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Assessing the PM2.5 impact of biomass combustion in megacity Dhaka, Bangladesh - PubMed (nih.gov)

This article is about crop burning in Dhaka, Bangladesh and attempts to figure out if there is more or less harmful PM2.5 particulate air pollution caused by either fossil fuels or biomass, and during which season is one or the other higher in the air pollution it produces. During monsoon season, fossil fuels lead in the most PM2.5 releases at 44.3%. When it is not monsoon season and is the winter season, the percentages are way higher for PM2.5 air particulate releases at 41.4% for the remainder of the year. Across the globe, there are now people stepping up to uncover the true and real environmental and health impacts this harmful particulate byproduct causes in different parts of the world and with differring weather conditions than what we see in North Carolina. 

https://www.researchgate.net/publication/351209404_PM25_Emissions_from_…;

This study is set in South/Southeast Asia and uncovering that, when trying to count the percentages of PM2.5 put off during biomass, the true amount of emissions were being gravely undercalculated. Specifically rice straw burning becuase the amount burned varied so much because of different harvest and burning practices that it just wasn't taken into consideration. What this study does is go bottom up using these strategies: "subnational spatial database of rice-harvested area, region-specific fuel-loading factors, region, and burning-practice-specific emission and combustion factors, including literature-derived estimates of straw and stubble burned"(Lasko et al. 2021, 1). 

In this essay the authors have highlighted some of the stakeholders in the fight against industrial biomass operations as members of the surrounding community who live with these operations as close as their own backyards, and experience the environmental pollution directly everyday. They highlighted Belinda Joyner, a resident of Northhampton County, and an environmental activist who rose to defend her community and their lands and livelihoods due to expanding hazardous infrastructures such as the Atlantic Coast Pipeline and the Enviva power plant. Other stakeholders besides activists and organziers such as Belinda include the people of Northampton County who attend hearings with government officials and take a stance agaisnt pollution, as well as organizations such as the Dogwood Alliance. The county is predominantly Black and working class, one of several in North Carolina that bear the brunt of exploittion and pollution by powerful biomass manufacturers such as Drax and Enviva.

This timeline essay provides more examples from recent years of community responses and collective action for environmental justice.

The development of both pipelines and CAFOs (confined animal feeding operations) in eastern NC have prompted action from justice organizations such as the North Carolina Environmnetal Justice Network (NCEJN). To address the ongoing problem of CAFOs, NCEJN has provided a number of resources on their site, as well as ways to take action by signing a petition to stop the use of hog waste as fertilizer. Prior to the Atlantic Coast Pipeline (ACP) being canceled in 2020, NCEJN played a role in organizing protests and taking legal actions- in conjunction with many other community member and activist groups- against Dominion and Duke Energy, the companies responsible for the ACP's construction. 

How does visualizing allows us to set the parameters to make the future vision a reality?

Public Health Alliance of Southern California. California Healthy Places Index. 2019. https://healthyplacesindex.org.

© 2018 Public Health Alliance of Southern California

Permission is hereby granted to use, reproduce, and distribute these materials for noncommercial purposes, including educational, government and community uses, with proper attribution to the Public Health Alliance of Southern California including this copyright notice. Use of this publication does not imply endorsement by the Public Health Alliance of Southern California.

© 2018 California Department of Public Health (CDPH)

Permission is hereby granted to use, reproduce, and distribute these materials for noncommercial purposes, including educational, government, and community uses, with proper attribution to the CDPH, including this copyright notice. Use of this publication does not imply endorsement by the CDPH.

The index does not include certain neighborhood characteristics critical to health because they did not meet the criteria for inclusion (described in question 3). For instance, this included physician ratios (the number of physicians per 100,000 population) because data was missing for a majority of census tracts. In fact, the steering committee was unable to locate much data on health care access or quality at the census-tract level (only data on health care insurance coverage was available).  

 The index was previously critiqued in ways that led to a shift from framing data in terms of “disadvantage” towards a framework of “opportunity”. This led to not only a renaming of the index (from “the Health Disadvantage Index to the Healthy Places Index) but also a shift in reporting of data (e.g. highlight the percentage of the population with a BA degree or higher rather than the percentage of population without a college degree). 

The HPI is also limited in terms of the effects of confounding, with some indicators with strong evidence of health effects showing contrary associations with life expectancy at birth by census tract. The steering committee has also acknowledged that the HPI might not be accurate for census tracts undergoing rapid population change (e.g. due to immigration, rapid gentrification, or other changes).

The HPI notably does not correlate strongly with CalEnviroScreen, which the steering committee for the HPI noted failed to identify one-third of census tracts with the worst conditions for population health. The HPI is ultimately more centered on considering environmental factors as a part of overall health, rather than as a central determinant. However, this disconnect between CalEnviroScreen and the HPI may also be a reflection of the challenges environmental injustice advocates have faced in linking environmental factors to health outcomes (which might not be as visible and geographically direct as the links between health and other indicators).

The HPI draws data about 25 community characteristics into a single indexed HPI score. The includes sub-scores for 8 “Policy Action Areas”: Economic, Education, Housing, Health Care Access, Neighborhood, Clean Environment, Transportation, and Social Factors. These scores are meant to be used to evaluate health geographically. Each policy action area includes the following individual indicators and weights:

ECONOMIC (0.32)

• Poverty
• Employment
• Income

EDUCATION (0.19)

• Pre-school enrollment
• High school enrollment
• Bachelors attainment

HEALTHCARE (0.05)

• Insured adults

HOUSING (0.05)

• Severe cost burden low income
• Homeownership
• Kitchen and plumbing
• Crowding

NEIGHBORHOOD (0.08)

• Retail jobs
• Supermarket access
• Parks
• Tree canopy
• Alcohol establishments

CLEAN ENVIRONMENT (0.05)

• Diesel PM
• Ozone
• PM2.5
• Drinking water

SOCIAL (0.10)

• Two parent household
• Voting

TRANSPORTATION (0.16)

• Healthy community
• Automobile access

*The steering committee for the HPI sought to include race/ethnicity as a 9th policy action area, but they were prohibited from doing so by state law which does not allow California state agencies to use race as a basis for public contracting.

The primary HPI Index is designed to align with life expectancy at birth as a predictive measure of community health status. However, the Healthy Places mapping tool can also be used to create custom scores using different indicators. The mapping tool includes detailed definitions of each indicator.

Each indicator is linked to a policy guide, which outlines concrete actions (e.g. best practices, emerging policy options) that local jurisdictions can take to improve HPI indicators. These actions are sometimes aimed at addressing direct links between policy and an action area, and other times aimed at addressed the root causes of an action area. The mapping tool also enables filtering results by “Decision support layers” like health outcomes, health risk behaviors, race/ethnicity, climate change effects, and other layers that the alliance identifies as important for advancing “resilient, equitable communities in California”. Geographies (e.g. census tracts) can also be compared by indicator using a ranking tool. The pool function can be used to create customized aggregations of data to map (e.g. adding several census-tracts together).