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

Temporal trend and driving effect of demographic transitions on embedded carbon emissions of Chinese households

A population is regarded as the main non-economic driver of carbon emissions, causing the climatic crisis, especially in China experiencing a dramatic demographic transition. In contrast to aging, low fertility, the most remarkable feature of the Chinese population transition, has always been ignored when evaluating carbon emissions, due to the lack of long-run data. To narrow this gap, an integrated framework combining the continuous input-output tables from 1997 to 2018 with the Mann-Kendall test and vector auto-regression was presented to clarify the fluctuating trend of household embedded carbon emissions and the driving pattern of low fertility, aging, and urbanization. Our main findings showed that changes in household embedded carbon emissions have increased sharply in the last two decades. The growth of Chinese household embedded carbon emissions began to accelerate in 2001, which lagged 1 year behind the demographic indicators. Low fertility has a positive impact on households' embedded carbon emissions. More importantly, the impact of low fertility is more significant and far-reaching than that of aging. These suggest that aggressive policies for stimulating fertility and low-carbon lifestyles should be considered by policy makers.

Sustained Reductions of Bay Area CO2 Emissions 2018-2022

Cities represent a significant and growing portion of global carbon dioxide (CO2) emissions. Quantifying urban emissions and trends over time is needed to evaluate the efficacy of policy targeting emission reductions as well as to understand more fundamental questions about the urban biosphere. A number of approaches have been proposed to measure, report, and verify (MRV) changes in urban CO2 emissions. Here we show that a modest capital cost, spatially dense network of sensors, the Berkeley Environmental Air Quality and CO2 Network (BEACO2N), in combination with Bayesian inversions, result in a synthesis of measured CO2 concentrations and meteorology to yield an improved estimate of CO2 emissions and provide a cost-effective and accurate assessment of CO2 emissions trends over time. We describe nearly 5 years of continuous CO2 observations (2018-2022) in a midsized urban region (the San Francisco Bay Area). These observed concentrations constrain a Bayesian inversion that indicates the interannual trend in urban CO2 emissions in the region has been a modest decrease at a rate of 1.8 ± 0.3%/year. We interpret this decrease as primarily due to passenger vehicle electrification, reducing on-road emissions at a rate of 2.6 ± 0.7%/year.

Atmospheric CO2 and 14CO2 observations at the northern foot of the Qinling Mountains in China: Temporal characteristics and source quantification

A two-year (March 2021 to February 2023) continuous atmospheric CO2 and a one-year regular atmospheric 14CO2 measurement records were measured at the northern foot of the Qinling Mountains in Xi'an, China, aiming to study the temporal characteristics of atmospheric CO2 and the contributions from the sources of fossil fuel CO2 (CO2ff) and biological CO2 (CO2bio) fluxes. The two-year mean CO2 mole fraction was 442.2 ± 16.3 ppm, with a yearly increase of 4.7 ppm (i.e., 1.1 %) during the two-year observations. Seasonal CO2 mole fractions were the highest in winter (452.1 ± 17.7 ppm) and the lowest in summer (433.5 ± 13.3 ppm), with the monthly CO2 levels peaking in January and troughing in June. Diurnal CO2 levels peaked at dawn (05:00-07:00) in spring, summer and autumn, and at 10:00 in winter. 14C analysis revealed that the excess CO2 (CO2ex, atmospheric CO2 minus background CO2) at this site was mainly from CO2ff emissions (67.0 ± 26.8 %), and CO2ff mole fractions were the highest in winter (20.6 ± 17.7 ppm). Local CO enhancement above the background mole fraction (ΔCO) was significantly (r = 0.74, p < 0.05) positively correlated with CO2ff in a one-year measurement, and ΔCO:CO2ff showed a ratio of 23 ± 6 ppb/ppm during summer and winter sampling days, much lower than previous measurements and suggesting an improvement in combustion efficiency over the last decade. CO2bio mole fractions also peaked in winter (14.2 ± 9.6 ppm), apparently due to biomass combustion and the lower and more stable wintertime atmospheric boundary layer. The negative CO2bio values in summer indicated that terrestrial vegetation of the Qinling Mountains had the potential to uptake atmospheric CO2 during the corresponding sampling days. This site is most sensitive to local emissions from Xi'an and to short distance transportation from the southern Qinling Mountains through the valleys.

Exploring the discrepancy between top-down and bottom-up approaches of fine spatio-temporal vehicular CO2 emission in an urban road network

Road transport emissions of high spatial and temporal resolution are useful for greenhouse gas emission assessment in local action plans. However, estimating these high-resolution emissions is not straightforward, and different indirect approaches exist. The main aim of this study is to examine the differences in CO2 emissions obtained with different methods within a street canyon network in Helsinki, Finland, where a mobile laboratory campaign to quantify traffic emissions has been conducted. We compared three aerodynamic resistance based top-down methods (MOST1, MOST2 and BHT) and three activity based bottom-up microscopic emission models (NGM, HBEFAv4.2 and PHEMlight). The resulted CO2 fluxes using different methods could vary a few orders of magnitude. The combination of MOST1 and NGM model leads to the smallest discrepancy (sMAPE = 16.90 %) and the highest correlation coefficient (r = 0.78) among the rest. We evaluated the discrepancies in terms of different spatial (microenvrionments, local climate zones LCZs and grid sizes) and temporal features (seasons and periods of day). Measurements taken in LCZs of open high-rise regions and microenvironments of main road tend to have larger discrepancies between the two approaches. Using a coarser grid would lead to a relatively small discrepancy and high correlation in the wintertime, yet a loss in distinctive spatial variation. The discrepancies were also elevated on winter evenings. Among all explanatory variables, relative humidity shows the strongest relative importance for the discrepancy of the two approaches, followed by LCZs. Therefore, we stress the importance of choosing a suitable model for vehicular CO2 emission calculation based on meteorological conditions and LCZs. Such model comparison made on a local scale directly supports environmental organisations and cities' climate action plans where detailed information of CO2 emissions are needed.

