Seasonal variations of elemental carbon in urban aerosols as measured by two common thermal-optical carbon methods

Particulate black carbon mass concentrations and the episodic source identification driven by atmospheric blocking effects in Astana, Kazakhstan

Black carbon (BC) is a component of fine particulate matter (PM2.5) that is a key contributor to adverse human health effects and climate forcing. To date, BC mass concentrations and possible sources in Kazakhstan have not been studied. Thus, understanding the temporal variations of BC for a large developing region with a complex climate is useful. In this study, measurements of fine particulate BC mass concentrations in Astana were made from June 2020 to October 2021 by measuring light absorption of PM2.5 on filters. The mean BC concentration was 2.56 ± 1.29 μg m-3 with maximum and minimum monthly mean BC concentrations being 4.56 ± 2.03 μg m-3 and 1.12 ± 0.42 μg m-3 in January 2021 and June 2020, respectively. Temporal analyses of BC, SO2, PM10, NOx, CO, meteorological and atmospheric stability parameters were performed. Aggregated pollutant 'episodic loadings' during the heating and non-heating periods were identified. Their relationships with blocking anticyclones and cyclones were investigated by examining the reversal of meridional gradients at 500 hPa geopotential height (GPH) maps and identifying Omega (Ω) and Rex blocking types. Astana has some of the highest BC concentrations of cities worldwide. Seasonal BC source location identification using Conditional Bivariate Probability Function (CBPF) analysis implicated combined heat and power (CHP) plant emissions as the major BC source in Astana. Significant increases in BC concentrations were observed during the cold season due to numerous sources, generally poorer atmospheric dispersion and blocking events. The Concentration Weighted Trajectory (CWT) analysis results showed that the distribution of the 75th percentile of BC during episodic periods actively controlled by blockings exceeding than the entire measurement period, which may reflect cross-border transport and adjacent countries.

Air pollution at Rochester, NY: Long-term trends and multivariate analysis of upwind SO2 source impacts

There have been many changes in the air pollutant sources in the northeastern United States since 2001. To assess the effect of these changes, trend analyses of the monthly average values were performed on PM_2.5 and its components including major ions, elemental carbon (EC), organic carbon (OC), and gaseous pollutant concentrations measured between 2001 (in some cases 1999) and 2015 at the NYS Department of Environmental Conservation sites in Rochester, NY. Mann-Kendall regression with Sen's slope was applied to estimate the trends and seasonality. Using piecewise regression, significant reductions in the air pollution of Rochester area were observed between 2008 and 2010 when a 260MW coal-fired power plant was decommissioned, new heavy-duty diesel trucks had to be equipped with catalytic regenerator traps, and the economic recession that began in 2008 reduced traffic and other activities. The monthly average PM_2.5 mass showed a downward trend (-5μg/m³; -41%) in Rochester between 2001 and 2015. This change is largely due to reductions in particulate sulfate that showed a 65% decrease. The sulfate concentrations were compared to changes in SO₂ emissions in seventeen upwind source domains, and other systematic changes by multivariate linear regression. Selectivity ratio obtained from target projection discriminated the most important source domains that are SO₂ emissions from Georgia for winter, North Carolina for transition (spring and fall) and Ohio along with other influences for summer. North Carolina and Michigan were identified as the main sources for entire period. These observations suggest that any further reductions in the specified regional SO₂ emissions would result in a proportional decrease in sulfate in Rochester.

Impact of ambient fine particulate matter carbon measurement methods on observed associations with acute cardiorespiratory morbidity

Elemental carbon (EC) and organic carbon (OC) represent a substantial portion of particulate matter <2.5 μm in diameter (PM2.5), and have been associated with adverse health effects. EC and OC are commonly measured using the National Institute of Occupational Safety and Health (NIOSH) method or the Interagency Monitoring of Protected Visual Environments (IMPROVE) method. Measurement method differences could have an impact on observed epidemiologic associations. Daily speciated PM2.5 data were obtained from the St Louis-Midwest Supersite, and St Louis emergency department (ED) visit data were obtained from the Missouri Hospital Association for the period June 2001 to April 2003. We assessed acute associations between cardiorespiratory ED visits and EC and OC from NIOSH and IMPROVE methods using Poisson generalized linear models controlling for temporal trends and meteorology. Associations were generally similar for EC and OC from the different measurement methods. The most notable difference between methods was observed for congestive heart failure and EC (for example, warm season rate ratios (95% confidence intervals) per interquartile range change in EC concentration were: NIOSH=1.06 (0.99-1.13), IMPROVE=1.01 (0.96-1.07)). Overall, carbon measurement method had little impact on acute associations between EC, OC, and ED visits. Some specific differences were observed, however, which may be related to particle composition.

