Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships

Extension of Japan's Prefectural Emission Accounting and Enrichment of Socioeconomic Data from 1990 to 2020

With the continuous increase in carbon dioxide emissions due to human activities and the resulting severe climate issues, there is global concern about energy conservation and emission reduction. However, detailed data on energy consumption and emissions at a fine-grained scale, particularly regarding spatial dimensions and sector-specific emissions, remains insufficient and in need of refinement and timely updates. In Japan, following the Fukushima nuclear disaster, there has been a significant shift from nuclear power generation to reliance on fossil fuels across various sectors, highlighting disparities in emissions data across different regions and industries. Our work extends the emissions time series for Japan's 47 prefectures, incorporating their socioeconomic characteristics over a broader time frame and with a more detailed sectoral classification. The emissions inventory, covering the period from 1990 to 2020, is based on the consumption of the three main fossil fuels across 32 sectors, with emissions carefully allocated for regional power generation. This dataset, presented in a unified format, is expanded to include longer time scales and more detailed socioeconomic data. It is anticipated to offer crucial insights for establishing regional emission reduction targets and identifying sectoral priorities for decarbonization.

Spatio-temporal evolution characteristics of carbon emissions from road transportation in the mainland of China from 2006 to 2021

The leaping forward of the economy has promoted the rapid growth of road traffic demand, resulting in the carbon emissions of road traffic increasing significantly. It is well known that a one-size-fits-all emission reduction policy is not feasible. Therefore, conducting an investigation on the carbon emissions of all provincial-level regions within a country can assist the government in formulating carbon emission policies at a macro level tailored to different regions. In this study, the whole provincial-level administrative regions in the mainland of China were selected to quantify the carbon emissions of road traffic, and the carbon emissions from 2006 to 2021 were obtained by employing the top-down model. What's more, spatiotemporal characteristics of road transportation carbon emissions in those regions were explored based on Moran's I spatial autocorrelation method. In addition, the LMDI model was constructed based on five driving factors, namely energy intensity, energy consumption intensity, industrial scale, economic development, and population size, and the decomposition analysis of driving factors is carried out. The results show that carbon emissions from road traffic in all provincial regions showed an overall rising trend in the research period, with an average annual growth rate of 11.83 %. The distribution of road transportation carbon emissions exhibited an east-high, west-low distribution, with significantly higher emissions in the eastern and coastal regions compared to inland areas, additionally, China's seven geographical regions showed an initial rapid increase in carbon emissions followed by a stable growth trend. Secondly, five types of spatial clustering were identified of carbon emissions within provincial regions. Thirdly, the impacts of energy intensity and industrial scale were detrimental to road transportation carbon emissions, whereas economic development, energy consumption intensity, and population size had contrasting effects. Implications according to the above conclusions were put forward, aiming to provide guidance for the sustainable development of road transportation and expediting the achievement of the "carbon peaking and carbon neutrality" objective.

Urban flask measurements of CO2ff and CO to identify emission sources at different site types in Auckland, New Zealand

As part of the CarbonWatch-NZ research programme, air samples were collected at 28 sites around Auckland, New Zealand, to determine the atmospheric ratio (RCO) of excess (local enhancement over background) carbon monoxide to fossil CO2 (CO2ff). Sites were categorized into seven types (background, forest, industrial, suburban, urban, downwind and motorway) to observe RCO around Auckland. Motorway flasks observed RCO of 14 ± 1 ppb ppm-1 and were used to evaluate traffic RCO. The similarity between suburban (14 ± 1 ppb ppm-1) and traffic RCO suggests that traffic dominates suburban CO2ff emissions during daytime hours, the period of flask collection. The lower urban RCO (11 ± 1 ppb ppm-1) suggests that urban CO2ff emissions are comprised of more than just traffic, with contributions from residential, commercial and industrial sources, all with a lower RCO than traffic. Finally, the downwind sites were believed to best represent RCO for Auckland City overall (11 ± 1 ppb ppm-1). We demonstrate that the initial discrepancy between the downwind RCO and Auckland's estimated daytime inventory RCO (15 ppb ppm-1) can be attributed to an overestimation in inventory traffic CO emissions. After revision based on our observed motorway RCO, the revised inventory RCO (12 ppb ppm-1) is consistent with our observations. This article is part of the Theo Murphy meeting issue 'Radiocarbon in the Anthropocene'.

Characterizing emission factors and oxidative potential of motorcycle emissions in a real-world tunnel environment

Transportation emissions significantly affect human health, air quality, and climate in urban areas. This study conducted experiments in an urban tunnel in Taipei, Taiwan, to characterize vehicle emissions under real driving conditions, providing emission factors of PM2.5, eBC, CO, and CO2. By applying multiple linear regression, it derives individual emission factors for heavy-duty vehicles (HDVs), light-duty vehicles (LDVs), and motorcycles (MCs). Additionally, the oxidative potential using dithiothreitol assay (OPDTT) was established to understand PM2.5 toxicity. Results showed HDVs dominated PM2.5 and eBC concentrations, while LDVs and MCs influenced CO and CO2 levels. The CO emission factor for transportation inside the tunnel was found to be higher than those in previous studies, likely owing to the increased fraction of MCs, which generally emit higher CO levels. Among the three vehicle types, HDVs exhibited the highest PM2.5 and eBC emission factors, while CO and CO2 levels were relatively higher for LDVs and MCs. The OPDTTm demonstrated that fresh traffic emissions were less toxic than aged aerosols, but higher OPDTTv indicated the impact on human health cannot be ignored. This study updates emission factors for various vehicle types, aiding in accurate assessment of transportation emissions' effects on air quality and human health, and providing a guideline for formulating mitigation strategies.

