Anthropogenic NOx emissions in Asia in the period 1990–2020

Nitrogen oxides emissions in Asia during the period 1990–2020 due to anthropogenic activity are presented. These estimates are based on the RAINS-ASIA methodology (Foell et al., 1995, Acid Rain and Emission Reduction in Asia, World Bank), which includes a dynamic model for energy forecasts, and information on 6 energy sectors and 9 fuel types. The energy forecasts are combined with process emission factors to yield NO_x emission estimates at the country level, the regional level, and on a 1 degree by 1 degree grid. In 1990 the total NO_x emissions are estimated to be ∼19 Tg NO₂, with China (43%), India (18%) and Japan (13%) accounting for 75% of the total. Emissions by fuel are dominated by burning of hard coal and emissions by economic activity are dominated by the power, transport, and industrial sectors. These new estimates of NO_x emissions are compared with those published by Hameed and Dignon (1988, Atmospheric Environment 22, 441–449) and Akimoto and Narita (1994, Atmospheric Environment 28, 213–225). Future emissions under a no-further-control scenario are also presented. During the period 1990–2020 the NO_x emissions increase by 350%, to ∼86 Tg NO₂. The increase in NO_x emissions by sector and end-use varies between countries, but in all countries this increase is strongest in the power and transport sectors. These results highlight the dynamic nature of energy use in Asia, and the need to take the rapid growth in NO_x emissions in Asia into account in studies of air pollution and atmospheric chemistry.     

Integrated Sampling and Analysis Methods for Determining NO x Emissions at Electric Utility Plants

Two integrated sampling and analysis methods for determining NO_x emissions in electric utility plants were developed and field tested. The collection systems consist of: a 4.0% potassium permanganate-2.0% sodium hydroxide solution in restricted-orifice impingers, and a 5A° molecular sieve in midget impingers. Sample analysis is accomplished by a colorimetric or ion-chromatographic procedure with the alkaline-permanganate method and by a colorimetric procedure with the molecular sieve method. The alkalinepermanganate method gives excellent agreement with the EPA reference method, Method 7, for NO _x measurements. The molecular sieve method shows a significant negative bias relative to Method 7. It is anticipated that the permanganate methods will be proposed as alternates to Method 7, for NO _x determinations, under the EPA New Source Performance Standards.     

Real-world fuel use and gaseous emission rates for flex fuel vehicles operated on E85 versus gasoline

Flex fuel vehicles (FFVs) typically operate on gasoline or E85, an 85%/15% volume blend of ethanol and gasoline. Differences in FFV fuel use and tailpipe emission rates are quantified for E85 versus gasoline based on real-world measurements of five FFVs with a portable emissions measurement system (PEMS), supplemented chassis dynamometer data, and estimates from the Motor Vehicle Emission Simulator (MOVES) model. Because of inter-vehicle variability, an individual FFV may have higher nitrogen oxide (NO_x) or carbon monoxide (CO) emission rates on E85 versus gasoline, even though average rates are lower. Based on PEMS data, the comparison of tailpipe emission rates for E85 versus gasoline is sensitive to vehicle-specific power (VSP). For example, although CO emission rates are lower for all VSP modes, they are proportionally lowest at higher VSP. Driving cycles with high power demand are more advantageous with respect to CO emissions, but less advantageous for NO_x. Chassis dynamometer data are available for 121 FFVs at 50,000 useful life miles. Based on the dynamometer data, the average difference in tailpipe emissions for E85 versus gasoline is ?23% for NO_x, ?30% for CO, and no significant difference for hydrocarbons (HC). To account for both the fuel cycle and tailpipe emissions from the vehicle, a life cycle inventory was conducted. Although tailpipe NO_x emissions are lower for E85 versus gasoline for FFVs and thus benefit areas where the vehicles operate, the life cycle NO_x emissions are higher because the NO_x emissions generated during fuel production are higher. The fuel production emissions take place typically in rural areas. Although there are not significant differences in the total HC emissions, there are differences in HC speciation. The net effect of lower tailpipe NO_x emissions and differences in HC speciation on ozone formation should be further evaluated.

