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Seasonal changes in the tropospheric NO2 column in the TP. The seasons are defined as winter (December–January–February, DJF), spring (March–April–May, MAM), summer (June–July–August, JJA) and autumn (September–October–November, SON). The corresponding seasonal wind vectors are overlaid
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The Third Pole, Hindu Kush Himalaya (HKH) and Tien Shan mountains, has been closely monitored for the past few decades because of its deteriorating environmental condition. Here, we analyse the spatio-temporal changes in tropospheric NO2 over TP using satellite observations from 2005 to 2020. The highest NO¬2 concentrations (i.e. ≥ 1 × 1015 molec....
Citations
... The major sources of NO 2 are motor vehicles, power plants and waste disposal systems (Seinfeld & Pandis, 2016;Gopikrishnan et al., 2022). NO 2 has a strong correlation with short-term anthropogenic activities and has a relatively short lifetime of few hours to days (Sharma et al., 2023;Kenagy et al., 2018). The secondary formation of ozone during daytime is regulated by the nonlinear chemical The letters indicate the first three letters of each city considered in the study (see Fig. 1 for their full names). ...
There is a significant increase in ozone at the surface and troposphere due to growing population, industrialization and urbanization. The initiation of National Clean Air Programme (NCAP) in 2019 marked a turning point in addressing air pollution in Indian cities. The Central Pollution Control Board (CPCB) ground-based measurements show a reduction in number of days with continuous exposure to 8 h surface ozone (MDA-8) exceeding 100 ppb since the implementation of NCAP. For instance, cities such as Visakhapatnam and Tirupati reported zero days of MDA-8 ozone surpassing 100 ppb in 2022. Also, a substantial reduction is observed in the frequency of MDA-8 ozone exceeding the 100 ppb threshold at other stations. The NO2 and PM2.5 measurements from CPCB show a decreasing trend at most stations, whereas satellite-based HCHO and NO2 measurements show negative (0–0.004 mol m−2 month−1) and positive (0–0.02 m−2 month−1) trends, respectively, during the period of 2019–2022. Therefore, although the implementation of NCAP is oriented towards reducing PM10 concentrations, it is also proven to be effective in curbing ozone pollution in most cities of India. This study, therefore, suggests to continue the efforts of NCAP and to implement tailored regulations for reducing ozone pollution in cities with high pollution.
... However, the changes in BC and OC are stronger from 2000 onwards. The increase in BC concentration after 2000 is mainly due to the large-scale transportation construction, increase in fossil fuel consumption, industrial development, agricultural activities and energy consumption in TP and neighboring countries (Kan et al., 2012;Sharma et al., 2023). The big change in BC concentration during winter and spring, and OC in spring after 2000 are closely associated with biomass burning aerosols from the south and Southeast Asia (Yang et al., 2021). ...
We analyse the long-term (1980-2020) changes in aerosols over the Third Pole (TP) and assess the changes in radiative forcing (RF) using satellite, ground-based and reanalysis data. The annual mean aerosol optical depth (AOD) varies from 0.06 to 0.24, with the highest values of around 0.2 in the north and southwest TP, which are dominated by dust from Taklimakan and Thar deserts, respectively. However, Organic Carbon (OC), Black Carbon (BC) and sulphate aerosols have significant contribution to the total AOD in the south and east TP. High amounts of dust are observed in spring and summer, but BC in winter. Trajectory analysis reveals that the air mass originated from East and South Asia carries BC and OC, whereas the air from South Asia, Central Asia and Middle East brings dust to TP. Significant positive trends in AOD is found in TP, with high values of about 0.002/yr in the eastern and southern TP. There is a gradual increase in BC and OC concentrations during 1980-2020, but the change from 2000 is phenomenal. The RF at the top of the atmosphere varies from -10 to 2 W/m2 in TP, and high positive RF of about 2 W/m2 is estimated in Pamir, Karakoram and Nyainquentanglha mountains, where the massive glacier mass exists. The RF has increased in much of TP during recent decades (2001-2020) with respect to previous decades (1981-2000), which can be due to the rise in BC and dust during the latter period. Therefore, the positive trend in BC and its associated change in RF can amplify the regional warming, and thus, the melting of glaciers or ice in TP. This is a great concern as it is directly connected to the water security of many South Asian countries.
