Urban mobility conditions play a main role in shaping inequalities in megacities. In the municipality of São Paulo, work-related trips take 62% longer, are 100% more lengthy and 25% more motorized ...compared to other reasons. The objective of this work is to quantitatively assess the city's master plan guidelines which encourage the decrease in the job-housing distance, through the creation of local job offers in the suburbs to effectively decrease the commuting time of the suburban population. The analysis was carried out using a specific spatial regression model (the Spatial Error Durbin Model), using data from an extensive origin-destination survey. Results show that an increase in 10% in local job offers in a 7-km radius buffer in São Paulo would decrease the mean distance travelled in about 5.2%, which would be particularly beneficial for the suburban areas. This highlights the importance of incorporating the spatial planning of land use within transport planning in a megacity environment. Therefore, policymakers should consider strategies to bring housing and jobs closer as means to not only decrease transport inequities, but also to mitigate pollutant emissions, health burdens and economic losses, leading to overall improvements in quality of life. With the growing trend in remote work imposed by the pandemic, it will be necessary to improve our understanding of the relationship between employment and urban mobility conditions.
Display omitted
•Poor urban mobility conditions lead to overall inequalities in megacities.•In São Paulo, work-related trips are longer and more motorized than other trips.•A spatial regression durbin error model was used to analyse 62,559 trips.•An increase in 10% in job availability in a 7-km radius led to trips 5.2% shorter.•Urban planning must be integrated with transport to decrease the job-housing distance.
Worldwide monitoring of fossil fuel carbon dioxide (FFCO2) has been fragmented, and mostly devoted to developed countries. Here we compare a previously published FFCO2 dataset with socio-economic ...characteristics in order to better tailor FFCO2 urban point-sources for a megacity of the Global South, the Metropolitan Area of Rio de Janeiro (MARJ), Brazil. Evaluations were performed by superimposing maps of the FFCO2 measurements on urban data acquired from the Brazilian Institute of Geography and Statistics, the latest Origin-Destination Survey of the MARJ, and correlation and regression analyses between FFCO2 and socioeconomic variables. While we confirmed that population density and the transportation sector are important drivers of FFCO2 concentrations, the centrality of urban activities within MARJ also creates undesirable clustered zones (e.g., the city centers and the main intercity bridge). At the intra-urban scale, both high- and low-income residents play important roles in FFCO2 levels. For instance, higher-income populations tend to produce more carbon pollution at their own residential areas, where most urban activities are located. Low FFCO2 levels were found in low-income areas with poor infrastructure. However, distance from the city center, age distribution, job availability, lack of basic services, and car ownership force low-income populations to commute through high-traffic areas, adding high FFCO2 levels to the same already clustered places. By integrating FFCO2 monitoring with many socioeconomic variables, we believe that we capture its spatial distribution as well as better understand the causes of its emission patterns. Therefore, future CO2 monitoring and assessment studies conducted in megacities can benefit from the insights and discussions presented in this study.
•Low FFCO2 levels were found in low-income areas with poor infrastructure.•A spatial regression model was used to analyze drivers of FFCO2 concentration.•High FFCO2 levels were found mostly on city centers and near intercity bridge.•A polycentric development model could mitigate emissions by reducing traffic demands.•FFCO2 remains a challenge even in areas with wide biofuel use, such as MARJ.
Fossil fuel-derived CO2 (Cff) emission patterns and their point sources across the Rio de Janeiro megacity and state were estimated from a single regional-scale Δ14C distribution map based on ...isotopic measurements of ipê leaves (Tabebuia, a popular flowering deciduous perennial tree). Data from multi-year sampling (i.e., 2014–2016) was renormalized to reflect 14C signatures of the 2015 calendar year. Spatial variability in Δ14C ranges from a maximum of 27.1 ± 0.4‰ (city of Petrópolis, a higher-elevation municipality) to a minimum of −43.6 ± 1.4‰ (i.e., approximately 27.6 ± 1 ppm of Cff — Santo Cristo, a district within the Rio de Janeiro city). Overall, higher Δ14C values correlate well with green habitats and high elevation areas, while lower values are associated with Cff emissions in densely populated areas with higher industrial and traffic footprints. Cff emissions are higher where local air circulation is poor, such as the area surrounding Guanabara Bay. Other areas with significantly higher Cff emissions were the Paraíba Valley and Mountain regions. These results may be explained by atmospheric transport of CO2 from neighboring states, such as São Paulo and Minas Gerais, and by the predominant west winds and the limited regional air flow created by large topographic features. Lower Cff emissions were observed in the Northwest and Lakes regions, which are dominated by agriculture and tourism activities. Our results highlight the potential of directly estimating Cff for studying urban landscapes in the southern region of Brazil through 14C time-integrated distribution mapping of ipê leaves. The method could also be used to augment greenhouse gas (GHG) emissions inventory studies trends in partitioning Cff from CO2 of bio-template sustainable sources.
•Ipê leaves have been successfully used to assess the emission of 14C-depleted CO2ff.•CO2ff was associated with traffic footprint, industrial processes and prevalent winds.•Deciduous tree leaf analysis is important for mitigating local CO2ff emissions.
Developing countries’ megacities, characterised by dense populations and socioeconomic disparities, often face high levels of pollutants, mainly from vehicle emissions. Poor air quality can lead to a ...range of public health problems which in turn, need to be addressed by public policies. The main goal of this article is to examine the impact of public policies and the influence of transport modes on air pollution of three districts from the Metropolitan Region of São Paulo, in Brazil: Pinheiros, Parque Dom Pedro II and Taboão da Serra. The method was held through a comparative analysis, which in turn, took into account urban indicators, urban mobility data and pollutants levels (CO and NOx). These data were collected from the 2007 and 2017 São Paulo Metrô Origin and Destination Surveys and the Air Quality Database of the Environmental Company of the State of São Paulo. As key findings, the three study areas’ pollutant concentrations presented a downward trend from 2007 to 2017 as the same time there was an increase in the public transport and non-motorized transport modes. However, it is important to highlight the confluence of the state and federal public policies occuring at the same period such as PRONCOVE, Rodoanel and the Yellow Subway Line. The identified socio-environmental disparities in the urban realm highlight the importance of localised analyses in order to reveal problems and opportunities to get a better response in terms of urban mobility and air quality. Thus, the perpetuation of constant policy’s updates and interdisciplinary collaboration is crucial.
In January 2020, an extreme precipitation event occurred over southeast Brazil, with the epicentre in Minas Gerais state. Although extreme rainfall frequently occurs in this region during the wet ...season, this event led to the death of 56 people, drove thousands of residents into homelessness, and incurred millions of Brazilian Reais (BRL) in financial loss through the cascading effects of flooding and landslides. The main question that arises is: To what extent can we blame climate change? With this question in mind, our aim was to assess the socioeconomic impacts of this event and whether and how much of it can be attributed to human‐induced climate change. Our findings suggest that human‐induced climate change made this event >70% more likely to occur. We estimate that >90,000 people became temporarily homeless, and at least BRL 1.3 billion (USD 240 million) was lost in public and private sectors, of which 41% can be attributed to human‐induced climate change. This assessment brings new insights about the necessity and urgency of taking action on climate change, because it is already effectively impacting our society in the southeast Brazil region. Despite its dreadful impacts on society, an event with this magnitude was assessed to be quite common (return period of ∼$\sim$4 years). This calls for immediate improvements on strategic planning focused on mitigation and adaptation. Public management and policies must evolve from the disaster response modus operandi in order to prevent future disasters.
PDF