Size-resolved aerosol chemical analysis of extreme haze pollution events during early 2013 in urban Beijing, China

Using size-resolved filter sampling and chemical characterization, high concentrations of water-soluble ions, carbonaceous species and heavy metals were found in both fine (PM2.1) and coarse (PM2.1-9) particles in Beijing during haze events in early 2013. Even on clear days, average mass concentration of submicron particles (PM1.1) was several times higher than that previously measured in most of abroad urban areas. A high concentration of particulate matter on haze days weakens the incident solar radiation, which reduces the generation rate of secondary organic carbon in PM1.1. We show that the peak mass concentration of particles shifted from 0.43-0.65μm on clear days to 0.65-1.1μm on lightly polluted days and to 1.1-2.1μm on heavily polluted days. The peak shifts were also found for the following species: organic carbon, elemental carbon, NH4(+), SO4(2-), NO3(-), K, Cu, Zn, Cd and Pb. Our findings demonstrate that secondary inorganic aerosols (36%) and organic matter (26%) dominated the fine particle mass on heavily polluted days, while their contribution reduced to 29% and 18%, respectively, on clear days. Besides fine particles, anthropogenic chemical species also substantially accumulated in the coarse mode, which suggests that particles with aerodynamic diameter larger than 2.1μm cannot be neglected during severe haze events.

Factors and Trends Affecting the Identification of a Reliable Biomarker for Diesel Exhaust Exposure

The monitoring of human exposures to diesel exhaust continues to be a vexing problem for specialists seeking information on the potential health effects of this ubiquitous combustion product. Exposure biomarkers have yielded a potential solution to this problem by providing a direct measure of an individual's contact with key components in the exhaust stream. Spurred by the advent of new, highly sensitive, analytical methods capable of detecting substances at very low levels, there have been numerous attempts at identifying a stable and specific biomarker. Despite these new techniques, there is currently no foolproof method for unambiguously separating diesel exhaust exposures from those arising from other combustion sources. Diesel exhaust is a highly complex mixture of solid, liquid, and gaseous components whose exact composition can be affected by many variables, including engine technology, fuel composition, operating conditions, and photochemical aging. These factors together with those related to exposure methodology, epidemiological necessity, and regulatory reform can have a decided impact on the success or failure of future research aimed at identifying a suitable biomarker of exposure. The objective of this review is to examine existing information on exposure biomarkers for diesel exhaust and to identify those factors and trends that have had an impact on the successful identification of metrics for both occupational and community settings. The information will provide interested parties with a template for more thoroughly understanding those factors affecting diesel exhaust emissions and for identifying those substances and research approaches holding the greatest promise for future success.

Organic and elemental carbon filter sets: preparation method and interlaboratory results

Carbonaceous aerosols play an important role in climate, visibility, air quality, and human health effects, and they have been routinely monitored in workplace and environmental settings. Different thermal analysis methods have been applied to determine the carbon content of carbonaceous aerosols. Good agreement between results for total carbon (TC) generally has been found, but the organic and elemental carbon (OC and EC) fractions determined by different methods often disagree. Measurement uncertainty is mainly due to pyrolysis and charring of OC sample components. Lack of reference materials has impeded progress on method standardization and understanding method biases. A relatively simple method for generating matched filter sets having known OC-EC contents is reported. After generation and analysis of each set to confirm agreement between filters, the filter sets were distributed to six laboratories for an interlaboratory comparison. Analytical results indicate a uniform carbon distribution for the filter sets and good agreement between the participating laboratories. Relative standard deviations (RSDs) for mean TC (OC + EC), OC, and EC results for seven laboratories were <10, 11, and 12% (respectively). Except for one EC result (RSD = 16%), RSDs reported by individual laboratories for TC, OC, and EC were <12%. The method of filter generation is generally applicable and reproducible. Depending on the application, different filter loadings and types of OC materials can be employed. Matched filter sets prepared by the described approach can be used for determining the accuracy of OC-EC methods and thereby contribute to method standardization.

Driver exposure to particulate matter in Bangkok

The aims of this study were to determine the particulate matter with aerodynamic diameters > or = 2.5 microm (PM2.5) and 2.5-10 microm (PM10-2.5) exposure levels of drivers and to analyze the proportion of elemental carbon (EC) and organic carbon (OC) in PM2.5 in Bangkok, Thailand. Four bus routes were selected. Measurements were conducted over 10 days in August (rainy season) 2008 and 8 days in January (dry season) 2009. The mean PM2.5 exposure level of the Tuk-tuk drivers was 86 microg/m3 in August and 198 microg/m3 in January. The mean for the non-air-conditioned bus drivers was 63 microg/m3 in August and 125 microg/m3 in January. The PM2.5 and PM10-2.5 exposure levels of the drivers in January were approximately twice as high as those in August. The proportion of total carbon (TC) in PM2.5 to the PM2.5 level in August (0.97 +/- 0.28 microg/m3) was higher than in January (0.65 +/- 0.13 microg/m3). The proportion of OC in the TC of the PM2.5 in August (0.51 +/- 0.08 microg/m3) was similar to that in January (0.65 +/- 0.07 microg/m3). The TC exposure by PM25 in January (81 +/- 30 microg/m3) remained higher than in August (56-21 microg/m3). The mean level of OC in the PM2.5 was 29 +/- 13 microg/m3 in August and 50 +/- 24 microg/m3 in January. In conclusion, the PM exposure level in Bangkok drivers was higher than that in the general environment, which was already high, and it varied with the seasons and vehicle type. This study also demonstrated that the major component of the PM was carbon, likely derived from vehicles.