Characterization of gaseous pollutant and particulate matter emission rates from a commercial broiler operation part II: Correlated emission rates

Emission rates of ammonia, acid gases, inorganic aerosols, methane, and size fractionated particulate matter were measured from a commercial broiler facility. This paper discusses the statistically influential parameters on numerous pollutants’ emission from a broiler chicken facility and generates emission correlations to fill data gaps and develop averaged emission factors.Live mass of the birds was commonly a significant variable to each pollutant’s emission. Some variables significantly impacted the pollutants’ emissions, such as litter moisture content, but were measured discretely and cannot be used for filling in data gaps.House parameter correlations were, therefore, developed using parameters measured at the facility, such as indoor temperature, relative humidity, and the live mass of the birds, and relied on the mutual behaviour of discretely measured explanatory parameters and continuously monitored confounding variables. The live mass and the difference in the indoor temperature and the house set-point temperature were the most significant variables in each pollutant’s correlation.The correlations predicted each pollutants emission to within 20% (total mass basis) over most broiler production cycles. Their validation on independent datasets also successfully estimated the flocks’ emissions to within 3%.Emission factors (EFs) were developed for methane, ammonia, and size fractionated particulate matter using measured data and correlated emissions to fill in data gaps. PM₁₀ (particulate matter ≤10 microns) EFs were estimated to be 4.6 and 5.9 g d^?1 [Animal Unit, AU]^?1 for five and six week production cycles, respectively. PM_2.5 (PM ≤ 2.5 microns) EFs were 0.8 and 1.4 g d^?1 AU^?1 for five and six week cycles, respectively. Ammonia and methane emission factors were estimated at 120.8 and 197.0 g d^?1 AU^?1, respectively for a five week production cycle.     

Global atmospheric emission inventory of polycyclic aromatic hydrocarbons (PAHs) for 2004

The global atmospheric emissions of the 16 polycyclic aromatic hydrocarbons (PAHs) listed as the US EPA priority pollutants were estimated using reported emission activity and emission factor data for the reference year 2004. A database for emission factors was compiled, and their geometric means and frequency distributions applied for emission calculation and uncertainty analysis, respectively. The results for 37 countries were compared with other PAH emission inventories. It was estimated that the total global atmospheric emission of these 16 PAHs in 2004 was 520 giga grams per year (Gg y^?1) with biofuel (56.7%), wildfire (17.0%) and consumer product usage (6.9%) as the major sources, and China (114 Gg y^?1), India (90 Gg y^?1) and United States (32 Gg y^?1) were the top three countries with the highest PAH emissions. The PAH sources in the individual countries varied remarkably. For example, biofuel burning was the dominant PAH source in India, wildfire emissions were the dominant PAH source in Brazil, while consumer products were the major PAH emission source in the United States. In China, in addition to biomass combustion, coke ovens were a significant source of PAHs. Globally, benzo(a)pyrene accounted for 0.05% to 2.08% of the total PAH emission, with developing countries accounting for the higher percentages. The PAH emission density varied dramatically from 0.0013 kg km^?2 y in the Falkland Islands to 360 kg km^?2 y in Singapore with a global mean value of 3.98 kg km^?2 y. The atmospheric emission of PAHs was positively correlated to the country's gross domestic product and negatively correlated with average income. Finally, a linear bivariate regression model was developed to explain the global PAH emission data.     

Broadband UV spectroscopy system used for monitoring of SO2 and NO emissions from thermal power plants

A gas monitoring system based on broadband absorption spectroscopic techniques in the ultraviolet region is described and tested. The system was employed in real-time continuous concentration measurements of sulfur dioxide (SO₂) and nitric oxide (NO) from a 220-ton h^?1 circulating fluidized bed (CFB) boiler in Shandong province, China. The emission coefficients (per kg of coal and per kWh of electricity) and the total emission of the two pollutant gases were evaluated. The measurement results showed that the emission concentrations of SO₂ and NO from the CFB boiler fluctuated in the range of 750–1300 mg m^?3 and 100–220 mg m^?3, respectively. Compared with the specified emission standards of air pollutants from thermal power plants in China, the values were generally higher for SO₂ and lower for NO. The relatively high emission concentrations of SO₂ were found to mainly depend on the sulfur content of the fuel and the poor desulfurization efficiency. This study indicates that the broadband UV spectroscopy system is suitable for industrial emission monitoring and pollution control.     

Methane emission from free-ranging sheep: a comparison of two measurement methods

Methane emissions from a flock of 14, 1-year old sheep grazing on a grass and legume pasture were measured using a micrometeorological mass-balance method and a sulphur hexaflouride (SF₆) tracer technique. The former measured the mean emission, over 45 min intervals, from all the sheep within a fenced 24 m×24 m enclosure, from the enrichment of methane (CH₄) in air as it passed over the sheep. The tracer technique measured emissions from a subset of 7 individual animals over 24 h periods from measurements of CH₄ and SF₆ concentrations in air exhaled by the sheep, and from the known rate of release of SF₆ from small permeation tubes placed in the animals’ rumens. Both methods gave highly similar results for 4 out of 5 days. When the species composition of dietary intake was steady during the last two days of measurement, the mean emission rate from the mass-balance method was 11.9±1.5 (SEM) g CH₄ sheep^-1 d^-1, while the rate from the tracer technique was 11.7±0.4 (SEM) g CH₄ sheep^-1 d^-1. These rates are for sheep with mean live mass of 27 kg, with a measured dry matter intake of 508 g sheep^-1 d^-1 and pasture dry matter digestibility of 69.5%. There was close agreement between these measurements and estimates from algorithms used to predict methane emissions from sheep for the Australian National Greenhouse Gas Inventory.     

Ethanol emission from loose corn silage and exposed silage particles

Silage on dairy farms has been identified as a major source of volatile organic compound (VOC) emissions. However, rates of VOC emission from silage are not accurately known. In this work, we measured ethanol (a dominant silage VOC) emission from loose corn silage and exposed corn silage particles using wind tunnel systems. Flux of ethanol was highest immediately after exposing loose silage samples to moving air (as high as 220 g m^?2 h^?1) and declined by as much as 76-fold over 12 h as ethanol was depleted from samples. Emission rate and cumulative 12 h emission increased with temperature, silage permeability, exposed surface area, and air velocity over silage samples. These responses suggest that VOC emission from silage on farms is sensitive to climate and management practices. Ethanol emission rates from loose silage were generally higher than previous estimates of total VOC emission rates from silage and mixed feed. For 15 cm deep loose samples, mean cumulative emission was as high as 170 g m^?2 (80% of initial ethanol mass) after 12 h of exposure to an air velocity of 5 m s^?1. Emission rates measured with an emission isolation flux chamber were lower than rates measured in a wind tunnel and in an open setting. Results show that the US EPA emission isolation flux chamber method is not appropriate for estimating VOC emission rates from silage in the field.     

Measurement of total site mercury emissions from a chlor-alkali plant using ultraviolet differential optical absorption spectroscopy and cell room roof-vent monitoring

This technical note describes a United States Environmental Protection Agency (U.S. EPA) measurement project to determine elemental mercury (Hg⁰) emissions from a mercury cell chlor-alkali (MCCA) facility in the southeastern U.S. during a 53-day monitoring campaign in the fall of 2006. The optical remote sensing (ORS) area source measurement method EPA OTM 10 was used to provide Hg⁰ flux data for the site. These results are reported and compared with cell room roof-vent monitoring data acquired by the facility for similar time periods. The 24-h extrapolated mercury emission rate estimates determined by the two monitoring approaches are shown to be similar with overall averages in the 400 g day^?1 range with maximum values around 1200 g day^?1. Results from the OTM 10 measurements, which include both cell room emissions and potential fugitive sources outside the cell room, are shown to be approximately 10% higher than cell room monitoring results indicating that fugitive emissions from outside the cell room produce a small but measurable effect for this site.     

