{"query_echo":{"q":"","filters":{"analysis_type":["technical integration"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'technical integration' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=technical+integration","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"iisd-003141","url":"https://climateinsightsdirectory.org/document/iisd-003141","title":"The Integration of Climate Data into the SAVi model","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"en","date_published":"2020-09","source_url":"https://www.iisd.org/system/files/2020-09/intregration-climate-data-savi-model.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details how climate indicators from the Copernicus Climate Data Store (CDS) are integrated into the SAVi tool to improve the analysis of infrastructure resilience. It covers a literature review of climate impacts on energy, irrigation, wastewater, buildings, roads, and nature-based infrastructure, providing specific equations to link climate variables to asset performance. The report includes simulation results for Johannesburg, South Africa, demonstrating how climate variables like temperature and precipitation affect load factors, thermal efficiency, and maintenance costs, ultimately impacting the economic viability and societal costs of these assets.","ai_generated":true,"unit":"iisd-003141#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Wind power generation is sensitive to wind speed; in Scotland, wind speed variations between -20 and +20 m/s impact turbine output by ranges from -26.06% to +13.66%.","ai_generated":true,"unit":"iisd-003141#insight-1","date_modified":"2026-10-23"},{"text":"Solar PV efficiency is negatively impacted by temperature; an increase of 1°C can decrease efficiency by up to 2% in some studies, while an increase of 1 unit (W/m2) of irradiance increases output by 5%.","ai_generated":true,"unit":"iisd-003141#insight-2","date_modified":"2026-10-23"},{"text":"Hydropower potential is highly sensitive to precipitation and river discharge, where a 1% change in these variables typically results in a 1% change in power generation.","ai_generated":true,"unit":"iisd-003141#insight-3","date_modified":"2026-10-23"},{"text":"Gas turbine power output decreases as ambient temperature rises; for every 1 Kelvin increase above ISO conditions, a turbine can lose 0.1% in thermal efficiency and 1.47 MW of gross power output.","ai_generated":true,"unit":"iisd-003141#insight-4","date_modified":"2026-10-23"},{"text":"Coal power plant load factors are negatively affected by moisture; a 1% increase in total moisture can reduce the plant load factor by 4%.","ai_generated":true,"unit":"iisd-003141#insight-5","date_modified":"2026-10-23"},{"text":"Nuclear power plant efficiency and output decrease with rising cooling water temperatures; an increase of 1°C can lead to a 0.12% to 0.16% decrease in thermal efficiency and a 0.39% to 0.45% decrease in net power output.","ai_generated":true,"unit":"iisd-003141#insight-6","date_modified":"2026-10-23"},{"text":"Electrical grid capacity and transformer efficiency decline with temperature; network capacity falls by approximately 1% for each 1°C increase.","ai_generated":true,"unit":"iisd-003141#insight-7","date_modified":"2026-10-23"},{"text":"Crop yields for major staples decrease with temperature increases: wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1% per 1°C increase in global mean temperature.","ai_generated":true,"unit":"iisd-003141#insight-8","date_modified":"2026-10-23"},{"text":"In Johannesburg, under the IPSL RCP 8.5 scenario, net irrigation requirements per hectare for maize are projected to increase by 23% by the 2090–2100 decade compared to 1980–1990.","ai_generated":true,"unit":"iisd-003141#insight-9","date_modified":"2026-10-23"},{"text":"Wastewater treatment nutrient removal is temperature-dependent; for nitrogen, a change of -1.5 to +5°C can impact removal efficiency by -6% per 1°C decrease in influent sewage temperature.","ai_generated":true,"unit":"iisd-003141#insight-10","date_modified":"2026-10-23"},{"text":"Rainwater harvesting potential in Johannesburg is significantly higher when using CDS climate data compared to constant seasonal values, with average annual yields of 3,068.6 litres/m2 versus 134.7 litres/m2.","ai_generated":true,"unit":"iisd-003141#insight-11","date_modified":"2026-10-23"},{"text":"Rooftop solar PV generation in Johannesburg is projected to decrease by 5.4% in load factor due to temperature increases, resulting in a cumulative reduction of 90.21 GWh over 80 years for 1 MW of capacity.","ai_generated":true,"unit":"iisd-003141#insight-12","date_modified":"2026-10-23"},{"text":"In Johannesburg, heating degree days (HDD) are forecasted to decline by 82% over 80 years, while cooling degree days (CDD) will increase from zero to 204 days per year.","ai_generated":true,"unit":"iisd-003141#insight-13","date_modified":"2026-10-23"},{"text":"Road maintenance costs increase with precipitation; for unpaved roads, maintenance costs increase by 0.8% for every 1% increase in maximum monthly precipitation.","ai_generated":true,"unit":"iisd-003141#insight-14","date_modified":"2026-10-23"},{"text":"Weather conditions increase road accident probability: a 100 mm increase in monthly rainfall increases probability by 