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Native Trees as a Provider of Vital Urban Ecosystem Services in Urbanizing New Zealand: Status Quo, Challenges and Prospects. LAND 2022. [DOI: 10.3390/land11010092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In New Zealand, over 87% of the population currently resides in cities. Urban trees can face a myriad of complex challenges including loss of green space, public health issues, and harm to the existence of urban dwellers and trees, along with domestic greenhouse gas (GHG) and air pollutant emissions. Despite New Zealand being a biodiversity hotspot in terms of natural environments, there is a lack of knowledge about native tree species’ regulating service (i.e., tree development and eco-physiological responses to low air quality, GHG, rising air temperatures, and drought) and how they grow in built-up environments such as cities. Therefore, we argue for the value of these native species in terms of ecosystem services and insist that they need to be viewed in relation to how they will respond to urban abiotic extremes and climate change. We propose to diversify planted forests for several reasons: (1) to improve awareness of the benefits of diverse planted urban forests; (2) to foster native tree research in urban environments, finding new keystone species; and (3) to improve the evidence of urban ecosystem resilience based on New Zealand native trees’ regulating services. This article aims to re-evaluate our understanding of whether New Zealand’s native trees can deal with environmental stress conditions similarly to more commonly planted alien species.
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Lucadamo L, Gallo L, Corapi A. PAHs in an urban-industrial area: The role of lichen transplants in the detection of local and study area scale patterns. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 284:117136. [PMID: 33915398 DOI: 10.1016/j.envpol.2021.117136] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 04/07/2021] [Accepted: 04/09/2021] [Indexed: 06/12/2023]
Abstract
Spatial variation of the levels of polycyclic aromatic hydrocarbons (PAHs) was evaluated within an urban-industrial district where the main anthropogenic pressures are a 15 MW biomass power plant (BPP) and road traffic. The use of a high-density lichen transplant network and wind quantitative relationships made it possible to perform a hierarchical analysis of contamination. Combined uni-bi and multivariate statistical analyses of the resulting databases revealed a dual pattern. In its surroundings (local scale), the BPP affected the bioaccumulation of fluoranthene, pyrene and total PAHs, although a confounding effect of traffic (mostly petrol/gasoline engines) was evident. Spatial variation of the rate of diesel vehicles showed a significant association with that of acenaphthylene, acenaphthene, fluorene, anthracene and naphthalene. The series of high-speed wind values suggests that wind promotes diffusion rather than dispersion of the monitored PAHs. At the whole study area scale, the BPP was a source of acenaphthylene and acenaphthene, while diesel vehicles were a source of acenaphthylene. PAHs contamination strongly promotes oxidative stress (a threefold increase vs pre-exposure levels) in lichen transplants, suggesting a marked polluting effect of anthropogenic sources especially at the expense of the mycobiont. The proposed monitoring approach could improve the apportionment of the different contributions of point and linear anthropogenic sources of PAHs, mitigating the reciprocal biases affecting their spatial patterns.
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Affiliation(s)
- L Lucadamo
- DiBEST (Department of Biology, Ecology and Earth Sciences), University of Calabria, 87036, Arcavacata di Rende, CS, Italy.
| | - L Gallo
- DiBEST (Department of Biology, Ecology and Earth Sciences), University of Calabria, 87036, Arcavacata di Rende, CS, Italy
| | - A Corapi
- DiBEST (Department of Biology, Ecology and Earth Sciences), University of Calabria, 87036, Arcavacata di Rende, CS, Italy
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Martenies SE, Keller JP, WeMott S, Kuiper G, Ross Z, Allshouse WB, Adgate JL, Starling AP, Dabelea D, Magzamen S. A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:3112-3123. [PMID: 33596061 PMCID: PMC8313050 DOI: 10.1021/acs.est.0c06451] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R2 of 0.83 and a root-mean-square error of 0.15 μg/m3 for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.