Urban form and its impacts on air pollution and access to green space: A global analysis of 462 cities

A better understanding of urban form metrics and their environmental outcomes can help urban policymakers determine which policies will lead to more sustainable growth. In this study, we have examined five urban form metrics-weighted density, density gradient slope, density gradient intercept, compactness, and street connectivity-for 462 metropolitan areas worldwide. We compared urban form metrics and examined their correlations with each other across geographic regions and socioeconomic characteristics such as income. Using the K-Means clustering algorithm, we then developed a typology of urban forms worldwide. Furthermore, we assessed the associations between urban form metrics and two important environmental outcomes: green space access and air pollution. Our results demonstrate that while higher density is often emphasized as the way to reduce driving and thus PM2.5 emissions, it comes with a downside-less green space access and more exposure to PM2.5. Moreover, street connectivity has a stronger association with reduced PM2.5 emissions from the transportation sector. We further show that it is not appropriate to generalize urban form characteristics and impacts from one income group or geographical region to another, since the correlations between urban form metrics are context specific. Our conclusions indicate that density is not the only proxy for different aspects of urban form and multiple indicators such as street connectivity are needed. Our findings provide the foundation for future work to understand urban processes and identify effective policy responses.

Carbon flow through continental-scale ground logistics transportation

The flourishing logistics in both developed and emerging economies leads to huge greenhouse gas (GHG) emissions; however, the emission fluxes are poorly constrained. Here, we constructed a spatial network of logistic GHG emissions based on multisource big data at continental scale. GHG emissions related to logistics transportation reached 112.14 Mt CO₂-equivalents (CO₂e), with seven major urban agglomerations contributing 63% of the total emissions. Regions with short transport distances and well-developed road infrastructure had relatively high emission efficiency. Underlying value flow of the commodities is accompanied by logistics carbon flow along the supply chain. The main driving factors affecting GHG emissions are driving speed and gross domestic product. It may mitigate GHG emissions by 27.50-1162.75 Mt CO₂e in 15 years if a variety of energy combinations or the appropriate driving speed (65-70 km/h) is adopted. The estimations are of great significance to make integrated management policies for the global logistics sector.

Detection of Anthropogenic CO2 Emission Signatures with TanSat CO2 and with Copernicus Sentinel-5 Precursor (S5P) NO2 Measurements: First Results

China's first carbon dioxide (CO₂) measurement satellite mission, TanSat, was launched in December 2016. This paper introduces the first attempt to detect anthropogenic CO₂ emission signatures using CO₂ observations from TanSat and NO₂ measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P) satellite. We focus our analysis on two selected cases in Tangshan, China and Tokyo, Japan. We found that the TanSat XCO₂ measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO₂ observations. The linear fit between TanSat XCO₂ and TROPOMI NO₂ indicates the CO₂-to-NO₂ ratio of 0.8 × 10^-16 ppm (molec cm^-2)^-1 in Tangshan and 2.3 × 10^-16 ppm (molec cm^-2)^-1 in Tokyo. Our results align with the CO₂-to-NO _x emission ratios obtained from the EDGAR v6 emission inventory.

Diverse biosphere influence on carbon and heat in mixed urban Mediterranean landscape revealed by high resolution thermal and optical remote sensing

A fundamental challenge in verifying urban CO₂ emissions reductions is estimating the biological influence that can confound emission source attribution across heterogeneous and diverse landscapes. Recent work using atmospheric radiocarbon revealed a substantial seasonal influence of the managed urban biosphere on regional carbon budgets in the Los Angeles megacity, but lacked spatially explicit attribution of the diverse biological influences needed for flux quantification and decision making. New high-resolution maps of land cover (0.6 m) and irrigation (30 m) derived from optical and thermal sensors can simultaneously resolve landscape influences related to vegetation type (tree, grass, shrub), land use, and fragmentation needed to accurately quantify biological influences on CO₂ exchange in complex urban environments. We integrate these maps with the Urban Vegetation Photosynthesis and Respiration Model (UrbanVPRM) to quantify spatial and seasonal variability in gross primary production (GPP) across urban and non-urban regions of Southern California Air Basin (SoCAB). Results show that land use and landscape fragmentation have a significant influence on urban GPP and canopy temperature within the water-limited Mediterranean SoCAB climate. Irrigated vegetation accounts for 31% of urban GPP, driven by turfgrass, and is more productive (1.7 vs 0.9 μmol m^-2 s^-1) and cooler (2.2 ± 0.5 K) than non-irrigated vegetation during hot dry summer months. Fragmented landscapes, representing mostly vegetated urban greenspaces, account for 50% of urban GPP. Cooling from irrigation alleviates strong warming along greenspace edges within 100 m of impervious surfaces, and increases GPP by a factor of two, compared to non-irrigated edges. Finally, we note that non-irrigated shrubs are typically more productive than non-irrigated trees and grass, and equally productive as irrigated vegetation. These results imply a potential water savings benefit of urban shrubs, but more work is needed to understand carbon vs water usage tradeoffs of managed vs unmanaged vegetation.

Contribution of on-road transportation to PM2.5

Fine particulate matter (PM_2.5) mainly originates from combustion emissions. On-road transportation is considered one of the primary sources of PM_2.5 emission. The relationship between on-road transportation and PM_2.5 concentration varies temporally and spatially, and the estimation for this variation is important for policymaking. Here, we reveal the quantitative association of PM_2.5 concentration with on-road transportation by the spatial panel Durbin model and the geographical and temporal weighted regression. We find that 6.17 billion kilometres (km) per km² on-road transportation increase is associated with a 1-μg/m³ county-level PM_2.5 concentration increase in the contiguous United States. On-road transportation marginally contributes to PM_2.5, only 1.09% on average. Approximately 3605 premature deaths are attributed to PM_2.5 from on-road transportation in 2010, and about a total of 50,223 premature deaths ascribe to PM_2.5 taking 6.49% from 2003 to 2016. Our findings shed light on the necessity of the county-level policies considering the temporal and spatial variability of the relationship to further mitigate PM_2.5 from on-road transportation.

