A Top-Down Regional Assessment of Urban Greenhouse Gas Emissions in Europe

<p>In order to meet the dual challenges of providing for a growing global population and mitigating climate change effects, it is necessary to consider how urban areas can grow while achieving carbon neutrality, which is a complex and difficult task. It requires increased understanding of carbon dynamics in the coupled urban social-ecological systems, including process-level understanding and distinction of natural and human-perturbed carbon exchanges and their interactions. A better understanding of these complex systems and processes could, for example, facilitate enhanced use of nature-based solutions (NBS) to help mitigate and offset the greenhouse gas (GHG) emissions of urban regions. This paper addresses part of this challenge, aiming to further understanding of the complex interactions between urban growth and GHG emissions implied by associated land use changes, including the influence of water bodies within the urban region on the carbon source-sink dynamics.</p><p> </p><p>The study involves a comprehensive analysis of the land-use related GHG emissions and removals (through carbon sequestration) in the urban region of Stockholm County in Sweden, which is currently experiencing large urban growth and rapid population growth. Stockholm County includes large urban areas, forested areas (both old and young preserved natural forests and managed forestry), farmlands, some wetlands, and a number of smaller towns and semi-urban areas. Geographically, much of the county is located on the Stockholm Archipelago – a series of islands in the Baltic Sea – and the remainder is dominated by many lakes, including Lake Mälaren, which is Sweden’s third largest lake and the main water supply for the capital city Stockholm. The water coverage prevailing in the county allows for investigation of its effects in combination and relation to the variable and changing urban and other land cover distribution on the regional GHG emissions and sequestrations. These effects may be considerable and are addressed in this study.</p><p> </p><p>Results include an inventory of existing and planned land uses in Stockholm County, and the GHG emissions or sequestration potentials associated with each of these. The land uses include urban and semi-urban areas, different types of natural and cultivated vegetation, agriculture, forestry, water bodies and wetlands. The study provides a map of Stockholm County’s GHG emission and sequestration potential, which is further analysed to advance our understanding of how future development in the county can be shaped to effectively minimize urban GHG emissions and maximize carbon sequestrations. The inclusion of water bodies in this GHG inventory proved to be particularly interesting; while lakes and other water bodies are often considered as ‘blue’ nature-based solutions (NBS) for maintaining and providing a number of ecosystem services in urban regions, our results indicate the lakes in Stockholm County as considerable sources of GHG emissions. The contribution of inland waters to the regional GHG emissions emphasizes the need and importance of improving rather than deteriorating the regional carbon sequestration potential in the urbanization process. This can be achieved by using and enhancing other types of NBS, such as rehabilitation of green areas like forests, in order to achieve carbon neutrality in this urban region.</p>

This chapter focuses on the anthropogenic greenhouse gas (GHG) emission trends from urban energy systems and the drivers of urban energy-related GHG emissions. As much as possible, quantitative information on GHG emissions in cities are compiled and key insights are shared on why and how they vary within and across cities. Place-based case studies from global cities are also used to provide relevant context. Although this section is not intended to replace a comprehensive literature review or the wealth of research and information developed and under development, it does aim to gather the current state of knowledge on urban GHG drivers. The synthesis is organized into five sections reflecting current knowledge on urban energy-related GHG emissions: (1) drivers, (2) trends, (3) potential transitions, (4) accounting, and (5) governance. Such background helps to explore three principal questions: (1) What are the drivers and variances for these GHG emissions? (2) What are the sources and types of GHG emissions as a result of urban energy systems and their transitions? (3) What role do various societal actors and governance systems have in shaping transitions in urban energy and GHG emissions?

At present, urban greenhouse gas (GHG) emissions from different wastewater treatment stages are attracting increasing attention. Based on the Guidelines of the China Greenhouse Gas List Compilation (Trial) and the IPCC National Greenhouse Gas List Guidelines in 2006, this paper evaluated urban GHG emissions from wastewater treatment in China from 2011 to 2020. The contribution rates of GHG emissions to the total GHG emissions were calculated for the different wastewater treatment stages. The variations in annual GHG emissions and differences in GHG emissions among different regions and provinces were also analyzed. The total amount of equivalent CO2 emissions reaches 1478.51 million tons, and the annual average amount of equivalent CO2 emissions from 2011 to 2020 is 147.9 million tons, which shows a trend of decreasing first and then increasing. The distribution of GHG emissions from wastewater treatment is uneven among provinces and regions; Guangdong Province has the highest emission, while the Xizang autonomous Region has the lowest. The correlation and contribution rate analysis revealed that paper production and chemical and side food production could discharge a large amount of wastewater with a high COD content, which may have an important impact on GHG emissions during the wastewater treatment stages. According to the study results, CH4 accounts for the largest proportion (63.08%) of the total GHG emissions. The most important source of CH4 comes from the industrial wastewater treatment stage. The annual average CO2 emissions account for 22.24% of the total GHG emissions, which are mainly from the power and chemical consumption stage. The annual average N2O emissions account for 14.68% of the total GHG emissions and are mainly from the wastewater collection and discharge stage. Therefore, in the future, GHG emission reduction strategies should focus on CH4 emissions in the industrial wastewater treatment stage and develop CH4 recycling and utilization technologies.