Low-cost urban carbon monitoring network and implications for china: a comprehensive review

The development and renewal of gas sensor technology have enabled more and more low-cost gas sensors to form a carbon monitoring network to meet the requirements of the city. In the context of China's commitment to achieving the "double carbon" target by 2060, this paper reviews the principles of four standard gas sensors and the application of several low-cost sensors in urban carbon monitoring networks, with the aim of providing a practical reference for the future deployment of carbon monitoring networks in Chinese cities. Moreover, the types, prices, and deployment of the sensors used in each project are summarized. Based on this review, non-dispersive infrared sensors have the best performance among the sensors and are commonly used in many cities. Lots of urban climate networks in cities were summarized by many reviews in the literature, but only a few sensors were studied, and they did not consider carbon dioxide (CO2) sensors. This review focuses on the dense CO2 urban monitoring network, and some case studies are also discussed, such as Seoul and San Francisco. To address the issue of how to better ensure the balance between cost and accuracy in the deployment of sensor networks, this paper proposes a method of simultaneously deploying medium-precision and high-precision fixed sensors and mobile sensors to form an urban carbon monitoring network. Finally, the prospects and recommendations, such as different ways to mitigate CO2 and develop an entire carbon monitoring system for future urban carbon monitoring in China, are also presented.

Health risk assessments of exposure carbon dioxide among communities and children around Tonasa cement plant, Pangkep Regency, Indonesia. Monte Carlo Simulation (MCS) application

Chronic exposure to carbon dioxide (CO2) can have a negative influence on one's health and be hazardous to the environment. It could be both directly and indirectly to those communities who are living near the CO2 point sources. This study aimed to investigate the magnitude of CO2 level in ambient air and its spatial distribution which then continued to assess the potential health risks posed by communities living surround the site as well as applied the Monte Carlo Simulation (MCS) approach to predict the risks magnitude among adult and children due to CO2 air pollution from the cement industry activities in Pangkep. This observational analytic study applied health risk assessment due to the CO2 exposure both to adult and children population. To estimate the non carcinogenic risk, study used the Monte Carlo Simulation model with 10,000 iterations to estimate the risk through the inhalation pathway suffered by communities, as well as analyzing the sensitivity level every single health risk parameter. The highest risks for the adults was in station 7 with 7,641 whereas the lowest risks was in station 3 with 1,194, respectively. Furthermore, the highest risks for child was in station 4 with 498 whereas the lowest one was in station 15 with 32, respectively. Those non carcinogenic HQ were exceed the standard for adult but not at risks for children. The results of the Monte Carlo Simulation that assessed the non risks cancer probability with the 5th and 95th percentiles demonstrated that adult population were at value of 0.83 and 1.53 0.83 and 1.53 respectively, that still indicated at low risk for developing adverse health effects among those communities temporarily. However, at the same percentiles children indicated at value of 199 and 388 that indicated at risk for developing adverse health effects among those children. In addition, level of sensitivity analysis result indicated that exposure frequency with (20,9%) for adult and the exposure duration with (25,6%) for children were the most contributing factors to health risks among, respectively. Simulation determines the critical factors with major effects in reducing health risks. The CO2 magnitude not poses risks to adults, by contrast, children are at risk. Thus, limiting exposure frequency and inhalation of CO2 levels in the school for children area are highly demanded.

Comprehensive evaluation of carbon sequestration potential of landscape tree species and its influencing factors analysis: implications for urban green space management

BACKGROUND

Continuous increasing carbon dioxide (CO2) has aggravated global warming and promoted urban tree planting projects for many countries. So it's imperative to select high carbon sequestering landscape tree species while considering their aesthetic values of urban green space.

RESULTS

32 tree species were selected as test objects which were commonly used in landscaping in Zhengzhou, a typical northern city of China. To assess the comprehensive carbon sequestration potential of landscape tree species in different plant configuration types, we simultaneously considered their daily net carbon sequestration per unit leaf area (wCO2), daily net carbon sequestration per unit land area (WCO2) and daily net carbon sequestration of the whole plant (QCO2) through cluster analysis. Besides that, we found out the key factors affecting carbon sequestration potential of landscape tree species by redundancy analysis.

CONCLUSION

Populus, P Stenoptera, P. acerifolia among large arbors (LA), V odoratissimum, P. Serratifolia, S. oblata among small arbors (SA), and B sinica var. Parvifolia, B. Megistophylla, L quihoui among shrubs (S) were recommended for local urban green space management. Photosynthetic rate (Pn), crown area (CA) and leaf area index (LAI) were the key factors which affected the comprehensive carbon sequestration potential both for LA, SA and S.

Urban environments provide new perspectives for forecasting vegetation phenology responses under climate warming

Given that already-observed temperature increase within cities far exceeds the projected global temperature rise by the end of the century, urban environments often offer a unique opportunity for studying ecosystem response to future warming. However, the validity of thermal gradients in space serving as a substitute for those in time is rarely tested. Here, we investigated vegetation phenology dynamics in China's 343 cities and empirically test whether phenological responses to spatial temperature rise in urban settings can substitute for those to temporal temperature rise in their natural counterparts based on satellite-derived vegetation phenology and land surface temperature from 2003 to 2018. We found prevalent advancing spring phenology with "high confidence" and delaying autumn phenology with "medium confidence" under the context of widespread urban warming. Furthermore, we showed that space cannot substitute for time in predicting phenological shifts under climate warming at the national scale and for most cities. The thresholds of ~11°C mean annual temperature and ~600 mm annual precipitation differentiated the magnitude of phenological sensitivity to temperature across space and through time. Below those thresholds, there existed stronger advanced spring phenology and delayed autumn phenology across the spatial urbanization gradients than through time, and vice versa. Despite the complex and diverse relationships between phenological sensitivities across space and through time, we found that the directions of the temperature changes across spatial gradients were converged (i.e., mostly increased), but divergent through temporal gradients (i.e., increased or decreased without a predominant direction). Similarly, vegetation phenology changes more uniformly over space than through time. These results suggested that the urban environments provide a real-world condition to understand vegetation phenology response under future warming.

