An improved understanding of NOx emissions in South Asian megacities using TROPOMI NO2 retrievals

Identifying air pollutant emissions has played a key role in improving air quality and hence the health of billions of people around the world. This has been done using research from multiple directions, two of which are the development of emission inventories and mapping air pollution using satellite remote sensing. The TROPOspheric Monitoring Instrument (TROPOMI) has been providing high resolution vertical column densities of nitrogen dioxide since late October 2018. Using the flux divergence method and a Gaussian Mixture Model, we identify peak emission hotspots over 4 cities in South Asia: Dhaka, Kolkata, Delhi and Lahore. We analyze data from November 2018 to March 2021 and focus on the three dry seasons (November to March) for which retrievals are available. The retrievals are shown to have sufficient spatial resolution to identify individual point and area sources. We further analyze the length scale and eccentricities of the hotspots to better characterize the emission sources. The TROPOMI emission estimates are compared with the EDGAR global emission inventory and the REAS regional inventory. This reveals areas of agreement but also significant discrepancies that should enable improvements and refinements of the inventories in the future. For example, urban emissions are underestimated while power generation emissions are overestimated. Some areas of light manufacturing cause significant signatures in TROPOMI retrievals but are mostly missing from the inventories. The spatial resolution of the TROPOMI instrument is now sufficient to provide detailed feedback to developers of emission inventories as well as to inform policy decisions at the urban to regional scale.

Large contribution of biomass burning emissions to ozone throughout the global remote troposphere

Ozone is the third most important anthropogenic greenhouse gas after carbon dioxide and methane but has a larger uncertainty in its radiative forcing, in part because of uncertainty in the source characteristics of ozone precursors, nitrogen oxides, and volatile organic carbon that directly affect ozone formation chemistry. Tropospheric ozone also negatively affects human and ecosystem health. Biomass burning (BB) and urban emissions are significant but uncertain sources of ozone precursors. Here, we report global-scale, in situ airborne measurements of ozone and precursor source tracers from the NASA Atmospheric Tomography mission. Measurements from the remote troposphere showed that tropospheric ozone is regularly enhanced above background in polluted air masses in all regions of the globe. Ozone enhancements in air with high BB and urban emission tracers (2.1 to 23.8 ppbv [parts per billion by volume]) were generally similar to those in BB-influenced air (2.2 to 21.0 ppbv) but larger than those in urban-influenced air (−7.7 to 6.9 ppbv). Ozone attributed to BB was 2 to 10 times higher than that from urban sources in the Southern Hemisphere and the tropical Atlantic and roughly equal to that from urban sources in the Northern Hemisphere and the tropical Pacific. Three independent global chemical transport models systematically underpredict the observed influence of BB on tropospheric ozone. Potential reasons include uncertainties in modeled BB injection heights and emission inventories, export efficiency of BB emissions to the free troposphere, and chemical mechanisms of ozone production in smoke. Accurately accounting for intermittent but large and widespread BB emissions is required to understand the global tropospheric ozone burden.

On the impact of Urbanisation on CO2 Emissions

We use a globally consistent, time-resolved data set of CO2 emission proxies to quantify urban CO2 emissions in 91 cities. We decompose emissiontrends into contributions from changes in urban extent, population density and per capita emissions. We find that urban CO2 emissions areincreasing everywhere but that the dominant contributors differ according to development level. A cluster analysis of factors shows that developingcountries were dominated by cities with rapid area and per capita CO2 emissions increases. Cities in the developed world, by contrast, show slow area and per capita CO2 emissions growth. China is an important intermediate case with rapid urban area growth combined with slower per capita CO2 emissions growth. For many developed countries, urban per capita emissions are often lower than their national average suggesting that urbanisation may reduce overall emissions. However trends in per capita urban emissions are higher than their national equivalent almost everywhere suggesting that urbanisation will become a more serious problem in future. An important exception is China whose per capita urban emissions are growing more slowly than the national value. We also see anegative correlation between trends in population density and per capita CO2 emissions, highlighting a strong role for densification as a tool toreduce CO2 emissions.

Greenhouse Gas Emissions from Global Cities Under SSP/RCP Scenarios, 1990 to 2100

Projections of greenhouse gas (GHG) emissions are critical to better understanding and anticipating future climate change under different socio-economic conditions and mitigation strategies. The climate projections and scenarios assessed by the Intergovernmental Panel on Climate Change, following the Shared Socioeconomic Pathway (SSP)-Representative Concentration Pathway (RCP) framework, have provided a rich understanding of the constraints and opportunities for policy action. However, the current emissions scenarios lack an explicit treatment of urban emissions within the global context. Given the pace and scale of urbanization, with global urban populations expected to increase from about 4.4 billion today to about 7 billion by 2050, there is an urgent need to fill this knowledge gap. Here, we estimate the share of global GHG emissions emanating from urban areas from 1990 to 2100 based on the SSP-RCP framework. The urban GHG emissions are presented in five regional aggregates and are based on a combination of the urban population share, 2015 urban per capita CO2eq emissions, SSP-based national CO2eq emissions, and recent analysis of urban per capita CO2eq trends. We find that urban areas account for the majority of global GHG emissions in 2015 (61.8%). Moreover, the urban share of global GHG emissions progressively increases into the future, exceeding 80% in some scenarios by the end of the century. The combined urban areas in Asia and Developing Pacific, and Developed Countries account for 65.0% to 73.3% of cumulative urban emissions between 2020 and 2100 across the scenarios. Given these dominant roles, we describe the implications to potential urban mitigation in each of the scenario narratives in order to meet the goal of climate neutrality within this century.

