High-resolution Emission Inventory Research Articles

Emission inventories of primary particles and pollutant gases for China

Detailed high-resolution emission inventories of primary particles (PM2.5, BC and OC) and pollutant gases (SO2, NOx, NH3, CO and VOCs) for China in 2007 were constructed on the basis of the latest fuel consumption data, mostly at the county level, and from socio-economic statistics and data on fossil and biomass fuels obtained from government agencies. New emission factors reflecting local features were also used. The calculated emissions were 13.212 Mt PM2.5, 1.4 Mt BC, 2.946 Mt OC, 31.584 Mt SO2, 23.248 Mt NOx, 16.017 Mt NH3, 164.856 Mt CO and 35.464 Mt VOCs. The national and regional emissions were gridded with 0.5° × 0.5° resolution for use in air quality models. Larger emissions were found in eastern and central China than in western China. The emissions estimated here are roughly equal to those obtained in previous studies, but with different contributions from because of seasonal changes in residential heating and biomass combustion. Finally, uncertainties in inventories were analyzed.

Developing a High-Resolution Vehicular Emission Inventory by Integrating an Emission Model and a Traffic Model: Part 2—A Case Study in Beijing

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 × 107 L, 4.28 × 104 t, 1.97 × 103 t, 0.28 × 103 t, and 0.14 × 103 t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.

Developing a High-Resolution Vehicular Emission Inventory by Integrating an Emission Model and a Traffic Model: Part 1—Modeling Fuel Consumption and Emissions Based on Speed and Vehicle-Specific Power

To improve the accuracy and applicability of vehicular emission models, this study proposes a speed and vehicle-specific power (VSP) modeling method to estimate vehicular emissions and fuel consumption using data gathered by a portable emissions monitoring system (PEMS). The PEMS data were categorized into discrete speed-VSP bins on the basis of the characteristics of vehicle driving conditions and emissions in Chinese cities. Speed-VSP modal average rates of emissions (or fuel consumption) and the time spent in the corresponding speed-VSP bins were then used to calculate the total trip emissions (or fuel consumption) and emission factors (or fuel economy) under specific average link speeds. The model approach was validated by comparing it against measured data with prediction errors within 20% for trip emissions and link-speed-based emission factors. This analysis is based on the data of light-duty gasoline vehicles in China; however, this research approach could be generalized to other vehicle fleets in other countries. This modeling method could also be coupled with traffic demand models to establish high-resolution emissions inventories and evaluate the impacts of traffic-related emission control measures.

Dry deposition of polycyclic aromatic hydrocarbons and its influence on surface soil contamination in Tianjin, China

ISCLT3 dispersion model was applied to calculate the flux of dry deposition of polycyclic aromatic hydrocarbons (PAHs) in Tianjin, China based on a high resolution emission inventory. Field observations of dry deposition at 22 sampling sites were used for model validation. The mean deposition flux densities (and standard deviation) of 15 PAHs were 4.62 +/- 2.99 microg m(-2) d(-1) and 2.75 +/- 1.78 microg m(-2) d(-1) in the heating and the non-heating seasons, respectively, with a time-weighted annual mean of 3.37 +/- 1.81 microg m(-2) d(-1) (based on the durations of the heating and non-heating seasons). High fluxes occurred in the urbanized areas as well as near two coke and gasification facilities. It was revealed that PAH concentrations in surface soil were correlated significantly with both dry deposition and soil organic matter content. Accordingly, a linear regression model was developed for predicting surface soil PAH concentration based on deposition flux density and soil organic matter content.

Inhalation exposure to ambient polycyclic aromatic hydrocarbons and lung cancer risk of Chinese population

