Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

Abstract

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice.

Air Quality, Health and Community Action

“…Shandas et al [74] have made use of spatial analysis to understand the community structure, population distribution, and air quality at the neighbor- A systematic review of 15 recent publications resulted in four strategies to improve urban air quality: general regulations on air emissions, road traffic related interventions, energy generation related interventions, and greenhouse gas emission reduction interventions [92]. Particulate matter and nitrogen dioxide were the pollutants of greatest concern in these 15 papers.…”

Arborização urbana e qualidade do ar na cidade de São Paulo

“…Somente 13,46% dos estudos apresentados nessa revisão, utilizam-se da interface IV -Árvores Urbanas, Qualidade do ar e Saúde Pública, com discussão e apresentação embasadas em dados originais ou secundários (ITO et al, 2015;LEE, 2014;HIRABAYASHI;GREENFIELD, 2014;RAO et al, 2014;SHANDAS et al, 2016;TSAO et al, 2014) Esses dados mostram que há uma certa dificuldade de realizar pesquisas de alto impacto que abordem os 3 espocos de pesquisa, que esse tipo de pesquisa pode estar iniciando sua tendência mundial, e que alguns países como o Brasil, por exemplo, apontam uma maior carência de dados fidedignos e ferramentas, como softwares e modelos próprios, que possam embasar sua abordagem interdisciplinar.…”

“…Estudos epidemiológicos vêm definindo que PM, NO2 e 03 são prejudiciais à saúde em áreas urbanas, principalmente PM2,5 que devido ao seu tamanho pode penetrar mais profundamente o corpo humano, induzindo a doenças pulmonares, problemas no sistema imunológico e morte prematura (JIN et al, 2014;LEE, 2014;RAO et al, 2014;TSAO et al, 2014). MORAKINYO; LAM, 2016aLAM, , 2016bMORANI et al, 2011;HIRABAYASHI;GREENFIELD, 2014;RAO et al, 2014;SHANDAS et al, 2016;WU et al, 2015a).…”

“…Já 27% dos estudos, utilizaram análises de uso e ocupação do solo, através de sensoriamento remoto, imagens de satélite de alta resolução, softwares como ArcGis e Landsat (ALONSO et al, 2011;ANDRUSAITYTE et al, 2016;BEYER et al, 2014;CHAN et al, 2015;CHEN et al, 2016;CURRIE;BASS, 2008;GARCÍA-GÓMEZ et al, 2016;GRAZULEVICIENE et al, 2015;HYSTAD et al, 2014;KABISCH;HAASE;VAN DEN BOSCH, 2016;KARDAN et al, 2015;KIHAL-TALANTIKITE et al, 2013;MANES et al, 2012;MORANI et al, 2011;QIU et al, 2009;TSAO et al, 2014;WU et al, 2015b QIU et al, 2009;SALMOND et al, 2013;SHANDAS et al, 2016;VIIPPOLA et al, 2016;WANG et al, 2012).…”