Implications: Reported comparisons of flex fuel vehicle (FFV) tailpipe emission rates for E85 versus gasoline have been inconsistent. To date, this is the most comprehensive evaluation of available and new data. The large range of inter-vehicle variability illustrates why prior studies based on small sample sizes led to apparently contradictory findings. E85 leads to significant reductions in tailpipe nitrogen oxide (NO_x) and carbon monoxide (CO) emission rates compared with gasoline, indicating a potential benefit for ozone air quality management in NO_x-limited areas. The comparison of FFV tailpipe emissions between E85 and gasoline is sensitive to power demand and driving cycles.     

A European-wide inventory of soil NO emissions using the biogeochemical models DNDC/Forest-DNDC

Soils are a significant source for atmospheric NO. However, due to the limited number of measurements and in view of the high temporal and spatial variability of NO emissions, as originating from dependencies from a series of environmental constraints such as soil properties, meteorology or N fertilization, inventories of soil NO emissions are still highly uncertain. In this work, the agricultural DNDC model was modified and applied on site scale in order to evaluate its capability to simulate soil NO emissions. DNDC captured differences in the magnitude of NO emissions between sites, but was less successful when simulating observed day-by-day variations. However, major peak emission events, e.g. due to fertilizer application or following rainfall events, were mostly simulated. DNDC as well as its forest version Forest-DNDC were finally linked to a GIS to calculate NO emissions from agricultural and forest soils across Europe. Using the same databases for agricultural soils, we also compared our estimate with other commonly used methodologies (Skiba-EMEP/CORINAIR, Yienger and Levy, Stehfest and Bouwman). A canopy reduction factor was not applied in this study. Estimates for NO emissions for agricultural soils for EU15 states varied in a range of 48.9–189.8 kt NO-N for the year 2000 depending on the approach used (Yienger and Levy > DNDC > Stehfest and Bouwman > Skiba-EMEP/CORINAIR). For forests, using the model Forest-DNDC as the only approach, we calculated soil NO emissions to be 75.1 kt NO-N yr^?1. The results show that soils in EU15 states are significant sources of atmospheric NO, though the share of soil NO emissions on total NO_x emissions (incl. NO_x emissions by combustion processes) in EU15 was only 4–6%. Given that soil NO emissions are largely driven by the availability of inorganic nitrogen (fertilization) and temperature, emissions are larger during the vegetation period. Especially during early summer when fertilizer-induced NO emissions from agricultural soils are peaking, the contribution of soil emissions to total NO_x emissions may most likely be well above 10%.     

Cost-Effective Reduction of NOx Emissions from Electricity Generation

ABSTRACT

This paper analyzes the benefits and costs of policies to reduce NO_x emissions from electricity generation in the United States. Because emissions of NOx contribute to the high concentration of atmospheric ozone in the eastern states associated with health hazards, the U.S. Environmental Protection Agency (EPA) has called on eastern states to formulate state implementation plans (SIPs) for reducing NO_x emissions. Our analysis considers three NO_x reduction scenarios: a summer seasonal cap in the eastern states covered by EPA's NO_x SIP Call, an annual cap in the same SIP Call region, and a national annual cap. All scenarios allow for emissions trading. Although EPA's current policy is to implement a seasonal cap in the SIP Call region, this analysis indicates that an annual cap in the SIP Call region would yield about $400 million more in net benefits (benefits less costs) than would a seasonal policy, based on particulate-related health effects only. An annual cap in the SIP Call region is also the policy that is most likely to achieve benefits in excess of costs. Consideration of omissions from this accounting, including the potential benefits from reductions in ozone concentrations, strengthens the finding that an annual program offers greater net benefits than does a seasonal program.     

Use of Subsampled Traffic Data to Estimate Roadway Emissions,Including Conversion to MOBILE6 Vehicle Classifications

Abstract

Air quality is degraded by many factors, among which the emissions from on‐road vehicles play a significant role. Timely and accurate estimate of such emissions becomes very important for policy‐making and effective control measures. However, lack of traffic data and outdated emission software make this task difficult. This research has demonstrated a new method that facilitates the vehicular emission inventories at the local level by using shorter-time Highway Performance Monitoring System (HPMS) traffic data along with the latest U.S. Environment Protection Agency (EPA) emission modeling software, MOBILE6. The conversion methodology was developed for converting readily available HPMS traffic volume data into EPA MOBILE-based traffic classifications, and a corresponding software program was written for automating the process. EPA MOBILE6 model was used to obtain emissions of nitrogen oxides (NO_x), volatile organic compound (VOC), and cabon monoxide (CO) emitted by the parent traffic and subsampled traffic data, and these emissions were additionally compared. The case study has shown that the difference of the magnitude between the emission estimates produced by certain subsampled and parent traffic data are minor, indicating that subsampled HPMS data can be used for reporting parent traffic emissions. It was also observed that traffic emissions follow a Weibull distribution, and NO_x emissions were more sensitive to the traffic data composition than VOC and CO. Lastly, use of average emission values of 20 or 30 consecutive minutes appears to be valid for representing hourly emissions.     

