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Environments
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Environmental Risk and Climate Change II
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Environmental Risk and Climate Change II

A special issue of Environments (ISSN 2076-3298).

Deadline for manuscript submissions: closed (1 October 2023) | Viewed by 46476

Special Issue Editor

Prof. Dr. Jason Levy

E-Mail Website
Guest Editor
Disaster Preparedness and Emergency Management, University of Hawaii, 2540 Dole Street, Honolulu, HI 96822, USA
Interests: epidemiology and prevention of congenital anomalies; psychosis and affective psychosis; cancer epidemiology and prevention; molecular and human genome epidemiology; evidence synthesis related to public health and health services research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Building on the success of the June 2022 Bonn Climate Change Conference, there is a need for more ambitious climate action, deeper cuts in greenhouse gas emissions, and enhanced resilience to adapt to the effects of climate change.

While governments agreed a package of decisions at the Glasgow Climate Pact at COP26 (the 2021 UN Climate Change Conference), the challenges linked to climate change require a multidisciplinary approach to manage climate change and related environmental, social, and financial risk, including strategies to provide financial support for developing countries, to mitigate the impact of climate change, and to adapt to global temperature rise. In order to pave the way for full implementation of the Paris Agreement, this Special Issue is seeking original papers that describe recent advances in various environmental risk issues in relation to climate shifts. While a technical perspective is welcome, an interdisciplinary, systems approach is encouraged to reduce greenhouse gas emissions and promote state-of-the-art solutions that can address climate change risk at local, national, or global scales. In this way, this Special Issue will help to prepare governments, scientists and industry for the UN Climate Change Conference (COP27) in Sharm el-Sheikh in November 2022.

The publications in the first volume, which we believe may be of interest to you, can be found here: https://www.mdpi.com/journal/environments/special_issues/climate_risk_2016.

Prof. Dr. Jason K. Levy
Guest Editor

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • case studies on climate change
  • climate change and sustainability, resilience, and vulnerability
  • environmental risk
  • trade-offs between development and environmental integrity
  • land use change and climate change, societal change, or policy change as a driver
  • climate change and poverty, marginality, and gender
  • models and analytical tools for modeling climate change
  • environmental management and sustainability

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Published Papers (10 papers)

