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Exposure to air pollution is a leading public health risk factor in India, especially over densely populated Delhi and the surrounding Indo-Gangetic Plain. During the post-monsoon seasons, the prevailing north-westerly winds are known to influence aerosol pollution events in Delhi by advecting pollutants from agricultural fires as well as from local sources. Here we investigate the year-round impact of meteorology on gaseous nitrogen oxides (NOx=NO+NO2). We use bottom-up NOx emission inventories (anthropogenic and fire) and high-resolution satellite measurement based tropospheric column NO2 (TCNO2) data, from S5P aboard TROPOMI, alongside a back-trajectory model (ROTRAJ) to investigate the balance of local and external sources influencing air pollution changes in Delhi, with a focus on different emissions sectors. Our analysis shows that accumulated emissions (i.e. integrated along the trajectory path, allowing for chemical loss) are highest under westerly, north-westerly and northerly flow during pre-monsoon (February–May) and post-monsoon (October–February) seasons. According to this analysis, during the pre-monsoon season, the highest accumulated satellite TCNO2 trajectories come from the east and north-west of Delhi. TCNO2 is elevated within Delhi and the Indo-Gangetic Plain (IGP) to the east of city. The accumulated NOx emission trajectories indicate that the transport and industry sectors together account for more than 80 % of the total accumulated emissions, which are dominated by local sources (>70 %) under easterly winds and north-westerly winds. The high accumulated emissions estimated during the pre-monsoon season under north-westerly wind directions are likely to be driven by high NOx emissions locally and in nearby regions (since NOx lifetime is reduced and the boundary layer is relatively deeper in this season). During the post-monsoon season the highest accumulated satellite TCNO2 trajectories are advected from Punjab and Haryana, where satellite TCNO2 is elevated, indicating the potential for the long-range transport of agricultural burning emissions to Delhi. However, accumulated NOx emissions indicate local (70 %) emissions from the transport sector are the largest contributor to the total accumulated emissions. High local emissions, coupled with a relatively long NOx atmospheric lifetime and shallow boundary layer, aid the build-up of emissions locally and along the trajectory path. This indicates the possibility that fire emissions datasets may not capture emissions from agricultural waste burning in the north-west sufficiently to accurately quantify their influence on Delhi air quality (AQ). Analysis of daily ground-based NO2 observations indicates that high-pollution episodes (>90th percentile) occur predominantly in the post-monsoon season, and more than 75 % of high-pollution events are primarily caused by local sources. But there is also a considerable influence from non-local (30 %) emissions from the transport sector during the post-monsoon season. Overall, we find that in the post-monsoon season, there is substantial accumulation of high local NOx emissions from the transport sector (70 % of total emissions, 70 % local), alongside the import of NOx pollution into Delhi (30 % non-local). This work indicates that both high local NOx emissions from the transport sector and the advection of highly polluted air originating from outside Delhi are of concern for the population. As a result, air quality mitigation strategies need to be adopted not only in Delhi but in the surrounding regions to successfully control this issue. In addition, our analysis suggests that the largest benefits to Delhi NOx air quality would be seen with targeted reductions in emissions from the transport and agricultural waste burning sectors, particularly during the post-monsoon season.

