On-road vehicle emissions: regulations, costs, and benefits

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 NO_x and PM greatly improved with the shift from the China II to China IV standards, as demonstrated by engine tests and field NO_x measurements. However, the NO_x 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 NO_x 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 NO_x 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.

Quantifying on-road vehicle emissions during traffic congestion using updated emission factors of light-duty gasoline vehicles and real-world traffic monitoring big data

Light-duty gasoline vehicles (LDGVs) have made up >90 % of vehicle fleets in China since 2019, moreover, with a high annual growth rate (> 10 %) since 2017. Hence, accurate estimates of air pollutant emissions of these fast-changing LDGVs are vital for air quality management, human healthcare, and ecological protection. However, this issue is poorly quantified due to insufficient reserves of timely updated LDGV emission factors, which are dependent on real-world activity levels. Here we constructed a big dataset of explicit emission profiles (e.g., emission factors and accumulated mileages) for 159,051 LDGVs based on an official I/M database by matching real-time traffic dynamics via real-world traffic monitoring (e.g., traffic volumes and speeds). Consequently, we provide robust evidence that the emission factors of these LDGVs follow a clear heavy-tailed distribution. The top 10 % emitters contributed >60 % to the total fleet emissions, while the bottom 50 % contributed <10 %. Such emission factors were effectively reduced by 75.7-86.2 % as official emission standards upgraded gradually (i.e., from China 2 to China 5) within 13 years from 2004 to 2017. Nevertheless, such achievements would be offset once traffic congestion occurred. In the real world, the typical traffic congestions (i.e., vehicle speed <5 km/h) can lead to emissions 5- 9 times higher than those on non-congested roads (i.e., vehicle speed >50 km/h). These empirical analyses enabled us to propose future traffic scenarios that could harmonize emission standards and traffic congestion. Practical approaches on vehicle emission controls under realistic conditions are proposed, which would provide new insights for future urban vehicle emission management.

Detecting candidate high NOx emitting light commercial vehicles using vehicle emission remote sensing

Vehicle emission remote sensing devices have been widely used for monitoring and assessing the real-world emission performance of vehicles. They are also well-suited to identify candidate high emitting vehicles as remote sensing surveys measure the on-road, real-driving emissions (RDE) of a high proportion of the operational vehicle fleet passing through a testing site. This study uses the Gumbel distribution to characterize the fuel-specific NO_x emission rates (g·kg^-1) from diesel vans (formally referred to as light commercial vehicles or LCVs) and screen candidate high emitting vehicles. Van emission trends of four European countries (Belgium, Sweden, Switzerland and the UK) from Euro 3 to Euro 6a/b have been studied, and the impact of road grade on candidate Euro 6a/b high-emitters is also evaluated. The measurements of Euro 6a/b fleets from four countries are pooled together, and a consistent 4% of candidate high-emitters are found in both class II and class III Euro 6a/b vans, accounting for an estimated 24% and 21% total NO_x emissions respectively. The pooled four country data is differentiated by vehicle models and manufacture groups. Engine downsizing of Euro 6a/b class II vans is suspected to worsen the emission performance when vehicles are driven under high engine load. The VW Group is found to be the manufacture with cleanest NO_x emission performance in the Euro 6a/b fleets. By distinguishing high-emitters from normally behaving vehicles, a more robust description of fleet behaviour can be provided and high-emitting vehicles targeted for further testing by plume chasing or in an inspection garage. If the vehicle is found to have a faulty, deteriorated or tampered emission after-treatment system, the periodic vehicle inspection safety and environmental performance certificate could be revoked.

Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China

On-road vehicle emissions play a crucial role in affecting air quality and human exposure, particularly in megacities. In the absence of comprehensive traffic monitoring networks with the general lack of intelligent transportation systems (ITSs) and big-data-driven, high-performance-computing (HPC) platforms, it remains challenging to constrain on-road vehicle emissions and capture their hotspots. Here, we established an intelligent modelling and visualization system driven by ITS traffic data for real-world, on-road vehicle emissions. Based on the HPC platform (named “City Brain”) and an agile Web Geographic Information System (WebGISs), this system can map real-time (hourly), hyperfine (10~1000 m) vehicle emissions (e.g., PM2.5, NOx, CO, and HC) and associated traffic states (e.g., vehicle-specific categories and traffic fluxes) over the Xiaoshan District in Hangzhou. Our results show sharp variations in on-road vehicle emissions on small scales, which even fluctuated up to 31.2 times within adjacent road links. Frequent and widespread emission hotspots were also exposed. Over custom spatiotemporal scopes, we virtually investigated and visualized the impacts of traffic control policies on the traffic states and on-road vehicle emissions. Such results have important implications for how traffic control policies should be optimized. Integrating this system with chemical transport models and air quality measurements would bridge the technical gap between air pollutant emissions, concentrations, and human exposure.

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 (NO_X) 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 NO_X 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 NO_X 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.

Rapid detection of high-emitting vehicles by on-road remote sensing technology improves urban air quality

Vehicle emissions are the most important source of air pollution in the urban environment worldwide, and their detection and control are critical for protecting public health. Here, we report the use of on-road remote sensing (RS) technology for fast, accurate, and cost-effective identification of high-emitting vehicles as an enforcement program for improving urban air quality. Using large emission datasets from chassis dynamometer testing, RS, and air quality monitoring, we found that significant percentages of in-use petrol and LPG vehicles failed the emission standards, particularly the high-mileage fleets. The RS enforcement program greatly cleaned these fleets, in terms of high-emitter percentages, fleet average emissions, roadside and ambient pollutant concentrations, and emission inventory. The challenges of the current enforcement program are conservative setting of cut points, single-lane measurement sites, and lack of application experience in diesel vehicles. Developing more accurate and vertical RS systems will improve and extend their applications.

Multi-Gas Detection System Based on Non-Dispersive Infrared (NDIR) Spectral Technology

Automobile exhaust gases, such as carbon dioxide (CO₂), carbon monoxide (CO), and propane (C₃H₈), cause the greenhouse effect, photochemical smog, and haze, threatening the urban atmosphere and human health. In this study, a non-dispersive infrared (NDIR) multi-gas detection system consisting of a single broadband light source, gas cell, and four-channel pyroelectric detector was developed. The system can be used to economically detect gas concentration in the range of 0–5000 ppm for C₃H₈, 0–14% for CO, and 0–20% for CO₂. According to the experimental data, the concentration inversion model was established using the least squares between the voltage ratio and the concentration. Additionally, the interference coefficient between different gases was tested. Therefore, the interference models between the three gases were established by the least square method. The concentration inversion model was experimentally verified, and it was observed that the full-scale error of the sensor changed less than 3.5%, the detection repeatability error was lower than 4.5%, and the detection stability was less than 2.7%. Therefore, the detection system is economical and energy efficient and it is a promising method for the analysis of automobile exhaust gases.

Statistical evaluation of on-road vehicle emissions measurement using a dual remote sensing technique

On-road remote sensing (RS) is a rapid, non-intrusive and economical tool to monitor and control the emissions of in-use vehicles, and currently is gaining popularity globally. However, a majority of studies used a single RS technique, which may bias the measurements since RS only captures a snapshot of vehicle emissions. This study aimed to use a unique dual RS technique to assess the characteristics of on-road vehicle emissions. The results show that instantaneous vehicle emissions are highly dynamic under real-world driving conditions. The two emission factors measured by the dual RS technique show little correlation, even under the same driving condition. This indicates that using the single RS technique may be insufficient to accurately represent the emission level of a vehicle based on one measurement. To increase the accuracy of identifying high-emitting vehicles, using the dual RS technique is essential. Despite little correlation, the dual RS technique measures the same average emission factors as the single RS technique does when a large number of measurements are available. Statistical analysis shows that both RS systems demonstrate the same Gamma distribution with ≥200 measurements, leading to converged mean emission factors for a given vehicle group. These findings point to the need for a minimum sample size of 200 RS measurements in order to generate reliable emission factors for on-road vehicles. In summary, this study suggests that using the single or dual RS technique will depend on the purpose of applications. Both techniques have the same accuracy in calculating average emission factors when sufficient measurements are available, while the dual RS technique is more accurate in identifying high-emitters based on one measurement only.