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Affiliation(s)
- Sheena E Martenies
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801-3028, United States
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado 80523-1019, United States
| | - Joshua P Keller
- Department of Statistics, Colorado State University, Fort Collins, Colorado 80523-1019, United States
| | - Sherry WeMott
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado 80523-1019, United States
| | - Grace Kuiper
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado 80523-1019, United States
| | - Zev Ross
- ZevRoss Spatial Analysis, Ithaca, New York 14850, United States
| | - William B Allshouse
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - John L Adgate
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - Sheryl Magzamen
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado 80523-1019, United States
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado 80045, United States
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Feng X, Shen J, Yang H, Wang K, Wang Q, Zhou Z. Time-Frequency Analysis of Particulate Matter (PM 10) Concentration in Dry Bulk Ports Using the Hilbert-Huang Transform. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17165754. [PMID: 32784870 PMCID: PMC7460512 DOI: 10.3390/ijerph17165754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/27/2020] [Accepted: 08/05/2020] [Indexed: 01/29/2023]
Abstract
To analyze the time–frequency characteristics of the particulate matter (PM10) concentration, data series measured at dry bulk ports were used to determine the contribution of various factors during different periods to the PM10 concentration level so as to support the formulation of air quality improvement plans around port areas. In this study, the Hilbert–Huang transform (HHT) method was used to analyze the time–frequency characteristics of the PM10 concentration data series measured at three different sites at the Xinglong Port of Zhenjiang, China, over three months. The HHT method consists of two main stages, namely, empirical mode decomposition (EMD) and Hilbert spectrum analysis (HSA), where the EMD technique is used to pre-process the HSA in order to determine the intrinsic mode function (IMF) components of the raw data series. The results show that the periods of the IMF components exhibit significant differences, and the short-period IMF component provides a modest contribution to all IMF components. Using HSA technology for these IMF components, we discovered that the variations in the amplitude of the PM10 concentration over time and frequency are discrete, and the range of this variation is mainly concentrated in the low-frequency band. We inferred that long-term influencing factors determine the PM10 concentration level in the port, and short-term influencing factors determine the difference in concentration data at different sites. Therefore, when formulating PM10 emission mitigation strategies, targeted measures must be implemented according to the period of the different influencing factors. The results of this study can help guide recommendations for port authorities when formulating the optimal layout of measurement devices.
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Affiliation(s)
- Xuejun Feng
- College of Habour, Coastal and Offshore Engineering, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (X.F.); (K.W.)
| | - Jinxing Shen
- College of Civil and Transportation Engineering, Hohai University, No.1, Xikang Road, Nanjing 210098, China
- Correspondence:
| | - Haoming Yang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science and Technology, No.219, Ningliu Road, Nanjing 210044, China;
| | - Kang Wang
- College of Habour, Coastal and Offshore Engineering, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (X.F.); (K.W.)
| | - Qiming Wang
- College of Science, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (Q.W.); (Z.Z.)
| | - Zhongguo Zhou
- College of Science, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (Q.W.); (Z.Z.)
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Evaluating the Environmental Performance and Operational Efficiency of Container Ports: An Application to the Maritime Silk Road. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16122226. [PMID: 31238585 PMCID: PMC6617059 DOI: 10.3390/ijerph16122226] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/18/2019] [Accepted: 06/19/2019] [Indexed: 02/06/2023]
Abstract
A major goal for port authorities, operators, and investors is to achieve efficient operations and effective environmental protection. This is because the environmental performance of a container port is important for its competitiveness and sustainable development. However, the container ports along the Maritime Silk Road (MSR) have caused numerous problems with the rapid development, among which the most significant problem is environmental pollution. In this paper, we aim to measure and compare the environmental performance and operational efficiency of ten major container ports along the MSR, including the ports of Shanghai, Hong Kong, Singapore, Kelang, Laem Chabang, Colombo, Dubai, Barcelona, Antwerp, and Hamburg. We develop an improved, inseparable data envelopment analysis (DEA) model with slack-based measures (SBMs) to evaluate and compare the environmental performance and operational efficiency, and we incorporate the desirable output of container throughput as well as the undesirable output of CO2 emission. Our results show that. Overall. these container ports perform better in terms of operational efficiency than environmental performance. We also provide insights for management and policy makers for container ports with different levels of operational efficiency and environmental performance.
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