Climate Change Warning Labels on Gas Pumps: The Role of Public Opinion Formation in Climate Change Mitigation Policies

This article analyzes City of Cambridge, Massachusetts legislation that requires all gasoline and diesel pumps to display a consumer warning label outlining the climate change and public health impacts from fuel combustion. This review of empirical and theoretical scholarship on efficacy of carbon label programs and health warning labels suggests government-sponsored "warming labels" may increase self-efficacy beliefs. The analysis reveals warming labels may activate extant climate concern norms and shift public opinion toward long term support of sustainable transportation emissions policies and practices.

Environmental co-benefits of urban greening for mitigating heat and carbon emissions

Urban greening has been as a popular and effective strategy for ameliorating urban thermal environment and air quality. Nevertheless, it remains an outstanding challenge for numerical urban models to disentangle and quantify the complex interplay between heat and carbon dynamics. In this study, we used a newly developed coupled urban canopy-carbon dynamics model to investigate the environmental co-benefits for mitigating urban heat stress as well as the reduction of carbon dioxide (CO₂) emission. In particular, we evaluated the impact of specific components of urban greening, viz. fraction of the urban lawn, bare soil, tree coverage, and irrigation on heat and carbon fluxes in the built environment. The results of numerical simulations show that the expansion of urban green space, in general, leads to environmental cooling and reduced CO₂ emission, albeit the efficacy varies for different vegetation types. In addition, adequate irrigation is essential to effect plant physiological functions for cooling and CO₂ uptake, whereas further improvement becomes marginal with excessive irrigation. The findings of this study, along with its implications on environmental management, will help to promote sustainable urban development strategies for achieving desirable environmental co-benefits for urban residents and practitioners.

Volatile chemical product emissions enhance ozone and modulate urban chemistry

Decades of air quality improvements have substantially reduced the motor vehicle emissions of volatile organic compounds (VOCs). Today, volatile chemical products (VCPs) are responsible for half of the petrochemical VOCs emitted in major urban areas. We show that VCP emissions are ubiquitous in US and European cities and scale with population density. We report significant VCP emissions for New York City (NYC), including a monoterpene flux of 14.7 to 24.4 kg ⋅ d^-1 ⋅ km^-2 from fragranced VCPs and other anthropogenic sources, which is comparable to that of a summertime forest. Photochemical modeling of an extreme heat event, with ozone well in excess of US standards, illustrates the significant impact of VCPs on air quality. In the most populated regions of NYC, ozone was sensitive to anthropogenic VOCs (AVOCs), even in the presence of biogenic sources. Within this VOC-sensitive regime, AVOCs contributed upwards of ∼20 ppb to maximum 8-h average ozone. VCPs accounted for more than 50% of this total AVOC contribution. Emissions from fragranced VCPs, including personal care and cleaning products, account for at least 50% of the ozone attributed to VCPs. We show that model simulations of ozone depend foremost on the magnitude of VCP emissions and that the addition of oxygenated VCP chemistry impacts simulations of key atmospheric oxidation products. NYC is a case study for developed megacities, and the impacts of VCPs on local ozone are likely similar for other major urban regions across North America or Europe.

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical-meteorological interactions that drive high pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in Western U.S. basins. Approximately 120 people participated, representing 50 institutions and 5 countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary-layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological-chemical linkages outlined here, nor to validate complex processes within coupled atmosphere-chemistry models.

The Impact of COVID-19 on CO2 Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas

Responses to COVID-19 have resulted in unintended reductions of city-scale carbon dioxide (CO2) emissions. Here, we detect and estimate decreases in CO2 emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. We present three lines of evidence using methods that have increasing model dependency, including an inverse model to estimate relative emissions changes in 2020 compared to 2018 and 2019. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines. Methods and measurements used herein highlight the advantages of atmospheric CO2 observations for providing timely insights into rapidly changing emissions patterns that can empower cities to course-correct CO2 reduction activities efficiently.

Identifying Volatile Chemical Product Tracer Compounds in U.S. Cities

With traffic emissions of volatile organic compounds (VOCs) decreasing rapidly over the last decades, the contributions of the emissions from other source categories, such as volatile chemical products (VCPs), have become more apparent in urban air. In this work, in situ measurements of various VOCs are reported for New York City, Pittsburgh, Chicago, and Denver. The magnitude of different emission sources relative to traffic is determined by measuring the urban enhancement of individual compounds relative to the enhancement of benzene, a known tracer of fossil fuel in the United States. The enhancement ratios of several VCP compounds to benzene correlate well with population density (R² ∼ 0.6-0.8). These observations are consistent with the expectation that some human activity should correlate better with the population density than transportation emissions, due to the lower per capita rate of driving in denser cities. Using these data, together with a bottom-up fuel-based inventory of vehicle emissions and volatile chemical products (FIVE-VCP) inventory, we identify tracer compounds for different VCP categories: decamethylcyclopentasiloxane (D5-siloxane) for personal care products, monoterpenes for fragrances, p-dichlorobenzene for insecticides, D4-siloxane for adhesives, para-chlorobenzotrifluoride (PCBTF) for solvent-based coatings, and Texanol for water-based coatings. Furthermore, several other compounds are identified (e.g., ethanol) that correlate with population density and originate from multiple VCP sources. Ethanol and fragrances are among the most abundant and reactive VOCs associated with VCP emissions.

