Impact Of Climate Change Factors Research Articles

Bibliometric Review of Passive Cooling Design Strategies and Global Thermal Comfort Assessment: Theories, Methods and Tools

Globally, a variety of factors, ranging from ethnicity and occupants’ lifestyles to the local climate characteristics of any studied location, as well as people’s age, can affect thermal comfort assessments. This review paper investigates the energy effectiveness of state-of-the-art passive systems in providing neutral adaptive thermal comfort for elderly people by exploring passive design strategies in four distinct climates, namely Canada, India, Abu Dhabi and the Eastern Mediterranean basin. The aim of the study is to analyse the available data provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers’ (ASHRAE) Global Thermal Comfort Database II, version 2.1. The main objective of the study is to develop an effective methodological framework for the on-going development of adaptive thermal comfort theory. To this extent, this study presents a comprehensive review of the assessment of energy effectiveness of passive design systems. To accomplish this, the impact of climate change factors in passive design systems was investigated. A meta-analysis method was adopted to determine the input variables for the statistical analysis. Cramer’s V and Fisher’s Exact tests were used to assess occupants’ thermal sensation votes (TSVs). The findings revealed that there are discrepancies detected between the in situ field experiments and the data recorded in the ASHRAE Global Thermal Comfort Database II. The study findings contribute to the development of adaptive thermal comfort theory by reviewing the existing methodologies globally. Furthermore, a critical review of the significance of occupants’ age differences should be conducted in the identification of neutral adaptive thermal comfort.

The Impact of Climate Change Factors on Financial Markets: Evidence from China

ABSTRACT This paper examines the impact of climate change factors, namely Climate Risk Index (CRI), Climate Policy Index (CPI), and Climate Concern Index (CCI), on China’s financial markets. By employing quantile vector autoregression model and conducting network analysis, this paper intends to reveal the dynamic relationship and the risk transmission mechanism between climate factors and various financial markets under different market conditions based on the data ranging from Nov.1, 2011 to December 31, 2021. We find that climate shocks intensify the risk contagion among China’s financial markets, and the impact induced by each factor would present heterogeneity. The results also indicate that the systemic importance of climate shock index varies across market conditions. The findings shed light on the complex interaction between climate shocks and financial markets, which should contribute to policy implications for financial market stability and risk prevention.

Geospatial Patterns of Non-Melanoma Skin Cancer in Relation to Climate Changes in Iran.

The purpose of this study is to examine the impact of climate change factors on the incidence of skin cancer in Iran. The statistical population for this study comprises skin cancer patients in Iran. All other data used in this research were extracted from Remote Sensing imagery, including Ultraviolet ray, Relative humidity, Cloud cover, incoming short-wave flux, elevation, and total hours of sunshine. Initially, spatial autocorrelation analysis and cluster patterns were calculated using General G and Moran's I indices. Subsequently, a Geographically Weighted Regression Model was used to establish a regression relationship between the climate change data and the detection and forecasting rate of skin cancer. Finally, the model's accuracy was evaluated by estimating the detection coefficient between the reality map and the forecasting map. The study found that UV radiation and relative humidity exhibit the highest positive and negative correlation, respectively, with the skin cancer rate in Iran. Geostatistical analysis revealed a clustered spatial distribution of skin cancer rates, and the proposed GWR model demonstrated high accuracy in predicting the skin cancer rate. The results indicate the highest positive correlation (+0.51) for UV ray and the most negative correlation (-0.43) for relative humidity. The Geostatistical analysis reveals spatial autocorrelation, cluster patterns, and non-randomness of the data. The detection rate of skin cancer increases from north to south and from west to east.

Study of the Impact of Climate Change Factors, Management Practices, and Labor Availability on Productivity of Agricultural Resource Management: The Case of Fruit Farmers in Binjai

Climate change poses significant challenges to agricultural systems, affecting productivity and sustainability. This study investigates the impact of climate change factors, management practices, and labor availability on agricultural resource management productivity among fruit farmers in Binjai. A sample of 121 farmers was surveyed, and data were analyzed using IBM SPSS. Results indicate a 1.5°C temperature increase over the past decade, negatively correlating with crop yields. Diverse management practices were observed, with integrated pest management positively influencing productivity. Labor availability exhibited seasonal variations, influenced by migration patterns. Spatial analysis highlighted temperature-sensitive clusters and regions prone to extreme weather events. The findings provide actionable insights for tailored interventions, emphasizing the need for climate-resilient strategies in Binjai's fruit farming.