The Indian capital megacity of Delhi is reeling under deteriorating air quality, and control measures are not yielding any significant changes, mainly due to a poor understanding of sources of emissions; hence, priority option in mitigation planning is lacking. In this paper, we have made an attempt to develop a spatially resolved technological high-resolution gridded (∼0.4km×0.4km) emission inventory for eight major pollutants of the Delhi region where high-resolution activity data of all possible major and unattended minor sources are generated by organizing a mega-campaign involving hundreds of volunteers. It is for the first time that we are able to estimate the decadal growth in emissions of various pollutants by comparing newly developed 2020 emissions with SAFAR (System of Air Quality and Weather Forecasting and Research) emissions of 2010 using the identical methodology and quantum of activity data. The estimated annual emissions for PM2.5, PM10, CO, NOx, VOC, SO2, BC, and OC over the Delhi National Capital Region (NCR) are estimated to be 123.8, 243.6, 799.0, 488.9, 730.0, 425.8, 33.6, and 20.3 Gg yr−1, respectively, for the year 2020. The decadal growth (2010–2020) in PM2.5 and PM10 is found to be marginal at 31 % and 3 %, respectively. The maximum growth is found to be in the transport sector followed by the industrial and other sectors. Maximum decadal growth found for the pollutants BC, OC, and NOx is 57 %, 34 %, and 91 %, respectively. The decadal shift of sectorial emissions with changing policies is examined. The complete dataset is available on Zenodo at https://doi.org/10.5281/zenodo.7715595 (Sahu et al., 2023).

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analyzed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and to identify the appropriate parameter combination for the VBS approach and hence to provide valuable information to improve our understanding of OA production.

Abstract This study reports a very high-resolution (400 m grid-spacing) operational air quality forecasting system developed to alert residents of Delhi and the National Capital Region (NCR) about forthcoming acute air pollution episodes. Such a high-resolution system has been developed for the first time and is evaluated during October 2019-February 2020. The system assimilates near real-time aerosol observations from in situ and space-borne platform in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to produce a 72-h forecast daily in a dynamical downscaling framework. The assimilation of aerosol optical depth and surface PM2.5 observations improves the initial condition for surface PM2.5 by about 45 µg/m3 (about 50%).The accuracy of the forecast degrades slightly with lead time as mean bias increase from + 2.5 µg/m3 on the first day to − 17 µg/m3 on the third day of forecast. Our forecast is found to be very skillful both for PM2.5 concentration and unhealthy/ very unhealthy air quality index categories, and has been helping the decision-makers in Delhi make informed decisions.

A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India. Observations and model results suggest that O3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O3 control strategies.

Fine particulate matter (PM2.5) and surface ozone (O3) are major air pollutants in megacities such as Delhi, but the design of suitable mitigation strategies is challenging. Some strategies for reducing PM2.5 may have the notable side effect of increasing O3. Here, we demonstrate a numerical framework for investigating the impacts of mitigation strategies on both PM2.5 and O3 in Delhi. We use Gaussian process emulation to generate a computationally efficient surrogate for a regional air quality model (WRF-Chem). This allows us to perform global sensitivity analysis to identify the major sources of air pollution and to generate emission-sector-based pollutant response surfaces to inform mitigation policy development. Based on more than 100 000 emulation runs during the pre-monsoon period (peak O3 season), our global sensitivity analysis shows that local traffic emissions from the Delhi city region and regional transport of pollution emitted from the National Capital Region (NCR) surrounding Delhi are dominant factors influencing PM2.5 and O3 in Delhi. They together govern the O3 peak and PM2.5 concentration during daytime. Regional transport contributes about 80% of the PM2.5 variation during the night. Reducing traffic emissions in Delhi alone (e.g. by 50 %) would reduce PM2.5 by 15 %–20 % but lead to a 20 %–25 % increase in O3. However, we show that reducing NCR regional emissions by 25 %–30 % at the same time would further reduce PM2.5 by 5 %–10 % in Delhi and avoid the O3 increase. This study provides scientific evidence to support the need for joint coordination of controls on local and regional scales to achieve effective reduction in PM2.5 whilst minimising the risk of O3 increase in Delhi.