Establishment of a database of emission factors for atmospheric pollutants from Chinese coal-fired power plants

Field measurements and data investigations were conducted for developing an emission factor database for inventories of atmospheric pollutants from Chinese coal-fired power plants. Gaseous pollutants and particulate matter (PM) of different size fractions were measured using a gas analyzer and an electric low-pressure impactor (ELPI), respectively, for ten units in eight coal-fired power plants across the country. Combining results of field tests and literature surveys, emission factors with 95% confidence intervals (CIs) were calculated by boiler type, fuel quality, and emission control devices using bootstrap and Monte Carlo simulations. The emission factor of uncontrolled SO₂ from pulverized combustion (PC) boilers burning bituminous or anthracite coal was estimated to be 18.0S kg t^?1 (i.e., 18.0 × the percentage sulfur content of coal, S) with a 95% CI of 17.2S–18.5S. NO_X emission factors for pulverized-coal boilers ranged from 4.0 to 11.2 kg t^?1, with uncertainties of 14–45% for different unit types. The emission factors of uncontrolled PM_2.5, PM₁₀, and total PM emitted by PC boilers were estimated to be 0.4A (where A is the percentage ash content of coal), 1.5A and 6.9A kg t^?1, respectively, with 95% CIs of 0.3A–0.5A, 1.1A–1.9A and 5.8A–7.9A. The analogous PM values for emissions with electrostatic precipitator (ESP) controls were 0.032A (95% CI: 0.021A–0.046A), 0.065A (0.039A–0.092A) and 0.094A (0.0656A–0.132A) kg t^?1, and 0.0147A (0.0092–0.0225A), 0.0210A (0.0129A–0.0317A), and 0.0231A (0.0142A–0.0348A) for those with both ESP and wet flue-gas desulfurization (wet-FGD). SO₂ and NO_X emission factors for Chinese power plants were smaller than those of U.S. EPA AP-42 database, due mainly to lower heating values of coals in China. PM emission factors for units with ESP, however, were generally larger than AP-42 values, because of poorer removal efficiencies of Chinese dust collectors. For units with advanced emission control technologies, more field measurements are needed to reduce emission factor uncertainties.     

Sulfuric odorous compounds emitted from pig-feeding operations

The objective of the study was to quantify the concentration and emission levels of sulfuric odorous compounds emitted from pig-feeding operations. Five types of pig-housing rooms were studied: gestation, farrowing, nursery, growing and fattening rooms. The concentration range of sulfuric odorous compounds in these pig-housing rooms were 30–200 ppb for hydrogen sulfide (H₂S), 2.5–20 ppb for methyl mercaptan (CH₃SH), 1.5–12 ppb for dimethyl sulfide (DMS; CH₃SCH₃) and 0.5–7 ppb for dimethyl disulfide (DMDS; CH₃S₂CH₃), respectively. The emission rates of H₂S, CH₃SH, DMS and DMDS were estimated by multiplying the average concentration (mg m⁻³) measured near the air outlet by the mean ventilation rate (m³ h⁻¹) and expressed either per area (mg m⁻² h⁻¹) or animal unit (AU; liveweight of the pig, 500 kg) (mg pig⁻¹ h⁻¹). As a result, the emission rates of H₂S, CH₃SH, DMS and DMDS in the pig-housing rooms were 14–64, 0.8–7.3, 0.4–3.4 and 0.2–1.9 mg m⁻² h⁻¹, respectively, based on pig's activity space and 310–723, 18–80, 9–39 and 5–22 mg AU⁻¹ h⁻¹, respectively, based on pig's liveweight, which indicates that their emission rates were similar, whether based upon the pig's activity space or liveweight. In conclusion, the concentrations and emission rates of H₂S were highest in the fattening room followed by the growing, nursery, farrowing and gestation rooms whereas those of CH₃SH, DMS and DMDS concentrations were largest in the growing room followed by the nursery, gestation and farrowing rooms.     