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Research

18 pages, 3958 KiB  
Article
Drought Monitoring Using Moderate Resolution Imaging Spectroradiometer-Derived NDVI Anomalies in Northern Algeria from 2011 to 2022
by Ramzi Benhizia, Kwanele Phinzi, Fatemeh Hateffard, Haithem Aib and György Szabó
Environments 2024, 11(5), 95; https://doi.org/10.3390/environments11050095 - 4 May 2024
Viewed by 2012
Abstract
Drought has emerged as a major challenge to global food and water security, and is particularly pronounced for Algeria, which frequently grapples with water shortages. This paper sought to monitor and assess the temporal and spatial distribution of drought severity across northern Algeria [...] Read more.
Drought has emerged as a major challenge to global food and water security, and is particularly pronounced for Algeria, which frequently grapples with water shortages. This paper sought to monitor and assess the temporal and spatial distribution of drought severity across northern Algeria (excluding the Sahara) during the growing season from 2011 to 2022, while exploring the relationship between the normalized difference vegetation index (NDVI) anomaly and climate variables (rainfall and temperature). Temporal NDVI data from the Terra moderate resolution imaging spectroradiometer (MODIS) satellite covering the period 2000–2022 and climate data from the European Reanalysis 5th Generation (ERA5) datasets collected during the period 1990–2022 were used. The results showed that a considerable portion of northern Algeria has suffered from droughts of varying degrees of severity during the study period. The years 2022, 2021, 2016, and 2018 were the hardest hit, with 76%, 71%, 66%, and 60% of the area, respectively, experiencing drought conditions. While the relationship between the NDVI anomaly and the climatic factors showed variability across the different years, the steady decrease in vegetation health indicated by the NDVI anomaly corroborates the observed increase in drought intensity during the study period. We conclude that the MODIS-NDVI product offers a cost-efficient approach to monitor drought in data-scarce regions like Algeria, presenting a viable alternative to conventional climate-based drought indices, while serving as an initial step towards formulating drought mitigation plans. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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18 pages, 5602 KiB  
Article
Projected Climate Change Effects on Global Vegetation Growth: A Machine Learning Approach
by Kieu Anh Nguyen, Uma Seeboonruang and Walter Chen
Environments 2023, 10(12), 204; https://doi.org/10.3390/environments10120204 - 26 Nov 2023
Cited by 3 | Viewed by 3415
Abstract
In this study, a machine learning model was used to investigate the potential consequences of climate change on vegetation growth. The methodology involved analyzing the historical Normalized Difference Vegetation Index (NDVI) data and future climate projections under four Shared Socioeconomic Pathways (SSPs). Data [...] Read more.
In this study, a machine learning model was used to investigate the potential consequences of climate change on vegetation growth. The methodology involved analyzing the historical Normalized Difference Vegetation Index (NDVI) data and future climate projections under four Shared Socioeconomic Pathways (SSPs). Data from the Global Inventory Monitoring and Modeling System (GIMMS) dataset for the period 1981–2000 were used to train the machine learning model, while CMIP6 (Coupled Model Intercomparison Project Phase 6) global climate projections from 2021–2100 were employed to predict future NDVI values under different SSPs. The study results revealed that the global mean NDVI is projected to experience a significant increase from the period 1981–2000 to the period 2021–2040. Following this, the mean NDVI slightly increases under SSP126 and SSP245 while decreasing substantially under SSP370 and SSP585. In the near-term span of 2021–2040, the average NDVI value of SSP585 slightly exceeds that of SSP245 and SSP370, suggesting a positive vegetation development in response to a more pronounced temperature increase in the near term. However, if the trajectory of SSP585 persists, the mean NDVI will commence a decline over the subsequent three periods (2041–2060, 2061–2080, and 2080–2100) with a faster speed than that of SSP370. This decline is attributed to the adverse effects of a rapid temperature rise on vegetation. Based on the examination of individual continents, it is projected that the NDVI values in Africa, South America, and Oceania will decline over time, except under the scenario SSP126 during 2081–2100. On the other hand, the NDVI values in North America and Europe are anticipated to increase, with the exception of the scenario SSP585 during 2081–2100. Additionally, Asia is expected to follow an increasing trend, except under the scenario SSP126 during 2081–2100. In the larger scope, our research findings carry substantial implications for biodiversity preservation, greenhouse gas emission reduction, and efficient environmental management. The utilization of machine learning technology holds the potential to accurately predict future changes in vegetation growth and pinpoint areas where intervention is imperative. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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12 pages, 837 KiB  
Article
The Impact of Climate Change on Environmental Sustainability and Human Mortality
by Xingzhi Mara Chen, Andrew Sharma and Hua Liu
Environments 2023, 10(10), 165; https://doi.org/10.3390/environments10100165 - 22 Sep 2023
Cited by 9 | Viewed by 11200
Abstract
Climate dictates the critical aspects of human environmental conditions. The frequency and intensity of extreme weather conditions due to human-induced climate change have alarmingly increased. Consequently, climate change directly affects environmental sustainability and human mortality in the short term and creates prolonged and [...] Read more.