Here we present results from an evaluation of model simulations from the International Hemispheric Transport of Air Pollution Phase II (HTAPII) and Chemistry Climate Model Initiative (CCMI) model inter-comparison projects against a comprehensive series of ground-based, aircraft and satellite observations of ozone mixing ratios made at various locations across India. The study focuses on the recent past (observations from 2008 to 2013, models from 2009–2010) as this is most pertinent to understanding the health impacts of ozone. To our understanding this is the most comprehensive evaluation of these models' simulations of ozone across the Indian subcontinent to date. This study highlights some significant successes and challenges that the models face in representing the oxidative chemistry of the region. The multi-model range in area-weighted surface ozone over the Indian subcontinent is 37.26–56.11 ppb, whilst the population-weighted range is 41.38–57.5 ppb. When compared against surface observations from the Modelling Atmospheric Pollution and Networking (MAPAN) network of eight semi-urban monitoring sites spread across India, we find that the models tend to simulate higher ozone than that which is observed. However, observations of NOx and CO tend to be much higher than modelled mixing ratios, suggesting that the underlying emissions used in the models do not characterise these regions accurately and/or that the resolution of the models is not adequate to simulate the photo-chemical environment of these surface observations. Empirical orthogonal function (EOF) analysis is used in order to identify the extent to which the models agree with regards to the spatio-temporal distribution of the tropospheric ozone column, derived using OMI-MLS observations. We show that whilst the models agree with the spatial pattern of the first EOF of observed tropospheric ozone column, most of the models simulate a peak in the first EOF seasonal cycle represented by principle component 1, which is later than the observed peak. This suggests a widespread systematic bias in the timing of emissions or some other unknown seasonal process. In addition to evaluating modelled ozone mixing ratios, we explore modelled emissions of NOx, CO, volatile organic compounds (VOCs) and the ozone response to the emissions. We find a high degree of variation in emissions from non-anthropogenic sources (e.g. lightning NOx and biomass burning CO) between models. Total emissions of NOx and CO over India vary more between different models in the same model intercomparison project (MIP) than the same model used in different MIPs, making it impossible to diagnose whether differences in modelled ozone are due to emissions or model processes. We therefore recommend targeted experiments to pinpoint the exact causes of discrepancies between modelled and observed ozone and ozone precursors for this region. To this end, a higher density of long-term monitoring sites measuring not only ozone but also ozone precursors including speciated VOCs, located in more rural regions of the Indian subcontinent, would enable improvements in assessing the biases in models run at the resolution found in HTAPII and CCMI.

Air pollution is linked to higher rates of human mortality especially those infected with COVID 19. Ozone is a harmful pollutant and is responsible for many health issues. However, some reports suggest that ozone is a strong disinfectant, and can kill the viruses. We hereby, report on the vulnerability of ozone due to COVID-19 lockdown whose levels flutter from surging to saturation in a highly polluted Indian capital, due to significant decline in anthropogenic emissions of ozone precursors. Average observed levels stabilized at 30 ppb, 12 ppb, 740 ppb, and 900 ppb for ozone (O3), nitrogen dioxide (NO2), carbon monoxide (CO) and volatile organic compounds (VOCs) respectively during lockdown period from 27th March to 10th April 2020. The NO2, CO and VOC declined by 50 %, 37 %, 38 % respectively during the lockdown period of 2020 as compared to similar period in 2019. The anomalous response of ozone during the lockdown is explained by resolving the poorly known complex O3-NOx-VOCs mechanism with the help of data from air monitoring stations in Delhi, India. The data obtained from this study advances the fundamental understanding of ozone chemistry that may lead to improved ozone parameterization in chemical transport models and better planning of ozone risk management strategies for any global mega cities.

