Seasonal characteristics of SO2, NO2, and CO emissions in and around the Indo-Gangetic Plain

A critical review and prospect of NO2 and SO2 pollution over Asia: Hotspots, trends, and sources

Nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) are two major atmospheric pollutants that significantly threaten human health, the environment, and ecosystems worldwide. Despite this, only some studies have investigated the spatiotemporal hotspots of NO₂ and SO₂, their trends, production, and sources in Asia. Our study presents a literature review covering the production, trends, and sources of NO₂ and SO₂ across Asian countries (e.g., Bangladesh, China, India, Iran, Japan, Pakistan, Malaysia, Kuwait, and Nepal). Based on the findings of the review, NO₂ and SO₂ pollution are increasing due to industrial activity, fossil fuel burning, biomass burning, heavy traffic movement, electricity generation, and power plants. There is significant concern about health risks associated with NO₂ and SO₂ emissions in Bangladesh, China, India, Malaysia, and Iran, as they pay less attention to managing and controlling pollution. Even though the lack of quality datasets and adequate research in most Asian countries further complicates the management and control of NO₂ and SO₂ pollution. This study has NO₂ and SO₂ pollution scenarios, including hotspots, trends, sources, and their influences on Asian countries. This study highlights the existing research gaps and recommends new research on identifying integrated sources, their variations, spatiotemporal trends, emission characteristics, and pollution level. Finally, the present study suggests a framework for controlling and monitoring these two pollutants' emissions.

Air quality trends in rural India: analysis of NO2 pollution using satellite measurements

India is a country with more than 67% of its population (947 million) residing in rural areas and 33% in urban areas (472 million) as of 2020. Therefore, health of the people living in rural India is very important for its future development plans, economy and growth. Here, we analyse the rural air quality using satellite measurements of NO₂ in India, as the sources of NO₂ are well connected to the industrial and economic uplift of a nation. Our analyses for the rural regions show distinct seasonal changes with the highest value (2.0 × 10¹⁵ molecules per cm²) in winter and the lowest in monsoon (1.5 × 10¹⁵ molecules per cm²) seasons. About 41% of the total NO₂ pollution in India is from its rural sources, but 59% of the urban sources were focused in the past studies. In addition, around 45% of the rural NO₂ pollution is due to road transport, whereas more than 90% of it in urban India comes from the power sector. Our assessment shows that the NO₂ exposure in rural regions is as serious as that in urban areas, indicating the need for more effective reduction of population exposure and protection of public health. Henceforth, this study reveals that rural India is gradually getting polluted from its nearby regions as well as from the new sources within. This is a big concern for the public health of the large rural population of India.

Restricted Anthropogenic Activities and Improved Urban Air Quality in China: Evidence from Real-Time and Remotely Sensed Datasets Using Air Quality Zonal Modeling

The study aims to examine the major atmospheric air pollutants such as NO2, CO, O3, PM2.5, PM10, and SO2 to assess the overall air quality using air quality zonal modeling of 15 major cities of China before and after the COVID-19 pandemic period. The spatio-temporal changes in NO2 and other atmospheric pollutants exhibited enormous reduction due to the imposition of a nationwide lockdown. The present study used a 10-day as well as 60-day tropospheric column time-average map of NO2 with spatial resolution 0.25 × 0.25° obtained from the Global Modeling and Assimilation Office, NASA. The air quality zonal model was employed to assess the total NO2 load and its change during the pandemic period for each specific region. Ground surface monitoring data for CO, NO2, O3, PM10, PM2.5, and SO2 including Air Quality Index (AQI) were collected from the Ministry of Environmental Protection of China (MEPC). The results from both datasets demonstrated that NO2 has drastically dropped in all the major cities across China. The concentration of CO, PM10, PM2.5, and SO2 demonstrated a decreasing trend whereas the concentration of O3 increased substantially in all cities after the lockdown effect as observed from real-time monitoring data. Because of the complete shutdown of all industrial activities and vehicular movements, the atmosphere experienced a lower concentration of major pollutants that improves the overall air quality. The regulation of anthropogenic activities due to the COVID-19 pandemic has not only contained the spread of the virus but also facilitated the improvement of the overall air quality. Guangzhou (43%), Harbin (42%), Jinan (33%), and Chengdu (32%) have experienced maximum air quality improving rates, whereas Anshan (7%), Lanzhou (17%), and Xian (25%) exhibited less improved AQI among 15 cities of China during the study period. The government needs to establish an environmental policy framework involving central, provincial, and local governments with stringent laws for environmental protection.