Gaseous emissions from outdoor concrete yards used by livestock

Measurements of ammonia (NH₃), nitrous oxide (N₂O) and methane (CH₄) were made from 11 outdoor concrete yards used by livestock. Measurements of NH₃ emission were made using the equilibrium concentration technique while closed chambers were used to measure N₂O and CH₄ emissions. Outdoor yards used by livestock proved to be an important source of NH₃ emission. Greatest emission rates were measured from dairy cow feeding yards, with a mean of 690 mg NH₃-N m⁻² h⁻¹. Smaller emission rates were measured from sheep handling areas, dairy cow collecting yards, beef feeding yards and a pig loading area, with respective mean emission rates of 440, 280, 220 and 140 mg NH₃-N m⁻² h⁻¹. Emission rates of N₂O and CH₄ were much smaller and for CH₄, in particular, emission rates were influenced greatly by the presence or absence of dung on the measurement area.     

Using a dispersion model to estimate emission rates of particulate matter from paved roads

From January 1996 to June 1997, we carried out a series of measurements to estimate emissions of PM₁₀ from paved roads in Riverside County, California. The program involved the measurement of upwind and downwind vertical profiles of PM₁₀, in addition to meteorological variables such as wind speed and vertical turbulent intensity. This information was analyzed using a new dispersion model that incorporates current understanding of micrometeorology and dispersion. The emission rate was inferred by fitting model predictions to measurements. The inferred emission factors ranged from 0.2 g VKT^-1 for freeways to about 3 g VKT^-1 for city roads. The uncertainty in these factors is estimated to be approximately a factor of two since the contributions of paved road PM₁₀ emissions to ambient concentrations were comparable to the uncertainty in the mean value of the measurement. At this stage, our best estimate of emission factor lies between 0.1 and 10 g VKT^-1; there is some indication that it is about 0.1 g VKT^-1 for heavily traveled freeways, and is an order of magnitude higher for older city roads. We found that measured silt loadings were poor predictors of emission factors.The measured emission factors imply that paved road emissions may contribute about 30% to the total PM₁₀ emissions from a high traffic area such as Los Angeles. This suggests that it is necessary to develop methods that are more reliable than the upwind–downwind concentration difference technique.     

On-road remote sensing measurements and fuel-based motor vehicle emission inventory in Hangzhou,China

Motor vehicles are one of the largest sources of air pollutants worldwide. Despite their importance, motor vehicle emissions are inadequately understood and quantified, esp. in developing countries. In this study, the real-world emissions of carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxide (NO) were measured using an on-road remote sensing system at five sites in Hangzhou, China in 2004 and 2005. Average emission factors of CO, HC and NO_x for petrol vehicles of different model year, technology class and vehicle type were calculated in grams of pollutant per unit of fuel use (g l⁻¹) from approximately 32,260 petrol vehicles. Because the availability of data used in traditional on-road mobile source estimation methodologies is limited in China, fuel-based approach was implemented to estimate motor vehicle emissions using fuel sales as a measure of vehicle activity, and exhaust emissions factors from remote sensing measurements. The fuel-based exhaust emission inventories were also compared with the results from the recent international vehicle emission (IVE) model. Results show that petrol vehicle fleet in Hangzhou has significantly high CO emissions, relatively high HC and low NO_x, with the average emission factors of 193.07±15.63, 9.51±2.40 and 5.53±0.48 g l⁻¹, respectively. For year 2005 petrol vehicles exhaust emissions contributed with 182,013±16,936, 9107±2255 and 5050±480 metric ton yr⁻¹ of CO, HC and NO_x, respectively. The inventories are 45.5% higher, 6.6% higher and 53.7% lower for CO, HC and NO_x, respectively, than the estimates using IVE travel-based model. In addition, a number of insights about the emission distributions and formation mechanisms have been obtained from an in-depth analysis of these results.     