High spatial resolution assessment of air quality in urban centres using lichen carbon, nitrogen and sulfur contents and stable-isotope-ratio signatures

Air pollution and poor air quality is impacting human health globally and is a major cause of respiratory and cardiovascular disease and damage to human organ systems. Automated air quality monitoring stations continuously record airborne pollutant concentrations, but are restricted in number, costly to maintain and cannot document all spatial variability of airborne pollutants. Biomonitors, such as lichens, are commonly used as an inexpensive alternative to assess the degree of pollution and monitor air quality. However, only a few studies combined lichen carbon, nitrogen and sulfur contents, with their stable-isotope-ratio signatures (δ¹³C, δ¹⁵N and δ³⁴S values) to assess spatial variability of air quality and to 'fingerprint' potential pollution sources. In this study, a high-spatial resolution lichen biomonitoring approach (using Xanthoria parietina and Physcia spp.) was applied to the City of Manchester (UK), the centre of the urban conurbation Greater Manchester, including considerations of its urban characteristics (e.g., building heights and traffic statistics), to investigate finer spatial detail urban air quality. Lichen wt% N and δ¹⁵N signatures, combined with lichen nitrate (NO₃^-) and ammonium (NH₄⁺) concentrations, suggest a complex mixture of airborne NO_x and NH_x compounds across Manchester. In contrast, lichen S wt%, combined with δ³⁴S strongly suggest anthropogenic sulfur sources, whereas C wt% and δ¹³C signatures were not considered reliable indicators of atmospheric carbon emissions. Manchester's urban attributes were found to influence lichen pollutant loadings, suggesting deteriorated air quality in proximity to highly trafficked roads and densely built-up areas. Lichen elemental contents and stable-isotope-ratio signatures can be used to identify areas of poor air quality, particularly at locations not covered by automated air quality measurement stations. Therefore, lichen biomonitoring approaches provide a beneficial method to supplement automated monitoring stations and also to assess finer spatial variability of urban air quality.

Dramatic decline of observed atmospheric CO2 and CH4 during the COVID-19 lockdown over the Yangtze River Delta of China

The temporal variation of greenhouse gas concentrations in China during the COVID-19 lockdown in China is analyzed in this work using high resolution measurements of near surface △CO₂, △CH₄ and △CO concentrations above the background conditions at Lin'an station (LAN), a regional background station in the Yangtze River Delta region. During the pre-lockdown observational period (IOP-1), both △CO₂ and △CH₄ exhibited a significant increasing trend relative to the 2011-2019 climatological mean. The reduction of △CO₂, △CH₄ and △CO during the lockdown observational period (IOP-2) (which also coincided with the Chinese New Year Holiday) reached up to 15.0 ppm, 14.2 ppb and 146.8 ppb, respectively, and a reduction of △CO₂/△CO probably due to a dramatic reduction from industrial emissions. △CO₂, △CH₄ and △CO were observed to keep declining during the post-lockdown easing phase (IOP-3), which is the synthetic result of lower than normal CO₂ emissions from rural regions around LAN coupled with strong uptake of the terrestrial ecosystem. Interestingly, the trend reversed to gradual increase for all species during the later easing phase (IOP-4), with △CO₂/△CO constantly increasing from IOP-2 to IOP-3 and finally IOP-4, consistent with recovery in industrial emissions associated with the staged resumption of economic activity. On average, △CO₂ declined sharply throughout the days during IOP-2 but increased gradually throughout the days during IOP-4. The findings showcase the significant role of emission reduction in accounting for the dramatic changes in measured atmospheric △CO₂ and △CH₄ associated with the COVID-19 lockdown and recovery.

A decade of CO2 flux measured by the eddy covariance method including the COVID-19 pandemic period in an urban center in Sakai, Japan

Cities constitute an important source of greenhouse gases, but few results originating from long-term, direct CO₂ emission monitoring efforts have been reported. In this study, CO₂ emissions were quasi-continuously measured in an urban center in Sakai, Osaka, Japan by the eddy covariance method from 2010 to 2021. Long-term CO₂ emissions reached 22.2 ± 2.0 kg CO₂ m^-2 yr^-1 from 2010 to 2019 (± denotes the standard deviation) in the western sector from the tower representing the densely built-up area. Throughout the decade, the annual CO₂ emissions remained stable. According to an emission inventory, traffic emissions represented the major source of CO₂ emissions within the flux footprint. The interannual variations in the annual CO₂ flux were positively correlated with the mean annual traffic counts at two highway entrances and exits. The CO₂ emissions decreased suddenly, by 32% ± 3.1%, in April and May 2020 during the period in which the first state of emergency associated with COVID-19 was declared. The annual CO₂ emissions also decreased by 25% ± 3.1% in 2020. Direct long-term observations of CO₂ emissions comprise a useful tool to monitor future emission reductions and sudden disruptions in emissions, such as those beginning in 2020 during the COVID-19 pandemic.