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Spatial apportionment of urban greenhouse gas emission inventory and its implications for urban planning: A case study of Xiamen, China

As cities work to reduce their total greenhouse gas (GHG) emissions, the transportation sector is lagging, accounting for a growing percentage of total emissions in many cities. The provision of public transit, and specifically urban rail transit, is widely seen as a useful tool for reducing urban transportation GHG emissions. More research, however, is needed to understand the net impact of new metro rail infrastructure on urban emissions and guide efforts to maximise the GHG savings through rail investments. This paper examines the net GHG emissions of the Jubilee line extension (JLE) in London, UK. The GHG emissions associated with construction, operation, ridership and changes in urban density associated with the provision of the new metro rail infrastructure are assessed. These components are then combined and compared to calculate the net GHG impact across the study period, which extends from opening in 1999 through 2011. The capital GHG emissions from construction of the JLE are calculated as 530 kilotonnes carbon dioxide equivalent (CO2e). The initial mode shift from other rail lines and long-term mode change from automobiles result in yearly GHG savings from riders on the JLE. A quasi-experimental analysis of land-use change near the JLE finds no calculable GHG saving from increased residential density. The GHG payback period is calculated between 13 and 19 years.

Abstract. In order to mitigate climate change, it is crucial to understand urban greenhouse gas (GHG) emissions precisely, as more than two-thirds of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the Munich Urban Carbon Column network (MUCCnet), the world's first urban sensor network, which has been permanently measuring GHGs, based on the principle of differential column measurements (DCMs), since summer 2019. These column measurements and column concentration differences are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city, making them a favorable input for an inversion framework and, therefore, a well-suited candidate for the quantification of GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring column-averaged CO2, CH4 and CO concentrations with a solar-tracking Fourier transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This also includes software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO2 since 2015, as well as concentration gradients between sites upwind and downwind of the city. Thanks to the automation, we were also able to continue taking measurements during the COVID-19 lockdown in spring 2020. By correlating the CO2 column concentration gradients to the traffic amount, we demonstrate that our network is capable of detecting variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this approach for long-term greenhouse gas monitoring in urban areas.

The net greenhouse gas impact of the Sheppard Subway Line

As climate change mitigation becomes pervasive on all spatial scales, mitigation options related to urban spatial planning and behavioral change become increasingly important. Because transport energy consumption seems to scale inversely with population density, increased attention focuses on the role of urban form. This study specifically analyzes the importance of population density for the reduction of urban greenhouse gas emissions in Europe. For this, drivers of both carbon dioxide (CO2) emissions from transport (for 134 cities) and total urban greenhouse gas emissions (CO2eq emissions) of 62 cities across Europe are investigated. Results indicate that population density is not, per se, a strong determinant of greenhouse gas emissions in European cities. Crucially, the spatial scale of the analysis matters and national influences modulate CO2eq emissions in the analyzed urban areas. Results show that greenhouse gas emissions of European urbanites increase significantly with decreasing household sizes and increasing personal wealth. Although the results are bound by data quality, it is assumed that the relative similarity of European cities is also leading to a lesser degree of importance of population density with respect to climate change mitigation. The results further encourage more thorough analyses of the role of household size and personal wealth for effective mitigation of climate change, additional spatially explicit econometric studies, and detailed, city-specific causal models of urban areas.

Understanding urban spatial heterogeneity of greenhouse gas (GHG) emissions from sectoral household consumption is crucial to facilitate moves towards low-carbon cities. In this study, we use Xiamen city of China as a case study to reveal the emission characteristics of household GHG as well as spatial heterogeneity. We conducted a face-to-face questionnaire survey and calculated GHG emissions of districts from household energy consumption, food consumption, transportation, housing, household waste and wastewater treatment. The GHG emissions and the amount of urban residential household consumption shows obvious spatial heterogeneity across districts. Total GHG emissions of Xiamen city were 8.39 Mt. CO2e, and average household and per capita of GHG emissions were 8.11 and 2.72 tCO2e, respectively. While total GHG emissions vary from 0.41 to 2.45 Mt. CO2e across six districts and range from 0.16 to 3.39 Mt. CO2e among six sectors. Household GHG emissions differ from 7.08 to 9.40 tCO2e, while the per capita emissions range between 2.41 to 3.14 tCO2e among districts. Results also showed that more urbanized areas with higher population density have larger total urban residential GHG emissions, whereas household emissions were comparatively lower in these areas. In contrast, our study did not show an (inverted-) U relationship or linear relationship between emissions and population, nor between emissions and income level. Household energy use is the largest sector emitting GHGs. These findings will be useful to underpin policy making towards low-carbon cities.

