Long-term exposure to air pollution and COVID-19 incidence: a prospective study of residents in the city of Varese, Northern Italy

ObjectivesTo investigate the association between long-term exposure to airborne pollutants and the incidence of SARS-CoV-2 up to March 2021 in a prospective study of residents in Varese city.MethodsCitizens of Varese aged ≥18 years as of 31 December 2019 were linked by residential address to 2018 average annual exposure to outdoor concentrations of PM2.5, PM10, NO2, NO and ozone modelled using the Flexible Air quality Regional Model (FARM) chemical transport model. Citizens were further linked to regional datasets for COVID-19 case ascertainment (positive nasopharyngeal swab specimens) and to define age, sex, living in a residential care home, population density and comorbidities. We estimated rate ratios and additional numbers of cases per 1 µg/m3 increase in air pollutants from single- and bi-pollutant Poisson regression models.ResultsThe 62 848 residents generated 4408 cases. Yearly average PM2.5 exposure was 12.5 µg/m3. Age, living in a residential care home, history of stroke and medications for diabetes, hypertension and obstructive airway diseases were independently associated with COVID-19. In single-pollutant multivariate models, PM2.5 was associated with a 5.1% increase in the rate of COVID-19 (95% CI 2.7% to 7.5%), corresponding to 294 additional cases per 100 000 person-years. The association was confirmed in bi-pollutant models; excluding subjects in residential care homes; and further adjusting for area-based indicators of socioeconomic level and use of public transportation. Similar findings were observed for PM10, NO2 and NO. Ozone was associated with a 2% decrease in disease rate, the association being reversed in bi-pollutant models.ConclusionsLong-term exposure to low levels of air pollutants, especially PM2.5, increased the incidence of COVID-19. The causality warrants confirmation in future studies; meanwhile, government efforts to further reduce air pollution should continue.

Ozone variation over tropics: Trends revealed from Dobson measurement over Indian stations

. Variations in ozone amounts have been studied using data obtained with Dobson spectrophotometers during 1966-1988 at Srinagar, New Delhi, Pune and Kodaikanal. Yearly average values of total ozone , and its vertical distribution by the Umkehr method in layers 1 to 9 have been computed. Departures from compo- site avarage value for the period (1966-1988) have been computed for both total ozone and its vertical distribution. The variation over New Delhi and Pune have been compared with those at Arosa reported by Dutsch {1989). The observed variations in the ozone distribution at New Delhi and Pune can be explained, as being within normal interannual changes. Tropospheric ozone in layer lover New Delhi shows some effects of an anthropogenic nature, on the other hand Pune does not exhibit in any influence of pollutants in any layer, either in the troposphere or stratosphert.

Analysis of the impact of geographic features, population distribution and power load on heat island effects in the metropolis of Shenzhen

Based on the air temperature data collected from automated weather stations, the urban heat island (UHI) intensity in Shenzhen metropolis is calculated and the impact of several factors, including land-sea distribution, population density, road coverage area and power load, on the UHI intensity are analyzed. The analysis shows that the land-sea distribution is the dominant factor for the UHI distribution in Shenzhen, with the climate-adjusting effect of the sea clearly reducing the UHI intensity in the east and west parts of Shenzhen. The middle part of Shenzhen is adjacent to Hong Kong and the climate-adjusting effect of the sea is weak, which leads to UHI intensity being centered around this area. The population density and road coverage area do impact the UHI in Shenzhen, with strong dependency between the UHI intensity and the two factors (p < 0.01). However, in the area with the densest roads, the UHI intensity is not high, which may be related to the high yearly-average wind speed in this area. Comparing the data from 2011 and 2010 shows strong impact of the power load on the UHI intensity in Shenzhen, and the increase of the UHI intensity in 2011 is highly likely to be due to the increase of the power load in the colder winter and the hotter summer of 2011.

