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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Past and Present Biophysical Redundancy of Countries as a Buffer to Changes in Food Supply

Spatially diverse trends in population growth, climate change, industrialization, urbanization and economic development are expected to change future food supply and demand. These changes may affect the suitability of land for food production, implying elevated risks especially for resource constrained, food-importing countries. We present the evolution of biophysical redundancy for agricultural production at country level, from 1992 to 2012. Biophysical redundancy, defined as unused biotic and abiotic environmental resources, is represented by the potential food production of 'spare land', available water resources (i.e., not already used for human activities), as well as production increases through yield gap closure on cultivated areas and potential agricultural areas. In 2012, the biophysical redundancy of 75 (48) countries, mainly in North Africa, Western Europe, the Middle East and Asia, was insufficient to produce the caloric nutritional needs for at least 50% (25%) of their population during a year. Biophysical redundancy has decreased in the last two decades in 102 out of 155 countries, 11 of these went from high to limited redundancy, and nine of these from limited to very low redundancy. Although the variability of the drivers of change across different countries is high, improvements in yield and population growth have a clear impact on the decreases of redundancy towards the very low redundancy category. We took a more detailed look at countries classified as 'Low Income Economies (LIEs)' since they are particularly vulnerable to domestic or external food supply changes, due to their limited capacity to offset for food supply decreases with higher purchasing power on the international market. Currently, nine LIEs have limited or very low biophysical redundancy. Many of these showed a decrease in redundancy over the last two decades, which is not always linked with improvements in per capita food availability.

biophysics↗
NASA NTRS2003

Changing the Paradigm: Preparing Students for the Computing Profession in the 21st Century

The dramatic technological developments of the past decade have led to a tremendous growth in the demand for computer science professionals well-versed in advanced technology and techniques. NASA, traditionally a haven for cutting-edge innovators, is now competing with every industrial and government sector for computer science talent. The computer science program at University of Texas at San Antonio (UTSA) faces challenges beyond those intrinsically presented by rapid technological change, because a significant number of UTSA students come from low-income families with no Internet or computer access at home. An examination of enrollment statistics for the computer science program at UTSA showed that very few students who entered as freshmen successfully graduated. The upper division courses appeared to be populated by graduate students removing deficiencies and by transfer students. The faculty was also concerned that the students who did graduate from the program did not have the strong technical and programming skills that the CS program had been noted for in the community during the 1980's.

Robbins, Kay A.↗
NASA NTRS2008

In the Shade of Affluence: The Inequitable Distribution of the Urban Heat Island

The urban heat island is an unintended consequence of humans building upon rural and native landscapes. We hypothesized that variations in vegetation and land use patterns across an urbanizing regional landscape would produce a temperature distribution that was spatially heterogeneous and correlated with the social characteristics of urban neighborhoods. Using biophysical and social data scaled to conform to US census geography, we found that affluent whites were more likely to live in vegetated and less climatically stressed neighborhoods likely to live in than low-income Latinos in Phoenix, Arizona. Affluent neighborhoods had cooler summer temperatures that reduced exposure to outdoor heat-related health risks, especially during a heat wave period. In addition to being warmer, poorer neighborhoods lacked critical resources in their physical and social environments to help them cope with extreme heat. Increased average temperatures due to climate change are expected to exacerbate the impacts of urban heat islands.

Harlan, Sharon L.↗
NASA NTRS2016

Impacts of Extreme Events on Human Health

Increased Exposure to Extreme Events Key Finding 1: Health impacts associated with climate-related changes in exposure to extreme events include death, injury, or illness; exacerbation of underlying medical conditions; and adverse effects on mental health[High Confidence]. Climate change will increase exposure risk in some regions of the United States due to projected increases in the frequency and/or intensity of drought, wildfires, and flooding related to extreme precipitation and hurricanes [Medium Confidence].Disruption of Essential Infrastructure Key Finding 2: Many types of extreme events related to climate change cause disruption of infrastructure, including power, water, transportation, and communication systems, that are essential to maintaining access to health care and emergency response services and safeguarding human health [High Confidence].Vulnerability to Coastal Flooding Key Finding 3: Coastal populations with greater vulnerability to health impacts from coastal flooding include persons with disabilities or other access and functional needs, certain populations of color, older adults, pregnant women and children, low-income populations, and some occupational groups [High Confidence].Climate change will increase exposure risk to coastal flooding due to increases in extreme precipitation and in hurricane intensity and rainfall rates, as well as sea level rise and the resulting increases in storm surge.

