevailing synoptic processes for future understanding how air pollution is transported towards and outwards the urban area. Land-use/ land cover data derived from the Landsat allowed distinguishing residential areas, industrial zones, main roads, water bodies and green areas which is crucial for the selection of suitable places for monitoring sites. Using mentioned principles and requirements, we propose 15 monitoring sites for the improved air quality network in Kyiv. This number of sites are greater than EU Directives claimed because conclusions were made on theoretical estimations without field measurements. The presented list of the monitoring sites needs additional analysis of spatio-temporal pollutants’ distribution in combination with atmospheric modelling. However, the analysis considers actual residential areas and emission sources in the background of the modern wind regime in Kyiv.

Real Driving Emissions Evaluation for A Heavy Duty Diesel Vehicle based on Engine-in-the-loop Methodology

Real driving emissions of a heavy-duty vehicle with a maximum total mass of 18000 kg were investigated by the engine-in-the-loop (EIL) methodology. Virtual vehicle model, driver model and real road model was established, then to combined with the actual engine and emission test equipment to fulfill the vehicle emission evaluation on engine test bed. The results indicate the road driving can be well reproduced on engine laboratory with good vehicle speed followability, engine speed and torque consistence. However, the emission results show a larger difference with a 3.6 gap for CO2, a 72.3% gap for NOx and a 40% gap for PN., respectively. Analysis shows that the intercooler temperature, the exhaust temperature and equipment difference has a combined effect on the emission accuracy.

DEVELOPMENT OF EMISSION INTENSITY FACTORS FOR A SOUTH AFRICAN ROAD-FREIGHT LOGISTICS SERVICE PROVIDER

The Global Logistics Emissions Council (GLEC) framework developed logistics emission factors to be used uniformly in North America and Europe. It included an approximation for African countries; however, actual South African emissions were not accurately reflected. Therefore, in this study, carbon emissions factors were calculated using calculated tonne-kilometres and the energy-based methodology. The authors obtained several datasets from a logistics service provider (LSP) consisting of vehicle routes, refuelling data, and freight load data. The project developed factors for each individual trip, for similar repetitive trips, and for the entire data set. These different sets of factors were developed to allow the use of different emission calculation and reporting standards. The LSP could use these emission intensity factors to estimate carbon emissions using the activity-based approach, report emissions according to legislation, and predict how much carbon emissions would be emitted to move a customer’s shipment. Keywords carbon emissions; emission intensity factor; logistics service providers; road freight; road transport; South Africa

Підвищення ролі будівельної галузі у сповільненні глобального потепління

The work reveals the current state of problems related to the growth of emissions greenhouse gases and environmental temperature due to excessive burning of fossil fuels (oil, coal, natural gas). The analysis of the implementation of the European experience is given introduction of taxation of carbon dioxide emissions, which had a positive effect on sales energy saving and reduction of greenhouse gas emissions. It is shown that the G20 countries account for 78 % of global greenhouse gas emissions, therefore they play a critical role in global mitigation efforts climatic changes. Indicators of Ukraine’s actual global carbon dioxide emissions and international obligations to reduce them and achieve climate neutrality are presented. The potential consequences for the country’s economy of the implementation of the cross-border mechanism have been revealed carbon border adjustment mechanism (Carbon Border Adjustment Mechanism — CBAM), a comparative analysis of taxes on greenhouse gas emissions in Ukraine and other countries is given. There have been generalized modern methods of utilization of carbon dioxide by its use in technologies for the production of cement concrete, fuel and other materials. The construction industry consumes up to 40 % of all energy carriers used in the country has huge reserves of saving energy resources. It is shown that it is an effective solution reducing greenhouse gas emissions and increasing global temperature remains implementation of low-clinker cement, non-metallic construction materials technology fittings Planting bushes, trees, landscaping walls and roofs, parking lots remain a recognized direction of landscape design and serve as a natural mechanism improvement of ecology. It is shown that the reduction plays a decisive role in the reduction of global warming the use of fossil fuels with subsequent abandonment of them in favor of RES. Expansion of the use of pellets for heating, implementation of green standards for new construction and insulation of the outdated housing stock will contribute to the reduction of energy consumption in construction.