ASSESSMENT OF INTERDEPENDENT CHANGES OF NEXUS FLUXES ON THE IMPACT OF CLIMATE CHANGE & LAND USE ON THE EXAMPLE OF THE DISTRICTS ALONG THE SYR DARYA

This research investigates the interplay between socioeconomic and environmental indicators in the Kyzylorda district along the Syr Darya River. Through an analysis of the food, energy, and water (FEW) functions and their implications for sustainable development, this study offers valuable insights for policymakers and practitioners. Specifically, we examine the impact of climate change factors, such as precipitation and temperature, on the production and yield of three key crops: wheat, rice, and corn. To conduct this study, we utilized daily temperature and precipitation data from the preceding years of 2021 and 2022, along with corresponding crop yield data for the same period. Our methodology draws upon established practices, including correlation analysis to assess the relationship between climatic factors and crop yield. Additionally, regression analysis enables us to develop predictive formulas to anticipate the effects of future climate changes on crop yield and agricultural practices in the region. Moreover, ANOVA employed to measure variations in daily temperature and precipitation during the certain period.

The Transformation Policy of Energy Enterprises under the "Double Carbon" Policy and the Causes and Risks of the Green Premium

When the climate problem is becoming more and more serious, and the impact of climate change factors on financial markets is becoming more and more significant, Chinese President Xi Jinping has put forward the 3060 "double carbon target." In order to respond positively to national policies, most energy enterprises have responded to obtain a green premium. This paper gives an example of the "green" measures taken by two different types of enterprises: the limited liability company and the joint stock limited company. It analyzes why they get the green premium. While bringing benefits, the green premium also brings macro and micro risks. This paper puts forward some solutions that these energy enterprises can use to deal with the risks posed by the green premium: ESG rating system is used to disclose the risk of energy enterprises, as well as the use of various means to disclose the possible behavior of the government to protect the risk and guide investors to invest rationally. It is hoped that through this paper, various energy enterprises can pay attention to the potential risks and remind investors to invest rationally in energy enterprises.

Climate Change and Effects on Molds and Mycotoxins.

Earth’s climate is undergoing adverse global changes as an unequivocal result of anthropogenic activity. The occurring environmental changes are slowly shaping the balance between plant growth and related fungal diseases. Climate (temperature, available water, and light quality/quantity; as well as extreme drought, desertification, and fluctuations of humid/dry cycles) represents the most important agroecosystem factor influencing the life cycle stages of fungi and their ability to colonize crops, survive, and produce toxins. The ability of mycotoxigenic fungi to respond to Climate Change (CC) may induce a shift in their geographical distribution and in the pattern of mycotoxin occurrence. The present review examines the available evidence on the impact of CC factors on growth and mycotoxin production by the key mycotoxigenic fungi belonging to the genera Aspergillus, Penicillium, and Fusarium, which include several species producing mycotoxins of the greatest concern worldwide: aflatoxins (AFs), ochratoxins, and fumonisins (FUMs).

Efficiency assessment of coal mine use and land restoration: Considering climate change and income differences