Benzene,toluene, ozone,NO2 and SO2 measurements in an urban street canyon in Thessaloniki,Greece

Benzene, toluene, sulphur dioxide, ozone and nitrogen dioxide were measured at a mean level of 13.5 m above ground in a narrow, four-lane street canyon (height 30 m, width 20 m) in Thessaloniki, Greece during the period January–July 1997 by means of a commercial differential optical absorption spectrometer (OPSIS DOAS). Primary pollutant levels were found to be 2.5–4.4 times higher during the cold part of the year than during the warm part of the year, the winter/summer ratio increasing with the reaction rate constant with OH for each of the measured species. Ozone, on the other hand, exhibited a winter/summer ratio of 0.36. NO₂ originates from both primary and secondary sources; its winter/summer concentration ratio of 1.4 lies, therefore, between those of primary pollutants and ozone. Pollution levels were influenced considerably by wind speed, while for the street canyon under study wind direction did not influence pollutant levels considerably. While primary pollution was found to decrease with increasing wind speed, ozone increased. Benzene mean levels during the study period were around 6 ppb and hence much higher than the EU annual limit value of 5 μg m⁻³ (1.44 ppb at STP). Toluene mean levels were around 14 ppb and hence also several times above the WHO recommendation of 2 ppb for 24 h. The apportionment of traffic emissions in four time zones used in most inventories in urban airshed models was tested using benzene and toluene measurements at low (<1 m s⁻¹) wind speeds. The agreement between model emissions and calculated emissions apportionment into the four time zones was good, except for Zone D (23:00–1:59), where model inventory emissions were somewhat too low.     

Greenhouse gas emissions from penguin guanos and ornithogenic soils in coastal Antarctica: Effects of freezing–thawing cycles

In coastal Antarctica, freezing and thawing influence many physical, chemical and biological processes for ice-free tundra ecosystems, including the production of greenhouse gases (GHGs). In this study, penguin guanos and ornithogenic soil cores were collected from four penguin colonies and one seal colony in coastal Antarctica, and experimentally subjected to three freezing–thawing cycles (FTCs) under ambient air and under N₂. We investigated the effects of FTCs on the emissions of three GHGs including nitrous oxide (N₂O), carbon dioxide (CO₂) and methane (CH₄). The GHG emission rates were extremely low in frozen penguin guanos or ornithogenic soils. However, there was a fast increase in the emission rates of three GHGs following thawing. During FTCs, cumulative N₂O emissions from ornithogenic soils were greatly higher than those from penguin guanos under ambient air or under N₂. The highest N₂O cumulative emission of 138.24 μg N₂O–N kg^?1 was observed from seal colony soils. Cumulative CO₂ and CH₄ emissions from penguin guanos were one to three orders of magnitude higher than those from ornithogenic soils. The highest cumulative CO₂ (433.0 mgCO₂–C kg^?1) and CH₄ (2.9 mgCH₄–C kg^?1) emissions occurred in emperor penguin guanos. Penguin guano was a stronger emitter for CH₄ and CO₂ while ornithogenic soil was a stronger emitter for N₂O during FTCs. CO₂ and CH₄ fluxes had a correlation with total organic carbon (TOC) and soil/guano moisture (M_c) in penguin guanos and ornithogenic soils. The specific CO₂–C production rate (CO₂–C/TOC) indicated that the bioavailability of TOC was markedly larger in penguin guanos than in ornithogenic soils during FTCs. This study showed that FTC-released organic C and N from sea animal excreta may play a significant role in FTC-related GHG emissions, which may account for a large proportion of annual fluxes from tundra ecosystems in coastal Antarctica.     

Definition of yearly emission factor of dust and greenhouse gases through continuous measurements in swine husbandry