An Euler atmospheric transport model (Canadian Model for Environmental Transport of Organochlorine Pesticides, CanMETOP) was applied and validated to estimate polycyclic aromatic hydrocarbon (PAH) ambient air concentrations at ground level in China based on a high-resolution emission inventory. The results were used to evaluate lung cancer risk for the Chinese population caused by inhalation exposure to PAHs. The uncertainties of the transport model, exposure, and risk analysis were assessed by using Monte Carlo simulation, taking into consideration the variation in PAH emission, aerosol and OH radical concentrations, dry deposition, respiration rate, and genetic susceptibility. The average benzo[a]pyrene equivalent concentration (B[a]P(eq)) was 2.43 [ approximately 1.29-4.50 as interquartile range (IR)] ng/m(3). The population-weighted B[a]P(eq) was 7.64 (IR, approximately 4.05-14.1) ng/m(3) because of the spatial overlap of the emissions and population density. It was estimated that 5.8% (IR, approximately 2.0-11%) of China's land area, where 30% (IR, approximately 17-43%) of the population lives, exceeded the national ambient B[a]P(eq) standard of 10 ng/m(3). Taking into consideration the variation in exposure concentration, respiration rate, and susceptibility, the overall population attributable fraction (PAF) for lung cancer caused by inhalation exposure to PAHs was 1.6% (IR, approximately 0.91-2.6%), corresponding to an excess annual lung cancer incidence rate of 0.65 x 10(-5). Although the spatial variability was high, the lung cancer risk in eastern China was higher than in western China, and populations in major cities had a higher risk of lung cancer than rural areas. An extremely high PAF of >44% was estimated in isolated locations near small-scale coke oven operations.

Modelling photochemical air pollutant formation in Hungary using an adaptive grid technique

A regional air quality model has been developed that describes the transport and chemical transformation of photochemical oxidants across Central Europe using an adaptive gridding method to achieve high spatial resolution. High-resolution emission inventories for Budapest and Hungary were utilised. The air pollution episode in August 1998 was modelled using a fixed coarse grid (mesh size 70 km) a fixed fine grid (17.5 km) and an adaptive, variable sized (from 17.5 to 70 km) grid. The fine and the adaptive grid models provided similar results, but the latter required 50% longer computing time. High ozone concentrations appeared downwind of Budapest and the plume extended up to about 150 km from the city at 17.00 on the simulated day. The simulation results were compared with ozone concentrations measured at the K-puszta and Hortobagy monitoring stations.

Development of a high-resolution emission inventory for Spain using the SMOKE modelling system: A case study for the years 2000 and 2010

Emission preparation is a critical stage in air quality modelling. The generation of input information from regulatory emission inventories compatible with the requirements of eulerian chemical-transport models needs a computationally efficient, reliable, and flexible emissions data processing system. The Sparse Matrix Operator Kernel System (SMOKE) was developed in the United States and redesigned by the US Environmental Protection Agency to support air quality modelling activities in the framework of the USEPA Models-3 system. In this contribution the adaptation of the SMOKE system to European conditions is discussed. The system has been applied to the Iberian Peninsula and the Madrid Region (Spain) to process Spain's official emission inventories and projections for the years 2000 and 2010. This software tool has been found useful to generate emission input information for the CMAQ model as well as providing a valuable platform for emission scenario analysis. The model has been proved flexible enough to accommodate and process emissions based on the EMEP/CORINAIR methodology, although the lack of meaningful ancillary information may hinder its application outside the US. This study has established a practical methodology for the adaptation of the SMOKE system to Spain and potentially to any other European country.

Identifying the Trans-Boundary Transport of Air Pollutants to the City of Istanbul Under Specific Weather Conditions

In this study, NO2 and SO2 levels during a specific winter episode in the city of Istanbul were researched with regard to the respective impact of weather conditions. The city under study has the largest population and is one of the most polluted cities of Turkey. Furthermore, Istanbul is vulnerable to trans-boundary transport of air pollutants from Europe, because its location is on the eastern end of the Continent, where westerly winds prevail. However, there has neither been any comprehensive study nor any regulation to fix and solve the air quality problem in the city so far. A framework was prepared to model air quality using MM5 for meteorological modeling and CMAQ for transport and chemistry modeling. This study was supported by the tracer and the trajectory investigations over the area of interest. The model results underestimated the concentration of air pollutants over Istanbul as expected. But, in spite of the coarse emission inventory, the similarity of the time series between the model and observation values during the simulation period is very encouraging for future studies. That is to say, the tracer and the trajectory studies indicated that trans-boundary sources are responsible for the poor air quality of Istanbul under specific weather conditions. It must be pointed out, though, that a high-resolution national emission inventory is needed to get more accurate results.