Partitioning, sources and variability of regional and local oxidant (OX = O3 + NO2) in a coastal rural area in the southwest of Iberian Peninsula

The purpose of this work is to investigate the behaviour and variability of oxidant levels (OX?=?NO₂?+?O₃), for the first time, in a rural coastal area in the southwest of the Iberian Peninsula, affected by several air masses types. Detailed database (built-up over the years 2008 to 2011, and containing around 500,000 data) from the Atmospheric Sounding Station “El Arenosillo” was used. The observed daily cycles of NO _x and OX were influenced by air masses coming from industrial and urban area. It can be seen that the concentration of OX is made up of a NO _x -independent ‘regional’ contribution (i.e. the O₃ background), and a linearly NO _x -dependent ‘local’ contribution from primary emissions, such as traffic. The local emission is very low in this area. Also, the regional contribution is similar to unpolluted sites and presents seasonal variation, being higher in May. However, our measurements showed that the proportion of OX in the form of NO₂ increases with the increase in NO _x concentration during the day. The higher proportion of NO₂ observed at night must be due to the conversion of NO to NO₂ by the NO?+?O₃ reaction. With regards to the source of the local NO _x -dependent contribution, it may be attributed to industrial emission, or the termolecular reaction 2NO?+?O₂?=?2NO₂, at high-NO _x levels and stagnant air during several days. Finally, we estimated the photolysis rate of NO₂, J _NO2, an important key atmospheric reaction coupled with ozone. We also present surface plots of annual variation of the daily mean NO _x and OX levels, which indicate that oxidants come from transport processes instead of local emissions associated as local photochemistry.     

Automated Chemical Mass Balance Receptor Modeling

Abstract

A nontrivial portion of heavy-duty vehicle emissions of NO_x and particulate matter (PM) occurs during idling. Regulators and the environmental community are interested in curtailing truck idling emissions, but current emissions models do not characterize them accurately, and little quantitative data exist to evaluate the relative effectiveness of various policies. The objectives of this study were to quantify the effect of accessory loading and engine speed on idling emissions from a properly functioning, modern, heavy-duty diesel truck and to compare these results with data from earlier model year vehicles. It was found that emissions during idling varied greatly as a function of engine model year, engine speed, and accessory load conditions. For the 1999 model year Class 8 truck tested, raising the engine speed from 600 to 1050 rpm and turning on the air conditioning resulted in a 2.5-fold increase in NO_x emissions in grams per hour, a 2-fold increase in CO₂ emissions, and a 5-fold increase in CO emissions while idling. On a grams per gallon fuel basis, NO_x emissions while idling were approximately twice as high as those at 55 mph. The CO₂ emissions at the two conditions were closer. The NO_x emissions from the 1999 truck while idling with air conditioning running were slightly more than those of two 1990 model year trucks under equivalent conditions, and the hydrocarbon (HC) and CO emissions were significantly lower. It was found that the NO_x emissions used in the California Air Resources Board’s (CARB) EMFAC2000 and the U.S. Environmental Protection Agency’s (EPA) MOBILE5b emissions inventory models were lower than those measured in all of the idling conditions tested on the 1999 truck.     

IAPCS: A Computer Model that Evaluates Pollution Control Systems for Utility Boilers

The IAPCS model, developed by U.S. EPA’s Air and Energy Engineering Research Laboratory and made available to the public through the National Technical Information Service, can be used by utility companies, architectural and engineering companies, and regulatory agencies at all levels of government to evaluate commercially available technologies for control of SO₂, NO_x, and particulate matter emissions from coal-fired utility boilers with respect to performance and cost. The model is considered to be a useful tool to compare alternative control strategies to be used by utilities to comply with the requirements of the CAA, and to evaluate the sensitivity of control costs with respect to many of the significant variables affecting costs.