The object of this study was to develop an accurate estimation method to evaluate the contribution of the various compartments of swine husbandry to dust and GHG (greenhouse gases, CO₂, CH₄ and N₂O) emission into the atmosphere during one year of observation.A weaning, a gestation, a farrowing and a fattening room in an intensive pig house were observed in three different periods (Autumn–Winter, Springtime and Summer, monitoring at least 60% of each period (20% at the beginning, in the middle and at the end) of each cycle).During monitoring, live weight, average live weight gain, number of animals and its variation, type of feed and feeding time were taken into account to evaluate their influence on PM₁₀, or the fraction of suspended particulate matter with an aerodynamic diameter less than or equal to 10 μm [Emission Inventory Guidebook, 2007. B1100 Particle Emissions from Animal Husbandry Activities. Available from: <http://reports.eea.europa.eu/EMEPCORINAIR5/en/B1100vs1.pdf> (accessed October 2008)] and to define GHG emission.The selected piggery had a ventilation control system using a free running impeller to monitor continuously real-time environmental and management parameters with an accuracy of 5%.PM₁₀ concentration was monitored by a sampler (Haz Dust EPAM 5000), either continuously or through traditional gravimetric technique, and the mean value of dust amount collected on the membranes was utilized as a correction factor to be applied to continuously collected data.PM₁₀ concentration amount incoming from inlets was removed from PM₁₀ emission calculation, to estimate the real contribution of pig house dust pollution into atmosphere.Mean yearly emission factor of PM₁₀ was measured in 2 g d^?1 LU^?1 for the weaning room, 0.09 g d^?1 LU^?1 for the farrowing room, 2.59 g d^?1 LU^?1 for the fattening room and 1.23 g d^?1 LU^?1 for the gestation room. The highest PM₁₀ concentration and emission per LU was recorded in the fattening compartment while the lowest value was recorded in the farrowing room.CO₂, CH₄ and N₂O concentrations were continuously measured in the exhaust ducts using an infrared photoacoustic detector IPD (Brüel & Kjaer, Multi-gas Monitor Type 1302, Multipoint Sampler and Doser Type 1303) sampling data every 15 min, for the 60% of the cycles.Yearly emission factor for CO₂ was measured in 5997 g d^?1 LU^?1 for the weaning room, 1278 g d^?1 LU^?1 for the farrowing room, 13,636 g d^?1 LU^?1 for the fattening room and 8851 g d^?1 LU^?1 for the gestation room.Yearly emission factor for CH₄ was measured in 24.57 g d^?1 LU^?1 for the weaning room, 4.68 g d^?1 LU^?1 for the farrowing room, 189.82 g d^?1 LU^?1 for the fattening room and 132.12 g d^?1 LU^?1 for the gestation room.Yearly emission factor for N₂O was measured in 3.62 g d^?1 LU^?1 for the weaning room, 0.66 g d^?1 LU^?1 for the farrowing room, 3.26 g d^?1 LU^?1 for the fattening room and 2.72 g d^?1 LU^?1 for the gestation room.     

Estimation of wind blown dust emissions in Europe and its vicinity

The assessment of the wind blown dust emission for Europe and selected regions of North Africa and Southwest Asia was carried out using a mesoscale model. The mesoscale model was parameterized based on the current literature review. The model provides data on PM₁₀ emission from several dust reservoirs (anthropogenic, agriculture, semi- and natural) with spatial resolution of 10 × 10 km and temporal resolution of 1 h. The spatial variability of PM₁₀ emission depends on soil texture, land cover/land use as well as meteorological conditions. Lands covered with water or permanently wet were excluded from the model. The land covered with vegetation is treated as dust reservoir whose dust emission capacity depends on the type of vegetation and cover. The dust reservoirs are divided into reservoirs with stable and unstable surface. The changes of emission in time depend on meteorological parameters.The wind blown dust emission should be treated as a non-continuous spatio-temporal process. The emissions are estimated with high uncertainty. The estimated PM₁₀ yearly total load emitted by wind from the European territory is highly differentiated in space and time and is equal to 0.74 Tg. The total load of PM₁₀ emitted by wind from North African and Southwest Asian land surface located in the vicinity of European boundaries is assessed as nearly 50% (0.43 Tg) of the total load estimated for the whole Europe.The average yearly PM₁₀ emission factor for Europe was estimated at 0.139 Mg km^?2.The PM₁₀ emission from agricultural areas is estimated at 52% of the total wind blown emission from the domain of the European Union project “Improving and applying methods for the calculation of natural and biogenic emissions and assessment of impacts to the air quality” - NatAir.PM₁₀ emission factor for natural areas of Europe is estimated at 0.021 Mg km^?2. Appropriate factors for agricultural areas and anthropogenic areas are 0.157 Mg km^?2 and 0.118 Mg km^?2, respectively. The latter two factors are probably underestimated due to omitting in the model of other dust emission mechanisms than aeolian erosion.     