A WRF-Chem model-based future vehicle emission control policy simulation and assessment for the Beijing-Tianjin-Hebei region, China

Using 2025 as the target year, we quantitatively assessed the reduction potentials of emissions of primary pollutants (including CO, HC, NO_x, PM_2.5 and PM₁₀) under different vehicle control policies and the impacts of vehicle emission control policies in the BTH region on the regional PM_2.5 concentration in winter and the surface ozone (O₃) concentration in summer. Comparing the different scenarios, we found that (1) vehicle control policies will bring significant reductions in the emissions of primary pollutants. Among the individual policies, upgrading new vehicle emission standards and fuel quality in Beijing, Tianjin, and Hebei will be the most effective policy, with emission reductions of primary pollutants of 26.3%-54.7%, 38.0%-70.3% and 46.0%-81.6% in 2025, respectively; (2) for PM_2.5 in winter, the Combined Scenario (CS) will lead to a reduction of 0.5-3.9 μg m^-3 (3.5%-11.6%) for the monthly average PM_2.5 concentrations in most areas. The monthly nitrate and ammonium concentrations would reduce by 5.8% and 5.3%, respectively, in the whole BTH region, indicating that vehicle emission control policies may play an important role in the reduction of PM_2.5 concentrations in winter, especially for nitrate aerosols; and (3) for O₃ concentrations in summer, vehicle emission control policies will lead to significant decreases. Under the CS scenario, the maximum reduction of monthly average O₃ concentrations in the summer is approximately 3.6 ppb (5.9%). Most areas in the BTH region have a decrease of 15 ppb (7.5%) in peak values compared to the base scenario. However, in some VOC-sensitive areas in the BTH region, such as the southern urban areas, significant reductions in NO_x may lead to increases in ozone concentrations. Our results highlight that season- and location-specific vehicle emission control measures are needed to alleviate ambient PM_2.5 and O₃ pollution effectively in this region due to the complex meteorological conditions and atmospheric chemical reactions.

Characterisation of diesel vehicle emissions and determination of remote sensing cutpoints for diesel high-emitters

Diesel vehicles are a major source of air pollutants in cities and have caused significant health risks to the public globally. This study used both on-road remote sensing and transient chassis dynamometer to characterise emissions of diesel light goods vehicles. A large sample size of 183 diesel vans were tested on a transient chassis dynamometer to evaluate the emission levels of in-service diesel vehicles and to determine a set of remote sensing cutpoints for diesel high-emitters. The results showed that 79% and 19% of the Euro 4 and Euro 5 diesel vehicles failed the transient cycle test, respectively. Most of the high-emitters failed the NO limits, while no vehicle failed the HC limits and only a few vehicles failed the CO limits. Vehicles that failed NO limits occurred in both old and new vehicles. NO/CO₂ ratios of 57.30 and 22.85 ppm/% were chosen as the remote sensing cutpoints for Euro 4 and Euro 5 high-emitters, respectively. The cutpoints could capture a Euro 4 and Euro 5 high-emitter at a probability of 27% and 57% with one snapshot remote sensing measurement, while only producing 1% of false high-emitter detections. The probability of high-emitting events was generally evenly distributed over the test cycle, indicating that no particular driving condition produced a higher probability of high-emitting events. Analysis on the effect of cutpoints on real-driving diesel fleet was carried out using a three-year remote sensing program. Results showed that 36% of Euro 4 and 47% of Euro 5 remote sensing measurements would be detected as high-emitting using the proposed cutpoints.

