Comparison of elemental and black carbon measurements during normal and heavy haze periods: implications for research

The Measurement of Atmospheric Black Carbon: A Review

Black Carbon (BC), the second-largest contributor to global warming, has detrimental effects on human health and the environment. However, the accurate quantification of BC poses a significant challenge, impeding the comprehensive assessment of its impacts. Therefore, this paper aims to critically review three quantitative methods for measuring BC: Thermal Optical Analysis (TOA), the Optical Method, and Laser-Induced Incandescence (LII). The determination principles, available commercial instruments, sources of deviation, and correction approaches associated with these techniques are systematically discussed. By synthesizing and comparing the quantitative results reported in previous studies, this paper aims to elucidate the underlying relationships and fundamental disparities among Elemental Carbon (EC), Equivalent Black Carbon (eBC), and Refractory Black Carbon (rBC). Finally, based on the current advancements in BC quantification, recommendations are proposed to guide future research directions.

Intercomparison of equivalent black carbon (eBC) and elemental carbon (EC) concentrations with three-year continuous measurement in Beijing, China

Due to the lack of black carbon (BC) measurement data in some cases, elemental carbon (EC) is often used as a surrogate of BC, with a simple assumption that they are interchangeable. Such assumption will inevitably lead to uncertainties in radiative forcing estimation and health impact assessment. In order to quantitatively and systematically evaluate the relationship between BC and EC as well as factors responsible for their difference, 3-year collocated equivalent BC (eBC) and EC measurements with 1-h resolution were performed in Beijing, China continuously from 2016 to 2019. EBC concentration was measured by the multi-wavelength aethalometer (AE-33) based on optical analysis, while EC concentration was determined by semi-continuous OC/EC analyzer with thermal-optical method. The results showed that around 90% of eBC concentration was higher than that of EC, with average difference between eBC and EC as 1.21 μg m^-3 (accounting for 33% of average eBC in Beijing). EBC and EC concentrations exhibited strong correlation (r = 0.90) during the whole study period, but the slopes (or eBC/EC ratio) and correlation coefficients varied across seasons (spring: 1.67 and 0.94; summer: 0.91 and 0.65; fall: 1.15 and 0.88; winter: 1.09 and 0.91, respectively). Based on the information from shell/core ratios by Single Particle Soot Photometer (SP2), source apportionment results by positive matrix factorization model, and chemical composition of PM_2.5, the differences between eBC and EC concentrations were found to be primarily related to BC aging process and secondary components as evidenced by strong positive correlation with secondary species (e.g., secondary organic carbon and nitrate). This study provided seasonal specific conversion factors of eBC and EC in Beijing and helpful reference for other areas, which will contribute new knowledge of carbonaceous aerosol and reduce uncertainty in assessing future climate change and health studies of BC.

Health risk assessment of China's main air pollutants

Background

With the rapid development of China’s economy, air pollution has attracted public concern because of its harmful effects on health.

Methods

The source apportioning of air pollution, the spatial distribution characteristics, and the relationship between atmospheric contamination, and the risk of exposure were explored. The in situ daily concentrations of the principal air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃) were obtained from 188 main cities with many continuous air-monitoring stations across China (2014 and 2015).

Results

The results indicate positive correlations between PM_2.5 and SO₂ (R² = 0.395/0.404, P < 0.0001), CO (R² = 0.187/0.365, P < 0.0001), and NO₂ (R² = 0.447/0.533, P < 0.0001), but weak correlations with O₃ (P > 0.05) for both 2014 and 2015. Additionally, a significant relationship between SO₂, NO_2, and CO was discovered using regression analysis (P < 0.0001), indicating that the origin of air pollutants is likely to be vehicle exhaust, coal consumption, and biomass open-burning. For the spatial pattern of air pollutants, we found that the highest concentration of SO₂, NO_2, and CO were mainly distributed in north China (Beijing-Tianjin-Hebei regions), Shandong, Shanxi and Henan provinces, part of Xinjiang and central Inner Mongolia (2014 and 2015).

Conclusions

The highest concentration and risk of PM_2.5 was observed in the Beijing–Tianjin–Hebei economic belts, and Shandong, Henan, Shanxi, Hubei and Anhui provinces. Nevertheless, the highest concentration of O₃ was irregularly distributed in most areas of China. A high-risk distribution of PM₁₀, SO₂ and NO₂ was also observed in these regions, with the high risk of PM₁₀ and NO₂ observed in the Hebei and Shandong province, and high-risk of PM₁₀ in Urumchi. The high-risk of NO₂ distributed in Beijing-Yangtze River Delta region-Pearl River Delta region-central. Although atmospheric contamination slightly improved in 2015 compared to 2014, humanity faces the challenge of reducing the environmental and public health effects of air pollution by altering the present mode of growth to achieve sustainable social and economic development.