This paper develops a tool for estimating energy-related CO2 emissions from the world's cities based on regression models. The models are developed considering climatic (heating-degree-days) and urban design (land area per person) independent variables. The tool is applied on 3646 urban areas for estimating impacts on urban emissions of a) global transitioning to Electric Vehicles, b) urban density change and c) IPCC climate change scenarios. Results show that urban density decline can lead to significant increase in energy emissions (upto 346% in electricity & 428% in transportation at 2% density decline by 2050). Among the IPCC climate scenarios tested, A1B is the most effective in reducing growth of emissions (upto 12% in electricity & 35% in heating). The tool can further be improved by including more data in the regression models along with inclusion of other relevant emissions and climatic variables.

Rapid monitoring and discriminating different anthropogenic pollution is a key scientific issue. To detect the applicability and sensitivity of magnetic measurements for evaluating different industrial pollution in urban environment, characteristics of topsoil from three typical fast developing industrial cities (Jinchang, Baiyin and Jiayuguan in Gansu province, northwestern China) were studied by magnetic and geochemical analyses. The results showed that magnetic susceptibility was enhanced near industrial areas, and PSD-MD magnetite dominated the magnetic properties. Magnetic concentration parameters (χlf, SIRM, and χARM) showed different correlations with heavy metals and PLI in the three cities, indicating significantly different magnetic response to different pollution sources. Principal component analysis showed that ferrimagnetic minerals coexist with heavy metals of Fe, As, Cu, Pb, and Zn in Baiyin and Fe, V, Cu, Mn, Pb, and Cr in Jiayuguan. Fuzzy cluster analysis and regression analysis further indicated that the sensitivity of magnetic monitoring to fuel dust is higher than that to mineral dust near non-ferrous metal smelters, and fossil fuel consumption is an important factor for increasing magnetite content. In all the three cities, the sensitivity of magnetic monitoring to pollutants from steel plants is much higher than that from non-ferrous metal plants. Therefore, magnetic proxies provide a rapid means for detecting heavy metal contamination caused by multi-anthropogenic pollution sources in a large scale area, however, the sensitivity was controlled by pollution sources.

Flow and dispersion of traffic pollutants in a generic urban neighborhood with avenue-trees were investigated with Computational Fluid Dynamics (CFD). In Part I of this two-part contribution, quality assessment and assurance for CFD simulations in urban and vegetation configurations were addressed, before in Part II flow and dispersion in a generic urban neighborhood with multiple layouts of avenue-trees were studied. In a first step, a grid sensitivity study was performed that inferred that a cell count of 20 per building height and 12 per canyon width is sufficient for reasonable grid insensitive solutions. Next, the performance of the realizable k-ε turbulence model in simulating urban flows and of the applied vegetation model in simulating flow and turbulence in trees was validated. Finally, based on simulations of street canyons with and without avenue-trees, an appropriate turbulent Schmidt number for modeling dispersion in the urban neighborhood was determined as Sct = 0.5.

Twelve nitro-PAHs (nPAHs) and four oxy-PAHs (oPAHs) were measured in air samples for 12 months at 18 sites in urban settings, rural villages, or rural fields in northern China. The nPAH concentrations were higher in urban areas (1.3 ± 1.3 ng/m3), and nPAH/parent PAH ratios were higher (suggesting important contributions from motor vehicles and secondary formation) in urban sites than in rural villages. oPAHs are primarily emitted from solid fuel combustion and motor vehicles, and similar oPAH concentrations were found in urban areas (23 ± 20 ng/m3) and rural villages (29 ± 24 ng/m3). The high numbers of motor vehicles in Beijing and intensive industrial activity in Taiyuan and Dezhou caused higher nPAH concentrations. No spatial trend in oPAH concentrations was found in the rural villages, because similar oPAH mixtures are emitted from solild fuel combustion. The nPAH and oPAH concentrations were higher in the winter, and correlated with residential energy consumption and precipitation.

Airborne measurements within the urban mixing layer (360 m) over Greater London are used to quantify CO2 emissions at the meso-scale. Daytime CO2 fluxes, calculated by the Integrative Mass Boundary Layer (IMBL) method, ranged from 46 to 104 μmol CO2m−2s−1 for four days in October 2011. The day-to-day variability of IMBL fluxes is at the same order of magnitude as for surface eddy-covariance fluxes observed in central London. Compared to fluxes derived from emissions inventory, the IMBL method gives both lower (by −37%) and higher (by 19%) estimates. The sources of uncertainty of applying the IMBL method in urban areas are discussed and guidance for future studies is given.