Investigating the Uncertainties Propagation Analysis of CO2 Emissions Gridded Maps at the Urban Scale: A Case Study of Jinjiang City, China

Gridded CO2 emission maps at the urban scale can aid the design of low-carbon development strategies. However, the large uncertainties associated with such maps increase policy-related risks. Therefore, an investigation of the uncertainties in gridded maps at the urban scale is essential. This study proposed an analytic workflow to assess uncertainty propagation during the gridding process. Gridded CO2 emission maps were produced using two resolutions of geospatial datasets (e.g., remote sensing satellite-derived products) for Jinjiang City, China, and a workflow was applied to analyze uncertainties. The workflow involved four submodules that can be used to evaluate the uncertainties of CO2 emissions in gridded maps, caused by the gridded model and input. Fine-resolution (30 m) maps have a larger spatial variation in CO2 emissions, which gives the fine-resolution maps a higher degree of uncertainty propagation. Furthermore, the uncertainties of gridded CO2 emission maps, caused by inserting a random error into spatial proxies, were found to decrease after the gridding process. This can be explained by the “compensation of error” phenomenon, which may be attributed to the cancellation of the overestimated and underestimated values among the different sectors at the same grid. This indicates a nonlinear change between the sum of the uncertainties for different sectors and the actual uncertainties in the gridded maps. In conclusion, the present workflow determined uncertainties were caused by the gridded model and input. These results may aid decision-makers in establishing emission reduction targets, and in developing both low-carbon cities and community policies.

Toward Accurate, Policy-Relevant Fossil Fuel CO2 Emission Landscapes

The bottom-up (BU) approach has been used to develop spatiotemporally resolved, sectorally disaggregated fossil fuel CO₂ (FFCO₂) emission data products. These efforts are critical constraints to atmospheric assessment of anthropogenic fluxes in addition to offering the climate change policymaking community usable information to guide mitigation. In the United States, there are two high-resolution FFCO₂ emission data products, Vulcan and the Anthropogenic Carbon Emissions System (ACES). As a step toward developing improved, accurate, and detailed FFCO₂ emission landscapes, we perform a comparison of the two data products. We find that while agreeing on total FFCO₂ emissions at the aggregate scale (relative difference = 1.7%), larger differences occur at smaller spatial scales and in individual sectors. Differences in the smaller-emitting sectors are likely errors in ACES input data or emission factors. ACES advances the approach for estimating emissions in the gas and oil sector, while Vulcan shows better geocoordinate correction in the electricity production sector. Differences in the subcounty residential and commercial building sectors are driven by different spatial proxies and suggest a task for future investigation. The gridcell absolute median relative difference, a measure of the average gridcell-scale relative difference, indicates a 53.5% difference. The recommendation for improved BU granular FFCO₂ emission estimation includes review, assessment, and archive of point source geolocations, CO emission input data, CO and CO₂ emission factors, and uncertainty approaches including those due to spatial errors. Finally, intensives where local utility data are publicly available could test the spatial proxies used in estimating residential and commercial building emissions. These steps toward best practices will lead to more accurate, granular emissions, enabling optimal emission mitigation policy choices.

Japan prefectural emission accounts and socioeconomic data 2007 to 2015

In the wake of the Fukushima nuclear disaster, Japan largely moved away from nuclear power generation and turned back towards an energy sector dominated by fossil fuels. As a result, the pace towards reaching emission reduction targets has largely slowed down. This situation indicates that higher emissions will continue to be generated if there is no appropriate and efficient measurement implemented to bridge the energy demand gap. To contribute adequate mitigation policies, a detailed inventory of both CO₂ emissions and socioeconomic factors, both at the national and regional level, should be issued. Thereby, this work contributes to a time-series emission with a record of 47 prefectures in Japan as well as their associated socioeconomic features. The compiled emission inventory is based on three major fossil fuels and 26 sectors with careful emission allocations for regional electricity generation. This dataset is uniformly formatted and can be expected to provide vital information to set regional reduction allowances and sectoral reduction priorities.

Comparing a global high-resolution downscaled fossil fuel CO2 emission dataset to local inventory-based estimates over 14 global cities

BACKGROUND

Compilation of emission inventories (EIs) for cities is a whole new challenge to assess the subnational climate mitigation effort under the Paris Climate Agreement. Some cities have started compiling EIs, often following a global community protocol. However, EIs are often difficult to systematically examine because of the ways they were compiled (data collection and emission calculation) and reported (sector definition and direct vs consumption). In addition, such EI estimates are not readily applicable to objective evaluation using modeling and observations due to the lack of spatial emission extents. City emission estimates used in the science community are often based on downscaled gridded EIs, while the accuracy of the downscaled emissions at city level is not fully assessed.

RESULTS

This study attempts to assess the utility of the downscaled emissions at city level. We collected EIs from 14 major global cities and compare them to the estimates from a global high-resolution fossil fuel CO2 emission data product (ODIAC) commonly used in the science research community. We made necessary adjustments to the estimates to make our comparison as reasonable as possible. We found that the two methods produce very close area-wide emission estimates for Shanghai and Delhi (< 10% difference), and reach good consistency in half of the cities examined (< 30% difference). The ODIAC dataset exhibits a much higher emission compared to inventory estimates in Cape Town (+ 148%), Sao Paulo (+ 43%) and Beijing (+ 40%), possibly related to poor correlation between nightlight intensity with human activity, such as the high-emission and low-lighting industrial parks in developing countries. On the other hand, ODIAC shows lower estimates in Manhattan (- 62%), New York City (- 45%), Washington D.C. (- 42%) and Toronto (- 33%), all located in North America, which may be attributable to an underestimation of residential emissions from heating in ODIAC's nightlight-based approach, and an overestimation of emission from ground transportation in registered vehicles statistics of inventory estimates.