Coal burning is still the main source of power generation in many Asian countries and is also the biggest cause of climate change. This research thus employs meta dynamic two-stage SBM (slack-based measure) under the exogenous model to examine 24 provinces in China as the research object. The first stage evaluates the efficiency of coal mining, taking employment in the coal industry and fixed assets in the mining industry as inputs, the development of non-oil and gas mineral resources a desirable output, and land damage as undesirable output and link. The second stage assesses the efficiency of land recovery, using land recovery funding as the input and recovery area as the output, and considers the climate change effect. The contribution herein is to discuss the degree of land destruction and the efficiency of land recovery through the different economic environments of different provinces and to divide the two groups by GDP. We also introduce high and low temperature days as exogenous variables to highlight the impact of climate change factors and to expose efficiency issues that may be underestimated. The results are as follows. (1) The efficiency value of the coal mining stage is higher than that of the land recovery stage, showing that China still pays more attention to economic benefits and ignores environmental responsibility issues. (2) More than 90% of China's provinces have coal mining expertise, but 70% of the provinces have low land recovery performance. (3) Eight provinces did not follow the Atmospheric Pollution Prevention Action Plan (APCP), the efficiency of coal mining deteriorated after the implementation of the policy. (4) Before the implementation of the APCP, land recovery in high GDP provinces was less efficient than in low GDP provinces. (5) Activating the APCP policy does not help technology upgrade. (6) The APCP policy caused the provinces to misevaluate their investments in fixed assets and misdirected their decisions on land recovery funding. However, the efficiency of land recovery after the implement of APCP was better. (7) Neglecting climatic factors causes serious errors in coal mine efficiency.

Field experiments and model simulation based evaluation of rice yield response to projected climate change in Southeastern China

Evaluating the impact of climate change factors, especially temperature and carbon dioxide (CO2), on rice yield is essential to ensure future food security. Because of the wide biogeographical distribution of rice, such evaluations are conducted exclusively through modeling efforts. However, geographical forecasts could, potentially, be improved by the inclusion of field-based data on projected increases in temperature and CO2 concentration from a given rice-growing region. In this study, the latest version of the ORYZA (v3) crop model was evaluated with additional yield data obtained from a temperature-controlled free-air CO2 enrichment system (T-FACE) in Southeastern China. ORYZA (v3) results were then evaluated in the context of phase five of the Coupled Model Intercomparison Project (CMIP5) for representative concentration pathways (RCP) 4.5 and RCP 8.5 using five global change models (GCMs). Our findings indicate that climate change, i.e., inclusion of CO2 and temperature effects, decreased mean rice yield by 3.5%, and 9.4% for RCP 4.5; and by 10.5 and 47.9% for RCP 8.5 for the scenarios in the 2050s and 2080s, respectively. The CO2 fertilizer effect partially compensated but did not offset the negative impacts of rising temperature on rice yields. Warmer temperatures were the primary factor that influenced yield by adversely affecting the spikelet fertility factor and spikelet number. Overall, climate change would have positive effects on rice yields until the middle-century in Southeastern China but negative effects were noted by the end of the century. These results may be of interest for informing policy makers and developing appropriate strategies to improve future rice productivity for this region of China.

Spatial analysis of the impact of climate change factors and adaptation strategies on productivity of wheat in Ethiopia

Wheat production is expected to be challenged by future climate change. However, it is unclear how wheat grown in diverse agroecologies will respond to climate change and adaptation management strategies. A geospatial simulation study was conducted to understand the impacts of climate change and adaptation management strategies on wheat (Triticum aestivum L.) production in Ethiopia. Simulation results showed that the average long-term baseline (1980–2005) wheat yield ranged from 1593 to 3356 kg/ha. This wheat yield range is within the national average (2100–2700 kg/ha) for this decade. In regions with cooler temperatures (<21 °C), mid-century temperatures and elevated CO2, along with increased N fertilizer slightly improved attainable yield levels above 3000 kg/ha. Whereas, in regions with heat and drought conditions wheat yield declined regardless the increase of N or CO2 levels. Wheat yield increased at a diminishing rate with increase in N fertilizer rate. However, N fertilizer did not increase yields under low rainfall conditions. Two to five irrigation per season contributed to yield improvement for low rainfall locations, while yield did not substantially improve for locations receiving adequate seasonal rainfall. Therefore, based on this study, improved N fertilizer application in combination with increased CO2 could improve wheat yield under future climate in most wheat producing regions (with adequate rainfall) of Ethiopia. Our results provide valuable information regarding impacts of climate change factors and adaptation strategies for producers, researchers, extension professionals and policy makers.

