Analysis of the atmospheric dust in Africa: The breathable dust's fine particulate matter PM2.5 in correlation with carbon monoxide

Rushingabigwi, Gerard; Nsengiyumva, Philibert; Sibomana, Louis; Twizere, Célestin; Kalisa, Wilson

doi:10.1016/j.atmosenv.2020.117319

Cited by 23 publications

(9 citation statements)

References 31 publications

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“…The observed spatial patterns highlight a stark contrast in PM 2.5 concentrations across different regions. This spatial heterogeneity in air pollution is contributed from the complex interplay of environmental factors [40,41], population density [42], and urbanization [9]. Our analyses found a prominent role of population increase in the unprecedented surge in population exposure to extreme PM 2.5 levels (∼460 million).…”

Section: Discussionmentioning

confidence: 62%

Substantial increase in population exposure to multiple environmental burdens in sub-Saharan Africa (2000-2019)

Sikarwar,

Golaz

2024

Environ. Res. Lett.

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In the face of increasing global environmental uncertainties, sub-Saharan Africa stands as a highly vulnerable region with a massive population marked with poverty and inequalities. Moreover, different environmental risk factors can coexist simultaneously as multiple environmental burdens (MEB); however, population exposure to MEB remains unexamined. Here, using open-access spatial data and critical thresholds, we quantify population exposure to four key environmental risk factors: hazardous fine particulate matter (PM2.5) levels, extreme temperature increase, prolonged severe droughts, and green deficit (scarcity of green trees). Further, we explore the concept of MEB, where these risk factors converge. We derive exposure for 2000 and 2019 at the pixel (1 km grid cell) level. We also check how population change, environmental change, and their interaction contribute to the total change in exposure. We found substantial changes in the population exposed from 2000 to 2019, i.e., an increase of ~460 million people to hazardous PM2.5 levels, ~16 million to extreme temperature increase, ~13 million to prolonged severe droughts, and ~246 million to green deficit. Population exposure to at least three of these four environmental risk factors (3EB) has increased by ~246 million. In this increase in exposure to 3EB, the contribution of environmental change is higher (48%), than that of interaction and population change (36% and 15%, respectively). Notably, there are striking disparities in population exposure, its change, and the contributing effects among countries and regions of sub-Saharan Africa.

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Section: Discussionmentioning

confidence: 62%

Substantial increase in population exposure to multiple environmental burdens in sub-Saharan Africa (2000-2019)

Sikarwar,

Golaz

2024

Environ. Res. Lett.

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“…Africa has already paid a lot of economic costs and reside for air pollution. According to a report (Roy, 2016), in 2013, the economic cost lution in Africa was estimated at USD 447 billion, resulting in some 250,000 d As a result, air quality protection and environmental management must be while stimulating economic growth and urban development [62]. Under our r limited economic conditions, some works still remain to be proposed for promo dinated development of urbanization and air quality in Africa:…”

Section: Policy Implicationsmentioning

confidence: 99%

The Driving Influence of Multi-Dimensional Urbanization on PM2.5 Concentrations in Africa: New Evidence from Multi-Source Remote Sensing Data, 2000–2018

Wei

Sun

Jiang

et al. 2021

IJERPH

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Africa’s PM2.5 pollution has become a security hazard, but the understanding of the varying effects of urbanization on driven mechanisms of PM2.5 concentrations under the rapid urbanization remains largely insufficient. Compared with the direct impact, the spillover effect of urbanization on PM2.5 concentrations in adjacent regions was underestimated. Urbanization is highly multi-dimensional phenomenon and previous studies have rarely distinguished the different driving influence and interactions of multi-dimensional urbanization on PM2.5 concentrations in Africa. This study combined grid and administrative units to explore the spatio-temporal change, spatial dependence patterns, and evolution trend of PM2.5 concentrations and multi-dimensional urbanization in Africa. The differential influence and interaction effects of multi-dimensional urbanization on PM2.5 concentrations under Africa’s rapid urbanization was further analyzed. The results show that the positive spatial dependence of PM2.5 concentrations gradually increased over the study period 2000–2018. The areas with PM2.5 concentrations exceeding 35 μg/m3 increased by 2.2%, and 36.78% of the African continent had an increasing trend in Theil–Sen index. Urbanization was found to be the main driving factor causing PM2.5 concentrations changes, and economic urbanization had a stronger influence on air quality than land urbanization or population urbanization. Compared with the direct effect, the spillover effect of urbanization on PM2.5 concentrations in two adjacent regions was stronger, particularly in terms of economic urbanization. The spatial distribution of PM2.5 concentrations resulted from the interaction of multi-dimensional urbanization. The interaction of urbanization of any two different dimensions exhibited a nonlinear enhancement effect on PM2.5 concentrations. Given the differential impact of multi-dimensional urbanization on PM2.5 concentrations inside and outside the region, this research provides support for the cross-regional joint control strategies of air pollution in Africa. The findings also indicate that PM2.5 pollution control should not only focus on urban economic development strategies but should be an optimized integration of multiple mitigation strategies, such as improving residents’ lifestyles, optimizing land spatial structure, and upgrading the industrial structure.

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“…uns* data preprocessing for WRF registry ............................................................................................ 4.4.2 AFWA dust emission code modifications ..................................................................... 5 Clow et al 2016;Al-Hemoud et al 2017;Middleton 2017;Schweitzer et al 2018;Bhattachan et al 2019;Rushingabigwi et al 2020). Also, dust storms degrade visibility, which can double as tactical advantage opportunities for battlespace concealment.…”

Section: Modismentioning

confidence: 99%

Implementation of an albedo-based drag partition into the WRF-Chem v4.1 AFWA dust emission module

Michaels¹,

Letcher²,

LeGrand³

et al. 2021

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Employing numerical prediction models can be a powerful tool for forecasting air quality and visibility hazards related to dust events. However, these numerical models are sensitive to surface conditions. Roughness features (e.g., rocks, vegetation, furrows, etc.) that shelter or attenuate wind flow over the soil surface affect the magnitude and spatial distribution of dust emission. To aide in simulating the emission phase of dust transport, we used a previously published albedo-based drag partition parameterization to better represent the component of wind friction speed affecting the immediate soil sur-face. This report serves as a guide for integrating this parameterization into the Weather Research and Forecasting with Chemistry (WRF-Chem) model. We include the procedure for preprocessing the required input data, as well as the code modifications for the Air Force Weather Agency (AFWA) dust emission module. In addition, we provide an example demonstration of output data from a simulation of a dust event that occurred in the Southwestern United States, which incorporates use of the drag partition.

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Analysis of the atmospheric dust in Africa: The breathable dust's fine particulate matter PM2.5 in correlation with carbon monoxide

Cited by 23 publications

References 31 publications

Substantial increase in population exposure to multiple environmental burdens in sub-Saharan Africa (2000-2019)

Substantial increase in population exposure to multiple environmental burdens in sub-Saharan Africa (2000-2019)

The Driving Influence of Multi-Dimensional Urbanization on PM2.5 Concentrations in Africa: New Evidence from Multi-Source Remote Sensing Data, 2000–2018

Implementation of an albedo-based drag partition into the WRF-Chem v4.1 AFWA dust emission module

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