Long-term Population Exposure Research Articles

Fine particulate matter air pollution and health implications for Nairobi, Kenya

Background: Continuous ambient air quality monitoring in Kenya has been limited, resulting in a sparse data base on the health impacts of air pollution for the country. We have operated a centrally located monitor in Nairobi for measuring fine particulate matter (PM2.5), the pollutant that has demonstrated impact on health. Here, we describe the temporal levels and trends in PM2.5 data for Nairobi and evaluate associated health implications. Methods: We used a centrally located reference sensor, the beta attenuation monitor (BAM-1022), to measure hourly PM2.5 concentrations over a 3-year period (21 August 2019 to 20 August 2022). We used, at minimum, 75% of the daily hourly concentration to represent the 24-hour concentrations for a given calendar day. To estimate the deaths attributable to air pollution, we used the World Health Organization (WHO) AirQ+ tool with input as PM2.5 concentration data, local mortality statistics, and population sizes. Results: The daily (24-hour) mean (±SEM) PM2.5 concentration was 19. 2 ± 0.6 (µg/m3). Pollutant levels were lowest at 03:00 and, peaked at 20:00. Sundays had the lowest daily concentrations, which increased on Mondays and remained high through Saturdays. By season, the pollutant concentrations were lowest in April and highest in August. The mean annual concentration was 18.4 ± 7.1 (µg/m3), which was estimated to lead to between 400 and 1,400 premature deaths of the city’s population in 2021 hence contributing 5%–8% of the 17,432 adult deaths excluding accidents when referenced to WHO recommended 2021 air quality guideline for annual thresholds of 5 µg/m3. Conclusion: Fine particulate matter air pollution in Nairobi showed daily, day-of-week, and seasonal fluctuations consistent with the anthropogenic source mix, particularly from motor vehicles. The long-term population exposure to PM2.5 was 3.7 times higher than the WHO annual guideline of 5 µg/m3 and estimated to lead to a substantial burden of attributable deaths. An updated regulation targeting measures to reduce vehicular emissions is recommended.

Tracking long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China 2015–2021

China has experienced severe air pollution in the past decade, especially PM2.5 and emerging ozone pollution recently. In this study, we comprehensively analyzed long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China during 2015–2021 regarding two-stage clean-air actions based on the Ministry of Ecology and the Environment (MEE) air monitoring network. Overall, the ratio of the population living in the regions exceeding the Chinese National Ambient Air Quality Standard (35 μg/m3) decreases by 29.9 % for PM2.5 from 2015 to 2021, driven by high proportions in the Middle Plain (MP, 42.3 %) and Lan-Xi (35.0 %) regions. However, this ratio almost remains unchanged for ozone and even increases by 1.5 % in the MP region. As expected, the improved air quality leads to 234.7 × 103 avoided premature mortality (ΔMort), mainly ascribed to the reduction in PM2.5 concentration. COVID-19 pandemic may influence the annual variation of PM2.5-related ΔMort as it affects the shape of the population exposure curve to become much steeper. Although all eleven urban agglomerations share stroke (43.6 %) and ischaemic heart disease (IHD, 30.1 %) as the two largest contributors to total ΔMort, cause-specific ΔMort is highly regional heterogeneous, in which ozone-related ΔMort is significantly higher (21 %) in the Tibet region than other urban agglomeration. Despite ozone-related ΔMort being one order of magnitude lower than PM2.5-related ΔMort from 2015 to 2021, ozone-related ΔMort is predicted to increase in major urban agglomerations initially along with a continuous decline for PM2.5-related ΔMort from 2020 to 2060, highlighting the importance of ozone control. Coordinated controls of PM2.5 and O3 are warranted for reducing health burdens in China during achieving carbon neutrality.

Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach

Operational forecasting systems based on chemical transport models (CTMs) nowadays generally produce concentration maps with a resolution in the order of 2–5 km, very rarely exceeding the sub-kilometre scale. The main reason for this restriction is the prohibitive computing cost that a simulation covering an entire country would have if set-up with a resolution in the order of meters. In this paper a hybrid forecast system, relying on the WRF-Chem model coupled with the PMSS Lagrangian modelling suite, has been developed and applied for each day of February 2019, to predict hourly NO2 and NOx concentrations with a spatial resolution of 4 m, for the urban area of Modena (a city located in the central Po Valley). Simulated meteorological fields (temperature, wind speed and direction) were assessed at three urban stations, compliant with WMO standards, and modelled concentrations were compared with measurements at two urban air quality stations located at background and traffic sites.Results show that meteorological variables are well captured by the hybrid system and statistical performances are in line with the benchmark values suggested by the European Environmental Agency and with similar case studies focusing on the same area. Modelled NO2 and NOx concentrations, notwithstanding a slight underestimation mainly evident at urban traffic stations for NOx, present a large agreement with related observations. The NO2 Model Quality Objective, as defined by Fairmode guidelines, was met for both the urban stations and the other statistical indexes considered in the evaluation fulfilled the acceptance criteria for dispersion modelling in urban environment, for both NO2 and NOx concentrations.In the second section of the study, the population exposure to forecasted NO2 concentrations has been evaluated adopting a generic model of dynamic population activity. The population was distributed at hourly time steps in specific urban micro-environments at the same resolution of the concentration maps (4 m) and the short-term exposure has been computed as the product between the population density in each model cell and related surface NO2 concentrations. An infiltration factor was also applied to estimate indoor concentrations. The hybrid system was shown to be particularly suited for assessing short-term peak exposure in areas influenced by traffic emissions. On the other hand, due to the limited time spent by the population within traffic related environments, the long-term population exposure calculated by the hybrid system tends to be similar to the WRF-Chem stand-alone estimate.

Spatiotemporal variability in long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across the Yangtze River Delta (YRD) region over 2010–2016: A multistage approach

The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across YRD during 2010–2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R2 and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9–8 times higher than the other major cities (7-year average: 192,000 μg·people/m3·km2). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%–33% higher than in low-risk areas. There were 12,574–14,504 total lung cancer deaths attributable to PM2.5, and lung cancer deaths in each square kilometer of urban areas were 7–13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment.

Impacts of climate change, population growth, and urbanization on future population exposure to long-term temperature change during the warm season in China.

Climate change is anticipated to raise overall temperatures in the twenty-first century and is likely to intensify population exposure to heat during the warm season and, as a result, increase the risk of heat-related illnesses and deaths. While earlier studies of heat exposure and related health impacts generally focused on the acute effects of short-term exposure indicated by high daily temperature or several days of very hot weather, recent research has suggested that small changes in seasonal average temperature over a long period of time is likely to pose significant health risk as well. Using downscaled climate projections under three Representative Concentration Pathways emission scenarios, high-spatial-resolution population data, and the latest population projections by the United Nations, we aim at projecting future changes in long-term population exposure to summer heat across China in the mid- and late-twenty-first century resulting from global climate change. As the impacts of population growth are often overlooked in projecting future changes in heat exposure, we estimated changes in population-weighted average temperature in the warmest quarter over two future 20-year time periods and compared them with changes in temperature only. Our analysis shows that, nationally, population-weighted average temperature in the warmest quarter is projected to increase by 2.2°C relative to the current situation in the 2050s and by 2.5°C in the 2070s, as the result of climate change and population growth. Despite the foreseeable population stabilization in China, changes in population-weighted temperature are projected to be higher than changes in temperature itself for the majority of the 33 provinces (ranging from 0.02°C to 1.27°C, or 1% to 126% higher in the 2050s and from 0.02°C to 1.16°C, or 1% to 73% higher in the 2070s), with the largest differences mainly occurring in Western China. The impact of urbanization is projected to be relatively insignificant. Our findings provide evidence of possible underestimation of future changes in long-term exposure to summer heat if the effect of population growth is not factored in.

Estimation of long-term population exposure to PM2.5 for dense urban areas using 1-km MODIS data