Methane emissions from an anaerobic swine lagoon

Gaseous methane (CH₄) emissions from a swine waste holding lagoon were determined periodically during the year. Micrometeorological techniques were used in order that emission rates from the lagoon were measured under ambient conditions with little disturbance to the natural environment. During the cold winter measurement period, CH₄ fluxes were linearly related to lagoon water temperature below 22°C (r=0.87). During warmer measurement periods, both water and air temperatures and windspeed affected emissions rates. In general, flux rates followed a diurnal pattern with greater fluxes during the day when both temperature and windspeed were greatest. Mathematical models using air and water temperature and windspeed factors could explain 47 to 75% of the variation in fluxes. Daily emission rates ranged from 1 to 500 kg CH₄ ha⁻¹ d⁻¹. The average flux for the year was 52.3 kg CH₄ ha⁻¹ d⁻¹ which corresponded to about 5.6 kg CH₄ animal⁻¹ yr⁻¹ from the primary lagoon.     

Decadal reductions of traffic emissions on a transit route in Austria – results of the Tauerntunnel experiment 1997

Real-world emissions of a traffic fleet on a transit route in Austria were determined in the Tauerntunnel experiment in October 1997. The total number of vehicles and the average speed was nearly the same on both measuring days (465 vehicles 30 min⁻¹ and 76 km h⁻¹ on the workday, 477 and 78 km h⁻¹ on Sunday). The average workday fleet contained 17.6% heavy-duty vehicles (HDV) and the average Sunday fleet 2.8% HDV resulting in up to four times higher emission rates per vehicle per km on the workday than on Sunday for most of the regulated components (CO₂, CO, NO_x, SO₂, and particulate matter-PM10). Emission rates of NMVOC accounted for 200 mg vehicle⁻¹ km⁻¹ on both days. The relative contributions of light-duty vehicles (LDV) and HDV to the total emissions indicated that aldehydes, BTEX (benzene, toluene, ethylbenzene, xylenes), and alkanes are mainly produced by LDV, while HDV dominated emissions of CO, NO_x, SO₂, and PM10. Emissions of NO_x caused by HDV were 16,100 mg vehicle⁻¹ km⁻¹ (as NO₂). Produced by LDV they were much lower at 360 mg vehicle⁻¹ km⁻¹. Comparing the emission rates to the results that were obtained by the 1988 experiment at the same place significant changes in the emission levels of hydrocarbons and CO, which accounted 1997 to only 10% of the levels in 1988, were noticed. However, the decrease of PM has been modest leading to values of 80 and 60% of the levels in 1988 on the workday and on Sunday, respectively. Emission rates of NO_x determined on the workday in 1997 were 3130 mg vehicle⁻¹ km⁻¹ and even higher than in 1988 (2630 mg vehicle⁻¹ km⁻¹), presumable due to the increase of the HD-traffic.     

China's grazed temperate grasslands are a net source of atmospheric methane

A budget for the methane (CH₄) cycle in the Xilin River basin of Inner Mongolia is presented. The annual CH₄ budget in this region depends primarily on the sum of atmospheric CH₄ uptake by upland soils, emission from small wetlands, and emission from grazing ruminants (sheep, goats, and cattle). Flux rates for these processes were averaged over multiple years with differing summer rainfall. Although uplands constitute the vast majority of land area, they consume much less CH₄ per unit area than is emitted by wetlands and ruminants. Atmospheric CH₄ uptake by upland soils was ?3.3 and ?4.8 kg CH₄ ha^?1 y^?1 in grazed and ungrazed areas, respectively. Average CH₄ emission was 791.0 kg CH₄ ha^?1 y^?1 from wetlands and 8.6 kg CH₄ ha^?1 y^?1 from ruminants. The basin area-weighted average of all three processes was 6.8 kg CH₄ ha^?1 y^?1, indicating that ruminant production has converted this basin to a net source of atmospheric CH₄. The total CH₄ emission from the Xilin River basin was 7.29 Gg CH₄ y^?1. The current grazing intensity is about eightfold higher than that which would result in a net zero CH₄ flux. Since grazing intensity has increased throughout western China, it is likely that ruminant production has converted China's grazed temperate grasslands to a net source of atmospheric CH₄ overall.     