Three decades of on-road mobile source emissions reductions in South Los Angeles

In May 2018, the University of Denver repeated on-road optical remote sensing measurements at two locations in Lynwood, CA. Lynwood area vehicle tailpipe emissions were first surveyed in 1989 and 1991 because the area suffered from a large number of carbon monoxide (CO) air quality violations. These new measurements allow for the estimation of fuel-specific CO and total hydrocarbon (HC) emissions reductions, changes in the longevity of emission-control components, and the prevalence of high emitters in the current fleet. Since 1989 CO emissions decreased approximately factors of 10 (120 ± 8 to 12.3 ± 0.2 gCO/kg of fuel) and 20 (210 ± 8 to 10.4 ± 0.4 gCO/kg of fuel) at our I-710/Imperial Highway and Long Beach Blvd. sites, respectively. These reductions are also reflected in the local ambient air measurements. Tailpipe HC emissions have decreased by a factor of 25 (50 ± 4 to 2.1 ± 0.3 gHC/kg of fuel) since 1991 at the Long Beach Blvd. location. The decreases are so dramatic that the vast majority of vehicles now have HC measurements that are indistinguishable from zero. The decreases have increased the skewedness of the emissions distribution with the 99th percentile now responsible for more than 37% (CO) and 28% (HC) of the totals. Ammonia emissions collected in 2018 at both Lynwood locations peak with 20-year-old vehicles (1998 models), indicating long lifetimes for catalytic converters. In 1989 and 1991, the on-road Lynwood fleets had significantly higher emissions than fleets observed in other locations within the South Coast Air Basin. The 2018 fleets now have means and emissions by model year that are consistent with those observed at other sites in Los Angeles and the U.S. This indicates that modern vehicle combustion management and after-treatment systems are achieving their goals regardless of community income levels. Implications: Recent on-road vehicle emission measurements at two locations in the Lynwood, CA area, first visited in 1989, found significant fuel specific CO and HC emission reductions. CO emissions have decreased by a factor of 10 and 20 at each location and HC emissions have declined by a factor of 25. This has increased the skewedness in both species emissions distribution. The 2018 fleets have means and emissions by model year that are now consistent with those observed at other U.S. sites indicating that modern vehicle emissions control advancements are achieving their goals regardless of community income levels.

Tackling nitric oxide emissions from dominant diesel vehicle models using on-road remote sensing technology

Remote sensing provides a rapid detection of vehicle emissions under real driving condition. Remote sensing studies showed that diesel nitrogen oxides emissions changed little or were even increasing in recent years despite the tightened emission standards. To more accurately and fairly evaluate the emission trends, it is hypothesized that analysis should be detailed for individual vehicle models as each model adopted different emissions control technologies and retrofitted the engine/vehicle at different time. Therefore, this study was aimed to investigate the recent nitric oxide (NO) emission trends of the dominant diesel vehicle models using a large remote sensing dataset collected in Hong Kong. The results showed that the diesel vehicle fleet was dominated by only seven models, accounting for 78% of the total remote sensing records. Although each model had different emission levels and trends, generally all the dominant models showed a steady decrease or stable level in the fuel based NO emission factors (g/kg fuel) over the period studied except for BaM1 and BdM2. A significant increase was observed for the BaM1 2.49 L and early 2.98 L models during 2005-2011, which we attribute to the change in the diesel fuel injection technology. However, the overall mean NO emission factor of all the vehicles was stable during 1991-2006 and then decreased steadily during 2006-2016, in which the emission trends of individual models were averaged out and thus masked. Nevertheless, the latest small, medium and heavy diesel vehicles achieved similar NO emission factors due to the converging of operation windows of the engine and emission control devices. The findings suggested that the increasingly stringent European emission standards were not very effective in reducing the NO emissions of some diesel vehicle models in the real world.

