Useful information on the potential radon risk in existing buildings can be obtained by combining data from sources such as potential risk maps, the ‘Sistema de Información sobre Ocupación del Suelo de España’ (SIOSE) [information system on land occupancy in Spain], cadastral data on built property and population surveys. The present study proposes a method for identifying urban land, premises and individuals potentially subject to radon risk. The procedure draws from geographic information systems (GIS) pooled at the municipal scale and data on buildings possibly affected. The method quantifies the magnitude of the problem in the form of indicators on the buildings, number of premises and gross floor area that may be affected in each risk category. The findings are classified by type of use: residential, educational or office. That information may guide health/prevention policies by targeting areas to be measured based on risk category, or protection policies geared to the construction industry by estimating the number of buildings in need of treatment or remediation. Application of the methodology to Greater Madrid showed that 47% of the municipalities have houses located in high radon risk areas. Using cadastral data to zoom in on those at highest risk yielded information on the floor area of the vulnerable (basement, ground and first storey) premises, which could then be compared to the total. In small towns, the area affected differed only scantly from the total, given the substantial proportion of low-rise buildings in such municipalities.

Understanding the effects of urban morphology on urban environmental noise (UEN) at a regional scale is crucial for creating a pleasant urban acoustic environment. This study seeks to investigate how the urban morphology influences the UEN in the Shenzhen metropolitan region of China, by employing remote sensing and geographic information data. The UEN in this study consists of not only regional environmental noise (RN), but also traffic noise (TN). The experimental results reveal the following findings: 1) RN is positively correlated with the nighttime light intensity (NTL) and land surface temperature (LST) (p < 0.05). More interestingly, landscape composition and configuration can also significantly affect RN. For instance, urban vegetation can mitigate the RN (r = −0.411, p < 0.01). There is a reduced RN effect when fewer buildings exist in an urban landscape, in terms of the positive relationship between building density and RN (r = 0.188, p < 0.01). Given the same percentage of building area, buildings are more effective at reducing noise when they are distributed across the urban scenes, rather than being spatially concentrated (r = −0.205, p < 0.01). 2) TN positively relates to large (r = 0.520, p < 0.01) and small–medium (r = 0.508, p < 0.01) vehicle flow. In addition, vegetation along or near roads can alleviate the TN effect (r = −0.342, p < 0.01). TN can also become more severe in urban landscapes where there is higher road density (r = 0.307, p < 0.01). 3) Concerning the urban functional zones, traffic land is the greatest contributor to urban RN, followed by mixed residential and commercial land. The findings revealed by this research will indicate how to mitigate UEN.

Green streets are increasingly being used as a stormwater management strategy to mitigate stormwater runoff at its source while providing other environmental and societal benefits, including connecting pedestrians to the street. Simultaneously, human exposure to particulate matter from urban transportation is of major concern worldwide due to the proximity of pedestrians, drivers, and cyclists to the emission sources. Vegetation used for stormwater treatment can help designers limit the exposure of people to air pollutants. This goal can be achieved through the deliberate placement of green streets, along with strategic planting schemes that maximize pollutant dispersion. This communication presents general design considerations for green streets that combine stormwater management and air quality goals. There is currently limited guidance on designing green streets for air quality considerations; this is the first communication to offer suggestions and advice for the design of green stormwater streets in regards to their effects on air quality. Street characteristics including (1) the width to height ratio of the street to the buildings, (2) the type of trees and their location, and (3) any prevailing winds can have an impact on pollutant concentrations within the street and along sidewalks. Vegetation within stormwater control measures has the ability to reduce particulate matter concentrations; however, it must be carefully selected and placed within the green street to promote the dispersion of air flow.

Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM2.5 and CO2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM2.5 concentrations with a maximum concentration above 100 μg m−3 at the building rooftop. The above-ground “hotspots” would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant “hotspots” into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed.

The urban environment holds numerous emission sources for air and noise pollution, creating optimum conditions for environmental multi-exposure situations. Evaluation of the joint-exposure levels is the main obstacle for multi-exposure studies and one of the biggest challenges of the next decade. The present study aims to describe the noise/NO2 multi-exposure situations in the urban environment by exploring the possible discordant and concordant situations of both exposures. Fine-scale diffusion models were developed in the European medium-sized city of Besançon (France), and a classification method was used to evaluate the multi-exposure situations in the façade perimeter of 10,825 buildings. Although correlated (Pearson's r = 0.64, p < 0.01), urban spatial distributions of the noise and NO2 around buildings do not overlap, and 30% of the buildings were considered to be discordant in terms of the noise and NO2 exposure levels. This discrepancy is spatially structured and associated with variables describing the building's environment. Our results support the presence of several co-existing, multi-exposure situations across the city impacted by both the urban morphology and the emission and diffusion/propagation phases of each pollutant. Identifying the mechanisms of discrepancy and convergence of multi-exposure situations could help improve the health risk assessment and public health.

The potential benefit of urban vegetation in reducing heat related mortality in the city of Melbourne, Australia is investigated using a two-scale modelling approach. A meso-scale urban climate model was used to quantify the effects of ten urban vegetation schemes on the current climate in 2009 and future climates in 2030 and 2050. The indoor thermal performance of five residential buildings was then simulated using a building simulation tool with the local meso-climates associated with various urban vegetation schemes. Simulation results suggest that average seasonal summer temperatures can be reduced in the range of around 0.5 and 2 °C if the city were replaced by vegetated suburbs and parklands, respectively. With the limited buildings and local meso-climates investigated in this study, around 5–28% and 37–99% reduction in heat related mortality rate have been estimated by doubling the city's vegetation coverage and transforming the city into parklands respectively.

