Transboundary and traffic influences on air pollution across two Caribbean islands

Temporal trends in ambient fine particulate matter and the impacts of COVID-19 on this pollutant in Grenada, West Indies

Most Caribbean islands do not have air pollution surveillance programs. Those who live in these countries are exposed to ambient air pollution from a variety of sources including motor vehicles, ocean-going vessels, and Saharan dust. We conducted an air sampling exposure study in Grenada to describe daily changes in fine particulate matter (PM_2.5) pollution, and during Saharan dust episodes. Further, we assessed the impacts of COVID-19 public health interventions on PM_2.5 concentrations in 2020. Four fixed-site PurpleAir monitors were installed throughout Grenada, and one on the neighboring island of Carriacou. PM_2.5 was measured between January 6 and December 31, 2020. We classified each of these days based on whether COVID-19 public health mitigation measures were in place or not. Descriptive analyses were performed to characterize fluctuations in PM_2.5, and we assessed the impacts of public health restrictions on PM_2.5 using multivariate regression. The mean daily PM_2.5 concentration in 2020 was 4.4 μg/m³. During the study period, the minimum daily PM_2.5 concentration was 0.7 μg/m³, and the maximum was 20.4 μg/m³. Daily mean PM_2.5 concentrations more than doubled on Saharan dust days (8.5 vs 3.6 μg/m³; p < 0.05). The daily mean PM_2.5 concentrations were estimated to be 1.2 μg/m³ lower when COVID-19 restrictions were in effect. Ambient PM_2.5 concentrations in Grenada are relatively low compared to other countries; however, Saharan dust episodes represent an important source of exposure. Low-cost sensors provide an opportunity to increase surveillance of air pollution in the Caribbean, however their value could be enhanced with the development of correction algorithms that more closely approximate values from reference-grade monitors.Implications: This study describes daily fluctuations in ambient PM_2.5 concentrations in Grenada in 2020. Overall, concentrations of PM_2.5 were low; however, we found that Saharan dust events cause daily exceedances in PM_2.5 above the current 24-hr limits of the World Health Organization. Moreover, the constructed models suggest that public health interventions to reduce the spread of COVID-19 reduced PM_2.5 concentrations by 27%.

Analysis of the air quality in upper atmospheric boundary layer in a high-density city in Asia using 3-year vertical profiles measured by the 3-Dimensional Real-Time Atmospheric Monitoring System (3DREAMS)

Past studies focused on ground-level air quality, whereas air quality in upper atmospheric boundary layer (ABL) remains unclear due to lack of long-term and high time-resolution profile data. This study utilized the 3-Dimensional Real-Time Atmospheric Monitoring System (3DREAMS) to provide vertical profiles of aerosol backscatter coefficients and wind for three years (2019-2021), along with DustTrak to describe and analyze the characteristics of aerosols in the upper ABL in a high-density city in Asia (Hong Kong, China). It is the first study to assess the long-term record and spatial variations of upper-level aerosol in a high-density city using a LiDAR network. Results show an opposite diurnal profile of aerosol comparing between ground-level and upper ABL, which is different with the diurnal pattern observed in ground measurements (higher air pollutant concentration level in daytime and lower in nighttime). The co-location vertical wind measurements provided the explanation of the opposite diurnal patterns. The 3-year vertical profiles also show the significant spatial variation of vertical distribution of aerosol at different locations, whereas the temporal variations can be affected by various factors such as emissions and transboundary air pollution. Our episode analysis clearly demonstrated the capability of 3DREAMS to monitor transboundary air pollution with detailed information of horizontal transport and vertical convection. 3DREAMS is therefore proved as a suitable system for transboundary air pollution monitoring. Our findings provide a critical reference for atmospheric scientists and decisionmakers to understand transboundary air pollution.

Influence of Climatic Factors on Human Hantavirus Infections in Latin America and the Caribbean: A Systematic Review

BACKGROUND

With the current climate change crisis and its influence on infectious disease transmission there is an increased desire to understand its impact on infectious diseases globally. Hantaviruses are found worldwide, causing infectious diseases such as haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS)/hantavirus pulmonary syndrome (HPS) in tropical regions such as Latin America and the Caribbean (LAC). These regions are inherently vulnerable to climate change impacts, infectious disease outbreaks and natural disasters. Hantaviruses are zoonotic viruses present in multiple rodent hosts resident in Neotropical ecosystems within LAC and are involved in hantavirus transmission.