Accounting for the carbon emissions from domestic air routes in China

This study seeks to build a database of China's 413 main routes in 2018, which contains the carbon emission intensity of the leading aircraft types, the Climb/Cruise/Descent (CCD) carbon emissions of each airline and each route, and the probable emissions when the routes are straight. First, the Modified Fuel Percentage Method (MFPM) is applied to calculate the carbon emission intensity of main aircraft types at various distances. Next, the carbon emissions and the Revenue Passenger Kilometers of 413 routes and 40 airlines are calculated. Then the carbon emissions of the actual route and straight route are analyzed. Dali-Kunming and Joy Air have the most significant emission intensity among the routes and airlines. However, the excess emissions from the non-straight routes account for about 10.15% of the actual emissions.

A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence

By installing on-board diagnostics (OBD) on tested vehicles, the after-treatment exhaust emissions can be monitored in real time to construct driving cycle-based emission models, which can provide data support for the construction of dynamic emission inventories of mobile source emission. However, in actual vehicle emission detection systems, due to the equipment installation costs and differences in vehicle driving conditions, engine operating conditions, and driving behavior patterns, it is impossible to ensure that the emission monitoring data of different vehicles always follow the same distribution. The traditional machine learning emission model usually assumes that the training set and test set of emission test data are derived from the same data distribution, and a unified emission model is used for estimation of different types of vehicles, ignoring the difference in monitoring data distribution. In this study, we attempt to build a diesel vehicle NOx emission prediction model based on the deep transfer learning framework with a few emission monitoring data. The proposed model firstly uses Spearman correlation analysis and Lasso feature selection to accomplish the selection of factors with high correlation with NOx emission from multiple sources of external factors. Then, the stacked sparse AutoEncoder is used to map different vehicle working condition emission data into the same feature space, and then, the distribution alignment of different vehicle working condition emission data features is achieved by minimizing maximum mean discrepancy (MMD) in the feature space. Finally, we validated the proposed method with the diesel vehicle OBD data that were collected by the Hefei Environmental Protection Bureau. The comprehensive experiment results show that our method can achieve the feature distribution alignment of emission data under different vehicle working conditions and improve the prediction performance of the NOx inversion model given a little amount of NOx emission monitoring data.

How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35)

Abstract. We perform observing system simulation experiments (OSSEs) with the GEOS-Chem adjoint model to test how well methane emissions over North America can be resolved using measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and similar high-resolution satellite sensors. We focus analysis on the impacts of (i) spatial errors in the prior emissions and (ii) model transport errors. Along with a standard scale factor (SF) optimization we conduct a set of inversions using alternative formalisms that aim to overcome limitations in the SF-based approach that arise for missing sources. We show that 4D-Var analysis of the TROPOMI data can improve monthly emission estimates at 25 km even with a spatially biased prior or model transport errors (42 %–93 % domain-wide bias reduction; R increases from 0.51 up to 0.73). However, when both errors are present, no single inversion framework can successfully improve both the overall bias and spatial distribution of fluxes relative to the prior on the 25 km model grid. In that case, the ensemble-mean optimized fluxes have a domain-wide bias of 77 Gg d−1 (comparable to that in the prior), with spurious source adjustments compensating for the transport errors. Increasing observational coverage through longer-timeframe inversions does not significantly change this picture. An inversion formalism that optimizes emission enhancements rather than scale factors exhibits the best performance for identifying missing sources, while an approach combining a uniform background emission with the prior inventory yields the best performance in terms of overall spatial fidelity – even in the presence of model transport errors. However, the standard SF optimization outperforms both of these for the magnitude of the domain-wide flux. For the common scenario in which prior errors are non-random, approximate posterior error reduction calculations (derived via gradient-based randomization) for the inversions reflect the sensitivity to observations but have no spatial correlation with the actual emission improvements. This demonstrates that such information content analysis can be used for general observing system characterization but does not describe the spatial accuracy of the posterior emissions or of the actual emission improvements. Findings here highlight the need for careful evaluation of potential missing sources in prior emission datasets and for robust accounting of model transport errors in inverse analyses of the methane budget.

