Journal of Atmospheric Chemistry最新文献

A novel coronavirus has affected almost all countries and impacted the economy, environment, and social life. The short-term impact on the environment and human health needs attention to correlate the Volatile organic compounds (VOCs) and health assessment for pre-, during, and post lockdowns. Therefore, the current study demonstrates VOC changes and their effect on air quality during the lockdown. The findings of result, the levels of the mean for total VOC concentrations were found to be 15.45 ± 21.07, 2.48 ± 1.61, 19.25 ± 28.91 µg/m³ for all monitoring stations for pre-, during, and post lockdown periods. The highest value of TVOCs was observed at Thane, considered an industrial region (petroleum refinery), and the lowest at Bandra, which was considered a residential region, respectively. The VOC levels drastically decreased by 52%, 89%, 80%, and 97% for benzene, toluene, ethylbenzene, and m-xylene, respectively, during the lockdown period compared to the previous year. In the present study, the T/B ratio was found lower in the lockdown period as compared to the pre-lockdown period. This can be attributed to the complete closure of non-traffic sources such as industries and factories during the lockdown. The Lifetime Cancer Risk values for all monitoring stations for benzene for pre-and-post lockdown periods were higher than the prescribed value, except during the lockdown period.

A detailed study on potential sources, variation, and environmental effects of the rainwater ions was carried out at Lothian Island, Sundarban mangrove forest, India, during the southwest monsoon (June–September) in 2019. On an event basis, the maximum rainwater precipitation was observed 17.65 mm Day ⁻¹ and a minimum of 1.02 mm Day ⁻¹. The maximum amount of total precipitation was recorded in the month of July (237 mm). The volume weighted mean (VWM) concentration shows that the total ionic composition was 93.7 μeq L⁻¹, whereas the percentage contribution of the total ionic concentration is found to be 45.97% to anions and 54.02% to the cations. Temporal variation was observed between early (June- July) and late monsoon (August—September), which shows a high concentration of major ions in early monsoon and low concentration in late monsoon due to the washout of atmospheric particles with the frequent and increasing precipitation. The pH values of the 78% samples show neutral pH and neutralization factors (NF) followed a sequence of NF_Ca ˃NF_Mg ˃ NF_NH4 with factors of 0.77, 0.34, and 0.14 indicating Ca²⁺ was the most potential species to balance the acidic ions (NO₃⁻, SO₄²⁻) over the study area. Source apportionment study indicates the significant influence of marine actions (long-range transport by monsoonal wind from marine origin, Sea spray, salty soil profile of mangrove) as the major source of ions over Sundarban. The rate of nutrient wet deposition in the form of rainwater was estimated and average monsoonal nitrogen flux was observed 0.87 kg ha⁻¹where NO₃ contributes the most (0.60 kg ha⁻¹). N and P deposition flux also showed a simultaneous pattern with the seasonal nutrient concentration of surrounding river water, which may be an indication of a possible contribution of atmospheric wet deposition in the spike of monsoonal nutrient concentration in river water.

The TROPOMI (TROPOspheric monitoring instrument) onboard Sentinel-5 Precursor (S5P) satellite provides high spatial resolution data of carbon monoxide (CO) while the MAIAC (Multiangle Implementation of Atmospheric Correction) is a newly developed algorithm applied to MODIS collection 6 observations to retrieve AOD (Aerosol Optical Depth) at a high spatial resolution of 1 km. The present study utilized the MAIAC AOD from MODIS Terra and Aqua polar-orbiting satellites between March 2000 to December 2021 and CO from Sentinel-5P during the available period July 2018-December 2021 over Pakistan. Moreover, we used three trend techniques (Linear regression, Mann–Kendall (MK), and Theil-Sen’s Slope) to examine the trends of AOD and CO over Pakistan. The results show that both AOD and CO have high values over central Punjab, western Balochistan, central Sindh, and Khyber Pakhtunkhwa. The mean annual high AOD of > 1.2 is observed in eastern Punjab because of an increase in urbanization, industrialization, and economical activities whereas the AOD of ~ 1.0 is observed over Balochistan, Sindh, and a few parts of Khyber Pakhtunkhwa. The highest mean annual CO of ˃0.03 mol/m^2 is seen over central Punjab, Sindh, and Khyber Pakhtunkhwa. The results show that seasonal mean MAIAC AOD ranging from 0.7 to > 0.9 was seen over Punjab and Sindh province during the monsoon season whereas the lowest AOD is detected in the winter season over few parts of Balochistan. In contrast, the highest mean seasonal CO ranging from 0.040 to > 0.055 mol/m^2 was seen in the winter season over Punjab. The lowest CO concentration is observed in the winter season over the northern region of Pakistan. Non-parametric analyses (MK and Theil-Sen’s slope) also show an increasing trend of CO over Pakistan from 2018 to 2021. Furthermore, we have also investigated the trends of AOD and CO over selected cities of Pakistan using linear regression, MK test, and Theil-Sen’s slope to reveal long-term air pollution trends.