Abstract The lack of long-term PM 2.5 measurements in developing countries makes it difficult to quantify the overall PM 2.5 pollution exposures and health impacts in these countries where the PM 2.5 concentrations are often very high. Moreover, it is also difficult for traditional fixed-site monitoring to capture the substantial spatial variability of PM 2.5 over dense urban areas or regions with significant topography. Hence, recent developments in satellite-based remote-sensing allowing the reconstruction of long-term, wide-area and high-resolution estimates of current and historical PM 2.5 concentration is an important step forward, allowing the quantification of the long-term pollution exposure of PM 2.5 in developing cities and in dense urban areas using the satellite-derived PM 2.5 data. In this study, instead of just looking at the spatial average PM 2.5 concentrations, we have studied the long-term population exposure of PM 2.5 by analyzing the population-weighted PM 2.5 concentrations at regional, city and district scales by combining 1 km × 1 km satellite-derived PM 2.5 and population density data sets. The variation of population exposure to PM 2.5 across the urban areas in the Pearl River Delta (PRD) region from 2000 to 2014 was studied. Our result shows that the PM 2.5 concentrations over the PRD increased steadily from 2000 to 2004, remained at quite a high level through 2008 and then started to decline after 2009. More importantly, our analysis also shows that, at regional, city and district levels, the population-weighted mean PM 2.5 concentrations from data with 1 km resolutions are typically the highest, followed by the population-weighted mean PM 2.5 concentrations from data with 10 km resolutions and then the simple spatial PM 2.5 averages. This suggests that the use of simple spatial concentrations can lead to systematic underestimation of the overall population exposure and the associated health impacts. This systematic difference is related to the positive correlation between PM 2.5 pollutant concentration and population density, and shows the usefulness of using high-resolution satellite-retrieved PM 2.5 concentrations to quantify the overall population exposure. The higher population-weighted mean PM 2.5 concentration in comparison with simple spatial average indicates that, for more effective reduction of overall population exposure and protection of public health, control efforts must be further targeted at high-population high-pollution areas, and land-use and city planning should also encourage population to redistribute away from the highly polluted areas.

Characterizing the Long-Term PM2.5 Concentration-Response Function: Comparing the Strengths and Weaknesses of Research Synthesis Approaches.

The magnitude, shape, and degree of certainty in the association between long-term population exposure to ambient fine particulate matter (PM2.5 ) and the risk of premature death is one of the most intensely studied issues in environmental health. For regulatory risk analysis, this relationship is described quantitatively by a concentration-response (C-R) function that relates exposure to ambient concentrations with the risk of premature mortality. Four data synthesis techniques develop the basis for, and derive, this function: systematic review, expert judgment elicitation, quantitative meta-analysis, and integrated exposure-response (IER) assessment. As part of an academic workshop aiming to guide the use of research synthesis approaches, we developed criteria with which to evaluate and select among the approaches for their ability to inform policy choices. These criteria include the quality and extent of scientific support for the method, its transparency and verifiability, its suitability to the policy problem, and the time and resources required for its application. We find that these research methods are both complementary and interdependent. A systematic review of the multidisciplinary evidence is a starting point for all methods, providing the broad conceptual basis for the nature, plausibility, and strength of the associations between PM exposure and adverse health effects. Further, for a data-rich application like PM2.5 and premature mortality, all three quantitative approaches can produce estimates that are suitable for regulatory and benefit analysis. However, when fewer data are available, more resource-intensive approaches such as expert elicitation may be more important for understanding what scientists know, where they agree or disagree, and what they believe to be the most important areas of uncertainty. Whether implicitly or explicitly, all require considerable judgment by scientists. Finding ways for all these methods to acknowledge, appropriately elicit, and examine the implications of that judgment would be an important step forward for research synthesis.

Air pollution and early deaths in the United States. Part I: Quantifying the impact of major sectors in 2005

Combustion emissions adversely impact air quality and human health. A multiscale air quality model is applied to assess the health impacts of major emissions sectors in United States. Emissions are classified according to six different sources: electric power generation, industry, commercial and residential sources, road transportation, marine transportation and rail transportation. Epidemiological evidence is used to relate long-term population exposure to sector-induced changes in the concentrations of PM2.5 and ozone to incidences of premature death. Total combustion emissions in the U.S. account for about 200,000 (90% CI: 90,000–362,000) premature deaths per year in the U.S. due to changes in PM2.5 concentrations, and about 10,000 (90% CI: −1000 to 21,000) deaths due to changes in ozone concentrations. The largest contributors for both pollutant-related mortalities are road transportation, causing ∼53,000 (90% CI: 24,000–95,000) PM2.5-related deaths and ∼5000 (90% CI: −900 to 11,000) ozone-related early deaths per year, and power generation, causing ∼52,000 (90% CI: 23,000–94,000) PM2.5-related and ∼2000 (90% CI: −300 to 4000) ozone-related premature mortalities per year. Industrial emissions contribute to ∼41,000 (90% CI: 18,000–74,000) early deaths from PM2.5 and ∼2000 (90% CI: 0–4000) early deaths from ozone. The results are indicative of the extent to which policy measures could be undertaken in order to mitigate the impact of specific emissions from different sectors — in particular black carbon emissions from road transportation and sulfur dioxide emissions from power generation.