We evaluate numerical simulations of surface ozone mixing ratios over the south Asian region during the pre-monsoon season, employing three different emission inventories in the Weather Research and Forecasting model with Chemistry (WRF-Chem) with the second-generation Regional Acid Deposition Model (RADM2) chemical mechanism: the Emissions Database for Global Atmospheric Research – Hemispheric Transport of Air Pollution (EDGAR-HTAP), the Intercontinental Chemical Transport Experiment phase B (INTEX-B) and the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS). Evaluation of diurnal variability in modelled ozone compared to observational data from 15 monitoring stations across south Asia shows the model ability to reproduce the clean, rural and polluted urban conditions over this region. In contrast to the diurnal average, the modelled ozone mixing ratios during noontime, i.e. hours of intense photochemistry (11:30–16:30 IST – Indian Standard Time – UTC +5:30), are found to differ among the three inventories. This suggests that evaluations of the modelled ozone limited to 24 h average are insufficient to assess uncertainties associated with ozone buildup. HTAP generally shows 10–30 ppbv higher noontime ozone mixing ratios than SEAC4RS and INTEX-B, especially over the north-west Indo-Gangetic Plain (IGP), central India and southern India. The HTAP simulation repeated with the alternative Model for Ozone and Related Chemical Tracers (MOZART) chemical mechanism showed even more strongly enhanced surface ozone mixing ratios due to vertical mixing of enhanced ozone that has been produced aloft. Our study indicates the need to also evaluate the O3 precursors across a network of stations and the development of high-resolution regional inventories for the anthropogenic emissions over south Asia accounting for year-to-year changes to further reduce uncertainties in modelled ozone over this region.

We evaluated three emission inventories of black carbon (BC) using Lagrangian particle dispersion model simulations and BC observations from a rural site in southern India (Gadanki; 13.48° N, 79.18° E) from 2008 to 2012. We found that 93 to 95% of the BC load at the observation site originated from emissions in India and the rest from the neighbouring countries and shipping. A substantial fraction (33 to 43%) of the BC was transported from northern India. Wet deposition is found to play a minor role in reducing BC mass at the site because of its proximity to BC sources during rainy season and relatively short rainy season over western and northern parts of India. Seasonally, the highest BC concentration (approx. 3.3 μg m−3) is observed during winter, followed by spring (approx. 2.8 μg m−3). While the model reproduced well the seasonal cycle, the modelled BC concentrations are significantly lower than observed values, especially in spring. The model bias is correlated to fire radiative power – a proxy of open biomass burning activity. Using potential emission sensitivity maps derived using the model, we suggest that underestimation of BC mass in the model during spring is due to the underestimation of BC fluxes over southern India (possibly from open-biomass-burning/forest-fires). The overall performance of the model simulations using three different emission inventories (SAFAR-India, ECLIPSE and RETRO) is similar, with ECLIPSE and SAFAR-India performing marginally better as both have about 30% higher emissions for India than RETRO. The ratio of observed to modelled annual mean BC concentration was estimated as 1.5 for SAFAR, 1.7 for ECLIPSE and 2.4 for RETRO.

Air quality during the Commonwealth Games (CWG, held in Delhi in October 2010) is analyzed using a new air quality forecasting system established for the games. The CWG stimulated enhanced efforts to monitor and model air quality in the region. The air quality of Delhi during the CWG had high levels of particles with mean values of PM2.5 and PM10 at the venues of 111 and 238 μg m−3, respectively. Black carbon (BC) accounted for ~ 10% of the PM2.5 mass. It is shown that BC, PM2.5 and PM10 concentrations are well predicted, but with positive biases of ~ 25%. The diurnal variations are also well captured, with both the observations and the modeled values showing nighttime maxima and daytime minima. A new emissions inventory, developed as part of this air quality forecasting initiative, is evaluated by comparing the observed and predicted species-species correlations (i.e., BC : CO; BC : PM2.5; PM2.5 : PM10). Assuming that the observations at these sites are representative and that all the model errors are associated with the emissions, then the modeled concentrations and slopes can be made consistent by scaling the emissions by 0.6 for NOx, 2 for CO, and 0.7 for BC, PM2.5, and PM10. The emission estimates for particles are remarkably good considering the uncertainty in the estimates due to the diverse spread of activities and technologies that take place in Delhi and the rapid rates of change. The contribution of various emission sectors including transportation, power, domestic and industry to surface concentrations are also estimated. Transport, domestic and industrial sectors all make significant contributions to PM levels in Delhi, and the sectoral contributions vary spatially within the city. Ozone levels in Delhi are elevated, with hourly values sometimes exceeding 100 ppb. The continued growth of the transport sector is expected to make ozone pollution a more pressing air pollution problem in Delhi. The sector analysis provides useful inputs into the design of strategies to reduce air pollution levels in Delhi. The contribution for sources outside of Delhi on Delhi air quality range from ~ 25% for BC and PM to ~ 60% for day time ozone. The significant contributions from non-Delhi sources indicates that in Delhi (as has been show elsewhere) these strategies will also need a more regional perspective.