To illustrate the use of the model for site-specific studies, the authors used the model to estimate control costs for SO₂ and NO_x control at Detroit Edison’s Monroe plant and two hypothetical plants under consideration and at three plants operated by New York State Electric and Gas Corporation. The economic and technical assumptions used to drive the model were those proposed by the utilities if cited, and if not cited, the model default values were used. The economic format and methodologies for costs cited in the Electric Power Research Institute’s Technical Assessment Guide are used in the IAPCS model. Depending on the specific conditions and assumptions for the cases evaluated, SO₂ control costs ranged from $417 to $3,159 per ton of SO₂ removed, and NO_x control costs ranged from $461 to $3,537 per ton of NO_x removed or reduced.     

Sub-region (district) and sector level SO2 and NOx emissions for India: assessment of inventories and mitigation flexibility

Sub-regional and sector level distribution of SO₂ and NO_x emissions inventories for India have been estimated for all the 466 Indian districts using base data for years 1990 and 1995. Although, national level emissions provide general guidelines for assessing mitigation alternatives, but significant regional and sectoral variability exist in Indian emissions. Districts reasonably capture this variability to a fine grid as 80% of these districts are smaller than 1°×1° resolution with 60% being smaller than even 1/2°×1/2°. Moreover, districts in India have well-established administrative and institutional mechanisms that would be useful for implementing and monitoring measures. District level emission estimates thus offer a finer regional scale inventory covering the combined interests of the scientific community and policy makers. The inventory assessment methodology adopted is similar to that prescribed by the Intergovernmental Panel on Climate Change (IPCC) for greenhouse gas (GHG) emissions. The sectoral decomposition at district level includes emissions from fossil fuel combustion, non-energy emissions from industrial activities and agriculture. Total SO₂ and NO_x emissions from India were 3542 and 2636 Gg, respectively (1990) and 4638 and 3462 Gg (1995) growing at annual rate of around 5.5%. The sectoral composition of SO₂ emissions indicates a predominance of electric power generation sector (46%). Power and transport sector emissions equally dominate NO_x emissions contributing nearly 30% each. However, majority of power plants are situated in predominantly rural districts while the latter are concentrated in large urban centers. Mitigation efforts for transport sector NO_x emissions would therefore be higher. The district level analysis indicates diverse spatial distribution with the top 5% emitting districts contributing 46.5 and 33.3% of total national SO₂ and NO_x emissions, respectively. This skewed emission pattern, with a few districts, sectors and point sources emitting significant SO₂ and NO_x, offers mitigation flexibility to policy makers for cost-effective mitigation.     

Comparisons of EPA Rollback,Empirical/Kinetic,and Physicochemical Oxidant Prediction Relationships in the San Francisco Bay Area

This paper describes, compares and evaluates selected Oxidant Prediction Relationships {OPRs) in terms of projections of hydrocarbon emission reductions required for attainment of the former 0.08 ppm standard and the new 0.12 ppm standard in the San Francisco Bay Area in 1985. The OPRs analyzed are the LIRAQ physicochemical model, EPA’s Empirical Kinetic Modeling Approach (EKMA), linear and Appendix J rollback, and an empirical OPR based on local observations.

LIRAQ simulations indicated that to achieve the 0.12 ppm ozone standard, 1985 hydrocarbon emissions must be reduced by 27% from projected levels. The equivalent reductions derived from simple linear rollback, linear rollback with 0.04 ppm background, and the local empirical OPR were 32%, 45% and 37%, respectively. The LIRAQ simulations also showed that reduction of both hydrocarbon and NO_x emissions is less effective than reduction of hydrocarbons only. The attempt to apply EKMA failed because the Bay Area’s low hydrocarbon/NO_x ratios and observed ozone levels are not consistent with the standard EKMA isopleth curves.

For planning, proper OPR selection is important because the wide range in the projections of various OPRs translates into a correspondingly wide range in control costs. Physicochemical OPRs are preferred because they are verifiable; they account for complex topography, meteorology, and source distributions; and because they can treat a variety of control strategies. In the future, the uncertainties associated with the projections can be resolved by assessing trends in air quality on a regular basis and by upgrading and reapplying the prediction methodologies as new information becomes available.     