Consequences of pre and post confinement on the atmospheric air pollutants during spread of COVID-19 in India

COVID-19, a severe respiratory syndrome, was diagnosed in Wuhan, China, and in the last week of January 2020, it was reported in India. The drastic speed of spreading of COVID-19 imposed a total lockdown in India for the first time in four stages. This leads to restrictions on transport, industries, coal-based power plants, etc. During these stages of lockdown, a detailed analysis was done to study the effect of confinement on various air pollutants, PM₁₀, PM_2.5, SO₂, CO, NH₃, and NO_x (NO, NO₂) over the thirteen different stations situated at different states in India. The data were compared with pre-confinement duration at different locations in India. During confinement, the air pollutants showed less value when compared with the pre-confinement stage alarming everyone and also the Indian government to bring up rules and regulations for better air quality index so that such pandemics should be reduced.

Interpreting the COVID effect on atmospheric constituents over the Indian region during the lockdown: chemistry, meteorology, and seasonality

Most of the published articles which document changes in atmospheric compositions during the various lockdown and unlock phases of COVID-19 pandemic have made a direct comparison to a reference point (which may be 1 year apart) for attribution of the COVID-mediated lockdown impact on atmospheric composition. In the present study, we offer a better attribution of the lockdown impacts by also considering the effect of meteorology and seasonality. We decrease the temporal distance between the impacted and reference points by considering the difference of adjacent periods first and then comparing the impacted point to the mean of several reference points in the previous years. Additionally, we conduct a multi-station analysis to get a holistic effect of the different climatic and emission regimes. In several places in eastern and coastal India, the seasonally induced changes already pointed to a decrease in PM concentrations based on the previous year data; hence, the actual decrease due to lockdown would be much less than that observed just on the basis of difference of concentrations between subsequent periods. In contrast, northern Indian stations would normally show an increase in PM concentration at the time of the year when lockdown was effected; hence, actual lockdown-induced change would be in surplus of the observed change. The impact of wind-borne transport of pollutants to the study sites dominates over the dilution effects. Box model simulations point to a VOC-sensitive composition.

Estimation of short-lived climate forced sulfur dioxide in Tehran, Iran, using machine learning analysis

This paper presents a time-series analysis of SO₂ air concentration and the effects of particulates (either PM_2.5 and PM₁₀) concentrations and meteorological conditions (relative humidity and wind speed) on SO₂ trend in Tehran for the period from 2011 to 2020. The source data were obtained from 21 monitoring stations of Air Quality Control Company and meteorological stations in Tehran. To predict the status of future concentration of SO₂, PM_2.5 and PM₁₀, a Box-Jenkins ARIMA approach was used to model the monthly time series. Considering the whole period of ten years, a somewhat downward trend was noted for SO₂ air concentration, even though a slight rising trend was observed in 2020 year. Monthly sulfur dioxide concentrations showed the lowest value in June and the highest value in January. Seasonal concentrations were lowest in spring and highest in winter. Then, in the ArcGIS software, the IDW method was used to obtain air pollution zoning maps. As a result, the highest average concentration of SO₂ occurred in the north and southwest of Tehran. In the last step, Relations between the SO₂ concentration and particulate matters and relative humidity and wind speed were calculated statistically using the daily average data. We finally concluded that the combined effect of particulate matters and relative humidity with the increasing role of Sulfur dioxide overcomes the decreasing role of wind speed. This study can contribute to a better understanding of the SO₂ air pollution in Tehran affected by meteorological conditions and the rapid urbanization and industrialization, followed by the possible combustion of fuel oil in power plants and health problems.