Effects of Ethanol (E85) versus Gasoline Vehicles on Cancer and Mortality in the United States

Ethanol use in vehicle fuel is increasing worldwide, but the potential cancer risk and ozone-related health consequences of a large-scale conversion from gasoline to ethanol have not been examined. Here, a nested global-through-urban air pollution/weather forecast model is combined with high-resolution future emission inventories, population data, and health effects data to examine the effect of converting from gasoline to E85 on cancer, mortality, and hospitalization in the United States as a whole and Los Angeles in particular. Under the base-case emission scenario derived, which accounted for projected improvements in gasoline and E85 vehicle emission controls, it was found that E85 (85% ethanol fuel, 15% gasoline) may increase ozone-related mortality, hospitalization, and asthma by about 9% in Los Angeles and 4% in the United States as a whole relative to 100% gasoline. Ozone increases in Los Angeles and the northeast were partially offset by decreases in the southeast. E85 also increased peroxyacetyl nitrate (PAN) in the U.S. but was estimated to cause little change in cancer risk. Due to its ozone effects, future E85 may be a greater overall public health risk than gasoline. However, because of the uncertainty in future emission regulations, it can be concluded with confidence only that E85 is unlikely to improve air quality over future gasoline vehicles. Unburned ethanol emissions from E85 may result in a global-scale source of acetaldehyde larger than that of direct emissions.

Inventory of black carbon and organic carbon emissions from China

We present detailed high-resolution emission inventories of black carbon (BC) and organic carbon (OC) from China in the year 2000. The latest fuel consumption data, including fossil and biomass fuels and socio-economic statistics were obtained from government agencies, mostly at the county level. Some new emission factors (EFs) from local measurements also were used. National and regional summaries of emissions are presented, and gridded emissions at 0.2°×0.2° resolution are shown. Our calculated emissions were 1500 Gg for BC and 4100 Gg for OC, mainly due to the burning of coal and biofuels. The carbonaceous aerosol emissions estimated here are higher than those in previous studies, mainly because coal burning by rural industries and residences were previously underestimated. More carbonaceous aerosols are emitted from eastern China than western China. A strong seasonal dependence is observed for emissions, with peaks in May and October and low emissions in April and July; this seasonality is mainly due to patterns in residential heating and agriculture waste open burning.

A high-resolution emission inventory for eastern China in 2000 and three scenarios for 2020

We develop a source-specific high-resolution emission inventory for the Shandong region of eastern China for 2000 and 2020. Our emission estimates for year 2000 are higher than other studies for most pollutants, due to our inclusion of rural coal consumption, which is significant but often underestimated. Still, our inventory evaluation suggests that we likely underestimate actual emissions. We project that emissions will increase greatly from 2000 to 2020 if no additional emission controls are implemented. As a result, PM2.5 concentrations will increase; however O3 concentrations will decrease in most areas due to increased NOx emissions and VOC-limited O3 chemistry. Taking Zaozhuang Municipality in this region as a case study, we examine possible changes in emissions in 2020 given projected growth in energy consumption with no additional controls utilized (BAU), with adoption of best available end-of-pipe controls (BACT), and with advanced, low-emission coal gasification technologies (ACGT) which are capable of gasifying the high-sulfur coal that is abundant in China. Emissions of NH3 are projected to be 20% higher, NMVOC 50% higher, and all other species 130–250% higher in 2020 BAU than in 2000. Both alternative 2020 emission scenarios would reduce emissions relative to BAU. Adoption of ACGT, which meets only 24% of energy service demand in Zaozhuang in 2020 would reduce emissions more than BACT with 100% penetration. In addition, coal gasification technologies create an opportunity to reduce greenhouse gas emissions by capturing and sequestering CO2 emissions below ground.