This study, using Chongqing City of China as an example, predicts the future motor vehicle population using the Gompertz Model and the motorcycle population using the piecewise regression model, and predicts and analyzes fuel consumption and greenhouse gas (GHG) emissions of motor vehicles from 2016 to 2035 based on the bottom-up method under different scenarios of improving the fuel economy of conventional vehicles, promoting alternative fuel vehicles, and the mixed policy of the above two policy options. The results indicate that the total population of motor vehicles in Chongqing will increase from 4.61 million in 2015 to 10.15 million in 2035. In the business-as-usual scenario, the road-transportation energy demand in Chongqing will keep increasing from 2015 and will peak in 2030, before it begins to decline by 2035. The trends for the tank to wheel (TTW) and well to wheel (WTW) GHG emissions are similar to that of energy demand. The WTW GHG emissions will increase from 24.9 Mt CO2e in 2016 to 50.5 Mt CO2e in 2030 and will then gradually decline to 48.9 Mt CO2e in 2035. Under the policy scenarios of improving fuel economy of conventional fuel passenger cars, promoting alternative fuel vehicles, and their mixed policy, direct energy consumption and TTW and WTW GHG emissions from 2016 to 2035 will be reduced to different levels. It is also found that the two types of policies have a hedging effect on the direct energy-consumption saving, TTW, and WTW GHG emission reductions. Sensitivity analysis of key parameters and policy settings is conducted to investigate the impact of their changes on the vehicle population projection, direct energy demand, and WTW GHG emissions. Some policy implications are suggested to provide reference for the formulation and adjustment of Chongqing’s, or even China’s, low-carbon road transportation policies in the future based on the analysis results.

Cities are at the heart of global anthropogenic greenhouse gas (GHG) emissions, with rivers embedded in urban landscapes as a potentially large yet uncharacterized GHG source. Urban rivers emit GHGs due to excess carbon and nitrogen inputs from urban environments and their watersheds. Here relying on a compiled urban river GHG dataset and robust modelling, we estimated that globally urban rivers emitted annually 1.1, 42.3 and 0.021 Tg CH4, CO2 and N2O, totalling 78.1 ± 3.5 Tg CO2-equivalent (CO2-eq) emissions. Predicted GHG emissions were nearly twofold those from non-urban rivers (~815 versus 414 mmol CO2-eq m−2 d−1) and similar to scope-1 urban emissions in intensity (1,058 mmol CO2-eq m−2 d−1), with particularly higher CH4 and N2O emissions linked to widespread eutrophication and altered carbon and nutrient cycling in urban rivers. Globally, the emissions varied with national income levels with the highest emissions happening in lower–middle-income countries where river pollution control is deficient. These findings highlight the importance of pollution controls in mitigating urban river GHG emissions and ensuring urban sustainability.

There is increased interest in understanding urban greenhouse gas (GHG) emissions. To accurately estimate city emissions, the influence of extraurban fluxes must first be removed from urban greenhouse gas (GHG) observations. This is especially true for regions, such as the U.S. Northeastern Corridor‐Baltimore/Washington, DC (NEC‐B/W), downwind of large fluxes. To help site background towers for the NEC‐B/W, we use a coupled Bayesian Information Criteria and geostatistical regression approach to help site four background locations that best explain CO2 variability due to extraurban fluxes modeled at 12 urban towers. The synthetic experiment uses an atmospheric transport and dispersion model coupled with two different flux inventories to create modeled observations and evaluate 15 candidate towers located along the urban domain for February and July 2013. The analysis shows that the average ratios of extraurban inflow to total modeled enhancements at urban towers are 21% to 36% in February and 31% to 43% in July. In July, the incoming air dominates the total variability of synthetic enhancements at the urban towers (R2 = 0.58). Modeled observations from the selected background towers generally capture the variability in the synthetic CO2 enhancements at urban towers (R2 = 0.75, root‐mean‐square error (RMSE) = 3.64 ppm; R2 = 0.43, RMSE = 4.96 ppm for February and July). However, errors associated with representing background air can be up to 10 ppm for any given observation even with an optimal background tower configuration. More sophisticated methods may be necessary to represent background air to accurately estimate urban GHG emissions.

Greenhouse gas emissions from global cities under SSP/RCP scenarios, 1990 to 2100

The extensible evaluation framework of urban green house gas emission reduction responsibility: A case of Shandong province in China