Climate dictates the critical aspects of human environmental conditions. The frequency and intensity of extreme weather conditions due to human-induced climate change have alarmingly increased. Consequently, climate change directly affects environmental sustainability and human mortality in the short term and creates prolonged and complicated long-term indirect grave risks. This paper examines three-level environmental impact risks associated with climate change on human mortality. It proposes a conceptual framework for developing an empirical event-based human mortality database related to climate change and communication strategies to enhance global environmental adaptation, resilience, and sustainability. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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22 pages, 2466 KiB  
Article
Assessing Coastal Erosion and Climate Change Adaptation Measures: A Novel Participatory Approach
by Carlos Coelho, Márcia Lima, Filipe M. Alves, Peter Roebeling, Joaquim Pais-Barbosa and Marco Marto
Environments 2023, 10(7), 110; https://doi.org/10.3390/environments10070110 - 26 Jun 2023
Cited by 4 | Viewed by 6158
Abstract
This work aims to provide a more complete characterization of coastal erosion mitigation and climate change adaptation measures by presenting a participatory approach that integrates medium- to long-term perspectives, considering simultaneously social, environmental, economic and engineering dimensions to help decision makers implement sustainable [...] Read more.
This work aims to provide a more complete characterization of coastal erosion mitigation and climate change adaptation measures by presenting a participatory approach that integrates medium- to long-term perspectives, considering simultaneously social, environmental, economic and engineering dimensions to help decision makers implement sustainable climate change adaptation (CCA) strategies. The work lists, explains and characterizes existing climate change mitigation and adaptation measures as well as their costs and positive and negative social, environmental and economic impacts, in three distinct databases. These databases are discussed, complemented and validated in participatory moments with local stakeholders of the Ovar Municipality, Portugal, which represents the case study to support the proposed methodology. Although Ovar is a pilot case, the integrated framework for resilient CCA has a global application with respect to methodologies and concepts. The proposed approach is useful to help coastal management entities to engage in more efficient, effective and beneficial planned action to mitigate coastal erosion and adapt to future climate change effects. The open-source databases and the participatory approach facilitate decision makers and coastal communities to navigate the complexity of solutions and build consensus around collective actions for coastal areas. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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14 pages, 2345 KiB  
Article
Resilience Appraisal of Water Resources System under Climate Change Influence Using a Probabilistic-Nonstationary Approach
by Saddam Q. Waheed, Maryam N. Alobaidy and Neil S. Grigg
Environments 2023, 10(5), 87; https://doi.org/10.3390/environments10050087 - 14 May 2023
Cited by 3 | Viewed by 2294
Abstract
The planning and management of water resources are being impacted by climate change, and are in need of comprehensive adaptation strategies to respond to future projections. The goal of this study is to support those strategies with a new decision-making paradigm that employs [...] Read more.
The planning and management of water resources are being impacted by climate change, and are in need of comprehensive adaptation strategies to respond to future projections. The goal of this study is to support those strategies with a new decision-making paradigm that employs a probabilistic-nonstationary hydroclimatic scenario to examine the long-term system resilience for multiple dam objectives. The modified approach to examine resilience was applied, and uses a bottom-up approach with a modified resilience concept to achieve the long-term operation targets. The approach integrates Global Circulation Models (GCMs) with a statistical weather generator (SWG) to produce a range of future scenarios. Then, the system response is evaluated against those scenarios. The study utilizes a pre-developed SWG to synthesize different trajectories by altering three weather variables: the precipitation amount, temperature mean, and wind-speed magnitude. The proposed has four staged phases: (1) identification of the future climate exposure using different GCMs; (2) future water supply estimation for scenarios using hydrological models; (3) future water demand estimation for scenarios of all system stakeholders; and (4) evaluation of system performance resilience for the dam operational purposes. The Diyala River Basin in Iraq was selected as a case study, to apply the suggested paradigm. The analysis of the GCM outputs revealed that the rainfall mean varies between −37% and +31%; temperature mean varies between +0.4 °C and 5.1 °C; and the mean wind speed varies between −22% and 11%. Based on these ranges, the future climate trajectories were simulated. According to the examination of the system’s response to those weather changes, the precipitation is the most effective parameter, followed by the temperature change, and lastly the wind speed. Furthermore, the findings show that the existing system operating rules are reliable in terms of flood protection but vulnerable in terms of drought management. The analysis of system resilience to manage the drought was found to be 0.74 for the future trajectories, while it was 0.91 for flood protection. This indicates that project managers should prioritize the drought and water scarcity management, due to climate change impact and upstream country development. The study also shows that the suggested resilience paradigm is capable of measuring the negative effects of climate change and able to provide long-term adaptation guidance for water resources management. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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21 pages, 2945 KiB  