METHODS

We conducted a systematic review to assess the association of climatic factors with human hantavirus infections in the LAC region. Literature searches were conducted on MEDLINE and Web of Science databases for published studies according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) criteria. The inclusion criteria included at least eight human hantavirus cases, at least one climatic factor and study from > 1 LAC geographical location.

RESULTS

In total, 383 papers were identified within the search criteria, but 13 studies met the inclusion criteria ranging from Brazil, Chile, Argentina, Bolivia and Panama in Latin America and a single study from Barbados in the Caribbean. Multiple mathematical models were utilized in the selected studies with varying power to generate robust risk and case estimates of human hantavirus infections linked to climatic factors. Strong evidence of hantavirus disease association with precipitation and habitat type factors were observed, but mixed evidence was observed for temperature and humidity.

CONCLUSIONS

The interaction of climate and hantavirus diseases in LAC is likely complex due to the unknown identity of all vertebrate host reservoirs, circulation of multiple hantavirus strains, agricultural practices, climatic changes and challenged public health systems. There is an increasing need for more detailed systematic research on the influence of climate and other co-related social, abiotic, and biotic factors on infectious diseases in LAC to understand the complexity of vector-borne disease transmission in the Neotropics.

Mobile monitoring and spatial prediction of black carbon in Cairo, Egypt

This study harnesses the power of mobile data in developing a spatial model for predicting black carbon (BC) concentrations within one of the most heavily populated regions in the Middle East and North Africa MENA region, Greater Cairo Region (GCR) in Egypt. A mobile data collection campaign was conducted in GCR to collect BC measurements along specific travel routes. In total, 3,300 km were travelled across a widespread 525 km of routes. Reported average BC values were around 20 µg/m³, announcing an alarming order of magnitude value when compared to the maximum reported values in similar studies. A bi-directional stepwise land use regression (LUR) model was developed to select the best combination of explanatory variables and generate an exposure surface for BC, in addition to a number of machine learning models (random forest gradient boost, light gradient boost model (LightGBM), Keras neural network (NN)). Data from 7 air quality (AQ) stations were compared-in terms of mean square error (MSE) and mean absolute error (MAE)-with predictions from the LUR and the NN model. The NN model estimated higher BC concentrations in the downtown areas, while lower concentrations are estimated for the peripheral area at the east side of the city. Such results shed light on the credibility of the LUR models in generating a general spatial trend of BC concentrations while the superiority of NN in BC accuracy estimation (0.023 vs 0.241 in terms of MSE and 0.12 vs 0.389 in terms of MAE; of NN vs LUR respectively).

Long-range air pollution transport in East Asia during the first week of the COVID-19 lockdown in China

Long-range transport (LRT) of air pollutants from East Asia during the northeast monsoon season impacts several downwind locations. In 2020, the initial COVID-19 lockdowns in China overlapped with Week 3 of the Chinese New Year (CNY) holiday, and an Asian outflow event. Thus, movement of the Chinese populace from city to city was already greatly reduced by the time of the LRT episode, although the reductions in industrial output are less clear. We found NO₂ column concentrations were reduced by 24% during the CNY Week 3 this year compared to previous years. The attenuated transport event arrived to northern Taiwan with a PM_2.5 concentration <45 μg m^-3 and most often <35 μg m^-3, which is 2-3 times lower than LRT episodes of similar back-trajectory and synoptic patterns. The whole episode persisted for about 60 h, longer than most LRT episodes from China to Taiwan. CMAQ v5.2.1 modeling of the LRT event with 100% emission and reduced emission scenarios, revealed emissions in China were approximately 50% less than normal periods. Due to the length of the episode and the significant reduction in emissions, Taiwan avoided a PM_2.5 surplus of 19.2 μg m^-3 on average during the episode, equivalent to a 0.5 μg m^-3 reduction for the whole 3-month winter season. Employing the 100% emission model scenario and scaling up to the average episode hours each winter, the PM_2.5 surplus delivered via plumes on the northeast monsoon is equivalent to a 0.5 μg m^-3 surplus for the whole year.