A tool for determining urban emission characteristics to be used in exposure assessment

The exposure of citizens to elevated air pollution concentrations is one of the major factors leading to the deterioration of the quality of life and possibly to health problems in urban areas. The concentration of air pollutants depends largely on pollutant emission levels. If the statistical probability distribution function of the concentration of an air pollutant is known, it is possible to estimate how many times this concentration exceeds the air quality standards, or estimate changes in the emission levels in an area. It can be also used to estimate the long term exposure of population to certain pollutants. In this paper fifteen theoretical probability distribution functions, were used to fit the actual concentration frequency distributions of CO, NO 2, O 3, SO 2, and Black Smoke (BS) in Athens, Greece for a 23-year period. The results showed that the theoretical distribution type best describing the distribution of the pollutants is Inverse Gaussian followed by the Extreme value distribution. The number of exceedances of air quality limits was used to validate the performance of the theoretical distributions that were best fitted to the observed ones. The temporal evolution of emission strength was estimated through the temporal evolution of the parameters of the probability distribution functions. Missing periods were accounted for by estimating the respective distribution functions through interpolation or extrapolation from the existing ones. The derived variation of emission levels consistently represents the emission reduction strategies enforced over the years, as well as the escalating growth of the passenger car fleet volume, and could be a useful tool for the design and assessment of emission control strategies.

PRELIMINARY OBSERVATIONS ON ENDOCRINE DISRUPTING EFFECTS OF POLYCHLORINATED BIPHENYLS (PCBS) IN THE POPULATION EXPOSED TO HEAVY ENVIRONMENTAL POLLUTION

A chemical factory, Chemko, at Strazske, East Slovakia, produced 21,500 tons PCBs during 1959–1984. Large amounts of PCBs contaminated the environment due to poor technological and preventive measures. Up to 20-times higher PCB levels were found in ambient air samples close to the Chemko landfill site and highly contaminated effluent canal. Some preliminary results of a complex study of PCB health effects are: We examined 1010 adult subjects from the polluted area [PA] and 1040 subjects from control area [CA]. The mean serum level of the sum of PCBs (ng/g, lipid adjusted) in the PA (378 specimens) was 2738 and in CA (1038 specimens) 871. Thyroid volume by ultrasound (mean±SD) was significantly higher in PA (10.77±5.09 ml, 90 % = 16.6 ml) than in CA (8.99±4.11 ml; 90 % 13.3 ml; P < 0.001) and the same was true for free thyroxine [FT4] (2.04±0.37 vs. 1.91±0.37 pmol/L) and total triiodothyronine [TT3] (17.04±3.12 vs. 15.99±2.58 nmol/L). In PA also significantly higher frequency of positive antithyroperoxidase antibodies [anti-TPO] was found in males (52,7 % vs. 7.9 %-P < 0.001) as well as in females (32.0 % vs. 24.5 %-P < 0.001). However, after 4 decades of heavy exposure the average level of thyrotropin and the prevalence of abnormally increased levels (>4.0 mU/L) in both areas was the same which shows a normal thyroid function. It was concluded that, in spite of increased thyroid volume, FT4 and FT3 level and positive anti-TPO frequency, the thyroid function in great majority of exposed subjects was normal, but presumably the set points of individual short and long feedback loops were shifted which resulted in a new final steady state. After a long-term exposure of population presumably only the sequels or remnants a previous long-term process may be found. A total of 478 8–9 years old school children were recruited (119 boys and 116 girls born and living in the PA and 124 boys and 119 girls in the CA). Comparison of performance of psychological tests showed differences between areas in tests of sensomotor reactions, in short memory, and in tests of high mental processes, in favor of CA. Three main types of developmental defects of tooth enamel were recorded in children: demarcated opacities, diffuse opacities, and hypoplasia. Preliminary results showed that the percentage of children with at least one permanent tooth affected by enamel defects was 66% in the PA compared to 55% in the CA group. After finishing all analyses, for each subject will be available a large amount of data: on various organochiorines serum concentrations and their metabolites, on toxic metals serum concentrations, on thyroid status, cognitive processes, dental status, concentrations, on thyroid status, cognitive processes, dental status, hearing impairment, cytochrome P450 enzymes and xenoestrogenic activities. This will make possible exposure-effect hypothesis testing using multifactorial analysis.

