Using crowdsourced data to estimate the carbon footprints of global cities

Cities are at the forefront of the battle against climate change. However, intercity comparisons and responsibility allocations among cities are hindered because cost- and time-effective methods to calculate the carbon footprints of global cities have yet to be developed. Here, we establish a hybrid method integrating top-down input–output analysis and bottom-up crowdsourced data to estimate the carbon footprints of global cities. Using city purchasing power as the main predictor of the carbon footprint, we estimate the carbon footprints of 465 global cities in 2020. Those cities comprise 10% of the global population but account for 18% of the global carbon emissions showing a significant concentration of carbon emissions. The Gini coefficients are applied to show that global carbon inequality is less than income inequality. In addition, the increased carbon emissions that come from high consumption lifestyles offset the carbon reduction by efficiency gains that could result from compact city design and large city scale. Large climate benefits could be obtained by achieving a low-carbon transition in a small number of global cities, emphasizing the need for leadership from globally important urban centres

Using crowdsourced data to estimate the carbon footprints of global cities

Cities are at the forefront of the battle against climate change. However, intercity comparisons and responsibility allocations among cities are hindered because cost- and time-effective methods to calculate the carbon footprints of global cities have yet to be developed. Here, we establish a hybrid method integrating top-down input–output analysis and bottom-up crowdsourced data to estimate the carbon footprints of global cities. Using city purchasing power as the main predictor of the carbon footprint, we estimate the carbon footprints of 465 global cities in 2020. Those cities comprise 10% of the global population but account for 18% of the global carbon emissions showing a significant concentration of carbon emissions. The Gini coefficients are applied to show that global carbon inequality is less than income inequality. In addition, the increased carbon emissions that come from high consumption lifestyles offset the carbon reduction by efficiency gains that could result from compact city design and large city scale. Large climate benefits could be obtained by achieving a low-carbon transition in a small number of global cities, emphasizing the need for leadership from globally important urban centres

Pluralizing the urban waste economy: insights from community-based enterprises in Ahmedabad (India) and Kampala (Uganda)

The delivery of urban basic infrastructure services is often guided by the modern infrastructure ideal, which aims for technical innovation, economic efficiency and uniformity through long-term, centralized management approaches. In rapidly growing urban centres of the global South, however, heterogeneous infrastructure configurations have long involved multiple systems in varying degrees of coexistence. This paper explores how community-based enterprises – organizations that aim not to turn a profit but rather to generate human well-being – contribute to, complement or conflict with wider municipal solid waste management strategies. It does so through two case studies, focused on Luchacos, a local enterprise turning waste into briquettes in an informal settlement of Kampala, Uganda; and the Self Employed Women’s Association (SEWA), a cooperative of waste pickers in Ahmedabad, India. Drawing on empirical data and policy analysis, the research finds that, given the necessary state support, community-based enterprises can contribute to a range of sustainability and development objectives.Urban Development ManagementManagement in the Built Environmen

Uncovering Blind Spots in Urban Carbon Management: The Role of Consumption-Based Carbon Accounting in Bristol, UK

The rapid urbanisation of the twentieth century, along with the spread of high-consumption urban lifestyles, has led to cities becoming the dominant drivers of global anthropogenic greenhouse gas emissions. Reducing these impacts is crucial, but production-based frameworks of carbon measurement and mitigation—which encompass only a limited part of cities’ carbon footprints—are much more developed and widely applied than consumption-based approaches that consider the embedded carbon effectively imported into a city. Frequently, therefore, cities are left blind to the importance of their wider consumption-related climate impacts, while at the same time left lacking effective tools to reduce them. To explore the relevance of these issues, we implement methodologies for assessing production- and consumption-based emissions at the city-level and estimate the associated emissions trajectories for Bristol, a major UK city, from 2000 to 2035. We develop mitigation scenarios targeted at reducing the former, considering potential energy, carbon and financial savings in each case. We then compare these mitigation potentials with local government ambitions and Bristol’s consumption-based emissions trajectory. Our results suggest that the city’s consumption-based emissions are three times the production-based emissions, largely due to the impacts of imported food and drink. We find that low-carbon investments of circa £3 billion could reduce production-based emissions by 25% in 2035. However, we also find that this represents <10% of Bristol’s forecast consumption-based emissions for 2035 and is approximately equal to the mitigation achievable by eliminating the city’s current levels of food waste. Such observations suggest that incorporating consumption-based emission statistics into cities’ accounting and decision-making processes could uncover largely unrecognised opportunities for mitigation that are likely to be essential for achieving deep decarbonisation

Copy Number Variation across European Populations

Genome analysis provides a powerful approach to test for evidence of genetic variation within and between geographical regions and local populations. Copy number variants which comprise insertions, deletions and duplications of genomic sequence provide one such convenient and informative source. Here, we investigate copy number variants from genome wide scans of single nucleotide polymorphisms in three European population isolates, the island of Vis in Croatia, the islands of Orkney in Scotland and the South Tyrol in Italy. We show that whereas the overall copy number variant frequencies are similar between populations, their distribution is highly specific to the population of origin, a finding which is supported by evidence for increased kinship correlation for specific copy number variants within populations

The Economic Case for Low Carbon Development in Rapidly Growing Developing World Cities: A case study of Palembang, Indonesia.

Where costs or risks are higher, evidence is lacking or supporting institutions are less developed, policymakers can struggle to make the case for low-carbon investment. This is especially the case in developing world cities where decision-makers struggle to keep up with the pace and scale of change. Focusing on Palembang in Indonesia, this paper considers the economic case for proactive investment in low-carbon development. We find that a rapidly growing industrial city in a developing country can reduce emissions by 24.1% in 2025, relative to business as usual levels, with investments of USD405.6 million that would reduce energy expenditure in the city by USD436.8 million. Emissions from the regional grid could be reduced by 12.2% in 2025, relative to business as usual trends, with investments of USD2.9 billion that would generate annual savings of USD175 million. These estimates understate the savings from reduced expenditure on energy subsidies and energy infrastructure. The compelling economic case for mainstreaming climate mitigation in this developing country city suggests that the constraints on climate action can be political and institutional rather than economic. There is therefore a need for more effective energy governance to drive the transition to a low-carbon economy

Genomic insights into the origin of farming in the ancient Near East

We report genome-wide ancient DNA from 44 ancient Near Easterners ranging in time between ~12,000 and 1,400 BC, from Natufian hunter–gatherers to Bronze Age farmers. We show that the earliest populations of the Near East derived around half their ancestry from a ‘Basal Eurasian’ lineage that had little if any Neanderthal admixture and that separated from other non-African lineages before their separation from each other. The first farmers of the southern Levant (Israel and Jordan) and Zagros Mountains (Iran) were strongly genetically differentiated, and each descended from local hunter–gatherers. By the time of the Bronze Age, these two populations and Anatolian-related farmers had mixed with each other and with the hunter–gatherers of Europe to greatly reduce genetic differentiation. The impact of the Near Eastern farmers extended beyond the Near East: farmers related to those of Anatolia spread westward into Europe; farmers related to those of the Levant spread southward into East Africa; farmers related to those of Iran spread northward into the Eurasian steppe; and people related to both the early farmers of Iran and to the pastoralists of the Eurasian steppe spread eastward into South Asia

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

BACKGROUND: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. METHODS AND FINDINGS: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. CONCLUSIONS: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior