PM2.5 concentrations in a typical residential apartment in Beijing and immediately outside of the building were measured simultaneously during heating and non-heating periods. The objective was to quantitatively explore the relationship between indoor and outdoor PM2.5 concentrations. A statistical method for predicting indoor PM2.5 concentrations was proposed. Ambient PM2.5 concentrations were strongly affected by meteorological conditions, especially wind directions. A bimodal distribution was identified during the heating season due to the frequent and rapid transition between severe pollution events and clean days. Indoor PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations but with 1–2 h delay, and the differences can be explained by ambient meteorological features, such as temperature, humidity, and wind direction. These results indicate the potential to incorporate indoor exposure features to the regional air quality model framework and to more accurately estimate the epidemiological relationship between human mortality and air pollution exposure.

House dust has been recognized as an important contributor to Pb exposure of children. Here we conducted a comprehensive study to investigate geographical variation of Pb in Chinese villager house dust. The influences of outdoor soil Pb concentrations, dates of construction, house decoration materials, heating types, and site specific pollution on Pb concentrations in house dust were evaluated. The concentrations of Pb in 477 house dust samples collected from twenty eight areas throughout China varied from 12 to 2510 mg/kg, with a median concentration of 42 mg/kg. The median Pb concentrations in different geographical areas ranged from 16 (Zhangjiakou, Hebei) to 195 mg/kg (Loudi, Hunan). No correlations were found between the house dust Pb concentrations and the age of houses, as well as house decoration materials. Whereas outdoor soil, coal combustion, and site specific pollution may be potential Pb sources. Principal component analysis (PCA) confirmed that elemental compositions of the house dust were controlled by both anthropogenic and geogenic sources. Using scanning electron microscopy (SEM), the Pb bearing particles in the house dust were also studied.

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.

Two major environmental issues, air quality and climate change, are interlinked because of their large dependence on atmospheric emissions from human activities, especially from the burning of fossil fuels. Emission of air pollutants and heat trapping gases have greatly increased over the last five decades from our dependence throughout the world on conventional fossil fuel sources in production of electricity and in transportation systems, resulting in significant environmental issues with air quality and climate change throughout our planet. Future emissions of pollutants will depend on the choices made about our use of energy and transportation. The purpose of this study is to examine for now and into the future the relationship between energy production, the associated use of fossil fuels, and resulting effects on air pollution. In the process, we examine a clean energy future, imagined in this case for 2050, and then consider the resulting potential effects on air quality.

The concentrations of monosaccharide anhydrides (levoglucosan, mannosan, galactosan), monocarboxylic acids (alkanoic acids C7 – C20 and two unsaturated fatty acids, palmitoleic and oleic acids) and organic and elemental carbon in PM1 aerosol samples were measured in two cities of the Czech Republic (Brno and Šlapanice) in winter and summer seasons of 2009 and 2010.Mass concentrations of PM1 aerosols (determined by weighing filters with collected aerosol) were higher in winter than in summer in both 2009 and 2010, in Brno as well as in Šlapanice.Organic compounds were analysed by GC–MS. The sum of average atmospheric concentration of monosaccharide anhydrides (MAs) in PM1 aerosol in Brno and Šlapanice was 273 and 646 ng m−3 in winter and 20–42 ng m−3 in summer. The higher concentrations of MAs in PM1 aerosols in winter seasons indicate higher frequency of biomass combustion than in summer seasons. Levoglucosan was the most abundant monosaccharide anhydride. Contrary to MAs, the concentrations of majority monocarboxylic acids were higher in summer (153–221 ng m−3) than in winter (116–206 ng m−3) in both cities in 2009 and in 2010. Palmitic acid was the most abundant monocarboxylic acid.The concentrations of both organic (OC) and elemental (EC) carbon were higher in winter than in summer, which corresponds especially to higher biomass burning and coal combustion in the frame of residential heating within winter seasons. Mass concentrations of the analysed aerosol samples were counted, i.e., OCBB and ECBB (biomass burning), OCFF and ECFF (fossil fuel combustion), and OCBIO (biogenic sources).Higher concentrations of MAs and PM1, OC and EC in winter seasons, could be caused not only by larger emissions from biomass or coal combustion, but also by less dispersion due to different atmospheric conditions.

In this study, stable carbon and nitrogen isotope ratios in the samples of pine needles collected in 2013 and 2014 from heavily urbanized area in close proximity to point-source pollution emitters, such as a heat and power plant, nitrogen plant, and steelworks in Silesia (Poland), were analyzed as bio-indicators of contemporary environmental changes. The carbon isotope discrimination has been proposed as a method for evaluating water-use efficiency. The measurement of carbon and nitrogen isotopes was carried out using the continuous flow isotope ratio mass spectrometer. The isotope ratio mass spectrometer allows the precise measurement of mixtures of naturally occurring isotopes. The δ¹⁵N values were calibrated relative to the NO-3 and USGS34 international standards, whereas the δ¹³C values were calibrated relative to the C-3 and C-5 international standards. The strong year-to-year correlations between the δ¹³C in different sampling sites, and also the inter-annual correlation of δ¹⁵N values in the pine needles at each of the investigated sampling sites confirm that the measured δ¹³C and δ¹⁵N and also intrinsic water-use efficiency (iWUE) trends are representative of the sampling site. Diffuse air pollution caused the variation in δ ¹³C, δ¹⁵N, and iWUE dependent on type of emitter, the localization in the space (distance and direction) from factories and some local effect of other human activities. The complex short-term variation analysis can be helpful to distinguish isotopic fractionation, which is not an effect explainable by climatic conditions but by the anthropogenic effect. Between 2012 and 2014, an increase in iWUE is observed at leaf level.