The results of a study of the elemental concentrations in PM₁₀ samples collected at a site in southwest Mexico City during 2016 and 2019, are presented. The concentrations of up to 19 elements were measured with X-ray fluorescence (XRF). These analyses were complemented with ion chromatography for eight ionic species (for the samples collected in 2016). The behaviors of the gravimetric mass and elemental concentrations are described for the morning, afternoon, and night-time periods in 2019. The elemental concentrations observed in the PM₁₀ samples did not present significant changes as compared to those published in previous works. It was found that the gravimetric mass concentrations were always below the official standards, except during a contingency period in May 2019. The positive matrix factorization (PMF) receptor model was used to identify contaminating sources and their relative contributions to the concentrations of the detected elements. The soil-related factors were the most abundant contributors, with other components associated to traffic, biomass burning, fuel oil, secondary aerosol, and dust resuspension. The occurrence of episodes in 2019 is explained with the aid of PMF and back-trajectories, while the contingency period is due to other chemical species not detected in PM₁₀ with XRF. A comparison with data collected in 2005 in downtown Mexico City is also carried out, as well as with urban areas in other countries.

In this study, 123 PM_2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM_2.5 concentration was 80.5 ± 38.2 μg/m³, with higher PM_2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM_2.5 mass concentration, respectively. SO₄²⁻, NO₃⁻ and NH₄⁺ were the dominant components, accounting for 40.2% of PM_2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO₃⁻/SO₄²⁻ was 0.86 ± 0.72, indicating that stationary sources play dominant role on PM_2.5 concentration. The ratio of OC/EC was 2.9 ± 1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM_2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively.

A Raman lidar system was operated along with the Microtops sunphotometer measurements to carry out the study of the variation of the optical properties of aerosols over Palampur (32.11° N and 76.53° E), India from 17th April to 11th May 2019. The lidar system is furnished with Raman (N₂) channel and depolarization channel allowing independent measurement of Lidar Ratio (LR) and linear depolarization ratio. The study reveals that the majority of the aerosols approximately were restricted within the planetary boundary layer (PBL) and very less loading was present in the free troposphere over the study location. The particle loading over the study period was found to be very less with aerosol backscatter coefficient (at 355 nm) ranging from ∼0.13 Mm⁻¹sr⁻¹ to ∼7.25 Mm⁻¹sr⁻¹ with mean value of 2.67 ± 0.82 Mm⁻¹sr⁻¹ and it is well supplemented by the mean aerosol optical depth (AOD) of 0.37 ± 0.13 obtained from Microtops Sunphotometer. The average lidar ratio values for 0-1 km altitude (L1) 72 ± 13sr, for 1-2 km (L2) altitude 55 ± 8sr, for 2-3 km (L3) 54 ± 15sr were observed as suggesting dominance of the biomass burning aerosols and anthropogenic aerosols. The particle depolarization ratio (355 nm) values were found from approximately 4.8 ± 2.7% to 11.5 ± 1.9% with the mean value of 7 ± 1.3% suggesting the presence of non-spherical particles. To trace the sources of the pollution, we derived the HYSPLIT trajectory which shows the majority of the movement was from local sources.

The forests of the boreal and mid-latitude zones of the Northern Hemisphere are the largest source of reactive volatile organic compounds (VOCs), which have an important impact on the processes occurring in the atmospheric boundary layer. However, the composition of biogenic emissions from them remains incompletely characterized, as evidenced by the significant excess OH radical concentrations predicted by models in comparison with those observed under the forest canopy. The missing OH sink in the models may be related to the fact that they do not take into account the emission of highly reactive VOCs by vegetation on the forest floor. In this work, we report the results of laboratory determinations of the composition of VOCs emitted by representatives of different groups of plants that form the living soil cover (LSC) in the forests of the boreal and mid-latitude zones: bryophytes, small shrubs, herbaceous plants, and ferns. In the chromatograms of volatile emissions of all 11 studied plant species, 254 compounds with carbon atoms ranging in number from two to 20 were registered. All plants were characterized by the emission of terpenes, accounting for 112 compounds, and the second largest group (35 substances) was formed by carbonyl compounds. Both groups of compounds are characterized by high reactivity and are easily included in the processes of gas-phase oxidation with the participation of radicals HO, NO₃ and ozone. These data indicate the importance of a thorough study of the so far disregarded source of VOCs, that is, the LSC in forests.