The regional impact of urban emissions on air quality in Europe: the role of the urban canopy effects

Urban areas are hot spots of intense emissions, and they influence air quality not only locally but on a regional or even global scale. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local- and regional-scale meteorological conditions. These are influenced by the presence of urbanized land surface via the so-called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw) how the urban emission impact (UEI) is modulated by the UCMF for present-day climate conditions (2015–2016) using two regional climate models, the regional climate models RegCM and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem; its meteorological part), and two chemistry transport models, Comprehensive Air Quality Model with Extensions (CAMx) coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by a rural one, while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban-emission-induced changes in near-surface concentrations of NO2, O3 and PM2.5. We found increases in NO2 and PM2.5 concentrations over cities by 4–6 ppbv and 4–6 µg m−3, respectively, meaning that about 40 %–60 % and 20 %–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions, and the rest is the result of emissions from the surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40 %–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases of around −2 to −4 ppbv (about 10 %–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air pollution is much stronger, and the modulation of UEI is also larger for such situations. Finally, we evaluated the contribution of the urbanization-induced modifications of vertical eddy diffusion to the modulation of UEI and found that it alone is able to explain the modeled decrease in the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional footprint of urban emissions. Ignoring these meteorological changes can lead to the strong overestimation of UEI.

Electrification of Urban Waste Collection: Introducing a Simulation-Based Methodology for Technical Feasibility, Impact and Cost Analysis

Electrification is a potential solution for transport decarbonization and already widely available for individual and public transport. However, the availability of electrified commercial vehicles like waste collection vehicles is still limited, despite their significant contribution to urban emissions. Moreover, there is a lack of clarity whether electric waste collection vehicles can persist in real world conditions and which system design is required. Therefore, we introduce a multi-agent-based simulation methodology to investigate the technical feasibility and evaluate environmental and economic sustainability of an electrified urban waste collection. We present a synthetic model for waste collection demand on a per-link basis, using open available data. The tour planning is solved by an open-source algorithm as a capacitated vehicle routing problem (CVRP). This generates plausible tours which handle the demand. The generated tours are simulated with an open-source transport simulation (MATSim) for both the diesel and the electric waste collection vehicles. To compare the life cycle costs, we analyze the data using total cost of ownership (TCO). Environmental impacts are evaluated based on a Well-to-Wheel approach. We present a comparison of the two propulsion types for the exemplary use case of Berlin. And we are able to generate a suitable planning to handle Berlin’s waste collection demand using battery electric vehicles only. The TCO calculation reveals that the electrification raises the total operator cost by 16–30%, depending on the scenario and the battery size with conservative assumptions. Furthermore, the greenhouse gas emissions (GHG) can be reduced by 60–99%, depending on the carbon footprint of electric power generation.

Quantifying urban, industrial, and background changes in NO₂ during the COVID-19 lockdown period based on TROPOMI satellite observations

The COVID-19 lockdown had a large impact on anthropogenic emissions of air pollutants and particularly on nitrogen dioxide (NO2). While the overall NO2 decline over some large cities is well-established, its quantification remains a challenge because of a variety of sources of NO2. In this study, a new method of isolation of three components: background NO2, NO2 from urban sources, and from industrial point sources is applied to estimate the COVID-19 lockdown impact on each of them. The approach is based on fitting satellite data by a statistical model with empirical plume dispersion functions driven by the observed winds. Population density and surface elevation data as well as coordinates of industrial sources were used in the analysis. The NO2 vertical column density (VCD) values measured by Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel‐5 Precursor over 263 urban areas for the period from March 16 to June 15, 2020, were compared with the average VCD values for the same period in 2018 and 2019. While background NO2 component remained almost unchanged, the urban NO2 component declined by 18–28 % over most regions. India, South America, and a part of Europe (particularly, Italy, France, and Spain) demonstrated a 40–50 % urban emissions decline. In contrast, decline over urban area in China, where the lockdown was over during the analyzed period, was only 3 % except for Wuhan, where more than 60 % decline was observed. Emissions from large industrial sources in the analyzed urban areas varies largely from region to region from +5 % for China to −40 % for India. Changes in urban emissions are correlated with changes in Google mobility data (the correlation coefficient is 0.66) confirming that changes in traffic was one of the key elements in decline of urban NO2 emissions. No correlation was found between changes in background NO2 and Google mobility data.

The regional impact of urban emissions on air quality in Europe: the role of the urban canopy effects

Urban areas are hot-spots of intense emissions and they influence air-quality not only locally but on regional or even global scales. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local and regional scale meteorological conditions. These are influenced by the presence of urbanized land-surface via the so called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw), how the urban emission impact (UEI) is modulated by the UCMF for present day climate conditions (2015–2016) using three regional climate-chemistry models: the regional climate models RegCM and WRF-Chem (its meteorological part), the chemistry transport model CAMx coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by rural one while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban emissions induced changes of near surface concentrations of NO2, O3 and PM2.5. We found increases of NO2 and PM2.5 concentrations over cities by 4–6 ppbv, and 4–6 μgm−3, respectively meaning that about 40–60 % and 20–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions and the rest is the result of emissions from surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases around −2 to −4 ppbv (about 10–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air-pollution is much stronger, as well as the modulation of UEI is larger for such situations. Finally, we evaluated the contribution of the urbanization induced modifications of vertical eddy-diffusion to the modulation of UEI, and found that it alone is able to explain the modelled decrease of the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional fingerprint of urban emissions. Ignoring these meteorological changes can lead to strong overestimation of UEI.