Environmental assessment on a soil washing process of a Pb-contaminated shooting range site: a case study

In this study, an environmental assessment on a soil washing process for the remediation of a Pb-contaminated shooting range site was conducted, using a green and sustainable remediation tool, i.e., SiteWise ver. 2, based on data relating specifically to the actual remediation project. The entire soil washing process was classified into four major stages, consisting of soil excavation (stage I), physical separation (stage II), acid-based (0.2 N HCl) chemical extraction (stage III), and wastewater treatment (stage IV). Environmental footprints, including greenhouse gas (GHG) emissions, energy consumption, water consumption, and critical air pollutant productions such as PM₁₀, NO _x , and SO _x , were calculated, and the relative contribution of each stage was analyzed in the environmental assessment. In stage I, the relative contribution of the PM₁₀ emissions was 55.3 % because the soil excavation emitted the fine particles. In stage II, the relative contribution of NO _x and SO _x emissions was 42.5 and 52.5 %, respectively, which resulted from electricity consumption for the operation of the separator. Stage III was the main contributing factor to 63.1 % of the GHG emissions, 67.5 % of total energy used, and 37.4 % of water consumptions. The relatively high contribution of stage III comes from use of consumable chemicals such as HCl and water-based extraction processes. In stage IV, the relative contributions of GHG emissions, total energy used, and NO _x and SO _x emissions were 23.2, 19.4, 19.5, and 25.3 %, respectively, which were caused by chemical and electricity demands for system operation. In conclusion, consumable chemicals such as HCl and NaOH, electric energy consumption for system operation, and equipment use for soil excavation were determined to be the major sources of environmental pollution to occur during the soil washing process. Especially, the acid-based chemical extraction process should be avoided in order to improve the sustainability of soil washing processes.     

Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation

We investigated variations in the relative sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NO_x) as inferred from the ratio of the tropospheric columns of formaldehyde to nitrogen dioxide (the “Ratio”) from the Aura Ozone Monitoring Instrument (OMI). Our modeling study suggests that ozone formation decreases with reductions in VOCs at Ratios <1 and NO_x at Ratios >2; both NO_x and VOC reductions may decrease ozone formation for Ratios between 1 and 2. Using this criteria, the OMI data indicate that ozone formation became: 1. more sensitive to NO_x over most of the United States from 2005 to 2007 because of the substantial decrease in NO_x emissions, primarily from stationary sources, and the concomitant decrease in the tropospheric column of NO₂, and 2. more sensitive to NO_x with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. In cities with relatively low isoprene emissions (e.g., Chicago), the data clearly indicate that ozone formation became more sensitive to NO_x from 2005 to 2007. In cities with relatively high isoprene emissions (e.g., Atlanta), we found that the increase in the Ratio due to decreasing NO_x emissions was not obvious as this signal was convolved with variations in the Ratio associated with the temperature dependence of isoprene emissions and, consequently, the formaldehyde concentration.     

Effects of uncertainty in the reaction of the hydroxyl radical with nitrogen dioxide on model-simulated ozone control strategies

We evaluated the effect of a 20% reduction in the rate constant of the reaction of the hydroxyl radical with nitrogen dioxide to produce nitric acid (OH+NO₂→HNO₃) on model predictions of ozone mixing ratios ([O₃]) and the effectiveness of reductions in emissions of volatile organic compounds (VOC) and nitrogen oxides (NO_x) for reducing [O₃]. By comparing a model simulation with the new rate constant to a base case scenario, we found that the [O₃] increase was between 2 and 6% for typical rural conditions and between 6 and 16% for typical urban conditions. The increases in [O₃] were less than proportional to the reduction in the OH+NO₂ rate constant because of negative feedbacks in the photochemical mechanism. Next, we used two different approaches to evaluate how the new OH+NO₂ rate constant changed the effectiveness of reductions in emissions of VOC and NO_x: first, we evaluated the effect on [O₃] sensitivity to small changes in emissions of VOC (d[O₃]/dE_VOC) and NO_x (d[O₃]/dE_NOx); and secondly, we used the empirical kinetic modeling approach to evaluate the effect on the level of emissions reduction necessary to reduce [O₃] to a specified level. Both methods showed that reducing the OH+NO₂ rate constant caused control strategies for VOC to become less effective relative to NO_x control strategies. We found, however, that d[O₃]/dE_VOC and d[O₃]/dE_NOx did not quantitatively predict the magnitude of the change in the control strategy because the [O₃] response was nonlinear with respect to the size of the emissions reduction. We conclude that model sensitivity analyses calculated using small emissions changes do not accurately characterize the effect of uncertainty in model inputs (in this case, the OH+NO₂ rate constant) on O₃ attainment strategies. Instead, the effects of changes in model inputs should be studied using large changes in precursor emissions to approximate realistic attainment scenarios.     

