Journal of Atmospheric Chemistry最新文献

This study investigates chemical composition of rainwater (RW) and its contribution from different sources collected over the period of two years (2016 and 2017) at a high altitude location (1380?m above mean sea level) located at Mahabaleshwar situated in the Western Ghats in Peninsular India. The volume weighted mean pH of RW was found to vary between 4.57 and 7.51 (average 5.95) indicating overall alkaline nature of the RW. Prominent ionic species in the RW were Ca²⁺ (25%), Na⁺ (19%), Cl^?(23%), SO₄^2? (10%), and Mg²⁺ (9%) with NH₄⁺, NO₃^? and K⁺ together forming about 8% of ionic composition. Moreover, ample presence of dust source (Ca²⁺) was found that acted as a major neutraliser to the acidic ions. The order of Neutralisation Factor of ions was Ca²⁺ > Mg²⁺ > NH₄⁺. In addition, a strong correlation between Na⁺ and Cl^? (r ≈ 0.99) further suggested substantial supplement of marine (NaCl) component to the RW. The impact of local anthropogenic activities such as fossil fuel/biomass burning was observed apart from some contribution from the long-range transport. The high contribution of non-sea salt fractions to Ca²⁺, SO₄^2?, Mg²⁺ and K⁺ showed a substantial effect of crustal and continental air masses. Results of source apportionment for the RW composition by using the Positive Matrix Factorization technique indicated four factors i.e. Marine and long range transport (Na⁺, Cl^?), crustal (Ca²⁺, Mg²⁺), emissions from the fossil fuel and biomass burning (NO₃^?, SO₄^2?) and the agriculture/farming activities (NH₄⁺).

Ambient particulate matter concentrations in Delhi and its peripheral towns has been a matter of serious concern in the last decade. Understanding the changing nature of the chemical composition of particulates, their spatial and seasonal variability can be utilized for identifying probable sources. This study presents an extensive dataset of the chemical composition of PM_2.5 and PM₁₀ collected using speciation samplers, from 19 locations representing different activities and spread across Delhi–NCR during summer and winter seasons in the year 2016–17. Identification of contributing sources using chemical ratios as source indicators is attempted. A distinct seasonal variability in both PM_2.5 and PM₁₀ was observed, with winter maxima and summer minima. The fine fraction i.e. PM_2.5 was dominated by organic matter (OM) with mean concentrations of 40.96±25.74?μg/m³ followed by Sulfate-Nitrate-Ammonium (SNA) ions (31.44±20.69?μg/m³) and Elemental Carbon (EC) (19.56±12.57?μg/m³); while the coarse fraction i.e. PM₁₀ was dominated by OM (73.03±40.55?μg/m³) and SNA (47.25±30.56?μg/m³) along with significant contributions from crustal materials (40.85±18.89?μg/m³). The chemical ratios suggested mixed sources of PM with major contributions from vehicular emissions, re-suspended and/or construction dust, and fossil fuel combustion along with intermittent contributions from biomass and open waste burning. This analysis provides useful insights into the sources and processes affecting the particulate formation and underlines the need to control primary emissions as well as secondary precursors for air quality improvements in the region. The data generated under this campaign can also serve as an essential input for further evaluation using receptor modeling.

The study analysed spatio-temporal distribution of fire radiative power (FRP) and estimates of trace gases [volatile organic compounds (VOCs) and nitrogen oxides (NOx)] along with their reactivity during biomass burning period of March (2003–2017) over the northeast region (NER), India. Reanalysis data of FRP along with emission rates of trace gases have been retrieved from Global Fire Assimilation System. Results showed that average FRP was estimated to be 0.37 Wm^?2 with the highest value in Mizoram (0.16 Wm^?2) among 7-states of the study region. Temporally, relatively higher FRP occurred during the year of 2006 and 2010 while lowest in 2017. FRP-based VOCs and NOx emission estimates were 431 and 69.5?mg/m²/day, respectively which are consistent with observed FRP. Among different groups of VOCs, oxygenated species were the largest group (~56%) estimated followed by alkenes, alkanes, aromatics, and biogenic. Photochemical reactivities of VOCs were estimated using propylene-equivalent and maximum incremental reactivity methods which showed oxygenated species had the highest contributions in chemical reactivity. Based on the MIR scale, the top ten leading contributor species for ozone (O₃) formation were in descending order of formaldehyde, acetaldehyde, ethene, propene, toluene, butane, isoprene, methanol, pentene, and hexane which accounted for approximately 97% of total ozone formation. We also examined the ozone formation regime using VOCs/NOx ratios which indicated that O3 formation was likely to be VOC-sensitive over NER. Our results could be used for the understanding of FRP-based trace gas emissions during biomass burning and to establish effective preventive measures for reduction in O₃ pollution.

Analysis of rainwater in historical cities plays a key role to save ancient monuments from atmospheric agents. In this study we sampled the Rome’s rainwater from February to July of 2018 and we analysed them to determine their chemical and physical parameters: pH, redox potential, conductivity, temperature, and the concentration of the main inorganic ions (Na⁺, K⁺, Ca⁺⁺, Mg⁺⁺, F^?, Cl^?, NO₃^?, SO₄^??). The volume of the daily fallen rainwater, the speed and direction of the wind in the sampling site were also collected. In order to find a correlation between all the above data we used the Principal Component Analysis (PCA). Results evidenced that there aren’t authentic “acid rains” as the minimum pH value that we found is 5.2. In some cases high concentrations of nitrates and sulphates were found with maximum values of 12.4?ppm and 18.7?ppm respectively. We also found no correlation between the rainwater’s composition and the seasonal period; on the contrary, the speed and direction of the wind, especially when coming from the sea or industrial country near Rome, play a noticeable role on the rainwater composition.

We introduce the CMC based Ionic Surfactant Activity model (CISA) to calculate activity coefficients in ternary aqueous solutions of an ionic surfactant and an inorganic salt. The surfactant can be either anionic or cationic and in the present development, the surfactant and inorganic salts share a common counterion. CISA incorporates micellization into the Pitzer–Debye–Hückel (PDH) framework for activities of mixed electrolyte solutions. To reduce computing requirements, a parametrization of the critical micelle concentration (CMC) is used to estimate the degree of micellization instead of explicit equilibrium calculations. For both binary and ternary systems, CISA only requires binary experimentally-based parameters to describe water–ion interactions and temperature–composition dependency of the CMC. The CISA model is intended in particular for atmospheric applications, where higher-order solution interaction parameters are typically not constrained by experiments and the description must be reliable across a wide range of compositions. We evaluate the model against experimental activity data for binary aqueous solutions of ionic surfactants sodium octanoate and sodium decanoate, as common components of atmospheric aerosols, and sodium dodecylsulfate, the most commonly used model compound for atmospheric surfactants. Capabilities of the CISA model to describe ternary systems are tested for the water–sodium decanoate–sodium chloride system, a common surrogate for marine background cloud condensation nuclei and to our knowledge the only atmospherically relevant system for which ternary activity data is available. For these systems, CISA is able to provide continuous predictions of activity coefficients both below and above CMC and in all cases gives an improved description of the water activity above the CMC, compared to the alternative model of Burchfield and Wolley [J. Phys. Chem., 88(10), 2149–2155 (1984)]. The water activity is a key parameter governing the formation and equilibrium growth of cloud droplets. The CISA model can be extended from the current form to include the effect of other inorganic salts with the existing database of binary PDH parameters and using appropriate mixing rules to account for ion specificity in the micellization process.