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.

Rapid urbanization, which is closely related to economic growth, human health, and micro-climate, has resulted in a considerable amount of anthropogenic heat emissions. The lack of estimation data on long-term anthropogenic heat emissions is a great concern in climate and urban flux research. This study estimated the annual average anthropogenic heat fluxes (AHFs) in Beijing–Tianjin–Hebei region in China between 1995 and 2015 on the basis of multisource remote sensing images and ancillary data. Anthropogenic heat emissions from different sources (e.g., industries, buildings, transportation, and human metabolism) were also estimated to analyze the composition of AHFs. The spatiotemporal dynamics of long-term AHFs with high spatial resolution (500 m) were estimated by using a refined AHF model and then analyzed using trend and standard deviation ellipse analyses. Results showed that values in the region increased significantly from 0.15 W· m−2 in 1995 to 1.46 W· m−2 in 2015. Heat emissions from industries, transportation, buildings, and human metabolism accounted for 64.1%, 17.0%, 15.5%, and 3.4% of the total anthropogenic heat emissions, respectively. Industrial energy consumption was the dominant contributor to the anthropogenic heat emissions in the region. During this period, industrial heat emissions presented an unstable variation but showed a growing trend overall. Heat emissions from buildings increased steadily. Spatial distribution was extended with an increasing tendency of the difference between the maximum and the minimum and was generally dominated by the northeast–southwest directional pattern. The spatiotemporal distribution patterns and trends of AHFs could provide vital support on management decision in city planning and environmental monitoring.

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.

The city of London, UK, has seen in recent years an increase in the number of high-rise/multi-storey buildings (“skyscrapers”) with roof heights reaching 150 m and more, with the Shard being a prime example with a height of ∼310 m. This changing cityscape together with recent plans of local authorities of introducing Combined Heat and Power Plant (CHP) led to a detailed study in which CFD and wind tunnel studies were carried out to assess the effect of such high-rise buildings on the dispersion of air pollution in their vicinity. A new, open-source simulator, FLUIDITY, which incorporates the Large Eddy Simulation (LES) method, was implemented; the simulated results were subsequently validated against experimental measurements from the EnFlo wind tunnel. The novelty of the LES methodology within FLUIDITY is based on the combination of an adaptive, unstructured, mesh with an eddy-viscosity tensor (for the sub-grid scales) that is anisotropic. The simulated normalised mean concentrations results were compared to the corresponding wind tunnel measurements, showing for most detector locations good correlations, with differences ranging from 3% to 37%. The validation procedure was followed by the simulation of two further hypothetical scenarios, in which the heights of buildings surrounding the source building were increased. The results showed clearly how the high-rise buildings affected the surrounding air flows and dispersion patterns, with the generation of “dead-zones” and high-concentration “hotspots” in areas where these did not previously exist. The work clearly showed that complex CFD modelling can provide useful information to urban planners when changes to cityscapes are considered, so that design options can be tested against environmental quality criteria.

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.

Human exposure to polycyclic aromatic hydrocarbons (PAHs) in indoor environments can be particularly relevant because people spend most of their time inside buildings, especially in homes. This study aimed to investigate the most important particle-bound PAH sources and exposure determinants in PM2.5 samples collected in 19 homes located in northern Italy. Complementary information about ion content in PM10 was also collected in 12 of these homes. Three methods were used for the identification of PAH sources and determinants: diagnostic ratios with principal component and hierarchical cluster analyses (PCA and HCA), chemical mass balance (CMB) and linear mixed models (LMMs). This combined and tiered approach allowed the infiltration of outdoor PAHs into indoor environments to be identified as the most important source in winter, with a relevant role played by biomass burning and traffic exhausts to be identified as a general source of PAHs in both seasons. Tobacco smoke exhibited an important impact on PAH levels in smokers' homes, whereas in the whole sample, cooking food and natural gas sources played a minor or negligible role. Nitrate, sulfate and ammonium were the main inorganic constituents of indoor PM10 owing to the secondary formation of ammonium sulfates and nitrates.

This study is a systematic assessment of different houses and apartments, their ages and renovation status, indoors and outdoors, and in summer vs. winter, with a goal of bringing some insight into the major sources of semivolatile organic compounds (SVOCs) and their variability. Indoor and outdoor air concentrations of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and novel flame retardants (NFRs) were determined at 17–20 homes in Czech Republic in winter and summer.Indoor concentrations were consistently higher than outdoor concentrations for all compounds; indoor/outdoor ratios ranged from 2–20, with larger differences for the current use NFRs than for legacy PCBs. Seasonal trends differed according to the use status of the compounds: the PCBs had higher summer concentrations both indoors and outdoors, suggesting volatilization as a source of PCBs to air. PBDEs had no seasonal trends indoors, but higher summer concentrations outdoors. Several NFRs (TBX, PBT, PBEB) had higher indoor concentrations in winter relative to summer. The seasonal trends in the flame retardants suggest differences in air exchange rates due to lower building ventilation in winter could be driving the concentration differences.Weak relationships were found with building age for PCBs, with higher concentrations indoors in buildings built before 1984, and with the number of electronics for PBDEs, with higher concentrations in rooms with three or more electronic items. Indoor environments are the primary contributor to human inhalation exposure to these SVOCs, due to the high percentage of time spent indoors (>90%) combined with the higher indoors levels for all the studied compounds. Exposure via the indoor environment contributed ∼96% of the total chronic daily intake via inhalation in summer and ∼98% in winter.

People typically spend most of their time indoors. We modeled the daily indoor PM10 concentrations of outdoor origin using a set of exposure parameters, including the fraction of residences with air conditionings (AC), the fraction of time that windows are closed when cooling occurs for buildings with AC, the fractions of time that windows are open or closed for buildings with or without AC, the particle penetration factors, air change rates, and surface removal rate constant of PM10. We calculated the time-weighted average of the simulated indoor PM10 concentration of outdoor origin and the original recorded outdoor PM10 concentration. We then evaluated the acute effects of PM10 using traditional and amended exposure metrics in 16 Chinese cities. Compared with the original estimates, the new effect estimates almost doubled, with improved model fit and attenuated between-city heterogeneity. Conclusively, this proposed exposure assessment approach could improve the effect estimates of ambient particles.

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.