CONCLUSIONS

The relatively good agreement suggests that the ODIAC data product could potentially be used as a first source for prior estimate of city-level CO2 emission, which is valuable for atmosphere CO2 inversion modeling and comparing with satellite CO2 observations. Our compilation of in-boundary emission estimates for 14 cities contributes towards establishing an accurate inventory in-boundary global city carbon emission dataset, necessary for accountable local climate mitigation policies in the future.

A spatial database of CO2 emissions, urban form fragmentation and city-scale effect related impact factors for the low carbon urban system in Jinjiang city, China

This paper presented the spatial database collected in 2013 for mitigating the urban carbon emissions of Jinjiang city, China. The database included the high-resolution CO₂ emissions gridded maps, urban form fragmentation evaluation maps, and city-scale effect related impact factors distribution maps at 30 m and 500 m. We collected the multi-sources data including statistical, vector, and raster data from open-access websites and local governments. We used a general hybrid approach based on global downscaled and bottom-up elements to produce the CO₂ emissions gridded maps. The urban fragmentation was measured by the landscape fragmentation metrics under the feature scale and the accurate identification of the urban functional districts. The percentage of the urban area and the points of interest (POI) density representing the city-scale effect related impact factors were calculated in each grid by the land use and POI data. Our database could be used for the validation of urban CO₂ emissions estimation at the city scale. The landscape metrics and city-scale effect related impact factors maps can also be used for evaluating the socio-economic status in order to solve the other urban spatial planning problems.

Wintertime CO2, CH4, and CO Emissions Estimation for the Washington, DC-Baltimore Metropolitan Area Using an Inverse Modeling Technique

Since greenhouse gas mitigation efforts are mostly being implemented in cities, the ability to quantify emission trends for urban environments is of paramount importance. However, previous aircraft work has indicated large daily variability in the results. Here we use measurements of CO2, CH4, and CO from aircraft over 5 days within an inverse model to estimate emissions from the DC-Baltimore region. Results show good agreement with previous estimates in the area for all three gases. However, aliasing caused by irregular spatiotemporal sampling of emissions is shown to significantly impact both the emissions estimates and their variability. Extensive sensitivity tests allow us to quantify the contributions of different sources of variability and indicate that daily variability in posterior emissions estimates is larger than the uncertainty attributed to the method itself (i.e., 17% for CO2, 24% for CH4, and 13% for CO). Analysis of hourly reported emissions from power plants and traffic counts shows that 97% of the daily variability in posterior emissions estimates is explained by accounting for the sampling in time and space of sources that have large hourly variability and, thus, caution must be taken in properly interpreting variability that is caused by irregular spatiotemporal sampling conditions.

Urban land cover type determines the sensitivity of carbon dioxide fluxes to precipitation in Phoenix, Arizona

Urbanization modifies land surface characteristics with consequent impacts on local energy, water, and carbon dioxide (CO2) fluxes. Despite the disproportionate impact of cities on CO2 emissions, few studies have directly quantified CO2 conditions for different urban land cover patches, in particular for arid and semiarid regions. Here, we present a comparison of eddy covariance measurements of CO2 fluxes (FC) and CO2 concentrations ([CO2]) in four distinct urban patches in Phoenix, Arizona: a xeric landscaping, a parking lot, a mesic landscaping, and a suburban neighborhood. Analyses of diurnal, daily, and seasonal variations of FC and [CO2] were related to vegetation activity, vehicular traffic counts, and precipitation events to quantify differences among sites in relation to their urban land cover characteristics. We found that the mesic landscaping with irrigated turf grass was primarily controlled by plant photosynthetic activity, while the parking lot in close proximity to roads mainly exhibited the signature of vehicular emissions. The other two sites that had mixtures of irrigated vegetation and urban surfaces displayed an intermediate behavior in terms of CO2 fluxes. Precipitation events only impacted FC in urban patches without outdoor water use, indicating that urban irrigation decouples CO2 fluxes from the effects of infrequent storms in an arid climate. These findings suggest that the proportion of irrigated vegetation and urban surfaces fractions within urban patches could be used to scale up CO2 fluxes to a broader city footprint.

Exploiting OMI NO2 satellite observations to infer fossil-fuel CO2 emissions from U.S. megacities

Fossil-fuel CO₂ emissions and their trends in eight U.S. megacities during 2006-2017 are inferred by combining satellite-derived NO_X emissions with bottom-up city-specific NO_X-to-CO₂ emission ratios. A statistical model is fit to a collection NO₂ plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NO_X emissions. Decreases in OMI-derived NO_X emissions are observed across the eight cities from 2006 to 2017 (-17% in Miami to -58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (-25% in Miami to -49% in Los Angeles), but there are some interannual discrepancies. City-specific NO_X-to-CO₂ emission ratios, used to calculate inferred CO₂, are estimated through annual bottom-up inventories of NO_X and CO₂ emissions disaggregated to 1 × 1 km² resolution. Over the study period, NO_X-to-CO₂ emission ratios have decreased by ~40% nationwide (-24% to -51% for our studied cities), which is attributed to a faster reduction in NO_X when compared to CO₂ due to policy regulations and fuel type shifts. Combining top-down NO_X emissions and bottom-up NO_X-to-CO₂ emission ratios, annual fossil-fuel CO₂ emissions are derived. Inferred OMI-based top-down CO₂ emissions trends vary between +7% in Dallas to -31% in Phoenix. For 2017, we report annual fossil-fuel CO₂ emissions to be: Los Angeles 113 ± 49 Tg/yr; New York City 144 ± 62 Tg/yr; and Chicago 55 ± 24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013-2016 average CO₂ emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO₂ emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments - with better spatial and temporal resolution - will better constrain the NO_X-to-CO₂ ratio and reduce the uncertainty in our method.