Unintended Effects of Energy Efficiency Policy: Lessons Learned in the Residential Sector

The European Union has set an ambitious goal to tackle climate change, and energy efficiency in the residential sector is among the measures required to close the gap between targeted and actual greenhouse gas emissions. While different policy tools have been applied, the diffusion rate of these measures remains low. A system dynamics simulation model of the residential sector was developed to assess the advantages and drawbacks of energy efficiency policy in the multi-family building sector based on experience accumulated over the last twelve years in Latvia. The model was validated in expert group model building sessions and with historical trends. Simulating the model, a hypothesis was tested that supported the idea that seemingly positive policy tools set the stage for a series of unintended adverse effects due to the complex interactions between different system components. The common assumption that information and financial support should result in significant energy efficiency diffusion proved to be wrong. It instead results in unintended long-term consequences that hamper national energy efficiency goals. The model carried out an analysis and brought insights for improving the effectiveness of government energy efficiency policy. It is concluded that models that broadly describe complex systems are needed to identify effective policies and foresee unintended side effects.

Allocation of carbon emission quotas among provinces in China: efficiency, fairness and balanced allocation.

This paper constructs the ZSG-SBM model, comprehensive fairness allocation model, and balance allocation model from the perspectives of efficiency, fairness, and balance. Making use of the actual input-output data of China's provincial economic system in 2019, and the above three models to study the reasonable scheme of China's provincial carbon emission quota allocation in 2019. The results show that ZSG efficiency allocation can significantly improve the carbon emission efficiency of inefficient provinces, and the carbon emissions of inefficient provinces after allocation reach the efficiency frontier. The carbon emission quota of 16 provinces which located in the central and western regions of China with underdeveloped economy and relatively low carbon emission efficiency need to be decreased, while the eastern coastal provinces with more developed economy and high carbon emission efficiency in China should increase their carbon emission quota. On the one hand, comprehensive fairness allocation reduces the carbon emission reduction target constraints of economically underdeveloped provinces; on the other hand, it strengthens the carbon emission reduction target constraints of low-carbon technology backward provinces. As a result, the carbon emission quota of economically developed provinces and provinces with high carbon intensity per unit GDP is reduced in this method. The result of balancing efficiency and fairness lies between ZSG efficiency allocation and comprehensive fairness allocation. In order to alleviate the huge pressure on the emission reduction of provinces with low actual carbon emission efficiency under the ZSG efficiency allocation mode, the Chinese government can gradually increase the weight of ZSG efficiency allocation results, and finally adopt a complete ZSG efficiency allocation scheme in the carbon peak year to realize the transformation of low-carbon economy.

Assessing the Mitigation Potential of Environmental Impacts From Circular Economy Strategies on an Industrial Sector and Its Value Chain: A Case Study on the Steel Value Chain in Quebec