Response of Land Use and Net Primary Productivity to Coal Mining: A Case Study of Huainan City and Its Mining Areas

The terrestrial ecosystem carbon cycle is essential to the global carbon cycle. Mining activities have seriously damaged the terrestrial ecosystem and destroyed the carbon sequestration ability of vegetation, which is of great significance to studying the effect of coal mining on land structure change and carbon sink function in cities and mining areas. However, the existing research lacks the targeted analysis of the carbon sink level of the mining area combined with the mining data. Based on the coal-mining information, land-use data, and MODIS NPP data, this study analyzed the spatio-temporal change characteristics of land use and NPP in Huainan City and its mining areas from 2001 to 2020. The results showed that: (1) 22.5% of the land types in the mining area have changed, much higher than 3.2% in Huainan; 40.08 km2 of the cropland in the mining area has been transformed into waterbodies, seriously affecting regional food security. (2) NPP fluctuates with rainfall, has a weak correlation with temperature, and is restricted by coal-mining factors. The average NPP of most coal mines is significantly lower than that of non-mining areas. The NPP of Huainan City showed an overall growth trend of 2.20 g/(m2 × a), which was much higher than the average value of 0.43 g/(m2 × a) in the mining area. Especially in the Guqiao mine, the difference in NPPslope before and after mining was as high as 16.92 g/(m2 × a). (3) The probability integral method was used to estimate that 195.16 km2 of land in Huainan would be damaged by mining in 2020. The distribution of damage degree was negatively correlated with NPPslope, which meant the more serious the damage was, the less NPPslope was. This study revealed the characteristics of land-use change and NPP spatio-temporal response in resource-based cities and mining-disturbed areas. It quantitatively estimated the impact of mining activities on regional carbon sink function. It can provide theory and data support for mining areas to carry out ecological protection and restoration, improve the environmental service function of resource-based cities, and formulate sustainable development strategies.

A multi-city urban atmospheric greenhouse gas measurement data synthesis

Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO₂) and methane (CH₄) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation.

Measurement(s)	carbon dioxide • methane • carbon monoxide
Technology Type(s)	spectroscopy
Sample Characteristic - Environment	city
Sample Characteristic - Location	North America

Artificial light pollution inhibits plant phenology advance induced by climate warming

Natural photic regime has been drastically altered by the artificial night sky luminance. Despite evidence of sufficient light brightness inducing plant physiology and affecting phenology, generalization regarding effects of light pollution on plant phenology across species and locations is less clear. Meanwhile, the relative contributions and joint effects of artificial light pollution and climate change or other anthropic stressors still remain unknown. To fill this knowledge gap, we utilized in situ plant phenological observations of seven tree species during 1991-2015 in Europe, night-time light dataset and gridded temperature dataset to investigate the impacts of the artificial light pollution on spatial-temporal shifts of plant phenological phases under climatic warming. We found 70% of the observation sites were exposed to increased light pollution during 1992-2015. Among them, plant phenological phases substantially delayed at 12-39% observation sites of leaf-out, and 6-53% of flowering. We also found plant species appeared to be more sensitive to artificial light pollution, and phenology advancement was hindered more prominently and even delay phenomenon exhibited when the color level showed stronger sky brightness. Linear mixed models indicate that although temperature plays a dominant role in shifts of plant phenological phases at the spatial scale, the inhibitory effect of artificial light pollution is evident considering the interactions. To our knowledge, this study is the first to quantitatively establish the relationship between artificial light pollution and plant phenology across species and locations. Meanwhile, these findings provide a new insight into the ecological responses of plant phenology to the potential but poorly understood environmental stressors under this warmer world and call for light pollution to be accorded the equal status as other global change phenomena.

Unveiling the changes in urban atmospheric CO2 in the time of COVID-19 pandemic: A case study of Florence (Italy)

The outbreak of COVID-19 pandemic was accompanied by global mobility restrictions and slowdown in manufacturing activities. Accordingly, cities experienced a significant decrease of CO2 emissions. In this study, continuous measurements of CO2 fluxes, atmospheric CO2 concentrations and δ13C-CO2 values were performed in the historical center of Florence (Italy) before, during and after the almost two-month long national lockdown. The temporal trends of the analyzed parameters, combined with the variations in emitting source categories (from inventory data), evidenced a fast response of flux measurements to variations in the strength of the emitting sources. Similarly, the δ13C-CO2 values recorded the change in the prevailing sources contributing to urban atmospheric CO2, confirming the effectiveness of carbon isotopic data as geochemical tracers for identifying and quantifying the relative contributions of emitting sources. Although the direct impact of restriction measurements on CO2 concentrations was less clear due to seasonal trends and background fluctuations, an in-depth analysis of the daily local CO2 enhancement with respect to the background values revealed a progressive decrease throughout the lockdown phase at the end of the heating season (>10 ppm), followed by a net increase (ca. 5 ppm) with the resumption of traffic. Finally, the investigation of the shape of the frequency distribution of the analyzed variables revealed interesting aspects concerning the dynamics of the systems.

Who avoids being involved in personal carbon trading? An investigation based on the urban residents in eastern China

Personal carbon trading scheme has been pulled into the public eye with the increasing urgency of downstream carbon emission reduction, and its feasibility largely depends on public acceptability. This study established a hierarchical framework for urban residents' approach-avoidance responses to personal carbon trading; adopted Likert scale and manikin task methods to assess the current states of residents' responses by investigating 1892 respondents in eastern China; employed one-way analysis of variance to identify the demographic differences of their responses; and used regression analysis to explore the influences of psychological factors on their responses. The findings showed that urban residents' responses to personal carbon trading scheme and participation could be classified into five response hierarchies: deep avoidance, shallow avoidance, uncertain, shallow approach, and deep approach. The average of residents' responses denoted a shallow approach, with the characteristics of median stability, duration, and noise. Moreover, residents holding deep approach responses to the scheme and participation respectively accounted for 42.365% and 34.275% of the total, which indicated a gap between attitude and behavior. Urban residents' responses exhibited significant differences with respect to demographic characteristics. Most of the residents with the most avoidance response were young males (i.e., 18-20 years old), older first-line employees (i.e., older than 50 years old), and those on subsistence incomes (i.e., annual individual or household income was RMB 30,000-50,000 yuan). Additionally, residents who held egoistic values, had low senses of social responsibility, knew little about carbon reductions, and preferred comfortable life were likely to avoid the scheme and participation. Finally, policy suggestions are proposed for the enhancement of urban residents' attitudes towards personal carbon trading, thereby providing valuable references for its implementation.