Effect of Ammonia in Gaseous Fuels On Nitrogen Oxide Emissions

The effect of ammonia in the fuel on NO_x emissions was investigated through laboratory experiments and field burner tests. It was found that the degree of conversion of pm-monia to NO_x was a strong function of excess air, ammonia content in the fuel, and of the degree of mixing in the flame. In premixed laboratory flames concentrations of NO_x above the peak equilibrium amounts were produced. In furnace diffusion flames the conversion to NO_x was much less. At substoichiometric air-fuel ratios all the ammonia appears to pyrolize, forming N₂, and only very little NO_x. Several methods for burning ammonia to produce low NO_x emissions were investigated.     

Identification of sources of atmospheric PM at the Pittsburgh Supersite—Part III: Source characterization

Single-particle mass spectrometry data collected during the Pittsburgh Supersite experiment was used to isolate an episode on 27 October 2001 when the measurement site was primarily influenced by emissions from coal combustion sources. Results showed that (a) 60–80% of the particles detected during this event belonged to the Na/Si/K/Ca/Fe/Ga/Pb particle class associated with coal combustion emissions, (b) observation of this class was an isolated event occurring only during the hours of 06:00–14:00 EST, and (c) the detection of these particles was highly correlated with shifts in wind direction. Coincident SMPS, TEOM PM_2.5, SO₂, NO_x, and O₃ measurements were in excellent agreement with the single-particle results in terms of both identifying and characterizing this event. The three most likely point sources of these particles were isolated and Gaussian plume dispersion models were used in reverse to predict their particle number, particle mass, and gas phase emissions. Calculated mass emission rates were in general agreement with the US EPA National Emissions Inventory (NEI) database emissions estimates and the Title V PM₁₀ limit. The largest of the three sources emits about 2.4×10¹⁷ fine and ultrafine particles per second.     

An Environmental Decision-Making Tool for Evaluating Ground-Level Ozone-Related Health Effects

Abstract

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O₃) exposure. ORAM was coupled with the U.S. Environmental Protection Agency’s (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O₃ concentration and allows the examination of various scenarios in which emission rates of O₃ precursors (basically, oxides of nitrogen [NO_x] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O₃ season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NO_x emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NO_x emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Adjoint inverse modeling of NOx emissions over eastern China using satellite observations of NO2 vertical column densities

A four-dimensional variational data assimilation system for optimization of NO_x emissions (RC4-NO_x) was developed. A parameterized NO_x chemistry scheme was introduced into the RC4-NO_x system, and key parameters such as chemical production and loss terms of NO_x were calculated in advance using the Community Multiscale Air Quality (CMAQ) modeling system. RC4-NO_x was applied to optimize NO_x emissions over eastern China (EC) in July 1996, 1999, and 2002 using Global Ozone Monitoring Experiment (GOME) satellite observations of NO₂ vertical column densities (VCDs) and a priori emissions from the Regional Emission Inventory in Asia (REAS). After assimilation, RC4-NO_x generally reproduced the spatial distribution, regional averaged values, and time evolution of GOME NO₂ VCDs. Over EC, a priori emissions were reduced by 20% in 1996 and by 8% in 1999, whereas a posteriori emissions were almost the same as a priori emissions in 2002. A priori emissions in the Beijing region were reduced by optimization over the whole simulation period. A posteriori emissions over the Yangtze Delta were larger than a priori emissions in 2002, although they were smaller in both 1996 and 1999. As in other areas, a priori emissions over the North China Plain were reduced in 1996; but those over the eastern part of the plain were increased in 1999, and the area of increased emissions moved slightly westward in 2002. In each region, the growth rates of a posteriori emissions during both 1996–1999 and 1999–2002 became generally larger than those of a priori emissions, and the trends of a posteriori emissions became similar to those of GOME NO₂ VCDs. Our inverse modeling analysis indicates that the rate of increase of NO_x emissions over EC from 1996 to 2002 was much larger for a posteriori emissions (49%) than for a priori emissions (19%).     