Hierarchical organization of urban mobility and its connection with city livability

The recent trend of rapid urbanization makes it imperative to understand urban characteristics such as infrastructure, population distribution, jobs, and services that play a key role in urban livability and sustainability. A healthy debate exists on what constitutes optimal structure regarding livability in cities, interpolating, for instance, between mono- and poly-centric organization. Here anonymous and aggregated flows generated from three hundred million users, opted-in to Location History, are used to extract global Intra-urban trips. We develop a metric that allows us to classify cities and to establish a connection between mobility organization and key urban indicators. We demonstrate that cities with strong hierarchical mobility structure display an extensive use of public transport, higher levels of walkability, lower pollutant emissions per capita and better health indicators. Our framework outperforms previous metrics, is highly scalable and can be deployed with little cost, even in areas without resources for traditional data collection.

Coupling population dynamics with earth system models: the POPEM model

Precise modeling of CO₂ emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO₂ emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

Anthropogenic and biogenic CO2 fluxes in the Boston urban region

With the pending withdrawal of the United States from the Paris Climate Accord, cities are now leading US actions toward reducing greenhouse gas emissions. Implementing effective mitigation strategies requires the ability to measure and track emissions over time and at various scales. We report CO2 emissions in the Boston, MA, urban region from September 2013 to December 2014 based on atmospheric observations in an inverse model framework. Continuous atmospheric measurements of CO2 from five sites in and around Boston were combined with a high-resolution bottom-up CO2 emission inventory and a Lagrangian particle dispersion model to determine regional emissions. Our model-measurement framework incorporates emissions estimates from submodels for both anthropogenic and biological CO2 fluxes, and development of a CO2 concentration curtain at the boundary of the study region based on a combination of tower measurements and modeled vertical concentration gradients. We demonstrate that an emission inventory with high spatial and temporal resolution and the inclusion of urban biological fluxes are both essential to accurately modeling annual CO2 fluxes using surface measurement networks. We calculated annual average emissions in the Boston region of 0.92 kg C·m-2·y-1 (95% confidence interval: 0.79 to 1.06), which is 14% higher than the Anthropogenic Carbon Emissions System inventory. Based on the capability of the model-measurement approach demonstrated here, our framework should be able to detect changes in CO2 emissions of greater than 18%, providing stakeholders with critical information to assess mitigation efforts in Boston and surrounding areas.

Modeling Ozone in the Eastern U.S. using a Fuel-Based Mobile Source Emissions Inventory

Recent studies suggest overestimates in current U.S. emission inventories of nitrogen oxides (NO _x = NO + NO₂). Here, we expand a previously developed fuel-based inventory of motor-vehicle emissions (FIVE) to the continental U.S. for the year 2013, and evaluate our estimates of mobile source emissions with the U.S. Environmental Protection Agency's National Emissions Inventory (NEI) interpolated to 2013. We find that mobile source emissions of NO _x and carbon monoxide (CO) in the NEI are higher than FIVE by 28% and 90%, respectively. Using a chemical transport model, we model mobile source emissions from FIVE, and find consistent levels of urban NO _x and CO as measured during the Southeast Nexus (SENEX) Study in 2013. Lastly, we assess the sensitivity of ozone (O₃) over the Eastern U.S. to uncertainties in mobile source NO _x emissions and biogenic volatile organic compound (VOC) emissions. The ground-level O₃ is sensitive to reductions in mobile source NO _x emissions, most notably in the Southeastern U.S. and during O₃ exceedance events, under the revised standard proposed in 2015 (>70 ppb, 8 h maximum). This suggests that decreasing mobile source NO _x emissions could help in meeting more stringent O₃ standards in the future.

On-road emissions of ammonia: An underappreciated source of atmospheric nitrogen deposition

We provide updated spatial distribution and inventory data for on-road NH₃ emissions for the continental United States (U.S.) On-road NH₃ emissions were determined from on-road CO₂ emissions data and empirical NH₃:CO₂ vehicle emissions ratios. Emissions of NH₃ from on-road sources in urbanized regions are typically 0.1-1.3tkm^-2yr^-1 while NH₃ emissions in agricultural regions generally range from 0.4-5.5tkm^-2yr^-1, with a few hotspots as high as 5.5-11.2tkm^-2yr^-1. Counties with higher vehicle NH₃ emissions than from agriculture include 40% of the U.S.

POPULATION

The amount of wet inorganic N deposition as NH₄⁺ from the National Atmospheric Deposition Program (NADP) network ranged from 37 to 83% with a mean of 58.7%. Only 4% of the NADP sites across the U.S. had <45% of the N deposition as NH₄⁺ based on data from 2014 to 2016, illustrating the near-universal elevated proportions of NH₄⁺ in deposition across the U.S. Case studies of on-road NH₃ emissions in relation to N deposition include four urban sites in Oregon and Washington where the average NH₄-N:NO₃-N ratio in bulk deposition was 2.3. At urban sites in the greater Los Angeles Basin, bulk deposition of NH₄-N and NO₃-N were equivalent, while NH₄-N:NO₃-N in throughfall under shrubs ranged from 0.6 to 1.7. The NH₄-N:NO₃-N ratio at 7-10 sites in the Lake Tahoe Basin averaged 1.4 and 1.6 in bulk deposition and throughfall, and deposition of NH₄-N was strongly correlated with summertime NH₃ concentrations. On-road emissions of NH₃ should not be ignored as an important source of atmospheric NH₃, as a major contributor to particulate air pollution, and as a driver of N deposition in urban and urban-affected regions.