Long-term data available from Lidar systems located at three different locations namely São José dos Campos, Brazil (23.2° S, 45.8° W), Gadanki (13.5° N, 79.2° E) and Reunion (20.8° S, 55.5° E) have been used to investigate the long-term variations like Annual, Semi-annual, Quasi-biennial, El Nino Southern Oscillation and solar cycle. These oscillations are also extracted from simultaneous satellite borne measurements of HALogen Occultation Experiment (HALOE) instrument onboard UARS and SABER onboard TIMED over these stations making largest time series covering the entire middle atmosphere. A good agreement is found between the LIDAR and satellite-derived amplitudes and phases between 30 and 65 km altitude, which suggests that satellite measurements can be used to investigate the long-term trends globally. Latter measurements are extended to 80 km in order to further investigate these oscillations. Large difference in the amplitudes between the eastern pacific and western pacific is noticed in these oscillations. Changing from cooling trends in the stratosphere to warming trends in the mesosphere occurs more or less at altitude around 70 km altitude and this result agrees well with that observed by satellite measurements reported in the literature. The peak in the cooling trend does not occur at a fixed altitude in the stratosphere however maximum warming trend is observed around 75 km at all the stations. The observed long-term trends including various oscillations are compared with that reported with various techniques.

The Model for Ozone and Related chemical Tracers-2 (MOZART-2) is used to examine the evolution of pollutant O3 in the upper troposphere over the Indian region. Vertical profiles of ozone mixing ratio retrieved from Microwave Limb Sounder (MLS) aboard Earth Observing System (EOS) AURA satellite for the period 2005–2009 and Tropospheric Emission Spectrometer (TES) aboard (EOS) AURA for the period 2006–2007 has been analyzed. The satellite observations reveal the evidence of downward propagation of ozone (100–200 ppb) due to stratospheric intrusion during the winter and pre-monsoon seasons. The regular feature of enhancement of ozone in the upper troposphere over India is presented. Results obtained by the MOZART-2 simulations (for years 2000–2005) confirm the observations and indicate stratospheric intrusion of O3 during winter and pre-monsoon seasons. Observed enhanced O3 mixing ratio in the upper troposphere is explained by, variation of Potential Vorticity (PV), tropopause pressure, relative humidity and CO-O3 correlation.

Recent thinning of glaciers over the Himalayas (sometimes referred to as the third polar region) have raised concern on future water supplies since these glaciers supply water to large river systems that support millions of people inhabiting the surrounding areas. Black carbon (BC) aerosols, released from incomplete combustion, have been increasingly implicated as causing large changes in the hydrology and radiative forcing over Asia and its deposition on snow is thought to increase snow melt. In India BC emissions from biofuel combustion is highly prevalent and compared to other regions, BC aerosol amounts are high. Here, we quantify the impact of BC aerosols on snow cover and precipitation from 1990 to 2010 over the Indian subcontinental region using two different BC emission inventories. New estimates indicate that Indian BC emissions from coal and biofuel are large and transport is expected to expand rapidly in coming years. We show that over the Himalayas, from 1990 to 2000, simulated snow/ice cover decreases by ~0.9% due to aerosols. The contribution of the enhanced Indian BC to this decline is ~36%, similar to that simulated for 2000 to 2010. Spatial patterns of modeled changes in snow cover and precipitation are similar to observations (from 1990 to 2000), and are mainly obtained with the newer BC estimates.