floods↗
NASA NTRS2018

Climate Change Impacts on Agriculture: Challenges, Opportunities, and AgMIP Frameworks for Foresight

Agricultural systems are currently undergoing rapid shifts owing to socioeconomic development, technological change, population growth, economic opportunity, evolving demand for commodities, and the need for sustainability amid global environmental change. It is not sufficient to maintain current harvest levels; rather, there is a need to rapidly increase production in light of a population growing to nearly 10 billion by mid-century and to more than 11 billion by 2100 (FAO, 2016; UN, 2016; Popkin et al., 2012). Current and future agricultural systems are additionally burdened by human-caused climate change, the result of accumulating greenhouse gas and aerosol emissions, ecological destruction, and land use changes that have altered the chemical composition of Earth’s atmosphere and trapped energy in the Earth system (IPCC, 2013; Porter et al., 2014). This increased energy has already raised average surface temperatures by approximately 1 degree Centigrade (GISTEMP Team, 2017; Hansen et al., 2010), leading early on to the term “global warming,” but this phenomenon is now more accurately referred to as “climate change” because it also modifies atmospheric circulation, adjusts regional and seasonal precipitation patterns, and shifts the distribution and characteristics of extreme events (Bindoff et al., 2013; Collins et al., 2013). Food and health systems face increasing risk owing to progressive climate change now manifesting itself as more frequent, severe extreme weather events—heat waves, droughts, and floods (IPCC, 2013). Often without warning, weather-related shocks can have catastrophic and reverberating impacts on the increasingly exposed global food system—through production, processing, distribution, retail, disposal, and waste. Simultaneously, malnutrition and ill health are arising from lack of access to nutritious food, exacerbated in crises such as food price spikes or shortages. For some countries, particularly import-dependent low-income countries, weather shocks and price spikes can lead to social unrest, famine, and migration.

Ruane, Alex C.↗
NASA NTRSDate not supplied

An Evening with NASA Scientists and Engineers: A Senior Living Community Outreach Program

Introduction: An Evening with NASA Scientists and Engineers is an outreach program for senior living communities, where participants learn from and interact with a scientist or engineer in a virtual setting. Participants learn about NASA science and engineering through a behind-the-scenes look from the people who work at NASA. The program focuses on both the stories behind the discoveries and the stories behind the people. The audience tunes in to the events via the NASA Zoom Webinar platform, where they have the opportunity to ask questions throughout the approximately 30-minute program. By bringing the audience into the conversation, we build rapport and thus improve their connection with NASA. Overview: An Evening with NASA Scientists and Engineers began in September 2020 when we identified a need for outreach to this particular demographic, as senior living communities had been hit especially hard by the COVID-19 pandemic. The program covers a wide range of topics, including heliophysics, astrophysics, planetary science, Earth science, planetary defense, and more, depending on what is topically appropriate at the time, and occurs on a roughly monthly basis. Each interactive presentation is between 20-25 minutes with 5-10 minutes of dedicated Q&A. Future dates and topics may change depending on new developments to NASA missions and stories. Audience: As of December 2021, we have four regularly attending senior living communities, spanning the East Coast from New Hampshire to Florida, with each joining the overall program at various stages of its development. The ability to reach many different senior living communities is crucial so that a diversity of people may benefit from this program. The audience consists of seniors with varying experience and comprehension levels – some are very familiar with the sciences while others are simply curious to learn more. Residents tune in to each event from their individual rooms or from their larger community rooms. RiverWoods Exeter. The RiverWoods Exeter community was our initial audience who acted as our “guinea pig” to see how this program might be implemented and to work out any major issues. They are located in Exeter, NH but also have two additional campuses in Durham, NH and Manchester, NH, that joined us a few months into the program. Culpepper Garden. Our second community to join the program was Culpepper Garden, a senior living community in Arlington, VA that provides both independent and assisted living housing to low-income seniors. Edinburgh Square. Our third community, Edinburgh Square, connected with us after hearing about the program through Culpepper Garden. Edinburgh Square is an HUD-subsidized retirement community in Roanoke, VA that houses both seniors and those living with disabilities. Moonstruck Astronomy Club. The Moonstruck Astronomy Club consists of residents from the On Top of the World retirement community in Ocala, FL and was the latest senior living community to join us. NASA Zoom Webinar: An Evening with NASA Scientists and Engineers reaches numerous senior living communities through live presentations that we host using the NASA Zoom Webinar virtual platform. Participants are typically already familiar with the Zoom platform which enables a lower barrier to entry. A recording of each talk is added to a designated video playlist on the NASA STEM YouTube channel so that audiences worldwide may view them [1]. These recordings began with our April 1, 2021 presentation, as this was when NASA Zoom Webinar was implemented, thus enabling us to record each talk. Metrics: We record attendance numbers from the senior living communities for each event as well as those from YouTube views after the presentation recording is posted online. Depending on which communities tune in, typical attendance numbers are between 60-100 people. RiverWoods Exeter has the most regularly attending residents, with an average of 55 attendees per event. As of December 2021, we have hosted fourteen events, nine of which were recorded and posted to our designated NASA STEM YouTube Channel playlist. The nine recordings combined have roughly 4,000 YouTube views thus far, with specific videos seeing higher view counts around launch dates (e.g. NASA’s DART mission) and trending topics (e.g. JWST). A list of speakers, topics, and links to presentation recordings is shown in Table 1. Future Program Expansion: Thus far, we have been adding communities on an individual basis. To make this process more streamlined, we are looking into working with senior living community networks and organizations such as LeadingAge [2]. In this manner, we will be able to reach more communities while also making it easier to send and receive relevant information.