0.2%–0.3%, and a 1°C increase in monthly temperature increases it by 1%–2%.","ai_generated":true,"unit":"iisd-003141#insight-15","date_modified":"2026-10-23"},{"text":"Urban green infrastructure can significantly reduce stormwater runoff; for example, green roofs in Chicago retained over 75% of the volume from a one-inch storm.","ai_generated":true,"unit":"iisd-003141#insight-16","date_modified":"2026-10-23"},{"text":"Vegetation cover reduces urban air temperatures; an average reduction of 1.635°C is observed for a 25% increase in vegetation cover.","ai_generated":true,"unit":"iisd-003141#insight-17","date_modified":"2026-10-23"},{"text":"In Johannesburg, increasing vegetation cover to 75% could potentially mitigate temperature-related labour productivity impacts entirely.","ai_generated":true,"unit":"iisd-003141#insight-18","date_modified":"2026-10-23"}],"climate_tags":["renewable energy","wind power","photovoltaics","hydropower","nuclear power","geothermal energy","electric power transmission","agricultural irrigation","crop yield","wastewater treatment","urban flooding","energy efficient building","rainwater harvesting","urban heat island","carbon sequestration","climate finance"],"geography_discussed":["Scotland","Black Sea","Greece","United States","Brazil","Zambezi River Basin","Dubai","Saudi Arabia","Vietnam","India","Malaysia","France","Iran","Norway","People's Republic of China","Los Angeles","Guangzhou","Netherlands","Spain","Chicago","Milwaukee","Japan","London","Sweden"],"frame_perspective":[],"analysis_type":["literature review","technical integration","simulation","economic assessment"]},{"id":"iisd-003144","url":"https://climateinsightsdirectory.org/document/iisd-003144","title":"Integration of Climate Data in the SAVi Wastewater Model","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"en","date_published":"2020-09","source_url":"https://www.iisd.org/system/files/2020-09/intregration-climate-data-savi-wastewater-model.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details how climate indicators—specifically precipitation, runoff, and temperature—from the Copernicus Climate Data Store (CDS) are integrated into the SAVi Wastewater model. It provides a literature review on how these variables affect wastewater treatment facility (WWTF) capacity and efficiency, such as the impact of heavy rainfall on sewage overflows and the effect of temperature on nutrient removal. The report includes simulation results for Johannesburg, demonstrating that climate-induced sewage overflows and urban runoff increase energy use, energy costs, and the social cost of carbon, while also causing environmental damage through nitrogen leaching.","ai_generated":true,"unit":"iisd-003144#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Precipitation impacts wastewater treatment plants by causing runoff that leads to overflows, which reduces treatment efficiency and increases operational costs; extreme flow can cause a complete shutdown of the facility.","ai_generated":true,"unit":"iisd-003144#insight-1","date_modified":"2026-10-23"},{"text":"Temperature changes affect the efficiency of pollutant removal in wastewater treatment. While higher temperatures can increase the removal efficiency of some pollutants, they can also promote the growth of algae and parasites that reduce overall efficiency and increase treatment time.","ai_generated":true,"unit":"iisd-003144#insight-2","date_modified":"2026-10-23"},{"text":"Increased wastewater viscosity, driven by low precipitation and higher temperatures, leads to accelerated depreciation of infrastructure and higher maintenance costs due to increased sludge settlement in sewers.","ai_generated":true,"unit":"iisd-003144#insight-3","date_modified":"2026-10-23"},{"text":"Simulation results for Johannesburg under the IPSL RCP8.5 scenario indicate that between 2020 and 2080, cumulative energy use for wastewater treatment in the CDS climate impact scenario is projected to be 2.25% higher than the no-impact scenario, totaling an additional 679 MWh.","ai_generated":true,"unit":"iisd-003144#insight-4","date_modified":"2026-10-23"},{"text":"The monetized impact of sewage overflows in the simulation includes an increase in energy costs by 135,803 USD, the social cost of carbon by 14,735 USD, and additional costs of 204,343 USD for nitrogen leaching into the environment.","ai_generated":true,"unit":"iisd-003144#insight-5","date_modified":"2026-10-23"},{"text":"In the urban stormwater runoff simulation, the CDS climate impact scenario shows a 13% reduction in cumulative stormwater loads (5.83 billion liters vs 6.7 billion liters) between 2020 and 2100 compared to the no-impact scenario, but introduces higher peak loads, with a maximum monthly load of 37.8 million liters.","ai_generated":true,"unit":"iisd-003144#insight-6","date_modified":"2026-10-23"},{"text":"Increased stormwater loads in the simulation are projected to raise total energy use by 5.4% compared to the no-impact scenario, equivalent to approximately 1,627 MWh over 80 years.","ai_generated":true,"unit":"iisd-003144#insight-7","date_modified":"2026-10-23"}],"climate_tags":["precipitation"],"geography_discussed":["Johannesburg","People's Republic of China"],"frame_perspective":[],"analysis_type":["simulation","literature review","technical integration"]}]}