Characteristics of wintertime carbonaceous aerosols in two typical cities in Beijing-Tianjin-Hebei region, China: Insights from multiyear measurements

In order to investigate the impact of "Blue Sky War" implemented during 2018-2020 on carbonaceous aerosols in Beijing-Tianjin-Hebei (BTH) region, China, fine particulate matter (PM_2.5) samples were collected simultaneously in Tianjin and Handan in three consecutive winters from 2018 to 2020. Organic carbon (OC) and elemental carbon (EC) in PM_2.5 were measured with the same thermal-optical methods and analysis protocols. Significant reductions in primary organic carbon (POC) and EC concentrations were observed both in Tianjin and Handan, with decreasing rates of 0.65 and 2.95 μg m^-3 yr^-1 for POC and 0.13 and 0.64 μg m^-3 yr^-1 for EC, respectively. The measured absorption coefficients of EC (b_{abs, EC}) also decreased year by year, with a decreasing rate of 1.82 and 6.16 Mm^-1 yr^-1 in Tianjin and Handan, respectively. The estimated secondary organic carbon (SOC) concentrations decreased first and then increased in both Tianjin and Handan, accounting for more than half of the total OC in winter of 2020-2021 and with increasing contributions especially in highly polluted days. SOC was recognized as one of key factors influencing EC light absorption. EC in the two cities was relatively more related to coal combustion and industrial sources. The reductions of primary carbonaceous components may be attributed to the air quality regulations targeting coal combustion and industrial sources emissions in BTH area. Potential source contribution function (PSCF) analysis results indicated that the major source areas of OC and EC in Tianjin were the southwest region of the sampling site, while the southeast areas for Handan. These findings demonstrated the effectiveness of air quality regulation in primary emissions in typical polluted cities in BTH region and highlighted the needs for further control and in-depth investigation of SOC formation along with implementation of air pollution control act in the future.

A Climatological Satellite Assessment of Absorbing Carbonaceous Aerosols on a Global Scale

A global climatology of absorbing carbonaceous aerosols (ACA) for the period 2005–2015 is obtained by using satellite MODIS (Moderate Resolution Imaging Spectroradiometer)-Aqua and OMI (Ozone Monitoring Instrument)-Aura aerosol optical properties and by applying an algorithm. The algorithm determines the frequency of presence of ACA (black and brown carbon) over the globe at 1° × 1° pixel level and on a daily basis. The results of the algorithm indicate high frequencies of ACA (up to 19 days/month) over world regions with extended biomass burning, such as the tropical forests of southern and central Africa, South America and equatorial Asia, over savannas, cropland areas or boreal forests, as well as over urban and rural areas with intense anthropogenic activities, such as the eastern coast of China or the Indo-Gangetic plain. A clear seasonality of the frequency of occurrence of ACA is evident, with increased values during June–October over southern Africa, during July–November over South America, August–November over Indonesia, November–March over central Africa and November–April over southeastern Asia. The estimated seasonality of ACA is in line with the known annual patterns of worldwide biomass-burning emissions, while other features such as the export of carbonaceous aerosols from southern Africa to the southeastern Atlantic Ocean are also successfully reproduced by the algorithm. The results indicate a noticeable interannual variability and tendencies of ACA over specific world regions during 2005–2015, such as statistically significant increasing frequency of occurrence over southern Africa and eastern Asia.

Comparison of Measurement-Based Methodologies to Apportion Secondary Organic Carbon (SOC) in PM2.5: A Review of Recent Studies

Secondary organic aerosol (SOA) is known to account for a major fraction of airborne particulate matter, with significant impacts on air quality and climate at the global scale. Despite the substantial amount of research studies achieved during these last decades, the source apportionment of the SOA fraction remains difficult due to the complexity of the physicochemical processes involved. The selection and use of appropriate approaches are a major challenge for the atmospheric science community. Several methodologies are nowadays available to perform quantitative and/or predictive assessments of the SOA amount and composition. This review summarizes the current knowledge on the most commonly used approaches to evaluate secondary organic carbon (SOC) contents: elemental carbon (EC) tracer method, chemical mass balance (CMB), SOA tracer method, radiocarbon (14C) measurement and positive matrix factorization (PMF). The principles, limitations, challenges and good practices of each of these methodologies are discussed in the present article. Based on a comprehensive—although not exhaustive—review of research papers published during the last decade (2006–2016), SOC estimates obtained using these methodologies are also summarized for different regions across the world. Conclusions of some studies which are directly comparing the performances of different methodologies are then specifically discussed. An overall picture of SOC contributions and concentrations obtained worldwide for urban sites under similar conditions (i.e., geographical and seasonal ones) is also proposed here. Finally, further needs to improve SOC apportionment methodologies are also identified and discussed.

Heavy metals in industrially emitted particulate matter in Ile-Ife, Nigeria

Iron and steel smelting facilities generate large quantities of airborne particulate matter (PM) through their various activities and production processes. The resulting PM that contains a variety of heavy metals has potentially detrimental impacts on human health and the environment. This study was conducted to assess the potential health effects of the pollution from the heavy metals in the airborne PM sampled in the vicinity of secondary smelting operations in Ile-Ife, Nigeria. X-ray fluorescence (XRF) was used to determine the elemental concentration of Pb, Cr, Cd, Zn, Mn, As, Fe, Cu, and Ni in the size-segregated PM samples. Pollution Indices (PI) consisting of Contamination Factor (CF), Degree of Contamination (DC) and Pollution Index Load (PLI) and Target Hazard Quotient (THQ) were employed to assess the pollution risk associated with the heavy metals in the PM. CF, DC and PLI values were 3< CF <6, >32 and >1, respectively for the three sites, indicating deterioration of the ambient air quality in the vicinity of the smelter. The heavy metals in the airborne PM pose a severe health risk to people living in vicinity of the facility and to its workers. The diminished air quality with the associated health risks directly depends on the industrial emissions from steel production and control measures are recommended to mitigate the likely risks.

Source identification and apportionment of PM2.5 and PM2.5-10 in iron and steel scrap smelting factory environment using PMF, PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM2.5 and PM2.5-10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m(3) for PM2.5 and 331.36, 190.01, and 184.60 μg/m(3) for PM2.5-10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM2.5-10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM2.5-10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.