S L Tiedeken↗
NASA NTRSDate not supplied

Employing NASA Earth Observations and Socioeconomic Data to Conduct Site Suitability Analyses on Residential Tree Planting Initiatives in Phoenix, Arizona

Phoenix, Arizona is the hottest large city in the United States with an average summer daytime temperature of 106°F. Temperatures in Phoenix continue to climb due to increasing global greenhouse gas concentrations and regional urbanization. The impacts of high temperatures, including heat-related illnesses and deaths, are disproportionately concentrated in low-income neighborhoods often characterized by little tree canopy, lack of green space, and insufficient access to shade. The City of Phoenix’s Office of Heat Response and Mitigation and Arizona State University’s Urban Climate Research Center, partnered with NASA DEVELOP to identify residential neighborhoods and parcels within qualified census tracts (QCTs) to be prioritized for tree planting initiatives using funding from the American Rescue Plan Act (ARPA). This project conducted analyses using NASA Earth observations, socioeconomic data from the 2019 American Community Survey, and local tree canopy and mobility data. For Earth observations, daytime land surface temperature, vegetation, and land cover were obtained from the Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI). The project team incorporated these data into a heat vulnerability index (HVI) with an emphasis on tree canopy and social vulnerability to rank block groups within QCTs and focused on the resulting top 25 block group HVI scores. These top 25 most vulnerable block groups were then processed through a parcel analysis to determine the feasibility of residential tree planting based on building footprints on each parcel. Within the top 25 block groups, 2,411 parcels were analyzed, and 3,133 existing trees were identified averaging 1.3 trees per parcel with 90% of parcels having 3 trees or less. Homes with 2 trees or fewer were considered high priority for future planting efforts. Based on the City’s goals for increased tree canopy the project team determined that <10,000 additional trees would need to be planted within the most vulnerable 25 block groups. The project findings have helped initiate community engagement efforts and have contributed to the approval of tree planting funds in Phoenix.

Ryan Hammock↗
NASA NTRS2023

Portland Urban Development: Quantifying and Visualizing Urban Heat with Compounding Vulnerabilities to Support Community Depaving Initiatives

Urban heat is a pressing concern in Portland, Oregon as climate change induced heat waves increase. Cities experience higher temperatures due to the urban heat island effect (UHI), and environmental injustice and disenfranchisement in minority communities expose low-income and Black, Indigenous, and People of Color (BIPOC) residents to more extreme and debilitating heat events. Our team identified Portland’s communities on the frontlines of urban heat impacts by overlapping environmental and social vulnerabilities using NASA Earth observations. We partnered with Depave, a Portland-based nonprofit that works alongside communities to replace pavement with greenspace in historically disenfranchised areas. Using Landsat 8 Thermal Infrared Sensor (TIRS) imagery, we mapped Land Surface Temperature (LST) and developed a heat-specific Social Vulnerability Index (SVI) through a Principal Component Analysis (PCA) to identify Portland’s communities with the highest potential heat vulnerability. Then, we calculated the temperature change of depaving in six case studies to quantify Depave's efforts in heat mitigation and environmental justice. Our analysis demonstrated that, throughout Portland, there are frontline communities experiencing high potential social vulnerability to extreme temperatures due to environmental injustices and over-pavement. Finally, Depave’s impact on urban heat is observable and quantifiable using remote-sensing data and tools, with an average of 1ºF LST decrease across the six case studies. We illustrated the significance of local urban heat mitigation efforts and propose next steps for conducting inclusive and intentional research that highlights the lived experiences and resilience of frontline communities.