Since the 1990s, the emission of pollutants was reduced in a majority of Polish and developing country factories whereas the level of energy production was similar to that prior to the 1990s. The conifer investigated in this study has grown for many years under the stress of industrial pollution. Despite this, the trees are preserved, to a large extent, sensitive to the natural climatic factors. We present a complex analysis of the climatic (sunshine, temperature, precipitation, humidity, and wind circulation) and anthropogenic factors influencing the radial increment dynamics of Scots pine (Pinus sylvestris L.) growing in the vicinity of the combined heat and power station in Łaziska (Poland). We analyzed the spatiotemporal distribution of growth reductions, the depth of reduction with respect to the distance from the emitter, the relationship between tree growth and climate during the industry development period and during proecological strategy application . Samples of carbon isotopic composition in pine needles from 2012 to 2013 were additionally determined. Pines series of 3 positions indicate that they have a similar sensitivity to most climatic elements of the previous and given year, but there is also a different rhythm between the studied populations of incremental growth of pines. The causes of diversity are due to the different types of habitat (site types) and industrial pollution. The variation in carbon stable isotopic composition in pine needles was connected with an increase of CO₂.

Tropical coastal areas are sensitive ecosystems to climate change, mainly due to sea level rise and increasing water temperatures. Furthermore, they may be subject to numerous stresses, including heat releases from energy production. The Urias coastal lagoon (SE Gulf of California), a subtropical tidal estuary, receives cooling water releases from a thermoelectric power plant, urban and industrial wastes, and shrimp farm discharges. In order to evaluate the plant thermal impact, we measured synchronous temperature time series close to and far from the plant. Furthermore, in order to discriminate the thermal pollution impact from natural variability, we used a high-resolution hydrodynamic model forced by, amongst others, cooling water release as a continuous flow (7.78 m³ s⁻¹) at 6 °C overheating temperature. Model results and field data indicated that the main thermal impact was temporally restricted to the warmest months, spatially restricted to the surface layers (above 0.6 m) and distributed along the shoreline within ∼100 m of the release point. The methodology and results of this study can be extrapolated to tropical coastal lagoons that receive heat discharges.

Integrating vegetation into architecture has become widely recognized as a multi-beneficial practice in architecture and engineering design to combat an array of environmental issues. Urban areas have microclimates that are different than the climates of their surrounding rural areas. Patterns in these differences over the years have shown that urban microclimates tend to be significantly warmer in comparison. This phenomenon is now recognized as the urban “heat island” effect. While the associated consequences of this urban heating are far reaching, excess energy expenditure, air pollution emissions, and threats to human health are among the most critical for evaluation. The integration of vegetative green space in urban planning, coupled with highly reflective materials in place of conventional paved surfaces on roads and rooftops have proven to be effective methods of urban heat island mitigation. While as separate entities these methods are effective, innovative technology has brought forth greening roofs which allows vegetation to compensate where other roof-cooling strategies fall short. Substantially, vertical greenery systems compensate where greening roofs fall short. This paper explores both integrated vegetation as an optimal mitigation strategy for urban heat islands and vertical plant walls as an optimal design.

Polychlorinated dibenzodioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) are toxic environmental pollutants that are often found in sediments. The Yangtze and Yellow rivers in China are two of the largest rivers in Asia and are therefore important aquatic ecosystems; however, few studies have investigated the PCDD/F and PCB content in the sediments of these rivers. Accordingly, this study was conducted to generate baseline data for future environmental risk assessments. In the present study, 26 surface sediments from the middle reaches of the Yellow and Yangtze rivers were analyzed for PCDD/Fs and dioxin-like (dl) PCBs by high-resolution gas chromatography and high-resolution mass spectrometry. The ranges of PCDD/F, dl-PCB, and WHO-TEQ content in sediments from the Yellow River were 2.1–19.8, 1.11–9.9, and 0.08–0.57 pg/g (dry weight), respectively. The ranges of PCDD/F, dl-PCB, and WHO-TEQ content in sediments from the Yangtze River were 6.1–84.9, 1.8–24.1, and 0.13–0.29 pg/g (dry weight), respectively. Total organic carbon and dl-PCB contents in the Yellow River were significantly correlated (Spearman’s correlation coefficient, r = 0.64, P < 0.05). It is well known that total organic carbon plays a role in the transport and redistribution of dl-PCB. Principal component analysis indicated that PCDD/Fs may arise from pentachlorophenol, sodium pentachlorophenate, and atmospheric deposition, while dl-PCBs likely originate from burning of coal and wood for domestic heating. The dioxin levels in the river sediments examined in this study were relatively low. These findings advance our knowledge regarding eco-toxicity and provide useful information regarding contamination sources.