Atmospheric gaseous elemental mercury [GEM] at 1.8, 4, and 59 m above ground, in parking lots, and in indoor and outdoor air was measured in Toronto City, Canada from May 2008–July 2009. The average GEM value at 1.8 m was 1.89 ± 0.62 ng m⁻³. The GEM values increased with elevation. The average GEM in underground parking lots ranged from 1.37 to 7.86 ng m⁻³ and was higher than those observed from the surface parking lots. The GEM in the indoor air ranged from 1.21 to 28.50 ng m⁻³, was higher in the laboratories than in the offices, and was much higher than that in the outdoor air. All these indicate that buildings serve as sources of mercury to the urban atmosphere. More studies are needed to estimate the contribution of urban areas to the atmospheric mercury budget and the impact of indoor air on outdoor air quality and human health.

The wide adoption of combined heat and power (CHP) can not only improve energy efficiency, but also strengthens energy system resiliency. While CHP reduces overall emissions compared to generating the same amount of electricity and heat separately, its on-site nature also means that CHP facilities operate in populated areas, raising concerns over their near-source air quality impact. Evaluation of the near-source impact of distributed CHP is limited by emission data availability, especially in terms of particulate matter (PM). In this paper, we report on stack emission testing results of a community-scale CHP plant with two natural gas turbine units (15 MW each) from measurements conducted in both 2010 and 2015, and assess the near-source air quality impact using an integrated modeling framework using the stack test results, site-specific meteorological data and terrain profiles with buildings. The NOx removal efficiency by selective catalytic reduction (SCR) is estimated to be ∼83% according to the emission testing. The integrated framework employs AERMOD to screen air quality in a 2.7 km × 2.3 km domain from 2011 to 2015 to identify the highest ground-level concentrations (GLCs). Examining the corresponding meteorological conditions, we find that those high GLCs appeared during the stable atmospheric boundary layer with relative high wind speed. Next, the worse-case scenarios identified from the screening process are simulated using the detailed Unsteady Reynolds Averaged Navier-Stokes (URANS) model coupled with a chemistry solver. The results generally show low GLCs of primary PM₂.₅ for this case study. However, our analysis also suggests greater building downwash impacts with the presence of taller and denser urban structures. Therefore, the near-source impact of natural gas-fired CHP in large metropolitan areas is worthy of further investigation.

Lead contamination is widespread across China, posing a serious public health concern. In quantifying child lead exposure, established health risk assessment (HRA) approaches often take into account residential soil lead levels. However, this may not constitute a significant exposure source for children in urban mainland China, where the population mainly dwell in high-rise buildings without back or front yards. In this setting, children's playgrounds may represent a more probable exposure source. The present study analyzed lead levels in settled dust on playground equipment and in surficial soils at 71 playgrounds in Beijing, China. Our results reveal that the average playground dust lead concentration was 80.5 mg/kg, more than twice the average soil lead concentration of 36.2 mg/kg. It was found that there are differences in statistical and spatial distributions for lead in playground dust and soils. Lead levels in equipment dust were largely consistent across Beijing, with elevated levels detected at locations in the main city area, the newly developed Tongzhou District, and the rural counties. Whereas average soil lead concentrations were higher at playgrounds in the main city area than other areas of Beijing. Statistical analysis suggests that the lead content in dust and soil may derive from different natural and anthropogenic sources. Equipment dust lead may be associated with long-distance atmospheric transportation and deposition. Whereas lead in soil is more likely to be associated with local traffic. This study also found that, in certain areas of Beijing, the risk of blood lead levels (BLLs) exceeding safe levels was up to 6 times higher when based on dust exposure than when based on playground soil exposure. The results of this study suggests that HRA undertaken for children in urban mainland China should pay closer attention to children's playgrounds as a lead exposure source, and, in particular, playground equipment dust.

If volatile organic compound (VOC)-contaminated soil exists underneath a building, vapors may migrate upwards and intrude into the interior air of the building. Most previous models used to simulate vapor intrusion (VI) were developed by assuming that the source was constant, although a few recent models, such as the Risk-Based Corrective Action (RBCA) Tool Kit (TK) model, have been developed to consider source depletion (SD). However, the RBCA TK model ignores the effects of building characteristics due to its assumption that the ground is not covered by the actual building it models, which leads to incorrect results since the presence of the building affects the SD. In this study, a SD model is developed based on the three processes of VI while considering the impact of key building parameters on SD. The proposed model (i.e., the SD model) still follows the law of mass conservation, and the sensitivity analysis shows that the soil-building pressure differential (dP) is an important building characteristic that affects SD. Taking trichloroethylene (TCE) for simulation in the case of a soil concentration below the saturation concentration, as the soil permeability decreases, the differences in the results between the SD model and RBCA TK model decrease; as the Peclet number decreases, the effect of the dP on the results of the SD model decreases. The new model only accounts for the migration of contaminants at the source of depletion; therefore, the model is more applicable for these contaminants, which are considered to have low-biodegradable characteristics. Furthermore, since the model emphasizes the impact of buildings on the source, it is applicable when there is a considerable building area above the source, such as large commercial buildings or residential communities with underground parking lots, which exist in most cities.