Environmental justice↗
NASA NTRS2023

An Urban Drainage Scheme for Large-Scale Flood Models

As flood modeling spatial resolutions get finer, physical processes normally neglected, such as urban drainage, must be accounted for. Here, we describe and evaluate an urban drainage scheme for large-scale flood models. The parameterization accounts for urban imperviousness, and water flow over streets and through a prescribed urban drainage network. A parameter sensitivity analysis is performed during three major extreme floods over Rio de Janeiro city, Brazil, at ∼200 m spatial resolution. Results show that, compared to a hypothetical case without urban drainage, representing a drainage network decreases urban flooding during selected extreme events across Rio de Janeiro by 31–53 %. Such a decrease is caused by an underground water storage of up to 2.5 billion m3 across the city during flood peaks. Underground water storage and transport smooth out and delay peak flows by a few hours over major rivers and channels draining the city. Simulations also indicate that the number of residents exposed to flooding drops by 60–80 %, from ∼5 million to 1–2 million, when an urban drainage system is considered during extreme events. Similar proportions are found for social infrastructure (i.e., schools and hospitals) exposed to flooding. Results reveal that racial minority and low-income populations could disproportionally be exposed to extreme floodings across the city. We conclude that representing urban drainage has a substantial impact on flood exposure and should be accounted for in fine resolution modeling. The proposed scheme is particularly useful in poorly monitored cities and where extreme floods are a frequent hazard yet to be tackled.

Urban drainage↗
NASA NTRS2024

Quantifying Food Security and Mitigation Risks Consequential to Climate Change Impacts on Crop Yields

Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the Integrated Model to Assess the Global Environment integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as agriculture, forestry and other land use emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.

crop yields↗
NASA NTRS2021

Grain export restrictions during COVID-19 risk food insecurity in many low and middle income countries

Global food security is threatened by the effects of COVID-19 on international agricultural supply chains and locusts destroying crops and livelihoods in the Horn of Africa and South Asia. We quantify the possible impacts on global supplies and prices of wheat, rice and maize. We show that local production declines have moderate impacts on global prices and supply – but trade restrictions and precautionary purchases by a few key actors could create global food price spikes and severe local food shortages.

Grain export restrictions↗
NASA NTRS1978

A New Look For Greenbelt

Greenbelt, Maryland, 12 miles from the nation's capital, is an efficiently planned model town and most of its 1600 homes are almost identical in appearance. Four of them, however, stand out from their neighbors; they have distinctive blue glass rooftop superstructures made up of a series of solar collectors. They are part of a NASA community aid program, a joint energy research project involving the Greenbelt housing cooperative and NASA's Goddard Space Flight Center, located near the community. Built in 1935, Greenbelt is one of three government-planned communities of President Franklin D. Roosevelt's first administration; the others are Greendale, Wisconsin and Greenhills, Ohio. The government built the towns to make available low-cost housing, provide employment for workers on relief in the Great Depression era, and to establish models designed to encourage construction of similar developments by private industry. In 1952, the residents of Greenbelt formed a nonprofit cooperative called Greenbelt Homes, Inc., which bought the dwellings, facilities and a large part of the land from the government. The homes are individually owned but collectively maintained by the co-op, with each owner paying a prorated share of utility and maintenance costs. Greenbelt residents are mostly in the low and medium income brackets, and one of every three families lives on a fixed retirement income. For that reason, the sharp escalation of fuel oil prices that began in 1973 imposed particular hardship on the co-op community. So Greenbelt Homes' management asked its NASA neighbor, Goddard Space Flight Center, for assistance in setting up a solar energy research project. The idea was to conduct a small scale demonstration to show what savings could be realized by solar heating Greenbelt homes, with an eye toward possible future expansion of solar energy systems as a means of combating rising fuel costs. Goddard undertook the project as part of the federal government's effort to research and demonstrate ways of conserving energy. The Center was well qualified for the assignment, having acquired extensive expertise in designing thermal control systems for satellites, which must maintain stable temperatures for successful operation.

Source record↗
NASA NTRS1989

Separation shock motion in fin, cylinder, and compression ramp - Induced turbulent interactions

In conjunction with new experimental results at Mach 5, an examination has been made of published data on unsteadiness of shock-induced turbulent boundary-layer separation. The data are all wall pressure fluctuation measurements made under the unsteady separation shock and are from interactions induced by compression ramps, blunt and sharp fins, and circular cylinders. There is little evidence of a link between the separation shock zero-crossing frequency and characteristic frequency of the incoming boundary layer. The low shock frequencies and low shock speeds, and the trends with changes in model geometric parameters and incoming boundary layer, suggest that turbulent or global fluctuations at the upstream boundary of the separated flow drive the shock motion.