Performance profiling of the unit trust funds in Malaysia with data mining techniques

Background: Millennials are exposed to many investment opportunities, and they have shown their interest in gaining more income via investments. One popular investment avenue is unit trusts. However, analysing unit trusts’ financial data and gaining valuable insights may not be as simple because not everyone has the required financial knowledge and adequate time to perform in-depth analytics on the numerous financial data. Furthermore, it is not easy to compile the performance of each unit trust available in Malaysia. The primary objective of this research is to identify unit trust funds that provide higher returns than their average peers via performance profiling. Methods: This research proposed a performance profiling on Malaysia unit trust funds using the two data mining techniques, i.e., Expectation Maximisation (EM) and Apriori, to assist amateur retail investors to choose the right unit trust based on their risk tolerance. EM clustered the unit trust funds in Malaysia into several groups based on their annual financial performances. This was then followed by finding the rules associated with each cluster by applying Apriori. The resulted rules shall serve the purpose of profiling the clustered unit trust funds. Retail investors can then select their preferred unit trust funds based on the performance profile of the clusters. Results: The yearly average total return of the financial year 2018 and 2019 was used to evaluate unit trust funds’ performance in the clusters. The evaluation results indicated that the profiling could provide valuable and insightful information to retail investors with varying risk appetites. Conclusions: This research has demonstrated that the financial performance profiling of unit trust funds could be acquired via data mining approaches. This valuable information is crucial to unit trust investors for selecting suitable funds in investment.

Analyzing the health risk assessment of particles in Isfahan Steel Company by AERMOD model

Introduction: One of the effects of air pollution in the community was increasing mortality rate. Determination of contamination was the first step in improving the existing conditions. Therefore, the way of pollutants distribution and the timing and spatial changes were important. This study aimed to evaluate the risk of Parental Emissions (PE) of Isfahan Steel company using AERMOD. Materials and methods: In this research, the distribution of suspended particles of the Isfahan Steel company were modeled in the AERMOD for 1 h, 24 h and yearly average (30×30 km2), then the comparison of the average concentrations modeled with air standards clean country and Environmental Protection Agency (EPA) regional risk maps were provided in Arc GIS. Results: The prediction of the distribution of 24-h mean concentrations indicated that the maximum value for the 24-h average was equal to 8.52 EPA and 25.25 times, the standard Iran's clean air. Also, the prediction of the distribution of average annual concentrations indicated that the maximum value for the average annual time was 91.1 times, the EPA standard and 4.78% higher than Iran's clean air standard. Conclusion: Health risk maps show that the risk spot was not regional in the direction of the region's wind and topography of the region was the main factor in the distribution of risky spots in the region. Legitimate use of the AERMOD could be useful in managing, controlling, and evaluating air pollutants especially in industrial units of the country.

Attestation of conformity of particulate matter measurements (HIVATO) 2019–2020

The National Reference Laboratory for Air Quality (NRL) ensures the high quality of air quality measurements in Finland by organising audits and intercomparison campaigns. In this project, the conformity of the particulate matter measurements was evaluated with a particular focus on the measurement used for calculating the average exposure index (AEI) of Finland. The representativity and applicability of the AEI measurements made at the Kallio station in Helsinki were evaluated. It was noticed that the results of the Kallio measurement represent well the average fine particle (PM2.5) concentrations and the yearly based trend of fine particles in Finland. In addition, the yearly average concentrations of fine particles have been smaller than the AEI limit value of 8.5 µg/m3, at all individual urban background stations in Finland since year 2015. The measurement results made with the PM monitor used for AEI measurement, i.e. TEOM 1405 analyser at the Kallio station, were compared to the results from the reference method that follows the standard SFS-EN 12341:2014. It was noticed that the uncertainty requirement of 25% was reached and therefore the quality of the measurement is sufficient to use it for the calculation of AEI. However, the fine particle concentrations were generally very low and therefore the requirements given in the standard SFS-EN 16450:2017 for an intercomparison against the reference method were not perfectly fulfilled. This report presents also results from intercomparison measurements made for automated continuous measurement systems (AMS). At the Virolahti station and at the Mäkelänkatu station in Helsinki, PM10 and PM2.5 measurements were compared. In Kuopio and in Lahti, intercomparison measurements were made for PM2.5 only. Based on the results from these intercomparisons, the calibration coefficients both for PM10 and PM2.5 were defined for the first time in Finland for a FIDAS 200 analyser that is a new PM monitor in the Finnish market. It was concluded that FIDAS 200 analysers can be used for the PM measurements in Finland when the calibration coefficients are applied for the data; however, one must note that the presented calibration coefficients do not fulfil the requirements given for the demonstration of equivalence (DoE). Nevertheless, these coefficients are recommended to be used until the official coefficients will be delivered from the next DoE campaign. Two AMS (SHARP 5030 and TEOM 1405) were compared to the reference method for the measurements of PM10 and PM2,5 in Virolahti and in Helsinki, respectively. It was revealed that the calibration coefficients based on the DoE in Kuopio (2014–2015) do not always fit ideally at different locations and seasons due to differences in the environmental characteristics of the measurement sites. Therefore, NRL recommends that DoE should be organised every five years and in between the DoE’s so called ongoing-intercomparison measurements should be carried out continuously. In the ongoing-intercomparison, suitability of the calibration coefficients from DoE will be verified in different locations with varying environmental characteristics. The ongoing-intercomparison campaigns should take place at one site from a half a year to one year and after that, the campaign should continue at a different location similarly. This would ensure that the influence of seasonal differences to the suitability of coefficients will be verified at each measurement site.

