{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Location" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Table of contents**\n", "- Overview\n", "- Setup\n", " - Authentication Token\n", "- Query\n", " - Output Description\n", "- Related Links" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Overview" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Scope 2 emissions are greenhouse gas emissions that can be indirectly controlled by an organization, such as the purchase of electricity.\n", "\n", "Use the Location API to calculate emissions from purchased electricity from an energy grid system." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ensure that Python 3+ is installed on your system.\n", "\n", "\n", "Note: To run this notebook, you must first add your credentials to `'../../../auth/secrets.ini'` in the following format:\n", "\n", "```\n", "[EAPI]\n", "api.api_key = \n", "api.tenant_id = \n", "api.org_id = \n", "\n", "```" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Install the prerequisite Python packages\n", "%pip install pandas configparser IPython requests" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import configparser\n", "import requests\n", "import json\n", "from IPython.display import display as display_summary" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Authentication Token" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Run the following code snippet to generate a Bearer Token by using your api_key configured in secrets.ini." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Authentication Success\n" ] } ], "source": [ "config = configparser.RawConfigParser()\n", "config.read(['../../../auth/secrets.ini','../../../auth/config.ini'])\n", "\n", "EAPI_API_KEY = config.get('EAPI', 'api.api_key')\n", "EAPI_TENANT_ID = config.get('EAPI', 'api.tenant_id')\n", "EAPI_CLIENT_ID = 'ghgemissions-' + EAPI_TENANT_ID\n", "EAPI_ORG_ID = config.get('EAPI', 'api.org_id')\n", "\n", "EAPI_AUTH_CLIENT_ID = 'saascore-' + EAPI_TENANT_ID\n", "EAPI_AUTH_ENDPOINT = config.get('EAPI', 'api.auth_endpoint')\n", "\n", "EAPI_BASE_URL = config.get('EAPI', 'api.base_url')\n", "EAPI_ENDPOINT = f\"{EAPI_BASE_URL}/location\"\n", "\n", "auth_request_headers: dict = {}\n", "auth_request_headers[\"X-IBM-CLIENT-ID\"] = EAPI_AUTH_CLIENT_ID\n", "auth_request_headers[\"X-API-KEY\"] = EAPI_API_KEY\n", "\n", "verify = True\n", "\n", "auth_url = f\"{EAPI_AUTH_ENDPOINT}?orgId={EAPI_ORG_ID}\"\n", " \n", "response = requests.get(url = auth_url,\n", " headers = auth_request_headers,\n", " verify = verify\n", " )\n", "if response.status_code == 200:\n", " jwt_token = response.text\n", " print(\"Authentication Success\")\n", "else: \n", " print(\"Authentication Failed\")\n", " print(response.text)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Query" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The example request payload (below) queries IBM Envizi - Emissions API for 1 megawatt-hour (MWh) in the state of New York, United States of America for 2025-01-01:\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "payload = {\n", " \"activity\": {\n", " \"type\": \"Electricity\",\n", " \"value\": 1,\n", " \"unit\": \"MWh\"\n", " },\n", " \"location\": {\n", " \"country\": \"USA\",\n", " \"stateProvince\": \"New York\"\n", " },\n", " \"time\": {\n", " \"date\": \"2025-01-01\"\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Create the query headers\n", "request_headers: dict = {}\n", "request_headers[\"Content-Type\"] = \"application/json\"\n", "request_headers[\"x-ibm-client-id\"] = EAPI_CLIENT_ID\n", "request_headers[\"Authorization\"] = \"Bearer \" + jwt_token\n", "\n", "# Submit the request\n", "response = requests.post(EAPI_ENDPOINT, \n", " headers = request_headers, \n", " data = json.dumps(payload))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For more information about allowable parameters for the payload, please see [Emissions API Developer Guide]()." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "\n" ] }, { "data": { "text/html": [ "
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transactionIdtotalCO2eCO2CH4N2OindirectCO2eunitdescription
03af233b8-5d46-4320-903c-df596cd34b98222.84404222.127810.355620.3606111.97581kgCO2eThe electricity emissions factor used to calculate this result was obtained from the year 2022 Managed - eGRID & US Climate Leaders factor set for the area United States and the region New York.
\n", "
" ], "text/plain": [ " transactionId totalCO2e CO2 CH4 \\\n", "0 3af233b8-5d46-4320-903c-df596cd34b98 222.84404 222.12781 0.35562 \n", "\n", " N2O indirectCO2e unit \\\n", "0 0.36061 11.97581 kgCO2e \n", "\n", " description \n", "0 The electricity emissions factor used to calculate this result was obtained from the year 2022 Managed - eGRID & US Climate Leaders factor set for the area United States and the region New York. " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "if response.text != \"\":\n", " # Get the response as json\n", " response_json = response.json()\n", " \n", " # Get json and convert to dataframe\n", " json_str = json.dumps(response_json)\n", " dict = json.loads(json_str)\n", " dataframe = pd.json_normalize(dict) \n", " \n", " # display\n", " print(\"\\n\\n\")\n", " pd.set_option('display.max_colwidth', None)\n", " display( dataframe) \n", "else:\n", " print(\"Empty Response\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Output Description" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "transactionId - An Emissions API transaction id.\n", "\n", "totalCO2e - The total emissions as CO2 equivalent (CO2e)\n", "\n", "CO2 - The amount of CO2 (Carbon Dioxide) in the CO2e value.\n", "\n", "CH4 - The amount of CH4 (Methane) in the CO2e value.\n", "\n", "N2O - The amount of N2O (Nitrous Oxide) in the CO2e value.\n", "\n", "HFC - The amount of HFCs (Hydrofluorocarbons) in the CO2e value.\n", "\n", "PFC - The amount of PFCs (Perfluorocarbons) in the CO2e value.\n", "\n", "SF6 - The amount of SF6 (Sulphur Hexafluoride) in the CO2e value.\n", "\n", "NF3 - The amount of NF3 (Nitrogen Trifluoride) in the CO2e value.\n", "\n", "bioCo2 - The amount of bio CO2 in the CO2 value.\n", "\n", "indirectCo2e - The amount of CO2e that is indirect in the CO2e value.\n", "\n", "unit - The unit of measure of the values.\n", "\n", "description - A description of the source factor set of the factor used in the calculation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Related Links" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[Emissions API Developer Guide]()" ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.1" } }, "nbformat": 4, "nbformat_minor": 4 }