Dolling, D. S.↗
NASA NTRS2021

Reductions in NO2 Burden Over North Equatorial Africa from Decline in Biomass Burning in Spite of Growing Fossil Fuel Use, 2005 to 2017

Socioeconomic development in low- and middle-income countries has been accompanied by increased emissions of air pollutants, such as nitrogen oxides [NOx: nitrogen dioxide (NO2) + nitric oxide (NO)], which affect human health. In sub-Saharan Africa, fossil fuel combustion has nearly doubled since 2000. At the same time, landscape biomass burning—another important NOx source—has declined in north equatorial Africa, attributed to changes in climate and anthropogenic fire management. Here, we use satellite observations of tropospheric NO2 vertical column densities (VCDs) and burned area to identify NO2 trends and drivers over Africa. Across the northern ecosystems where biomass burning occurs—home to hundreds of millions of people—mean annual tropospheric NO2 VCDs decreased by 4.5% from 2005 through 2017 during the dry season of November through February. Reductions in burned area explained the majority of variation in NO2 VCDs, though changes in fossil fuel emissions also explained some variation. Over Africa’s biomass burning regions, raising mean GDP density (USD·km−2) above its lowest levels is associated with lower NO2 VCDs during the dry season, suggesting that economic development mitigates net NO2 emissions during these highly polluted months. In contrast to the traditional notion that socioeconomic development increases air pollutant concentrations in low- and middle-income nations, our results suggest that countries in Africa’s northern biomass-burning region are following a different pathway during the fire season, resulting in potential air quality benefits. However, these benefits may be lost with increasing fossil fuel use and are absent during the rainy season.

air pollution↗
NASA NTRSDate not supplied

Biomass burning declines lead to large net reductions in NO2 concentrations over north equatorial Africa in spite of growing fossil fuel emissions

Socio-economic development in low and middle-income countries has been accompanied by increased emissions of air pollutants such as nitrogen oxides (NOx: nitrogen dioxide (NO2) + nitric oxide (NO)), which affect human health. In sub-Saharan Africa, fossil fuel combustion has nearly doubled since 2000. At the same time, biomass burning—another important NOx source—has declined in Africa’s northern biomass burning region, attributed to changes in climate and anthropogenic fire management associated with agricultural development. Here we use satellite observations of tropospheric NO2 vertical column densities (VCDs) and burned area to identify NO2 trends and drivers over Africa. Across the northern ecosystems where biomass burning occurs—home to over 350 million people—mean annual tropospheric NO2 VCDs decreased by 4.5% from 2005 through 2017 during the biomass burning season of November through February. Reductions in burned area explained the majority of these change in NO2 VCDs, but there were also weaker relationships between changes in NO2 VCDs and fossil fuel emissions over parts of West Africa, which were stronger during rainy season. Over Africa’s biomass burning regions, NO2 VCDs tended to decrease with increasing population density up to a threshold of approximately 180 people per km2, suggesting that anthropogenic activity causes a net reduction in NO2 emissions across roughly 90% of the continent’s biomass burning regions. In contrast to the widely-held perception that socio-economic development worsens air quality in low and middle-income nations, our results suggest that countries in Africa’s northern biomass burning region are following a different pathway, resulting in regional air quality benefits. However, these benefits may be lost with increasing fossil fuel use.

Biomass burning↗
NASA NTRS2024

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity↗
NASA NTRS2021

From Low-Cost Sensors to High-Quality Data: A Review of Challenges and Summary of Best Practices for Effectively Using Low-Cost Particulate Matter Mass Sensors

Low-cost sensors for particulate matter mass (PM) enable spatially dense, high temporal resolution measurements of air quality that traditional reference monitoring cannot. Low-cost PM sensors are especially beneficial in low and middle-income countries where few, if any, reference grade measurements exist and in areas where the concentration fields of air pollutants have significant spatial gradients. Unfortunately, low-cost PM sensors also come with a number of challenges that must be addressed if their data products are to be used for anything more than a qualitative characterization of air quality. The various PM sensors used in low-cost monitors are all subject to biases and calibration dependencies, corrections for which range from relatively straightforward(e.g. meteorology, age of sensor) to complex (e.g. aerosol source, composition, refractive index). The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.

low-cost sensors↗