Review of Urban Secondary Organic Aerosol Formation from Gasoline and Diesel Motor Vehicle Emissions

Secondary organic aerosol (SOA) is formed from the atmospheric oxidation of gas-phase organic compounds leading to the formation of particle mass. Gasoline- and diesel-powered motor vehicles, both on/off-road, are important sources of SOA precursors. They emit complex mixtures of gas-phase organic compounds that vary in volatility and molecular structure-factors that influence their contributions to urban SOA. However, the relative importance of each vehicle type with respect to SOA formation remains unclear due to conflicting evidence from recent laboratory, field, and modeling studies. Both are likely important, with evolving contributions that vary with location and over short time scales. This review summarizes evidence, research needs, and discrepancies between top-down and bottom-up approaches used to estimate SOA from motor vehicles, focusing on inconsistencies between molecular-level understanding and regional observations. The effect of emission controls (e.g., exhaust aftertreatment technologies, fuel formulation) on SOA precursor emissions needs comprehensive evaluation, especially with international perspective given heterogeneity in regulations and technology penetration. Novel studies are needed to identify and quantify "missing" emissions that appear to contribute substantially to SOA production, especially in gasoline vehicles with the most advanced aftertreatment. Initial evidence suggests catalyzed diesel particulate filters greatly reduce emissions of SOA precursors along with primary aerosol.

Theoretical study of interactions of a Li+(CF3SO2)2N− ion pair with CR3(OCR2CR2)nOCR3 (R = H or F)

Interactions of a lithium bis(trifluoromethane sulfonyl)imide (Li⁺Tf₂N⁻) ion pair with oligoethers are investigated via density functional theory (DFT).

Long-term trends in motor vehicle emissions in u.s. urban areas

A fuel-based approach is used to estimate long-term trends (1990-2010) in carbon monoxide (CO) emissions from motor vehicles. Non-methane hydrocarbons (NMHC) are estimated using ambient NMHC/CO ratios after controlling for nonvehicular sources. Despite increases in fuel use of ∼10-40%, CO running exhaust emissions from on-road vehicles decreased by ∼80-90% in Los Angeles, Houston, and New York City, between 1990 and 2010. The ratio of NMHC/CO was found to be 0.24 ± 0.04 mol C/mol CO over time in Los Angeles, indicating that both pollutants decreased at a similar rate and were improved by similar emission controls, whereas on-road data from other cities suggest rates of reduction in NMHC versus CO emissions may differ somewhat. Emission ratios of CO/NOx (nitrogen oxides = NO + NO2) and NMHC/NOx decreased by a factor of ∼4 between 1990 and 2007 due to changes in the relative emission rates of passenger cars versus diesel trucks, and slight uptick thereafter, consistent across all urban areas considered here. These pollutant ratios are expected to increase in future years due to (1) slowing rates of decrease in CO and NMHC emissions from gasoline vehicles and (2) significant advances in control of diesel NOx emissions.

Valuation of plug-in vehicle life-cycle air emissions and oil displacement benefits

We assess the economic value of life-cycle air emissions and oil consumption from conventional vehicles, hybrid-electric vehicles (HEVs), plug-in hybrid-electric vehicles (PHEVs), and battery electric vehicles in the US. We find that plug-in vehicles may reduce or increase externality costs relative to grid-independent HEVs, depending largely on greenhouse gas and SO(2) emissions produced during vehicle charging and battery manufacturing. However, even if future marginal damages from emissions of battery and electricity production drop dramatically, the damage reduction potential of plug-in vehicles remains small compared to ownership cost. As such, to offer a socially efficient approach to emissions and oil consumption reduction, lifetime cost of plug-in vehicles must be competitive with HEVs. Current subsidies intended to encourage sales of plug-in vehicles with large capacity battery packs exceed our externality estimates considerably, and taxes that optimally correct for externality damages would not close the gap in ownership cost. In contrast, HEVs and PHEVs with small battery packs reduce externality damages at low (or no) additional cost over their lifetime. Although large battery packs allow vehicles to travel longer distances using electricity instead of gasoline, large packs are more expensive, heavier, and more emissions intensive to produce, with lower utilization factors, greater charging infrastructure requirements, and life-cycle implications that are more sensitive to uncertain, time-sensitive, and location-specific factors. To reduce air emission and oil dependency impacts from passenger vehicles, strategies to promote adoption of HEVs and PHEVs with small battery packs offer more social benefits per dollar spent.