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.

An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO2 Retrievals

A growing constellation of satellites is providing near-global coverage of column-averaged CO2 observations. Launched in 2019, NASA's OCO-3 instrument is set to provide XCO2 observations at a high spatial and temporal resolution for regional domains (100 × 100 km). The atmospheric column version of the Stochastic Time-Inverted Lagrangian Transport (X-STILT) model is an established method of determining the influence of upwind sources on column measurements of the atmosphere, providing a means of analysis for current OCO-3 observations and future space-based column-observing missions. However, OCO-3 is expected to provide hundreds of soundings per targeted observation, straining this already computationally intensive technique. This work proposes a novel scheme to be used with the X-STILT model to generate upwind influence footprints with less computational expense. The method uses X-STILT generated influence footprints from a key subset of OCO-3 soundings. A nonlinear weighted averaging is applied to these footprints to construct additional footprints for the remaining soundings. The effects of subset selection, meteorological data, and topography are investigated for two test sites: Los Angeles, California, and Salt Lake City, Utah. The computational time required to model the source sensitivities for OCO-3 interpretation was reduced by 62% and 78% with errors smaller than other previously acknowledged uncertainties in the modeling system (OCO-3 retrieval error, atmospheric transport error, prior emissions error, etc.). Limitations and future applications for future CO2 missions are also discussed.

Sensor array for wireless remote monitoring of carbon dioxide and methane near carbon sequestration and oil recovery sites

Carbon sequestration and enhanced oil recovery are two important geochemical applications currently deployed using carbon dioxide (CO₂), a prevalent greenhouse gas. Despite the push to find ways to use and store excess CO₂, the development of a large-area monitoring system is lacking. For these applications, there is little literature reporting the development and testing of sensor systems capable of operating in remote areas without maintenance and having significantly low cost to allow their deployment across a large land area. This paper presents the design and validation of a low-cost solar-power distributed sensing architecture using a wireless mesh network integrated, at selective nodes, into a cellular network. This combination allows an “internet of things” approach in remote locations and the integration of a large number of sensor units to monitor CO₂ and methane (CH₄). This system will allow efficient large area monitoring of both rare catastrophic leaks along with the common micro-seepage of greenhouse gas near carbon sequestration and oil recovery sites. The deployment and testing of the sensor system was performed in an open field at Oklahoma State University. The two-tear network functionality and robustness were determined from a multi-year field study. The reliability of the system was benchmarked by correlating the measured temperature, pressure, and humidity measurement by the network of devices to existing weather data. The CO₂ and CH₄ gas concentration tracked their expected daily and seasonal cycles. This multi-year field study established that this system can operate in remote areas with minimal human interactions.

Demonstration of a solar-powered sensor array for remote carbon sequestration and enhanced oil recovery monitoring. An unattended sensor array can collect real-time gas concentrations, allow leak detection, and measure daily concentration cycles.

Sustainability-Sport-Physical Activity

The present study is a synthesizing analysis of international literature on correlations between sustainability, sport, and physical activity. The study of sustainability is considered essential in modern research; its multidisciplinary approach relies on sports science and sports economics as well. There are several aspects of sustainability that are closely associated with health and health preservation; the beneficial effect of exercise on health is also widely known. For the analysis of this complex matter, our current study relied on secondary sources, and besides exploring specialist literature, it also illustrates and analyzes related statistical data. Our results highlight the correlations between living environment and physical activity, the importance of increasing individual commitment towards sustainability and using green spaces for exercising, as well as questions on social and environmental development in relation to physical activity. The study revealed the existence of highly complex links between physical environment, physical activities, and sustainability. The results section of our study provides a brief summary on the possible ways of making people physically active. Increasing physical activity is of paramount importance for achieving the objectives formulated in relation to sustainability.

Determinants of Residents' Approach-Avoidance Responses to the Personal Carbon Trading Scheme: An Empirical Analysis of Urban Residents in Eastern China

The personal carbon trading (PCT) scheme is a policy instrument for reducing downstream carbon emissions and creating a green lifestyle, and a bottleneck hampering its implementation is the behavioral willingness of residents. Due to a pre-existing stimulus-response association, the willingness of residents can be intuitively reflected by their approach–avoidance responses. This study theoretically analyzed the mechanisms for influencing residents’ approach–avoidance responses towards the personal carbon trading scheme based on open-ended interviews, and empirically examined the mechanisms by developing rating scales and conducting questionnaire surveys on urban residents in eastern China. Findings showed that residents’ approach–avoidance responses could be negatively affected by their preference for comfort, whereas they were positively impacted by their ecological values, sense of social responsibility, cognition of the behaviors for carbon emission reduction, and cognition of personal carbon trading. In terms of subjective norms, the culture of environmentalism had a positive effect on residents’ responses to PCT scheme, while the culture of consumerism caused a negative impact on their responses. Furthermore, the perceived behavioral controls of residents partially mediated the relationships between their psychological characteristics and approach–avoidance responses. Finally, primary and pivotal suggestions were proposed for nudging Chinese urban residents towards approaching the personal carbon trading scheme, which provide theoretical support and practical guidance for its implementation.