Local plant responses to global problems: Dactylis glomerata responses to different traffic pollutants on roadsides

The growing number of road vehicles is a major source of regional and global atmospheric pollution increasing concentrations of CO₂ in the air, and levels of metals in air and soil. Nevertheless, the effects of these pollutants on plants growing at roadsides are poorly documented. We carried out an observational study of unmanipulated plants growing by the road, to identify the morpho-physiological responses in a perennial grass Dactylis glomerata. Firstly, we wanted to know the general effect of traffic intensity and ambient CO₂ and its interactions on different plant traits. Accordingly, we analyzed the photosynthetic response by field A/Ci Response Curves, SLA, pigment pools, foliar nitrogen, carbohydrates and morphological traits in plants at three distances to the road. Secondly, we wanted to know if Dactylis glomerata plants can accumulate metals present on the roadside (Pb, Zn, Cu, and Sr) in their tissues and rhizosphere, and the effect of these metals on morphological traits. The MANCOVA whole model results shown: 1) a significant effect of road ambient CO₂ concentration on morphological traits (not affected by traffic intensity, P _{interaction CO2 x traffic intensity}>0.05), that was mainly driven by a significant negative relationship between the inflorescence number and ambient CO₂; 2) a positive and significant relationship between ambient CO₂ and the starch content in leaves (unaffected by traffic intensity); 3) a reduction in J_max (electron transport rate) at high traffic intensity. These lines of evidences suggest a decreased photosynthetic capacity due to high traffic intensity and high levels of ambient CO₂. In addition, Pb, Cu, Zn and Sr were detected in Dactylis glomerata tissues, and Cu accumulated in roots. Finally, we observed that Dactylis glomerata individuals growing at the roadside under high levels of CO₂ and in the presence of metal pollutants, reduced their production of inflorescences.

Long-term urban carbon dioxide observations reveal spatial and temporal dynamics related to urban characteristics and growth

Cities are concentrated areas of CO2 emissions and have become the foci of policies for mitigation actions. However, atmospheric measurement networks suitable for evaluating urban emissions over time are scarce. Here we present a unique long-term (decadal) record of CO2 mole fractions from five sites across Utah's metropolitan Salt Lake Valley. We examine "excess" CO2 above background conditions resulting from local emissions and meteorological conditions. We ascribe CO2 trends to changes in emissions, since we did not find long-term trends in atmospheric mixing proxies. Three contrasting CO2 trends emerged across urban types: negative trends at a residential-industrial site, positive trends at a site surrounded by rapid suburban growth, and relatively constant CO2 over time at multiple sites in the established, residential, and commercial urban core. Analysis of population within the atmospheric footprints of the different sites reveals approximately equal increases in population influencing the observed CO2, implying a nonlinear relationship with CO2 emissions: Population growth in rural areas that experienced suburban development was associated with increasing emissions while population growth in the developed urban core was associated with stable emissions. Four state-of-the-art global-scale emission inventories also have a nonlinear relationship with population density across the city; however, in contrast to our observations, they all have nearly constant emissions over time. Our results indicate that decadal scale changes in urban CO2 emissions are detectable through monitoring networks and constitute a valuable approach to evaluate emission inventories and studies of urban carbon cycles.

Accounting for urban biogenic fluxes in regional carbon budgets

Many ecosystem models incorrectly treat urban areas as devoid of vegetation and biogenic carbon (C) fluxes. We sought to improve estimates of urban biomass and biogenic C fluxes using existing, nationally available data products. We characterized biogenic influence on urban C cycling throughout Massachusetts, USA using an ecosystem model that integrates improved representation of urban vegetation, growing conditions associated with urban heat island (UHI), and altered urban phenology. Boston's biomass density is 1/4 that of rural forests, however 87% of Massachusetts' urban landscape is vegetated. Model results suggest that, kilogram-for-kilogram, urban vegetation cycles C twice as fast as rural forests. Urban vegetation releases (R_E) and absorbs (GEE) the equivalent of 11 and 14%, respectively, of anthropogenic emissions in the most urban portions of the state. While urban vegetation in Massachusetts fully sequesters anthropogenic emissions from smaller cities in the region, Boston's UHI reduces annual C storage by >20% such that vegetation offsets only 2% of anthropogenic emissions. Asynchrony between temporal patterns of biogenic and anthropogenic C fluxes further constrains the emissions mitigation potential of urban vegetation. However, neglecting to account for biogenic C fluxes in cities can impair efforts to accurately monitor, report, verify, and reduce anthropogenic emissions.

The Material Stock–Flow–Service Nexus: A New Approach for Tackling the Decoupling Conundrum

Fundamental changes in the societal use of biophysical resources are required for a sustainability transformation. Current socioeconomic metabolism research traces flows of energy, materials or substances to capture resource use: input of raw materials or energy, their fate in production and consumption, and the discharge of wastes and emissions. This approach has yielded important insights into eco-efficiency and long-term drivers of resource use. But socio-metabolic research has not yet fully incorporated material stocks or their services, hence not completely exploiting the analytic power of the metabolism concept. This commentary argues for a material stock–flow–service nexus approach focused on the analysis of interrelations between material and energy flows, socioeconomic material stocks (“in-use stocks of materials”) and the services provided by specific stock/flow combinations. Analyzing the interrelations between stocks, flows and services will allow researchers to develop highly innovative indicators of eco-efficiency and open new research directions that will help to better understand biophysical foundations of transformations towards sustainability.