Article
Rural Agriculture and Poverty Trap: Can Climate-Smart Innovations Provide Breakeven Solutions to Smallholder Farmers?
by Akaniyene Ignatius Akpan and Dimitrios Zikos
Environments 2023, 10(4), 57; https://doi.org/10.3390/environments10040057 - 24 Mar 2023
Cited by 7 | Viewed by 5594
Abstract
Agriculture is widely recognized as a solution to food insecurity and poverty, especially in rural areas. However, 75% of the world’s poor live in rural areas, and agriculture is the primary source of their livelihood. One may wonder if the observed correlation between [...] Read more.
Agriculture is widely recognized as a solution to food insecurity and poverty, especially in rural areas. However, 75% of the world’s poor live in rural areas, and agriculture is the primary source of their livelihood. One may wonder if the observed correlation between agriculture and poverty also suggests causation. If that is the case, then what such causal relationship might exist? Is agriculture a vehicle for poverty alleviation or a source of poverty trap? The role of climate change is rather undisputed: associated extreme weather phenomena cause severe negative impacts on agriculture, exacerbating rural poverty. However, climate-smart agriculture (CSA) is acclaimed to potentially reverse the situation by eliminating poverty and food insecurity. Against this backdrop, the paper investigates whether smallholder farmers who adopt CSA could achieve food security and better income. This aim was approached through three key research objectives (i) to examine the effects of climate change on smallholder farmers, (ii) to examine the extent to which smallholder farmers adopt CSA and the barriers to adoption, and (iii) to investigate empirically the effects of CSA practices in terms of food security and poverty alleviation. The Upper West and Upper East regions in Ghana were selected purposively for the case study, and the data collected were analyzed using inferential and descriptive techniques. The results revealed no statistically significant positive relationship between the adoption of CSA with food security and income. Poor socioeconomic and market conditions marred the expected positive effects of CSA, hence the need for the provision of agricultural infrastructures and inputs as well as the creation of market for commodities. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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19 pages, 2487 KiB  
Article
Long-Term Changes of Positive Anomalies of Erythema-Effective UV Irradiance Associated with Low Ozone Events in Germany 1983–2019
by Gudrun Laschewski and Andreas Matzarakis
Environments 2023, 10(2), 31; https://doi.org/10.3390/environments10020031 - 15 Feb 2023
Cited by 3 | Viewed by 3020
Abstract
In order to assess whether there is an increasing need for adaptation to the associated human health risks, the long-term occurrence (1983–2019) of low-ozone events (LOEs) with associated near-surface anomalies of erythema-effective UV irradiance was examined using an impact-related approach. Based on satellite [...] Read more.
In order to assess whether there is an increasing need for adaptation to the associated human health risks, the long-term occurrence (1983–2019) of low-ozone events (LOEs) with associated near-surface anomalies of erythema-effective UV irradiance was examined using an impact-related approach. Based on satellite data, means of four locations in Germany (Sylt, Berlin, Frankfurt, Munich) were compared for three subperiods (T1: 1983–1989, T2: 1990–1997, T3: 1998–2019). The period of peak global ozone depletion in the 1990s (T2) is characterized by a larger frequency of LOEs than the preceding (T1) and the subsequent (T3) subperiods. During the most recent subperiod (T3), the mean number of LOEs is 1.1 ± 0.5 events/year, with a variability of 0 to 4.2 ± 0.8 events/year, and shows a statistically significant decrease in the annual number of −4.8%/year. The annual totals of the LOE-associated anomalies of the erythema-effective UV radiation dose show no trend during T3. With regard to LOE-associated UV index anomalies, spring is the season most affected by LOEs, with more than half of all cumulative UV peak loads, while the absolute maximum values of the LOE-associated UV index anomaly of about 1.8 UV index occur near the summer solstice. Within the most recent subperiod (T3), summer contributes an increasing share of the peak loads. Overall, the study confirms that LOEs pose health risks due to intermittent, pronounced positive anomalies in erythema-effective UV irradiance and therefore require special attention and adaptation measures. Long-term changes can be identified, but to date there has been no evidence of an increasing health risk in Germany. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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11 pages, 5386 KiB  
Article
Ecotoxicological Assessment of Potentially Toxic Elements in Waterworks Sludge Amended Soils Using Bermudagrass Bioassay
by Sai Leung Ng
Environments 2023, 10(2), 28; https://doi.org/10.3390/environments10020028 - 3 Feb 2023
Viewed by 2487
Abstract
Waterworks sludge has the potential to be used as a soil amendment, but the ecotoxicological risk of potentially toxic elements should not be underestimated. In this regard, this study determined the contents of nine potentially toxic elements (Cr, Ni, Cd, Cu, Pb, Zn, [...] Read more.