Impact of the COVID-19 pandemic on air pollution in Chinese megacities from the perspective of traffic volume and meteorological factors

During 2020, the COVID-19 pandemic resulted in a widespread lockdown in many cities in China. In this study, we assessed the impact of changes in human activities on air quality during the COVID-19 pandemic by determining the relationships between air quality, traffic volume, and meteorological conditions. The megacities of Wuhan, Beijing, Shanghai, and Guangzhou were selected as the study area, and the variation trends of air pollutants for the period January-May between 2016 and 2020 were analyzed. The passenger volume of public transportation (PVPT) and the passenger volume of taxis (PVT) along with data on precipitation, temperature, relative humidity, wind speed, and boundary layer height were used to identify and quantify the driving force of the air pollution variation. The results showed that the change rates of fine particulate matter (PM_2.5), NO₂, and SO₂ before and during the lockdown in the four megacities ranged from -49.9% to 78.2% (average: -9.4% ± 59.3%), -55.4% to -32.3% (average: -43.0% ± 9.7%), and - 21.1% to 11.9% (average: -10.9% ± 15.4%), respectively. The response of NO₂ to the lockdown was the most sensitive, while the response of PM_2.5 was smaller and more delayed. During the lockdown period, haze from uninterrupted industrial emissions and fireworks under the effect of air mass transport from surrounding areas and adverse climate conditions was probably the cause of abnormally high PM_2.5 concentrations in Beijing. In addition, the PVT was the most significant factor for NO₂, and meteorology had a greater impact on PM_2.5 than NO₂ and SO₂. There is a need for more national-level policies for limiting firework displays and traffic emissions, as well as further studies on the formation and transmission of secondary air pollutants.

Humidity-Insensitive NO2 Sensors Based on SnO2/rGO Composites

This study reported a novel humidity-insensitive nitrogen dioxide (NO₂) gas sensor based on tin dioxide (SnO₂)/reduced graphene oxide (rGO) composites through the sol-gel method. The sensor demonstrated ppb-level NO₂ detection in p-type sensing behaviors (13.6% response to 750 ppb). Because of the synergistic effect on SnO₂/rGO p-n heterojunction, the sensing performance was greatly enhanced compared to that of bare rGO. The limit of detection of sensors was as low as 6.7 ppb under dry air. Moreover, benefited from the formed superhydrophobic structure of the SnO₂/rGO composites (contact angle: 149.0°), the humidity showed a negligible influence on the dynamic response (S_g) of the sensor to different concentration of NO₂ when increasing the relative humidity (RH) from 0 to 70% at 116°C. The relative conductivity of the sensor to 83% relative humidity was 0.11%. In addition, the response ratio (S_g/S_RH) between 750 ppb NO₂ and 83% RH was 649.0, indicating the negligible impaction of high-level ambient humidity on the sensor. The as-fabricated humidity-insensitive gas sensor can promise NO₂ detection in real-world applications such as safety alarm, chemical engineering, and so on.

COVID-19's lockdown effect on air quality in Indian cities using air quality zonal modeling

The complete lockdown due to COVID-19 pandemic has contributed to the improvement of air quality across the countries particularly in developing countries including India. This study aims to assess the air quality by monitoring major atmospheric pollutants such as AOD, CO, PM_2.5, NO₂, O₃ and SO₂ in 15 major cities of India using Air Quality Zonal Modeling. The study is based on two different data sources; (a) grid data (MODIS- Terra, MERRA-2, OMI and AIRS, Global Modeling and Assimilation Office, NASA) and (b) ground monitoring station data provided by Central Pollution Control Board (CPCB) / State Pollution Control Board (SPCB). The remotely sensed data demonstrated that the concentration of PM_2.5 has declined by 14%, about 30% of NO₂ in million-plus cities, 2.06% CO, SO₂ within the range of 5 to 60%, whereas the concentration of O₃ has increased by 1 to 3% in majority of cities compared with pre lockdown. On the other hand, CPCB/SPCB data showed more than 40% decrease in PM_2.5 and 47% decrease in PM₁₀ in north Indian cities, more than 35% decrease in NO₂ in metropolitan cities, more than 85% decrease in SO₂ in Chennai and Nagpur and more than 17% increase in O₃ in five cities amid 43 days pandemic lockdown. The restrictions of anthropogenic activities have substantial effect on the emission of primary atmospheric pollutants.

Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM2.5 and PM10) and gaseous pollutants (NO2, O3, CO, and SO2) during lockdown (25th March - 3rd May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM2.5, PM10, NO2, and CO has been found in all the regions during the lockdown. SO2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM2.5, PM10, and NO2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O3 has increased over IGP due to less O3 loss. The most significant reduction (∼40-60%) was found in PM2.5 and PM10. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM2.5, PM10, NO2, and enhancement in O3 was proportional to the population density. Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.

Air quality improvement during triple-lockdown in the coastal city of Kannur, Kerala to combat Covid-19 transmission

The novel SARS-CoV-2 coronavirus that emerged in the city of Wuhan, China, last year has since become the COVID-19 pandemic across all continents. To restrict the spread of the virus pandemic, the Government of India imposed a lockdown from 25 March 2020. In India, Kannur district was identified as the first "hotspot" of virus transmission and a "triple-lockdown" was implemented for a span of twenty days from 20 April 2020. This article highlights the variations of surface O3, NO, NO2, CO, SO2, NH3, VOC's, PM10, PM2.5 and meteorological parameters at the time of pre-lockdown, lockdown and triple-lockdown days at Kannur town in south India using ground-based analyzers. From pre-lockdown days to triple-lockdown days, surface O3 concentration was found to increase by 22% in this VOC limited environment. NO and NO2 concentrations were decreased by 61% and 71% respectively. The concentration of PM10 and PM2.5 were observed to decline significantly by 61% and 53% respectively. Reduction in PM10 during lockdown and triple-lockdown days enhanced the intensity of solar radiation reaching the lower troposphere, and increased air temperature and reduced the relative humidity. Owing to this, surface O3 production over Kannur was found to have increased during triple-lockdown days. The concentration of CO (67%), VOCs (61%), SO2 (62%) and NH3 (16%) were found to decrease significantly from pre-lockdown days to triple-lockdown days. The air quality index revealed that the air quality at the observational site was clean during the lockdown.

Multi-Model Evaluation of Meteorological Drivers, Air Pollutants and Quantification of Emission Sources over the Upper Brahmaputra Basin

The temporal distributions of meteorological drivers and air pollutants over Dibrugarh, a location in the upper Brahmaputra basin, are studied using observations, models and reanalysis data. The study aims to assess the performance of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem), the WRF coupled with Sulfur Transport dEposition Model (WRF-STEM), and Copernicus Atmosphere Monitoring Service (CAMS) model over Dibrugarh for the first time. The meteorological variables and air pollutants viz., black carbon(BC), carbon monoxide(CO), sulphur dioxide(SO2), Ozone(O3), and oxides of Nitrogen(NOx) obtained from WRF-Chem, WRF-STEM and CAMS are evaluated with observations. The source region tagged CO simulated by WRF-STEM delineate the regional contribution of CO. The principal source region of anthropogenic CO over Dibrugarh is North-Eastern India with a 59% contribution followed by that from China (17%), Indo-Gangetic Plains (14%), Bangladesh (6%), other parts of India (3%) and other regions (1%). Further, the BC-CO regression analysis is used to delineate the local emission sources. The BC-CO correlations estimated from models (0.99 for WRF-Chem, 0.96 for WRF-STEM, 0.89 for CAMS), and reanalysis (0.8 for Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) are maximum in pre-monsoon whereas surface observations show highest correlations (0.81) in winter. In pre-monsoon season, 90% of the modeled CO is due to biomass burning over Dibrugarh.