A high resolution regional chemistry-transport model has been used to study the distribution of exposure-plant response index (AOT40, Accumulated exposure Over a Threshold of 40 ppb, expressed as ppb h) over the Indian geographical region for the year 2003 as case study. The directives on ozone pollution in ambient air provided by United Nations Economic Commission for Europe (UNECE) and World Health Organization (WHO) for vegetation protection (AOT40) have been used to assess the air quality. A substantial temporal and spatial variation in AOT40 values has been observed across the Indian region. Large areas of India show ozone values above the AOT40 threshold limit (3000 ppb h for 3 months). Simulated AOT40 values are found to be substantially higher throughout the year over the most fertile Indo-Gangetic plains than the other regions of India, which can have an adverse effect on plants and vegetation in this region. The observed monthly AOT40 values reported from an Indian station, agree reasonably well with model simulated results. There is an underestimation of AOT40 in the model results during the periods of highest ozone concentration from December to March. We find that the simulated AOT40 target values for protection of vegetation is exceeded even in individual months, especially during November to April. Necessary and effective emission reduction strategies are therefore required to be developed in order to curb the surface level ozone pollution to protect the vegetation from further damage in India whose economy is highly dependent on agricultural sector and may influence the global balance.

Spatiotemporal characteristics of the ozone quasi-biennial oscillation (QBO) over the tropical-subtropical stratosphere (40° S–40° N) have been examined by analyzing data from the Microwave Limb Sounder (MLS) aboard Upper Atmospheric Research Satellite (UARS) for the period 1992–1999. A combination of regression analysis and wavelet analysis combines to act as an accurate QBO filter. Wavelet analysis provides inter-annual variability of amplitude and phase of the ozone QBO in the vertical structure of tropical-subtropical stratosphere. It gives minute details of phase propagation and descend rates, which can be used as input to models. Latitude-height structure shows evidence of a secondary meridional circulation induced by the QBO as double peak structure at the equator with maximum amplitude at two pressure levels 30 hPa and 9 hPa and a node at 14 hPa. The equatorial maxima are out of phase with each other. The maximum amplitude (~1.4 ppmv) of the ozone QBO was observed near the equator at 10 hPa. Descent rate of the easterly phase is greater than westerly. The lag correlation of the ozone QBO with circulation and variation of descent rates in the vertical structure of the stratosphere are examined in detail. In the equatorial upper stratosphere ozone anomalies descent with the rate ~1.5 km/month but in tropics and subtropics (above 2 hPa) they propagate upward.

In the upper atmosphere, greenhouse gases produce a cooling effect, instead of a warming effect. Increases in greenhouse gas concentrations are expected to induce substantial changes in the mesosphere, thermosphere, and ionosphere, including a thermal contraction of these layers. In this article we construct for the first time a pattern of the observed long-term global change in the upper atmosphere, based on trend studies of various parameters. The picture we obtain is qualitative, and contains several gaps and a few discrepancies, but the overall pattern of observed long-term changes throughout the upper atmosphere is consistent with model predictions of the effect of greenhouse gas increases. Together with the large body of lower atmospheric trend research, our synthesis indicates that anthropogenic emissions of greenhouse gases are affecting the atmosphere at nearly all altitudes between ground and space.

In this paper a brief overview of the changes in atmospheric ion compositions driven by the human-induced changes in related neutral species, and temperature from the troposphere to lower thermosphere has been made. It is found that ionic compositions undergo significant variations. The variations calculated for the double-CO2 scenario are both long-term and permanent in nature. Major neutrals which take part in the lower and middle atmospheric ion chemical schemes and undergo significant changes due to anthropogenic activities are: O, O2, H2O, NO, acetonitrile, pyridinated compounds, acetone and aerosol. The concentration of positive ion/electron density does not change appreciably in the middle atmosphere but indicates a marginal decrease above about 75 km until about 85 km, above which the magnitude of negative trend decreases and becomes negligible at 93 km. Acetonitrile cluster ions in the upper stratosphere are likely to increase, whereas NO+ and NO+(H2O) in the mesosphere and lower thermosphere (MLT) region are expected to decrease for the double CO2 scenario. It is also found that the atmospheric density of pyridinated cluster ions is fast rising in the troposphere.