The Long-term Decrease of 90Sr in the Environment and its Transfer to Man after a Nuclear Fallout

Due to its long physical half-life, and the fact that its long-term mobility in the environment as well as its radiotoxicity is higher than that of 137Cs, the long-term bio-availability of 90Sr in the environment is of importance with regard to the long-term population exposure after fallout from nuclear weapons detonations or a severe reactor accident. It will also substantially influence the time-span required until re-utilisation of highly contaminated territory is possible again. An assessment of the long-term decrease of the activity concentration in all foodstuffs relevant for internal exposure after severe 90Sr fallout was performed. The observed effective half-lives were approximately 1.8-2.1 years in the first 2-3 years after the end of fallout and 8-10 years in the following three decades. This is equivalent to a biological half-life of about 13.2 years and results in a total 50 year dose of 6.2 times the first year exposure. Due to this decline in 90Sr-availability, the average annual activity intake of 90Sr in Austria has decreased from 840 Bq at the climax of the nuclear weapons tests to about 42 Bq in 1997 for adults, and from 500 Bq to about 35 Bq for 1 year old infants. This is equivalent to a 90Sr ingestion dose of 1.2 microSv for adults and 2.5 microSv for 1 year old infants in 1997 or less than 0.4% of the ingestion dose by natural radionuclides in the diet.

Estimating long-term population exposure to ozone in urban areas of Europe

Tropospheric ozone concentrations regarded as harmful for human health are frequently encountered in Central Europe in summertime. Although ozone formation generally results from precursors transported over long distances, in urban areas local effects, such as reactions due to nearby emission sources, play a major role in determining ozone concentrations. Europe-wide mapping and modeling of population exposure to high ozone concentrations is subject to many uncertainties, because small-scale phenomena in urban areas can significantly change ozone levels from those of the surroundings. Currently the integrated assessment modeling of European ozone control strategies is done utilizing the results of large-scale models intended for estimating the rural background ozone levels. This paper presents an initial study on how much local nitrogen oxide (NO x ) concentrations can explain variations between large-scale ozone model results and urban ozone measurements, on one hand, and between urban and nearby rural measurements, on the other. The impact of urban NO x concentrations on ozone levels was derived from chemical equations describing the ozone balance. The study investigated the applicability of the method for improving the accuracy of modeled population exposure, which is needed for efficient control strategy development. The method was tested with NO x and ozone measurements from both urban and rural areas in Switzerland and with the ozone predictions of the large-scale photochemical model currently used in designing Europe-wide control strategies for ground-level ozone. The results suggest that urban NO x levels are a significant explanatory factor in differences between urban and nearby rural ozone concentrations and that the phenomenon could be satisfactorily represented with this kind of method. Further research efforts should comprise testing of the method in more locations and analyzing the performance of more widely applicable ways of deriving the initial parameters.

Joint proposal to ban nuclear power in Earth orbit

The lack of long-term PM2.5 measurements in developing countries makes it difficult to quantify the overall PM2.5 pollution exposures and health impacts in these countries where the PM2.5 concentrations are often very high. Moreover, it is also difficult for traditional fixed-site monitoring to capture the substantial spatial variability of PM2.5 over dense urban areas or regions with significant topography. Hence, recent developments in satellite-based remote-sensing allowing the reconstruction of long-term, wide-area and high-resolution estimates of current and historical PM2.5 concentration is an important step forward, allowing the quantification of the long-term pollution exposure of PM2.5 in developing cities and in dense urban areas using the satellite-derived PM2.5 data. In this study, instead of just looking at the spatial average PM2.5 concentrations, we have studied the long-term population exposure of PM2.5 by analyzing the population-weighted PM2.5 concentrations at regional, city and district scales by combining 1 km × 1 km satellite-derived PM2.5 and population density data sets. The variation of population exposure to PM2.5 across the urban areas in the Pearl River Delta (PRD) region from 2000 to 2014 was studied. Our result shows that the PM2.5 concentrations over the PRD increased steadily from 2000 to 2004, remained at quite a high level through 2008 and then started to decline after 2009. More importantly, our analysis also shows that, at regional, city and district levels, the population-weighted mean PM2.5 concentrations from data with 1 km resolutions are typically the highest, followed by the population-weighted mean PM2.5 concentrations from data with 10 km resolutions and then the simple spatial PM2.5 averages. This suggests that the use of simple spatial concentrations can lead to systematic underestimation of the overall population exposure and the associated health impacts. This systematic difference is related to the positive correlation between PM2.5 pollutant concentration and population density, and shows the usefulness of using high-resolution satellite-retrieved PM2.5 concentrations to quantify the overall population exposure. The higher population-weighted mean PM2.5 concentration in comparison with simple spatial average indicates that, for more effective reduction of overall population exposure and protection of public health, control efforts must be further targeted at high-population high-pollution areas, and land-use and city planning should also encourage population to redistribute away from the highly polluted areas.