Background conditions for an urban greenhouse gas network in the Washington, D.C. and Baltimore metropolitan region

As city governments take steps towards establishing emissions reduction targets, the atmospheric research community is increasingly able to assist in tracking emissions reductions. Researchers have established systems for observing atmospheric greenhouse gases in urban areas with the aim of attributing greenhouse gas concentration enhancements (and thus, emissions) to the region in question. However, to attribute enhancements to a particular region, one must isolate the component of the observed concentration attributable to fluxes inside the region by removing the background, which is the component due to fluxes outside. In this study, we demonstrate methods to construct several versions of a background for our carbon dioxide and methane observing network in the Washington, DC and Baltimore, MD metropolitan region. Some of these versions rely on transport and flux models, while others are based on observations upwind of the domain. First, we evaluate the backgrounds in a synthetic data framework, then we evaluate against real observations from our urban network. We find that backgrounds based on upwind observations capture the variability better than model-based backgrounds, although care must be taken to avoid bias from biospheric carbon dioxide fluxes near background stations in summer. Model-based backgrounds also perform well when upwind fluxes can be modeled accurately. Our study evaluates different background methods and provides guidance determining background methodology that can impact the design of urban monitoring networks.

Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform

Urban environments are characterized by pronounced spatiotemporal heterogeneity, which can present sampling challenges when utilizing conventional greenhouse gas (GHG) measurement systems. In Salt Lake City, Utah, a GHG instrument was deployed on a light rail train car that continuously traverses the Salt Lake Valley (SLV) through a range of urban typologies. CO₂ measurements from a light rail train car were used within a Bayesian inverse modeling framework to constrain urban emissions across the SLV during the fall of 2015. The primary objectives of this study were to (1) evaluate whether ground-based mobile measurements could be used to constrain urban emissions using an inverse modeling framework and (2) quantify the information that mobile observations provided relative to conventional GHG monitoring networks. Preliminary results suggest that ingesting mobile measurements into an inverse modeling framework generated a posterior emission estimate that more closely aligned with observations, reduced posterior emission uncertainties, and extends the geographical extent of emission adjustments.

The Relationship between Land Cover and Sociodemographic Factors

Multiple social and environmental justice concerns are linked to the urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. Because of this, the implications of the relationships between built urban form, sociodemographic factors, and air quality warrant analysis at a high spatial resolution. This study used 1m resolved LiDAR data to characterize land use in Salt Lake County, Utah, and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non-irrigated cover, increased built cover, and higher amounts of households living under poverty were related to higher long-term PM2.5 exposure. Due to regional air pollution concerns, several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research-grade air quality sensors.

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.

Effect of Air Pollution on Glutathione S-Transferase Activity and Total Antioxidant Capacity: Cross Sectional Study in Kuwait

BACKGROUND

Air pollution poses a significant threat to human health worldwide. Investigating potential health impacts is essential to the development of regulations and legislation to minimize health risks.

OBJECTIVES

The aim of the present study was to investigate the potentially hazardous effect of air pollution on the Ali Sabah Al Salem residential area in Kuwait by comparing the pollution level to a control area (Al-Qirawan) by assessing two biomarkers: erythrocyte glutathione S-transferases (e-GST) and total blood antioxidant, and then correlating the activity to pollution-related oxidative stress.

METHODS

The average concentrations of several airborne gases were measured at Ali Sabah Al Salem and Al-Qirawan, including ozone, carbon monoxide, nitrogen dioxide, nitrogen oxides, particulate matter less than 10 μm (PM₁₀), sulfur dioxide, ammonia, carbon dioxide, hydrogen sulfide, methane, and non-methane hydrocarbon. A total of fifty-eight participants were sampled from two different areas and divided into two groups. The study group was composed of 40 residents exposed to polluted ambient air in the Ali Sabah Al Salem residential area. A reference group composed of 18 residents in the Al-Qairawan area living far from major pollution sources was also tested.

RESULTS

All measured gases were higher in concentration at Ali Sabah Al Salem compared to the Al-Qirawan area. Furthermore, PM₁₀ and sulfur dioxide were higher than World Health Organization (WHO) guidelines. The e-GST activity was lower among participants of the Ali Sabah Al Salem residential area compared to participants living in the Al-Qairawan area. The total antioxidant capacity in whole blood of Ali Sabah Al Salem residents was significantly (p<0.0001) higher than in control subjects.

CONCLUSIONS

Residents in Ali Sabah Al Salem are exposed to a high level of air pollution that has a serious impact on glutathione S-transferases levels. Subsequently, regulations on pollution sources are needed to lower current health risks. Furthermore, the present study provides evidence that finger-prick blood sampling is a quick, non-invasive method suitable for screening e-GST activity and total antioxidants which may be applied for surveillance purposes.

PARTICIPANT CONSENT

Obtained.

ETHICS APPROVAL

The study was approved by the Scientific Research Committee of the Public Authority for Applied Education and Training, Kuwait.

COMPETING INTERESTS

The authors declare no competing financial interests.

Policy-Relevant Assessment of Urban CO2 Emissions

Global fossil fuel carbon dioxide (FFCO₂) emissions will be dictated to a great degree by the trajectory of emissions from urban areas. Conventional methods to quantify urban FFCO₂ emissions typically rely on self-reported economic/energy activity data transformed into emissions via standard emission factors. However, uncertainties in these traditional methods pose a roadblock to implementation of effective mitigation strategies, independently monitor long-term trends, and assess policy outcomes. Here, we demonstrate the applicability of the integration of a dense network of greenhouse gas sensors with a science-driven building and street-scale FFCO₂ emissions estimation through the atmospheric CO₂ inversion process. Whole-city FFCO₂ emissions agree within 3% annually. Current self-reported inventory emissions for the city of Indianapolis are 35% lower than our optimal estimate, with significant differences across activity sectors. Differences remain, however, regarding the spatial distribution of sectoral FFCO₂ emissions, underconstrained despite the inclusion of coemitted species information.