On the Impact of Granularity of Space-based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1×1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1×1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 30×30 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

Vehicle Emissions as an Important Urban Ammonia Source in the United States and China

Ammoniated aerosols are important for urban air quality, but emissions of the key precursor NH₃ are not well quantified. Mobile laboratory observations are used to characterize fleet-integrated NH₃ emissions in six cities in the U.S. and China. Vehicle NH₃:CO₂ emission ratios in the U.S. are similar between cities (0.33-0.40 ppbv/ppmv, 15% uncertainty) despite differences in fleet composition, climate, and fuel composition. While Beijing, China has a comparable emission ratio (0.36 ppbv/ppmv) to the U.S. cities, less developed Chinese cities show higher emission ratios (0.44 and 0.55 ppbv/ppmv). If the vehicle CO₂ inventories are accurate, NH₃ emissions from U.S. vehicles (0.26 ± 0.07 Tg/yr) are more than twice those of the National Emission Inventory (0.12 Tg/yr), while Chinese NH₃ vehicle emissions (0.09 ± 0.02 Tg/yr) are similar to a bottom-up inventory. Vehicle NH₃ emissions are greater than agricultural emissions in counties containing near half of the U.S. population and require reconsideration in urban air quality models due to their colocation with other aerosol precursors and the uncertainties regarding NH₃ losses from upwind agricultural sources. Ammonia emissions in developing cities are especially important because of their high emission ratios and rapid motorizations.

Soil respiration contributes substantially to urban carbon fluxes in the greater Boston area

Urban areas are the dominant source of U.S. fossil fuel carbon dioxide (FFCO2) emissions. In the absence of binding international treaties or decisive U.S. federal policy for greenhouse gas regulation, cities have also become leaders in greenhouse gas reduction efforts through climate action plans. These plans focus on anthropogenic carbon flows only, however, ignoring a potentially substantial contribution to atmospheric carbon dioxide (CO2) concentrations from biological respiration. Our aim was to measure the contribution of CO2 efflux from soil respiration to atmospheric CO2 fluxes using an automated CO2 efflux system and to use these measurements to model urban soil CO2 efflux across an urban area. We find that growing season soil respiration is dramatically enhanced in urban areas and represents levels of CO2 efflux of up to 72% of FFCO2 within greater Boston's residential areas, and that soils in urban forests, lawns, and landscaped cover types emit 2.62 ± 0.15, 4.49 ± 0.14, and 6.73 ± 0.26 μmolCO2 m(-2) s(-1), respectively, during the growing season. These rates represent up to 2.2 times greater soil respiration than rates found in nearby rural ecosystems in central Massachusetts (MA), a potential consequence of imported carbon amendments, such as mulch, within a general regime of landowner management. As the scientific community moves rapidly towards monitoring, reporting, and verification of CO2 emissions using ground based approaches and remotely-sensed observations to measure CO2 concentrations, our results show that measurement and modeling of biogenic urban CO2 fluxes will be a critical component for verification of urban climate action plans.

Improvement of the environmental and operational characteristics of vehicles through decreasing the motor fuel density

The environmental and operational characteristics of motor transport, one of the main consumers of motor fuel and source of toxic emissions, soot, and greenhouse gases, are determined to a large extent by the fuel quality which is characterized by many parameters. Fuel density is one of these parameters and it can serve as an indicator of fuel quality. It has been theoretically substantiated that an increased density of motor fuel has a negative impact both on the environmental and operational characteristics of motor transport. The use of fuels with a high density leads to an increase in carbonization within the engine, adversely affecting the vehicle performance and increasing environmental pollution. A program of technological measures targeted at reducing the density of the fuel used was offered. It includes a solution to the problem posed by changes in the refining capacities ratio and the temperature range of gasoline and diesel fuel boiling, by introducing fuel additives and adding butanes to the gasoline. An environmental tax has been developed which allows oil refineries to have a direct impact on the production of fuels with improved environmental performance, taking into account the need to minimize the density of the fuel within a given category of quality.

Assessing the global warming potential of human settlement expansion in a mesic temperate landscape from 2005 to 2050

Expansion of human settlements is an important driver of global environmental change that causes land use and land cover change (LULCC) and alters the biophysical nature of the landscape and climate. We use the state of Massachusetts, United States (U.S.) to present a novel approach to quantifying the effects of projected expansion of human settlements on the biophysical nature of the landscape. We integrate nationally available datasets with the U.S. Environmental Protection Agency's Integrated Climate and Land Use Scenarios model to model albedo and C storage and uptake by forests and vegetation within human settlements. Our results indicate a 4.4 to 14% decline in forest cover and a 35 to 40% increase in developed land between 2005 and 2050, with large spatial variability. LULCC is projected to reduce rates of forest C sequestration, but our results suggest that vegetation within human settlements has the potential to offset a substantial proportion of the decline in the forest C sink and may comprise up to 35% of the terrestrial C sink by 2050. Changes in albedo and terrestrial C fluxes are expected to result in a global warming potential (GWP) of +0.13 Mg CO2-C-equivalence ha(-1)year(-1) under the baseline trajectory, which is equivalent to 17% of the projected increase in fossil fuel emissions. Changes in terrestrial C fluxes are generally the most important driver of the increase in GWP, but albedo change becomes an increasingly important component where housing densities are higher. Expansion of human settlements is the new face of LULCC and our results indicate that when quantifying the biophysical response it is essential to consider C uptake by vegetation within human settlements and the spatial variability in the influence of C fluxes and albedo on changes in GWP.