This research project aims to evaluate the potential reduction of environmental impacts from circular economy strategies on an industrial sector at a regional scale with a case study on Greenhouse Gas (GHG) emissions in Quebec's steel industry and its value chain. To do so, an integrated model has been created based on the matrix approach, building on material flow analysis (MFA) tracking flows and stocks and on life cycle assessment (LCA) to compute direct (from the activity, e.g., combustion process) and indirect (from the supply chain, e.g., production of raw material inside or outside of region) emissions. This theoretical model is designed to be applied to any emissions or environmental impacts from a specific sector in a given region and enable to model the effects of circularity strategies to both flows and related environmental impacts. The overall mitigation potential of individual or combined circular economy strategies on a specific sector could thus be evaluated across its entire value chain. In the case study, a set of the most promising circular strategies applicable in the Quebec context were identified, and the GHG reduction potential within and outside the province is calculated and compared with actual emissions. Six circular strategies were analyzed acting at three different levers, namely, GHG/material (increase iron recycling rate, switch to hydrogen-based reduction production), material/product (reduce weight of vehicle, limit over-specification in building construction), and product/service (increase buildings and cars lifetime, increase car-sharing), and therefore impact rather direct or indirect emissions on different stages of the steel life cycle. Combining these six strategies into a consolidated scenario shows that a circular-driven economy allows to cut down GHG emissions of the cradle-to-gate steel industry value chain by −55%, i.e., 1.67 Mt CO2e. Taking into account use phase of steel, overall reductions are estimated at −6.03 Mt CO2e, i.e., −30% of the whole life cycle.

Can accurate distance-specific emissions of nitrogen oxide emissions from cars be determined using remote sensing without measuring exhaust flowrate?

Portable Emission Measurement Systems (PEMS) are commonly used to measure absolute (mass per unit distance) emissions of a range of pollutants from road vehicles under real driving conditions. Because measuring large numbers of vehicles with PEMS is impractical, this paper investigates how vehicle emission remote sensing device (RSD) can supplement the use of PEMS. We simulate whether remote sensing measurements can accurately predict a vehicle's real-world distance-specific nitrogen oxides (NOX) emissions using RSD without measuring its exhaust flow rate. The approach uses readily available type-approval carbon dioxide (CO2) emission data together with average real-world divergences from studies based on user-reported fuel economy data. We find that at least 30 RS measurements from a given vehicle's journey are needed to reach a mean absolute error of 30% compared to a large reference data set of individual PEMS measurements. With that condition met, it is concluded that estimates agree well with actual NOX emissions from cars and the applied method does not introduce a systematic bias. It is also found that the accuracy of estimates for distance-specific NOX emissions does not significantly improve when more than 300 remote-sensing samples are available, with a mean absolute error converging to 23%. We conclude that this method could be used to screen large car fleets and identify vehicles or group of vehicles that are likely grossly exceeding air pollution standards.

Plug-in hybrid electric vehicle utility factor in China cities: Influencing factors, empirical research, and energy and environmental application

Promoting Plug-in Hybrid Electric Vehicles (PHEVs) is a promising strategy to mitigate the climate change and improve the environment in the road transportation sector. To evaluate the complex energy saving and GHG emission reduction contribution of on-board fuel and electricity, utility factor (UF) is the most widely adopted parameter to weight the distance driven by electricity and on-board fuel, respectively. However, few researches focus on city-level actual utility factors based on quantitative analysis of the influencing factors, especially in China. In this research, a probability-distribution-based PHEV UF function is constructed from travel pattern parameters, charging frequency and PHEV charge depleting range. Then the urban city-level UF at actual travel and charging patterns are derived from PHEV driving big data in seven typical cities in China. The sales-weighted actual UF is 0.49 and 0.64 for a 50 km-electric-range PHEV and a 80 km-electric-range PHEV; therefore, PHEVs with over 80 km electric range are recommended in China urban areas due to better energy saving and emission reduction potential. Finally, carbon and pollutant emissions are analyzed, actual PHEV carbon emission is 133–137 g/km currently while it could drop to 71–88 g/km at a grid with 80% renewable energy; therefore, cleaner grid would largely contribute to PHEV environmental effects. • A quantified probability distribution PHEV utility factor function is derived. • The sales-weighted actual UF is 0.49–0.64 for 50- and 80 km-electric-range PHEVs. • Actual PHEV carbon emission could drop 47% at a grid with 80% renewable energy. • PHEVs with over 80 km electric range are recommended in China urban areas.