Global mercury emissions from combustion in light of international fuel trading.

The spatially resolved emission inventory is essential for understanding the fate of mercury. Previous global mercury emission inventories for fuel combustion sources overlooked the influence of fuel trading on local emission estimates of many countries, mostly developing countries, for which national emission data are not available. This study demonstrates that in many countries, the mercury content of coal and petroleum locally consumed differ significantly from those locally produced. If the mercury content in locally produced fuels were used to estimate emission, then the resulting global mercury emissions from coal and petroleum would be overestimated by 4.7 and 72%, respectively. Even higher misestimations would exist in individual countries, leading to strong spatial bias. On the basis of the available data on fuel trading and an updated global fuel consumption database, a new mercury emission inventory for 64 combustion sources has been developed. The emissions were mapped at 0.1° × 0.1° resolution for 2007 and at country resolution for a period from 1960 to 2006. The estimated global total mercury emission from all combustion sources (fossil fuel, biomass fuel, solid waste, and wildfires) in 2007 was 1454 Mg (1232-1691 Mg as interquartile range from Monte Carlo simulation), among which elementary mercury (Hg(0)), divalent gaseous mercury (Hg(2+)), and particulate mercury (Hg(p)) were 725, 548, and 181 Mg, respectively. The total emission from anthropogenic sources, excluding wildfires, was 1040 Mg (886-1248 Mg), with coal combustion contributing more than half. Globally, total annual anthropogenic mercury emission from combustion sources increased from 285 Mg (263-358 Mg) in 1960 to 1040 Mg (886-1248 Mg) in 2007, owing to an increased fuel consumption in developing countries. However, mercury emissions from developed countries have decreased since 2000.

Distribution of atmospheric particulate matter (PM) in rural field, rural village and urban areas of northern China.

Atmospheric PM10 were measured for 12 months at 18 sites along a 2500 km profile across northern China. Annual mean PM10 concentrations in urban, rural village, and rural field sites were 180 ± 171, 182 ± 154, and 128 ± 89 µg/m(3), respectively. The similarities in PM10 concentrations between urban and rural village sites suggest that strong localized emissions and severe contamination in rural residential areas are derived from solid fuels combustion in households. High PM10 concentrations in Wuwei and Taiyuan were caused by either sandstorms or industrial activities. Relatively low PM10 concentrations were observed in coastal areas of Dalian and Yantai. Particulate air pollution was much higher in winter and spring than in summer and fall. Multiple regression analysis indicates that 35% of the total variance can be attributed to sandstorms, precipitation and residential energy consumption. Over 40% of the measurements in both urban and rural village areas exceeded the national ambient air quality standard.

Inhalation exposure of traffic police officers to polycyclic aromatic hydrocarbons (PAHs) during the winter in Beijing, China.

This study concerns the use of personal samplers to evaluate the exposure of traffic police to polycyclic aromatic hydrocarbons (PAHs) during the winter of 2005 in Beijing. We measured the samples collected for gas and particulate phases PAHs with the same technique used for an earlier study during the summer of 2004, and evaluated exposure risk based on the calculated benzo(a)pyrene equivalent concentrations (BaP(eq)) of both summer and winter. The mean exposure concentrations of gaseous and particulate phase PAHs in the winter are 4300+/-2900 ng/m(3) and 750+/-1000 ng/m(3), respectively, significantly higher than those measured simultaneously at control sites and also considerably higher than the values measured during the summer. The exposure PAH profiles for police and the control subjects are similar with predominant naphthalene in gaseous phase and dominant fluoranthene, pyrene, anthracene and naphthalene in particulate phase. Large daily variations occur both in summer and winter, because of the changes in the weather conditions especially wind speed and relative humidity which tend to disperse and scavenge PAHs in air. In the winter, the average BaP(eq) value for traffic police is 82.1 ng/m(3), which is significantly higher than those for the control subjects and the national standard of 10 ng/m(3) for ambient air. Particulate phase PAHs contribute more than 90% of the total exposure risk in the winter. Annually, weighted-average probabilities of exceeding the national standard (10 ng/m(3)) are 69.3% and 20.6% for the police and the controls, respectively.

Emission of polycyclic aromatic hydrocarbons in China by county.

Quantitative relationships among social, economic, and climate parameters, and energy consumption for Chinese provinces, provide data for regression models' estimated rates of energy consumption and emission of polycyclic aromatic hydrocarbons (PAHs) by county. A nonlinear model was used for domestic coal combustion with total population and annual mean temperature as independent variables. Linear regression models were utilized for all other types of fuel consumption. Monte Carlo simulation demonstrated that emission factors, rather than the regression modeling, constitute the main source of uncertainty in prediction. Models were validated using available energy data of several northern and southern counties of China from the literature. The total PAHs produced by each county is approximately equivalent to the sum of the total emission from energy, coke, and aluminum production.

Dispersion modeling of polycyclic aromatic hydrocarbons from combustion of biomass and fossil fuels and production of coke in Tianjin, China.