Long-term (2005-2015) trend analysis of PM2.5 precursor gas NO2 and SO2 concentrations in Taiwan

Ground air monitoring stations have been installed in Taiwan since 1993 to ensure whether the criteria air pollutants meet the ambient air quality standards. In the present study, the data from the monitoring stations were used to evaluate long-term (2005-2015) trend of NO₂ and SO₂ in three metropolitan cities (northern Taipei, central Taichung, and southern Kaohsiung), two eastern coastal cities (Hualien and Taitung), and one agricultural city in west-central plain (Douliu); those cities essentially covered the entire region of Taiwan. The results indicate that SO₂ and NO₂ concentrations of all studied six cities meet the annual average standards of 30 and 50 ppb, respectively. After deseasonalizing the original data and using 7-month moving average, the trend analysis reveals a decreasing trend ranging from 0.15 to 0.57 ppb/year (R² from 0.33 to 0.85) for NO₂ and 0.06 to 0.45 ppb/year (R² from 0.32 to 0.92) for SO₂; the corresponding reductions over the 10-year span are 4 to 42% for NO₂ and 22 to 52% for SO₂. The reduction trend, despite the growth in GDP, vehicle numbers and energy consumption, industrial output, etc., is similar to those of developed countries. Clearly, there are seasonal/monthly variation patterns for these two precursor gases with minimum levels in summer (July) and maximum in winter (December). The concentration reductions, however, were lagging behind the respective emission reductions. There are significant correlations among six cites for NO₂ (r = 0.58-0.93) and, to some extent, SO₂ (0.32-0.66). The correlation between SO₂ and NO₂ (r = 0.46-0.74) indicates same or similar emission sources. Furthermore, the correlation between observed pollutant concentrations and their emission is excellent for SO₂ in two cities (0.79-0.96). The SO₂/NO₂ ratios vary with city and time and the value is site specific. For example, in 2005, the SO₂/NO₂ ratio was 0.38 in Kaohsiung and 0.18 in both Taipei and Taichung, the latter reflecting significant contribution from mobile sources. However, they all converged to 0.18-0.28 in 2015 in the six cities evaluated. All in all, the policies/measures made by the central and local government are effective in reducing ambient SO₂ and NO₂ levels.

Loss of crop yields in India due to surface ozone: an estimation based on a network of observations

Surface ozone is mainly produced by photochemical reactions involving various anthropogenic pollutants, whose emissions are increasing rapidly in India due to fast-growing anthropogenic activities. This study estimates the losses of wheat and rice crop yields using surface ozone observations from a group of 17 sites, for the first time, covering different parts of India. We used the mean ozone for 7 h during the day (M7) and accumulated ozone over a threshold of 40 ppbv (AOT40) metrics for the calculation of crop losses for the northern, eastern, western and southern regions of India. Our estimates show the highest annual loss of wheat (about 9 million ton) in the northern India, one of the most polluted regions in India, and that of rice (about 2.6 million ton) in the eastern region. The total all India annual loss of 4.0-14.2 million ton (4.2-15.0%) for wheat and 0.3-6.7 million ton (0.3-6.3%) for rice are estimated. The results show lower crop loss for rice than that of wheat mainly due to lower surface ozone levels during the cropping season after the Indian summer monsoon. These estimates based on a network of observation sites show lower losses than earlier estimates based on limited observations and much lower losses compared to global model estimates. However, these losses are slightly higher compared to a regional model estimate. Further, the results show large differences in the loss rates of both the two crops using the M7 and AOT40 metrics. This study also confirms that AOT40 cannot be fit with a linear relation over the Indian region and suggests for the need of new metrics that are based on factors suitable for this region.

CO variability and its association with household cooking fuels consumption over the Indo-Gangetic Plains