Monitoring the soot emissions of passing cars

We report on the first application of a novel fast on-road sensing method for measurement of particulate emissions of individual passing passenger cars. The studywas motivated by the shift of interest from gases to particles in connection with strong adverse health effects. The results correspond very much to findings by Beaton et al. (Science, May 19,1995) for gaseous hydrocarbon and CO emissions: A small percentage of "superpolluters" (here 5%) account for a high percentage (here 43%) of the pollution (here elemental carbon). We estimate that up to 50% of the particulate emissions of vehicles could be avoided on the basis of the present legislation, if on-road monitoring would be applied to enforce maintenance. Our fast sensing method for particles is based on photoelectron emission from the emitted airborne soot particles in combination with a CO2 sensor delivering a reference.

On-road vehicle particulate matter and gaseous emission distributions in Las Vegas, Nevada, compared with other areas

During the spring and summer of 2000, 2001, and 2002, gaseous and particulate matter (PM) fuel-based emission factors for approximately 150,000 low-tailpipe, individual vehicles in the Las Vegas, NV, area were measured via on-road remote sensing. For the gaseous pollutants (carbon monoxide, hydrocarbons, and nitrogen oxide), a commercial vehicle emissions remote sensing system (VERSS) was used. The PM emissions were determined using a Lidar-based VERSS. Emission distributions and their shapes were analyzed and compared with previous studies. The large skewness of the distributions is evident for both gaseous pollutants and PM and has important implications for emission reduction policies, because the majority of emissions are attributed to a small fraction of vehicles. Results of this Las Vegas study and studies at other geographical locations were compared. The gaseous pollutants were found to be close to those measured by VERSS in other U.S. cities. The PM emission factors for spark ignition and diesel vehicles are in the range of previous tunnel and dynamometer studies.

Emissions reductions as a result of automobile improvement

Remote sensing of light duty vehicle on-road tailpipe exhaust has been used to measure on-road mass emissions of automobile fleets in Denver for 13 years and in two other U.S. cities for 5 years. Analysis of these fleets shows that newer automobiles, during a period of fairly constant new car standards, have become continually less polluting independent of measurement location. Improving emissions control technology spurred by federal regulations is thought to have brought about these trends.

Ethical and economic issues in the use of zero-emission vehicles as a component of an air-pollution mitigation strategy

The air pollution generated by motor vehicles and by static sources is, in certain geographic areas, a very serious problem, a problem that exists because of a failure of the marketplace. To address this marketplace failure, the State of California has mandated that by 2003, 10% of the Light-Duty Vehicle Fleet (LDV) be composed of Zero-Emission Vehicles (ZEVs). However, the policy-making process that was utilized to generate the ZEV mandate was problematic and the resulting ZEV mandate is economically unsound. Moreover, an ethical analysis, based primarily upon the work of John Rawls, suggests that implementation of the California ZEV mandate is--in spite of the wide latitude that ought to be given to policy decision makers--unethical. A more ethical and economically efficient approach to the pollution caused by marketplace failure is one that relies on market incentives and thereby achieves the desired improvement in air quality by appealing both to the self-interest of motorists and to those businesses that are directly or indirectly involved with the automobile industry. Such an approach would take better advantage of the creative forces of the market and improvements in technology over time and avoid the infringements on individual liberty and fairness embodied in the ZEV mandate.