Nitrogen oxide emission calculation for post-Panamax container ships by using engine operation power probability as weighting factor: A slow-steaming case

In this study, the nitrogen oxide (NO_x) emission factors and total NO_x emissions of two groups of post-Panamax container ships operating on a long-term slow-steaming basis along Euro–Asian routes were calculated using both the probability density function of engine power levels and the NO_x emission function. The main engines of the five sister ships in Group I satisfied the Tier I emission limit stipulated in MARPOL (International Convention for the Prevention of Pollution from Ships) Annex VI, and those in Group II satisfied the Tier II limit. The calculated NO_x emission factors of the Group I and Group II ships were 14.73 and 17.85 g/kWhr, respectively. The total NO_x emissions of the Group II ships were determined to be 4.4% greater than those of the Group I ships. When the Tier II certification value was used to calculate the average total NO_x emissions of Group II engines, the result was lower than the actual value by 21.9%. Although fuel consumption and carbon dioxide (CO₂) emissions were increased by 1.76% because of slow steaming, the NO_x emissions were markedly reduced by 17.2%. The proposed method is more effective and accurate than the NO_x Technical Code 2008. Furthermore, it can be more appropriately applied to determine the NO_x emissions of international shipping inventory.

Implications: The usage of operating power probability density function of diesel engines as the weighting factor and the NO_x emission function obtained from test bed for calculating NO_x emissions is more accurate and practical. The proposed method is suitable for all types and purposes of diesel engines, irrespective of their operating power level. The method can be used to effectively determine the NO_x emissions of international shipping and inventory applications and should be considered in determining the carbon tax to be imposed in the future.     

Analysis and modelling of the pollutant emissions from European cars regarding the driving characteristics and test cycles

Within the European research project ARTEMIS, significant works have been conducted to analyse the hot emissions of pollutant from the passenger cars regarding the driving cycles and to propose modelling approaches taking into account large but heterogeneous datasets recorded in Europe. The review and analysis of a large range of test cycles enabled first the building-up of a set of contrasted cycles specifically designed for characterizing the influence of the driving conditions. These cycles were used for the measurement of the pollutants emission rates from nine passenger cars on a chassis dynamometer.Emissions measured on 30 vehicles tested on cycles adapted to their motorization (i.e., cycles for high- or low-powered cars, inducing thus a significant difference in the dynamic) were also considered for analysing the influence of the cycles and of the kinematic parameters on the hot emission rates of the regulated pollutants (CO, HC, NO_x, CO₂, PM). An analyses of variance demonstrated the preponderance of the driving type (urban, rural road, motorway), of the vehicle category (fuel, emission standard) and emitting status (high/normal emitter) and thus the pertinence of analysing and modelling separately the corresponding emissions. It also demonstrated that Urban driving led systematically to high diesel emission rates and to high CO₂, HC and NO_x emissions from petrol cars. Congested driving implied high CO₂ (diesel and petrol) and high diesel NO_x emission. On motorway, the very high speeds generated high CO₂, while unsteady speeds induced diesel NO_x and petrol CO over-emissions. A search for pertinent kinematic parameters showed that urban diesel emissions were mostly sensitive to stops and speed parameters, while petrol emissions were rather sensitive to acceleration parameters. On the motorway, diesel NO_x and CO₂ emissions rates increased with the speed variability and occurrence of high speeds, while CO₂ and CO over-emission from petrol cars were linked to the occurrence of strong acceleration at high speeds.A modelling approach based on partial least square regression was tested, which demonstrates its ability to discriminate satisfactorily the emissions according to dynamic related parameters and in particular when considering the two-dimensionnal distribution of instantaneous speed and acceleration.Finally, a strategy was proposed to analyse the large but heterogeneous set of hot emission data collected within the ARTEMIS project. The approach consisted in analysing the similarity of the numerous cycles as regards their kinematic, grouping them into reference test patterns through an automatic clustering, and then computing reference emissions for these patterns. These principles enabled the development of a method to compute the emissions at a low spatial scale, i.e. the so-called traffic situation approach, which was implemented in the European Artemis model for estimating the cars’ pollutant emissions.