Inventory of aerosol and sulphur dioxide emissions from India: I—Fossil fuel combustion

A comprehensive, spatially resolved (0.25°×0.25°) fossil fuel consumption database and emissions inventory was constructed, for India, for the first time. Emissions of sulphur dioxide and aerosol chemical constituents were estimated for 1996–1997 and extrapolated to the Indian Ocean Experiment (INDOEX) study period (1998–1999). District level consumption of coal/lignite, petroleum and natural gas in power plants, industrial, transportation and domestic sectors was 9411 PJ, with major contributions from coal (54%) followed by diesel (18%). Emission factors for various pollutants were derived using India specific fuel characteristics and information on combustion/air pollution control technologies for the power and industrial sectors. Domestic and transportation emission factors, appropriate for Indian source characteristics, were compiled from literature. SO₂ emissions from fossil fuel combustion for 1996–1997 were 4.0 Tg SO₂ yr⁻¹, with 756 large point sources (e.g. utilities, iron and steel, fertilisers, cement, refineries and petrochemicals and non-ferrous metals), accounting for 62%. PM_2.5 emitted was 0.5 and 2.0 Tg yr⁻¹ for the 100% and the 50% control scenario, respectively, applied to coal burning in the power and industrial sectors. Coal combustion was the major source of PM_2.5 (92%) primarily consisting of fly ash, accounting for 98% of the “inorganic fraction” emissions (difference between PM_2.5 and black carbon+organic matter) of 1.6 Tg yr⁻¹. Black carbon emissions were estimated at 0.1 Tg yr⁻¹, with 58% from diesel transport, and organic matter emissions at 0.3 Tg yr⁻¹, with 48% from brick-kilns. Fossil fuel consumption and emissions peaked at the large point industrial sources and 22 cities, with elevated area fluxes in northern and western India. The spatial resolution of this inventory makes it suitable for regional-scale aerosol-climate studies. These results are compared to previous studies and differences discussed. Measurements of emission factors for Indian sources are needed to further refine these estimates.     

Characterization of emissions from portable household combustion devices: particle size distributions,emission rates and factors,and potential exposures

A series of source tests were conducted to characterize emissions of particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO₂), methane (CH₄), and total hydrocarbon (THC ) from five types of portable combustion devices. Tested combustion devices included a kerosene lamp, an oil lamp, a kerosene space heater, a portable gas range, and four unscented candles. All tests were conducted either in a well-mixed chamber or a well-mixed room, which enables us to determine emission rates and emission factors using a single-compartment mass balance model. Particle mass concentrations and number concentrations were measured using a nephelometric particle monitor and an eight-channel optical particle counter, respectively. Real-time CO concentrations were measured with an electrochemical sensor CO monitor. CO₂, CH₄, and THC were measured using a GC-FID technique. The results indicate that all particles emitted during steady burning in each of the tested devices were smaller than 1.0 μm in diameter with the vast majority in the range between 0.1 and 0.3 μm. The PM mass emission rates and emission factors for the tested devices ranged from 5.6±0.1 to 142.3±40.8 mg h⁻¹ and from 0.35±0.06 to 9.04±4.0 mg g⁻¹, respectively. The CO emission rates and emission factors ranged from 4.7±3.0 to 226.7±100 mg h⁻¹ and from 0.25±0.12 to 1.56±0.7 mg g⁻¹, respectively. The CO₂ emission rates and emission factors ranged from 5500±700 to 210,000±90,000 mg h⁻¹ and from 387±45 to 1689±640 mg g⁻¹, respectively. The contributions of CH₄ and THC to emission inventories are expected to be insignificant due both to the small emission factors and to the relatively small quantity of fuel consumed by these portable devices. An exposure scenario analysis indicates that every-day use of the kerosene lamp in a village house can generate fine PM exposures easily exceeding the US promulgated NAAQS for PM_2.5.