A USEPA, procedure, ISCLT3 (Industrial Source Complex Long-Term), was applied to model the spatial distribution of polycyclic aromatic hydrocarbons (PAHs) emitted from various sources including coal, petroleum, natural gas, and biomass into the atmosphere of Tianjin, China. Benzo[a]pyrene equivalent concentrations (BaPeq) were calculated for risk assessment. Model results were provisionally validated for concentrations and profiles based on the observed data at two monitoring stations. The dominant emission sources in the area were domestic coal combustion, coke production, and biomass burning. Mainly because of the difference in the emission heights, the contributions of various sources to the average concentrations at receptors differ from proportions emitted. The shares of domestic coal increased from approximately 43% at the sources to 56% at the receptors, while the contributions of coking industry decreased from approximately 23% at the sources to 7% at the receptors. The spatial distributions of gaseous and particulate PAHs were similar, with higher concentrations occurring within urban districts because of domestic coal combustion. With relatively smaller contributions, the other minor sources had limited influences on the overall spatial distribution. The calculated average BaPeq value in air was 2.54 +/- 2.87 ng/m3 on an annual basis. Although only 2.3% of the area in Tianjin exceeded the national standard of 10 ng/m3, 41% of the entire population lives within this area.

A chemical extraction method for mimicking bioavailability of polycyclic aromatic hydrocarbons to wheat grown in soils containing various amounts of organic matter.

In this study, we have evaluated the extent to which organic matter contents in soils influence the accumulation of PAHs by the roots of wheat plants and have developed a rapid chemical method for determining the bioavailability of PAH. Four polycyclic aromatic hydrocarbons (PAHs), naphthalene, acenaphthylene, fluorene, and phenanthrene, were added to natural soil samples with different amounts of organic matterfor pot experiments to evaluate apparent bioavailability of PAHs to wheat roots (Triticum aestivum L.). The extractabilities of PAHs in the soil were tested by a sequential extraction scheme using accelerated solvent extraction with water, n-hexane, and a mixture of dichloromethane and acetone as solvents. The water or n-hexane-extractable PAHs were positively correlated to dissolved organic matter (DOM) and negatively correlated to total organic matter (TOM), indicating mobilization and immobilization effects of DOM and TOM on soil PAHs, respectively. The apparent accumulation of PAHs by wheat roots was also positively and negatively correlated to DOM and TOM, respectively. As a result, there are positive correlations between the amounts of PAHs extracted by water or n-hexane and the quantities accumulated in plant roots, suggesting the feasibility of using water- or n-hexanes-extractable fractions as indicators of PAH availability to plants.

Multimedia fate model for hexachlorocyclohexane in Tianjin, China.

A level III fugacity model was applied to characterize the fate of gamma-HCH in Tianjin, China, before the 1990s when the contamination reached its maximum at steady state. Geometric means were used as model inputs. The concentrations of gamma-HCH in air, surface water, soil, sediment, crops, and fish as well as transfer fluxes across the interface between the compartments were derived under the assumption of steady state. The calculated concentrations were validated by independent data collected from the literature. There was generally good agreement between the estimated and the observed concentrations, and the differences were all less than 0.6 log units for air, water, soil, sediment, and fish and approximately 1 order of magnitude for crops. Around 97% of gamma-HCH accumulated in soil and sediment. Wastewater irrigation was not an important pathway for delivering gamma-HCH to soil as compared to the dominant source of agricultural application. Degradation and advective airflow carried much gamma-HCH out of the system. Sensitivities of the model estimates to input parameters were tested, and a coefficient of variation normalized sensitivity coefficient was defined for the test. The most influential parameters were degradation rates in sediment and soil, application rates, concentrations in wastewater, and adsorption coefficients. Monte Carlo simulation was conducted for model uncertainty analysis. The model was run 20 000 times using randomly generated data from predefined log-normal distribution density functions. All calculated concentrations and fluxes were log-normally distributed. The dispersions of the calculated and observed concentrations were compared in terms of coefficients of variation to distinguish between true variability and model uncertainty.

Fate modeling of phenanthrene with regional variation in Tianjin, China.

A multimedia fate model with spatially resolved air and soil phases was developed and evaluated. The model was used for calculation of phenanthrene concentrations in air, water, soil, and sediment in Tianjin area and transport fluxes between the adjacent bulk phases under steady-state assumption. Both air and soil phases were divided into 3113 individual compartments of 4 km2 each to assess the spatial variation of phenanthrene concentrations and fluxes. Independently measured phenanthrene concentrations in air, water, and soil were used for model validation. The spatial variation in soil was validated using a set of measured phenanthrene concentrations of 188 surface soil samples collected from the area. Most data used either for model calculation or for model validation were collected during the last 5 years. As the results of the model validation, the calculated mean values for phenanthrene concentrations in various bulk phases are in fair agreement with those independently observed and are very close to those calculated using the model without spatial variation. The absolute difference between the calculated and the measured mean concentrations are 0.14, 0.48, and 0.13 log-units (mol/m3) for air, water, and soil, respectively. The spatial distribution patterns of phenanthrene in both air and soil were well modeled. Spatially, however, the model overestimated the soil phenanthrene level at low concentration range and underestimated it at high concentration range. The calculated distribution of phenanthrene in the air matches well with the emission from fossil fuel combustion, while the calculated distribution pattern in the soil is similar to that observed.