A Simplified Framework for High-Resolution Urban Vegetation Classification with Optical Imagery in the Los Angeles Megacity

High spatial resolution maps of Los Angeles, California are needed to capture the heterogeneity of urban land cover while spanning the regional domain used in carbon and water cycle models. We present a simplified framework for developing a high spatial resolution map of urban vegetation cover in the Southern California Air Basin (SoCAB) with publicly available satellite imagery. This method uses Sentinel-2 (10–60 × 10–60 m) and National Agriculture Imagery Program (NAIP) (0.6 × 0.6 m) optical imagery to classify urban and non-urban areas of impervious surface, tree, grass, shrub, bare soil/non-photosynthetic vegetation, and water. Our approach was designed for Los Angeles, a geographically complex megacity characterized by diverse Mediterranean land cover and a mix of high-rise buildings and topographic features that produce strong shadow effects. We show that a combined NAIP and Sentinel-2 classification reduces misclassified shadow pixels and resolves spatially heterogeneous vegetation gradients across urban and non-urban regions in SoCAB at 0.6–10 m resolution with 85% overall accuracy and 88% weighted overall accuracy. Results from this study will enable the long-term monitoring of land cover change associated with urbanization and quantification of biospheric contributions to carbon and water cycling in cities.

Effects of urban forms on CO2 emissions in China from a multi-perspective analysis

Effectively evaluating the effects of urban forms on CO₂ emissions has become a hot topic in socioeconomic sustainable development; however, few studies have been able to explore the urban form-CO₂ emission relationships from a multi-perspective view. Here, we attempted to analyze the relationships between urban forms and CO₂ emissions in 264 Chinese cities, with explicit consideration of the government policies, urban area size, population size, and economic structure. First, urban forms were calculated using the urban land derived from multiple-source remote sensing data. Second, we collected and processed CO₂ emissions and three control variables. Finally, a correlation analysis was implemented to explore whether and to what extent the spatial patterns of urban forms were associated with CO₂ emissions. The results show that urban form irregularity had a more significant impact on CO₂ emissions in low-carbon pilot cities than in non-pilot cities. The impact of the complexity of urban forms on CO₂ emissions was relatively significant in the small- and large-sized cities than in the medium-sized cities. Moreover, urban form complexity had a significant correlation with CO₂ emissions in all of the cities, the level of which basically increased with the population size. This study provides scientific bases for use in policy-making to prepare effective policies for developing a low-carbon economy with consideration of the associations between urban forms and CO₂ emissions in different scenarios.

A Multiscale Evaluation of the Coupling Relationship between Urban Land and Carbon Emissions: A Case Study of Chongqing, China

Exploring the coupling relationship between urban land and carbon emissions (CE) is one of the important premises for coordinating the urban development and the ecological environment. Due to the influence of the scale effect, a systematic evaluation of the CE at different scales will help to develop more reasonable strategies for low-carbon urban planning. However, corresponding studies are still lacking. Hence, two administrative scales (e.g., region and county) in Chongqing were selected as experimental objects to compare and analyze the CE at different scales using the spatiotemporal coupling and coupling coordination models. The results show that urban land and carbon emissions presented a significant growth trend in Chongqing at different scales from 2000 to 2015. The strength of the spatiotemporal coupling relationship between urban land and total carbon emissions gradually increased with increasing scale. At the regional scale, the high coupling coordination between urban land and total carbon emissions was mainly concentrated in the urban functional development region. Additionally, the high coupling coordination between urban land and carbon emission intensity (OI) was still located in the counties within the metropolitan region of Chongqing, but the low OI was mainly distributed in the counties in the northeastern and southeastern regions of Chongqing at the county level. This study illustrates the multiscale trend of CE and suggests differentiated urban land and carbon emission reduction policies for controlling urban land sprawl and reducing carbon emissions.

Fossil Fuel Combustion Is Driving Indoor CO2 Toward Levels Harmful to Human Cognition

Human activities are elevating atmospheric carbon dioxide concentrations to levels unprecedented in human history. The majority of anticipated impacts of anthropogenic CO2 emissions are mediated by climate warming. Recent experimental studies in the fields of indoor air quality and cognitive psychology and neuroscience, however, have revealed significant direct effects of indoor CO2 levels on cognitive function. Here, we shed light on this connection and estimate the impact of continued fossil fuel emissions on human cognition. We conclude that indoor CO2 levels may indeed reach levels harmful to cognition by the end of this century, and the best way to prevent this hidden consequence of climate change is to reduce fossil fuel emissions. Finally, we offer recommendations for a broad, interdisciplinary approach to improving such understanding and prediction.

14C-AMS measurements in modern tree rings to trace local fossil fuel-derived CO2 in the greater Xi'an area, China

Fossil fuel-derived CO₂ (CO_2ff) time series are critical to understanding urban carbon emissions, and to devise strategies to mitigate emission reduction. Using tree ring ¹⁴C archives, we reconstruct an historical CO_2ff time series from 1991 to 2015 in the greater Xi'an region, China. CO_2ff concentrations from the urban sites reached 22.5 ppm, with an average of 14.0 ppm, while average values from rural and mountain sites averaged about 6.0 ppm. These values provide a good measure of the distribution of anthropogenic CO₂ emissions in the region. We also observed CO_2ff concentration increases from both urban and rural sites during the study period, with more significant increases among urban sites. The persistent rise in CO_2ff was attributed to increasing energy consumption caused by regional socio-economic development, which are corroborated by strong correlations between CO_2ff and socioeconomic parameters.

Greenhouse gas observations from the Northeast Corridor tower network

We present the organization, structure, instrumentation, and measurements of the Northeast Corridor greenhouse gas observation network. This network of tower-based in situ carbon dioxide and methane observation stations was established in 2015 with the goal of quantifying emissions of these gases in urban areas in the northeastern United States. A specific focus of the network is the cities of Baltimore, MD, and Washington, DC, USA, with a high density of observation stations in these two urban areas. Additional observation stations are scattered throughout the northeastern US, established to complement other existing urban and regional networks and to investigate emissions throughout this complex region with a high population density and multiple metropolitan areas. Data described in this paper are archived at the National Institute of Standards and Technology and can be found at https://doi.org/10.18434/M32126 (Karion et al., 2019).