This study examines the spatio-temporal trends obtained from decade long (Jan 2003-Dec 2014) satellite observational data of Atmospheric Infrared Sounder (AIRS) and Measurements of Pollution in the Troposphere (MOPITT) on carbon monoxide (CO) concentration over the Indo-Gangetic Plains (IGP) region. The time sequence plots of columnar CO levels over the western, central and eastern IGP regions reveal marked seasonal behaviour, with lowest CO levels occurring during the monsoon months and the highest CO levels occurring during the pre-monsoon period. A negative correlation between CO levels and rainfall is observed. CO vertical profiles show relatively high values in the upper troposphere at ∼200 hPa level during the monsoon months, thus suggesting the role of convective transport and advection in addition to washout behind the decreased CO levels during this period. MOPITT and AIRS observations show a decreasing trend of 9.6 × 10¹⁵ and 1.5 × 10¹⁶ molecules cm^-2 yr^-1, respectively, in columnar CO levels over the IGP region. The results show the existence of a spatial gradient in CO from the eastern (higher levels) to western IGP region (lower levels). Data from the Census of India on the number of households using various cooking fuels in the IGP region shows the prevalence of biomass-fuel (i.e. firewood, crop residue, cowdung etc.) use over the eastern and central IGP regions and that of liquefied petroleum gas over the western IGP region. CO emission estimates from cooking activity over the three IGP regions are found to be in the order east > central > west, which support the existence of the spatial gradient in CO from eastern to the western IGP region. Our results support the intervention of present Indian government on limiting the use of biomass-fuels in domestic cooking to achieve the benefits in terms of the better air quality, household health and regional/global climate change mitigation.

Variability of atmospheric carbonyl sulfide at a semi-arid urban site in western India

Atmospheric carbonyl sulfide (COS) is a major precursor for sulfate aerosols that play a critical role in climate regulation. Recent studies have highlighted the importance of COS measurements as a reliable means to constrain biospheric carbon assimilation. In a scenario of limited availability of COS data around the globe, we present gas-chromatographic measurements of atmospheric COS mixing ratios over Ahmedabad, a semi-arid, urban region in western India. These measurements, being reported for the first time over an Indian site, enable us to understand the diurnal and seasonal variation in atmospheric COS with respect to its natural, anthropogenic and photochemical sources and sinks. The annual mean COS mixing ratio over Ahmedabad is found to be 0.83±0.43ppbv, which is substantially higher than free tropospheric values for the northern hemisphere. Inverse correlation of COS with soil and skin temperature, suggests that the dry soil of the semi-arid study region is a potential sink for atmospheric COS. Positive correlations of COS with NO2 and CO during post-monsoon and the COS/CO slope of 0.78pptv/ppbv reveals influence of diesel combustion and tire wear. The highest concentrations of COS are observed during pre-monsoon; COS/CO2 slope of 44.75pptv/ppmv combined with information from air mass back-trajectories reveal marshy wetlands spanning over 7500km(2) as an important source of COS in Ahmedabad. COS/CO2 slopes decrease drastically (8.28pptv/ppmv) during post-monsoon due to combined impact of biospheric uptake and anthropogenic emissions.

Variability of SO₂, CO, and light hydrocarbons over a megacity in Eastern India: effects of emissions and transport

The Indo-Gangetic plain (IGP) has received extensive attention of the global scientific community due to higher levels of trace gases and aerosols over this region. Satellite retrievals and model simulations show that, in particular, the eastern part IGP is highly polluted. Despite this attention, in situ measurements of trace gases are very limited over this region. This paper presents measurements of SO₂, CO, CH₄, and C₂-C₅ NMHCs during March 2012-February 2013 over Kolkata, a megacity in the eastern IGP, with a focus on processes impacting their levels. The mean SO₂ and C2H6 concentrations during winter and post-monsoon periods were eight and three times higher compared to pre-monsoon and monsoon. Early morning enhancements in SO₂ and several NMHCs during winter connote boundary layer effects. Daytime elevations in SO₂ during pre-monsoon and monsoon suggest impacts of photo-oxidation. Inter-species correlations and trajectory analysis evince transport of SO₂ from regional combustion sources (e.g., coal burning in power plants, industries) along the east of the Indo-Gangetic plain impacting SO₂ levels at the site. However, C₂H₂ to CO ratio over Kolkata, which are comparable to other urban regions in India, show impacts of local biofuel combustions. Further, high levels of C₃H₈ and C₄H₁₀ evince the dominance of LPG/petrochemicals over the study location. The suite of trace gases measured during this study helps to decipher between impacts of local emissions and influence of transport on their levels.