Long-term trends in observed carbon monoxide (CO) concentrations were analyzed in seven major South Korean cities from 1989 to 2013. Temporal trends were evident on seasonal and annual timescales, as were spatial gradients between the cities. As CO levels in the most polluted cities decreased significantly until the early 2000s, the data were arbitrarily divided into two time periods (I: 1989–2000 and II: 2001–2013) for analysis. The mean CO concentration of period II was about 50% lower than that of period I. Long-term trends of annual mean CO concentrations, examined using the Mann–Kendall (MK) method, confirm a consistent reduction in CO levels from 1989 to 2000 (period I). The abrupt reduction in CO levels was attributed to a combination of technological improvements and government administrative/regulatory initiatives (e.g., emission mitigation strategies and a gradual shift in the fuel/energy consumption mix away from coal and oil to natural gas and nuclear power).

Fine particulate matter (PM2.5) is a growing public health concern especially in industrializing countries but existing monitoring networks are unable to properly characterize human exposures due to low resolution spatiotemporal data. Low-cost portable monitors can supplement existing networks in both developed and industrializing regions to increase density of sites and data. This study tests the performance of a low-cost sensor in high concentration urban environments. Seven Portable University of Washington Particle (PUWP) monitors were calibrated with optical and gravimetric PM2.5 reference monitors in Xi'an, China in December 2013. Pairwise correlations between the raw PUWP and the reference monitors were high (R2 = 0.86–0.89). PUWP monitors were also simultaneously deployed at eight sites across Xi'an alongside gravimetric PM2.5 monitors (R2 = 0.53). The PUWP monitors were able to identify the High-technology Zone site as a potential PM2.5 hotspot with sustained high concentrations compared to the city average throughout the day.

Short chain chlorinated paraffins (SCCPs) have been of considerable concern in recent years due to their high production volumes, environmental persistency and potential for long range atmospheric transport. Vegetation can take up considerable amounts of semivolatile organic compounds from the atmosphere and can act as indicators of local contamination. Paired pine needles and bark were sampled around Beijing during winter and summertime to investigate the distribution of SCCPs in urban areas. Levels in bark samples ranged 5.79–37.5 μg/g on a lipid normalized basis (lw) with a geometric mean (GM) of 16.9 μg/g lw whereas levels were 3.03–40.8 (GM 11.8) μg/g lw for needles. Average congener group abundance profiles showed equal contribution of all four carbon groups (C10–13) in wintertime whereas higher abundances of C10 and C11 groups were found during summer. Uptake of SCCPs occurred mainly via kinetically limited gaseous deposition and particle bound deposition in the investigated area.

Health effects by consuming urban garden products are discussed controversially due to high urban pollution loads. We sampled wild edible mushrooms of different habitats and commercial mushroom cultivars exposed to high traffic areas within Berlin, Germany. We determined the content of cadmium and lead in the fruiting bodies and analysed how the local setting shaped the concentration patterns. EU standards for cultivated mushrooms were exceeded by 86% of the wild mushroom samples for lead and by 54% for cadmium but not by mushroom cultures. We revealed significant differences in trace metal content depending on species, trophic status, habitat and local traffic burden. Higher overall traffic burden increased trace metal content in the biomass of wild mushrooms, whereas cultivated mushrooms exposed to inner city high traffic areas had significantly lower trace metal contents. Based on these we discuss the consequences for the consumption of mushrooms originating from urban areas.

Turfgrass covers a large fraction of the urbanized landscape, but the carbon exchange of urban lawns is poorly understood. We used eddy covariance and flux chambers in a grassland field manipulative experiment to quantify the carbon mass balance in a Singapore tropical turfgrass. We also assessed how management and variations in environmental factors influenced CO2 respiration. Standing aboveground turfgrass biomass was 80 gC m−2, with a mean ecosystem respiration of 7.9 ± 1.1 μmol m−2 s−1. The contribution of autotrophic respiration was 49–76% of total ecosystem respiration. Both chamber and eddy covariance measurements suggest the system was in approximate carbon balance. While we did not observe a significant relationship between the respiration rates and soil temperature or moisture, daytime fluxes increased during the rainy interval, indicating strong overall moisture sensitivity. Turfgrass biomass is small, but given its abundance across the urban landscape, it significantly influences diurnal CO2 concentrations.