To investigate the effects of decadal solar variability on ozone and temperature in the tropical stratosphere, along with interconnections to other features of the middle atmosphere, simultaneous data obtained from the Halogen Occultation Experiment (HALOE) aboard the Upper Atmospheric Research Satellite (UARS) and the Stratospheric Aerosol and Gas Experiment II (SAGE II) aboard the Earth Radiation Budget Satellite (ERBS) during the period 1992–2004 have been analyzed using a multifunctional regression model. In general, responses of solar signal on temperature and ozone profiles show good agreement for HALOE and SAGE~II measurements. The inferred annual-mean solar effect on temperature is found to be positive in the lower stratosphere (max 1.2±0.5 K / 100 sfu) and near stratopause, while negative in the middle stratosphere. The inferred solar effect on ozone is found to be significant in most of the stratosphere (2±1.1–4±1.6% / 100 sfu). These observed results are in reasonable agreement with model simulations. Solar signals in ozone and temperature are in phase in the lower stratosphere and they are out of phase in the upper stratosphere. These inferred solar effects on ozone and temperature are found to vary dramatically during some months, at least in some altitude regions. Solar effects on temperature are found to be negative from August to March between 9 mb–3 mb pressure levels while solar effects on ozone are maximum during January–March near 10 mb in the Northern Hemisphere and 5 mb–7 mb in the Southern Hemisphere.

To study the mesospheric temperature inversion, daily temperature profiles obtained from the Halogen Occultation Experiment (HALOE) aboard the Upper Atmospheric Research Satellite (UARS) during the period 1991-2001 over the Indian tropical region (0-30° N, 60-100° E) have been analyzed for the altitude range 34-86km. The frequency of occurrence of inversion is found to be 67% over this period, which shows a strong semiannual cycle, with a maximum occurring one month after equinoxes (May and November). Amplitude of inversion is found to be as high as 40K. Variation of monthly mean peak and bottom heights along with amplitude of inversions also show the semiannual cycle. The inversion layer is detected most frequently in the altitude range of 70-85km, with peak height ranging from 80 to 83km and that of the bottom height from 72 to 74km. A comparison of frequency of temperature inversion with that obtained from Rayleigh lidar observations over Gadanki (13.5° N, 60-100° E) is found to be reasonable. The seasonal variation of amplitude and frequency of occurrence of temperature inversion indicates a good correlation with seasonal variation of average ozone concentration over the altitude range of the inversion layer.

This paper discusses the influence of aerosols on UV erythemal dose over four metro cities in India. Tropospheric Emission Monitoring Internet Service (TEMIS), archived UV-index (UV-I), and UV daily erythemal dose obtained from SCIAMACHY satellite were used in this study during June 2004 and May 2005 periods covering four important Indian seasons. UV-Index (UV-I), an important parameter representing UV risk, was found to be in the high to extreme range in Chennai (8.1 to 15.33), moderate to extreme range in Mumbai and Kolkata (5 to 16.5), and low to extreme over Delhi (3 to 15). Average UV erythemal dose showed seasonal variation from 5.9 to 6.3 KJm−2 during summer, 2.9 to 4.4 KJm−2 during postmonsoon, 3 to 4.5 KJm−2 during winter, and 5.1 to 6.19 KJm−2 during premonsoon seasons over the four cities. To estimate the influence of aerosols on reducing UV dose, UV aerosol radiative forcing and forcing efficiency were estimated over the sites. The average aerosol forcing efficiency was found to be from -1.38±0.33 to -3.01±0.28 KJm−2 AOD−1 on different seasons. The study suggests that aerosols can reduce the incoming UV radiation dose by 30–60% during different seasons.