Adaptive Thermal Comfort of an Office for Energy Consumption-Famagusta Case

The aim of this study was to determine how much thermal comfort can be obtained through heat/energy transfers between the office/external air and the transparent/opaque surfaces of an office by combining different transparent and opaque wall surface ratios with different window opening percentages using dynamic thermal simulations. It found that the optimum window-to-wall ratio (WWR) for energy conservation is 40%, with a 20% window opening ratio. The 80% and 90% thermal comfort ranges of the adaptive thermal comfort methodology are found in May, October, September, and the yearly average, while June and August are only in the range of 80% acceptability. The office constantly loses heat through air flow with any glass size on its external facade and any window opening ratio. Moreover, all sizes of opaque and transparent internal surfaces transferred heat from outside by conduction, while the opaque wall similarly always transferred energy to heat up the office air internally and outside air externally through convection. The external glass also heats the office air by convection, except in the months of January, November, and December.

On the Thermal Resilience of Venetian Open Spaces

Venice is known for its urban heritage fragility. The city is experiencing an increase in yearly average temperatures affecting outdoor–indoor comfort and average energy expenditure. Owing to existing literature demonstrating how local microclimate depends on urban density, form, and materials, this investigation studies the influence of the changing local climate on Venetian vernacular open spaces, known as Campi. Based on the comparison of contemporary weather and the Intergovernmental Panel on Climate Change’s (IPCC) future predictions for the 2050 scenario, this investigation highlights how Campi’s open spaces and the surrounding buildings, canals, and green public areas contribute to building climate resilience. By employing advanced modelling, the study analyses microclimate and outdoor comfort with respect to users’ perception of Physiological Equivalent Temperature (PET). The ENVI-met tool is used to simulate the thermal behaviour of two representative Campi: SS. Giovanni e Paolo and S. Polo. Despite significant temperature growths, Venetian urban fabric characteristics seem to play a crucial role in strengthening the climate resilience of open spaces, thus preserving outdoor comfort quality in a warmer future. The analysis shows how the historical matrix of open spaces and buildings cooperate. Thus, this study offers a contribution to how built heritage should be considered in light of climate change.

Hygrothermal simulations of timber-framed walls with air leakages

Air leakages can create substantial excess moisture loads into envelope structures and degrade their hygrothermal performance. Multiple previous research projects have studied the behaviour and modelling of air leakages in building physics applications, but it is still quite rare to see air leakages being considered in practical building design simulations. The purpose of this paper is to present the selection of input parameters for air leakage simulations, utilisation of a factorial design to manage simulation cases and the results for a timber-frame wall with and without air leakages. According to the results, the air permeability of mineral wool and the air pressure difference over the envelope were the two most important factors for the dry air mass flow through the structure, as opposed to gap width and leakage route. An ideally airtight structure had a better hygrothermal performance compared to leaky structure. However, when leakages were present, the exact yearly average air flow rate in the range 70…420 dm3/(m2h) did not have a strong correlation to the performance indicators. For the other studied variables, the existence of a 50 mm thick mineral wool insulation on the exterior side of the gypsum board wind barrier and the impacts from climate change had the biggest effect on the moisture performance of the structure.

Assessment of the Road Traffic Air Pollution in Urban Contexts: A Statistical Approach

In the article a statistical approach to the assessment of the emission rates discharged by the road traffic in a spatial context is proposed. It exploits an indicator, the Yearly Average Vehicle, representing the pollutant emission rate of the average vehicle belonging to a specific category, and considers the statistical variability of most of the involved traffic parameters: vehicle speed and mileage travelled in the considered time period. Finally, indicators, assessing both the most probable value among the possible emission rates and the extent of their variability range, are proposed. They may also be used to underpin decision making-processes, when the effects of different policies addressing air pollution issues, are to be evaluated. Therefore, they are suitable for the analysis supporting urban planning activities, with a view to addressing and mitigating the effects and the consequences of pollution due to the transportation sector of the urban context.