Waterworks sludge has the potential to be used as a soil amendment, but the ecotoxicological risk of potentially toxic elements should not be underestimated. In this regard, this study determined the contents of nine potentially toxic elements (Cr, Ni, Cd, Cu, Pb, Zn, As, Mn, and Al) of bermudagrass [Cynodon dactylon (L.) Pers.] grown in waterworks sludge amended soils. Treatments involved different loading rates of waterworks sludge, soil types, and fertilization options that represented different scenarios of greening applications. The recommended metal levels in plant tissues and maximum tolerable levels for feeding cattle are adopted as benchmarks for gauging the ecotoxicological risk to the first and second trophic levels of the ecosystem, respectively. No recommended levels for potentially toxic elements are exceeded when sludge loading rate is not higher than 50% (wt/wt). When various fertilization treatments are applied to 25% (wt/wt) sludge amended soils, the accumulation of aluminum and zinc deserves our attention because a few samples exceed the recommended levels. They are mainly samples of below-ground biomass. Overall, using waterworks sludge as a soil amendment does not cause an obvious ecotoxicological risk. The findings can provide a valuable reference to other cities for the sustainable management of waterworks sludge. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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20 pages, 3867 KiB  
Article
Regional Climate Change Effects on the Viticulture in Portugal
by Rainer Ferdinand Wunderlich, Yu-Pin Lin and Andrianto Ansari
Environments 2023, 10(1), 5; https://doi.org/10.3390/environments10010005 - 22 Dec 2022
Cited by 3 | Viewed by 4506
Abstract
The grapevine (Vitis vinifera) is widely cultivated for the production of wine and other commodities. Wine is globally traded, with an annual market value of approximately USD 4 billion in Portugal alone. However, climate change is expected to profoundly alter regional [...] Read more.
The grapevine (Vitis vinifera) is widely cultivated for the production of wine and other commodities. Wine is globally traded, with an annual market value of approximately USD 4 billion in Portugal alone. However, climate change is expected to profoundly alter regional temperature and precipitation regimes across the Iberian Peninsula and, thus, in continental Portugal, potentially threatening to impact viticulture. We used boosted regression trees and environmental variables describing the climate, soil, topography, and irrigation with a large number of presences (N = 7002) to estimate grapevine suitability for a baseline (1981–2010) and three future periods spanning from 2011 to 2100 using two climate trajectories (SSP3-7.0 and SSP5-8.5) and irrigation scenarios (continued and ceased). Under SSP3-7.0 with irrigation and SSP5-8.5 without irrigation, our results suggest a decline in suitable viticulture area across continental Portugal of ~20% and ~80% by 2041–2070 and 2011–2041, respectively. Following this decline, our data suggest a potential recovery by 2071–2100 of ~6% and ~186%, respectively. However, regional change is more complex: by 2071–2100, the Região Norte, the Douro wine region, and the Algarve, for example, each would experience future changes in suitable area in the range of approximately −92% to −48%, −86% to −24%, and −59% to 267%, respectively, depending mostly on the practicality of irrigation. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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13 pages, 1945 KiB  
Article
Impacts of Climatic Variability on Agricultural Total Factor Productivity Growth in the Southern United States
by Kartik Joshi, Michée A. Lachaud, Daniel Solís and Sergio Alvarez
Environments 2022, 9(10), 129; https://doi.org/10.3390/environments9100129 - 11 Oct 2022
Cited by 3 | Viewed by 3981
Abstract
This study investigates the impact of climatic variability on both agricultural production and total factor productivity (TFP) in the Southern United States (US). It also aims at identifying the drivers of productivity in this region. The analysis is tailored to inform decision makers [...] Read more.
This study investigates the impact of climatic variability on both agricultural production and total factor productivity (TFP) in the Southern United States (US). It also aims at identifying the drivers of productivity in this region. The analysis is tailored to inform decision makers about effective policy options to increase and sustain productivity in this important agricultural region. We use data from the US Department of Agriculture, National Climatic Data Center, and US Geological Survey to estimate alternative stochastic production frontier models. The estimated parameters are then analyzed and used to compute and decompose TFP into several measures of efficiency. The results show that agricultural production in the Southern US is more responsive to labor and has been increasing at a 1.13 percent rate annually. The findings also suggest that while precipitation, on average, has a positive and significant impact on productivity, intra-annual variation in both temperature and precipitation, which can be considered as anomalies, has a negative and significant impact on production. The impact of climatic effects on productivity across states is mixed and technological progress has been the main driver of TFP growth. Findings indicate that climatic variability is having a negative impact on agricultural productivity in the Southern US, similar in magnitude to the positive impact of irrigation. Full article
(This article belongs to the Special Issue Environmental Risk and Climate Change II)
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