The ESCOMPTE program: an overview

In this paper, the “Expérience sur Site pour COntraindre les Modèles de Pollution atmosphérique et de Transport d'Emissions” (ESCOMPTE) program is presented. The ESCOMPTE program is used to produce a relevant set of data for testing and evaluating regional pollution models. It includes high-resolution (in space and time) atmospheric emission inventories and field experiments, and covers an area of 120×120 km, centered over the Marseilles-Berre area in the southeast of France during Summer 2001. This region presents a high occurrence of photochemical pollution events, which result from numerous industrial and urban sources of primary pollutants. From the dynamical characteristics of the area, sea-breeze circulation and channeling effects due to terrain features highly influence the location of the pollutant plumes. ESCOMPTE will provide a highly documented framework for dynamics and chemistry studies. Campaign strategies and experimental set up are described. During the planning phase, existing modeling results helped defining the experimental design. The campaign involved surface measurement networks, remote sensing, ship-borne, balloon-borne, and airplane measurements. Mean standard meteorological parameters and turbulent fluxes, ozone, ozone precursors, photochemically active trace gases, and aerosols were measured. Five intensive observation periods (IOPs) were documented using a wide spectrum of instruments, involving aircraft (7) (one of them equipped with a Doppler lidar, the others for in situ meteorological and chemical measurements), constant volume balloons (33), ozone lidars (5), wind profilers (15 sodars and radars), Doppler scanning lidar (1), radiosonde systems (at 4 locations), instrumented ships (2). In addition to the air quality networks from environmental agencies, 15 supplementary ground stations equipped for chemistry and/or meteorology and/or surface flux measurements, were operational. All instruments were calibrated and compared during a Quality Control/Quality Assurance (QC/QA) week, at the very beginning of the campaign. Fifteen days were intensively documented during five IOPs, referenced as 1, 2a, 2b, 3, and 4. High pollution levels were encountered during sea-breeze conditions observed during IOPs 2b and 3, whereas IOPs 2a and 4 corresponded to moderate wind, and channeled plume regimes. In addition, hourly emissions inventories for all IOPs were established to complete data sets and to finalize the ESCOMPTE database (EDB). Two other projects were associated to ESCOMPTE: urban boundary layer (UBL) and tropospheric water vapor content by GPS tomography (GPS/H 2O). They took advantage of the scientific environment provided by ESCOMPTE.

A country-specific, high-resolution emission inventory for methane from livestock in Asia in 2000

Methane emissions from livestock in South, Southeast, and East Asia were estimated to be about 29.9 Tg CH4 in 2000 using the Food and Agriculture Organization database and district-level data on regional activity and emission factors, considering regional specificities. These emissions consisted of 25.9 Tg CH4 from enteric fermentation and 4.0 Tg CH4 from livestock manure management systems. India had the greatest production, with 11.8 Tg CH4 from livestock, primarily cattle and buffaloes. China was also a high-emission country, producing about 10.4 Tg CH4. To determine their spatial distribution, emissions at the country and district levels were plotted on a 0.5×0.5° grid according to weight, using high-resolution land cover/use datasets. This gridded database shows considerable emissions throughout the Ganges basin, with peak emissions exceeding 30 Gg CH4 grid−1 in the Ganges River delta. The total methane emissions from livestock increased by an average of 2% per annum from 1965 to 2000. The recent increase in methane emissions in China was especially remarkable.

CONSTRUCTING A HIGH RESOLUTION AIR POLLUTION MAP OF EUROPE FOR EPIDEMIOLOGICAL APPLICATIONS

Air pollution epidemiology faces the problem of searching for small increases in risk against a background of great uncertainty and noise in the available environmental and health data. It is therefore essential both to be able to combine and compare results from local-scale studies, and to conduct large, population level studies over wide geographical areas. Both of these approaches are typically hampered by the lack of consistent data on air pollution, and the use of different methods and measures of exposure assessment. The APMoSPHERE (Air Pollution Modelling for Support to Policy on Health, Environment and Risk management in Europe) project is aimed at using GIS and remote sensing methods to develop a set of consistent air pollution maps (for PM10, black smoke, SO2, NO2, CO and O3), at a spatial resolution of ca. 1km, for the whole of the European Union, that can be used for both epidemiological and policy purposes. Different modelling approaches are being developed and assessed including: a) the compilation of high resolution emissions inventories by disaggregating national emission statistics to the local level, using land cover, socio-economic and other data; b) use of geostatistical and stochastic methods to model spatial variations in air pollution; c) development of a landscape stratification system for modelling air pollution; d) use of Bayesian hierarchical modelling techniques to model time-space variations in air pollutionl e) evaluation of the use of satellite data to monitor urban and regional variations in air pollution.