Impact of Climate Change on Agricultural Total Factor Productivity Based on Spatial Panel Data Model: Evidence from China

To respond to the adverse impact of climate change on agricultural total factor productivity, the question of how to adopt actively appropriate strategies is particularly critical for the stakeholders. However, the previous researchers have paid more attention to investigating the measure methods, regional differences, and determinants of Chinese agricultural total factor productivity, but the possible impact of climate change factors like rainfall, temperature, and evaporation on regional agricultural total factor productivity in China have not yet received the attention that they deserve. Furthermore, more importantly, the study on how to take active measures to reduce and mitigate the negative effects from climate change is relatively small. Therefore, in allusion to the above-mentioned problems, using the data envelopment analysis and building a spatial panel data model embedded with climate change factors, this paper calculated Chinese agricultural total factor productivity and then explored the possible impact of climate change on regional agricultural total factor productivity at a provincial level in China. Results mainly show that the impact of some factors, like annual total precipitation, average temperature in the growing season, and evaporation intensity on regional agricultural total factor productivity, are all very significant and negative, which suggests that the more precipitation, the higher the temperature is, and the higher evaporation intensity would lower agricultural total factor productivity in China. Furthermore, in order to response to mitigate the adverse effects from climate change on agricultural total factor productivity, local governments should continue to increase financial support for the local agricultural economic development, because this action could be beneficial for the related stakeholders in improving agricultural total factor productivity. Summing up, our evidence study would provide an important basic theory basis in terms of increasing agricultural total factor productivity and promoting regional agricultural economic development in China.

Timing of critical developmental stages and leaf production in field-grown spring wheat for use in crop models

Detailed information on the timing of terminal spikelet formation, anthesis, maturity and the rate of leaf appearance is crucial to the predictive accuracy of the AFRCWHEAT2 growth simulation model for wheat. To obtain appropriate data under different growing conditions for two spring wheat (Triticum aestivum L.) cultivars (cvs Minaret and Canon), a main field experiment was conducted comprising eight sowing dates between mid-March and late June 1994; data from single sowings of Minaret in 1992 and 1995 were also included in the analysis. Minaret is the focus of a major European study of the impact of climate change factors on the growth and development of wheat, and data of the type reported here were essential to support the modelling aspects of the project involving AFRCWHEAT2.The accumulated thermal time from emergence to critical developmental stages was similar for all sowings of both cultivars, even though biomass was greatly reduced in the later sowings. Although final leaf numbers were comparable for all sowing dates, the rate of leaf appearance was correlated with the rate of change of day length at crop emergence in Minaret. The unmodified AFRCWHEAT2 model did not predict the timing of critical growth stages and leaf numbers well, but removal of the vernalization and photoperiod factors from the developmental sub-model greatly improved the accuracy of such predictions. These results strongly suggest that fixed quantities of thermal time may be employed successfully to predict the timing of critical developmental stages of these spring wheat cultivars over a range of sowing dates, geographic locations and climatic conditions, since development appeared to be a linear function of temperature.Despite removing the photoperiod and vernalization functions, the model consistently over-predicted final leaf number because leaf production by the model continued until 1·8 phyllochrons before anthesis, as compared to the three phyllochrons actually recorded for Minaret. AFRCWHEAT2 could therefore be further modified to reproduce more accurately the smaller number of leaves typical of these spring cultivars.

Impact of climate change factors on the clonal sedge Carex bigelown: implications for population growth and vegetative spread

Hypothesized life‐cycle responses to climate change for the arctic, clonal perennial Carex bigelown are constructed using a range of earlier observations and experiments together with new information from monitoring and an environmental perturbation study These data suggest, that under current climate change scenarios, increases in CO2, temperature and nutrient availability would promote growth in a qualitatively similar way The evidence suggests that both tiller size and daughter tiller production will increase, and be shifted towards production of phalanx tillers which have a greater propensity for flowering Furthermore, age at tillering as well as tiller life span may decrease, whereas survival of younger age classes might be higher Mathematical models using experimental data incorporating these hypotheses were used to a) integrate the various responses and to calculate the order of magnitude of changes in population growth rate (γ). and b) to explore the implications of responses in individual demographic parameters for population growth rate The models suggest that population growth rate following climate change might increase significantly, but not un‐realistically so. with the younger, larger, guerilla ullers being the most important tiller categones in contributing to X The rate of vegetative spread is calculated to more than double, while cyclical trends in flowering and populauon growth are predicted to decrease substantially