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The urban heat island is an unintended consequence of humans building upon rural and native landscapes. We hypothesized that variations in vegetation and land use patterns across an urbanizing regional landscape would produce a temperature distribution that was spatially heterogeneous and correlated with the social characteristics of urban neighborhoods. Using biophysical and social data scaled to conform to US census geography, we found that affluent whites were more likely to live in vegetated and less climatically stressed neighborhoods than low-income Latinos in Phoenix, Arizona. Affluent neighborhoods had cooler summer temperatures that reduced exposure to outdoor heat-related health risks, especially during a heat wave period. In addition to being warmer, poorer neighborhoods lacked critical resources in their physical and social environments to help them cope with extreme heat. Increased average temperatures due to climate change are expected to exacerbate the impacts of urban heat islands.

Purpose – This work aims to study the treatment of adsorbant on the increasing liquid hydrocarbon quality produced by pyrolysis low density polyethylene (LDPE) plastic waste at low temperature. The hydrocarbon distribution, physicochemical properties and emission test were also studied due to its application in internal combustion engine. This research uses pure Calcium carbonate (CaCO₃) and pure activated carbon as adsorbant, LDPE type clear plastic samples with control variable that is solar gas station.

Design/Methodology/Approach – LDPE plastic waste of 10 kg were vaporized in the thermal cracking batch reactor using LPG 12 kg as fuel at range temperature from 100 to 300°C and condensed into liquid hydrocarbon. Furthermore, this product was treated with the mixed CaCO₃ and activated carbon as adsorbants to decrease contaminant material.

Findings – GC-MS identified the presence of carbon chain in the range of C6–C44 with 24.24% of hydrocarbon compounds in the liquid. They are similar to diesel (C6–C14). The 30% of liquid yields were found at operating temperature of 300°C. The calorific value of liquid was 46.021 MJ/Kg. This value was 5.07% higher than diesel as control.

Originality/Value – Hydrocarbon compounds in liquid produced by thermal cracking at a low temperature was similar to liquid from a catalytic process.

In this chapter the potential to use water-based Trombe walls to provide heated water for building applications during the summer months is investigated. Design Builder software is used to model a simple single-story building with a south-facing Trombe wall. The effects of using different thermal storage mediums within the Trombe wall on building heating loads during the winter and building cooling loads during the summer are modeled. The amount of thermal energy stored and temperature of water within the thermal storage medium during hot weather conditions were also simulated. On a sunny day on Toronto, Canada, the average temperature of the water in a Trombe wall integrated into a single-story building can reach ∼57°C, which is high enough to provide for the main hot water usages in buildings. Furthermore, the amount of water heated is three times greater than that required in an average household in Canada. The results from this work suggest that water-based Trombe walls have great potential to enhance the flexibility and utility of Trombe walls by providing heated water for building applications during summer months, without compromising performance during winter months.

Purpose – The vulnerability and adaptive capacities of cities in Latin America have received relatively less attention compared to other regions of the world. This chapter seeks to address these gaps by (a) examining vulnerability to the health impacts from air pollution and temperature, and exploring whether socioeconomic factors between neighborhoods differentiate these risks within the cities of Bogota, Buenos Aires, Mexico City, and Santiago and (b) assessing the capacity of urban populations to perceive and respond to vulnerability and risk.

Design/methodology/approach – Because of the complex nature of vulnerability, we combined a set of quantitative and quantitative methods and data to determine whether and under what conditions the people in these cities are vulnerable (e.g., Time Series Analysis, Generalized Linear Model, and statistical correlations of exposure and human mortality with socioeconomic vulnerability).

Findings – We found high levels of PM10, ozone, and other criteria air pollutants in three cities for which we had data. However, the pattern of their impacts on health depends on the particulars of pollutant levels and atmospheric and weather conditions of each city. Our results reflect the varied facets of urban vulnerability and shed light on the nature of the associated human health risks. Although wealthy populations have access to education, good quality housing, and health services to mitigate some environmental risks, overall the data show that health impacts from air pollution and temperature in the study cities do not necessarily depend on socioeconomic differentiations.

Research limitations/implications – Although we sought to use quantitative and qualitative methods, given the complexity of the research, it has proven difficult to fully explore these issues across scales and with a full accounting of local context.

Practical implications – Our findings show that wealthy and educated populations may be equally at risk to the health implications of air pollution. Policies designed to mitigate these risks should not use socioeconomic characteristics as predictors of a population's risk in relation to air pollution.

Originality/value – This research contributes valuable insights into the dynamics of vulnerability to air pollution in Latin American cities, a region that has been historically underrepresented in empirical studies of urban risk. We have also combined a range of methods and approaches to improve our understanding of the multifaceted nature of urban vulnerability to global environmental change.

The major component of agriculture production includes the type of seed, soil, climatic conditions, irrigation pattern, fertilizer, weed control, and technology used. Soil is one of the prime elements in modern times for agriculture. Soil is also one of the primary and important factors for crop production. The available soil nutrient status and external applications of fertilizers decide the growth of crop productivity (Annoymous, 2017). The upcoming research question that needs to be addressed is What is the application of soil data on soil health management for sustaining agriculture? Driven by the need, the aim of the present study is (a) to explore the soil parameters of a district, (b) compare the values with the standards, and (c) pave a way for mapping the crops with suitability of soil health. This study will not only be beneficial for the district to take appropriate steps to improve the soil health but also would help in understanding the causal relationship among soil health parameters, cropping pattern, and crop productivity.

Over the last decades, there has been an increasing interest among scientists on the linkage between population health and climate and environmental factors, as well as health impacts of climate change and climate variability. Numerous studies have been done and substantial results achieved, but mostly in the developed countries, and not much quantitative evidence or assessment of the impacts at national and local levels has been provided for developing countries.

The relationship between electricity demand and weather in the United States has been studied as of late due to increased demand, de-regulation, and new pricing models. The influence of weather or seasonality in energy consumption, particularly electricity demand, has been widely researched. A significant scientific interest in the seasonality of energy consumption has led to an important number of papers exploring the role of weather variability and change on energy consumption. Most of these papers model demand as a function of seasonal climate factors.

The goal of this research is a broad examination of monthly residential electricity demand for a region of the mid-Atlantic using Excel and step-wise regression. This is achieved by using a sequence of models built in Excel in which different patterns are gradually introduced in the estimations. Data over a seven-year period is utilized. A backward elimination step-wise regression analysis is employed to determine which independent variables best model the data. Initial independent variables included high monthly temperature, low monthly temperature, time, year, month, seasonal quarter, and introduction of a “green” tax credit for solar and wind energy.

Models for forecasting the electricity demand and the predictive power of these models is assessed. The work is organized as follows: Data description and the methodology, trend and the seasonality of electricity usage in the mid-Atlantic region, the predictive power and seasonality of the models, and main conclusions drawn from the study.

This chapter aims to identify new perspectives of geothermal energy investments. For this purpose, all studies in the Web of Science regarding the geothermal energy are taken into consideration. These studies are evaluated with the help of text-mining approach. In this framework, most frequently stated words, two words, and three words are identified. It is concluded that technological development with respect to the geothermal energy is an important issue in this framework. After that, it is also determined that risk is another important factor in this regard. Finally, new implications regarding the geothermal energy are also considered by the researchers. Geothermal energy has a positive contribution to solve many different problems, such as energy dependency, current account deficit problem, and carbon emission. Hence, this study generated the significant issues to improve these investments. While considering the results, it is understood that technological developments related to the geothermal energy projects should be followed effectively. In addition, an effective risk evaluation should be conducted before implementing these projects.