High-resolution emission inventory of the Lombardy region: development and comparison with measurements

Abstract In the framework of the EUROTRAC-2 subproject limitation of oxidant production an emission inventory was developed for the Lombardy region in Italy with a 1 h temporal and 3 km spatial resolution. The emissions were processed in a bottom-up approach. We outline the emissions processing strategy used and summarize the inventory characteristics. Spatial maps and diurnal series charts of the total emissions of nitrogen oxides (NO x ), carbon monoxide CO, volatile organic compounds (VOC) are provided. The emission inventory shows distinct patterns for the urban area and the non-metropolitan region. We compare ratios of CO to NO x and CO to different VOC-classes between the emission inventory and measurements performed at two sites representative for the urban and non-metropolitan areas. Ratios were determined from the slopes of correlations between CO and the respective species class. Observed CO/NO x ratios are higher in the urban and non-metropolitan area by factors of 2 and 3, respectively. CO/VOC ratios show different discrepancies depending on the VOC-class but are generally lower in the emission inventory. Observations at the two sites yielded similar concentration ratios opposite to the inventory.

Simulation of air pollution with nested models in North Rhine-Westphalia

High resolution modeling of air pollution events requires nested models. CARLOS is a combination of two comprehensive air quality simulation models that calculate chemistry and transport on regional and local scales. Both models apply nesting techniques to describe the influx of tracers into the inner highly resolved modeling domain. High resolution emission inventories are available for the innermost nest on the large scale, which allow the separate treatment of traffic and point sources. Results of a simulation for North Rhine-Westphalia in August 1997 are presented for two nesting levels, increasing the resolution from 27 km in Central Europe to 3 km in the domain of the second nest. One result is also presented for the local scale employing two nesting levels with a resolution of 1 km and 333m, respectively. Statistical indices are used to indicate the quality of the predictions of ozone. Comparison of observations at the stations Köln-Chorweiler and Wuppertal with modeled concentrations shows good agreement of ozone and reasonable reproduction of NO 2 concentrations.

Temporal disaggregation of travel demand for high resolution emissions inventories

The commonly used photochemical air quality model, the Urban Airshed Model (UAM), requires emission estimates with grid-based, hourly resolution. In contrast, travel demand models, used to simulate the travel activity model inputs for the transportation-related emissions estimation, typically only provide traffic volumes for a specific travel period (e.g. the a.m. and p.m. peak periods). A few transportation agencies have developed procedures to allocate period-based travel demand data into hourly emission inventories for regional grid cells. Because there was no theoretical framework for disaggregating period-based volumes to hourly volumes, application of these procedures frequently relied upon a single hypothetical hourly distribution of travel volumes. This study presents a new theoretical modeling framework that integrates traffic count data and travel demand model link volume estimates to derive intra-period hourly volume estimates by trip purpose. We propose a new interpretation of the model coefficients and define hourly allocation factors by trip purpose. These allocation factors can be used to disaggregate the travel demand model ‘period-based’ simulation volumes into hourly resolution, thereby improving grid-based, hourly emission estimates in the UAM.

Implications of Transient Mode Duration for Spatially Disaggregated High-Resolution Emission Inventory Studies

High resolution emission inventory studies, such as urban air-shed modeling, often use spatially disaggregated emission parameters in the form of link-specific emissions. A key input variable that influences operating mode mix on highway links is the transient mode duration (TMD) in which start-related emissions occur. The TMD variable also establishes the emission rates to be embedded in emission factor models. The basic emission rates built into the MOBILE model are based on a TMD of 505 seconds, which was based on the federal test procedure (FTP). For newer vehicles, it is indicated that the TMD is much less than 505 seconds. This study examines the effects of variations in TMD on the distribution of cold and hot transient VMT on network links, as well as their effect on overall emissions. A network assignment model developed to track operating modes of vehicles on network links was used on a large California city network. The MOBILE model was used to derive bag-specific emission rates. The experiment includes a series of traffic assignment runs with varying TMD and postprocessing of the assignment output. Link-specific distribution of operating mode mix and total emissions were derived. It is indicated that TMD significantly influences the distribution of operating modes, as well as total emissions. The results indicate that as the TMD decreases, the share of cold transient VMT from freeways diminishes, while that of the local roads increases. It was indicated that total emissions on various link groups may fall within a range of 90 to 300 percent of the total emissions derived from the present FTP duration of 505 seconds. It is recommended that the transient mode duration variable be reexamined for deriving emission rates to be embedded in the future versions of emission factor models.