Meteorological factors play a key role in air pollution, where high ozone (O3) levels are often associated with intense solar radiation and high temperatures. These factors have one of the largest effects on the temporal dynamics of air pollutants. Other key quantities in this process are concentrations of NO and NO2. Accordingly, this work aims to study the correlations between the concentrations of O3, NO, NO2, with the levels of global solar radiation and temperature, and also the correlation of each of these quantities measured in pairs of two close monitoring stations in the same municipality. For this purpose, we have used data from QUALAR-CETESB for NO, NO2, O3 concentrations, global solar radiation (RADG), and temperature (TEMP) during the period from 01/01/2018 to 31/07/2023, measured in 18 monitoring stations in the State of São Paulo (Campinas-Taquaral, Campinas-Vila União, Capão Redondo, Carapicuíba, Catanduva, Guaratinguetá, Guarulhos-Paço Municipal, Guarulhos-Pimentas, Limeira, Marília, Parque D. Pedro II, Paulínia, Ribeirão Preto, São Bernardo-Centro, São José dos Campos-Jardim Satélite, Santos, Santos-Ponta da Praia, and Taubaté). Data from near each other stations were only available for Campinas-Taquaral/Campinas-Vila União, Guarulhos-Pimentas/Guarulhos-Paço Municipal, and Santos/Santos-Ponta da Praia. Methodologically, the correlations between the variables of interest (NO, NO2, O3, RADG, TEMP) were first analyzed by calculating the Pearson correlation coefficient (r). In cases where a very weak correlation was found (|r| < 0.1), or the Pearson correlation was not statistically significant (i.e., p-value > 0.05), we also computed the Kendall and Spearman correlation coefficients to account for possible nonlinearities. In each case, each correlation r was broadly classified as weak (|r| < 0.3), moderate (0.3 ≤ |r| < 0.5), and strong (|r| ≥ 0.5). Unless otherwise specified, we used the term “correlation” to mean “Pearson correlation”, indicating its classification as VAR1-VAR2 (number of stations and corresponding classification). Correlations: O3-TEMP (16, strong positive), O3-RADG (16, strong positive), NO-NO2 (15 strong positive), RADG-TEMP (16 strong positive), NO2-O3 (7 strong negative, 9 moderate negative), NO-O3 (16 moderate negative), NO-RADG (11 weak negative), NO-TEMP (14 weak negative), NO2-RADG (9 weak negative, 5 moderate negative). Only for the correlation NO2-TEMP, we found three stations where the Pearson correlation was not statistically significant, and the resulting Kendall and Spearman correlations were less than 0.1; for the other fifteen, we found NO2-TEMP (7 moderate negative, 8 weak negative). Considering the correlations in close stations (Campinas-Taquaral/Campinas-Vila União, 10 km; Guarulhos-Pimentas and Guarulhos-Paço Municipal, 11 km; Santos and Santos-Ponta de Praia, 3 km), all the correlations between the measurements of the same variable within these three pairs of stations were classified as strongly positive. The three correlations of NO in the pairs of Campinas, Guarulhos, and Santos deserve attention as having the lowest correlation values: 0.66 for NO in the Guarulhos pair, 0.70 for NO in the Campinas pair and, for NO in the Santos pair, due to the lack of Pearson correlation, a Kendall and Spearman correlations of 0.66 and 0.80, respectively. Moreover, for all these three pairs of stations, the mean values of the correlations of each variable measured at the referred three pairs of stations obey the following order: rmean(TEMP) > rmean(RADG) > rmean(O3) > rmean(NO2) > rmean(NO). The reported results are consistent with what is expected from the tropospheric ozone cycle. They also suggest different atmospheric processes occurring at different sites. Our purpose here is to reveal trends and quantify all the ten correlations between the concentrations of NO, NO2, O3, global solar radiation, and temperature.
The Third Pole (TP) is a high mountain region in the world, and is well-known for its pristine environment, but recent development activities in the region have degraded its air quality. Here, we investigate the spatial and temporal changes of the air pollutants ammonia (NH₃), sulphur dioxide (SO₂) and carbon monoxide (CO) in TP, and reveal their sources using satellite measurements and emission inventory. We observe a clear seasonal cycle of NH3 in TP, with high values in summer and low values in winter. The intense agriculture activities in the southern TP are the cause of high NH₃ (6–8 × 1016 molec./cm2) there. Similarly, CO shows a distinct seasonal cycle with high values in spring in the southeast TP due to biomass burning. In addition, the eastern boundary of TP in the Sichuan and Qinghai provinces also show high values of CO (about 1.5 × 1018 mol/cm2), primarily owing to the industrial activities. There is no seasonal cycle found for SO₂ distribution in TP, but relatively high values (8–10 mg/m2)) are observed in its eastern boundary. The high-altitude pristine regions of inner TP are also getting polluted because of recent human activities in and around TP, as we estimate positive trends in CO (0.5–1.5 × 1016 mol/cm2/yr) there. In addition, positive trends are also found in NH₃ (0.025 × 1016 molec./cm2/yr) during 2008–2020 in most regions of TP and SO₂ (about 0.25–0.75 mg/m2/yr) in the Sichuan and Qinghai region during 2000–2020. As revealed by the emission inventory, there are high anthropogenic emissions of NH3, SO2 and CO within TP. There are emissions of pollutants from energy sectors, oil and refinery, agriculture waste burning and manure management within TP. These anthropogenic activities accelerate the ongoing development in TP, but severely erode its environment.