Greenhouse gas observations from the Northeast Corridor tower network

We present the organization, structure, instrumentation, and measurements of the Northeast Corridor greenhouse gas observation network. This network of tower-based in situ carbon dioxide and methane observation stations was established in 2015 with the goal of quantifying emissions of these gases in urban areas in the northeastern United States. A specific focus of the network is the cities of Baltimore, MD, and Washington, DC, USA, with a high density of observation stations in these two urban areas. Additional observation stations are scattered throughout the northeastern US, established to complement other existing urban and regional networks and to investigate emissions throughout this complex region with a high population density and multiple metropolitan areas. Data described in this paper are archived at the National Institute of Standards and Technology and can be found at https://doi.org/10.18434/M32126 (Karion et al., 2019).

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.

The urban imprint on plant phenology

The modification of the surface radiation and energy balance in urban areas causes their temperatures to exceed those of the surrounding countryside¹. It has thus been suggested that urban environments may serve as field laboratories for studying the effects of a warming climate on biota in a space-for-time substitution^2–5. We investigated changes in the timing of plant phenology and temperature across study sites differing in the degree of urbanization using publicly available pan European data sets for the period 1981-2010^6,7. We found a significant advancement in leaf development, flowering and fruiting phenological phases with higher degrees of urbanization, while a significant delay was observed for leaf senescence phenological phases. Along with these phenological changes an increase of air temperature with higher degrees of urbanization was observed. This increase was largest during the periods of leaf development, flowering and fruiting and smallest during the period of leaf senescence. Based on these results we show that the apparent temperature sensitivity of phenological phases to urban warming is either significantly dampened (leaf development, flowering and fruiting) or reversed (leaf senescence) compared to the temperature sensitivity inferred from temporal changes in phenology and temperature. We conclude that gradients in urbanization represent a poor analog for the temporal changes in plant phenology, apparently due to confounding factors associated with urbanization.

Vehicle emissions and fertilizer impact the leaf chemistry of urban trees in Salt Lake Valley, UT

The urban nitrogen (N) and carbon (C) cycles are substantially influenced by human activity. Alterations to these cycles include increased inputs from fossil fuel combustion and fertilizer use. The leaf chemistry of urban trees can be used to distinguish between these different N and C sources. Here, we evaluated relationships between urban vegetation and different N and C sources in street and residential trees in the Salt Lake Valley, Utah. We tested three hypotheses: 1) unfertilized street trees on high traffic density roads will have higher leaf %N, more enriched δ¹⁵N and more depleted δ¹³C than unfertilized street trees on low traffic density roads; 2) trees in high income residential neighborhoods will have higher leaf %N, more depleted δ¹⁵N and more enriched δ¹³C than trees in lower income neighborhoods; and 3) unfertilized street trees will have lower leaf %N, more enriched δ¹⁵N and more depleted δ¹³C than fertilized residential trees. Leaf δ¹⁵N was more enriched near high traffic density roads for one study species. However, street tree δ¹⁵N and δ¹³C were largely influenced by vehicle emissions from primary and secondary roads within 1000 m radius rather than the immediately adjacent road. Leaf δ¹³C was correlated with neighborhood income, although this relationship may be the result of variations in irrigation practices rather than variations in C sources. Finally, unfertilized trees in downtown Salt Lake had lower leaf %N, more enriched δ¹⁵N and more depleted δ¹³C than fertilized trees. These results highlight that urban trees can serve as biomonitors of the environment. Moreover, they emphasize that roads can have large spatial footprints and that the leaf chemistry of urban vegetation may be influenced by the spatial patterns in roads and road densities at the landscape scale.

Dynamic Assessment of Construction Materials in Urban Building Stocks: A Critical Review

There is a lack of understanding on the different types of dynamics of building stocks, in real life and in models. Moreover, there is now a particular interest in the embodied impacts of construction materials, since with the increasing efficiency of buildings operation, embodied impacts gain more importance in the overall building life cycle. This critical review wants to advance the understanding of the type of dynamics, methods, and tools used. The well-known IPAT equation is adapted for building stocks and three dynamics are defined: spatial, evolutionary temporal, and spatial-cohort dynamic. A framework is defined that can help researchers choose a method, tool, and dynamics of input parameters depending on their research goal, case study, and data. Moreover, generally valid conclusions are drawn, including MFA is useful to model spatially dynamic material flows; GIS is needed to include spatial dynamics. Retrofit, compared to construction and demolition, is understudied and usually analyzed through top-down methods. Material intensity and emission intensity are rarely modeled in a dynamic way. Overall, scholars seem to perform increasingly data intensive and complex studies tailored to a specific case study. However, there are big differences in the quality depending on the dynamic of input parameters.

Estimating vehicle carbon dioxide emissions from Boulder, Colorado, using horizontal path-integrated column measurements

We performed 7.5 weeks of path-integrated concentration measurements of CO2, CH4, H2O, and HDO over the city of Boulder, Colorado. An open-path dual-comb spectrometer simultaneously measured time-resolved data across a reference path, located near the mountains to the west of the city, and across an over-city path that intersected two-thirds of the city, including two major commuter arteries. By comparing the measured concentrations over the two paths when the wind is primarily out of the west, we observe daytime CO2 enhancements over the city. Given the warm weather and the measurement footprint, the dominant contribution to the CO2 enhancement is from city vehicle traffic. We use a Gaussian plume model combined with reported city traffic patterns to estimate city emissions of on-road CO2 as (6.2 ± 2.2) × 105 metric tons (t) CO2 yr-1 after correcting for non-traffic sources. Within the uncertainty, this value agrees with the city's bottom-up greenhouse gas inventory for the on-road vehicle sector of 4.5 × 105 t CO2 yr-1. Finally, we discuss experimental modifications that could lead to improved estimates from our path-integrated measurements.