Aerosol acidity is found to exert negative effects on ecosystem diversity and architectural appearance. Current analytical technology is unable to measure in-situ aerosol acidity (i.e., pH value) of ambient fine particle due to the absence of appropriate pH electrodes. Thermodynamic modeling methods including ISORROPIA II and Extended Aerosol Inorganics Model Version IV (E-AIM V) are mostly used in the estimation of in-situ aerosol acidity with the inputs of water soluble ions worldwide. This study proposes a flexible method with the aid of multilayer perceptron (MLP) neural network analysis to estimate in-situ aerosol acidity of ambient fine particle (< 2.5 μm in aerodynamic diameter or PM_2.5) with the inputs of water soluble ions (i.e., Cl⁻, NO₃⁻, SO₄²⁻, Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺), gaseous air pollutants (i.e., CO, NO₂, SO₂) and meteorological parameters (i.e., humidity and temperature). The dataset consists of ambient fine particles collected across four individual sampling periods in the autumn and winter of 2019 and 2020 at a suburban site of Nanjing. The pH values of ambient fine particle were found to be ranging from 2.0 to 4.0 estimated by E-AIM model. Levels of pH estimated by MLP neural network analysis agreed well with pH values estimated by E-AIM model with R² value of 0.98.

Rapid transport by deep convection is an important mechanism for delivering surface emissions of reactive halocarbons and other trace species to the tropical tropopause layer (TTL), a key region of transport to the stratosphere. Recent model studies have indicated that increased delivery of short-lived halocarbons to the TTL could delay stratospheric ozone recovery. We report here measurements in the TTL over the western Pacific Ocean of short-lived halocarbons and other trace gases that were transported eastward after convective lofting over Asia. Back-trajectories indicate the sampled air primarily originated from the Indian subcontinent. While short-lived organic bromine species show no measurable change over background mixing ratios, short-lived chlorinated organic species were elevated above background mixing ratios (dichloromethane (Δ48.2 ppt), 1,2-dichloroethane (Δ4.21 ppt), and chloroform (Δ4.85 ppt)), as well as longer-lived halogenated species, methyl chloride (Δ82.0 ppt) and methyl bromide (Δ1.91 ppt). This transported air mass thus contributed an excess equivalent effective chlorine burden of 316 ppt, with 119 ppt from short lived chlorinated species, to the TTL. Non-methane hydrocarbons (NMHC) were elevated 60 - 400% above background mixing ratios. The NMHC measurements were used to characterize the potential source regions, which are consistent with the convective influence analysis. The measurements indicate a chemical composition heavily impacted by biofuel/biomass burning and industrial emissions. This work shows that convection can loft Asian emissions, including short-lived chlorocarbons, and transport them to the remote TTL.

This study presents the chemical composition (carbonaceous and nitrogenous components) of aerosols (PM_2.5 and PM₁₀) along with stable isotopic composition (δ¹³C and δ¹⁵N) collected during winter and the summer months of 2015–16 to explore the possible sources of aerosols in megacity Delhi, India. The mean concentrations (mean ± standard deviation at 1σ) of PM_2.5 and PM₁₀ were 223 ± 69 µg m⁻³ and 328 ± 65 µg m⁻³, respectively during winter season whereas the mean concentrations of PM_2.5 and PM₁₀ were 147 ± 22 µg m⁻³ and 236 ± 61 µg m⁻³, respectively during summer season. The mean value of δ¹³C (range: − 26.4 to − 23.4‰) and δ¹⁵N (range: 3.3 to 14.4‰) of PM_2.5 were − 25.3 ± 0.5‰ and 8.9 ± 2.1‰, respectively during winter season whereas the mean value of δ¹³C (range: − 26.7 to − 25.3‰) and δ¹⁵N (range: 2.8 to 11.5‰) of PM_2.5 were − 26.1 ± 0.4‰ and 6.4 ± 2.5‰, respectively during the summer season. Comparison of stable C and N isotopic fingerprints of major identical sources suggested that major portion of PM_2.5 and PM₁₀ at Delhi were mainly from fossil fuel combustion (FFC), biomass burning (BB) (C-3 and C-4 type vegitation), secondary aerosols (SAs) and road dust (SD). The correlation analysis of δ¹³C with other C (OC, TC, OC/EC and OC/WSOC) components and δ¹⁵N with other N components (TN, NH₄⁺ and NO₃⁻) are also support the source identification of isotopic signatures.