RESUMO
Ambient fine particulate matter (PM2.5) comprises a diverse array of carbonaceous species, and the impact of carbonaceous aerosols (CA) extends to both long-term and short-term effects on human health and the environment. Understanding the distinctive composition of CA is crucial for gaining insights into the origins of airborne particulate matter. Due to their diverse physicochemical properties and intricate heterogeneous reactions, CA often exhibits temporal and spatial variations. Ground-based and highly time-resolved apportionment methods play a vital role in discerning CA emissions. This study utilized high-time resolution data of total carbon (TC) and black carbon (BC) for CA apportionment in northern Taiwan. The advanced numerical model (TC-BC(λ)), coupled with continuous measurement data, facilitated CA allocation based on optical absorption characteristics, organic or elemental carbon composition, and the distinction between primary and secondary origins. Primary carbonaceous aerosols dominated the monitoring site, accounting for 67.5 % compared to the 32.5 % contribution from secondary forms of CA. The summer season exhibited a maximum increase in secondary organic aerosols (SOA) at 41.5 %. Diurnal variations for primary emissions, such as BCc and primary organic aerosols (POA), showed marked peaks for BCff and POAnon-abs during morning rush hours. In contrast, BCbb and POABrC displayed bimodal peaks with increased concentrations during evening hours. Conversely, SOA exhibited significantly different diurnal trends, with SOABrC peaking late at night due to aqueous phased reactions and a noontime peak of SOAnon-abs observed due to photo-oxidation processes. Furthermore, the study employed backward trajectory analysis and concentration-weighted trajectories (CWTs) to examine the long-range transport of CA, identifying potential sources, origins, and transport patterns of CA components to the receptor site in Taiwan during different seasons.
RESUMO
The proportion of patients diagnosed with cancer has been shown to rise with the increasing aging global population. Advanced age is a major risk factor for morbidity and mortality in older adults. As individuals experience varying health statuses, particularly with age, it poses a challenge for medical professionals in the cancer field to obtain standardized treatment outcomes. Hence, relying solely on chronological age and disease-related parameters is inadequate for clinical decision-making for elderly patients. With functional, multimorbidity-related, and psychosocial changes that occur with aging, oncologic diseases may develop and be treated differently from younger patients, leading to unique challenges in treatment efficacy and tolerance. To overcome this challenge, personalized therapy using biomarkers has emerged as a promising solution. Various categories of biomarkers, including inflammatory, hematological, metabolic, endocrine, and DNA modification-related indicators, may display features related to both cancer and aging, aiding in the development of innovative therapeutic approaches for patients with cancer in old age. Furthermore, physical functional measurements as non-molecular phenotypic biomarkers are being investigated for their potential complementary role in structured multidomain strategies to combat age-related diseases such as cancer. This review provides insight into the current developments, recent discoveries, and significant challenges in cancer and aging biomarkers, with a specific focus on their application in advanced age.